Consumer Choice; Variety in the Retail Setting

An EMBS master’s thesis, by R.T.I. van Hees. Submitted May 24, 2012, at the University of León, Spain, to professors I. Trevisan, S. Ganassali, R. Wagner and C. Rodriguez-Santos.

CONSU MER CHOICE Variety in the Retail Setting

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Source cover figure: HSBC (2012). Expat 2011 rating of local stores and

markets. Retrieved April 15, 2012, from http://expatexplorer.hsbc.com/#/countries.

This master’s thesis was written as part of the European Master in Business Studies

(EMBS) program in partial fulfillment of the requirements for the following

academic degrees:

− Università Degli Studi de Trento: “Laurea Magistrale - CLASSE LM77

Lauree Magistrali in Scienze Economico-Aziendali”

− Université de Savoie: “Master en Droit Economie Gestion”

− Universität Kassel: “Master of Arts”

− Universidad de León: “Master Universitario Europeo en Dirección de

Empresas”.

All rights reserved. No part of this publication may be reproduced, stored in a

database or retrieval system, or distributed in any form or by any means, electronic,

mechanical, photocopying, recording or otherwise, without prior written permission

of the author.

Correspondence concerning this paper can be sent by e-mail to Iris van Hees at

[email protected].

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Abstract

Presenting choice wisely is increasingly important in the retail sector because

choice is expanding. Many choices are of little importance and are made in a matter

of seconds when the customer is confronted with the assortment. Therefore, in store

presentation can have great influence on the amount of mental energy people expend

in deciding, whether or not they decide and what product is chosen. In the western

world choice is perceived as desirable and there are various pressures for more

choice. Preference for choice is however not only related strongly to culture, but also

to personality, involvement and context among others. The amount of variety

offered profoundly affects peoples purchasing behavior by fostering indecision

especially when customers are unsure about their preferences. Assortment size also

affects decision confidence and post-purchase satisfaction. Presenting choice can be

most effectively done when products are organized according to the consumer’s

decision tree, thereby forming the customer’s choice set and limiting the amount of

choices consciously made.

This paper presents two empirical studies in addition to the extensive

literature review. The first study explores similarities and differences in Dutch and

American attitudes toward choice in retailers through an application of the tripartite

attitude theory. It shows that Dutch more often than Americans find that there is too

much choice and feel less benefitted by having choice. Furthermore, it provides

support for the assumption that reactions to choice are based on largely the same

perceptions and believes. The second research furthers the cross-cultural comparison

by analyzing assortment evaluations, indecision and choice satisfaction in more

detail. For the American sample many results from previous research were

duplicated. The Dutch sample, however, gives reason to believe Dutch reactions to

choice are fundamentally different and more negative. Further investigations of

Dutch perceptions of and reactions to choice showed that Dutch experience many of

the benefits and drawbacks of choice found by American research. Furthermore, it

provides insight into presentation effects in retailers, stressing the importance of

appropriate assortments and assortment organization.

Keywords: choice, retail, assortment planning, variety growth, consumer

psychology, purchasing decisions, excessive choice, retail marketing, shelf

management

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List of Tables

Table 1: Types of new products. ................................................................... 17 Table 2: Choice exposure styles. ................................................................... 30 Table 3: Distribution for ‘liking’ of the amount of choice in stores. .............. 66 Table 4: The believed benefits of having choice in stores.............................. 68 Table 5: Amount of respondents that did, did not and did not but

indicated reason to complain. ............................................................ 70 Table 6: Benefits associated to choice........................................................... 89 Table 7: Extent to which negative feelings were experienced. ....................... 91 Table 8: Cross-tabulation of liking and given reason .................................... IV

Table 9:Cross-tabulation of whether there was perceived benefit and reason given. ...................................................................................... V

Table 10: Cross-tabulation of whether the respondent complained and given reason or mediator. .................................................................. VI

Table 11: Relationship between attitude components. .................................. VII Table 12: Relationship between attitude components for Dutch

respondents. ................................................................................... VIII Table 13: Relationship between attitude components for American

respondents. ...................................................................................... IX

Table 14: Recalled product type by nationality. ........................................ XVII Table 15: Recalled product type by gender. .............................................. XVII Table 16: Age of the memory by product type. ......................................... XVII Table 17: Age of the memory and decision difficulty for Dutch. .............. XVIII Table 18: Importance to choose right by nationality. ................................ XVIII Table 19: Importance to choose right by product type. ............................. XVIII Table 20: Product knowledge and nationality ............................................ XIX

Table 21: Product Knowledge and Importance. ......................................... XIX

Table 22: Assortment Evaluation and Nationality ........................................ XX

Table 23: Assortment evaluation and satisfaction with choice ...................... XX

Table 24: Assortment evaluation and satisfaction with choice by nationality. ....................................................................................... XX

Table 25: Assortment evaluation and knowledge ....................................... XXI Table 26: Assortment evaluation and product knowledge by nationality. ... XXI Table 27: Assortment evaluation and decision importance. ....................... XXII Table 28: Assortment evaluation and decision importance by nationality. . XXII Table 29: Decision ease and remembered assortment size. ....................... XXIII Table 30: Decision ease and Choice set size for Americans. ................... XXIV

Table 31: Decision importance and decision ease. .................................. XXIV

Table 32: Product knowledge and decision ease. ...................................... XXV

Table 33: Decision ease by nationality. ..................................................... XXV

Table 34: Satisfaction with the made choice and decision ease by nationality. .................................................................................. XXVI

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Table 35: Satisfaction with the made choice and considering purchase deferral by nationality. ................................................................ XXVI

Table 36: Satisfaction with the made choice and considering postponing the decision by nationality.......................................................... XXVII

Table 37: Satisfaction with choice and product knowledge. ................... XXVII Table 38: Satisfaction with choice and choice importance by nationality.XXVIII Table 39: Ability to express identity by acceptance little variety basic

goods. ......................................................................................... XXIX

Table 40: Choice identity and self-expression. ........................................ XXIX

Table 41: Benefits associated to choice by gender. ................................... XXX

Table 42: Assortment evaluation and appropriateness categorization. ..... XXXI Table 43: Assortment evaluation and exceeding variety expectations...... XXXI Table 44: Assortment evaluation and product availability. ..................... XXXII Table 45: Assortment evaluation and special offers. .............................. XXXII Table 46: Assortment evaluation and increased expectations. ............... XXXIII Table 47: Difficulties deciding and self-efficacy. .................................. XXXIII Table 48: Drawbacks to deciding factor loadings by gender. ................. XXXIV

Table 49: Decision difficulty and process satisfaction. .......................... XXXIV

Table 50: Satisfaction made choice and positive surprise. ..................... XXXIV

Table 51: Positive surprise and increased expectations. ......................... XXXV

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List of Figures

Figure 1: Value added as percentage of GDP in 2010 and share of total

businesses enterprises in 2008 in the retail and wholesale sector for selected EU countries. ................................................................... 6

Figure 2: Concentration ratio's in the European retail sector in 2004/2005. .......................................................................................... 7

Figure 3: Countries of operations of five major international retailers. .......... 11 Figure 4: Number of countries with physical and online store presence

for selected fashion retailers in 2010. ................................................ 13 Figure 5: Online retail sales as share of total national sales in 2011. ............. 13 Figure 6: Online purchases and the percentage of households that have

Internet access in Europe and Turkey. ............................................... 14 Figure 7: Per capita sales area (in m2) in 2010. ............................................. 21 Figure 8: Number of products offered by the average grocer per category

in 2004. ............................................................................................. 24 Figure 9: Assortment depth; number of items sold by Aldi by category

by country. ........................................................................................ 25 Figure 10: Relationship between perceived variety and likelihood of

purchase. ........................................................................................... 41 Figure 11: Variety and decisions; relationships identified in the literature

review. .............................................................................................. 54 Figure 12: Pareto chart of reasons for liking/disliking the amount of

choice in stores. ................................................................................ 67 Figure 13: Pareto chart of believed benefits of choice. .................................. 69 Figure 14: Number of stores per 1,000 inhabitants in 2007 for selected

countries .............................................................................................II Figure 15: Share of grocery sales by format in Europe, 2000 vs 2004. .......... III

vi

List of Abbreviations

EU – European Union

GDP – Gross Domestic Product

GfK – Growth for Knowledge

ICT – Information and Communication Technology

p - Probability

POPAI – Point-Of-Purchase Advertising Institute

PPP – Purchasing Power Parity

SD – Standard Deviation

SE – Standard Error

SKU – Stock Keeping Unit

UHT – Ultra High Temperature

UK – the United Kingdom

US/USA – United States/United States of America

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Table of Content

Abstract ii

List of Tables iii

List of Figures v

List of Abbreviations vi

Table of Content vii

Preface x

Introduction 1

1. Research Question 1

2. Preliminary Definitions 2

3. Research Methodology 3

1. Industry Introduction 5

1. Sales, GDP and Industry Structure 5

2. National Industry Developments 8

3. Globalization 10

4. Online Ret@il 12

2. Sources of Variety and the Prevalence of Choice 17

1. Categorizing new products 17

2. Product and Brand Variety 18

3. Global Assortment Sizes 20

4. Store Formats and Assortments 22

5. Assortment Depth 24

3. Consumer Demand for Variety 26

1. Sides to Variety 26

2. Exposing Oneself to Choice 29

3. Maximizers and Satisficers 31

4. Making Purchasing Decisions 32

1. The Purchase Decision 32

2. Involvement, Information Search and Decision Novelty 33

viii

3. In-store Decisions 34

4. In-Store Decisions and Heuristics 36

5. Purchasing from Variety 38

1. Product Choice and Variety 38

2. Chance of Purchase and Variety 39

3. Chance of Purchase, Trade-offs and Preference Uncertainty 41

4. Memory and Time 43

5. Knowledge and Articulated Preferences 45

6. Customization and Personalization 47

6. Variety and Post-Purchase Satisfaction 50

1. Post-Purchase Satisfaction 50

2. Opportunity Costs and Escalation of Expectations 51

3. Regret and Responsibility 52

7. Choice Moderation by Retailers 55

1. The Retailers and Variety 55

2. Presentation Effects 57

3. Other Moderating Policies 59

8. Study 1: Attitude Towards Choice 62

1. Study Design 62

2. Analysis Procedure 62

3. Sampling Procedure and Sample 65

4. Results 65

5. Discussion of Results and Methodology 73

9. Study 2: Choice and Satisfaction 75

1. Study Design 75

2. The Instrument 76

3. Sampling Procedure and Sample 78

4. Analysis Procedure Cross-Cultural Study 78

5. Recalled Choices 79

6. Results Cross-Cultural Comparison 82

7. Discussion on Cross-Cultural Findings 86

8. Analysis Procedure Study of Dutch Respondents 87

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9. Specific Results for Dutch Respondents 88

10. Discussion of Dutch Results 93

11. Discussion of the Methodology 95

Conclusion, Recommendations, Discussion and Future Outlook 97

References 100

Appendix A: Legend figure 6 I

Appendix B: Additional Industry Data II

Appendix C: Study 1; Extra Information IV

Appendix D: Study 2; Questionnaire American Respondents X

Appendix E: Study 2; Questionnaire Dutch Respondents XII

Appendix F: Study 2; Extra Information Cross-Cultural ComparisonXVII

Appendix G: Study 2; Extra Information Analysis Dutch RespondentsXXIX

Personal Affirmation in Lieu of Oath 1

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Preface

The classes on marketing and product innovation during the EMBS-program

made me wonder what free competition and the expansion of product alternatives

mean for the everyday consumer. To some extent consumers and their experiences

seem to have been marginalized by an academic and corporate discourse focused on

profit and sales as the main criteria for market success. The underlying and

widespread assumption is that optimized profits in competitive markets imply needs

being served in the best feasible manner. Thus, the consumers’ reaction to this

competitive approach and expansion of choice is reduced to the product they choose

to spend their money on and the amount of money that is spent. However, though

this reasoning makes sense within economic theory, in practice consumer reactions

are much more complex.

Some of the problematic of the ongoing boom of choice were brought to my

attention by the virtue of TED.com, a nonprofit initiative that I have to thank for

providing much inspiration over the years. From amongst their many contributors

I’d like to make a special note of two speakers, namely Barry Schwartz and Sheena

Iyengar from whom I borrowed some ideas with which I started this research. Most

striking was that though we need choice to be free, not all choice increases freedom,

and the availability of many choices may in fact decrease happiness and overall

well-being.

Fortunately, some retailers pick up on their clients’ confusion, and other

negative reactions to choice such as indecision, and attempt to reduce this by

organizing and limiting their assortments. A theoretical framework is still missing

and much of the existing knowledge has been developed inside big retail chains and

is therefore not available to their smaller competitors. This master thesis is my

contribution to both the development of a framework and increasing awareness of

the costs of choice, including time, confusion and decreased satisfaction, as well as

increasing knowledge on when and how having much choice is beneficial.

Moreover, this thesis investigates to what extent these negative effects are culturally

bound. For this surveys were spread among both Americans and Dutch revealing

some interesting similarities but more strikingly revealing profound differences. This

text should not only be helpful to retailers, but also for marketers, students and the

general public alike.

xi

I would like to thank Melanie van der Lee for her explanation of the

workings of grocery store shelf management, a task she has carried out

professionally for many years for one of the Netherlands largest grocery chains. I

would like to thank everyone who took the time to help me with the pre-testing as

well as the respondents of my questionnaires and the two panel bureaus. Finally, I

would like to thank my parents and friends who took the time to discuss my ideas

with me and my tutors Michael Gierczak and José Luis Vazquez.

León, Spain, May 24th, 2012,

Iris van Hees

Introduction 1

Introduction

1. Research Question

Whichever the form of the increase in variety, the amount of product

alternatives is profoundly interlinked with the free market responding to consumers,

as well as the globalization of demand and supply. Primarily, one may attribute this

increase in variety as a logical, expected and desired effect of the market economy

which promotes innovation and caters to the buyer’s needs. Therefore, it follows that

with this increase in choice people are able to find products that better fit their wants

and needs, will overall be getting more satisfied, and the market will, with time,

reach an optimum. However, there are some indications that this increase in choice

is taking its toll, especially when it comes to the satisfaction with the purchased

goods and services and the general consumer well-being. Therefore, consumer

reactions to the increase of choice are important to investigate, especially now that

the Internet vastly expands the amount of alternative products available to

consumers, and marketers are more and more introducing products for only limited

periods of time.

The main question of this paper is: ‘To what extent is the amount of choice

offered by Western retailers to non-professional customers desirable?’ This

question is sub-divided as follows:

-How pervasive is choice in retailing to non-professional consumers?

-How does the amount of choice affect customers?

-What are industry best-practices when it comes to presenting choice?

-To what extent are the responses to choice similar in the USA and the

Netherlands?

The first sub question, ‘How pervasive is choice in retailing to non-

professional consumers?’ is answered in chapters one and two. Here the history of

retail over the past 200 years is discussed as well as the progression of the amount of

choices offered by retailers. The second sub question, ‘How does the amount of

choice affect customers?’ is discussed theoretically in chapter three to six. The

discussion covers why consumers may or may not want choice, how retail

purchasing decisions are made and how choices and their outcomes are affected by

the amount and sort of alternatives available. Then chapter seven gives an overview

Introduction 2

of known industry best-practices in an attempt to answer the third sub question,

‘What are industry best-practices when it comes to presenting choice?’

Following this theoretical framework, own research is presented as an

answer to the fourth sub-question: ‘To what extent are the responses to choice

similar in the USA and the Netherlands?’ First a look is taken at the general attitude

towards choice, followed by an investigation of assortment satisfaction, satisfaction

with made purchasing decisions and the occurrence of indecision. The final research

focus is an investigation into Dutch perceptions of and reactions to choice, focusing

on associated benefits and drawbacks as well as in-store assortment presentation.

The paper concludes with recommendations for retailers and marketers as well as

suggestions for future research and a general future outlook.

2. Preliminary Definitions

In the context of this thesis retailer refers to a company that is: “primarily

involved in the activity of purchasing products from other organizations with the

intent to resell those goods to private households, generally without transformation,

and rendering services incidental to the sale of merchandise” (Zentes, Morschett,

Schramm-Klein, 2011, p.1). Retailing covers all consumer products such as food,

apparel, consumer goods, financial services, leisure, etc. There are many different

retail formats, which can be split in store and non-store (IMAP, 2010). Here the

focus is on store formats and to lesser extent online stores. Non-store retailers such

as catalogues, door-to-door, telephone and direct response television are excluded.

The recommendations of this paper are equally applicable to companies that sell

their own products directly to consumers, for example through factory outlets, as

long as their target group and store formats are similar.

A non-professional customer is whoever has the possibility to choose from

the product assortment of the store, for personal consumption, regardless of whether

or not a purchase is made.

Choosing or making a decision in the context of this thesis, will be defined

as a response to a situation in which alternative courses of action are under

consideration and

“the decision maker can form expectations concerning future events

and outcomes following from each course of action, expectations that can be

Introduction 3

described in terms of degrees of belief or probabilities. (…). The

consequences associated with the possible outcomes can be assessed on an

evaluative continuum determined by current goals and personal values.”

(Hastie & Dawes, 2009, p.24).

Finally, product alternatives are those products that by the customer are

seen as substitutes and therefore fall in the same product category. More alternatives

implying more choice and fewer alternatives providing less choice. There are

various ways to measure assortment variety within a product category. To measure

assortment depth, one can look at the number of Stock Keeping Units (SKUs) it

contains. Alternatively, to measure variety one can look at the attribute variety (see

van Herpen & Pieters, 2002, for a detailed mathematical description) also referred to

as assortment entropy (Fasolo, Hertwig, Huber & Ludwig, 2009). Attribute variety

calculations primarily rely on the amount of aspects on which products can vary and

the amount of different attributes they can take. For example, when three shirts are

offered there is more variety when they do not only differ in color but also in size.

These shirts additionally present more variety if instead of there being two colors

there are three. Here the perception of customers is crucial to determine which

product aspects do and do not create variety, for example if the stich size in these

shirts differ by .1mm very few customers, not to say none, will notice. As products

become less and less objectively different from each other some consumers may

cease to count them as possible choices. Based on this reasoning, groups of two

products can be placed on a continuum of the amount of choice they present.

Products that differ little on few attributes present little choice and products that

differ widely on many attributes present much choice. Research suggests that

attribute based variety calculations correspond better to perceived variety than SKU

based measures, however these calculations are more costly and rely more heavily

on the researcher’s judgment.

3. Research Methodology

This thesis is based on three distinct approaches to research. The first half is

based on literature research. This is followed by chapter seven which in part is based

on literature research, in part on an in depth interview and for the remainder on the

Introduction 4

stories of various professionals in the retail field. The last part of this thesis is based

on the qualitative and quantitative analysis of two surveys.

The literature research is primarily based on publications in research journals

and by specialized marketing research companies. If multiple researches were found

that covered the topic preference was given to the most recent publication. When

looking at global data special emphasis was placed on both Europe, and specifically

the Netherlands, and the USA. Next to these sources also some books from the

university library, newspaper articles and conference talks were used. For some of

the data presented primarily in the earlier chapters the Eurostat and UNData

databases were used.

Next to the literature research chapter seven on the presentation of choice by

retailers is additionally based on an in depth interview with a manager in charge off

category presentation of a large Dutch grocery retailer who has worked together

closely with the research department there. The interview took place December 28,

2011. The retailer wants to remain unnamed. For this chapter also the experiences of

some other retail professionals were used, taken mainly from thematic forums.

The final part of this thesis resents the results of two surveys which were

developed using the presented literature and tackle various questions. The combined

sample size is over 570, including both Dutch and Americans, recruited both through

the author’s personal network as well as online panels. All quantitative analyses

were carried out using either Microsoft Excel 2010 or SPSS 17.0. For more detailed

information regarding the methodology, please see the studies’ respective

methodology sections.

The recommendations and conclusions chapter that concludes this thesis is

based on all research presented, and as said before aims to provide practitioners with

a more profound understanding of the problematic as well as concrete tools to

counteract possible downsides of choice.

Industry Introduction 5

1. Industry Introduction

Before discussing how consumers are affected by the increasing amount of

choice in Western countries, it is important to have established that consumers are

faced with increasing amounts of product alternatives, and before that we need to

have an image of the retail industry and its development. Therefore, this chapter

provides an introduction to the global retail industry, with a special focus on the

USA and Europe.

As covered in the general introduction, the retail industry is comprised of

those individuals and companies that sell finished products to the consumers, and the

sector can be subdivided in food, soft (clothing) and hard goods (IMAP, 2010).

Although in some cases the manufacturer is also the retailer, typically product

distribution is carried out by specialized companies. Products are either sold directly

from the manufacturer to the retailer, or through wholesalers. Often specialized

services such as storage, transportation and ICT are outsourced. The industry is labor

intensive and has a moderate to use of capital (Michigan State University, 2012).

Retail competition is mainly price based, but also location, assortment, store lay-out

and reputation matter.

1. Sales, GDP and Industry Structure

In 2009 global retail sales were 13.9 trillion dollars, compared to 7 trillion in

2000 (IMAP, 2010; Deloitte, 2002). However, total retail sales are closely related to

Gross Domestic Product (GDP), because personal incomes minus saving rate and

plus lending, are spent in retail, insurance, services, rent, water, electricity, gas and

investments. In Europe retail spending was between 27 to 40% of private spending

in 2009, in Russia as much as 60%, and in the US approximately 50 to 55% (GfK,

GeoMarketing, 2010; the Office of Consumer Affairs, 2011). The amount of this

which was spent on food differs between countries, and to some extent reflects

welfare. According to Lasserre (2007) in Western European countries spending on

food was between 30 and 40% of total retail spending in 2003, in the US this share

was lower (27%) and in Asian countries this was higher (46% in Japan and 59% in

China).


Due to the close relationship between retail sales and GDP the added value

of the industry as a percentage of GDP is a better measure of its size. The value

added by the retail industry (including wholesale, restaurants and hotels is on

average 15.7% of GDP (own calculations based on 2010 data of 207 countries

retrieved from UNData). The added value of wholesale, retail, restaurants and hotels

over GDP has shown a constant drop since the 1970’s, being 16.2% in 1970, 16.1%

in 1980, 15.8% in 1990, and 15.7% in 2000 (based on data from 183, 183, 214 and

209 countries respectively). In 2010, the lowest contributions of retail to GDP was in

oil producing countries, such as Kuwait, Saudi Arabia and Qatar with 4 to 5%, and

the highest in islands and city states such as Monaco and islands such as Barbados

with 35 to 39%.

Figure 1: Value added as percentage of GDP in 2010 and share of total businesses enterprises in 2008 in the retail and wholesale sector for selected EU countries.

Source: Calculated based on Eurostat and United Nations data (UNData).

On average 14.5% of European GDP is added value from the wholesale and

retail industry. This is 1.2% lower than the world average. The relative GDP

importance of the wholesale and retail sectors in various European countries, as

visualized in figure 1, is spread between 8.8% in Norway and 18.6% in Portugal.

Also the amount of enterprises active in the retail or wholesale industry relative to

the total amount of enterprises differed widely between the countries. In some, such

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as Slovakia, Germany and Finland there were relatively few, while in Bulgaria and

Romania there were relatively many. On average 22.4% of European enterprises are

retailers or wholesalers.

Comparing the GDP contribution to the amount of companies in the sector

shows that especially in Bulgaria and Romania retail firms on average contribute

relatively little, a finding supported by Wrigley and Lowe (2010) who analyzed

concentration of the European retail markets (see figure 2). Data from Nielsen

(2010a) shows 5-firm concentration ratios of 97% in Australia, 95% in New

Zeeland, 76% in Hong Kong, 57% in Taiwan, 32% in Korea and 9% in China.

Globally the top 250 retailers had a market share of slightly more than 27% in 2009

(Deloitte, 2009), showing that few decision makers have an influence over the daily

shopping experience and consumption habits of a large part of the global population,

though their reach differs greatly from country to country.

Figure 2: Concentration ratio's in the European retail sector in 2004/2005.

Source: Wrigly and Lowe (2010).

In the retail industry there increasingly is a divide between very small and

very large companies, a trend that will be discussed in more detail later this chapter.

While, as said before, the largest companies have large market shares the majority of

registered retailers is very small. Data from Haskel, Jarmin, Motohashi and Sadun

(2007) shows that the majority of enterprises in the retail sector had only one

establishment in 2002 (95% of firms in Japan and the US and 94% of firms in the

UK). The size of companies with more than one establishment varies more widely


cross countries. In Japan firms with more than one establishment on average have 7,

in the UK 8 and in the US 13. This indicates that the US retailers are much more

consolidated than their Japanese and English counterparts. This difference in chain

size and concentration can largely be explained through recent sector developments

that have also driven the globalization of the sector, and will be elaborated upon

shortly.

2. National Industry Developments

Over the last two centuries the manner in which people purchase their food,

beverages and other supplies in the Western world has changed drastically (see

Wrigley & Lowe, 2002 for an extensive discussion of the changing retail structures).

Previously almost always separate retailers, such as vegetable stores, butchers,

bakers, milkmen and grocers, merged into new store formats such as department

stores, super- and hypermarkets under the influence of growing urban middle

classes, rising ownership of cars, fridges and freezers and mass production

(Mooijman, 2004; Wraigley & Lowe, 2002; Seth & Randall, 2001; Tat Keh & Park,

1997).

For this format change the invention of the ‘self-service’ supermarket in the

1937 was crucial (Wrigley & Lowe, 2002). Self-service is slowly spreading from

Western markets such as the US, where approximately 85% of sales are self-service,

to Asia (53%) and countries such as India (6%; Nielsen, 2010a). Furthermore, other

aspects of modern retailing have emerged after 1900, such as pre-packaged foods,

window displays, advertising, and clear, fixed pricing (Alexander & Akehurst,

1998). Also the automation of payments, both through the introduction of barcodes

as well as checks and electronic payment methods, and the automation of stock

keeping and supply chain management have allowed for an increase in labor

productivity and the creation of economies of scale.

This increase in store size is also known as the retail life cycle. The retail life

cycle relates store type to maturity of the economy, and to maturity of the retail

sector in particular (Zentes, Morschett & Schramm-Klein, 2011). As time progresses

the store formats become larger and larger offering more and more alternatives, both

in depth and breadth, two assortment aspects that are explained in the next chapter.

The point where stores become smaller again seems to not have been reached yet.


The increase in store size was paralleled by a dramatic decrease in the

amount of grocers per citizen from the start of the 1900 to now, which is logical as

larger stores need a larger customer base to be sustainable. Data from Haskel,

Jarmin, Motohashi and Sadun (2007) shows that in 1997 there were approximately

11 stores per 1000 inhabitants in Japan, 5 stores per 1000 inhabitants in the UK and

4 stores per 1000 inhabitants in the US. Comparing this to their data of 2002, and

data from Euromonitor (2009) of 2007 shows a negative trend (see Appendix A for

statistics for 2007 for a wide selection of countries). This trend is undoubtedly

influenced by the rise of modern store formats such as that of Walmart who’s stores

are only viable with a minimum customer base of 150,000 (Lasserre, 2007).

Data from the Netherlands shows that this is not just a recent trend. Where at

the start of the nineteenth century there was one grocer for each 200 people in 2001

there was on average 1 grocer per 850 people, and by 2005 1 for each 1,000 (Betje

Boerhave, 2011). Although many of the smallest villages have found local stores

disappearing, and distances to stores increasing this decrease in stores per

inhabitants did not lead to fewer stores being available to most people. Because

towns and cities grew and the range that consumers could easily travel increased as

well. People were often faced with both more and larger stores, especially in cities

serving as regional retail centers (Mooijman, 2004). Thus, as the stores became

bigger, most consumers found that the amount of stores at which they could buy a

product increased.

The growth in store size was combined with the rise of chain stores.

Modernized larger retailers gained a competitive advantage over less modernized

smaller firms, and mainly in the 1980’s and 1990’s independent grocers started

disappearing while chains gained market share (Wrigly and Lowe, 2010). In the

Netherlands which in 1990 still had over 60,000 independent grocers in 2010 only

around 20,000 were left (Deloitte, 2011). And as 35.3% of independent grocers with

a turn-over below 75,000 euros per week indicated in July that year to expect to go

out of business within the next five years this trend is likely to continue. At the same

time large chains report no such fears and the largest three holdings (each owning

multiple retail firms) now have an 85.7% market share. Also the three main

discounters do well, with a combined market share of 19%.

Concentration led to a power shift from manufacturers to distributor chains

(Wrigly and Lowe, 2010). In the same 1980’s to 1990’s period the ICT revolution


allowed for more buyer-driven supply chains and retailers introduced lean methods

of supply chain management. These developments allowed retailers, such as Tesco,

to reduce stock days from 45 in 1978 to around 15 from the 1990’s onward.

3. Globalization

Retail globalization has a long history; the first ‘modern’ retailers to

internationalize were luxury, specialty and department stores, which between 1880

and 1945 opened stores in cosmopolitan cities (Alexander, 1997). Furthermore,

between 1960 and 1974 many leading Western European retailers started to look to

other countries for growth and invested both in neighboring countries as well as the

USA. In this period Carrefour expanded to Spain, and Ahold to the USA. Then, after

a period of downturn and economic shocks, not only did the Western European

retailers restart international investments between 1983 and 1989, but also the

Japanese started investing in both markets.

Real retail globalization started in the 1990’s, with those retailers that had

concentrated, automated and introduced lean systems (consisting mainly of Western

European and American firms) exporting their expertise to countries in which

retailers had not yet done so (Wrigly & Lowe, 2010; Alexander, 1997). They thereby

mainly focused on countries in their own region as a consequence of the

development of regional trade blocks such as the NAFTA, the European Single

Market and the opening up of Eastern European and Asian countries. For example,

the number of retail establishments in Eastern Europe owned by Western European

firms increased from 28 in 1991, to 1,800 in 2002 (Igan & Suzuki, 2011).

Figure 3, shows how some leading retailers have expanded internationally

over the last decades. As their success relies mainly on their competitive advantages

outlined before, this globalization has put a firm stamp on the retail industry, by

concentrating retailers and modernizing the business models to include ICT and new

forms of supply chain management. Moreover, internationalization has enlarged and

homogenized store formats, presentation, management and product selections. This

effect is especially strong in those countries that do not have ‘modernized’ retail

sector. Of course, this process of change takes time, and thus the largest

Westernization and preference for larger store formats can be observed in countries


such as Poland, the Czech Republic, Hungary and Slovakia, and to a lesser extent in

countries such as Bulgaria, Romania, Ukraine and Russia (Igan & Suzuki, 2011).

Figure 3: Countries of operations of five major international retailers.

Source: IGD (2009).

The top 250 largest global retailers are still actively internationalizing,

though as shown in figure 3 Ahold has reduced the amount of countries drastically.

The international share of sales of the largest retailers has steadily increased from

near zero in the early 1990’s, to 22.2% in 2009 (Deloitte, 2011). However, the

industry remains less globalized than for example consumer products, hospitality,

telecommunications and entertainment (Deloitte, 2009).

Overall, American retailers, though leading in sales revenue, are less

globalized then their European counterparts. In 1999 four of the USA’s ten largest

retailers only operated in the domestic market, and the other six had foreign sales

ranging between 0.5 and 18.4% (Ashfaq, n.d.). The average was 11.1% of foreign

sales for those of six top 10 US retailers that were internationally active. A number

that, when taking the top 10 US retailers regardless of their foreign activity, drops to

7.6% of foreign sales over total sales. In 2011 only two of the top 10 American

retailers did not have foreign sales (Schulz, 2011). The average part of foreign sales

was 16.7% for the whole top 10, and 19.6% when only taking into account the 8

internationally active ones. This increase was for a large part due to the increase in

international activities of Walmart, the largest retailer in the world, which increased

foreign sales from 13.9% to 27.1% by 2011.


The top European retailers in 1999 had a larger share of international sales,

for example the French Carrefour had 37.7% foreign sales, ITM Enterprises SA.

36%, the German MetroAG 40% and the Dutch company Ahold 76.4% (Ashfaq,

n.d.). Also in 2009 European retailers where more globalized than their American

counterparts with more than one-third of sales revenue came from foreign operations

(Deloitte, 2011). This difference likely originates from the fact that European

companies have smaller home markets and can easily internationalize due to the

European Single Market.

4. Online Ret@il

The latest big development in the retail industry has been the rise of online

selling. During the dot-com bubble in the late 1990’s many solely-online retailers

appeared (Wrigley & Lowe, 2010). However, these online retailers did not initially

cause the market disruption that was expected by many. Instead, e-commerce

became dominated by the online channels of traditional retailers, referred to now as

the ‘bricks and clicks’ model (see figure 4 for some examples from the fashion retail

sector). Also many online stores made alliances with mortar and brick stores as they

found that having a physical store boosts their online sales.

Though not growing as fast as originally expected, online retailing has

obtained a large market share. By 2009 global online sales were 348.6 billion US

Dollars, 2.5% of global retail sales (IMAP, 2010). Of these 22.6% were electronics,

other often sold items include books, fashion, airline tickets and software. The

online market is however not limited to these. For example in the UK online grocery

shopping is rather developed with 19% of adults having used the service in 2009.

The largest e-commerce market is the US with 37.2% of online sales. In the

US approximately 7% of sales revenue was earned through online channels. Second

largest are UK e-commerce sales, constituting ⅓d of total e-commerce sales in

Europe (Alisson, 2011). As can be seen in figure 5 the UK is also the country with

the highest relative share of online sales, followed by Germany and most of

Northern Europe.


Figure 4: Number of countries with physical and online store presence for selected fashion retailers in 2010.

Source: Cushman and Wakefield (2011).

Figure 5: Online retail sales as share of total national sales in 2011.

Source: Redrawn from the Center for Retail Research (n.d.)

Not only has e-commerce grown rapidly over the last two decades, it also has

a large, 16.1%, predicted growth rate for 2012 (IMAP, 2010). Forrester (2012)

predicts sales growth rates of 11 to 12% in mature e-commerce countries such as

1,3%

3,1% 3,5%

5,1%

6,9% 7,3%8,2% 8,0%

8,7% 9,0%

12,0%

0%

2%

4%

6%

8%

10%

12%

14%

Number of countries with physical store

Num

ber

of c

ount

ries

with

onl

ine

deli

very


Japan, South Korea and Australia, a 25% growth in China and 57% in India between

2011 and 2016.

In 2008 an overwhelming majority of Internet users in South Korea (99%),

UK (97%), Germany (97%), Japan (97%) and the US (94%) had experience with

online retail (Achille, 2008). Within Europe, especially countries in the west and

north, such as the Netherlands, the UK, and Sweden are predicted to have large

shares, approximately 80%, of their population, including those without Internet

access, shop online by 2015 (Alison, 2011). In southern European countries, such as

Italy, Spain and Greece, this percentage will be substantially lower, around 50%.

Logically, there is a strong relationship between Internet access and experience with

online retail, which is demonstrated in figure 6.

Figure 6: Online purchases and the percentage of households that have Internet access in Europe and Turkey.

Note: see Appendix A for a legend to the country abbreviations.

Source: Cushman and Wakefield (2011).

When comparing Europe as a whole to Internet shopping in other continents,

Nielsen (2010b) found that Internet shopping is more or less equally popular in all

countries. Approximately 84% of connected users have some experience with online

% of households with Internet access

% o

f ho

useh

olds

mak

ing

an o

nlin

e

Purc

hase

in th

e pa

st 1

2 m

onth

s


retailers. The exception to this is the Middle East, Africa and the Pakistan where

relatively many (50%) Internet users have not yet bought items online.

For consumers, retailers and manufacturers alike the rise of online retail has

made decisions more complex. For retailers and manufacturers multi-channeling has

become increasingly important strategically, as a balance needs to be found between

the offer in physical stores and that in online channels (IBM, 2002). In 2008 61%

researched products online but purchased it in a store, and 56% researched products

in the store and bought it online (Gaffney, 2009).

With the rise of online retailing it has become impossible for consumers to

inform themselves about all options available to them (IMAP, 2010). The

assortments of online stores are often more category specific and thus relatively deep

and lesser known brands are more dominant. When a consumer decides to use the

Internet as shopping channel almost instantly many more stores come available to

him or her. In 2010 close to one-third of European online shoppers made purchases

online outside of their home country. Similarly, in the US, over 25% purchased

items from retailers based outside of the US thorough online channels. This share

was one-third Among US consumers aged 18–24. However, language barriers

persist and delivery is sometimes geographically limited.

Consumers that do not purchase online are often influenced by information

on the Internet as they read customer reviews and look up customer ratings. In the

first quarter of 2010 in Europe 19% of those with Internet access use these sources

of information at least once a month and 46% of Internet users feel these ratings help

them reach decisions (Western Europe Technographics Survey Q1 2010 as cited by

IMAP, 2010). Reviews were consulted most frequently for consumer electronics,

cars and software (Nielsen, 2010b). During the early stages of the Internet

consumers started generating content on rating and review sites and feedback portals

have been created. These were later followed by discussion forums, consumer blogs,

Micro-community sites, audio and video blogs and what have become known as

‘social media’ such as Facebook and Twitter. The latest development in this area is

the increased availability of these sources of information within the traditional

retailers as mobile phone Internet connections continue improving and special apps

are designed.

In conclusion, the retail industry is of great economic importance in almost

all countries, and comprises many companies in each country. Though the majority


of companies in the industry are small there are also many large players that have

gained dominance over their supply chains. Over the past two centuries the industry

has seen many changes, such as the rise of self-service, the introduction of ICT

systems, the concentration and globalization of its companies and the rise of online

retailing. The globalization of retailers has had as main drivers the retailers need for

growth opportunities and the export of best practices, and the latter has had a great

influence on countries with less developed internal retail markets, such as Eastern

Europe.

From the consumer’s perspective there has been an increase in store size, and

the effects of urbanization and more widespread personal means of transportation

have been that more stores have become available to most. This is especially true

with the rise of e-retailing, which provides everyone with an Internet connection

access to more retailers than are present in their village or region. Keeping this first

image of the retail industry and its development in mind the following chapter will

discuss what changes have increased product variety and how much choice

consumers are faced with. The latter will be done through an examination of store

sizes, formats and assortments sizes.

Sources of Variety and the Prevalence of Choice 17

2. Sources of Variety and the Prevalence of Choice

1. Categorizing new products

The previous chapter has described the changes in the retail industry,

however also the products that are sold have fundamentally changed over the last

century. All increase in variety has originated from the introduction of ‘new’

products. According to Tat Keh and Park (1997) new products can be categorized as

shown in table 1. Based on this framework, for the purpose of this paper three

sources of product variety are discussed in more depth, namely supplier variety,

product variety and branding.

Source: Tat Keh & Park (1997).

Firstly, product origin variety has expanded for products due to

improvements in transportation and increasing international trade. To illustrate this

Table 1: Types of new products.


consider that in 1989 the US imported many goods, such as agricultural products,

from an average of 12 different supplying countries (Mostashari, 2010). In 2007

these same products were imported from an average of 16 different countries. This is

a measure for product variety as instead of offering only French red wine, also

Brazilian, Spanish and South-African red wine are now available. Similar increase in

variety was demonstrated by Broda and Weinstein (2004), who found that while in

1972 products were imported into the US from an average of 31.4 different

suppliers, by 1997 this had increased to 42.7 suppliers. A trend they also found for

European countries as well as Hong Kong, Mexico, the former Soviet Union,

Singapore, Taiwan and Brazil. Data on Europe shows that the same trend continued

during the 1995 to 2007 period as well (Jubiläumsfonds der Österreichischen

Nationalbank, 2009, as cited in Foster, Poeschl, & Stehrer, 2008).

A striking feature of this trend is that the goods that importers source from

the fewest countries (petroleum and other fuel oils, coal, and wheat) are all generic

goods (Broda Weinstein, 2004). Similarly goods that are sourced from many

countries (e.g., medicines, specialized industrial machinery, and motor vehicle parts)

are likely to be quite differentiated when it comes to producing countries. This is

possibly due to their lesser relationship to natural resources and increasing

importance of human capital and intellectual property rights.

This trend of increasing supplier variety, paradoxically, was probably

possible only thanks to suppliers increasing their production levels through

consolidation and economies of scale (Philpott, 2007; Howard, 2006). Thus, while to

the consumer more supplier variety became available, increasingly large and few

globalized producers were supplying. The same goes for the retailers. Due to

urbanization and increased consumer mobility, consumers are able to go to more

different stores. However, the same chains are present in many towns, and more

recently have an increasingly global presence, reducing the total variety of retailers

(Wrigley & Lowe, 2002). Most recently, Internet retailing has made many more

stores and products available to consumers all around the world.

2. Product and Brand Variety

Secondly, over the past years variety in (available) products has expanded.

Broadly, these products can be split into three general groups: those that are


modified, those that are newly available and those that are newly invented. Milk is a

product of which the diversity has increased over the past 100 years through product

modification, as it developed from a product that was sold from door-to-door to a

grocery store item. Not only can one now buy (cow) ‘milk’, but one chooses

between whole, semi skimmed, skimmed, a specific % of fat, organic, flavored,

pasteurized, sterilized, ultra high temperature (UHT), evaporated, condensed,

filtered, dried, homogenized and, if lucky, the original untreated (or ‘raw’) milk.

Furthermore, the product has also been modified by changing the containers. One

can buy milk in differently sized and shaped containers, containers that can be made

of a variety of materials, such as carton, plastic and glass, to be opened in a variety

of manners. Product innovation may well go beyond functional satiation and move

products from being necessity to luxury goods (Baudisch, 2006).

Other sources of increasing product variety are new inventions, creating not

only variety in existing product categories, but at times add product categories as

well. All consumer electronics, including light bulbs and telephones have been

developed over the last 200 years (Acton, 1994; Boyer, 2001). Also many

consumables are relatively new such as energy drinks as well as many cleaning and

personal hygienic products (Rouse, 2010; Holmes, 2001; Romanowski, 1998). New

introductions are often produced for little more than a year, creating an ever

changing stream of new products (Swartz, 2004).

Finally, there are newly available products. For example previously localized

products have spread across the globe. Food and other perishable products are a

good example as they could spread only after the revolution in freight. Since then

the markets have been flooded with foreign foods such as bananas and rice.

Furthermore, this combined with evolving production methods has made it possible

for various seasonal fruits and vegetables, such as grapes, strawberries, sweet

peppers and tomatoes to be in ready supply all throughout the year. Especially

globalized retailers benefit from this as they can use their local procurement

networks to purchase local specialties cheaply.

Branding has been another source of variety. Brands can introduce

differences that were not perceived before. Often this is achieved by associating the

brand with characteristics that objectively have little or no relationship to the

product. How brands introduce the perception of variety is most easily shown when

looking at how products from one manufacturer are rebranded and sold as


alternatives, such as for example the Albert Heijn and Etos1 private brand shampoo.

Brands can also exaggerate the existing differences, as happens for example with

flour, sugar or milk. At other times brands can mask variety, as products from

various producers or products that are adapted to local tastes are sold under the same

name. A good example of this is coca cola which does not quite taste the same

everywhere.

3. Global Assortment Sizes

The various mechanisms in which new products become available together

resulted in 5,694 new grocery store items and 10,558 new varieties in 1988 (Borin,

Farris & Freeland, 1994). In 1998 20,000 grocery store items were released of which

11,000 food products (Nestle, 2002; Garg, Jones & Sheedy, 1999). Of these

introductions 1,200 (6%) were new products or line as well as brand extensions, the

rest products had existed before but had yet not been locally available.

With the introduction of 20,000 new products a year stores have almost

limitless possibilities for assortment growth (as most stores have assortments of less

than 4,000 items). And to accommodate these new products retailers have grown

assortments over the past decades. To get an impression of how much choice has

expanded for the average consumer we consider the assortment size of a grocer.

According to Garg, Jones and Sheedy (1999) and Nestle (2002) while the average

US grocery store carried an average of 9,000 items in 1974, in 1980 this had risen to

15,000 and by 1997 the average store sold as many as 30,000 items. According to

firstresearch.com (2005) the average US grocery store carried 40,000 different

items, in 2008 the average number of items had risen to almost 47,000 (Minesota

Grocers Association, 2011). Thus assortment sizes more than trebled over the course

of the past three decades.

Not in all countries have such large levels of assortment been reached

(Nielsen, 2010c). In fact, grocery stores in the US on average have the largest

assortments. In China, Brazil, Mexico and Argentina the average store carries only a

little over one third of the items in their US counterparts (approximately 11,000),

and European countries such as France and the UK are in the middle (with stores on

average carrying 15,000 and 20,000 SKUs respectively).

1 Both brands are owned by Ahold


This does not mean that all stores have such large assortments. When looking

at retailers in the USA Bishop (2010) found that half of them had between 2,000 and

3,500 items in their assortment in 2009. 20% had less than 2,000 items and only

23% of the stores had more than 4,001 items. Unfortunately, the amount of countries

for which data on the average amount of SKUs in stores is available is very limited.

Therefore, to quantify the amount of choice offered to people in various countries

some researchers have used sales area as a proxy for the size of the assortments, as

the more products one sells the more space is needed (Hunneman, 2011; Arnold,

Ruth & Tigert, 1981). Sales area per capita is however no more than a proxy as

presentation method and the size of items displayed impacts the sales area per capita

greatly.

Figure 7: Per capita sales area (in m2) in 2010.

Source: adapted from Jahn & Müller (2011).

The US has the world’s largest sales area per capita, with an average of 3.86

m2 of retail space per inhabitant in 2008 (Hill, 2009). India, on the other hand, with

0.19 m2 per capita, may well have the lowest sales area per capita, while

simultaneously many Indians work in retail (Khanna, 2008). Data for Europe can be

found in figure 7, where ‘Northern EU’ includes Norway, Sweden, Finland and

Denmark, and ‘Eastern EU’ Slovenia, Czech Republic, Croatia, Estonia, Poland,

Slovakia, Hungary, Lithuania and Latvia. Austria and the Netherlands have

relatively many square meters per capita, while Russia, Turkey, Bulgaria and

Romania have relatively few.

0

0,2

0,4

0,6

0,8

1

1,2

1,4

1,6

1,8


Comparing this data on the retail area per capita in 2010 as reported by Jahn

and Müller (2011) to the purchasing power per capita in thousands for 2010 as

reported by the International Monetary Fund (2011), we find that the two are

moderately correlated (r(32) = .55, p < .001). People that can spend more also tend

to have more store space, and thus most likely more choice. Furthermore, both retail

sales area and purchasing power have increased over the last two decades, reflecting

the growth in the amount of available product alternatives.

Eurostat provides more insight in the sales area by providing data on the total

sales area per store size category for 2007. This data shows that within Europe small

stores are especially frequent in Portugal, Austria, France, Spain and Greece, with

70-90% of all sales area in stores less than 120 m2 and 90-95% under 399 m2 (own

calculations). In Denmark, Finland, Norway, Germany and the Netherlands stores

with a size up to 399 m2 own between 70-90% of all sales area and also larger

formats are frequent. The UK has most large format sales area, with under 55% of

sales area in stores smaller than 399 m2, and 16% in stores of more than 10,000 m2.

In Eastern Europe, Bulgaria, Czech Republic, Latvia, Lithuania, Hungary, Romania,

Slovakia and Estonia, there is a dual preference with 45% of total sales area

belonging to stores less than 120 m2 and 46% in stores between 1,000 and 2,500 m2.

This situation is much different from for example that of India, where 96% of its 12

million small retailers are smaller than 47 m2 (Khanna, 2008).

4. Store Formats and Assortments

Assortment size can be split in breadth, the amount of categories, and depth,

the amount of different items per category (Zentes, Mirschett &Schramm-Klein,

2011). Stores with deep assortments are called specialty stores, while stores with

broad assortments are diversified. Stores such as book stores, audio visual stores, pet

stores, vegetable stores, butchers, bike stores, home improvement stores and clothing

stores are specialty stores, while hypermarkets and department stores fall in the

diversified category. This split between specialty and diversified stores should be

treated as a continuum. Globally category mitigation is an increasing trend, with

retailers’ positioning themselves as specialist in a few categories, while also having

a couple of other shallow categories to their assortment. Furthermore, for example

department stores have both deep and broad assortments, while a small news stand


or a convenience store has relatively little breadth and little depth. In 2009 in Europe

79% of retail companies using store formats were specialized (own calculations

based on Eurostat data). This percentage was higher for continental Western Europe

(between 84 and 94%) and much lower for Eastern Europe, where on average only

55% was specialized.

Assortment breadth and size together determine store format (detailed

explanations of each store format can be found in Zentes, Mirschett & Schramm-

Klein, 2011). When looking at the US and Western Europe, department stores have

by large the broadest assortments, namely around 100,000 often subdivided in five

or more broad product categories. The second largest assortments are found in

hypermarkets which carry between 50 and 80,000 items (Levy & Weitz, 2009). Off-

price and ‘do it yourself’ stores on average carry 50,000 items, and home

improvement stores and category specialists carry between 20 to 40,000 items.

Discount stores carry 30,000 items, and drug stores 10 to 20,000. Conventional

supermarkets have around 10,000-15,000 items, and specialty stores which offer the

most service have on average 5,000 items. Hard discounters are the smallest with on

average 1,000 SKUs. Off-price and drug stores have the least space per item, while

home improvement stores have the most.

For grocery sales Lassere (2007) found that while in the USA hypermarkets

are more than four times as popular as supermarkets and convenience stores and

almost twice as popular as discounters. This situation is much different in other

countries. Research by Igan and Suzuki (2011) shows that in most European

countries three grocery store formats dominate, namely hypermarkets, supermarkets

and discounters (see Appendix B, figure 15). These formats widely differ on their

assortment sizes and in 2004 the most popular were supermarkets with an average

market share of 40%, and least popular discounters with a market share below 10%

in many markets. Hypermarkets were popular in countries such as France, Germany

and the Czech Republic. Discounters were mainly popular in Germany and the

countries around it, such as Austria, Hungary, Belgium and Denmark. Also

convenience stores are popular in Germany.


5. Assortment Depth

However, all this tells us relatively little about how many product

alternatives a customer is faced with when making a purchase. To answer this

question we turn to assortment depth. Fasolo, Hertwig, Huber and Ludwig (2009)

examined differences in assortment sizes between one large and one small

supermarket in Germany. For the twelve identified common categories they found

that the large grocer always offered more choice than the smaller one. Where the

large store on average offered 54 varieties the small one offered only 7. On average

there were 8.6 times more options available in the large store. The difference was

smallest for toast, where the large grocer offered nine varieties and the small one six,

and largest for butter, where the small one had one variety and the large one 20. The

most extensive assortments were found for yogurt (210 and 26 varieties

respectively) and jam (138 and 13 varieties respectively). They found that large

assortments had more attribute levels (not more attributes) and were able to maintain

product difference by offering larger attribute ranges.

A cross -cultural analysis of assortment depth was made by Einarsson

(2007), who analyzed the amount of products offered by grocers in various

countries. Higher amounts of choice were found in France and Finland than in for

example Norway (see figure 8). These data however are highly unrepresentative, as

all countries have many different store formats, which in turn differ on the

assortments offered. Also the amount of variety within each category is influenced

by the local popularity of the category. Furthermore, what one may count as variety,

another observer may not, such as Rubens apples, six pre-packaged Rubens apples

and 1 kilogram pre-packaged Rubens apples.

Figure 8: Number of products offered by the average grocer per category in 2004.

Based on: Einarsson (2007).

0

100

200

300

Diary Meat Beverages Cold cuts Average

Denmark Finland Iceland Norway Sweden France


There is some cross-cultural data available when it comes to the hard-

discounter Aldi (Nielsen, 2007). Assortment depth in these stores is highest in

Austria and in the south of Germany, while being lower in Denmark, France and the

Netherlands (see figure 9).

Figure 9: Assortment depth; number of items sold by Aldi by category by country.

Source: redrawn from Nielsen (2007).

It can be concluded that over the past decades the assortments offered to

consumers have expanded as many new products have and continue to enter the

markets. Approximations based on grocery stores show that the amount of products

on offer has increased with more than 50% over the last decade, and the rise of the

almost unlimited online assortments only add to this. Choice is especially abundant

in the US and Western Europe. The country with the largest stores in Europe is the

UK and also in Eastern Europe large formats have been increasingly popular. Within

Europe the largest preference for small stores can be found in Southern Europe.

Nowadays consumers are confronted with thousands of articles in most store formats

and in large grocers even tens of thousands. The amount of choice is however hard

to quantify, and the importance of category definitions when assessing choice can be

seen clearly when comparing the amount of products per category of the Aldi data

discussed before with those of Einarsson (2007).

For now this concludes the discussion of retailers as we lay our focus on the

customers, and specifically how and where they make purchasing decisions.

Furthermore, the effects of variety during and after the purchase are explored with

the objective to form a culturally sensitive model of the interactions between variety

and purchase satisfaction.

8,3

5,2 5,3

8,7

6,75,3

6,7 6,6

0

2

4

6

8

10

Consumer Demand for Variety 26

3. Consumer Demand for Variety

1. Sides to Variety

In chapter two it has been detailed how choice has extended over the last 200

years. Furthermore, some data was provided on store size preference. This chapter

will explain why diversity is often wanted by consumers and thus provides reasons

for why stores have different assortment sizes from country to country.

When choices are repeated two opposite tendencies manifest themselves as

consumers ask themselves whether to stick with the favorite or to vary (Fishbach,

Ratner & Zhang, 2011). Variety seeking is especially dominant in products

consumed for hedonic reasons. Choosing variation is often internally motivated by

(expected) satiation, the need for new stimuli and to avoid having a boring image in

favor of an interesting and unique one. Furthermore, when consumers are new to a

product category they may try to get more familiar and knowledgeable through trial.

On the opposite side, however, consumers also seek stability and consistency and are

motivated to demonstrate loyalty. This is especially strong when during the initial

choice the consumer believes he has made some form of commitment. The extent to

which consumers pursue variety seeking or commitment strategies is dependent on

amongst others their expected satiation and cues in the purchasing environment.

A reason for variety is that even though people may have stable preferences,

or even be brand dependent, different people prefer a different brand. Godin (2003)

relates the existence of specific product preferences to product class diversity. He

asserts that product categories that have ‘otakus’, a Japanese term referring to people

obsessed with a specific product comparable to connoisseurs, become more diverse.

This is because otakus do not only try out as many different varieties as possible, but

also tell their friends about it effectively increasing product class involvement.

Furthermore, they encourage people to express strong brand and product

preferences, and increase the importance of choice.

Whether or not people try to establish uniqueness or stability choosing is

related to identity. Chernev (2004) reports that an individual’s preference for product

choice is positively related to the extent to which this choice is perceived to affect

identity. Moreover, preference for choice is higher when self-image is centered on

the notions of autonomy and independence. The relationship between demand for


choice and identity increases in importance when decisions are communicated to

others (Ratner and Kahn, 2002).

In Western cultures having choice, of which the freedom to control

individual purchasing is a core pillar, is highly valued (Schwartz, 2004). Research in

healthcare shows that 95.6% of the 823 respondents found having choices extremely

important and 30.3% thought that making choices was extremely important (Leotti,

Iyengar & Ochsner, 2010). In agreement with this, another research shows that both

animals and humans display a preference for choice over non-choice even when

outcomes in both situations are the same, and making the second choice will require

extra effort. Also choosing between more alternatives is reported to be more

enjoyable and attractive than choosing between a more limited set (Iyengar &

Lepper, 2000). Furthermore, neuroscience has shown that results that are obtained

through choice are more gratifying than rewards that did not involve choice.

Research has demonstrated a direct link between freedom, or better said its

opposite namely confinement, and variety seeking. Levav and Zhu (2009)

demonstrated that customers in aisles with less width seek more diversity than

customers in broader aisles. Furthermore, they are more likely to choose lesser

known brands. This difference in variety seeking was associated to the extent to

which they felt physically confined. In fact, the aisle width does not need to be

changed to create this felt confinement. Primers, such as questions about the aisle

width, are sufficient to increase variety seeking. It is important to notice that aisle

width had no effect on peoples expressed mood.

Preference for choice in part reflects the general belief that more choice leads

people to do better. This belief primarily relies on the logic that as the amount of

alternatives increases, it is likely that some of the added alternatives are closer to the

optimal solution than the alternatives in the original set were (Chernev, 2004). There

is some research suggesting that there are limits to the amount of choice people find

attractive. Arunachalam, Henneberry, Lusk and Norwood (2009) found that when

American students were asked whether they’d like to choose from a set of 24 types

of soda or a set of six containing a random selection of the larger set, 42% of the 45

students indicated to prefer choosing from the smaller set. In addition whether or not

people like and do better on tasks involving choice depends on culture and does not

directly transfer to cultures in which group decision making, and decision making by

authorities are preferred (Iyengar, 2010). For example, Japanese children perform


better when their mothers have chosen for them, while American children perform

better when choosing themselves.

An additional cultural source for different perceptions of choice is exposure

to communism (Iyengar, 2010). For example elderly Eastern Europeans often

associated choice with fear, as they had gotten used to not having any choice and

had to adapt relatively quickly to the amount of choice offered in modern market

economies. Although the development of most European countries, including

Western Russia, was very similar for many centuries this changed when communism

gained popularity. Communism, with its radically different production scheme relied

much less on consumer demand to pull the market. And though there was marketing

under these systems as well, they were much more product type rather than brand

focused.

As all skills are learned through culture, people that come from cultures that

promoted the availability of few or no brand alternatives may now experience more

difficulties discerning differences between various products and may therefore have

more problems determining their preference as well as experience more trouble

deciding on what to purchase. For example Iyengar (2010) found that many

Russians did not perceive any difference between different types of soda when they

were offered Coca Cola, Coca Cola Diet, Sprite, Dr. Pepper, Pepsi, Pepsi Diet and

Mountain Dew. Rather they perceived this choice as ‘soda’ or ‘no soda’. When

offered the choice between these seven sodas, orange juice and water this was

perceived as three alternatives, namely juice, water or soda. Americans on the other

hand perceive each type of soda as a separate alternative. This is just one example of

how the perception of variety varies and shows how “the value of choice depends on

our ability to perceive differences between the options” (ibid. 11:47-11:55). A study

from Boyd and Bahn (2009) shows that ability to perceive variety indeed is related

to assortment preference. Those who perceive little variety prefer assortments that

offer less choice and those that perceive much variety prefer assortments offering

more choice. When choosing right becomes more important this difference in

preference becomes more pronounced.

Fisher (1984) suggests that consumer preferences may diverge as societies

become more affluent. As not having anything becomes less and less of a concern,

people shift their attention to address satiation, thereby generating preference for

choice. This is supported by our earlier finding of the positive relationship between


the amount of choice in retail stores and purchasing power. Moreover, people that

are faced with more choice have more chance to develop articulated preferences.

And as more concrete preferences leads to increased preference for choice (in an

experiment by Chernev, 2004, that will be discussed in more detail later) in demand

driven economies a self-reinforcing cycle could drive choice to expand.

Consumer demand for variety varies per country, consumer group, person,

and product category. A study by Rozin, Fischler, Shields and Masson (2006) of the

opinions of over 6,000 respondents shows that preference even within the western

world differs substantially. In France, Germany and Switzerland approximately 30%

of the population prefers choosing from 50 flavors of ice cream over choosing from

10. In Italy and the UK this percentage is higher (39 and 44 respectively). In the US

the preference for the larger assortment is highest (56%). A similar pattern was

found for restaurant menu size expectations, with around 20% of French, German

and Swiss respondents expecting many, compared to 29% of Italians, 40% of

English and 36% of Americans. A weak correlation was found between the two. For

all countries older respondents were less likely to prefer having much choice.

2. Exposing Oneself to Choice

Of course, consumers do not expose themselves to the same amount of

choice for each decision. I fact most consumers actively choose either to expose

themselves to choice or to avoid it. Kahn and Isen (1993) found that people look for

more variety when they are in a good mood. Consumers that consistently expose

themselves to as much choice as possible for the majority of choices they make are

referred to as maximizers. The differences between maximizers and satisficers will

be discussed shortly. First, however, a more comprehensive overview of choice

exposure strategies is given.

Haynes, Pipkin, Black & Cloud (1994) define six types of exposure style

profiles based on a research on maternity apparel store patronage of 100 pregnant

women (see table 2). First of all, there are shoppers, people with this profile know

many stores selling the item, considered visiting many of these and visit many as

well. These shoppers are highly involved, and show high interest in and enjoyment

of the shopping process. Their attitude towards planning shopping trips is very

positive. They are motivated little by the functionality (the search for information,


negotiation, purchase etc.) and more by the symbolic (the effects on self-image and

expectations related to social roles) and experiential (experiences resulting from the

experience) aspects of shopping. In line with this they are relatively little product

and price oriented. Demographically, this group includes the relatively old, wealthy

and well-educated.

Table 2: Choice exposure styles.

Source: Haynes, Pipkin, Black & Cloud (1994).

Secondly, there are narrowers. These people also know a lot of stores, but

considered substantially less and visited even fewer. They are unlikely to want to

plan shopping trips and are hardly motivated by the symbolic value of shopping.

Narrowers pay more attention to brand than the average consumer and focus less on

value for price. This group has no particular demographic profile, except that they

tend to be relatively more career oriented.

Thirdly, apathetics have low awareness of which stores are available,

consider few stores and visit few stores. They are young and the most career

focused, however have little income and little education. They put little emphasis on

the experiential side of shopping, are highly product oriented, care relatively little

about price, and want the store to have relatively much product knowledge.

Fourth, loyals are highly involved with shopping which they value for its

functionality; shopping allows them to get good value for money. While they know

the fewest stores, they visit a moderate amount, showing interest in those stores


which allow them to get the most out of their limited income. The fifth group, late

bloomers, are similar to loyals but know, consider and go to more stores. They are

likewise motivated by functionality, however instead of product involvement they

are concerned with reducing price and time taken.

The final group is the avoiders. Customers in this group dislike shopping the

most, have little involvement in the shopping process and get little satisfaction from

the process nor its outcomes. Although they know a moderate amount of stores they

consider and also visit the least. Their income levels are high, and they view

shopping as necessary and uninteresting.

3. Maximizers and Satisficers

The decision whether to stop searching once a product with desired

characteristics is found or to evaluate all available alternatives in an effort to make

the best possible decision effectively determines exposure to choice. Swartz (2004)

defines maximizers as people that “seek and accept only the best” (p.77), the

alternative to which is satisficing; settling for the alternative that meets the criteria

without worrying that another option may be better. Though maximizing-satisfying

can be constructed as a general personality trait, it is unlikely for a person’s

maximizing tendency to be fixed across product categories. Furthermore, there is an

interrelation with the extent to which people know what they prefer, a characteristic

which is further discussed in chapter 5.

For maximizers every purchase has to be the best purchase that could be

made, and therefore maximizers attempt to evaluate as many alternatives as are

available to them and consequently take longer to decide. In addition Schwartz,

Ward, Monterosso, Lyubomirsky, White and Lehman (2002) found that maximizing

was correlated with the amount of social comparisons made and the frequency of

counterfactual thinking during the purchase process.

In conclusion, want for choice and reactions to choice are culturally,

personality and circumstance dependent. The following chapters will investigate

choice more in depth, with a particular emphasis on choosing from variety.

Making Purchasing Decisions 32

4. Making Purchasing Decisions

1. The Purchase Decision

In the following chapters the focus will be on the customer’s purchasing

decisions and the effects of variety on their satisfaction with and after the purchase.

The following chapter will take a look at both theory as well as findings on

purchasing decisions. Firstly, the rational decision process will be discussed,

followed by differences between rebuys and new purchases. The frequency that

people make in store decisions, as well as what kind of decisions these are and how

they are made is covered in the last two sections.

All purchasing decisions start with people recognizing that they want or need

a product; followed by a search for information as well as an evaluation of the

alternatives based on set criteria (see Christ, 2008 for a more elaborate discussion of

each stage). This can be followed by the purchase of a product, which then is

evaluated during use. The decision making process outlined above is a rational one,

in which the consumer mentally evaluates the alternatives, maximizing the expected

utility (Hastie & Dawes, 2009). However, consumers are also influenced by other

factors, including moods, emotions, the consumer’s habits, imitation of a role model

and perceived cultural mandates.

For example, when working memory is occupied with as little as

remembering seven digits 63% of participants chose chocolate cake, while

participants that only had two digits in their working memory chose chocolate cake

only in 43% of cases (Shiv & Fedorikhin, 1999). This shows that when working

memory is occupied, people more easily make choices in favor of physically

pleasing alternatives, because the rational mind is too occupied to control impulses.

For reaching a decision especially the information search and evaluation of

alternatives stages are important. During these stages consumers make a (mental)

ranked list of the relevant products available to them and their characteristics. The

size of the evoked set (the mental list of alternatives) is not unlimited, as working

memory cannot contain an infinite number of items, nor evaluate the items that it

does contain on many aspects simultaneously, this is also known as bounded

rationality (Hoyer, 1984). In a classic study by Miller (1956) he asserts that we can

remember only a limited amount of information, more or less the size of seven digits

or ‘chunks’ (the smallest meaningful memory units, including letters, acronyms,


numbers, colors, etc.) if we focus on one characteristic. If we focus on more

characteristics the total amount of what we remember goes up, while the amount of

items remembered per category goes down, and also the accuracy of our memory

goes down. There are some techniques people use to increase the sets they can

handle, such as making relative judgments, increase the amount of dimensions, or

split the decision. People can also write the options down, as well as commit

knowledge to their long term memory.

2. Involvement, Information Search and Decision Novelty

Consumers do not go through the full decision process for each purchase as

extensively. A combination of two purchase characteristics seems to largely

determine the extent to which people engage in the search for information and

evaluate the various alternatives (Christ, 2008). These two characteristics are

involvement and decision novelty. These two characteristics combined lead to four

different types of purchasing decisions. Decisions that have been made repeatedly

before and are considered uninvolving and are referred to as routine purchases or

straight rebuys. Purchases that are relatively uninvolving but novel are called minor

new purchases, and purchases that are relatively involving and have not been made

before are called major new purchases. Finally, there are relatively involving

repeated purchases.

When making routine purchases customers rely on a previous purchasing

decision for their current product choice, minimizing cognitive effort (Hoyer, 1984).

They have found the product which satisfies them, may feel a certain loyalty to this

product, but most importantly give little thought to alternative products. Routine

purchases allow customers to completely ignore approximately 75% of the items on

the shelves (Swartz, 2004). Customers planning a routine purchase may still be

persuaded to evaluate other alternatives when there is a sales promotion. Also when

an item is out of stock, customers have to make either a minor new purchase, visit

another store or come back later. Under these conditions it may be found that what

was thought to be an uninvolving product is involving after all. Routine purchases

are discussed in more detail in the following section.

A second type of purchasing decision is customers making a minor new

purchase. As the product is neither expensive nor highly involving they make use of


limited problem solving. Consumers making these types of decisions are unlikely to

search information before entering the store and are likely to buy whichever product

alternative is offered as long as it meets their requirements and the price does not

exceed their expectations. A common decision strategy, the use of heuristics, is

discussed later in this chapter.

Finally, there are major purchases, which in the case of non-professional

consumers are unlikely to be re-buys as major purchases within one product

category are rather infrequent. Furthermore, if there is a need to make a large

purchase more than once this is often due to product failure, in which case

alternatives will be considered. When customers are faced with major purchases, due

to high involvement and/or high prices, they are likely to take much time for each

decision making step evaluating many of the offered options in detail, visiting

multiple stores and search online for information (Beatty & Smith, 1987).

3. In-store Decisions

Approximately two out of three purchases involve in-store decision making

(Inman, Winer & Ferraro, 2009). The MacFadden Communications Group LLC

(1996) reports more details for the mass merchandising retail sector based on a

sample of 1,399 American consumers. Namely, 41.5% of home furnishing purchases

were found to be decided in store. Domestics, such as towels, blankets and table

linens were often bought spontaneously with 48% of purchases being unplanned.

Also electronics were often (40%) decided upon in the store. In store decision

making in this context was defined as those consumers that either have no or only a

general idea as to what they are seeking, but have not yet decided on the product

they want.

The Point-Of-Purchase Advertising Institute (POPAI, 1995, as cited in

Shimp, 2008) reports that items with particularly high in-store decision rates in

supermarkets were first aid (93%), toys, crafts and sporting goods (93%),

housewares (90%), stationary (90%) and candy (89%). For mass merchandise

purchases high in-store decision rates were found in the following categories apparel

accessories (92%), foils and other food wraps (91%), hardware electric and

plumbing (90%), infant and toddler wear (90%) and garbage bags (88%). Examples

of product categories with exceptionally low in-store decision rates for supermarkets


are produce (33%), meat and seafood (47%), eggs (53%), coffee (58%) and baby

food (58%). In mass merchandise disposable diapers (35%), baby food (35%) eye

drops (52%), prerecorded music and videos (54%) and coffee, tea and cacao (55%)

had relatively low in-store decision rates. Overall non-necessities seem to have

higher in-store decision rates, as well as necessities that are not on top of the mind

(such as garbage bags).

As the previous studies show, many purchases involve some type of in-store

decision making. The extent to which decisions are made in-store is an important

decision characteristic, and purchases can be unplanned, generally planned or

specifically planned. Specifically planned purchses are those for which the customer

has decided upon the exact variety he/she wants to buy before enterring the store,

often these are straight re-buys, but they can also be products that the customer has

decided upon after seeing an advertisement, or after a long purchase decision. When

specificly planned purchases are changed in store, with the customer for example

buying Pringles instead of the planned Lays chips, this is referred to as a switch

purchase, which in grocery stores accounts for approximately 4% of sales, and for

approximately 3% in mass merchandisers (POPAI, 1995 as cited by Shimp, 2008;

The MacFadden Communications Group LLC, 1996).

In the case of a generally planned purchase, the customer has only decided

upon the category before enterring the store, while for an unplanned purchase, the

need recognition occurs in the store. Craft and hobby supplies were bought more

often unplanned (68%) than planned (The MacFadden Communications Group LLC,

1996). Unplanned purchases for all categories in mass merchandise stores are 53%,

generally planned 18% and 26 % are specifically planned.

A research by Inman, Winer and Ferraro (2009) investigates the in-store

decision making of 2,300 consumers sampled in 1995 from 28 different grocery

stores across the US making over 34,000 purchases. The research shows that the

majority of grocery store purchases in unplanned (60,9%), 32.5% of purchases is

specifically planned and 6.6% is generally planned. That purchases are unplanned

however, does not necessarily mean that once the consumer has decided to buy a

product in a certain category all brands will have equal chances of being considered.

These unplanned purchases are much more likely to be unplanned re-buys than

unplanned new purchases. Unplanned purchases are most likely for infrequently


bought products and more hedonistic products and made more often by consumers

on hedonistic shopping trips.

People making least unplanned purchases tend to use shopping lists, visit

fewer aisles, visit stores more often, spend less time in the store and pay in cash

(Inman, Winer & Ferraro, 2009). Women make 14% more unplanned purchases than

men, and also people buying groceries for larger households are more likely to make

unplanned purchases. Furthermore, people make approximately 10% more

unplanned purchases when they are more familiar with a store. “This may be

because consumers who are most familiar with the store are more willing to let the

store guide their need recognition” (ibid, p.24). Whether the respondents were

shopping alone or with others had no influence on the amount of unplanned

purchases.

4. In-Store Decisions and Heuristics

Given that shoppers make so many decisions in a matter of seconds, it has

been questioned to what extent the decision process described at the start of this

chapter applies for these small choices. A study by Hoyer (1984) of 120 supermarket

customers who were given a choice task between laundry detergents (a product

which is low on involvement, and has much variety), shows that most people

examined less than than two products (on average 1.42, 72% only examined one

product), and picked up on average only 1.2 products. Only 12% of the consumers

made a comparison between more than two products, and no-one looked at more

than 5 products. The majority (89%) of people did not look at shelf tags at all, and

75% took less than 10 seconds after entering the aisle to decide what brand to

purchase (mean=13 seconds, median=8.5 seconds).

The hypothesis Hoyer (1984) had formed was that consumers must use some

sort of simple rule to base their decision on. These rules of thumb, or heuristics, are

stragtegies that ignore part of the information allowing decisions to be made quicker,

more accurately and/or with less effort than under more complex decision making

(Gigerenzer & Gaissmaier, 2011). An interesting variant of this is the take-the best

heuristic, in which one searches his/her memory or envirnment for cues that

differentiate the alternatives meaningfully. Once a cue has been found that

discriminates between the alternatives wichever alternative scorers higher for this


cue is chosen. Most shoppers (91%) indicated to use some form of heuristic, the

remaining 9% using two or more heuristics. Most either bought the cheapest (15%),

the one they liked most (17%), the one they know works well (12%) or the one the

wife likes (7%). When grouping the responses into categories it was found that 28%

decided based on performance, 22.5% on price, 20% on affect and 11% on

normative heuristics. Especially when price heuristics are used Hoyer (1984) found

that consumers take more time evaluating alternatives, possibly as this heuristic

relies less on memory and is relatively easily checked in-store.

These heuristics may be stable for a product category, or constructed at the

moment a decision needs to be made. The repeated use of any such heuristic is

dependent on the decision outcome. In this manner simple heuristics may become

more complex over time, for example: ‘buy the cheapest Japanese brand’.

It is important to differentiate between product loyalty due to habit, the

constant application of stable evaluation methods and brand loyalty. Underhill

(1999) relates decreasing brand loyalty to increasing amounts of product choices that

are made on a purchase-by-purchase basis, rather than based on a stable brand

preference. Maheswaran, Mackie and Chaiken (1992) have attempted to measure the

interrelation, by presenting 122 business students with various descriptions of the

study’s importance, the brand track record and the products attributes. Their results

show that uninvolved consumers were influenced solely by the reputation of the

brand name. Subjects with high involvement were affected by product attributes and

only by brand name if its reputation was in line with these. Their findings provide

support not only for heuristics being used mainly for uninvolving products, but also

for involvement and motivation to reduce brand name importance if product

attributes do not match brand image.

The rational purchase model introduced in the start of this chapter has been

found to only limitedly apply to consumer choice in the retail sector. Most notably

involvement and decision novelty affect decision style. For repeated low

involvement decisions little cognitive effort is spent and decisions are either made

based on loyalty or heuristics. More involving and novel decisions however more

closely resemble the rational model, though limitations to memory should be taken

into account. Many decisions are made inside the retailer, because of this, it is

important to look at how the variety offered by the retailer affects customers’

decisions, most notably their likelihood to purchase.

Purchasing from Variety 38

5. Purchasing from Variety

1. Product Choice and Variety

The amount of variety presented has an effect on what product gets chosen.

As discussed in the previous chapter, choices are not fully rational, and can be

influenced by seemingly unrelated factors such as the extent to which memory is

occupied. Sela, Berger and Liu (2008) found that when two options were offered

55% chose fresh fruit over cookies, while when twelve options were offered 76%

chose the fruit. Similarly, when confronted with two ice-creams 20% of participants

chose the low-fat option, while 37% did so when faced with ten products. These

studies show that customers’ preferences may in fact be changed through the

presented amount of variety. This change in preference may be due the need for

justification, because as more variety becomes available preference shifts from

hedonic to utilitarian/healthier choices.

In a slightly different experiment, participants were faced with either two or

six printers and two or six mp3 players (Sela, Berger & Liu, 2008). When there were

in total four options people were least likely to prefer a printer (11%). However,

when the amount of available options for either mp3 players or printers increased the

amount of participants that chose the printer went up (to 32-54%). The most notable

result is that when the variety of mp3 players increased the frequency with which

they were chosen decreased. This provides support for customers fulfilling utilitarian

rather than hedonic objectives when faced with more choice. In addition, it was

found that rather than assortment size alone, the experienced choice difficulty

explained the choice for more utilitarian alternatives.

The choice for hedonic or utilitarian options is based on an interaction

between mood and assortment size. For example, participants that were primed with

indulging were more likely to choose a laptop for fun, than those that were primed

for work when choosing from small assortments (Sela, Berger & Liu, 2008). When

choosing from larger assortments, however, the effect of the priming was

significantly less pronounced. On the other hand, those participants that were given a

reason to reward themselves were more likely to do so when assortments were

larger. These experiments show that the amount of variety presented in retailers has

a large influence not only on what alternative we buy but also on which criteria we

seek to meet.


2. Chance of Purchase and Variety

Purchases decisions are more complex than solely what option should be

selected. As variety expands deciding between options is perceived as increasingly

difficult (Chernev, 2003). This difficulty in deciding may cause customers to

postpone the decision or to not buy at all. Choice deferral decisions can be under the

customers attention before selection has taken place, but research on choice deferral

has demonstrated that this decision whether or not to buy is often made after

consumers have decided which option they would like most (Dhar & Nowlis, 1999).

The likelihood of deferral is related to how easy this product selection decision is;

the more difficult and unsure the customer is about their preference the more likely

he or she is to decide to defer the purchase. Looking at the relationship between

choice deferral and variety is not only important from a sales perspective, but

additionally because indecision and choice deferral lead people to doubt their

decision making skills, lower self-confidence, increased shopper fatigue and an

overall decrease in the enjoyment of the shopping experience (Mitchell, Walsh &

Yamin 2005; Mitchell & Papavassilou, 1997; Matzler, Stieger & Füller, 2011).

One of the field’s most renowned papers on when variety leads to decreasing

chances of purchase was published in 2000 by Iyengar and Lepper. This paper

contains several experiments. The first experiment was a field experiment in which a

jam-tasting booth was operated for 5 hours for each of two conditions on a Saturday

in a large grocery store. The regular assortment contained 300 types of jam. On the

booth first 24 types of jam were offered, and the second Saturday only 6 types of

jam were offered. The extensive offer did not include the four most commonly

preferred jam types, and the limited assortment was selected from the more

extensive one by selecting two often preferred types, two moderately often preferred

types as well as two least often preferred types.

The results of the experiment were that both booths attracted the same

proportion of men and women, and also subsequent observed behavior did not

significantly depend on gender. The booth that presented more choice attracted the

attention of many more of the customers that passed by (60%) than the booth with

limited choice (40%). The amount of jams each customer tried was not significantly

different, with customers trying on average 1.5 types of jam when presented with

extensive choice and 1.4 when presented with limited choice. However, customers

faced with the limited assortment were much more likely to purchase a jar of jam


than customers who were faced with the extensive assortment (30% and 3%

respectively). This suggest that having fewer alternatives is in fact more motivating

than having many. This study however has many limitations, the most important of

which is that the intentions of people that approached both booths may have

differed.

In a second study Iyengar and Lepper (2000) participants sampled a

chocolate that either was chosen for them, that they chose from a limited assortment

or that they chose from an extensive assortment. The participants that did not choose

themselves were shown either the limited or extensive assortment to control for the

amount of alternatives presented. In total there were 134 student participants who all

indicated to like chocolates, split equally between the 4 experimental conditions. It

was found that students deciding between 30 chocolates took more time to decide

than students choosing between 6 types of chocolates. The average time taken to

decide was 24.4 and 8.9 seconds respectively. Additionally, participants that decided

between 30 types of chocolate indicated that there had been too much choice, while

participants that chose from between 6 chocolates indicated that the amount of

choice had been “just right”. The amount of choices had no effect on reported

expected satisfaction, and participants in both groups were equally likely to have

picked the alternative they usually chose. Participants that indicated that the

assortment had contained too much variety reported to have found choosing more

enjoyable, frustrating and difficult. While the experience of difficulty and frustration

were correlated, neither of these was correlated with enjoyment, indicating that

choice can be enjoyable and overwhelming at the same time.

After tasting the chocolate 48% of the participants that had been presented

limited choice purchased some chocolates. This was much higher than the 12% of

people in the extensive choice condition and the 10% of those in the no-choice

condition. In fact, there was no significant difference between the likelihood of

purchase of the latter two groups. This shows that those that were faced with

extensive choice were hardly more satisfied with the resulting chocolate than those

that had had no choice at all, and that rather than large assortments allowing people

to do better our capacity to choose results in choices that are hardly better than

results obtained with no choice at all.

A study by Heitmann, Herrmann and Kaiser (2007) looked at 583 German

customers of three major consumer electronics retailers who considered the DVD


player or digital camera assortments during a minimum of five minutes. Overall,

50.6% of the respondents had bought an item, 49.4% had not. Figure 10 shows the

relationship between assortment size and purchase frequency they found. This

suggests that there is an optimal range for variety, with three being too few, and 12

options being too many. Shah and Wolford (2007) found a similar result when

selling pens. Price was kept the same and assortments were varied between two and

twenty options. The proportion of potential customers making a purchase was

highest with an assortment between eight and twelve pens, second highest with an

assortment of two to six and lowest with assortments of 14 and more.

Figure 10: Relationship between perceived variety and likelihood of purchase.

Source: Heitmann, Herrmann & Kaiser (2007).

3. Chance of Purchase, Trade-offs and Preference Uncertainty

As the previously discussed researches have shown the size of the assortment

is related to the chance of purchase. Dhar (1997) suggested that difficulty to select a

single item is one of the most prominent reasons to delay a purchasing decision. This

choice not to choose can be combined with a choice to look for more information

and/or more alternatives. This happens most often when there is no clearly superior

product, due either through trade-off difficulty or preference uncertainty. These

theories were confirmed by his experimental study of 190 American students

imagining the purchase of four different consumer electronics (bookshelf speakers,

answering machines, laptops and electric shavers). When there was only one product

alternative around 60% of the students decided to purchase the given option. When


an alternative was added which was relatively heterogeneous, thus high on trade-

offs, purchase rates were lower (48%), in favor of search for other brands. This

tendency was stronger when the added alternative was relatively homogeneous

compared to the first option, thus presenting relatively few trade-offs. Finally, when

an alternative product that was worse than the original option was provided purchase

rates went up, and fewer people were interested in obtaining information on other

brands.

Dhar (1997) replicated these results using 300 students who were first shown

five product alternatives and then told to imagine that the store they were currently

in, depending on the experimental condition, had either one or two of them. They

were asked to indicate whether they would buy a provided alternative or visit

another store. It was found that when multiple attractive options were available

participants were more likely to postpone their purchase then when only one

attractive option was available, even though also when only one option was

available they already knew of the existence of the other alternatives. This supports

the hypothesis that the existence of trade-offs can cause people to postpone their

purchase. When an inferior alternative was available in the store people were less

likely to postpone their decision. Participants across the experimental conditions

rated the chance of a better sale similarly, therefore the chance of purchase seems

related to preference uncertainty and inability to make trade-offs, rather than a belief

one could do better by searching further.

A third study by Dhar (1997) in which 30 students vocalized their thoughts

about their choice between either two similar products, choice set {A,B}, or two

products of which one was superior, choice set {A,C}, showed that participants were

cognitively more involved when products were similar. Furthermore, when the

participant decided to defer the choice between comparable alternatives both

alternatives received as much attention as the chosen alternative had for those that

did make a purchase. When there was a clear superior alternative participants that

did decide gave the chosen alternative as much thought as the participants making a

choice from set {A,B}. The non-chosen alternative however received much less

attention. When participants faced with set {A,C} decided to defer the choice they

gave the alternatives much less thought. Thus, especially choice sets with similar

alternatives lead to indecision, and customers faced with this type of choice try for a

longer amount of time to choose.


The experiments from Dhar (1997) consistently show that people are most

likely to decide on an article when they are sure of their preference between two

articles, followed by when only one alternative is available and finally least likely to

make a choice when trade-offs are involved. These results are confirmed by various

other experimental researches (Schwartz, 2004). For example, when participants

were asked to choose whether or not to purchase, 73% decided to purchase if a

discounted CD player was offered and an inferior non-discounted CD player was

offered as well, 66% of the participants faced with one discounted CD player would

make the purchase, and 54% of people faced with two discount offers would make

the purchase. Furthermore, a choice between a relatively unsafe cheap car, and a

relatively safe higher priced car, with the price difference being what the participant

indicated this higher safety would be worth, led participants to experience negative

emotions and if possible the participants tended to avoid the choice altogether. The

negative emotions evaluating trade-offs arouses may impair decisions as it distracts

and narrows focus.

Schwartz (2004) suggests that the avoidance of trade-offs is a major

motivator for the use of consumer reports, experts and other sources. By relying on

their opinion decision makers are able to skip evaluating many characteristics of the

alternatives. Unlike the average purchaser opinion leaders have taken the time to

obtain information from a wide variety of sources, including stores and category-

specific magazines (Shoham & Ruvio, 2008). The less knowledgeable purchaser,

when faced with a difficult choice in which there are either trade-offs or in which he

is not sure of his personal preference, may attempt to make a more optimal decision

by adopting the choice of an opinion leader (Leotti, Iyengar & Ochsner, 2010)

4. Memory and Time

The most obvious limiting factors to the amount of alternatives one can

consider during a purchasing decision are memory and time limits. Schwsartz (2004)

suggests that though people want to limit the amount of alternatives they consider,

when faced with large assortments it is easy for them to repeatedly decide in favor of

including one more alternative into their mental list. This is called the ‘tyranny of

small choices’ because though including one more seems harmless, when done

repeatedly the set of alternatives under evaluation tends to become unmanageably


large. Especially as with the amount of products under consideration, the time this

evaluation takes increases exponentially. Simultaneously, though products differ on

increasingly various aspects, the amount of product aspects evaluated goes down

(Miller, 1956). However, being pressured for time will limit the amount of options

that can be considered.

Research by Dhar and Nowlis (1999) shows that time pressure is related to

choice deferral and that this relationship varies as the characteristics of the

assortment change. In the initial study 196 undergraduate marketing students were

asked two make a choice between two alternatives in three product categories. These

products were either both attractive or there was one clear superior product, and

either an answer for all three choices was expected within 45 seconds or participants

were given unlimited time. The results of this were that those presented with

equally attractive options and unlimited time reached a decision much less often

(choice deferral rates around 36%) than those under time pressure (choice deferral

rates around 21%). When presented with clearly superior and inferior options, time

pressure did not have an influence on choice deferral (choice deferral rates were

around 22%).

This result may be explained by those under time pressure process

information more selectively and focus more on characteristics unique to the product

(Dhar & Nowlis, 1999). When there is no time pressure on the other hand customers

may be more likely to focus on characteristics shared by both products in an attempt

to process all information. Results from their second study using 240 undergraduate

marketing students showed that assortments containing products with moderately

attractive features in common were more likely to cause choice deferral than

assortments with highly attractive common characteristics. This effect was less for

those participants under time pressure and larger for those that had little time

pressure. Their third study of 262 students showed that time pressure leads to

decreased choice deferral only if the unique characteristics of the products are

attractive and the common ones unattractive, but not when the common ones are

attractive and the uncommon ones are not.

In conclusion, these studies show that time pressure simplifies decisions by

focusing the purchasers attention on unique attractive features rather than features

products have in common and less attractive characteristics. Further the studies


showed that under time pressure less information was collected (Dhar & Nowlis,

1999).

5. Knowledge and Articulated Preferences

Up until now we have discussed making decisions without taking into

account more person specific factors. There are various person bound characteristics

that have a profound effect on how one perceives and is affected by variety. Here the

focus will be on knowledge, involvement and articulated preferences. The final

section of the chapter will discuss a special variation on choice variety, namely

customization.

When people become more knowledgeable about a product they perceive

less variety within the assortment (Park & Lessig, 1981). In particular the perceived

category breadth is reduced as more and more mental product categories are created

for each characteristic. For customers with little or no direct information about a

product through experience the more recognized differences there are the more

cognitive burden there is to evaluate all these categories. Therefore, customers with

no or little knowledge are more likely to focus primarily on price and brand and

group all alternatives in one or few large categories. People with moderate and a lot

of experience perceive more variety of product characteristics, make more groups

and thus perceive less category breadth. Those with moderate knowledge focus

primarily on functional characteristics, however have little knowledge to evaluate

these on causing them to take, in the case of microwaves 40%, more time to reach a

conclusion then those with both less and more knowledge. People with a lot of

knowledge, due to prior ownership, focused on both functional characteristics as

well as brand and price equally while making a decision. Their final finding is that

people with less knowledge feel less confident in their evaluations of criteria and

less confident in their decision as well.

One influencing factor is that individuals vary in the extent to which they

have verbalized product preferences (Chernev, 2004). While some may know

exactly what characterizes the preferred pre-packaged meat, another, though equally

aware of the characteristics of pre-packaged meat may have no such clear cut

articulated preference. This moderates the effects of having much variety. People

who have articulated preferences are able to directly evaluate to what extent


products are satisfactory, while those that do not need to simultaneously articulate

what they perceive as ideal and rank the available alternatives. This dual task

becomes more and more complex as variety grows because there is an increasing

amount of attributes that need to be considered.

Chernev (2004) tested this theory using an experimental set-up. For this 101

American students were equally divided over four experimental conditions. Half the

participants were asked beforehand to describe their ideal chocolates by picking

their ideal kind on four characteristics, namely type, mix, flavor and nut content. The

second characteristic of the conditions was that students were faced with either eight

or 20 chocolates to choose from. The choice alternatives were split between two

brands, in both conditions the ‘limited assortment’ brand carried alternatives that

were the same as those offered by the other brand. Therefore, effectively there were

four and 16 alternatives in each condition.

The results Chernev (2004) obtained showed that for those who picked from

more alternatives the ones that had articulated their preferences chose much more

often than those that had not articulated their preference (98% and 72%

respectively). On the other hand when deciding from a smaller assortment, there

were less people that made a choice in both conditions, but no significant group

differences (54% and 43% respectively). This shows that increased assortment sizes

enable those with more specific wishes to choose from amongst the alternatives

more effectively than those with less articulated wishes. Furthermore, those that had

articulated their ideal chocolate type beforehand were more likely to choose from the

brand that offered a larger assortment (93%) than those who did not articulate their

preferences (43%). Thus, one may conclude that people who have less articulated

preferences are more likely to prefer limited assortments. Finally, participants were

more confident that they had selected the optimal alternative when faced with the

smaller assortment, a difference that was larger for participants with articulated

preferences. When choosing from the larger assortment participants that had

articulated preferences were much less confident about their choice than participants

that had not articulated their preference.

Further research showed that people that have articulated preferences can

skip the early decision stages allowing them to reduce the effort spent in searching

information (Chernev, 2004). People without articulated preferences are more likely

to first attempt to understand the attribute structure of the assortment, then form their


preference and then find their preferred alternative. Also, as people with articulated

preferences did not observe the characteristics of all alternatives, it is speculated that

they stop searching for information once an alternative was found that sufficiently

matched their ideal product, a characteristic previously attributed to satisficers as

well. The extent to which preferences are articulated has a greater influence on

search style as assortment size grows.

When participants were asked to justify their decisions afterwards those with

articulated preferences used more confirmatory arguments, such as ‘I chose option x

because I like white chocolate’, than participants that had not articulated their

preferences. However, the relative amount of confirmatory statements was equal

across the groups. Participants that had not articulated their preferences were more

likely to give disconfirmatory reasons, such as ‘I did not choose option x because I

do not like white chocolate’.

Chernev’s (2004) results also showed that those that articulated their

preference beforehand were able to recall fewer alternatives. Both groups were

equally likely to recall alternatives incorrectly. Participants that had articulated their

preferences beforehand were more likely to recall options presented earlier on the

list of alternatives, while participants that had not articulated their preference were

equally likely to recall options mentioned early as options that were mentioned later.

This supports the idea that those with more precise preferences are more likely to

stop evaluating alternatives once an adequate alternative is found.

These experiments provide evidence that the more the decision maker’s

preferences are specified the less difficult choosing becomes. This effect of

articulation is especially pronounced as assortment sizes grow. There is a main

reason that having specific criteria facilitates choice. It enables the purchaser to,

rather than having to create an overall picture of the offered variety and choose the

preferred option from that, stop evaluating alternatives once a product with desired

characteristics is found.

6. Customization and Personalization

The difference between customization and personalization is for the former a

unique design is made based on the customer’s needs and wants while in the latter

the customer picks from among predefined alternatives for each characteristic and


thus compiles his product (Franke, Keinz & Steger, 2009). The two terms however

are used interchangeably by many researchers as well as marketing applications and

also here both will be used to refer to personalization.

Customizing and personalizing have become increasingly popular, especially

as the Internet provides an easy platform for customers to define and communicate

their preferences almost directly to the production department (Franke, Keinz &

Steger, 2009). Innovations in production and delivery have also facilitated the

growth of personalization. And increasing heterogeneity in demand allows

companies to define choice sets that are not exceedingly large but do satisfy almost

their complete target group. Offering personalization is attractive because it provides

a large number of alternatives under one name and allows customers to get a product

or service closer to what they are looking for. However research has suggested

various downsides to customization, most notably the high customer participation

that it requires and the customer’s inability to recognize the opportunities offered.

A study on customization of newspapers in Austria found that people faced

with a customized newspaper evaluated it more positively than participants faced

with newspapers targeted the average consumer, those designed by experts and those

based on segmentation (Franke, Keinz & Steger, 2009). Those faced with a

customized version were more willing to pay, had a higher intention to purchase the

product and had a more positive attitude toward the product. Preference insight and

the ability to express this insight increase the benefit derived from customization.

These results were reproduced in a study between online customization versus

standardized products for fountain pens, kitchens, skis and breakfast cereals. For

these products additionally product involvement was shown to increase the benefits

of customization.

Levav, Heitmann, Herrmann and Iyengar (2010) did three studies in this

respect. First they investigated the customization of suits by giving 73 MBA

students the chance to win a substantial discount on their ideal suit by designing it.

The amount of options provided was diverse, for example there were 100 suit

fabrics, 20 types of suit buttons and 20 dress socks. Participants were either provided

with the category with most options first and that with least last, or the other way

around. Results show that when the amount of options gradually increases the

amount of times participants choose default remains more or less stable. When they

on the other hand are first presented with much choice and after that with decreasing


amounts they choose the default option more and more often. In addition to making

more choices the participants who were first faced with little choice were more

satisfied with the result and more confident that they would make the same choices

again than those that had first been asked to decide about the suit fabric.

In the second study Levav, Heitmann, Herrmann and Iyengar (2010) looked

at car personalization in Germany in co-operation with a large European car

manufacturer. In total 450 clients of various dealers were asked to design their sedan

using the online customization software. The participants were invited by the dealer

who was unaware of the purpose of the study. The customization process contains

67 product attributes, with between 4 and 56 different options of which one is

selected by default, and takes around 30 minutes. The price of the car is updated as

each attribute is decided and customers can go backwards in their selection process.

During experiment two, eight of the customization decisions were selected

and placed at the start of the process. Results replicated the finding that those

choosing from much variety first are more likely to choose default, especially in

subsequent choices, indicating shopping fatigue. In addition, those first choosing

from much variety were willing to pay significantly more for their car (€1,482.37

more on an overall average of €36,507.48). Moreover, the overall satisfaction was

lower for those that had started with having much choice. Thus, while customizing

the car less and being less satisfied with it participants that started with much choice

were willing to pay more. This while only the order of the first eight out of 67

customization decisions was changed. This effect however disappeared when the

study was duplicated with 300 participants using instead of the high variety

expensive engine a low variety less expensive radio and keeping the other seven

items the same. Purchasers that were more knowledgeable were less likely to choose

default and thus less affected by the order of choice.

Combined these studies show that for customization is most beneficial for

those that know what they want and who are therefore able to make decisions

regardless of the order of the attributes. Also those that are less sure about their

preferences through customization arrive at a product they like better than they

would the standardized version. However, customers that are less sure about their

preferences need more guidance when choosing and should not be presented with

too much choice at the start. Companies, however, should consider the attribute

order carefully as it has a large influence on how much customers are willing to pay.

Variety and Post-Purchase Satisfaction 50

6. Variety and Post-Purchase Satisfaction

1. Post-Purchase Satisfaction

Choosing from larger assortments takes more mental effort is perceived as

more difficult and induces feelings of frustration. Additionally, choosing from larger

assortments is more likely to lead to choice avoidance. Choice avoidance is

moderated by knowledge, time pressure, assortment variety and involvement. On the

other hand, having choice can also bring enjoyment and reinforce identity.

Downsides to choosing from more variety are believed to be compensated by, as

discussed in chapter three, doing better both objectively as well as subjectively.

Objective choice accuracy found that people looking for specific product

characteristics were equally well off in large as small assortments (Fasolo, Hertwig,

Huber & Ludwig, 2009). People with less specific objectives pick more accurately in

stores with small assortments and less so in stores with large variety. Furthermore,

there are other indicators that purchasers deciding from large assortments may not

do better than those in limited assortment contexts. As discussed in the section

‘Knowledge and Articulated Preferences’ in chapter five, the participants in

Chernev’s (2004) study were more confident that they had selected the optimal

alternative when they had decided in a limited assortment context than when they

had faced the larger assortment. This effect on decision confidence is especially

pronounced when no ideal product or reference point such as a previously bought

satisfactory product is present (Chernev, 2003).

Additionally, when people choose from many alternatives their satisfaction

with the purchased product is relatively low. Coming back to the research on

choosing between chocolates discussed in the section ‘Product Choice and Variety’

in chapter five, Iyengar and Lepper (2000) found that when participants choose from

among six alternative chocolates were significantly more satisfied with the taste of

the chocolates and reported less regret than participants who had been able to choose

from among 30 alternatives. This reduction in satisfaction is not there for everyone.

When participants were asked to choose from either five different types of coffee

those that had articulated preferences tended to be somewhat less satisfied then those

that did have articulated preferences, while unknowingly drinking the same coffee

(Mogliner, Rudnick & Iyengar, 2008). When asked to choose from among 50

uncategorized types of coffee the satisfaction of those that did not have articulated


preferences dropped substantially, while the satisfaction of those with articulated

preferences increased a bit.

There are various suggested reasons as to why people may feel less satisfied

with their choices when there are more available alternatives. This chapter will

discuss some of these, namely opportunity costs, escalation of expectations, regret

and responsibility for the outcome.

2. Opportunity Costs and Escalation of Expectations

First of all there are opportunity costs. Opportunity costs are the costs

associated to not choosing each of the other available alternatives (Schwartz, 2004).

These opportunity costs lessen the subjective desirability of the chosen alternative,

because the purchaser loses the opportunity to experience the alternative. Carmon,

Wertenbroch and Zeelenberg (2003) attempted to measure this, as they named it,

option attachment by asking 53 American students, 114 Dutch students and 156

Chinese students to imagine various scenarios. Results showed that when greater

attachment to the non-chosen option was described participants projected greater

post-purchase discomfort and heightened attractiveness of the forsaken alternatives.

This was true when the option attachment was increased because of greater option

proximity, a longer period of deliberation, forfeiture rather than acquisition, hedonic

rather than utilitarian consumption and prior ownership.

Furthermore, Carmon, Wertenbroch and Zeelenberg (2003) also analyzed the

occurrence of opportunity costs of real choices. For this 43 university staff-members

were assigned to one of four experimental conditions, characterized by whether they

were presented a choice and whether or not they had to elaborate. They were all

presented three times with sets of two coupons for each of which the people in the

elaboration condition had to elaborate upon the advantages and disadvantages of

each coupon. Then those in the choose condition were asked to choose which one

they preferred. Finally all participants rated the attractiveness of the less appealing

coupon, after which all participants received either the coupon they chose or a

random one. Rating results showed that the less appealing coupon was rated more

favorably when it had not been chosen, thus supporting the existence of opportunity

costs. This effect was stronger when the choosers had also elaborated beforehand,

thus supporting that higher option attachment increased opportunity costs.


As the amount of options available increases, the amount of desirable

features of these options also increases (Schwartz, 2004). Therefore, when choosing

from among many opportunity costs are likely to be heightened. It is very unlikely

for one option to be better in every aspect than all other available options. In this

manner the made trade-offs decrease satisfaction with the final choice. In

conclusion, while larger assortments are more likely to include an option that you

like, it is precisely the fact that it will include things that you like that makes you

less likely to choose and less satisfied with your choice. Furthermore, when people

attempt to limit these effects through settling for the first satisfying alternative they

are less likely to perform better objectively speaking as well.

As the amount of alternatives increases it becomes increasingly easy to

imagine alternatives that are better (Schwartz, 2004). When there is only one

alternative, the worst that can happen is that one gets disappointed, however, as the

amount of alternatives increases, people expect that at least one of the alternatives

resembles their ideal product more and more (Diehl & Poynor, 2010). Because of

this their evaluation of the best they could possibly do by choosing any alternative

goes up. Unfortunately, as the perception of the best one could do increases, the

chosen alternative tends to look worse and worse in comparison. And as

comparisons with what is perceived as possible is often the only meaningful

benchmark available when evaluating a product, satisfaction decreases. This,

Schwartz speculates is related to the fact that consumers are less likely to be

positively surprised when their expectations are higher.

3. Regret and Responsibility

Regret is an emotion that purchasers experience when after making their

purchase they change their decision in favor of an alternative (Schwartz, 2004). The

frequency with which regret is experienced is strongly correlated with the extent to

which people compare what they bought to current offers. Regret is worse when the

causes for a bad outcome are small and when the now regretted option was

considered during the decision process.

According to Schwartz (2004) regret is often expressed through

counterfactual thoughts. Counterfactual thoughts express the world as it currently is

not but as it could be or could have been. These types of thoughts can improve how


we feel about our current situation when we imagine other, worse, possible

situations. Imagining better current situations however makes us regret the choices

that we have made and makes us less satisfied with the chosen alternatives.

Unfortunately, studies have shown that people are much more likely to imagine and

vocalize better alternative current situations rather than worse, thus counterfactual

thoughts tend to increase the amount of experienced regret, and decrease our

satisfaction with both the made choices as the chosen alternatives.

When looking at the relationship between sunk costs, expenses that cannot be

regained no matter the future course of action, and regret it has been found that the

higher the sunk costs the more likely people are to attempt to avoid regret (Schwartz,

2004). For example, people that paid more for a theater ticket were more likely to

attend the performance than people that paid less.

Empirical evidence that regret increases with the amount of alternatives

available has been provided by Heitmann, Herrmann and Kaiser (2007). They

collected responses from 583 German electronics customers that had deliberated at

least five minutes over the assortment of either digital cameras or DVD players.

50.6% Of the respondents had bought an item, 49.4% had not. Results indicated that

anticipated regret increased with the assortment size and moreover that it was a

driving factor behind low purchase rates when large assortments were offered.

Maximizers, who are the ones most willing to expose themselves to choice,

are more likely to experience regret, anticipate experiencing regret and express

counterfactual thoughts. Therefore, though satisficers may be impacted little by

having more choice maximizers may be more so.

A final possible drawback of choice is its relation with perceived control

over outcomes (Schwartz, 2004). As a consequence, as ones choice increases so

does one’s control over the outcomes. However, having a larger amount of options

also increases the chance that a consumer mistakes one product for another. And

thus while meaning to buy product A finds himself back at home with product B.

When we perceive higher control over the outcome, not only does our regret over

negative outcomes increase, but so does our perceived responsibility for them

(Schwartz, 2004). Unfortunately, this sense of responsibility may link unsatisfying

products to self-blame and negative self-perception. The sense of responsibility is

lessened when decisions are justified rather than impulse based. Inman and


Zeelenberg (2002) found that when decisions were justified less regret was

experienced than when the decision had been impulse based.

This chapter has outlined various reasons why people that are faced with

more choice may be less satisfied with their choice. Most explanations provided are

taken from Schwartz (2004), namely opportunity costs, regret, escalation of

expectations and responsibility for the outcome. For some of these support from

other authors has been found. However, many of these hypotheses are difficult to

test, and as the extent to which the customer engages with the alternatives as well as

world view play a large role, research has often been inconsistent.

In conclusion, the literature review shows that increased variety has many

negative impacts on decisions (see figure 11 for a summary). Identified mediators of

variety are the extent to which products differ, time pressure, involvement,

knowledge and articulated preferences. The remaining part of this research will

discuss what the presentation of choice can do to mitigate these effects and attempt

to replicate these findings through empirical research of both Dutch and Americans.

Figure 11: Variety and decisions; relationships identified in the literature review.

Note: Green boxes represent positive, red ones negative and blue non-linear relationships.

Decision Product Use

Indecision

Need for justification

Enjoyment choosing

Frustration

Shopping fatigue

Shopping experience

Confidence choice Product satisfaction

Opportunity costs

Satisfaction Choice

Regret

Aspects considered

Product expectations

Responsibility

Objective Accuracy

Choice Moderation by Retailers 55

7. Choice Moderation by Retailers

1. The Retailers and Variety

The third sub-question that is defined in the introduction is: ‘What are

industry best-practices when it comes to presenting choice?’ This chapter aims to

give a brief overview with as main focus the continuing drivers for retailers to

expand choice, presentation effects and other retailers’ policies that have the

potential to influence consumer reactions to choice. Within presentation effects

emphasis is placed on categorization and decision trees. For the latter the findings of

an in depth interview on how a major Dutch retailer presents choice are used.

The customer is not the only party that does not always benefit from

increased variety, also for retailers there are costs (Oppewal & Koelemeijer, 2005).

First of all, if a retailer offers more variety he needs more shelf place to present this

variety on. Restocking takes longer as there are more products that need to be

restocked and inventories go up as for each individual product sufficient items need

to be in stock to prevent stockouts. As more SKUs are added the ICT systems need

to accommodate more unique numbers and the chance that errors are made in the

imputation of data grows. Finally, more category managers are needed to negotiate

with more suppliers, plan which products are offered and monitor their profitability.

Furthermore, the practical consequence of the scientific evidence from the

previous chapters is that when slight reductions are made (1-5% decreases) category

revenues grow with 1-14% (Nielsen, 2010c). Boatwright and Nunes (2001) found

similar results for online grocery assortments. On average they decreased

assortments with 20% leading to 11% in sales growth. Research additionally shows

that when options are highly attractive smaller assortments are preferred over larger

ones (Chernev & Hamilton, 2009). Thus, rather than expanding assortments the

solution may be to select products more wisely.

Therefore, it is no surprise that also retailers have recently attempted to

reduce their assortments. Taylor and Chaudoir (2010) found that grocery store food

assortments had shrunk with 1% during 2009, with 22% of stores increasing their

assortments with an average of 3%, while 40% decreased it with an average of 5%.

Further assortment reductions of approximately 15% were expected during 2010. At

the end of 2009 Walmart announced a 20% reduction in part to reduce clutter

(Supply Chain Digest, 2011).


This change in strategy has met with some serious obstacles. Suppliers

pressure for increasing rather than decreasing assortments. Furthermore, often

customer dependence on specific product varieties is cited as reason against

assortment reductions. In addition, it remains true that customer interest and varying

profit margins are often drivers for category mitigation and thus customer driven

increases in variety also remain present (Zentes, Mirschett &Schramm-Klein, 2011).

There are few specific categories in which USA consumers want more variety,

namely well marketed new products, medium marketed premium products (so called

A-brands) and low marketed store brands (Nielsen, 2010c). Also, overall consumers

seem to want more variety. Research shows that customers evaluate larger

assortments more favorably (Oppewal & Koelemeijer, 2005). Furthermore, larger

assortments attract more attention, provide the store with a competitive advantage

and may lead to increased consumption (Mogliner, Rudnick & Iyengar, 2008).

Bishop (2010) found that 72% of US retailers have increased their

assortments over the past 5 years. For 2011 37% said they were likely and 8%

indicated to be extremely likely to add new product categories, while 30% indicated

to want to reduce the total assortment. Also Walmart reversed its strategy in 2010

announcing to expand its assortments again with an average of 11% (Supply Chain

Digest, 2011). In the Netherlands assortment expansion has been the trend for 2009,

2010 and 2011 (Deloitte, 2009, 2010, 2011). For 2011 on average retailers planned

to enlarge assortments with 20-30%.

However, some research has cast doubts on to what extent customers are

capable of recognizing changes in the assortment variety offered. Nielsen (2010c)

found that when assortments are cut 30% of consumers believe that they in fact have

increased and only 6% recognizes the reduction. This latter finding does not mean

that consumers are incapable of recognizing the amount of choice offered. Data on

retailers in the UK shows that hard-discounters with their smaller assortments score

low on perceived amount of choice, other supermarket chains, such as Sainsbury’s,

Tesco and Asda score higher (Cox & Brittain, 2004). However, this finding does

show that there is more that determines customers perception of variety than only

the amount of different products sold.


2. Presentation Effects

There are various manners in which the perception of variety can be

influenced and the negative effects of too much variety can be mitigated. Possibly

the most defining factor of the amount of variety and the difficulty consumers have

deciding between the alternatives is how the store presents choice. Retail marketers

can increase the perceived variety by varying messiness, shelf space and by

featuring popular options (Mogliner, Rudnick & Iyengar, 2008). Furthermore, retail

marketers should be careful to not present alternatives spanning more than 1.20m

horizontally, as this makes it more difficult for customers to maintain oversight (van

der Lee, personal communication, December 28, 2011).

Assortments can be both organized and unorganized. Kahn and Wansink

(2004) studied the effect of sortation on consumption in both small and large

assortments of jelly beans and pencils. Note that for the dependent variable, rather

than purchase, the number eaten and used was chosen. They found that for

disorganized assortments assortment size did not influence consumption. However,

when confronted with organized assortments people tended to consume less when

the assortment was smaller and more when the assortment was larger.

The organization structure can be labeled, in which case the amount of

categories in which the assortment is divided influence perceived variety (Mogliner,

Rudnick & Iyengar, 2008). Categories identify differences between items to

choosers that are less familiar with the assortment and do not (yet) have articulated

preferences. Furthermore, the presence of categories, even when they are irrelevant

for the products, allow people with little articulated preferences to be more satisfied

with the made choices. People with articulated preferences on the other hand are

more satisfied when choosing from large assortments without categories than from

small assortments or large assortments with categories. These findings can be related

to the findings described in chapter five showing that choosing can be both

confusing as well as a source for enjoyment. Though the presence of categories

mitigates the effects of assortment size on people with different amounts of

knowledge, on average both groups were less satisfied with their choice when made

from an assortment of 50 divided into ten categories than they were when deciding

from an assortment of five.

Categorization as noted before helps consumers with little knowledge make

sense out of large assortments. Furthermore, it can reduce time spent and cognitive


effort. However, categorization is much more effective when categories are

meaningful than when random alternatives are grouped. This is illustrated well by

the experiences of an artisan producing and selling unique fashion accessories with

floral motives (Flowersbyfarha, 2009). At first, all accessories were displayed in the

store organized by flower and ribbon types. This organization was chosen because

these characteristics were the theme around which the sub-collection was based

artistically. However, customers looked for the item based on color. To facilitate the

customer’s search the inventory was reorganized by color. This ‘rainbow’ display

received many compliments, especially for the individual works, but sales did not

increase much, as customers often commented that there was too much choice to

choose from. Only the most highly motivated would make the effort to sort through

the options. Therefore, the display selection was limited and further sub-categorized

based on accessory type. Then sales increased.

The search path of customers in this case is rather short. Most likely

customers first find the color that they like, secondly look for the type of fashion

accessory they are interested in and then attempt to select one suiting alternative.

The overview of which decisions customers make first, and which follow after that

is called the consumer decision tree (Zentes, Mirschett & Schramm-Klein, 2011). A

consumer decision tree primarily answers which product characteristics are

important to the customer and on which levels they are prepared to switch between

alternatives. For example, it was found that people buying canned peas were more

likely to switch to canned carrots than to peas conserved in a glass jar (van der Lee,

personal communication, December 28, 2011). The consumer decision tree should

play a central role in which products are presented together as well as which product

categories should be placed close to each other. Consumer decision trees also can

help decide where choice can be reduced and where choice should be increased.

Finally, and most importantly consumer decision trees offer one of the clearest

evidence based guidelines with respect to product presentation.

For grocery store items the consumer decision tree should be revised each

year to once every five years depending on product category innovation as well as

the speed at which consumer search patterns change (company documents of a large

international retailer, 2011). Furthermore, the decision tree differs per target group,

and therefore, assortments may need to be organized differently depending on

whether the store is located in an urban area, the relative amount of (young) families


as well as other demographics. Furthermore, consumer decision trees can help to

identify differences between category perceptions of customers with varying

amounts of knowledge, preference awareness and variety seeking tendencies.

Bishop (2010) reported that relatively few companies reported using

consumer decision trees. Only 6.1% of retailers with ten or fewer stores reported

always or most of the time using consumer decision trees, compared to 15% of

companies with 11-50 stores and 16.7% of chains with more than 50 stores. Survey

results from 50 leading and mid-range consumer packaged goods retailers show that

49% of these retailers use consumer decision trees (The Grocery Manufacturers

Association, McKinsey & Company & Nielsen, 2010).

Often a lack of customer decision making is apparent when evaluating

product presentation in retailers. For example, grocery stores often categorize meat

based on animal type, such as chicken or veil. However, customers are highly

unlikely to switch between biological and non-biological and therefore it would be

more convenient for all customers if the assortment was first categorized based on

biological versus other meat and only then based on type of meat. Retailers should

also be more aware when using product brand to structure their assortments. While

for shampoo people are likely to choose for a brand this is less the case for biscuits.

However, the C1000, a Dutch grocer, presents both biscuits and shampoo based on

brand. When trying to buy for example roze koek this gives the initial impression

that there is only one variety. It is not until after searching the full six meter shelf

that one can say with certainty that all alternatives are identified. A similar case may

be made for the presentation of make-up, where at the very least the less

knowledgeable consumer searches based on product type, color and price rather than

brand.

3. Other Moderating Policies

Next to the presentation of choice retailers have various other techniques at

their disposal. Interventions from store personnel can effectively limit choice and

help people to reach decisions. Personnel can guide customers to the right aisle, give

advice, make suggestions and provide additional information. Furthermore,

personnel can be used as a direct gate-keeper to the assortment. For example, as a

sales counter employee of a menswear tailor shop John (2009) presented no more


than four shirts at a time, and only when all are rejected took out another four. In this

manner most customers never saw most of the assortment. Similar conventions are

present at restaurants, where often no more than three or four specials are presented.

To a lesser extent a similar strategy is employed by many libraries and bookstores,

where more popular books are presented on special shelves, less popular books on

the normal shelves and least popular books are kept in storage or are available for

order.

Another manner in which choice can be mitigated is the inclusion of a

default option. This allows for easier decision making through reliance on the sellers

recommendation. Default options do not limit the assortment itself, but rather only

presents the full assortment to those that express interest in it. Default options in

retail can take many forms, such as the house wine in restaurants and car radios that

can be customized if the customer desires it.

There are also manners of sub-categorization that span across product

categories and which can be used without placing the products together. An example

of this is labeling. Currently many forms of product labeling exist that set a product

apart from other products by adding an easily identifiable product attribute. There

are labels indicating that the product is fair-trade, biological, organic, a healthy

choice and others. Moreover, sales promotions and discounts can also be seen as

labels signaling information to customers that may make it easier for the customer to

differentiate between products and justify their decision.

The perceived risk associated with the choice can be reduced by the

existence of product trials, such as test drives and product stands in grocers. Another

manner in which risk can be reduced is return policy. More lenient policies make it

easier for customers to correct mistakes and thus less important to choose right.

Unfortunately, no research regarding the mitigating effect of return policies on

decision making and assortment variety in the field of store-retailing have been

found.

As variety for most commonly purchased products is large, and retailers only

have limited space retailers have to decide on what assortments to offer. Ideally the

chosen assortment jointly optimizes the amount of customers as well as their

spending, thus maximizing profits. As this chapter has discussed variety has various

drawbacks for the retailer, and as the previous chapters have discussed various

drawbacks for the customers as well. However, larger assortments attract more


attention and customers have expressed preference for larger retailers carrying larger

assortments.

Presentation can influence purchasing behavior, can help to increase sales,

and it is important to be aware that presentation affects the perception of variety.

Broader aisles induce customers to seek less variety, as do organized small

assortments. However, unorganized assortments increase decision difficulty

especially among less knowledgeable customers. Though assortments with many

choices attract attention, customers may decide more easily when presented with

fewer. Furthermore, presentation should emphasize differences to minimize

preference uncertainty and indecision. Finally, consumer decision trees, sales

personnel intervention, default options and effective return policies can mitigate

indecision effects of the assortment size presented.

Study 1: Attitude Towards Choice 62

8. Study 1: Attitude Towards Choice

1. Study Design

In this study both American and Dutch respondents were asked regarding

their attitude towards choice in supermarkets. Attitude for the purpose of this study

is defined as “a learned predisposition to respond in a consistent evaluative manner”

(Ostrom, 1969, p.12) and the tripartite theory was used to sub-divide it in three main

components, namely affective, cognitive and behavioral. The affective component

relates to one’s feelings, the cognitive component includes both perceptions and

believes, and the behavioral component refers to the actions taken.

The main objective of this survey was to identify similarities and differences

between American and Dutch attitudes. For this purpose the following hypotheses

were developed:

H1: American and Dutch respondents’ attitudes towards choice differ on all

attitude components.

H2: The reasons provided by American and Dutch respondents’ for their

attitudes towards choice differ.

H3: The attitude component scores are related to gender and age.

H4: The three attitude components are positively related.

The affective component is operationalized through a self-reported measure

of liking for the amount of choice in stores, the behavioral through whether or not

the respondent had complained about the offered assortment sizes and the cognitive

by asking the respondent about his or her believes regarding the benefits of choice.

The following questions were formulated:

• Why do or don't you like the amount of choice in stores?

• Can you give an example of when you have complained or wanted to complain

about a store being too big and/or offering too much choice?

• Do you believe that you benefit from the amount of choice available? Why or

why not?

2. Analysis Procedure

First of all, sample composition is described, with specific attention to

nationality, gender and age. Cross-tabulations were made, using the χ2 tests for


independence to determine whether or not the gender distribution differed between

the two countries. To test for age differences between the two nationalities and

gender, as well as for possible interaction effects a two-way ANOVA test was

conducted.

To test the hypothesis that people in the two countries have the same attitude

towards choice the answers for each question were scored. First, all answers were

read and coded into groups based on the answer given. For the affective component

four groups were made, namely those that did not like the amount of choice, those

that did not like the amount of choice with specific mentioning of being offered too

much choice, those that did like the amount of choice and those that indicated that it

depended on either the store or the product. For the behavioral component three

groups were made, namely people that had not complained, people that had not

complained but did express complaints in their response and those that had

complained. For the cognitive components the respondents were also grouped in

three groups, namely those that believe they benefit, those that do not believe they

benefit and those that are unsure whether or not they do or indicated that it is context

dependent.

Secondly, the answers were read again and common themes were identified

and coded, grouping them where possible. These were then compared to the

concepts provided by the theory discussed earlier in this thesis. Reasons for liking

choice identified in previous research are the possibility to match preference,

enjoyment of the choice process, variety seeking, increased confidence in the made

choice, finding everything at one location and the importance of having freedom of

choice. Reasons for disliking choice are cognitive overload leading to confusion,

doubts, increased mistake probability and indecision and decreased motivation.

Previous research also identifies several moderators for choice, most notably

articulated preference, satisficing, familiarity and avoidance.

To ensure data quality during coding cases with non-sense and uninformative

answers were deleted. After the coding, to determine the quality of responses both

the amount of coded responses and the amount of reasons were looked at in

comparison to the amount of answers given. For the behavioral component rather

than comparing the amount of reasons to complain to the total number of

respondents it was compared to only those that indicated to have or have wanted to

complain.


After all questions were coded various analysis were conducted. First of all,

χ2 tests for independence were used to determine whether or not there are significant

between country differences between attitude component scores. Secondly, χ2 tests

for independence were used to determine whether or not gender differences existed

with regard to attitude component scores, both for the complete sample as well as

within the two countries. Thirdly, age differences between the component scores

were tested for using a one-way ANOVA. When the ANOVA test was significant a

LSD post hoc test was used to identify significant group differences.

Secondly, the reasons given for the attitude components were analyzed. The

distributions for both countries are reported jointly using a Pareto chart. And χ2 tests

for independence were used to determine whether or not there are significant

between country differences in the most frequent reasons given (reasons with

expected cell counts under 5 were excluded). To gain more insight in the factors

underlying the attitude components it was chosen to illustrate the main themes with

quotes from the answers (translated to English), indicating the respondent’s

nationality, age and gender. Additionally, the reasons given were split by component

group.

For the relationship between the attitude components it was decided to look

both at the frequency that people had all negative and all positive component scores

(note that the behavioral one was scored in the opposite direction from the other

two). As the ranking of the liking groups is unclear (should ‘no’ and ‘too much’ be

grouped or treated as opposite extremes) it was decided to treat the component

scores as categorical rather than ordinal variables. The variables were recoded into

dummies (consisting of 0 and 1) and phi (mean square contingency) coefficients

were calculated. The square of this coefficient is equal to the two-by-two chi-square

test statistic divided by the sample size. The phi-coefficient, like Pearson’s r, will

have a value between -1 and 1 if the variables have an equal distribution; otherwise

the minimum and maximum values are lower. These relationships were checked for

cross-cultural reliability by additionally generating them for both countries

separately and reporting those that are related in both samples.

For all tests and assumption checks a 5% significance threshold was used.

For all χ2 tests the assumption of minimum expected cell count of five was checked,

and categories were regrouped where necessary. For the ANOVA the assumption of

independence was met due to the study design. The normality of age within each


sub-group was tested for using both the Kolmogorov-Smirnov statistic as well as Q-

Q plots. The assumption of homogeneity of variance is tested for using Levene’s

test.

3. Sampling Procedure and Sample

Two samples were obtained, one of American respondents and another of

Dutch respondents. For the Dutch respondents the survey was translated from

English into Dutch. The questionnaire was distributed through two online panels,

and for the American respondents a 50/50 gender quota was used. Furthermore, only

one reply per ip-address was allowed to reduce the chance of one respondent

answering multiple times. The survey was started by 135 Americans and 122 Dutch,

of whom 127 Americans and 118 Dutch completed the survey (a completion rate of

94 and 97% respectively). Another six Americans and four Dutch were excluded

from the analysis because of incomplete or inappropriate answers.

The final sample size was 236, of whom 42% were men. The Dutch sample

had a significantly different gender distribution than the American one (χ2(1,

N=233)=4.52, p=.034). In the American sample 49% was male, and in the Dutch

sample 35%. The average age in the sample was 38.3 (SD=15.1, youngest=14,

oldest=73) and did not differ significantly based on country or gender. Furthermore

no interaction effect was found between these two and age.

On average respondents took 2:07 minutes to answer the three questions. For

the affective component there were relatively many answers that could not be

grouped (22%), the average amount of reasons given per respondent was .9. For the

cognitive component there were few answers that could not be coded (3%), and

there on average was one reason given per respondent. Finally, for the behavioral

component there was only 1 answer that could not be grouped (<1%) and on average

.6 reasons were given per respondent indicating to have or have wanted to complain.

4. Results

4.1 The Affective Component

The distribution of liking of the amount of choice in stores can be seen in

table 3. Overall the majority of people liked the amount of choice (64%) another


19% indicated that they did not of whom 11% indicated there was too much choice.

The Dutch sample had a significantly different distribution from the American one

(χ2(3, N=185)=13.83, p=.003). They indicated less often that they disliked the

amount of choice and more frequently that there was too much choice. There were

no significant gender differences between nor within the countries for liking the

amount of choice offered in stores.

Table 3: Distribution for ‘liking’ of the amount of choice in stores.

Age was significantly related to liking, F(3, 179)=3.806, p=.011. Those that

did not like the amount of choice on average were 27.5 (SD=12.8), those that did

like the amount of choice were on average 37.2 (SD=14.5), those that said it

depended on average were 40.0 (SD=15.2) and those that believed there was too

much choice were on average were 44.5 (SD=15.3) years old. Those that did not like

the amount of choice were significantly younger than all others (mean difference

with ‘depends’=-12.3, p=.010; mean difference with ‘yes’=-9.5, p=.023; mean

difference with ‘too much’=-16.8, p=.001). Those that felt there was too much

choice were significantly older than those that did not like choice and also older than

those that do (mean difference=7.3, p=.048).

Reasons why people liked or disliked choice were very closely related to the

amount of choice they were offered. Most commonly they cited their perception of

variety (17%) and the large amount of choice offered (13%; coded as ‘lot of choice’)

as basis for their affect. Another common reason cited was the availability of the

wanted product (10%), the fit of the offered options to what was wanted (9%) and

the possibility to get everything at one store (3%). 5% Of the respondents indicated

to like choosing from many options and another 5% indicated to have trouble

making decisions when many varieties were available. Also the assortments quality

and price variety were often cited, with people indicating that much choice allowing

US NL total

too much 6 (6%) 14 (18%) 20 (11%)

yes 71 (66%) 47 (61%) 118 (64%)

no 13 (12%) 1 (1%) 14 (8%)

depends 18 (17%) 15 (19%) 33 (18%)

total 108 (100%) 77 (100%) 185 (100%)


them to get more value for money, cheaper products or the opposite saying for

example that: “It seems there is a greater significance on creating variety than

producing quality products” (American, 21, male).

Figure 12: Pareto chart of reasons for liking/disliking the amount of choice in stores.

For the main eight reasons there was no significant difference between Dutch

and Americans on the frequency they were cited, χ2(7, N=165)=12.4, p=.088.

However Americans tended to report more overt liking for choosing from variety

and also reported more indecision, as well as more diverse benefits and negative

feelings associated with having choice. For example, one American said that “Too

many, and too many times I have picked up the wrong thing because it was low this,

or lite that, or just not the regular brand. I think there are too many choices there on

the shelves these days. If you need special food then go to a special food store...”

(48, male).

When looking at the less frequently cited reasons especially Dutch indicated

that the higher amounts of choice enabled them to compare products better. Another

common theme in the Dutch sample was that people related the amount of choice in

stores to the perceived lack of variety in stores, often complaining that the same

chains were present everywhere and that there were too few original, independent

stores.

0%

25%

50%

75%

100%

0

5

10

15

20

25

30

35

40

cummulative percentage




frequency

frequency

frequency

frequency

American Dutch Cummulative percentage


Grouping the reasons given by whether or not the amount of choice was

liked, showed that those that were unsatisfied with the amount of choice offered

most often indicated to want more (22%), indicated that what they were looking for

was often unavailable (17%), disliked that they had to visit multiple stores (17%)

and found that there were too many of the same stores (11%) (see Appendix C for a

full cross-tabulation). Respondents that indicated that were ambiguous about liking

the available amount of choice gave similar reasons to those that did not like choice,

namely 26% wanted more choice, 16% found that products they wanted were

unavailable, 8% indicated to like having everything they wanted in one store and

another 8% indicated to that there were too many chain stores.

The reasons given by those that like the amount of available choice were the

appropriate amount of choice offered (21%), the provided variety (20%), the fact

that all products they want are available (11%) and that the available products fit to

what they want (11%). The respondents that feel there is too much choice reported

indecision (36%), negative feelings, for example feeling overwhelmed (14%), the

fact that there is a lot of choice (14%) and that the amount of choice negatively

impacts their decision quality (7%).

4.2 The Cognitive Component

Table 4: The believed benefits of having choice in stores.

The distribution of the believed benefits of the amount of choice in stores can

be seen in table 4. Overall the majority of people believed having choice benefitted

them (68%) another 11% were unsure and 21% did not believe so. The Dutch

sample had a significantly different distribution from the American one (χ2(2,

N=228)=11.30, p=.004). Dutch indicated much more often than Americans to not

believe they benefitted from the amount of choice (31% and 13% respectively) and

were less likely to believe that they did (59% and 76% respectively). The amount of

US NL total

no 15 (13%) 34 (31%) 49 (21%)

unsure 13 (11%) 11 (10%) 24 (11%)

yes 90 (76%) 65 (59%) 155 (68%)

total 118 (100%) 110 (100%) 228 (100%)


people that were unsure did not differ much between the Netherlands and the United

States (10% and 11% respectively). Belief in benefit was not significantly related to

gender between nor within the countries.

Age was significantly related to believed benefit, F(2,223)=3.083, p=.048.

Those that did not believe they benefit were 41.5 (SD=14.6), those that said it

depended on average were 32.3 (SD=15.5), those that did like the amount of choice

were on average 37.5 (SD=14.9) years old. Those that did not believe they benefit

were significantly older than those that indicated an ambiguous belief (mean

difference=9.2, p=.015).

Figure 13: Pareto chart of believed benefits of choice.

Respondents from both countries indicated that the main reason for believed

benefit was that it provided them with cheaper products, either through larger price

variety or through competition. A second reason was that they believed that as the

amount of choice increases at least one of the alternatives would be closer to what

they want, like or need. Furthermore, many indicated to benefit from having variety,

for example because: “you don’t have to buy the same product each time” (Dutch,

17, female). Also the ability to compare and reach a better decision were cited as

reasons for benefit. The frequency the six most common reasons were cited differed

significantly between the Netherlands and the US (χ2(5, N=140)=13.6, p=.018).

Americans were more likely to indicate that more choice allowed them to buy

0%

25%

50%

75%

100%

0

10

20

30

40

50

60





frequency

frequency

frequency

frequency

USA NL Cumm


something closer to what they wanted and Dutch were more likely to indicate that

increased choice made it easier to compare products.

Other perceived benefits of choice were that it allows you to visit less stores

and thus save time and gas, can make less common products easier to find, and gives

one the possibility to decide for oneself. Having choice is also considered by one

respondent as modern. There was also a multitude of reasons why people did not

believe they benefit from choice, such as choosing taking more time, increased

spending, shopping less, indecision and specific products being more difficult to find

among a multitude of others.

The most commonly provided reason why people do not believe they

benefitted were lack of variety (67%) and the most common reasons given by people

that do believe they benefit was that products were cheaper (29%) and 16%

indicated that choice allows them to pick products that fit well with what they want

(see Appendix C, table 9 for a complete cross-tabulation).

4.3 The Behavioral Component

The distribution of the believed benefits of the amount of choice in stores can

be seen in table 5. The majority of people have never complained (85%), 11% of

these however did indicate to have reasons to complain. 15% of respondents have

complained about stores being too big and/or carrying too many items. The Dutch

sample did not significantly differ from the American one (χ2(2, N=235)=5.389,

p=.068). Americans tended to be less likely to express having no reasons to

complain (68% vs. 81%). There were no significant gender or age differences

between nor within the countries and whether or not people had complained.

Table 5: Amount of respondents that did, did not and did not but indicated reason to complain.

US NL Total

No 82 (68%) 92 (81%) 174 (74%)

No, but 17 (14%) 8 (7%) 25 (11%)

Yes 22 (18%) 14 (12%) 36 (15%)

Total 121 (100%) 114 (100%) 235 (100%)


Most of the respondents had not complained and saw no reason to complain

about having a lot of choice. Especially not because one can limit the amount of

aisles one walks through (mentioned by Americans three times) or avoid large store

formats completely (mentioned by one Dutch and one American respondent). Four

American respondents indicated that familiarity with the store decreased the

confusing and overwhelming effects of choice.

Reasons given for complaining included difficulties finding a product

(mentioned six times by Americans and once by a Dutch person), loss of oversight

(mentioned five times by Dutch respondents), indecision (mentioned four times, of

which three were times by American respondents). Americans gave various other

reasons to complain. Namely large stores being overly crowded (mentioned thrice),

the amount of choice being intimidating (mentioned thrice), products being

unavailable (mentioned twice) and confusion (mentioned once). (Again a cross-

tabulation of the reasons, and mediators, grouped by whether or not the respondent

had complained can be found in Appendix C, table 10).

4.4 Attitude

Relating the answers on the affective, cognitive and behavioral components

provides some insight into attitude towards choice. A large group (42.8%, 42% of

Dutch and 43% of Americans, no gender differences) scored positively on all three

aspects saying to like, benefit and not complain about the amount of available

choice. And 5 (3%) of the respondents had a completely negative attitude towards

choice (signified by complaints, no perceived benefit and indicating they found there

was too much choice).

Looking at specific respondent profiles it was found that people that had

complained were less likely to like choice, phi(184)=-.228, p=.002, and more likely

to believe that there was too much choice, phi(184)=.284, p<.000 (see Appendix C,

table 11 for a comprehensive overview of all relationships). Also those that had

complained were more likely to be unsure about the benefits of choice,

phi(227)=.231, p<.000, and less likely to believe they benefit from having choice,

phi(227)=-.214, p=.001. People that had not complained, but gave reasons why they

would want to were more likely to indicated that their liking for choice depended,

phi(184)=.151, p=.041. Respondents that had not complained and gave no reasons


why they may want to were less likely to say that their liking of choice depends,

phi(150)=-.171, p=.037, and more likely to like the amount of choice in stores,

phi(150)=.190, p=.020.

Respondents that like the amount of choice in stores believe more often that

they benefit from having choice, phi(181)=.364, p<.000, and were less often unsure

about their benefit, phi(181)=-.232, p=.002, and also less often believed that they did

not benefit, phi(185)=-.229, p=.002. Respondents that did not like the amount of

choice were less likely to believe they benefit, phi(228)=-.138, p=.038. Respondents

that believed there was too much choice were less likely to believe they benefit from

choice, phi(181)=-.281, more likely to be unsure about the benefits, phi(181)=.168,

p=.024, and more likely to believe they did not benefit, phi(185)=.168, p=.023.

When splitting the file on nationality, and looking at the associations

between the attitude components only three relationships were found to be present

for both (tables containing all relationships per country can be found in Appendix

C). Namely, respondents from both countries that indicated a believed benefit from

choice were more likely to like the amount of choice in stores, phi(75)=.449, p<.000

and phi(106)=.299, p=.002 for Dutch and Americans respectively. Those that felt

there is too much choice are more likely to have complained, phi(76)=.325, p=.004

and phi(108)=.289, p=.002 for Dutch and Americans respectively. Finally, those that

had complained were less likely to believe they benefit, phi(109)=-.248, p=.009 and

phi(118)=-.226, p=.014 for Dutch and Americans respectively.

Thus, the hypothesis that the components are positively related was accepted

for the affective and cognitive and affective and behavioral relationships, because

those that liked choice more were more likely to believe they benefit and were less

likely to complain and those that believed there was too much choice were more

likely to believe there was no benefit of having choice and were more likely to have

complained. There was also support for a positive relationship between the cognitive

and behavioral components as those that believed they benefit from having choice

were less likely to have complained. These relationships between components were

similar for Dutch and Americans.


5. Discussion of Results and Methodology

The results of this study support H1. Americans were more likely to believe

that there was too little choice, more likely to believe that they benefit and more

likely to indicate having reasons to complain, though they were no more likely than

Dutch to have complained. Dutch more often believed that there was too much

choice. Simultaneously it was found that near half of the respondents of both

nationalities had a solely positive attitude towards choice.

The reasons provided by American and Dutch respondents’ for their attitudes

towards choice differ when looking at the cognitive and behavioral components.

Reasons given for affect did not differ significantly, thereby providing only partial

support for H2. The reasons given by the respondents confirmed those present in the

theory, namely they like choice because it increases the chance and extent to which

preference are matched and reduces the amount of stores one needs to visit.

Furthermore, the respondents were variety seeking, valued being able of choosing

for themselves, and felt that having more choices improved their decisions. Also

some of the reasons for disliking found in the literature, most notably confusion,

indecision and decreased motivation. Also two moderators were identified namely

avoidance and familiarity.

Dutch had an especially negative attitude towards the presence of chain

stores and often put stress on there being variety of interest to others. Americans on

the other had more often reported to prefer going to smaller stores and reported more

negative feelings as a reaction to having much choice.

With respect to H3, no support was found for gender differences. For age

differences in attitude limited support was found. Young people were more likely to

think that they benefitted from choice and that there was not enough choice offered

to them. Older people were less likely to believe they benefitted and more likely to

believe that there was too much choice.

Supporting H4 the three attitude components were positively related. Also

looking at the countries separately support for this hypothesis was found. However,

reflecting the differences in component scores and reasons the relationships between

the components were rather different between the countries.

There are some limitations to this research, first of all the attitude

components were all measured with only one question. As coding often proved

difficult it may have been better to split the questions between for the attitude score


and another question asking for the reason. However, this would have not revealed

that there is a great difference between people that do not like the amount of choice

because there is too little and those that believe there is too much. Furthermore, as

the online panels used placed a limitation on the amount of questions that could be

asked, namely five, splitting the questions was not possible.

Also the validity and reliability of the questions can be questioned as the

reasons given for the affective component are often perceptions and beliefs.

Furthermore, the behavioral question merely covered one aspect of behavior towards

choice, for example omitting whether or not people avoided going to large stores.

Moreover, complaining can be interpreted in two distinct manners. Namely,

complaining as in privately or publicly expressing a negative evaluation, but also as

the voicing of this opinion directly to a representative of the retail chain.

Both the samples are relatively small (leading to a relatively large, 10%,

confidence interval for each country). The sampling method was non-probability and

there are also some downsides specific to the use of panels, most notably the high

self-selection bias and the presence of professional respondents, both which reduce

the validity of generalizations. Furthermore, the effective sample size for reasons

given by component group and the sample size of reasons given for complaints in

general are even smaller.

The questionnaire was translated to ensure the Dutch respondents were able

to understand the question correctly and lower the barrier to answering accurately

and elaborately. However, manners of expressing the same idea may be different

between the Netherlands and the United States leading to incorrect grouping of

reasons. Moreover, all component scores are heavily dependent on the acceptability

of expressing certain believes. For example, whereas there has been much public

attention for the rise of chain retailers and the negative consequences of this for local

retailers in the Netherlands, this may not have been the case in the United States.

All questions were related to the amount of choice currently offered by stores

and thus only relative conclusions can be drawn. However, as described in chapter 2,

Americans are faced with more choice and variety than the Dutch are. Because of

this the finding that Dutch more often feel that there is too much choice, whereas

Americans more often feel that there is too little shows that Americans in fact desire

more choice than the Dutch. These ideas, among others, are further examined in

study 2.

Study 2: Choice and Satisfaction 75

9. Study 2: Choice and Satisfaction

1. Study Design

Study 1 found that though literature research indicates that stores are bigger

in the USA and customers are faced with more choice Dutch respondents more often

felt that there is too much choice. Americans, on the other hand, are more often

dissatisfied with the assortment sizes because they are too small. What underlies this

difference in satisfaction with the amount of choice offered? And to what extent do

findings from American studies on choice translate to the Dutch?

The difference in the evaluation of the amount of choice assortments offer

may be related to the perceived assortment breadth as well as the customer’s self-

exposure to choice and his or her capacity to cope. Dutch respondents are

hypothesized to evaluate the assortment size less favorable than Americans because

they perceive higher assortment breadth. Furthermore, they have a more negative

attitude towards having much choice due to having more difficulties deciding and

higher self-exposure to choice. These difficulties in deciding, the higher perceived

assortment breadth and the higher self-exposure additionally make Dutch people less

satisfied with their choices than Americans are. As the theoretical background shows

the customer’s knowledge and the importance of the decision affect both the

perceived category breadth and the size of the choice sets created these two factors

are controlled for with special attention to non-linear effects. Based on this the

following hypotheses are tested:

H1: Dutch give lower assortment evaluations than Americans.

H2: Assortment evaluations are based on the same underlying factors in the

Netherlands and in the United States.

H2a: Assortment evaluations are related to perceived category breadth

similarly in both countries.

H2b: Assortment evaluations from both nationalities decrease as they are less

satisfied with their choices.

H2c: In both countries assortment evaluations depend on the customer’s

knowledge and the decision importance.

H3: Dutch are less satisfied with the choices they make than Americans are.

H4: Satisfaction with the made choice is based on the same underlying

factors in both countries.


H4a: People that have more difficulties choosing are less happy with their

choices.

H4b: Dutch are more likely than Americans to have trouble deciding.

H4c: People that choose from larger assortments or choice sets are less happy

with their choices.

H4d: People that choose from larger assortments or choice sets have more

difficulties choosing.

H5: People making more important decisions have more trouble choosing.

H6: People making more important decisions create larger choice sets.

H7: People who have more knowledge have less trouble deciding.

H8: People who have more knowledge perceive larger assortments.

H9: People who have more knowledge smaller choice sets.

The second part of this study has a distinct objective: the identification of

Dutch perceptions of, reactions to and attitude towards choice in retailers. Rather

than testing hypothesis this analysis takes an exploratory approach including factors

identified in the literature review. The first focus is on describing the want for

choice, the relationship between choice and identity and the perceived benefits of

choice. The latter will complement the qualitative approach of study 1 with a more

quantitative one, remedying the validity issues and allowing for the testing of

relationships between perceived benefits and age, gender and urbanization. A second

focus of the research is identifying how variety in assortments is perceived, to what

extent people are influenced by presentation and how this relates to assortment

evaluation. Thirdly, the extent to which choice in retailers gives rise to drawbacks is

analyzed in relation to decision satisfaction and fourth post-purchase satisfaction is

investigated.

2. The Instrument

Many of the constructs of interest are highly dependent on the choice

situation one is in. Furthermore, to test the hypotheses it is crucial that there is some

degree of deliberate decision making. Therefore, at the start of the survey the

respondents were asked the following (see Appendix D for a copy of the survey):

“Please remember the last time that you were in a store choosing

between two or more varieties of the same product (for example between


different shirts, snacks or different brands of detergent). Answer the following

questions about this experience.”

This was followed by two questions asking for some insights in the memory,

namely: ‘What did you want to buy?’ and ‘How long ago did this happen?’ One

question asking for the extent to which the respondent agreed with the statement ‘I

am satisfied with the choice I made.’ using a six-point Likert scale. Difficulties

choosing were prompted for by two questions, one asked whether the respondent

had considered either not buying the product or postponing the decision and the

second asked the respondent to complete the sentence: ‘Making the decision was...’

with one of five answer possibilities ranging from ‘very easy’ to ‘very difficult’.

In study 1 four distinct assortment size evaluations were found ‘no’,

‘depends’, ‘yes’ and ‘too much’. However, this raised questions regarding whether

or not those that found there sometimes was too much choice should be regarded as

an extension of the group that was satisfied or dissatisfied with the amount of

choice. Therefore, in this study it was chosen to for the extent to which the

respondent agreed with the statement: ‘I was satisfied with the offered amount of

choice.’

Perceived category breadth was operationalized by asking for the

remembered amount of alternatives offered, and the self-exposure to choice was

measured through the amount of alternatives considered. Finally, the two moderators

of choice included in this research were asked for through the question to which

extent the respondent agreed with the statements: ‘For this product it is important to

choose the right one.’ and ‘I knew a lot about the product.’

Dutch respondents were asked additional questions, mainly six modality

Likert scale based (Appendix E for a complete overview). The questions were

grouped in ten categories. These were presented in the following order: memory

details, satisfaction and indecision, assortment size and variety, choice set size and

variety, the decision experience, involvement, post-purchase behavior and

satisfaction, purchase environment and attitude, culture and finally background.

Within the categories question order was randomized to reduce structural biases as

much as possible. For the same reason questions regarding satisfaction were asked

early on.


3. Sampling Procedure and Sample

For the cross-country comparison two samples were obtained, one of

American respondents and another of Dutch respondents. American respondents

were recruited through an online panel where a 50/50 gender quota was used. The

Dutch respondents, who completed a more extensive survey, were recruited through

social media, mainly Facebook and LinkedIn, where a snowball method was

employed. The questionnaire was distributed spring 2012. On average the American

respondents took 1:29 minutes to answer the ten questions.

The survey was started by 206 Americans and an unknown number of Dutch,

of whom 190 Americans (92% completion rate) and 157 Dutch completed the

survey. Due to some respondents giving inadequate responses the final sample size

was 340. Of the Americans 51% was male, compared to 61% of Dutch. Therefore,

weighting was applied homogenizing the Dutch gender distribution to 50% of men,

and a weighted sample size of 188. The average age in the sample was 39 (SD=15,

youngest=15, oldest=81) and did not differ significantly between the Dutch and

American sample. Women were significantly younger than men (mean=34.5,

SD=14.5 and mean=42.7, SD=13.9 respectively), t(365)=-5.5, p=<.000.

Most of the Dutch respondents (43%) live in small cities of 20,000-100,000

inhabitants, 25% lives in towns smaller than that or in rural areas, and the remaining

33% lives in cities larger than 100,000 inhabitants.

4. Analysis Procedure Cross-Cultural Study

To start seven respondents who had not named a product were deleted from

the data. The remaining responses were then recoded into groups based on retail

type: food, fashion, electronics and other. The latter contains products such as paint,

helmets, pens, detergent, cosmetics and hobby items. Secondly, the numeric

variables assortment size and the size of the choice set were screened for outliers.

For assortment size numbers between 10 and 20 were recoded as 9 (there were no

nine’s mentioned yet), numbers between 21 and 50 were recoded as 10 and numbers

higher than 50 as 11. For choice set size there were 11 extremely large observations,

namely three of 5, three of 6, one of 8 and 4 of 10. As none of these are

unrealistically large it was decided to keep them as they are.


After the data set was cleaned and all variables appropriately recoded, a

missing value analysis was carried out. Three variables had more than 2% missing

values. The assortment size had 19 (5.6%) missing values, knowledge 60 (17.6%)

and satisfaction 62 (18.2%). The latter two are due to troubles with the online panel

technology for the American sample.

A comparison of the two samples was made focusing on gender distributions

per nationality. Based on this it was decided to weight the Dutch female respondents

with a factor 1.5 (compared to 1 for all others) in order to obtain a 50-50

distribution. Also age was looked at, and a two-sample independent t-test was

conducted to ensure that there were no significant age differences.

To test the hypotheses mentioned before, several tests were conducted.

Where appropriate, ANOVA tests and t-tests were used to analyze group differences

in continuous variables such as age, assortment size and choice set. When nominal

and/or categorical variables were crossed χ2-tests were used. For all of these separate

tests were conducted for the two countries and only if both were significant an

overall test was conducted, unless otherwise stated. All appropriate assumptions

were checked as in study 1, and variables were regrouped where necessary. Only

when no regrouping was possible expected cell counts of less than 5 were accepted,

but only if there were no more than two occurrences within one two-way table.

5. Recalled Choices

To interpret what the recalled choices can tell us about assortment size

evaluation, choice satisfaction and choice difficulty a thorough understanding of the

memories is crucial. People most frequently (39%) recalled deciding over food.

Apparel decisions were recalled by 24%, electronics by 12% and other products by

25%. There were no significant differences between the countries (see Appendix F,

table 14). The product type was significantly related to gender, with women less

often remembering situations involving technology, χ2(3, N=366)=23.3, p<.000 (see

Appendix F, table 15). Furthermore, product group was significantly related to age

in both the Netherlands and the USA, F(3,174)=4.504, p=.005 for American and

F(3,181)=6.595, p<.000 for Dutch respondents. USA respondents recalling food

choices were on average 40.2 (SD=13.6), those choosing fashion 37.3 (SD=13.9),

those deciding upon electronics 39.6 (SD=8.8) and those deciding on other types of


products 38.1 (SD=14.0). Dutch respondents choosing food were on average 33.5

(SD=14.6), those deciding on fashion 43.6 (SD=16.0), those deciding on electronics

45.8 (SD=12.7) and those deciding on other products 39.1 (SD=15.6). Product group

was not significantly related to the amount of options considered. For American

respondents product group was related to the store’s assortment size, F(3,

169)=2.545, p=.058. Respondents reported remembering significantly fewer options

when choosing a fashion item than when choosing an item classified as ‘other’

(mean difference=1.9, SE=.7).

There were significant differences between the nationalities for the age of the

memory, χ2(3, N=372)=25.3, p<.000. Of the American respondents 63%

remembered a decision made during this week and another 21% a decision last

week. Only 12% recalled something from last month and 4% from longer ago.

Dutch respondents took experiences that were less recent, with 38% recalling

something that happened this week, 29% a decision from last week, 23% a decision

from last month and 10% recalling a decision from longer ago. Dutch women were

more likely than Dutch men to recall memories from this week (50.5% versus

26.0%), χ2(4, N=189)=14.4,p=.006. The age of the recalled memory was related to

the age of the respondent, F(5, 363)=9.896, p<.000. Respondents recalling a memory

form this week were on average 34.8 (SD=13.8), those recalling from last week 40.1

(SD=15.0), those recalling from last month 41.4 (SD=13.7), those recalling from this

winter 48.4 (SD=10.4) and those recalling a product choice form longer ago 58.4

(SD=14.8) years old. In addition, memories concerning electronics and other

products were significantly older than recalled choices about food and apparel, χ2(6,

N=368)=65.0, p<.000 (see Appendix F, table 16).

There was no significant relationship between the age of the memory and the

satisfaction with the made choice and assortment evaluation. However, for Dutch

respondents choices recalled from longer ago were perceived as more difficult χ2(9,

N=191)=17.5, p=.042 (see Appendix F, table 17). Furthermore, for Dutch

respondents were more likely to have considered postponing the decision when the

recalled memory was older, χ2(3, N=185)=8.3, p=.042. Respondents that recalled

choices from this or last week were relatively unlikely to have considered

postponing the decision (22% did so). Respondents remembering decisions from last

month had a 40% chance to have considered postponing and 47% of respondents

recalling memories from longer ago had considered postponing the decision.


Looking at the importance of the decision made Americans indicated that

their recalled decisions were more important than did the Dutch respondents, χ2(5,

N=370)=48.6, p<.000 (see Appendix F, table 18). This difference was most striking

when looking at the amount of people indicating that they to some extent disagree

that for the chosen product it is important to choose the right one. Only 5% of

Americans indicated that it was not that important to choose the right one compared

to 29% of Dutch. Older respondents indicated less perceived importance than

younger ones, F(5,359)=3.333, p=.006. Respondents that indicated that the choice

was highly important (mean=42.0, SD=14.9, N=117) were significantly older than

all participants slightly disagreeing (mean=33.8, SD=12.7, N=25), mostly

disagreeing (mean=32.1, SD=16.2, N=20) and completely disagreeing (mean=32.5,

SD=14.2, N=19) that it was important to choose the right product. Decisions made

about food were rated significantly less important than other decisions concerning

the other product categories χ2(9, N=366)=36.9, p<.000 (see Appendix F, table 19).

Dutch are significantly less likely to believe they know a lot about the

product in question than Americans are, χ2(5, N=312)=85.3, p<.000 (see Appendix

F, table 20 for a full cross-tabulation). Half (50%) of the Americans completely

agreed with the statement that they knew a lot, 30% mostly agreed and 17% slightly

agreed. Of the Dutch respondents 12% completely agreed, 22% mostly agreed, 25%

slightly agreed, 21% slightly disagreed, 14% mostly disagreed and the last 5%

completely disagreed. For Dutch respondents knowledge was positively related to

the respondent’s age, F(5, 177)=1.007, p=.008. Those that believed to know a lot

were older (mean=42.7, SD=15.1) than those who did not (mean=34.5, SD=16.2).

No significant relationships with gender, age of the memory or product type were

found. Product knowledge and importance of the choice were significantly

positively related, χ2(16, N=314)=97.3, p<.000 (see Appendix F, table 21).

In addition, Dutch respondents were asked to indicate if there was a specific

reason why they had to choose between alternatives. Analysis of the given answers

shows that 21 respondents were attempting to manage expenditure, eight were

looking for the best value for money, five needed to match specific criteria and four

found that their preferred option was unavailable. Thirteen respondents indicated

that they had to decide between multiple liked options, nine were faced with

multiple options while being uninterested in that much variety, six lacked experience

in choosing the product, two were trying to find a less complicated product than on


average was offered and another two were seeking variety from their usual choice.

Eight respondents indicated that they made a choice between price and values, either

buying biological or fair-trade products.

6. Results Cross-Cultural Comparison

6.1 Assortment Evaluation

The present study reproduces the earlier result that Dutch are less satisfied

with the amount of choice offered than Americans, χ2(3, N=309)=20.2, p<.000 (see

Appendix F, table 22). Half of Americans (52.8%) indicate to have been completely

satisfied with the amount of choice offered and another 31.2% being mostly

satisfied. Of the Dutch respondents, however only 28.8% was completely, 39.1%

mostly and 18.5% was slightly satisfied. Evaluation did not significantly differ based

on product type, gender or age.

There was no significant difference between the remembered assortment

sizes of Dutch and Americans, however Dutch tended to remember more

alternatives, t(347)=-1.66, p=.099. Overall, the respondents indicated remembering

5.45 alternatives (SD=3.10), Americans on average remembered 5.18 alternatives

(SD=3.23) and Dutch remembered 5.73 (SD=5.45). A one-way ANOVA showed no

support for a relationship between assortment size and assortment evaluation neither

for the overall sample nor for the countries separately. Thus, though Dutch tended to

tended to remember slightly larger assortments (mean=5.7, SD=2.9) than Americans

(mean=5.2, SD=3.2), t(347)=-1.66, P<.1, this does not explain the difference in

evaluation of the assortments.

Customers that are less satisfied with their decisions are also less satisfied

with the assortment, χ2(6, N=308)=25.0, p<.000 (see Appendix F, table 23). This

may be explained by Dutch people not only giving lower assortment evaluations but

also being less satisfied with their choices. Comparing the satisfaction with the made

choice reported by Dutch and Americans it was found that Dutch tended to be less

positive about their decisions, χ2(2, N=370)=4.9, p=.088. Whereas 60% of

Americans was completely satisfied with their choice only 50% of Dutch were.

Analyzing the two countries separately shows that the relationship between

satisfaction with the made choice and the evaluation of the assortment are indeed

culture specific (see Appendix F, table 23). Whereas in the USA there is a


significant relationship, χ2(4, N=125)=42.7, p<.000, this is not observed with

respondents from the Netherlands.

People with less knowledge gave worse assortment evaluations, χ2(10,

N=254)=22.8, p.012 (see Appendix F, table 25 and

table 26). As discussed before the USA respondents indicated having more

knowledge than the Dutch respondents and Americans were also more positive in

their assortment evaluations. Looking at the relationship between assortment

evaluations and knowledge reveals that only in the USA this relationship exists, χ2(4,

N=67)=18.8, p=.001.

There is a significant relationship between evaluation and importance, χ2(10,

N=311)=22.9, p.011 (cross tab see Appendix F, table 27 and table 28). As discussed

before the American respondents indicated that their choices were more important.

When looking at the relationship in the two countries separately it was found that in

the USA assortments are evaluated more positively if the made decision is more

important, χ2(4, N=215)=14.3, p=.006. No support for this interrelation was found

for Dutch respondents, χ2(6, N=186)=9.6, p=.142.

6.2 Explaining Indecision and Decision Difficulty

The survey included two measures of decision ease which were recoded into

three distinct measurers. Of the Dutch respondents 41% considered not buying the

product compared to 20% of Americans, which is a significant difference, χ2(1,

N=367)=20.2, p<.000. There were no significant differences in the frequency with

which people considered postponing the decision which was 27% in both countries.

However, Dutch men (37%) were significantly more likely to have considered

postponing the decision than Dutch women (20%), χ2(1, N=184)=6.9, p=.008.

Americans indicated to have found the decision significantly more easy to make,

χ2(3, N=372)=34.1, p<.000. 30% Of Americans found their decision very easy

compared to 7% of Dutch (see Appendix F, table 33). Dutch on the other hand more

often found the decision neither difficult nor easy (26% compared to 15%).

The three measures were related to each other, χ2(9, N=372)=42.9, p.000. Of

those that considered neither postponing nor not buying the product (N=199) 24%

found the decision very easy, 51% easy, 16% neither easy nor difficult and 10%

difficult. Of those that considered not buying the product (N=72) 11% found the


decision very easy, 47% easy, 25% neither and 17% difficult. For those that

considered postponing the decision (N=58) 21% indicated that the final choice had

been very easy, 33% that it had been easy, 24% neither and 22% had found making

the decision difficult. Those that considered both postponing and not buying (N=43)

had most trouble deciding, with only 2% finding it very easy, 28% finding it easy,

30% finding it neither easy nor difficult and 40% found it difficult.

Independent sample t-tests revealed no support for relationships between

choice deferral, as measured through the consideration of postponing and not buying

the product and variety, as measured through assortment size and the amount of

alternatives considered. Perceived decision ease was found to be related to

assortment size, F(3, 345)=4.581, p=.004. Those that found the decision very easy

remembered significantly less alternatives than all others (see Appendix F, table 29

for a complete overview of significant mean differences). For American respondents

it was additionally found that choice set size was related to perceived decision ease,

F(3, 181)=4.983, p=.002 (see Appendix F, table 30). Overall as perceived decision

difficulty increased so did the amount of alternatives considered.

Products for which the decision is very important were more often very easy

to decide on than other products for both nationalities, χ2(9, N=374)=36.3, p<.000

(see Appendix F, table 31). On the other hand, those making important decisions

were more likely to consider postponing them (36%) than those making rather

important or neither important nor unimportant decisions (25%) and those making

unimportant decisions (14%), χ2(3, N=366)=10.8, p=.013. Only for Dutch

respondents an relationship was found between importance of the decision and

whether or not deferring the purchase was considered, χ2(3, N=184)=10.7, p=.019.

Not buying the product was considered most often by those making decisions that

were either rather important or neither important nor unimportant (53% and 50%

respectively). Of those making decisions about products where choosing right is

very important 38% considered not buying, and 25% of those making unimportant

decisions considered not buying the product. No significant relationship was found

between the importance of decisions and the choice set size.

Concerning product knowledge no significant relationship was found with

the frequency of considering postponing the purchase nor with the frequency of

considering not buying the product. There was a significant relationship between

knowledge and perceived ease of the decision (see Appendix F, table 32). Those that


believed they had most knowledge were most likely to have found the decision easy

(33% thought so) compared to 16% on average. Those that indicated have very little

knowledge were least likely to find making a decision easy; 45% found that making

a decision had been difficult, compared to 17% on average. Knowledge was not

significantly related to remembered assortment size nor to the size of the choice set.

6.3 Explaining Satisfaction with Made Choices

As discussed in the section 6.1 Dutch tend to be less satisfied with the

choices they make. This section will look at some possible explanations for choice

satisfaction, namely the difficulties experienced while choosing, the assortment size

and the size of the choice set.

Satisfaction with the made choice is significantly related to the ease of the

decision for Americans, χ2(6, N=183)=31.6, p<.000, but not for Dutch, χ2(6,

N=190)=9.3, p=.159 (see Appendix F, table 34). Decisions that were easier were

also rated as more satisfying. For the Dutch respondents satisfaction was related to

whether or not they had considered not buying the product, χ2(2, N=184)=10.7,

p=.005, and whether or not they had considered postponing the decision, χ2(2,

N=184)=7.8, p=.021 (see Appendix F, table 35 and table 36). In both cases if such

considerations had been made the satisfaction with the made choice was lower. For

Americans neither of these significantly relate to choice satisfaction.

There was no significant difference between the size of the choice sets of

Dutch and Americans, however Americans tended to consider fewer alternatives,

t(365)=-1.66, p=.097. Overall, the respondents indicated remembering considering

2.82 alternatives (SD=1.89), Americans on average considered 2.65 alternatives

(SD=1.96) and Dutch considered 2.98 (SD=1.80). As discussed before though Dutch

tended to remember larger assortments there was no significant difference between

the countries. Neither assortment size nor the size of the choice set was found to be

related significantly to satisfaction with the made choice; not for the overall sample

nor for the nationalities separately.

Satisfaction with the made choice was significantly related to product

knowledge, χ2(8, N=313)=38.4, p<.000, and having more knowledge related with

making more satisfying decisions (see Appendix F, table 37). For Americans

satisfaction with the made choice was also significantly related to the importance of


the choice, χ2(4, N=183)=13.8, p=.008 (see Appendix F, table 37). More important

choices were perceived as more satisfying than less important ones.

7. Discussion on Cross-Cultural Findings

The present study duplicates the earlier finding as support was found for H1

as Dutch were less satisfied with the assortments than Americans. There was no

support for H2a as in neither country assortment breadth was related to assortment

evaluation. There is partial support for hypothesis H2b, as in the USA assortment

evaluations are less positive when people are less satisfied with their choice. There is

also partial support for H2c, as Americans that know more and find their decisions

more important gave higher assortments evaluations than Americans that knew less

and or made less important assortment decisions. Such relationships were however

not found for the Dutch respondents, leading to a rejection of H2. Assortment

evaluations seem to be based on different underlying factors in the Netherlands than

in the USA. While in the USA sample support is found for the hypothesis derived

from the theory, these do not seem to apply to the Netherlands.

Looking at satisfaction it was found that Dutch tend to be less satisfied with

their choices, therefore H3 has been partially accepted. For US respondents

satisfaction with the made choice was higher when they perceived the choice as

easier. And the Dutch rated their satisfaction with the made choice lower when they

had considered either postponing or not buying the product. This provides support

for H4a, though different aspects of choice difficulty seem to be of influence for

Dutch and Americans. Partial support was found for H4b. Dutch indicated that there

decisions had been less easy and more often considered not buying the product than

Americans did. No difference was found for the frequency with which people

considered postponing the decision. No support was found for H4c and H4d as

assortment and choice set sizes do not seem to influence satisfaction with the made

decision. In conclusion no support was found for H4 as no common factors

underlying choice satisfaction were found.

With respect to H5, it was found that people making more important

decisions found it easier to decide but are also more likely to consider postponing

the decision. Both people making very important decisions and unimportant

decisions were less likely to consider not buying the product. No support was found


for H6, people making more important decisions do not work with larger choice sets.

Regarding knowledge only partial support was found for H7, as those having more

knowledge report having found the decision easier to make. No support was found

for H8 and H9.

This research revealed structurally lower scorings by Dutch on topics as

satisfaction with the made choice, knowledge, importance, the ease of the decision

and assortment evaluations. The amount of options, remembered by Dutch tended to

be higher than the amount remembered by Americans, both when looking at the

assortment size and choice set. Therefore, though American retailers tend to be

larger than Dutch, Dutch retailers may have broader assortments. An alternative

explanation is that Dutch category perceptions are broader, or that Dutch were more

involved with the decision.

Looking at the overall picture, it seems that the factors taken into account do

not account for the difference in assortment evaluation between Americans and

Dutch. Although when taking the complete sample many of the constructs appear to

explain evaluation, in reality they only explain variation in evaluation for the USA

and are non-significant when looking at solely the Dutch respondents. As very few

of the hypotheses seem to explain the Dutch satisfaction with choice and the

evaluation of the assortments the following section will look into the Dutch

perceptions of, attitudes towards and reactions to choice in more detail using a more

exploratory approach.

8. Analysis Procedure Study of Dutch Respondents

Using the same sample of Dutch respondents as was used in part one of this

study some further analyses were carried out. This analysis of Dutch respondents is

complementary to the previously presented results. First, results regarding believes

regarding choice are presented as addition to and replication of study 1. Secondly,

perception of variety in retailers and presentation are explored in relation to

assortment evaluations. Thirdly, possible negative experiences and associations with

the decision process are explored. Fourth, post-purchase feelings were investigated,

with an emphasis on mediators for the relationship between assortment and choice

set size and choice satisfaction. Included mediators are: experienced positive


surprise, regret, thinking about and looking at other alternatives, increased

expectations and outcome responsibility. Only significant effects are reported.

For the analysis mainly χ2-tests and ANOVA’s were used according to the

procedure described before. Principal components analyses were carried out

regarding benefits and downsides associated to choice. The analysis of benefits

included six variables, namely liking of the act of choosing, and the belief that

having choice increases freedom, decision quality, control, happiness and enables

one to do better, which were measured on a six level interval Likert scale.

Furthermore, principal component analysis was applied to negative associations with

the decision process, including frustration, stress, feeling of being overwhelmed and

perceived wasted time extracted (see the appropriate result sections for more

information including assumption checks).

9. Specific Results for Dutch Respondents

9.1 Beliefs Regarding Choice

Of the respondents 50.6% believed that for generic products such as milk,

flower, sugar and water no brand differentiations were needed. As many Dutch

(49.7%) believed that the product choices they make have a large influence on their

life, while 50.3% did not believe this to be the case. Somewhat more respondents

(60.7%) feel that product choice allows them to express their identity. Those that

feel one product alternative for basic products is enough were less likely to believe

that product choice enabled them to show identity than those that did not feel one

brand would suffice, χ2(5, N=158)=11.0, p=.052 (see Appendix G, table 39).

Furthermore, the extent to which products are perceived to affect life is related to

perceived ability to express identity through product choice, χ2(9, N=159)=22.3,

p=.008 (see Appendix G, table 40).

The survey contained various other possible believed benefits of choice,

namely liking of the act of choosing, the belief that having choice increases freedom,

decision quality, control, happiness and enables one to do better (the extent to which

respondents agreed to the existence of each benefit is summarized in percentages in

table 6). Overall, as in study 1 respondents associate benefit with choice. Unlike

study 1 however all of the benefits were significantly related to gender, with women

associating fewer benefits to having choice (see Appendix G, table 41).


Table 6: Benefits associated to choice.

Like choosing

Increases freedom

Increases decision quality

Enables doing better

Increases control

Increases happiness

Completely agree 13,1% 13,6% 11,4% 8,8% 8,05 8,4%

Mostly agree 35,4% 31,0% 23,9% 27,3% 23,1% 21,4%

Slightly agree 23,7% 31,4% 24,2% 26,1% 31,8% 31,3%

Slightly disagree 14,0% 12,4% 22,9% 26,3% 17,6% 17,7%

Mostly disagree 7,3% 5,5% 11,9% 8,2% 12,8% 14,1%

Completely disagree

6,5% 6,2% 5,7% 3,2% 6,7% 7,0%

N 157 158 157 156 156 158

Principal component analysis was carried out regarding benefits associated to

choice. The variables were sufficiently correlated (Barlett’s test for sphericity:

χ2(15)=371.5, p<.000 and KMO =.879) and the communalities were between .48

and .71. One factor was extracted with an eigenvalue of 3.57, the second factor did

not meet the minimum eigenvalue criteria as the eigenvalue was .67. The factor

explains 59.5% of variation of the original variables. The model fit was average with

80% non-redundant residual correlations (under .05) indicating that relatively much

information got lost during the creation of the factors. The following formula was

found for calculating factor scores based on the original variables:

Benefit of choice=.708*enjoyment of choosing + .694*freedom +

.782*decision quality + .792*achieving better outcomes + .802*control +

.838*happiness

Like the individual variables benefit of choice is significantly lower for

women than for men, t(151)=-3.6, p<.000. Furthermore, older respondents scored

higher, r(150)=.319, p<.000, and also respondents living in more urban areas had a

more positive attitude towards choice F(2, 150)=3.9, p=.023, linearity: F(1,

150)=7.3, p=.008, deviation from linearity: F(1,150)=.5, p=.498. A linear positive

relationship was found between the perceived influence of bought products on one’s

life and believed benefit of choice, F(3, 148)=7.7, p<.000, linearity: F(1, 148)=19.8,

p<.000, deviation from linearity: F(2,148)=.7, p=.670. Also a linear positive

relationship was found between ability to express identity to product choice and

benefit of choice, F(3, 149)=15.8, p=.001, linearity: F(1, 149)=14.9, p<.000,


deviation from linearity: F(2,149)=.9, p=.608. No significant relationships were

found between perceived benefit of choice and perceived increase in choice or the

amount of experience shopping.

9.2 Assortment Perception, Presentation and Evaluation

Most Dutch (86.9%) feel that more product alternatives have become

available to them over the last years. This is unrelated to urbanization of the area

they live in is and age. Regardless the product type of the remembered choice,

65.3% was faced with more variety than they had expected. When asked to qualify

the amount of differences between the product offered 20% of respondents said they

differed very little, 41% that they differed somewhat and 31% that they were rather

different. 5% of the respondents perceived the offered products as extremely

different and 3% as not at all different. Products were perceived to vary most widely

on intrinsic attributes such as functionality, design and taste (44%), followed by

price (21%) and brand (15%).

Assortments were perceived to be very well categorized by 49% and rather

well by 26%. The remaining 25% felt that alternatives could have been placed closer

together. Products were easily found by 74% of respondents, the remaining 26% had

some to a lot of trouble location the products within the assortment. For 17% of the

respondents the assortment did not include the wanted product, and 50% was

influenced in their decision by special offers. 38% of the respondents feel that their

choice is to some extent influenced by the available variety.

Product offer and presentation as measured through the above mentioned

variables did not relate significantly to the amount of perceived variety, however it

did relate to assortment evaluation (see appendix G, table 42 to 47). Evaluations of

those that found more variety than they expected were also more positive, χ2(8,

N=153)=33.1, p<.000. Those who increased their expectations due to the size of the

assortment were also likely to evaluate it more positively, χ2(6, N=152)=13.7,

p=.033. Respondents who were influenced in their decision by special offers were

more likely to give a positive evaluation, χ2(8, N=150)=21.8, p=.005. When the

wanted product was not available assortment evaluation was lower, χ2(4,

N=154)=20.4, p<.000. Evaluation is related to how close alternatives were together,

χ2(6, N=150)=23.0, p=.001, people that considered items that were placed close


together were more likely to give a positive evaluation than those that considered

alternatives that were placed further from each other.

9.3 The Decision Experience and Decision Process Satisfaction

Dutch people most often (42.3%) indicated to sometimes have difficulties

deciding between alternatives, 24.8% indicated to hardly ever or never have trouble,

23.6% indicated to regularly have problems deciding, and 9.3% indicated to often or

always have experience difficulties. The frequency of experiencing trouble is

significantly related to gender, χ2(3, N=157)=10.7, p=.013, men more frequently

have hardly any trouble, while women more frequently experience decision

difficulty often. The frequency with which difficulties are experienced is related to

self-efficacy, χ2(6, N=153)=13.4, p=.038 (see Appendix G, table 47). Those that

more often experience difficulties in deciding express less belief in their ability to

make good decisions.

Table 7: Extent to which negative feelings were experienced.

Time wasted Overwhelmed Stress Frustration

Completely agree 5,4% 4,8% 1,0% 2,4%

Mostly agree 9,4% 10,6% 5,1% 7,2%

Slightly agree 17,6% 20,3% 10,4% 22,9%

Slightly disagree 14,0% 18,2% 14,8% 17,7%

Mostly disagree 29,0% 21,3% 25,6% 26,0%

Completely disagree 24,7% 24,8% 43,0% 23,8%

Note: n=158

For some of the respondents the decision was associated with negative

feelings (see table 7 where the extent to which respondents agreed to the existence of

each drawback is summarized in percentages). Principal component analysis was

carried out regarding these drawbacks of deciding. The variables were sufficiently

correlated (Barlett’s test for sphericity: χ2(6)=135.6, p<.000 and KMO =.745). The

communalities were relatively low with values between .42 and .69. One factor was

extracted with an eigenvalue of 2.25, the second factor did not meet the minimum

eigenvalue criteria as the eigenvalue was .73. The factor explains 56.3% of variation


of the original variables. The following formula was found for calculating factor

scores based on the original variables:

Experienced drawbacks = .651*overwhelmed + .717*wasted time +

.828*frustration + .792*stress

As all contributing variables were significantly related to gender the factor

analysis was also carried out for both genders separately. No reasons were found to

apply different loadings based on gender (see Appendix G, table 48).

Men were less likely to experience drawbacks than women, t(156, 79)=2.0,

p=.049. Older respondents reported less negative associations with the process than

younger respondents, r(156)=.162, p=.044. People with larger choice sets tended to

experience more drawbacks, r(156)=-.137, p=.089. No relationship between

experienced drawbacks and assortment size was found, even though choice set and

assortment size were correlated, r(147)=.449, p<.000.

The experience of drawbacks is negatively related to perceived decision ease,

F(2, 155)=23.625, p<.000, test for linearity: F(1, 155)=45.209, p<.000, deviation

form linearity F(1, 155)=1.736, p=.190. The experience of drawbacks was not found

to be related to whether the respondent liked multiple options, nor was perceived

decision ease. While the use of heuristics did not influence experienced drawbacks

significantly, the extent to which a satisficing strategy was used did, F(4,

152)=3.125, p=.017. The more people bought the first product found that matched

their criteria the less drawbacks to deciding they experienced.

Negative decisions feelings were significantly related to satisfaction with the

decision process, F(3, 154)=7.433, p<.000, test for linearity: F(1, 154)=19.209,

p<.000, deviation form linearity F(1, 154)=.574, p=.424. Those that are satisfied had

significantly higher scores, indicating less experienced drawbacks, than those that

were less satisfied. Satisfaction with the decision process was also directly related to

perceived decision difficulty, χ2(4, N=158)=11.2, p=.024, people that found making

the decision very easy indicated high satisfactions with the decision process and

those that found it difficult reported less satisfaction (see Appendix G, table 49).

9.4 Post-Purchase Satisfaction

As discussed in the cross-cultural analysis 50% of Dutch were completely

satisfied with the made decision. This satisfaction was found to be related to the


whether or not the respondents would buy the product again, χ2(6, 156)=99.313,

p<.000. 84% of those satisfied with the choice would buy the product again, 57% of

those that were mostly satisfied would consider buying the product again and 73%

of those unsatisfied with their decision would not buy the product again.

No direct relationship between assortment size and satisfaction with the

made decision was found, however satisfaction with the made decision was found to

be related to the extent to which a positive surprise was experienced, χ2(6,

156)=34.9, p<.000 (see Appendix G, table 50). When a positive surprise was

experienced satisfaction with the made decision increased. Positive surprises were

more likely when choice sets were smaller, F(3, 149)=3.6, p=.016. People that were

very positively surprised on average considered 1.5 (SE=.5) options less than those

that were not positively or negatively surprised and 1.4 (SE=.5) options less than

those that were negatively surprised. Furthermore, positive surprises were less likely

when assortment sizes had increased expectations, χ2(12, 154)=24.6, p=.017 (see

Appendix G, table 51). Increased expectations in turn were again more likely when

assortment sizes were larger, F(4, 145)=6.0, p<.000. Thus indirectly assortment sizes

may lower decision satisfaction by influencing product expectations.

10. Discussion of Dutch Results

With respect to cultural attitude towards choice Dutch were found to want

(brand) variety even for products that are widely considered uninvolving. This

preference increases as people feel more able to express identity through choice as

was suggested in chapter three. Also other benefits of choice identified in the

literature were held by Dutch, namely that having more product choice increases

freedom, decision quality, control, happiness, enables one to do better and that

choosing is enjoyable. Women perceived fewer benefits, while people living in

urban areas and older people perceived more. Lastly, the amount of perceived

benefit increased as product choice was related stronger to identity.

The study further confirmed that the amount of choice has grown over the

past years. No support was found for a relationship between urbanization and choice

expansion, though theory suggested greater choice expansions in urbanized areas.

Most people perceived relatively little difference between the products in the

assortment and assortments were perceived to vary most on intrinsic attributes, and


to a lesser extent on price and brand. This is surprising as both in studies respondents

indicated to mainly look for and decide based on price and value for money.

The importance of point-of-sale marketing was underlined as many of the

choices were consciously influenced by the available assortment and also special

offers often played a role in of decisions. Moreover, a large proportion of the

recalled decisions involved situations in which the preferred alternative was not

available, negatively impacting assortment evaluation. This supports the retailers’

fear for the salience of these experiences, and subsequent large assortments.

Especially since study 1 found that Dutch often express tolerance for variety when it

caters to the wants and needs of others.

Though in the majority of recalled cases all alternatives had been located

close together in a substantial part this was not the case. The extent to which the

assortment was appropriately sorted was positively related to assortment evaluation,

underscoring the importance of understanding customer choice sets. Assortment

evaluation was additionally positively related to perceived variety, increased

expectations and being influenced by special offers. This shows that for assortment

evaluation not only variety is important but also the extent to which this variety is of

interest to the customer.

The third section of the analysis explored drawbacks of choice, decision

difficulty and decision satisfaction. It was found that most Dutch had difficulties

deciding between alternatives, women more so than men. This gender difference

may however alternatively be explained by the frequency of making purchases

which was not controlled for. Product choice was associated with wasted time,

frustration, feeling overwhelmed and to a lesser extent with stress. All these together

were experienced less by older participants, and less by men, groups which also

associated more benefits to choice. Age may moderate choice as more experience

choosing has been accumulated and people are more aware of their preferences. Men

may use more effective decision styles than women, be more tolerant to negative

emotions, or expose themselves to different amounts or types of choices. More

research into these differences are needed, especially as traditional gender

differences in purchasing divisions disappear more and more. More negative

emotions were experienced by those considering more alternatives. This possibly

relates to the increased difficulty deciding documented in part one of this study, but

again more research is needed.


Finally, it was found that post-purchase satisfaction was influenced by

whether or not the product was positively surprising, which in turn was related to

increased expectations due to assortment variety and the assortment and choice set

size. This provides some support for the hypothesis that choosing from more variety

may lead to lower subjective decision quality.

These studies explored further to what extent findings of American research

on choice under variety could be transferred to Dutch. The initial cross-cultural

analysis showed little support for cultural transferability. The more in depth analysis,

on the other hand, found that many concepts and relationships proposed in the theory

apply to the Dutch as well.

11. Discussion of the Methodology

Methodologically the study has several limitations; most notable are its use

of memories and the instrument used. Furthermore, like study 1 the sample is non-

probability and small decreasing both reliability of the study and generalizability.

The use of memories facilitated establishing a broad overview, provided data

on decisions that are really made, rather than solely imagined. The ease with which

most respondents could come up with an example, often not more than two weeks

old, highlights the ubiquity of conscious choice in the current retail setting,

regardless of product type. Only one American respondent said that when asked to

remember a choice made in retail: ‘I do not remember this happening’ (male, 49).

The use of memories furthermore, to a certain extent, allows for

generalization over product categories and retailers. The drawback however is that

for specific product types sample sizes are too small to draw conclusions.

Furthermore, as the recalled memories differed based on nationality it is difficult to

determine how reliable and valid the between country differences are.

Respondent could freely contribute his own experience selecting only based

on the criteria that the decision had to be made consciously enough to be

remembered. However, this construction also introduced a selection bias in favor of

more salient memories, thereby not unlikely inflating reports for example with

respect to negative associations to the decision. Additionally, relying on memories

poses various limitations. First of all, time may affect each of the answers

individually as well as the relationships among them. Overall, reports become less


accurate. Furthermore, no causal relationships can be established, and that makes the

effects of variety difficult to assess. For example, people that have difficulty

choosing may have expanded their choice sets in an attempt to reach a decision,

rather than the choice set remaining unchanged throughout the decision process.

Importance of the decision and product knowledge were controlled for in the

cross-cultural comparison. It is however beyond the scope of this study to

additionally control for other known mediators and moderators, such as involvement

and familiarity with the assortment.

With regard to the instrument there are various points for discussion. As

none of the questions were used in previous research the survey was pre-tested by

eight participants and proof-read by two native English speakers, however the scales

were not validated. Whereas study 1 has the problem that answers were provided in

two different languages making scoring more difficult, here the quality of Dutch

responses may be lower as they did not complete the survey in their mother tongue.

Some answer categories were not optimal, for example whether or not people had

considered not buying the product was assigned a six point Likert scale. The item on

assortment evaluation facilitates analysis as it provides a clear continuum. However,

this does not help answer the question posed in the discussion of study 1 whether or

not having too much choice should be interpreted as a linear extension of a good

assortment, or as a return to a bad assortment.

All constructs are measured through self-report scales and as only one

question was included for most constructs validity could not be checked as only one

measuring item was included. Analysis of Dutch responses shows that the validity of

some questions is compromised, as for example not everyone that did purchase the

product though not immediately indicated to have considered postponing the

decision. Possibly this can be explained as they never meant to purchase the product

straight away, but rather were gathering information.

Finally, remembered variety and choice set size had to be recoded to reduce

outliers. However, this may have masked differences in choice environment. Those

faced with over 50 alternatives are more likely to have chosen using the internet, as

recalled memories were not limited to in-store decisions. Either way, those faced

with such extensive choice sets are much less likely to evaluate all options and more

likely to have other information sources and decision aiding tools available.


Conclusion, Recommendations, Discussion and Future Outlook

It is safe to conclude that choice, in the sense of available alternatives, has

become increasingly pervasive in retailing, both in the USA as well as in Europe.

And due to the concentration and globalization trends in retail, as well as the rise of

the internet, choice is increasingly pervasive all around the world. Over the past two

centuries store formats in Europe and the USA have become larger offering both

deeper and broader assortments. New inventions, innovations, newly available

products and increased variety of existing products through package size, pricing

and branding fill the shelves. And only temporarily available products additionally

increase the variety. Furthermore, due to urbanization and increased personal

mobility the amount of different stores customers can choose from has increased.

Moreover, the rise of the Internet has made it easier for customers to share and

retrieve information regarding products and services. Additionally, the Internet

provides a global channel which widely expands the amount and variety in retailers

customers can easily access. Also, through the Internet the amount of product

alternatives that are available has become almost unlimited, especially when looking

at sites facilitating trade between customers.

The literature review revealed various effects of assortment size on customer

purchase decisions. As assortment size increases it draws more customer attention.

However, likelihood of purchase, though initially growing as well soon drops. The

point where more variety becomes detrimental depends not only in product type and

customer involvement, but also on factors such as the customer’s variety seeking

tendencies, the perceived relationship between product choice and identity,

knowledge and the customers decision making strategy. The relationship is further

influenced by time pressure and the extent to which the customer has articulated

preferences. Evidence from customization experiments shows that it is important to

gradually increase provided alternatives over subsequent choices to reduce shopping

fatigue. Having a high amount of options can be both a source for enjoyment as well

as frustration and thus fundamentally affect the shopping experience. Assortment

size can affect the product chosen as customers are less likely to pay attention to

many product attributes and looking more for choice justification. Also after the

decision process assortment size continues to have an effect on the post-purchase

confidence and satisfaction. Choice from large assortments leads to lower decision


confidence and less satisfaction with the chosen product, due to higher expectations,

opportunity costs, regret and responsibility.

Many choices are of little importance and are made in a matter of seconds

when the customer is confronted with the assortment. The empirical research shows

that many respondents were influenced by the available variety and in particular by

special offers. Appropriate presentation of choice in retail can reduce cognitive

effort, affect the perception of variety and increase sales. Smaller aisles induce

customers to seek more variety, and organized small assortments induce less variety

seeking. Though assortments with many choices attract attention, customers may

decide more easily when presented with fewer. For the same reason presentation

should emphasize differences, for example through clear labeling of healthy choices,

to minimize preference uncertainty and indecision. Large assortments can be made

more accessible, especially for the less knowledgeable and less involved customer

through categorization. However, even well categorized assortments may be less

attractive then smaller ones. Therefore, information regarding the target group, such

as provided by consumer decision trees, is crucial in making presentation and

assortment size decisions. Other methods of mediating choice are sales personnel

intervention, default options and effective return policies.

The understanding of choice from variety must be articulated within the

broader context of cultural values, norms and the social construction of reality. In

the literature some indications were found that the preference for and response to

product choice may be different based on culture. Both studies found support for the

effect of culture and the existence of cultural differences. The initial cross-cultural

analysis showed little support for cultural transferability of research on product

choice under variety. The more in depth analysis on the other hand found that many

concepts and relationships proposed in the theory do apply to Dutch as well.

The main question of this paper is: ‘To what extent is the amount of choice

offered by Western retailers to non-professional customers desirable?’ The

research presented here shows that customers often want variety and presenting

larger assortments leads to better evaluations and more attention. Furthermore, there

is a biological preference for choice. However, presenting too much choice

decreases the quality of the shopping experience, purchase likelihood and post-

purchase satisfaction. Deciding how much choice to offer however can be difficult

as many mediators play a role that are not only person bound but also context


related. Moreover, preference for choice is prioritized versus other preferences and

cognitive as well as behavioral patterns dependent on context, individual

characteristics, socio-economic status and culture. Deeper understanding of this

process of prioritization is needed before a conclusive answer can be given.

As customers become more used to choice it may be that choice becomes

more desirable as learning effects take place. It is important that this possible

learning effect is investigated as the retail industry is highly dependent on the size of

the middle class, which is growing especially fast in countries where now little

assortment variety is offered. Also, more in general the relationship between

assortment familiarity, indecision and drawbacks of choice should be investigated as

familiarity is likely a large moderator of all assortment size related drawbacks.

Further research should also focus on choice presentation online. The

Internet provides a platform where there is virtually no limitation to the amount of

choice that can be offered. However, also here the customer may decide not to

decide when faced with too many options, including the amount of websites that a

product can be ordered through and the amount of different payment methods. Also

other situations in which large amount of choice are presented should be

investigated. It is likely that there are specific characteristics setting apart products

for which near unlimited amounts of variety do not have detrimental effects, and

which allow selling a large variety to become the competitive advantage it is for

websites such as Amazon and Threadless.

A main limitation to this thesis is its sole focus on the variety offered in-

store. However, this may not reflect accurately the amount of variety offered. For

example, the bread people buy is most often not eaten alone. Instead customers

combine it with at least one other product such as meat or jam, thereby creating

much more choice than only the number of products would suggest. When more

variety is offered by instead of bread selling sandwiches, though the in-store variety

increases, actual variety decreases. Furthermore, only variety within one store is

taken into account, largely ignoring variety created by assortment differences

between stores, an aspect that especially the Dutch were unhappy with. Maybe this

explains why though there is widespread belief in the benefits of choice it can be

observed that ratings of retailers within the western world, as presented on the front

page, are higher there where stores are smaller.

□

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Appendix A: Legend figure 6 I

Appendix A: Legend figure 6

AT -Austria

BE - Belgium

BG - Bulgaria

CY - Cyprus

CZ - Czech Republic

DE - Germany

DK - Denmark

EE - Estonia

EL - Greece

ES - Spain

EU - European Union

FI - Finland

FR - France

FYRM - Macedonia

HR - Croatia

HU - Hungary

IR - Ireland

IS - Iceland

IT - Italy

LT - Lithuania

LU - Luxembourg

LV- Latvia

MT - Malta

NL - the Netherlands

NO - Norway

PL - Poland

PT - Portugal

RO - Romania

SE - Sweden

SI - Slovenia

SK - Slovakia

TU - Turkey

UK - the United Kingdom

Appendix B: Additional Industry Data II

0 5 10 15 20

Mexico

Morocco

Netherlands

New Zealand

Norway

Philippines

Poland

Portugal

Romania

Russia

Saudi Arabia

Singapore

Slovakia

South Africa

South Korea

Spain

Sweden

Switzerland

Taiwan

Thailand

Turkey

Ukraine

United Kingdom

USA

Venezuela

Vietnam

Appendix B: Additional Industry Data

Figure 14: Number of stores per 1,000 inhabitants in 2007 for selected countries.

Data source: Euromonitor (2009).

0 5 10 15 20

Argentina

Australia

Austria

Belgium

Brazil

Bulgaria

Canada

Chile

China

Colombia

Czech Republic

Denmark

Egypt

Finland

France

Germany

Greece

Hong Kong

Hungary

India

Indonesia

Ireland

Israel

Italy

Japan

Appendix B: Additional Industry Data III

Figure 15: Share of grocery sales by format in Europe, 2000 vs 2004.

Source: Igan & Suzuki (2011).

Appendix C: Study 1; Extra Information IV

Appendix C: Study 1; Extra Information

Table 8: Cross-tabulation of liking and given reason.

Total No Depends Yes Too much Other

Variety 37 1 2 21 1 12

Lot of choice 30 0 0 23 2 5

Availability 22 3 6 12 0 1

Want more choice 19 4 10 3 2 0

Fit to want 19 0 2 12 0 5

Quality (price) 16 1 3 4 0 8

Indecision 11 1 1 3 5 1

Like choosing 11 0 1 7 0 3

Compare 9 0 1 3 0 5

Freedom to choose 7 1 0 5 0 1

Same stores 7 2 3 1 1 0

Cheaper 7 1 1 4 0 1

Amount of stores visited 7 3 3 0 0 1

Negative feelings 5 0 2 1 2 0

Something for everyone 5 0 1 4 0 0

More competition 4 1 0 2 0 1

Store organization 3 0 2 0 0 1

Decision quality 2 0 0 0 1 1

Express self 1 0 0 1 0 0

Novelty 1 0 0 1 0 0

Total 223 18 38 107 14 46

Appendix C: Study 1; Extra Information V

Table 9:Cross-tabulation of whether there was perceived benefit and reason given.

Total No Depends Yes Other

Cheaper 50 0 6 44 0

Fit to want 26 0 2 24 0

Variety 24 6 0 18 0

Price variety 17 0 2 15 0

Ease comparison 13 0 0 12 1

Good/better choice 10 1 1 8 0

Like choice 8 0 0 8 0

Time & gas 7 0 2 5 0

Availability 6 0 1 5 0

Freedom to decide 5 1 0 4 0

Quality 4 0 0 4 0

Increased spending 3 1 2 0 0

Ownership decision 3 0 0 3 0

Other positive 1 0 0 0 1

Other negative 1 0 0 0 1

Total 178 9 16 150 3

Appendix C: Study 1; Extra Information VI

Table 10: Cross-tabulation of whether the respondent complained and given reason or mediator.

Total No No, but Yes Other

Difficulties finding 7 0 5 1 1

Loss oversight 5 0 2 3 0

Indecision 4 0 1 2 1

Too crowded 3 0 1 2 0

Intimidating 3 0 2 0 1

Availability 2 0 0 2 0

Confusion 1 0 0 1 0

Familiarity 4 0 3 1 0

Limit aisles 3 0 2 0 1

Avoidance 2 0 2 0 0

Total 34 0 18 12 4

Appendix C: Study 1; Extra Information VII

Table 11: Relationship between attitude components.

Complained? Benefit

Yes No, but No Yes Unsure No

Liking depends phi .003 .151* -.171* -.130 .097 .078

p .965 .041 .037 .082 .194 .293

N 184 184 150 181 181 185

Like choice phi -.228** -.124 .190* .364** -.232** -.229**

p .002 .095 .020 .000 .002 .002

N 184 184 150 181 181 185

Too much choice phi .284** .039 -.123 -.281** .168* .168*

p .000 .595 .133 .000 .024 .023

N 184 184 150 181 181 185

Dislike amount of choice

phi .093 -.029 .018 -.138* .091 .093

p .157 .663 .803 .038 .172 .156

N 235 235 199 228 228 236

Unsure benefit phi .231** .062 -.120

p .000 .352 .096

N 227 227 195

Yes benefit phi -.214** -.002 .037

p .001 .975 .608

N 227 227 195

No benefit phi .048 -.038 .034

p .462 .563 .630

N 235 235 199

Note: *p<.05, **p<.01, all significances two-tailed.

Appendix C: Study 1; Extra Information VIII

Table 12: Relationship between attitude components for Dutch respondents.

Complained? Benefit


Liking depends phi .030 -.026 -.035 .145 -.032 -.115

p .770 .785 .710 .123 .741 .231

N 100 114 114 115 110 110

Like choice phi .135 -.126 .055 .094 .151 -.175

p .291 .278 .640 .417 .195 .133

N 63 76 76 77 75 75

Too much choice phi .178 -.119 -.291* -.210 -.358** .449**

p .162 .305 .011 .067 .002 .000

N 63 76 76 77 75 75

Choice not liked phi -.417** .285* .325** .119 .320** -.359**

p .001 .013 .004 .303 .005 .002

N 63 76 76 77 75 75

Unsure benefit phi .026 -.024 -.003

p .797 .801 .974

N 100 114 114

Yes benefit phi -.234* .139 .369**

p .021 .149 .000

N 97 109 109

No benefit phi .087 -.055 -.248**

p .397 .568 .009

N 97 109 109


Appendix C: Study 1; Extra Information IX

Table 13: Relationship between attitude components for American respondents.

Complained? Benefit


Liking depends

phi .051 -.063 .113 .193* .136 -.249**

p .617 .489 .216 .034 .143 .007

N 99 121 121 121 118 118

Like choice phi -.333**

.303** -.031 .049 .061 -.082

p .002 .001 .747 .612 .537 .406

N 87 108 108 108 106 106

Too much choice

phi .209 -.138 -.188 -.244* -.149 .299**

p .053 .153 .052 .011 .129 .002

N 87 108 108 108 106 106

Amount of choice disliked

phi .073 -.101 .289** .147 .033 -.138

p .503 .298 .002 .129 .738 .159

N 87 108 108 108 106 106

Unsure benefit

phi -.025 -.008 .148

p .805 .933 .106

N 99 121 121

Yes benefit phi -.041 .010 .130

p .689 .916 .162

N 98 118 118

No benefit phi .048 .002 -.226*

p .639 .984 .014

N 98 118 118


Appendix D: Study 2; Questionnaire American Respondents X

Appendix D: Study 2; Questionnaire American Respondents

Please remember the last time that you were in a store choosing between two or more varieties of the same product (for example between different shirts, snacks or different brands of detergent). Answer the following questions about this experience. What did you want to buy?

How long ago did this happen?

This week

Last week

Last month

This winter

In the past year

More than a year ago I am satisfied with the choice I made.

Completely Agree

Mostly Agree

Slightly Agree

Slightly Disagree

Mostly Disagree

Completely Disagree Which of the following did you consider?

not buying the product

postponing the decision

none of the above How many alternatives did the store(s) offer? (please respond with a concrete number)

I was satisfied with the offered amount of choice.

Appendix D: Study 2; Questionnaire American Respondents XI

Completely Agree

Mostly Agree

Slightly Agree

Slightly Disagree

Mostly Disagree

Completely Disagree How many alternatives did you consider? (again, please respond with a concrete number)

Making the decision was...

Very easy

Rather easy

Neither easy nor difficult

Rather difficult

Very difficult For this product it is important to choose the right one.

Completely Agree

Mostly Agree

Slightly Agree

Slightly Disagree

Mostly Disagree

Completely Disagree I knew a lot about the product.

Completely Agree

Mostly Agree

Slightly Agree

Slightly Disagree

Mostly Disagree

Completely Disagree

Appendix E: Study 2; Questionnaire Dutch Respondents XII

Appendix E: Study 2; Questionnaire Dutch Respondents

Retail Consumption Choice - Version 1

ImaginePlease remember the last time that you were in a store choosing between two or more varieties of the same product (for

example between different shirts, snacks or different brands of detergent). Answer the following questions about this

experience.

What did you want to buy?

Was there a special reason why you had to choose which alternative to purchase?

Please indicate your agreement with each of these statements.

Completely

Agree

Mostly

Agree

Slightly

Agree

Slightly

Disagree

Mostly

Disagree

Completely

Disagree

I considered not buying the product.

I would buy the product again.

I was positively surprised by the product.

I considered postponing the decision.

I am satisfied with the choice I made.

How long ago did this happen?

Did you buy the product?

Appendix E: Study 2; Questionnaire Dutch Respondents XIII


Did you compare products from different stores?

Yes No

In how many stores did you look at the assortment for this product while choosing?

How many alternatives did the store(s) offer?

How different were the offered alternatives from each other?

Not at all Very little Somewhat Rather Extremely

Please rank what differences there were between the offered alternatives (1=here products differ most; 6=on this the alternatives differ least).

Functionalty/design/taste Product quality Package size

Product price Brand Company image

The following questions are about all the products the store offered in this product category.

Please indicate your agreement with each statement

Completely

Agree

Mostly

Agree

Slightly

Agree

Slightly

Disagree

Mostly

Disagree

Completely

Disagree

All alternatives were placed together.

The store(s) offered more variety than I expected.


It was easy to find the products in the store(s).

Appendix E: Study 2; Questionnaire Dutch Respondents XIV


Decision Feelings

Please indicate to what extent you agree with the followng statements.

Completely

Agree

Mostly

Agree

Slightly

Agree

Slightly

Disagree

Mostly

Disagree

Completely

Disagree

I wasted time choosing between the alternatives.

Making the decisions was stressful.

I feel satisfied with my decision process.

I felt overwhelmed by the amount of products

available.

Choosing between the alternatives was frustrating.

Making the decision was ...

Very easy Rather easyNeither easy nor

difficultRather difficult Very difficult

How much time did you take for this decision?

Less than 5 minutesBetween 5 and 10

minutes

Between 10 and 30

minutes

More than half an

hour


Post-Purchase Completely

Agree

Mostly

Agree

Slightly

Agree

Slightly

Disagree

Mostly

Disagree

Completely

Disagree

The amount of alternatives available increased my

expectations.

I have regretted I bought this alternative.

After deciding, I still looked at new alternatives.

Because I chose I am responsible for my

satisfaction with this product.

After purchasing, I thought of alternatives that I

could have bought instead.

Involvement

Please indicate the extent to which you agree with each statement.

Completely

Agree

Mostly

Agree

Slightly

Agree

Slightly

Disagree

Mostly

Disagree

Completely

Disagree

This product influences how others see you.

For this product it is difficult to choose the right

one.

For this product it is important to choose the right

one.

I can't say I particularly like this product.

The product is very important to me.

The product was related to one of my

interests/hobbies.

Appendix E: Study 2; Questionnaire Dutch Respondents XV


Purchase

Please indicate your agreement with each of the following statements.

Completely

Agree

Mostly

Agree

Slightly

Agree

Slightly

Disagree

Mostly

Disagree

Completely

Disagree

I believe I am capable of making great decisions.

I had not bought such a product before.

I had previously used some of the alternatives.

Special offers influenced my choice.

I planned to buy this product.

The product I wanted was not there.

I made more effort than others to choose the best

alternative available.

I closely examined and compared the alternatives.

I took more time than most others to make this

decision.

There were multiple alternatives that I liked.

The available variety changed my original choice.

I made the decision based on one simple criteria

(such as price, quality, familiarity, brand etc)

I knew a lot about the product.

Once I found the product I looked for I bought it.


Please indicate to what extent you agree with the followng statements.

Completely

Agree

Mostly

Agree

Slightly

Agree

Slightly

Disagree

Mostly

Disagree

Completely

Disagree

For basic products (such as milk, flour, sugar and

water) no product brand variation is needed.

The products I buy have a large influence on my

life.

Having more choices increases my personal

freedom.

Product choices enable me to show who I am.

Having more choices increases my happiness.

Having more choices enables me to do better.

Being able to choose from multiple alternatives

increases my control over my life.

Having more options makes my decisions better.

Over the past years more product alternatives

have become available to me.

I like making choices.

Culture

Appendix E: Study 2; Questionnaire Dutch Respondents XVI


General QuestionsWhat is your gender?

Male Female

How old are you?

Please select what country you are from.

the Netherlands Germany Spain Other

If your country was not in the list, please indicate what country you live in.

In what kind of area do you live?

Rural area, village or

small town (<20.000)

Small city

(20.000-100.000)

City

(100.000-500.000)

Large city (over

500.000)

How experienced a shopper are you?

Not at all A little Somewhat Rather Very Extremely

How often do you have difficulty deciding between alternatives?

Never Hardly ever Sometimes Regularly Often Almost always

Appendix F: Study 2; Extra Information Cross-Cultural Comparison XVII

Appendix F: Study 2; Extra Information Cross-Cultural Comparison

Table 14: Recalled product type by nationality.

Product Type

FMCG-Food Apparel Electronics Other Total

USA 70 (39.1%) 40 (22.3%) 18 (10.1%) 51 (28.5%) 179 (100%)

NL 73 (39.0%) 48 (25.7%) 26(13.9%) 40 (21.4%) 187 (100%)

Total 143 (39.1%) 88 (24.0%) 44 (12.0%) 91 (24.9%) 366 (100%)

Table 15: Recalled product type by gender.

Product Type

FMCG-Food Apparel Electronics Other Total

Women 79 (43.9%) 43 (23.9%) 7 (3.9%) 51 (28.3%) 180 (100%)

Men 64 (34.4%) 45 (24.2%) 37 (19.9%) 40 (21.5%) 186 (100%)

Total 143 (39.1%) 88 (24.0%) 44 (12.0%) 91 (24.9%) 366 (100%)

Table 16: Age of the memory by product type.

Age of the memory

This week Last week This month Older Total

Prod

uct t

ype

FMCG-Food 99 (68.8%) 34 (23.6%) 11 (7.6%) 0 (0%) 144 (100%)

Fashion 37 (42.0%) 20 (22.7%) 24 (27.3%) 7 (8.0%) 88 (100%)

Electronics 12 (27.3%) 8 (18.2%) 15 (34.1%) 9 (20.5%) 44 (100%)

Other 38 (41.3%) 32 (34.8%) 14 (15.2%) 8 (8.7%) 92 (100%)

Total 186 (50.5%) 94 (25.5%) 64 (17.4%) 24 (6.5%) 368 (100%)

Appendix F: Study 2; Extra Information Cross-Cultural Comparison XVIII

Table 17: Age of the memory and decision difficulty for Dutch.

Ease

Very easy Rather easy Neither Difficult Total

Age

of

the

mem

ory

This week 7 (9.7%) 37 (51.4%) 13 (18.1%) 15 (20.8%) 72 (100%)

Last week 6 (10.7%) 28 (50.0%) 15 (26.8%) 7 (12.5%) 56 (100%)

Last month 0 (0%) 19 (43.2%) 18 (40.9%) 7 (15.9%) 44 (100%)

Longer ago 0 (0%) 8 (42.1%) 4 (21.1%) 7 (36.8%) 19 (100%)

Total 13 (6.8%) 92 (48.2%) 50 (26.2%) 36 (18.8%) 191 (100%)

Table 18: Importance to choose right by nationality.

USA NL Total

For

this

pro

duct

it is

im

port

ant t

o ch

oose

rig

ht. Completely Agree 76 (41.5%) 42 (22.5%) 118 (31.9%)

Mostly Agree 71 (38.8%) 60 (32.1%) 131 (35.4%)

Slightly Agree 26 (14.2%) 30 (16.0%) 56 (15.1%)

Slightly Disagree 9 (4.9%) 17 (9.1%) 26 (7.0%)

Mostly Disagree 0 (0%) 20 (10.7%) 20 (5.4%)

Completely Disagree

1 (.5%) 18 (9.6%) 19 (5.1%)

Total 183 (100%) 187 (100%) 370 (100%)

Table 19: Importance to choose right by product type.

Importance

Total

Very Rather Neither Not

Prod

uct t

ype

FMCG-Food

27 (18.9%) 47 (32.9%) 26 (18.2%) 43 (30.1%) 143 (100%)

Fashion 31 (35.2%) 35 (39.8%) 12 (13.6%) 10 (11.4%) 88 (100%)

Electronics 21 (47.7%) 16 (36.4%) 4 (9.1%) 3 (6.8%) 44 (100%)

Other 37 (40.7%) 32 (35.2%) 13 (14.3%) 9 (9.9%) 91 (100%)

Total 116 (31.7%) 130 (35.5%) 55 (15.0%) 65 (17.8%) 366 (100%)

Appendix F: Study 2; Extra Information Cross-Cultural Comparison XIX

Table 20: Product knowledge and nationality.

USA NL Total

I kn

ew a

lot a

bout

the

prod

uct.

Completely Agree 63 (50.4%) 23 (12.3%) 86 (27.6%)

Mostly Agree 37 (29.6%) 41 (21.9%) 78 (25.0%)

Slightly Agree 21 (16.8%) 47 (25.1%) 68 (21.8%)

Slightly Disagree 4 (3.2%) 40 (21.4%) 44 (14.1%)

Mostly Disagree 0 (0%) 26 (13.9%) 26 (8.3%)

Completely Disagree 0 (0%) 10 (5.3%) 10 (3.2%)

Total 125 (100%) 125 (100%) 187 (100%)

Table 21: Product knowledge and importance.

I knew a lot about the product.

Completely agree

Rather agree

Slightly agree

Slightly disagree

Disagree Total

For

this

pro

duct

it is

impo

rtan

t to

choo

se r

ight

.

Completely agree

45 17 16 7 4 89

(50.6%) (19.1%) (18.0%) (7.9%) (4.5%) (100%)

Rather agree 27 43 23 12 10 115

(23.5%) (37.4%) (20.0%) (10.4%) (8.7%) (100%)

Slightly agree 7 11 16 10 3 47

(14.9%) (23.4%) (34.0%) (21.3%) (6.4%) (100%)

Slightly disagree

1 3 9 7 4 24

(4.2%) (12.5%) (37.5%) (29.2%) (16.7%) (100%)

Disagree 6 2 6 9 16 39

(15.4%) (5.1%) (15.4%) (23.1%) (41.0%) (100%)

Total 86 76 70 45 37 314

(27.4%) (24.2%) (22.3%) (14.3%) (11.8%) (100%)

Appendix F: Study 2; Extra Information Cross-Cultural Comparison XX

Table 22: Assortment evaluation and nationality.

American Dutch Total

I w

as s

atis

fied

wit

h th

e of

fere

d am

ount

of

cho

ice.

Completely Agree 66 (52.8%) 53 (28.8%) 119 (38.5%)

Mostly Agree 39 (31.2%) 34 (18.5%) 111 (35.9%)

Slightly Agree 10 (8%) 34 (18.5%) 44 (14.2%)

Slightly Disagree to Completely Disagree

8 (8%) 25 (13.6%) 35 (10.3%)

Total 125 (100%) 184(100%) 309 (100%)

Table 23: Assortment evaluation and satisfaction with choice.

Satisfaction with choice

Total

Completely Mostly Less positive

Eva

luat

ion

asso

rtm

ent

Completely satisfied 81 (48.5%) 30 (27.5%) 8(25.0%) 119 (38.6%)

Mostly satisfied 56 (33.5%) 47 (43.1%) 8 (25.0%) 111 (36.0%)

Slightly satisfied 15 (9.0%) 20 (18.3%) 9 (28.1%) 44 (14.3%)

Not satisfied 15 (9.0) 12 (11.0%) 7 (21.9%) 34 (11.0%)

Total 167 (100%) 109 (100%) 32 (100%) 308 (100%)

Table 24: Assortment evaluation and satisfaction with choice by nationality.

Satisfaction with choice

Completely Mostly Less positive Total

USA

Eva

luat

ion Very positive 54 (72.0%) 10 (27.8%) 2 (14.3%) 66 (52.8%)

Rather positive 14 (18.7%) 21 (58.3%) 4 (28.6%) 39 (31.2%)

Worse 7 (9.3%) 5 (13.9%) 8 (57.1%) 20 (16.0%)

Total 75 (100%) 36 (100%) 14 (100%) 125 (100%)

NL

Eva

luat

ion Very positive 27 (29.3%) 20 (27.4%) 6 (33.3%) 53 (29.0%)

Rather positive 42 (45.7%) 26 (35.6%) 4 (22.2%) 72 (39.3%)

Worse 23 (25.0%) 27 (37.0%) 8 (44.4%) 58 (31.7%)

Total 92 (100%) 73 (100%) 18 (100%) 183 (100%)

Appendix F: Study 2; Extra Information Cross-Cultural Comparison XXI

Table 25: Assortment evaluation and knowledge.

Assortment Evaluation

Very good Rather good Worse Total I

knew

a lo

t abo

ut th

e pr

oduc

t. Completely Agree 36 (61.0%) 14 (23.7%) 9 (15.3%) 59 (100%)

Mostly Agree 20 (33.3%) 21 (35.0%) 19 (31.7%) 60 (100%)

Slightly Agree 14 (25.0%) 23 (41.1%) 19 (33.9%) 56 (100%)

Slightly Disagree 10 (23.3%) 19 (44.2%) 14 (32.6%) 43 (100%)

Mostly Disagree 8 (32.0%) 10 (40.0%) 7 (28.0%) 25 (100%)

Completely Disagree 4 (36.4%) 4 (36.4%) 3 (27.3%) 11 (100%)

Total

92 (36.2%) 91 (35.8%) 71 (28.0%) 254 (100%)

Table 26: Assortment evaluation and product knowledge by nationality.

Assortment evaluation

Very positive

Rather positive

Less positive Total

USA

‘I k

new

a lo

t ab

out t

he

prod

uct’

Completely agree

27 (73.0%) 6 (16.2%) 2 (5.4%) 37 (100%)

Mostly agree 6 (31.6%) 7 (36.8%) 5 (26.3%) 19 (100%)

Less agreement 2 (15.4%) 4 (30.8%) 6 (46.2%) 13 (100%)

Total 35 (52.2%) 18 (26.9%) 14 (20.9%) 67 (100%)

NL

‘I k

new

a lo

t abo

ut th

e pr

oduc

t’

Completely agree

9 (37.5%) 8 (33.3%) 7 (29.2%) 24 (100%)

Mostly agree 12 (29.3%) 14 (34.1%) 15 (36.6%) 41 (100%)

Slightly agree 12 (25.5%) 18 (38.3%) 17 (36.2%) 47 (100%)

Slightly disagree

10 (25.6%) 19 (48.7%) 10 (25.6%) 39 (100%)

Disagree 12 (33.3%) 14 (38.9%) 10 (27.8%) 36 (100%)

Total 55 (29.4%) 73 (39.0%) 59 (31.6%) 187 (100%)

Appendix F: Study 2; Extra Information Cross-Cultural Comparison XXII

Table 27: Assortment evaluation and decision importance.


Very positive

Rather positive

worse Total

For

this

pro

duct

it is

im

port

ant t

o ch

oose

the

righ

t on

e.

Completely Agree 52 (54.7%) 25 (26.3%) 18 (18.9%) 95 (100%)

Mostly Agree 32 (30.5%) 41 (39.0%) 32 (30.5%) 105 (100%)

Slightly Agree 18 (36.0%) 20 (40.0%) 12 (24.0%) 50 (100%)

Slightly Disagree 4 (17.4%) 10 (43.5%) 9 (39.1%) 23 (100%)

Mostly Disagree 5 (25.0%) 11 (55.0%) 4 (20.0%) 20 (100%)

Completely Disagree

9 (50.0%) 5 (27.8%) 4 (22.2%) 18 (100%)

Total 120 (38.6%) 112 (36.0%) 79 (25.4%) 311 (100%)

Table 28: Assortment evaluation and decision importance by nationality.


Very positive

Rather positive

Less positive Total

USA

‘For

this

pro

duct

it

is im

port

ant t

o ch

oose

the

righ

t on

e.’

Completely agree

37 (67.3%) 14 (25.5%) 4 (7.3%) 55 (100%)

Mostly agree 19 (43.2%) 18 (40.9%) 7 (15.9%) 44 (100%)

Slightly agree and less

10 (38.5%) 7 (26.9%) 9 (34.6%) 26 (100%)

Total 66 (52.8%) 39 (31.2%) 20 (16.0%) 125 (100%)

NL

‘For

this

pro

duct

it

is im

port

ant t

o ch

oose

the

righ

t on

e.’

Completely agree

15 (37.5%) 11 (27.5%) 14 (35.0%) 40 (100%)

Mostly agree 13 (21.3%) 23 (37.7%) 25 (41.0%) 61 (100%)

Slightly agree 11 (35.5%) 15 (48.4%) 5 (16.1%) 31 (100%)

Disagree 15 (27.8%) 24 (44.4%) 15 (27.8%) 54 (100%)

Total 54 (29.0%) 73 (39.2%) 59 (31.7%) 186 (100%)

Appendix F: Study 2; Extra Information Cross-Cultural Comparison XXIII

Table 29: Decision ease and remembered assortment size.

(I) Ease** (J) Ease** Mean Difference (I-J) SE p

1 2 -,960* ,452 ,035

3 -1,902* ,525 ,000

4 -1,328* ,568 ,020

2 1 ,960* ,452 ,035

3 -,942* ,433 ,030

4 -,368 ,483 ,447

3 1 1,902* ,525 ,000

2 ,942* ,433 ,030

4 ,574 ,552 ,299

4 1 1,328* ,568 ,020

2 ,368 ,483 ,447

3 -,574 ,552 ,299 Notes: * The mean difference is significant at the 0.05 level.

** Making the decision was very easy (1), rather easy (2), neither easy nor difficult (3), difficult (4).

Appendix F: Study 2; Extra Information Cross-Cultural Comparison XXIV

Table 30: Decision ease and choice set size for Americans.

(I) EASE** (J) EASE** Mean Difference (I-J) SE p

1 2 -,624 ,340 ,068

3 -1,519* ,444 ,001

4 -1,299* ,461 ,005

2 1 ,624 ,340 ,068

3 -,895* ,420 ,035

4 -,675 ,438 ,125

3 1 1,519* ,444 ,001

2 ,895* ,420 ,035

4 ,220 ,523 ,675

4 1 1,299* ,461 ,005

2 ,675 ,438 ,125

3 -,220 ,523 ,675

Notes: *. The mean difference is significant at the 0.05 level.

**Making the decision was very easy (1), rather easy (2), neither easy nor

difficult (3), difficult (4).

Table 31: Decision importance and decision ease.

Decision ease

Total Very easy Rather easy Neither Difficult

‘For

this

pro

duct

it is

im

port

ant t

o ch

oose

th

e ri

ght o

ne.’

Very 37 (55%) 36 (21%) 22 (28%) 24 (39%) 119 (32%)

Rather 16 (24%) 70 (42%) 24 (31%) 22 (36%) 132 (35%)

Neither 8 (12%) 27 (16%) 11 (14%) 11 (18%) 57 (15%)

Not 6 (9%) 35 (21%) 21 (27%) 4 (7%) 66 (18%)

Total 67 (100%) 168 (100%) 78 (100%) 61 (100%) 374 (1005)

Appendix F: Study 2; Extra Information Cross-Cultural Comparison XXV

Table 32: Product knowledge and decision ease.

Decision ease

Total Very easy Rather easy Neither Difficult

I kn

ew a

lot a

bout

the

prod

uct.

Completely agree 28 29 10 19 86

Mostly agree 10 41 16 11 78

Slightly agree 4 40 19 6 69

Slightly disagree 3 19 14 9 45

Mostly disagree 3 12 8 4 27

Completely disagree 1 2 3 5 11

Total 49 143 70 54 316

Table 33: Decision ease by nationality.

USA NL Total

Ease Very easy 54 (29.5%) 13 (6.9%) 67 (18.0%)

Rather easy 76 (41.5%) 91 (48.1%) 167 (44.9%)

Neither 28 (15.3%) 49 (25.9%) 77 (20.7%)

Difficult 25 (13.7%) 36 (19.0%) 61 (16.4%)

Total 183 (100%) 189 (100%) 372 (100%)

Appendix F: Study 2; Extra Information Cross-Cultural Comparison XXVI

Table 34: Satisfaction with the made choice and decision ease by nationality.

Ease

Total Very easy

Rather easy Neither Difficult

USA

Sati

sfac

tion

w

ith

choi

ce Very 44 48 12 6 110

Rather 9 22 10 12 53

Not so much 1 6 6 7 20

Total 54 76 28 25 183

NL

Satis

fact

ion

wit

h ch

oice

Very 7 53 18 16 94

Rather 5 32 22 16 75

Not so much 1 7 10 3 21

Total 13 92 50 35 190

Table 35: Satisfaction with the made choice and considering purchase deferral by nationality.

Considered not buying

Total No Yes

USA Satisfaction Very 91 (61.9%) 19 (52.8%) 110 (60.1%)

Rather 43 (29.3%) 10 (27.8%) 53 (29.0%)

Not so much 13 (8.8%) 7 (19.4%) 20 (10.9%)

Total 147 (100%) 36 (100%) 183 (100%)

NL Satisfaction Very 64 (59.3%) 29 (38.2%) 93 (50.5%)

Rather 38 (35.2%) 34 (44.7%) 72 (39.1%)

Not so much 6 (5.6%) 13 (17.1%) 19 (10.3%)

Total 108 (100%) 76 (100%) 184 (100%)

Appendix F: Study 2; Extra Information Cross-Cultural Comparison XXVII

Table 36: Satisfaction with the made choice and considering postponing the decision by nationality.

Considered Postponing

Total No Yes

USA Satisfaction Very 86 (63.2%) 24 (51.1%) 110 (60.1%)

Rather 38 (27.9%) 15 (31.9%) 53 (29.0%)

Not so much 12 (8.8%) 8 (17.0%) 20 (10.9%)

Total 136 (100%) 47 (100%) 183 (100%)

NL Satisfaction Very 74 (56.5%) 18 (34.0%) 92 (50.0%)

Rather 44 (33.6%) 28 (52.8%) 72 (39.1%)

Not so much 13 (9.9%) 7 (13.2%) 20 (10.9%)

Total 131 (100%) 53 (100%) 184 (100%)

Table 37: Satisfaction with choice and product knowledge.

Satisfaction

Total Very Rather Less

I kn

ew a

lot a

bout

the

prod

uct.

Completely agree 68 (79.1%) 13 (15.1%) 5 (5.8%) 86 (100%)

Mostly agree 45 (57.7%) 27 (34.6%) 6 (7.7%) 78 (100%)

Slightly agree 27 (39.7%) 30 (44.1%) 11 (16.2%) 68 (100%)

Slightly disagree 17 (38.6%) 22 (50.0%) 5 (11.4%) 44 (100%)

Disagree 15 (40.5%) 14 (37.8%) 8 (21.6%) 37 (100%)

Total 172 (55.0%) 106 (33.9%) 35 (11.2%) 313 (100%)

Appendix F: Study 2; Extra Information Cross-Cultural Comparison XXVIII

Table 38: Satisfaction with choice and choice importance by nationality.

Satisfaction

Very Rather Less Total

USA

Impo

rtan

ce Very 56 (73.7%) 13 (17.1%) 7 (9.2%) 76 (100%)

Rather 40 (56.3%) 23 (32.4%) 8 (11.3%) 71 (100%)

Less 14 (38.9%) 17 (47.2%) 5 (13.9%) 36 (100%)

Total 110 (60.1%) 53 (29.0%) 20 (10.9%) 183 (100%)

NL

Impo

rtan

ce Very 26 (61.9%) 12 (28.6%) 4 (9.5%) 42 (100%)

Rather 31 (52.5%) 23 (39.0%) 5 (8.5%) 59 (100%)

Less 36 (42.4%) 37 (43.5%) 12 (14.1%) 85 (100%)

Total 93 (50.0%) 72 (38.7%) 21 (11.3%) 186 (100%)

Appendix G: Study 2; Extra Information Analysis Dutch Respondents XXIX

Appendix G: Study 2; Extra Information Analysis Dutch Respondents

Table 39: Ability to express identity by acceptance little variety basic goods.

For basic products (such as milk, flour, sugar and water) no product

brand variation is needed.

Total Agree Disagree

Prod

uct c

hoic

es e

nabl

e m

e to

sho

w w

ho I

am

.

Completely agree 8 (10.0%) 4 (5.1%) 12 (7.5%)

Mostly agree 14 (17.5%) 14 (17.7%) 28 (17.6%)

Slightly agree 23 (28.8%) 33 (41.8%) 56 (35.2%)

Slightly disagree 19 (23.8%) 8 (10.1%) 27 (17.0%)

Mostly disagree 11 (13.8%) 8 (10.1%) 19 (11.9%)

Completely disagree 5 (6.3%) 12 (15.2%) 17 (10.7%)

Total 80 (100%) 79 (100%) 159 (100%)

Table 40: Choice identity and self-expression.

The products I buy have a large influence on my life.

Total

Completely Agree

Slightly Agree

Slightly Disagree

Mostly Disagree

Prod

uct c

hoic

es e

nabl

e m

e to

sho

w w

ho I

am

. Completely agree

14 (42.4%) 15 (32.6%) 5 (13.2%) 6 (14.3%) 40 (25.2%)

Slightly agree

12 (36.4%) 17 (37.0%) 15 (39.5%) 11 (26.2%) 55 (34.6%)

Slightly disagree

5 (15.2%) 6 (13.0%) 9 (23.7%) 8 (19.0%) 28 (17.6%)

Mostly disagree

2 (6.1%) 8 (17.4%) 9 (23.7%) 17 (40.5%) 36 (22.6%)

Total 33 (100%) 46 (100%) 38 (100%) 42 (100%) 159 (100%)

Appendix G: Study 2; Extra Information Analysis Dutch Respondents XXX

Table 41: Benefits associated to choice by gender.

Like choosing

Increases freedom

Increases decision quality

Enables doing better

Increases control

Increases happiness

men

Completely agree

15.6% 15.2% 17.9% 12.8% 12.7% 13.9%

Mostly agree 46.8% 38.0% 32.1% 38.5% 26.6% 27.8%

Slightly agree 20.8% 25.3% 21.8% 19.2% 30.4% 27.8%

Slightly disagree

11.7% 8.9% 17.9% 20.5% 13.9% 12.7%

Mostly disagree 2.6% 8.9% 7.7% 6.4% 7.6% 13.9%

Completely disagree

2.6% 3.8% 2.6% 2.6% 8.9% 3.8%

n 77 79 78 78 79 79

wom

en

Completely agree

11.4% 11.5% 5.1% 5.1% 3.8% 3.8%

Mostly agree 24.1% 24.4% 16.5% 16.5% 20.0% 15.0%

Slightly agree 26.6% 38.5% 26.6% 32.9% 32.5% 33.8%

Slightly disagree

16.5% 16.7% 27.8% 31.6% 21.3% 22.5%

Mostly disagree 11.4% 1.3% 16.5% 10.1% 17.5% 15.0%

Completely disagree

10.1% 7.7% 7.6% 3.8% 5.0% 10.0%

n 79 78 79 79 80 80

stat

isti

cs df 5 5 5 5 5 5

N 156 157 157 157 159 159 χ2 15.1 12.2 16.1 15.1 9.8 12.6 p .010 .032 .007 .010 .080 .027

Appendix G: Study 2; Extra Information Analysis Dutch Respondents XXXI

Table 42: Assortment evaluation and appropriateness categorization.


Total

Completely agree Slightly agree

Mostly disagree

All

alte

rnat

ives

w

ere

plac

ed

toge

ther

. Completely agree 56 (74.7%) 10 (13.3%) 9 (12.0%) 75 (100%)

Mostly agree 26 (65.0%) 13 (32.5%) 1 (2.5%) 40 (100%)

Slightly agree 13 (68.4%) 3 (15.8%) 3 (15.8%) 19 (100%)

Mostly disagree 8 (50.0%) 1 (6.3%) 7 (43.8%) 16 (100%)

Total 103 (68.7%) 27 (18.0%) 20 (13.3%) 150 (100%)

Table 43: Assortment evaluation and exceeding variety expectations.


Total

Completely agree

Slightly agree

Mostly disagree

The

sto

re(s

) of

fere

d m

ore

vari

ety

than

I

expe

cted

.

Completely agree 26 (81.3%) 4 (12.5%) 2 (6.3%) 32 (100%)

Mostly agree 26 (78.8%) 5 (15.2%) 2 (6.1%) 33 (100%)

Slightly agree 27 (75.0%) 8 (22.2%) 1 (2.8%) 36 (100%)


Mostly disagree 13 (50.0%) 2 (7.7%) 11 (42.3%) 26 (100%)

Total 104 (68.0%) 28 (18.3%) 21 (13.7%) 153 (100%)

Appendix G: Study 2; Extra Information Analysis Dutch Respondents XXXII

Table 44: Assortment evaluation and product availability.


Total

Completely agree

Slightly agree

Mostly disagree

The

pro

duct

I

wan

ted

was

not

th

ere.

Mostly agree 6 (37.5%) 7 (43.8%) 3 (18.8%) 16 (100%)


Completely disagree 72 (76.6%) 16 (17.0%) 6 (6.4%) 94 (100%)

Total 105 (68.2%) 28 (18.2%) 21 (13.6%) 154 (100%)

Table 45: Assortment evaluation and special offers.


Total

Completely Agree

Slightly Agree

Mostly Disagree

Spec

ial o

ffer

s in

flue

nced

my

choi

ce. Completely agree 17 (70.8%) 5 (20.8%) 2 (8.3%) 24 (100%)

Mostly agree 25 (92.6%) 2 (7.4%) 0 (0%) 27 (100%)

Slightly agree 16 (66.7%) 5 (20.8%) 3 (12.5%) 24 (100%)


Completely disagree 31 (64.6%) 4 (8.3%) 13 (27.1%) 48 (100%)

Total 104 (69.3%) 25 (16.7%) 21 (14.0%) 150 (100%)

Appendix G: Study 2; Extra Information Analysis Dutch Respondents XXXIII

Table 46: Assortment evaluation and increased expectations.


Total

Completely Agree

Slightly Agree

Mostly Disagree

The

am

ount

of

alte

rnat

ives

av

aila

ble

incr

ease

d m

y ex

pect

atio

ns. Completely agree 39 (76.5%) 9 (17.6%) 3 (5.9%) 51 (100%)


Mostly disagree 20 (52.6%) 8 (21.1%) 10 (26.3%) 38 (100%)

Completely disagree

20 (62.5%) 5 (15.6%) 7 (21.9%) 32 (100%)

Total 104 (68.4%) 27 (17.8%) 21 (13.8%) 152 (100%)

Table 47: Difficulties deciding and self-efficacy.

I believe I am capable of making great decisions.

Total

Completely agree Mostly agree Slightly agree

How

oft

en d

o yo

u ha

ve d

iffi

culty

de

cidi

ng b

etw

een

alte

rnat

ives

?

Never 15 (39.5%) 18 (47.4%) 5 (13.2%) 38 (100%)

Sometimes 28 (43.1%) 25 (38.5%) 12 (18.5%) 65 (100%)

Regularly 7 (19.4%) 15 (41.7%) 14 (38.9%) 36 (100%)

Often 2 (14.3%) 7 (50.0%) 5 (35.7%) 14 (100%)

Total 52 (34.0%) 65 (42.5%) 36 (23.5%) 153 (100%)

Appendix G: Study 2; Extra Information Analysis Dutch Respondents XXXIV

Table 48: Drawbacks to deciding factor loadings per gender.

All Men Women

Eigenvalue 2.250 2.224 2.259

Choosing between the alternatives was frustrating. .828 .843 .806

Making the decisions was stressful. .792 .818 .765

I felt overwhelmed by the amount of products available. .651 .666 .644

I wasted time choosing between the alternatives. .717 .634 .780

Note: Extraction Method: Principal Component Analysis.

Table 49: Decision difficulty and process satisfaction.

I feel satisfied with my decision process.

Total

Completely Agree Mostly Agree Slightly Agree

Mak

ing

the

deci

sion

was

...

Very easy 8 (72.7%) 2 (18.2%) 1 (9.1%) 11 (100%)

Rather easy 31 (40.8%) 36 (47.4%) 9 (11.8%) 76 (100%)

Less easy 19 (26.8%) 36 (50.7%) 16 (22.5%) 71 (100%)

Total 58 (36.7%) 74 (46.8%) 26 (16.5%) 158 (100%)

Table 50: Satisfaction made choice and positive surprise.

I am satisfied with the choice I made.

Total Completely

Agree Mostly Agree

Mostly Disagree

I w

as p

ositi

vely

su

rpri

sed

by th

e pr

oduc

t.

Completely Agree 23 (92.0%) 2 (8.0%) 0 (0%) 25 (100%)

Mostly Agree 26 (51.0%) 24 (47.1%) 1 (2.0%) 51 (100%)

Slightly Agree 21 (42.0%) 22 (44.0%) 7 (14.0%) 50 (100%)

Mostly Disagree 8 (26.7%) 14 (46.7%) 8 (26.7%) 30 (100%)

Total 78 (50.0%) 62 (39.7%) 16 (10.3%) 156 (100%)

Appendix G: Study 2; Extra Information Analysis Dutch Respondents XXXV

Table 51: Positive surprise and increased expectations.

The amount of alternatives available increased my expectations.

Total

Completely agree

Slightly agree

Slightly disagree

Mostly disagree

Completely disagree

I w

as p

ositi

vely

sur

pris

ed

by th

e pr

oduc

t. Completely agree

10 (40.0%)

0 (0%)

4 (16.0%)

5 (20.0%)

6 (24.0%)

25 (100%)

Mostly agree

6 (12.2%)

7 (14.3%)

12 (24.5%)

14 (28.6%)

10 (20.4%)

49 (100%)

Slightly agree

6 (12.0%)

13 (26.0%)

12 (24.0%)

13 (26.0%)

6 (12.0%)

50 (100%)

Mostly disagree

6 (20.0%)

2 (6.7%)

4 (13.3%)

8 (26.7%)

10 (33.3%)

30 (100%)

Total 28 (18.2%)

22 (14.3%)

32 (20.8%)

40 (26.0%)

32 (20.8%)

154 (100%)

Personal Affirmation in Lieu of Oath

„I hereby confirm that this master thesis was independently authored by myself,

using solely the referred sources and support. I additionally assert that this thesis

has not been part of another examination process and that it has not yet been

published in any kind.”

León, May 24th 2012

Iris van Hees