修士論文

The Effect of Customer Relationship Management Efforts on Customer Expectations: A Study of the Japanese Airline Service

2011 年 01 月 19 日

神戸大学大学院経営学研究科

所属研究室 南知惠子研究室

市場科学専攻

学籍番号 095b114b

氏 名 趙 媛媛

Master Thesis:

The Effect of Customer Relationship Management

Efforts on Customer Expectations:

A Study of the Japanese Airline Service

SallyZhao

19/01/2011

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The Effect of Customer Relationship Management Efforts on Customer Expectations: A Study of the Japanese Airline Service

Abstract

The notion of customer relationship management has been shown to be a worthwhile

strategy for targeting customers in the service industry. Bearing in mind the changeable

demands of customers, and limited corporate resources, many scholars believe that it is

necessary to consider customer’s expectations when implementing CRM in order to satisfy

customers on a continuous basis and implement CRM strategy effectively. However, based

on the literature review that I conducted in my research, it is shown that little research exists,

which studies the relationship between CRM and customer expectations directly. Therefore,

the original aspect to this paper is, it fills a theoretical gap in CRM research by focusing on

the direct relationship between CRM and customer expectations. In the practically, it sheds

the light on the importance of considering customer expectation while implementing CRM

strategy.

Generally, this research contributes to the CRM study area in the following four

aspects. 1) measured customer expectations by using the three types of relationship

benefits ,these are confidence benefits, special treatment benefits and social benefits - and

tested the western countries-based measurement in Japan, 2) based on the extensive

literature on CRM, I obtained and tested three significant CRM dimensions in B2C market.

These are affective commitment, front-office employees and loyalty programs. This research

empirically proved the possibility of researching CRM in business-to-consumer market

through these three dimensions. 3) Conducted an empirical study by using multiple

regression models to test the relationship between CRM and the three types of benefits that

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customers’ expectations to receive from their relationship with airlines. The data that used in

this research were collected from both students and alumni of Kobe University and their

friends. 4) Compared the importance of three important CRM dimensions: affective

commitment, loyalty program and front-office employees as they affect confidence, special

treatment and social benefits expected by customers in the service industry.

The findings of my research show that CRM has a positive effect on customer

expectations. Theoretically, this research tested the causality of affective commitment and

the three types of benefits. Also, confirmed the importance of the role of front-office

employees and loyalty programs in the CRM implementation. Specially, it was found that (1)

affective commitment plays the most important role when customers expect to receive

confidence benefits (2) front-office employees are the key factor affecting special treatment

and social benefits (3) a financial and non-financial rewards combined loyalty program has a

crucial effect on special treatment benefits and social benefits received by customers.

Besides the theoretical implications, practically, if we consider the different ways in which

CRM affects customer expected benefits, it is clear that managers need to consider their

priorities when allocating their corporate resources in order to implement CRM more

effectively.

In the end, based on the result of this research I addressed future research may

further investigate the relationship between CRM, customer expectations and customer

intentions.

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Table of contexts

Acknowledge ⅲ

CHAPTER 1 Introduction 1

CHAPTER 2 Theoretical Backgrounds 4

1. Trends of Customer Relationship Management 4

2. Dimensions of Customer Relationship Management 8

2-1. Affective commitment 10

2-2. Front-office employees 11

2-3. Loyalty program 12

3. The Consequences of CRM 13

4. Customer Expectations in Customer Relationship Management

Research 17

5. Summary 19

CHAPTER 3 Research Questions and Hypotheses 21

Research Questions 21

Hypotheses 22

CHAPTER 4 Methodology 28

1. Research Setting 28

2. Variables 28

3. Data Collection 31

4. Operationalization of Constructs 34

5. Research Design 35

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CHAPTER 5 Results of Analyses and Findings 37

1. Results of Factor Analysis of CRM-related Factors 37

2. Results of Factor Analysis of Customer Expectation-related Factors 38

3. Hypotheses Testing- Results in Multiple Regression Analyses 39

3-1. Multicollinearity Testing 39

3-2. Result of Multiple Regression Analyses of Confidence Benefits, Special

Treatment Benefits and Social Benefits 40

4. Summary of Findings 42

CHAPTER 6 Conclusion 44

1. Contribution 44

2. Theoretical Implication and Practical Implication 45

2-1. Theoretical Implication 46

2-2. Practical Implication 48

CHAPTER 7 Limitations and Future Research 52

Bibliography 53

Appendix 1 Variables and Operational Definitions 62

Appendix 2 English Questionnaire 64

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Acknowledge

Special thanks to my supervisor professor Chieko Minami, for her valuable guidance she

has given me throughout my two years study in Kobe University and her precious comments

on this dissertation. During the past two years she made me realize how interesting it is to

learn to become a scholar. Her advice and encouragement is very much appreciated as well.

Many thanks to all of my teachers in business and administration department of Kobe

University thank you for guiding me into the research world. Specially thanks to professor

Katsuyoshi Takashima, professor Makoto Matsuo and professor Kiyoshi Takahashi for giving

their valuable time and consolation.

Thanks to researcher Doctor Morimura, doctor candidates Mr. Hou and Mr. Allam of Kobe

University for their valuable advice.Thanks to Smith Philip BA from Cambridge University for

helping me proofread my English writings.Thanks to the fulltime students, MBA students, and

alumina of business and administration department of Kobe University for their valuable time

and great cooperation when answering my survey.

Most importantly, thanks my parents. I cannot finish this thesis and my research without

your continuous support and encouragement.

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CHAPTER 1 Introduction

From the mid-1900s until recently, research on customer relationship management

(CRM) has been prominent amongst academics and executives. It has been proven that

CRM is closely related to loyalty marketing, and can be used by companies as an effective

marketing strategy to target customers (Minami 2006, Rust and Chung, 2006, Sun et al,

2006). According to Sun (2006), CRM is about introducing the right product to the right

customer at the right time through the right channel to satisfy customers' evolving demands,

even before they realize they need them. CRM has been implemented in different industries

in the last decade, most notably in the service industry. Claycomb and Martin (2002) pointed

out that the significant role CRM plays in increasing the loyalty of profitable customers is of

prime importance for most service companies. Meanwhile, within the context of the service

economy, Dimitriadis and Stevens (2008) have highlighted how CRM systems and

technologies provide multiple opportunities to deal with service characteristics like

intangibilities, inseparability, heterogeneity and perishability (Parasuraman et, al, 1985).

Moreover, Lovelook and Wirtz (1996) have pointed out that well-implemented CRM systems

can offer a unified customer interface that delivers customization and personalization to

satisfy customers. Indeed, with each transaction, the relevant account details, knowledge of

customer preferences and past transactions, or history of a service problem, are at the

fingertips of the person serving the customer. As a result, service companies are able to

provide customers with better services, while customers are likely to expect more benefits in

their relationship with service companies.

Based on the well-accepted argument that CRM creates value for customers, and

customer loyalty brings value to firms, Minami and Dawson (2007) clarified that CRM

implementation leads to customer satisfaction, customer satisfaction results in customer

retention, and customer retention will bring financial rewards to companies. It can be seen

that it is crucial to achieve customer satisfaction in the first place when implementing CRM

strategy. According to Stefanou, Sarmaniotis and Stafyla (2003), customer satisfaction is

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related to perceived performance and expectations, and if performance matches

expectations or exceeds them, the customer is satisfied or highly satisfied respectively. From

the customers’ perspective, it is not difficult to imagine that customers have their own

different kinds of service expectations. For instance, when using an airline service, some

people want to be upgraded to a higher status of loyalty program, while others hope to be

able to buy cheaper tickets. Moreover, it could be counter-productive to respond to all

customer expectations in the same way, or to perceive them as unchangeable. By

accumulating consumption experiences, companies receive thorough customer information

through CRM, and this may create further benefits for customers, e.g. Amazon’s analysis of

which other books customers have bought with a similar profile to yours and customer rating

of books.

There is still limited research focusing on whether CRM has effects on customer

expectations, or whether it has an equal influence on customers' expectations of receiving all

types of benefits when they are in a continuous relationship with service companies

(Dimitriadis and Stevens, 2008, Hennig-Thurau and Hansen, 2000). I suggest that it will be

worthwhile to examine customer expectations, since these expectations will not only be a

crucial factor in influencing their overall satisfaction with service companies, but also affect

their decision to stay with the company in the future (Lemon, White and Winer, 2002

Lovelook and Wirtz, 1996, Johnson and Mathews, 1997). Furthermore, I also believe that

determining how customer expectations are influenced by CRM efforts will help companies

implement CRM strategy more effectively. For instance, if it is found that customers’

perception of service companies’ front-office employees play the most important role in

influencing customers ‘expectations of receiving special treatment benefits, service

companies should pay much more attention to the role of their front-office staff in the CRM

implementation process.

Therefore, this research aims to clarify the effect of CRM efforts on customer

expectations (the benefits customers expect to receive) from the perspective of customers in

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the service industry. First, the theoretical background of this research is provided, in which

the trends and dimensions of CRM, variables that will be used in this research as CRM

dimensions, the outcome of CRM, as well as a brief description of the concepts related to

customer expectation, are reviewed. Then, research questions and hypotheses are

described, followed by the introduction on research methodology. Next, the results of the

analyses, findings, and contribution of the research, as well as the theoretical and

managerial implications of the findings, are described. Finally, limitations and suggestions for

future research are discussed.

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CHAPTER 2 Theoretical Background

1. Trends of Customer Relationship Management

Over the past decade, there has been an explosion of interest in customer

relationship management (CRM) among both academics and company executives (e.g.

Reinartz, Krafft and Hoyer, 2004, Payne and Frow, 2005). CRM means different things to

different people (See Table 1). According to Hoskins (2003), it is possible to develop a

clearer understanding of CRM by recalling its origins, the principles that drove its

development and the theoretical arguments about how to recognize it.

Generally, CRM has its origins in two unrelated locations (Dowling, 2002). The first

was in the United States, where CRM was driven by technology. According to Payne and

Frow (2005), the term “customer relationship management” emerged in the information

technology (IT) vendor and practitioner communities in the mid-1990s. Usually, it is used to

describe technology-based customer solutions, for example in sales force automation (SFA).

Zablan, Bellenger and Johnston (2004) believed that it is important to emphasize that

technology plays a substantial role in CRM efforts among other things, since it seamlessly

links front (e.g. sales) and back office (e.g. logistics) functions to provide efficient and

effective management, with interactions across different customer touch-points. It can be

seen that technology is a very important part of CRM from the standpoint of research trends

in the United States. Working as a technical tool, CRM can control customer data and allow

the company to understand customers’ needs, and more specifically their potential needs, so

that they can increase the efficiency and effectiveness of targeting potential customers, as

well as increasing customer satisfaction.

The other place CRM developed was in business-to-business marketing within

Scandinavia and Northern Europe (Dawling, 2002). The IMP (Industrial Marketing and

Purchasing) Group played a significant role in developing an understanding about the nature

and effects of building long-term, trust-based relationships with customers. There is a

widespread consensus that the research on CRM derives from the research into relationship

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marketing (Kondo, 2008, Payneand Frow, 2005, Minamiand Dawson, 2007, Parvatiyar and

Sheth, 2001). Berry (1983) initially coined the term ‘relationship marketing’, he defined it as

“attracting, maintaining and, in multi-service organizations, enhancing customer

relationships.” Parvatiyarand Sheth (2001) pointed out that the terms ‘relationship marketing’

and ‘CRM’ are often used interchangeably. Minami and Dawson (2007) emphasized that

CRM has been regarded as an applied area of the theory of relationship marketing.

Furthermore, according to Das (2009), both RM and CRM strongly focus on individual buyer-

seller relationships; they accept that these relationships are longitudinal in nature, and that

both parties benefit in the process (Sin et al., 2005). Similarly, Light (2001) stated that CRM

evolved from business processes such as relationship marketing and an increased emphasis

on improved customer retention through the effective management of customer relationships.

Moreover, Kondo (2008) highlighted that CRM can be viewed as a derivative of relationship

marketing. Additionally, the benefits issue that results from CRM is emphasized by some

researchers. According to Zablah, Bellenger and Johnston (2004), CRM is concerned with

the development and maintenance of a portfolio of profit-maximizing customer relationships

that is likely to include exchange relationships that vary along the transactional-relationships

continuum. Finally, CRM strategies will not be effective if they do not deliver positive

outcomes, profit for organizations, and competitive value and quality for customers (Zineldin,

2006). In short, CRM can be regarded, to some degree, as a subset of relationship

marketing that brings benefits to both customers and companies.

However, when extending relationship marketing to the mass consumer market,

O’Malley and Tynan (2000) argued that the emotional dimension of consumers should be

considered in relationship building. Therefore, when researching CRM in the business-to-

consumer markets, the emotional factors of customers are also considered. For instance,

commitment is treated as the most prominent customer perception in representing the

strength of a relationship between suppliers and customers (Moorman, Zaltman, and

Desphande, 1992, Morgan and Hunt, 1994). Affective commitment is used as one of the

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customers’ relationship perceptions by Verheof (2003) when researching the relationship

between customer relationship management efforts on customer retention and customer

share development.

When it comes to the research of CRM in Japan, Minami and Dawson (2007)

mention that this has taken a different direction from American and British based research.

According to Minami (2006), CRM was introduced to Japan by consulting firms in the late

1990s. Most researchers approach CRM as an example of database marketing. The

research stream in Japan had mainly focused on techniques of data analysis and data

mining aspects of CRM, although the holistic CRM market has grown dramatically. Therefore,

in her research, she studied CRM from a marketing approach, and examined the

relationships between CRM research and relationship marketing, loyalty marketing, and

service marketing. Moreover, based on the consideration of building relationships with

customers and pursuing profitability, CRM is treated as a technology-based customer-loyalty

construction program in her research.

Based on the review of the important definitions and main threads of CRM, we can

summarize that

Technology and loyalty programs play significant roles in CRM strategy.

People-related factors cannot be ignored in the successful implementation of CRM.

Instead of the one-time transaction relationship, CRM means to build up a long-term

relationship.

Most authors view CRM as a combination of strategy and information systems. They

believe that the attention should be on customers in order to serve them better and

bring value to both customers and companies.

CRM focuses on selected key, profitable customers rather than every customer.

Since this research tends to focus on the effects of CRM from the customer’s

perspective, I would like to view CRM according to Payne and Frow's definition (2005), Swift

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(2000), Greenberg (2001) and Minami (2006), which is as follows:

CRM is an IT-based strategic approach requiring a cross-functional integration of

processes, people and technology that seeks to understand and influence customer behavior

through meaningful communication so as to target customers more effectively in the long-

term. CRM is closely related to relationship marketing and loyalty programs. The purpose of

it is to deepen companies’ understanding of the needs and wants of their customers in order

to bring both of them benefits.

Table 1: Summary of some representative definitions of CRM

Reference Definition

Parvitiyar

and Sheth

(2001)

CRM is comprehensive strategy and process of acquiring, retaining, and

partnering with selective customers to create superior value for the

company and the customer.

Payne and

Frow (2005)

CRM is a strategic approach that is concerned with creating improved

shareholder value through the development of appropriate

relationships with key customers and customer segments.

CRM unites the potential of relationship marketing strategies and IT to

create profitable, long-term relationships with customers and other key

stakeholders.

CRM provides enhanced opportunities to use data and information to

both understand customers and co-create value with them. This

requires a cross-functional integration of processes, people,

operations, and marketing capabilities that is enabled through

information, technology, and applications.

Swift (2000) CRM is an enterprise approach to understanding and influencing customer

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(Source: created by the author)

2. Dimensions of Customer Relationship Management

Distinct dimensions of customer relationship management have been used in

different research. Yim, Anderson and Swaminathan (2005) used focusing on key customers,

incorporating CRM-based technology, managing knowledge and organizing around CRM as

the dimensions of CRM. The result of this research indicates that managers need to focus on

these four key CRM dimensions to enhance customer loyalty and sales growth significantly.

Additionally, in their analysis and discussion, they examined the expanding role of

salespeople in successful CRM implementation and outcomes. Sin, Tse and Yim (2005),

viewed CRM as a multi-dimensional construct consisting of four broad behavioral

components: key customer focus, CRM organization, knowledge management, and

Technology-based CRM. They developed a reliable and valid scale for measuring the four

dimensions. Chen and Popovich (2003) found that the success of CRM initiatives is heavily

behavior through meaningful communication to improve customer

acquisition, customer retention, customer loyalty, and customer profitability

Boulding et al

(2005)

CRM build relationships and use systems to collect and analyze data, but

it also includes the integration of all these activities across the firm, linking

these activities to both firm and customer value, extending this integration

along the value chain, and developing the capability of integrating these

activities across the network of firms that collaborate to generate customer

value, while creating shareholder value for the firm.

Greenberg

(2001)

CRM is a business strategy to select and manage customers to optimize

long-term value. CRM requires a customer-centric business philosophy and

culture to support effective marketing, sales, and service process. CRM

applications can enable effective Customer Relationship Management,

provided that an enterprise has the right leadership, strategy and culture.

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influenced by the interplay between three key organizational elements: people, processes,

and technology. Specifically, they emphasized the importance of individual employees, since

they are the building blocks of customer relationships. Raman, Wittmann and Rauseo (2006)

used a third-party survey run on a popular website that serves as a forum for CRM users,

developers, and consultants to investigate CRM implementation. They proposed a model

that explains the role of organizational learning, business process orientation, customer-

centric orientation, and task-technology fit in enabling the transformation of CRM from

technological tool to an advantage-producing resource. Meanwhile, Kondo (2008) pointed

out that CRM can be understood from three aspects: a process, a strategy to target

customers more effectively, and a combination of these two aspects. He believed that CRM

can be understood from two sides: customer relationship strategy and the organizational

management process to support this strategy. Moreover, he also emphasized that the

success of CRM implementation is dependent on the organizational power.

When researching CRM in the business to consumer markets, Minami (2006) pointed

out the close relationship between CRM and loyalty marketing, emphasizing the importance

of loyalty programs in inducing customer retention. Dowling (2002) believed that CRM

systems include call centers, web sites, customer services, customer support initiatives, and

loyalty programs - all designed to help understand and manage the relationship between

companies and their customers. In particular, he mentioned the CRM tactic of customer

loyalty program and its effectiveness. Javalgi, Martin and Young (2006) discussed the

importance of market research information in developing a market orientation, and its impact

on internal service organizations, by illustrating several anecdotal and case examples. They

interpreted the framework of CRM as service satisfaction initiatives, service loyalty programs,

customer retention programs, and enhanced customer lifetime profitability. Verhoef (2003)

conducted a research from the perspective of customers, using the customers' relationship

perceptions - customer satisfaction, affective commitment and payment equity, and

relationship marketing instruments - direct mailing and loyalty programs as the dimensions

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of CRM. He found that affective commitment and loyalty programs which provide economic

incentives positively affect both customer retention and customer share development, while

direct mailing has little effect on customer share development.

By reviewing the previous research, three important CRM constructs were found.

These were affective commitment, front-office employees, and loyalty programs. These are

used as the dimensions of CRM in this research, and will be introduced in the following

paragraphs. The reasons for using them will be presented in the methodology section.

2-1. Affective commitment

Fullerton (2005) summarized that customer commitment has two components in

marketing research: affective commitment and continuance commitment. Many

unidimensional conceptualizations of commitment in the marketing research contexts tapped

the affective dimension of commitment (e.g. Garbarino and Johnson, 1999; Hennig-Thurau

et al., 2002; Morgan and Hunt, 1994; Verheof, 2003, etc.). Affective commitment is a central

construct in relationship marketing literature. According to Gustafsson, Johnson and Roos

(2005), affective commitment is a hotter or more emotional factor that develops through the

degree of reciprocity or personal involvement that a customer has with a company.

Garbarino and Johnson (1999) pointed out that affective commitment is a more emotional

factor compared with cumulative commitment. It develops through the degree of personal

involvement or reciprocity that a customer has with a company and will lead to a higher level

of trust. Fullerton (2005) emphasized that affective commitment exists when the individual

customer is attached to their relational partner or when the individual customer identifies with

the relational partner. Affective commitment has been used as an important variable in the

research on relationship marketing and CRM (e.g. Morgan and Hunt, 1994, Garbarino and

Johnson, 1999, Verheof, 2003, etc). In addition, there have been many previous researches

to prove that affective commitment is positively influenced by customer satisfaction (e.g.

Hennig-Thurau, Gwinner and Gremler, 2002; Fullerton,2003 Garbarino and Johnson, 1999;

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Adjei and Clark, 2010, Davis-Sramek; Droge, Mentzer and Myers, 2009)

2-2. Front-office employees

CRM technology alone would not make CRM successful. Henning-Thurau and

Thurau (2003) emphasized that, in service marketing, the behavior of employees plays a

central role with regard to customers’ perception of satisfaction and service quality.

Essentially, employees can be divided into two types: back-office employees and front-office

employees. The front-office employees have a direct impact on customers’ quality and

benefits perception. There are particular industries (e.g. hotel, airline, travel, banking, etc), in

which front-office plays an extremely significant role in CRM implementation (Ku and Fan,

2009). Some researchers believe that, operating at the frontier of the customer-organization

interface, front-office employees are essential in providing added benefits for customers

while creatively managing the buyer-seller relationship. They are also generally believed to

have the greatest influence in reducing customer defection, and the level of their success

with the customer largely determines the effectiveness of CRM implementation (e.g. Hennig-

Thurau and Thurau,2003, Bettencourt and Gwinner,1996). Specifically, when it comes to the

CRM research in the hospitality industry, Ku and Fan (2009) emphasize the significant role

front-office-employees play in the relationship with customers. They point out that, with the

increasing popularity of purchasing budget travel packages on the internet, customers have

become more demanding in terms of the level of expertise and knowledge they expect from

their advisors. Customers not only need their advisors to treat them in a warm, friendly

manner to maintain the relationship with them, but also expect them to be equipped with a

comprehensive knowledge of the products, market and the customer ’s individual preferences.

Therefore, in this research, customers’ perceptions of both service quality and the

professionalism of front-office employees will be considered.

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2-3. Loyalty program

According to Minami and Dawson (2007), CRM consists of two important parts,

namely business intelligence and loyalty marketing for the service and retail industries.

Minami (2006) emphasized that implementing CRM to collect the purchase history and to

incentivize the continuous purchasing of customers, it is necessary for companies to

implement loyalty schemes. Minami and Dawson (2007) also stated that the loyalty program

was induced originally by American airline firms in the form of frequent flyer programs,

followed by hotel, finance-card and retail firms. Bolton, Kannan and Bramlett (2000)

researched the implications of loyalty program membership and service experiences for

improving customer retention and value. They pointed out that reward programs based on

service usage levels (e.g. frequent buyer programs) have become common in the

transportation and hospitality industries.

The loyalty program has been used as one of the dimensions of CRM in some

research (e.g. Dowling, 2002, Javalgi, Martin and Young, 2006, Minami, 2006, Verhoef, 2003,

etc). Liu (2007) suggested that loyalty programs are an important component of a firm’s

customer relationship management strategy. They aim to increase customer loyalty by

rewarding them for doing business with the firms. Researchers have divided the benefits of

loyalty programs for consumer into two broad types. Referring to Lovelook and Wirtz (1996),

one of these is financial rewards (hard benefits), and the other is non-financial rewards (soft

benefits) (Dreze and Nunes, 2008). Financial rewards include discounts on purchases and

loyalty program rewards like frequent flier miles, etc. Non-financial rewards (soft benefits)

mean benefits that cannot be translated directly into monetary terms. According to Dreze and

Nunes (2008), soft benefits comprise special privileges such as restricted check-in counters

and individually tailored communications, etc. They stated that instead of just rewarding

consumers based on the accumulation of purchases, loyalty programs are conducted to

provide the firm’s best customers with less obvious contingent benefits. In this research, a

loyalty program is viewed as a combined program to provide customers with both financial

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and non-financial rewards.

3. The Consequences of CRM

Payne and Frow (2005) pointed out that CRM stresses two-way communication - from

company to customer and from customer to company to build the customer asset over time.

Buttle (2001) stated, “CRM is about the development and maintenance of long-term mutually

beneficial relationships with strategically significant customers”. Dowling (2002) stated that

CRM is a strategic concept that incorporates the strategic outcomes of satisfaction, loyalty,

customer retention and profitability, while relying on technology to harness market relevant

data and guide decision-making. Minami (2006) emphasized that the ultimate purpose of

customer relationship management is to bring profitability to both the company and

customers when implementing CRM strategy. She systematically summarized the outcome

of CRM implementation from the standpoint of marketing research. There are two research

approaches to the consequences of CRM. One is to look at the benefits brought to the

companies by CRM implementation (for instance, customer retention and the financial

benefits). The other is to consider another kind of value available to customers, in which

customer satisfaction is the most essential value (Mithas, Krishnan and Fornell, 2005).

There has been a lot of research which has shown that CRM can provide customers

with a satisfying experience. For instance, Payne and Frow (2005) pointed out that CRM

activity involves collecting and intelligently using customer and other relevant data (the

information process) to build a consistently superior customer experience. Meanwhile, if we

refer to Stefanou et al. (2003), it is possible to provide customers with a satisfying customer

experience through CRM application, where customers can experience effective purchasing

process by referring to the recommendations that companies provide to them by analyzing

their historical purchasing data and customized services. Kolter (2001) suggested that what

customers really want from the relationship with a company could be very important for

companies to satisfy their customers effectively and continuously. According to Mithas,

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Krishnan and Fornell (2005), there are at least three reasons why customer relationship

management applications are likely to bring customers satisfaction. First, CRM applications

enable firms to customize their offerings for each customer. Second, in addition to enhancing

the perceived quality of the offering, CRM applications also enable firms to improve the

reliability of consumption experiences by facilitating the timely, accurate processing of

customer orders, requests, and the ongoing management of customer accounts. Finally,

CRM applications also help firms manage customer relationships more effectively across the

stages of relationship initiation, maintenance, and termination. In other words, it is a verdict

on the accomplishment of expectations, motivated by an attribute of the product or the

service (or by the product or service as a whole) that provides customers with a level of

pleasure.

When it comes to customer satisfaction itself, Olive (1997) pointed out that this is a

very complex concept which may be interpreted in multiple ways. In this paragraph, several

different standpoints on viewing customer satisfaction are argued. Johnson, Sivadas and

Garbarino (2008) summarized the different standards when interoperating customer

satisfaction as follows: 1) the type of response (cognitive or affective), 2) the time of

evaluation (immediate to an encounter or retrospective of past consumption), 3) the

psychological process used to construe the response (e.g. disconfirmation of expectations,

attribution, equity perceptions), and 4) the object of evaluation (e.g. transaction, a firm, an

attribute). Meanwhile, some researchers have studied customer satisfaction based on its

relationship with customer expectations. Cho and Fjermestad, (2005) stated that researchers

in the customer satisfaction/dissatisfaction area posited that the fulfillments of expectations is

a determinant of customer satisfaction, in addition, Johnson and Fornell (1991) pointed out

that as a customer’s product experience grows, expectations should become strong and

their effect on satisfaction should increase, according to the “expectation and disconfirmation

model”. They pointed out that, as customer experience continues to grow, expectations

should increase in both confidence and accuracy, and in a manner that is consistent with a

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product’s perceived performance. Eventually, current performance and expectations may

coincide. That research suggests that production expectations, as a separate theoretical

construct, will not play a fundamental role in satisfaction judgments at the extremes of

experience. However, other scholars have researched customer satisfaction from a different

standpoint. Johnson and Fornell (1991) and Oliver (1997) insisted on treating customer

satisfaction as “overall / cumulative satisfaction”. Overall satisfaction is “an overall evaluation

based on the total purchase and consumption experience with a good or service over time”

(Anderson, Fornell and Lehmann, 1994, p54), and it can be distinguished from transaction-

specific customer satisfaction, which is an immediate post-purchase evaluative judgment or

affective reaction to the most recent transactional experience with a firm.

When reviewing customer satisfaction in the CRM literature, it was found that,

essentially, there are at least three trends to explain customer satisfaction: (1) Overall

satisfaction, which is a cumulative construct, summing satisfaction with specific products and

services of the organization and with various facets of the company, such as the physical

facilities (e.g. Garbarino and Johnson, 1999). (2) Relating it to perceived performance and

expectations (e.g., Stefanou, Sarmaniotis and Stafyla 2003). If performance matches

expectations or exceeds them, the customer is satisfied or highly satisfied respectively.

However, if performance falls short of expectations, the customer is dissatisfied. (3)

Measuring transactional specific satisfaction (e.g. Srinivasan and Moorman, 2005). However,

according to Garbarino and Johnson (1999), instead of capturing the transient and

encounter-specific evaluations and emotions, applied market research tends to measure

customer satisfaction as the consumer’s general level of satisfaction based on all

experiences with the firm, and as customers’ needs have been fulfilled repeatedly. Therefore,

in this research, based on the reviewed literature, customer satisfaction is viewed as overall

satisfaction; it represents a pleasurable level of fulfillment of the customer’s expectation,

needs and desires (Johnson, Sivadas and Garbarino, 2008).

According to Lemon, White and Winer (2002), if customers are satisfied overall, they

16 / 65

are likely to stay with the same company in the future. They researched how customer

future-focused expectations, over and above the effects of satisfaction, influence the

customer’s decision to discontinue a service relationship. They found that 1) customers’

future expectations, usage of and benefits from a service relationship have a significant

influence on customer retention, 2) customers update their future expectations following an

adaptive expectations approach, incorporating recent usage experiences into their next-

period expectations.

To summarize, and bearing in mind that the purpose of CRM is bringing mutual

benefits to both companies and customers, satisfied customers have been viewed as the key

to maintaining a long-term relationship, as when customers are satisfied by CRM

implementation, they will feel affective commitment toward the company. This is also likely to

be related to high customer loyalty; because loyal customers may be more possible to keep

in a relationship with the company, this will improve the corporation’s financial profits.

However, the needs and wants of customers are not static. Therefore, Yim, Anderson and

Swaminathan (2004) also insisted that successful CRM activities must continuously adapt to

the evolving needs and wants of customers and determine what customers really expect for

from the continuous relationship.

Additionally, based on the previous researches, I consider that it is probable to assume

CRM efforts may have an influence on customer expectations (the different kinds of benefits,

which customers expect to gain from the relationship with a service company). There are at

least three reasons why this assumption can be made.

i. With the development of CRM application, customized offerings, (for instance,

customized products, services and personalized service encounters) will be available to

each customer. By tracking the data of each customer, it will be possible to ascertain

what kind of specific benefits these customers expect to receive from their relationship

with the company (Dowling, 2002).

ii. Customers’ consumption experiences have become more reliable since their

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expectations on time spending and purchase decision, etc, have been fulfilled

automatically by the data management system of CRM application ( Zablan, Bellenger

and Johnston, 2004).

iii. Different kinds of customer expectations could be determined by CRM application

across the stages of relationship initiation, maintenance and termination (Payneand

Frow, 2005). For instance, after the first purchase, companies will understand the

customer’s purchasing habits and special preferences, such as in the airl ine industry.

Some customers are low price-oriented, while others may be status-oriented. By

understanding what customers expect, companies could provide customers with

different items in order to maintain a relationship with them, making them feel satisfied

overall during the whole purchase process, which would in turn make them more likely

to stay in the relationship for a long time.

4. Customer Expectations in Customer Relationship Management Research

Hoskins (2003) summarized the development of CRM research, and mentioned that

the development of CRM technology has changed customer expectations to some extent.

Dimitriadis and Stevens (2008) conducted an internal and external gap model to research

customers’ reaction to a service company's CRM strategy and to link relational benefits

directly to the design and control of a CRM strategy. They found that expectations could be

used as a mean of designing appropriate interaction flows with customers, while relationship

expectations from the customers’ point of view could be used as a segmentation variable to

identify customer relationship profiles and address them with specific means. In their model,

a gap between customer expectations and CRM strategy formulation is pointed out. They

also suggested that the way relationship expectations are created has not been clearly

defined, and those customers’ perceptions and expectations of relationships with a service

company are still unexplored research issues.

What a customer expects from a relationship with a service company has been

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measured in many previous researches as relationship benefits or as value in a relationship

(Dimitriadis and Stevens, 2008; Gwinner, Gremler and Bitner, 1998; Hennig-Thurau, Gwinner

and Gremler, 2002; Reynolds and Beatty, 1999, Lovelock and Wirtz, 1996, Lovelock and

Wright, 2002). Gwinner, Gremler and Bitner (1998) conducted in-depth interviews with 21

customers to arrive at a better qualitative understanding of the benefits customers gain from

engaging in ongoing business relationships with service providers. They developed and also

empirically supported a typology of three relational benefits: confidence benefits, special

treatment benefits and social benefits. According to Hennig-Thurau, Gwinner and Gremler

(2002), confidence benefits refer to perceptions of reduced anxiety and comfort in knowing

what to expect in the service encounter, while Gwinner, Gremler and Bitner (1998) described

them as “feelings of reduced anxiety, trust, and confidence in the provider”(p.106). The latter

also mentioned the conceptual closeness of confidence benefits and trust. Therefore, in my

research, a combined confidence benefits/trust construct is examined. In other words, by

referring the previous work, in this research, confidence benefits is viewed as “feelings by

customers that in an established relationship there was less risk of something going wrong,

more confidence in correct performance, greater ability to trust the provider, lowered anxiety

when purchasing, better knowledge of what to expect, and an expectation of receiving the

firm’s highest level of service” (Lovelock and Wright, 2002, p.103.). While, according to

Hennig-Thurau, Gwinner and Gremler (2002) and Lovelock and Wright (2002), "Special

treatment benefits take the form of relationship consumers receiving price breaks, faster

service, or individualized additional services”.( Hennig-Thurau, Gwinner and Gremler, 2002,

p.234.) Social benefits pertain to the emotional part of the relationship, and are characterized

by personal recognition of customers by employees, the customer’s own familiarity with

employees, enjoyment of certain social aspects of the relationships, and the creation of

friendships between customers and employees (Hennig-Thurau, Gwinner and Gremler, 2002,

Lovelock and Wright, 2002).

According to Gwinner, Gremler and Bitner (1998), the relational outcome, such as

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commitment to the firm, is dependent upon the customers receiving certain relational

benefits. Furthermore, Hennig-Thurau, Gwinner and Gremler (2002) conducted an empirical

study of 336 service customers to test a model describing the relationship between customer

satisfaction, commitment, confidence benefits, social benefits, special treatment benefits

and relationship outcomes (e.g. customer loyalty, word-of-mouth). The results showed

support for their model and indicated that the concepts of customer satisfaction, commitment,

confidence benefits, and social benefits serve significantly to contribute to relationship

marketing outcomes in services. Specifically, they discovered that social benefits and special

treatment benefits have a directly positive influence on commitment. Meanwhile, Reynolds

and Beatty (1999) conducted an empirical study to show that the perception of relationship

benefits is positively associated with satisfaction with the salesperson. However, these

previous researches did not mention whether affective commitment of customers to a service

company, and their perceptions of front-office employees, will have an impact on their desire

to claim benefits in future transaction processes with that company. Neither do they mention

whether affective commitment and front office employees have an equal influence on

customers' expect to obtain different types of benefits.

5. Summary

Customer relationship management has been acknowledged and regarded as one of

the marketing strategies to target customers more effectively (e.g. Bull, 2003, Nguyen, Sherif

and Newby, 2007, Reinartz, Krafft and Hoyer, 2004). There have been many papers on the

framework of CRM (e.g. Reinartz, Krafft and Hoyer, 2004, Payne and Frow, 2005), the

relationship between CRM and relationship marketing (e.g. Parvatiyarand Sheth, 2001) and

the outcomes (i.e. the benefits) of CRM implementation to the company. A successful CRM

strategy helps companies improve customer retention, customer loyalty, and their market

share (Verhoef, 2003, Lemon, White and Winer, 2002). However, most of the research on

CRM has been conducted from a corporate standpoint, while research into CRM from the

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customer’s perspective remains limited (e.g. Bohling et al, 2006, Dimitriadis and Stevens,

2008).

Kotler (2001) stated that one of the most popular clichés today is that a winning

company is one that consistently exceeds customer expectations. Indeed, compared with

meeting customer expectations, which will only satisfy customers, exceeding their

expectations will delight them, and those delighted customers will bring much higher

profitability to the companies. Nevertheless, when a customer’s expectations are exceeded,

he has higher expectations next time. As Lemon, White and Winer (2002) stated, customers

update their expectations for the future following an adaptive expectations approach,

incorporating recent usage experiences into their next-period expectations. The company

has to work much harder to exceed these higher expectations in order to retain that

customer, and it will get more difficult and more costly for the company. Since customers

expect many kinds of benefits, such as higher service quality, added services, great

convenience, customized services and information, status upgrades, and so forth, it is very

challenging for companies to decide how to meet heightened customer expectations

effectively.

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CHAPTER 3 Research Questions and Hypotheses

Research Questions:

There are certain corporations that have considered customer expectation as a very

significant factor when dealing with CRM strategy. For instance, the consultant firm

Accenture clarified their CRM service thus: “Accenture Customer Relationship Management

(CRM) consulting services help clients achieve high performance by efficiently anticipating,

meeting and exceeding their customers' expectations.” Dimitriadis and Stevens (2008) found

that relationship expectations from the customers’ point of view could be used as a

segmentation variable to identify customer relationship profiles and address them with

specific means. In addition, they suggested that many companies have adopted CRM

systems without thinking of customer expectations in terms of relationships, and that this will

cause some problems in implementing CRM effectively. Based on the reviewed CRM

literature, there are some papers on the role of customer expectations in CRM activities (e.g.

Hoskins, 2003, Dimitriadis and Stevens, 2008). No empirical research could be found to

clarify the direct relationship between CRM and customer expectations in the service

industry. Because there are significant practical applications and a theoretical gap, I assume

that it is necessary to conduct an empirical research of CRM and customer expectations.

According to Dimitriadis and Stevens (2008), customer expectation in relationship

marketing is mainly measured in terms of relationship benefits, these being confidence

benefits, special treatment benefits, and social benefits (Dimitriadis and Stevens, 2008,

Gwinner, Gremler and Bitner, 1998, Hennig-Thurau, Gwinner and Gremler, 2002, Reynolds

and Betty, 1999, Lovelock and Wirtz, 1996, Lovelock and Wright, 2002). Gwinner, Gremler

and Bitner (1998) researched relationship benefits that customers expect to receive during a

continuous relationship in services industries. They proposed that there is causality between

relationship benefits and relationship strength. They also emphasized that a long-term

relationship results in certain relationship benefits that strengthen the ties and result in a

continued relationship. This built-up relationship then leads to the receipt of even more

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relationship benefits. Based on this research, and in order to identify and understand how

managerially controlled antecedent variables influence important relationship marketing

outcomes, Hennig-Thurau, Gwinner and Gremler (2002) researched the links between

relationship quality (customer satisfaction and commitment), relationship benefits

(confidence, special treatment and social benefits) and relationship marketing outcomes

(customer loyalty and word-of-mouth). They used confidence benefits, special treatment

benefits and social benefits received by customers as independent variables, and indicated

that confidence benefits have a positive effect on customer satisfaction while social benefits

and special treatment benefits have a positive effect on customer commitment. However,

according to Gwinner, Gremler and Bitner (1998), there may be another direction of causality

between relationship benefits and relationship strength. In other words, it is possible to use

relationship benefits as dependent variables to be influenced by the relationship strength.

Therefore, with consideration to the theoretical and practical gap of CRM research, I

decided to research the relationship between CRM and customer expectation from the

perspective of customers in the service industry. My research will try to fill the gaps by

answering the following questions: Does CRM affect customer expectations in the service

industry? Are all kinds of expected benefits (confidence benefits, special treatment benefits

and social benefits) equally affected by CRM efforts in the service industry?

Hypotheses:

The hypotheses about CRM and the benefits which customers expect are introduced

in the following paragraphs. Conceptual models about all of these hypotheses will be

presented at the end of this section.

According to the literature review, affective commitment is seen as an emotional factor.

It is usually used to represent commitment in a marketing research context (e.g. Garbarino

and Johnson, 1999, Hennig-Thurau, et al., 2002, Morgan and Hunt, 1999, Verheof, 2003).

According to Garbarino and Johnson (1999), affective commitment represents the personal

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involvement or reciprocity a customer has with a company, and results in a higher level of

trust. Fullerton (2005) stated that affective commitment makes customers trust and have

confidence in a company. In a consumer services environment, affective commitment-based

relationships exist (for example, the trust and friendship based relationship which exists

between a hairstylist and a client). Fullerton (2003) emphasized that the crucial aspect of

affective commitment is that customers ask for an emotional attachment to their partner in a

consumption relationship, and friendship is closely related to the affective commitment

construct. Berry (1995) also contends that when customers have a higher level of

commitment to the organization, there is a kind of social bond between customers and

employees, while Henning-Thurau, Gwinner and Gremler (2002) proved that there is a

positive relationship between special treatment benefits, social benefits and commitment.

They pointed out that an organization provides additional types of special treatment benefits,

including financial benefits and customized services that can result in increasing commitment.

They also doubt there is an opposing relationship between special treatment benefits and

commitment. In other words, commitment may have a positive effect on special treatment

benefits. According to Gwinner, Gremler and Bitner (1998) the improved relationship effort

results in the receipt of even more special treatment benefits. Therefore, I believe it is

possible to imagine that affective commitment will have a positive effect on customers’

expectations of special treatment benefits in future transaction processes. Based on the

above arguments, in the relationship between customers and a service company the

following hypotheses related to affective commitment are proposed:

H1-1: Affective commitment has a positive influence on customers' expectations of receiving

confidence benefits.

H1-2: Affective commitment has a positive influence on customers' expectations of receiving

special treatment benefits.

H1-3: Affective commitment has a positive influence on customers' expectations of receiving

social benefits.

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Mendoza et al. (2006) stated that it is necessary to confirm the importance of the

personal relationship established between the client and the company via the company’s

employees, and that these individual employees are the building blocks of customer

relationships. About the importance of front-office employees, Hart et al. (1990) stated that

frontline employees can have latitude over their service activities and abilities to address

specific customers’ needs in order to act in a fully customer-centric manner to bring

customers benefits that they deserve through the relationship with service companies.

Bhattacharya and Bolton (2000) mentioned that service employees can create customer

satisfaction and develop personal trust with customers. Additionally, Bettencourt and

Gwinner (1996) conducted a qualitative study to emphasize that the front-office employee is

crucial in delivering a customized service experience in the service business. They

suggested that, based on an individual consumer’s needs, front-office employees can tailor

or create a unique bundle of service attributes or benefits. Berry (1995) researched the

relationship marketing in service marketing. He discussed the benefits to the customers and

pointed out that, if they have a good relationship with a given supplier, customers can reap

social benefits. Gwinner, Gremler and Bitner (1998) stated that customers may develop

friendships with those employees with whom they are familiar. The service provider, with

whom customers have built up a relationship, will provide customers with confidence in the

services of that company. They also stated that frontline employees could provide customers

with different kinds of personalized services. Moreover, the frontline employees are the

people who interact with customers directly, so it could be assumed that front-office

employees are able to understand their kinds of special needs and wants. Therefore, it is

reasonable to believe in the importance of front-office staff when it comes to providing

customers with the benefits they are expecting. Customers choose a specific service

company not only because they are attracted to the company itself, but also because they

believe that the front-office employees who are going to serve them are friendly, professional,

trustworthy and able to deliver them customized services. This friendly, helpful and

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professional attitude is a major factor in customers' perception of those employees, and in

turn influences their expectations. The remainder of this research will refer to these

perceptions of employees' attitudes as ‘front office employees’.

Therefore, I propose in the relationship between customers and a service company,

H2-1: Front-office employees have a positive influence on customers’ expectations of

receiving confidence benefits.

H2-2: Front-office employees have a positive influence on customers' expectations of

receiving special treatment benefits.

H2-3: Front-office employees have a positive influence on customers’ expectations of

receiving social benefits.

There are some studies that have shown that loyalty program will bring customers

different kinds of benefits. According to Bolton, Kannan and Bramlett (2002), loyalty

programs may be able to provide customers with added economic and customized service

benefits to strengthen their marketing relationship with the firm. Loyalty programs can make

customers feel special, important, and appreciated. Lacey, Suh and Morgan (2007) pointed

out that customer loyalty programs are the most prevalent mechanism used by firms to

practice preferential treatment to customers. Lovelook and Wirtz (1996) suggested that non-

financial rewards, especially if linked to higher tier service levels, are typically more powerful

than the economic rewards, because the former can create tremendous value for customers

(for example, feeling confident in the company, its customized goods, and services). In other

words, unlike the economic rewards, the non-financial rewards of loyalty programs are

directly related to a firm's core service and directly enhance the customers’ experience and

value perception. Based on O’ Malley and Tynan (1998) nonfinancial rewards could reduce

risk, in other words bring confidence to customers, in the relationships between customers

and companies. Additionally, those non-financial rewards coming from loyalty programs

could bring customers the social benefits of relationship participation. Leenheer, et al (2007)

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studied the effectiveness of loyalty programs and emphasized their sociological effects. They

pointed out that loyalty programs enhance customer loyalty through several economic,

psychological and sociological mechanisms. Loyalty programs can make customers know

that they are provided with better value than others are, and create an image for customers

that they are belong to a preferred or special customer group. Bhattacharya, Rao, and Glynn

(1995) pointed out that customers who become members of a loyalty program are likely to

identify more strongly with the company, since the membership brings them a feeling of

belonging to a group of privileged customers.

Therefore, I propose that in the relationship between customers and a service company

H3-1: Loyalty programs have a positive influence on customers' expectations of receiving

confidence benefits.

H3-2: Loyalty programs have a positive influence on customers' expectations of receiving

special treatment benefits.

H3-3: Loyalty programs have a positive influence on customers' expectations of receiving

social benefits.

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Figure.1. Conceptual Models of Hypotheses:

1. Conceptual model of Affective commitment(AC), loyalty program (LP) and front-office

employees (FOE) with confidence benefits (CB)

+

+

+

2. Conceptual model of Affective commitment(AC), loyalty program (LP) and front-office

employees (FOE) with special treatment benefits (STB)

+

+

+

3. Conceptual model of Affective commitment(AC), loyalty program (LP) and front-office

employees (FOE) with social benefits (SB)

+

+

+

AC

LP

FOE

CB

AC

LP

FOE

STB

AC

LP

FOE

SB

28 / 65

CHAPTER 4 Methodology

1. Research Setting

Bowen (1990) classified service firms into three types. These are (a) services

directed at people and characterized by high customer contact, together with individually

customized service solutions (e.g. financial consulting, medical care, travel agencies,

hairdressing), (b) services directed at an individual’s property, in which moderate to low

customer contact is the norm and where the service can be customized only slightly (e.g.

shoe repair, retail banking, pest control, pool maintenance), and (c) services typically

directed at people, and which provide standardized service solutions with moderate

customer contact (e.g. airlines, movie theaters) (Cited by Hennig-Thurau, Gwinner and

Gremler, 2002, Gwinner, Gremler and Bitner, 1998).

Airlines will be used as the context of this study. In Japan, CRM strategy has been

employed by some well-known airlines. For instance, the FFP (Frequent flyer program),

which is regarded as a type of CRM strategy, was introduced by JAL in 1997 under the term

‘Mileage Bank’, while ANA began their ‘My Mileage Club’ program a month later. According to

Boland, Morrison and O’ Neill (2002), the airline industry has reached a crossroads, and

customer relationships must be fostered in order for airlines to maintain competitive

advantages and profitability in the long term. One of the primary goals of CRM is to

differentiate a company’s services to the customer through personalization. They emphasize

that airlines need to understand how their core customers respond to the specific initiatives,

services and treatments that are provided to them by implementing CRM strategy. Therefore,

I believe it is useful to research the relationship between CRM and customer expectations in

the airline industry.

2. Variables:

2-1. Independent variables:

Affective commitment, loyalty program and front office employees - three very

29 / 65

important CRM dimensions that have been discussed in the literature review - were used as

independent variables in this research. There are two reasons for using them. Firstly, it was

found in previous research that customer retention, customer share, and customer

satisfaction are significant metrics in CRM (Verheof, 2003; Mithas, Krishnan and Fornell,

2005 etc). Referring to Dimitriadis and Stevens (2008), relationship expectation and

perception of the relationship are key customer-related factors of CRM success. Based on

Parasuraman et al. (1985), when the perceptions of flows of experiences generated by the

relationship correspond to the customer’s expectations, relationship satisfaction will occur

and relationship success will be fulfilled. In order to maximize those important metrics in

CRM, corporations use relationship marketing instruments (Verhoef, 2003). There are some

instruments that have been used in previous research by Verhoef (2003), in which loyalty

programs and direct mailing were used, while Hennig-Thurau and Thurau (2003) focused

their research on employees. Generally, loyalty programs in the airline service are termed

‘Frequent Flyer Programs (FFPs)’ and have been viewed as an essential part of CRM

implementation in the airline industry (e.g. ANA, JAL, etc). Front-office employees play a very

significant role in CRM implementation in airline industries (Ku and Fan, 2009), and are

regarded as a crucial factor when considering CRM in the airline industry (e.g. Boland,

Morrison and O’Neill, 2002, Viaene and Cumps, 2005).

On the other hand, Verhoef (2003) stated that corporations aim to enhance

customers’ relationship perceptions by building close relationships with those customers,

while Dimitriadis and Stevens (2008) pointed out that perception has mainly been addressed

in the related literature under the term ‘relationship quality’, and that this relationship quality

is related to affective commitment. According to Bhattacharya, Rao and Glynn (1995),

effective commitment in practice means customers’ emotional attachment to the service

provider. Morgan and Hant (1994) pointed out that commitment is an essential factor for

successful long-term relationships, and this has become a well-studied construct in both

relationship marketing and customer relationship management research. (Fullerton, 2003,

30 / 65

Yim, Anderson and Swaminathan, 2004, Verheof, 2003).

2-2. Dependent variables

When considering customer expectation, according to Dimitriadis and Stevens

(2008), what a customer expects from a relationship with a company has mainly been

measured in terms of relationship benefits (Bolton, Kannan and Bramlett, 2000, Reynolds

and Beatty, 1999). Additionally, based on Gwinner, Gremler and Bitner (1998), these

relationship benefits are grouped into three categories: confidence benefits, special

treatment benefits and social benefits. Therefore, the three types of relationship benefits are

used in this research.

2-3. Dummy variables

Lovelock and Wright (2002) state that customer expectations are influenced by

certain demographic factors, such as gender, therefore, I also used gender as a dummy

variable in my research. Furthermore, since my research is focused on the airline industry, it

is not difficult to imagine that people use airlines for different purposes, either business or

private use (Boland, Morrison and O’Neill, 2002). Therefore, I also used ‘reason for using

airline’ as one of the factors to predict customer expectation, in other words, to explain the

confidence, special treatment and social benefits which customers are looking forward to

receiving during the interaction process with the airline. However, because my interest in this

research is whether CRM has an effect on customer expectations, I did not propose the

relationship between ‘reason for using airline’ and ‘customer expectation’.

To summarize, in this research I used confidence, social and special treatment

benefits that customers expect to receive during the continuous relationship with airlines as

the dependent variables, and these are hypothesized to be influenced by the dimensions of

CRM - affective commitment, loyalty programs and front-office employees. In addition,

reason for using airline and gender were also used to predict the dependent variables.

31 / 65

Figure.2.Conceptual Model of the Research:

+

+ + + +

+

+

+

+

3. Data collection

Since this research focuses on customers’ expectations of the airlines with which

they have a relationship, survey respondents of this research should be people who have

flown at least once during the past two years. The data set used in this research consists of

three parts in order to attain a sufficient number of samples. Fifty-five questionnaires were

distributed to undergraduate students who ranged from the second to fourth year in the

consumer behavior class of the Business and Administration department at Kobe University

on November 19th, 2010. Fifty questionnaires were returned and seventeen of them were

dropped, due either to incomplete responses or not having flown in the previous two years.

Additionally, fifty questionnaires were distributed to graduate students from either Business

and Administration or the Graduate school of Human Development and Environment at Kobe

University from November 8th to 22

nd,, 2010. All of them were returned, with ten dropped for

incomplete responses. The sampling also took place in an advanced marketing class of MBA

students at Kobe University. Seventy-five questionnaires were distributed and all of them

were returned, with two dropped due to incomplete responses. Because the majority of

respondents were not students in the previous research (that of Hennig-Thurau, Gwinner

and Gremler, 2002), I also used some convenience data from alumni of Kobe University and

their friends in order to collect samples of non-students. Forty questionnaires were

AC

FOE

LP SB

STB

CB

32 / 65

distributed from November 1st to 25

th, 2010, and thirty-four responses were received with

complete responses.

To summarize, I distributed 220 surveys and managed to collect 209 samples, of

which 180 were usable. The final sample consisted of 112 males and 68 females, with

respondents distributed across the five occupation categories - students, employees,

managers, civil servants and part-time workers. 107 samples out of the total number of 180

samples came from non-students. In line with the previous research, the majority of the

respondents in this research were not students (see Graph 1 for a distribution of the

occupation of respondents.)

When it comes to respondents’ reasons for using an airline in the past two years, 80

were travelling on business, while 100 were using the airline for private reasons such as

travelling, visiting family, studying abroad and others. (See Graph 2 for details)

0

20

40

60

80

student employee manager civil servant part-time worker

Graph 1 Distribution of Respondents' Occupations

33 / 65

On the question of frequency of using airlines during the past two years, 18 people

travelled by plane at least once, 26 people 2-3 times, 46 people 4-5 times, 35 people 6-7

times and 55 people more than 8 times. In other words, around 76% of the respondents had

used airlines more than 4 times during the past two years (see Graph 3 for details).

Significantly, more than half of the respondents (58.3%) had joined the loyalty program of the

airline they usually use. Furthermore, about 63.9% of the respondents expected to obtain

benefits from the airline they usually use (see Graph 4 for details).

0

20

40

60

80

100

travelling business visiting family studying abroad others

Graph 2

Distribution of reasons for using airline

18

26

46

35

55

Once 2-3 times 4-5 times 6-7 times more than 8

times

Graph 3 Distribution of the frequency of using airlines

during the past two years

34 / 65

4. Operationalization of Constructs

In order to measure the constructs effectively, the measures I used in this research

either referred to or were cited directly from the previous studies. For the independent

variables, sequentially, affective commitment construct was borrowed from Bansal et al

(2004) and Gustafsson,Johnson andRoos (2005), in which I modified the reverse code of “I

do not feel emotionally attached to …” (from Bansal et al, 2004) into the regular code of “I

feel emotionally attached to the airline.” Measurements of front-office employees referred to

Hart et al. (1990) and Baker et al. (2002). Hart et al (1990) suggested that the front-office

employees must be empowered with the authority to attend to customer needs. Baker et al.

(2002) used “friendly employees” and “helpful employees” as a measurement of employee

perceptions. They used “treated well” as one of the measurements of interpersonal service

quality perceptions. Loyalty program constructs were combined from the items that have

been used or suggested by Wulf, Odekerken-Schroder and Lacobucci (2001) and Dreze and

Nunes (2008). Dreze and Nunes (2008) suggested that loyalty programs for consumers fall

into two broad classes. One is hard benefits (tangible rewards); another is soft benefits

(intangible rewards, recognition). Intangible rewards consist of special privileges such as

priority on boarding or check-in, and so on. Wulf, Odekerken-Schroder and Lacobucci (2001)

18 13

34

61

54

0

10

20

30

40

50

60

70

do not want them at all

do not want them

ambivalent want them very much

want them very much

Graph 4 Desire to obtain benefits from airlines

35 / 65

used “offers discounts”, “something extra” and “rewards” as measurements of tangible

rewards. Confidence benefits, special treatment benefits and social benefits were measured

with the scales provided by Hennig-Thruau, Gwinner and Gremler (2002) and Gwinner,

Gremler and Bitner (1998).

All of these items were measured using 5 scales; in which 1 signifies strong

disagreement with the statement and 5 suggests strong agreement with the statement.

When I created the questionnaire I purposely modified the Japanese statements based on

the original English operational definitions in the English papers to make the questions easy

for Japanese customers to understand and answer. Additionally, in order to assess construct

validity and clarify wording, I conducted a pre-test of the original scales using a small group

of 30 customers consisting of 17 females and 13 males, with respondents distributed across

four out of the five main age categories (20s, 30s, 40s, and 50s). After factor analysis, items

such as “I have developed a friendship with the attendants” were deleted due to low factor

loading (see appendix 1 for the operational definition and appendix 2 for the survey items in

the final research).

5. Research Design

In order to find out the direct relationship between CRM and customer expectations, in

other words, whether and how affective commitment, front-office employee, loyalty program,

gender, reason for using airline influence confidence benefits, special treatment benefits and

social benefits, and by referring to some previous research (e.g. Verheof, 2003), multiple

regression analysis is conducted in this research by using SPSS 17. (see Fig .1,2)

Before conducting the multiple regression analysis, for avoiding research bias, and

referring to Oshio (2009), the means and standard deviations of all question items were

calculated in advance in order to test the potential veiling and floor effects.

According to Leech, Barrett and Morgan (2008), an exploratory factor analysis (EFA)

was conducted on both independent variables and dependent variables using SPSS 17, to

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test how variables are related to underlying constructs and construct reliabilities. I decided to

use the principal axis factor method because it does not require multivariate normality - the

variables either do not need to be normally or jointly distributed. Referring to Oshio (2009),

three factor analyses were conducted and promax rotation was used for deciding items that

were to be used to test the constructs. According to Matsuo and Nakamura (2008), items

with a loading of less than 0.35 or with cross-loadings greater than 0.35 on more than one

factor were dropped because they do not provide a sufficiently pure measure of a specific

construct.

Next, three regression models were created to determine the best linear combination

of affective commitment: front-office employees, loyalty programs, reason for using airline

and gender. These were used for predicting confidence benefits, special treatment benefits

and social benefits respectively. Data was standardized before conducting multiple

regression analyses. Moreover, in the three multiple regression models, I used gender as a

dummy variable, coding it as 1 = male, 0 = female. ‘Reason for using airline,’ was coded as 1

= business, 0 = non business (In the questionnaire, there are five kinds of purposes -

traveling, business, visiting family, studying abroad and other to choose from).

In the end, the result of the three multiple regression models were compared to draw

the conclusions of this research.

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CHAPTER 5 Results of Analysis and Findings

There were thirteen items for measuring CRM and twelve items used in the customer

expectation questionnaire to measure the benefits customers are expecting to receive from

the relationship with the airline. Referring to Oshio (2009), before conducting factor analysis,

one item from special treatment benefits (number 22, Mean=4.04, SD=.977, M+ SD =5.02)

was deleted for having a veiling effect. Using items which do not have either veiling or floor

effects, I conducted three factor analyses for both CRM-related items and the three types of

benefits. For the CRM-related items, principle axis factor analysis without rotation was

conducted to determine the number of factors. Secondly, principle axis factor analysis with

Promax rotation was conducted to assess the underlying structures for its items, and lastly,

principle axis factor analysis with Promax rotation was conducted again to determine the final

structures of factors. The same factor analysis process was also conducted on the three

types of benefits.

1. Results of Factor Analysis of CRM-related Factors

For the CRM-related items, after the first factor analysis without rotation, based on the

fact that the items from number 5 to number 16 were designed to index three constructs,

three factors were requested: affective commitment, front-office employees, and loyalty

programs (the change of total eigenvalue was 3.98, 1.90, and 1.64). After the second factor

analysis with promax rotation, number 10 was deleted due to a factor loading lower than 0.35.

In the end, after rotation, the first factor accounted for 32.0% of the variance, the second

factor accounted for 12.8%, and the third factor 11.1%. Table 2 displays the items and factor

loadings for the rotated factors, with loadings less than .35 omitted to improve clarity. The

first factor includes numbers 6, 5, 8, 9, and 7, the second factor includes 15, 14, and 16, and

the third factor includes 12, 11, and 13. Referring to the “Variables and operation definition”,

the first factor is “affective commitment” (AC), the second factor is “loyalty program” (LP) and

third factor is “front-office employees” (FOE). Table2 indicates that the construct reliabilities

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(Cronbach’s Alpha) for all of the CRM-related variables were larger than .70, and referring to

Fornell and Larcker (1981), the reliability of these variables were indicated.

Table 2: Factor loadings and Cronbach’s Alpha for the underlying dimensions of CRM

(after rotation)

Note: Loadings<.35 are omitted.

2. Result of Factor Analysis of Customer Expectation-related Factors

For the customer expectation-related items, the same method with the FA on CRM-

related factors was used. After the first factor analysis without rotation, three factors were

requested, based on the fact that the items from number 17 to number 28 were designed to

index three constructs: confidence benefits, special treatment benefits and social benefits.

(The change of total eigenvalue was 4.85, 1.72 and 1.30). After the second analysis with

promax rotation, the first factor accounted for 35.3% of the variance, the second factor

accounted for 11.4%, and the third factor 6.6%. Table 3 displays the items, factor loadings

and Cronbach’s Alpha for the rotated factors, with loadings less than .35 omitted to improve

clarity. The first factor includes numbers 27, 26 and 28, the second factor includes numbers

18, 20, 19 and 17, and the third factor includes numbers 23, 24, 25 and 21. Referring to the

“Variables and operation definition”, the first factor is “social benefits” (SB), the second factor

is “confidence benefits” (CB) and the third factor is “special treatment benefits” (STB). Table3

Name of variables

Question numbers

Factor Loadings a* 1 2 3

AC

Affective commitment

6 .910 .83

5 .757

8 .624

9 .601

7 .587

LP

Loyalty program

15 .929 .79

14 .807

16 .508 FOE

Front-office employees

12 .830 .73

11 .799

13 .482

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indicates that the construct reliabilities (Cronbach’s Alpha) for all of the customer

expectation-related variables were larger than .70, and referring to Fornell and Larcker

(1981), the reliabilities of these variables were indicated.

Table 3: Factor loadings and Cronbach’s Alpha for the underlying dimensions of CE

(after rotation)

Note: Loadings<.35 are omitted

3. Hypotheses Testing- Results in Multiple Regression Analyses

3-1. Multicollinearity Testing

In order to determine whether the predictors are highly correlated so that

multicollinearity, which will lead the influence on dependent variable to be counteracted by

the two highly related variables, is likely to be a problem, I checked the correlations among

the predictor variables prior to running the multiple regression by using SPSS.17 (Leech,

Barrett and Morgan, 2008). The result of the correlation coefficient of predictor variables is

displayed in Table4. According to Leech, Barrett and Morgan (2008) high correlation is

shown when variables are correlated with Pearson correlations at .50 or .60 and above.

From the result displayed in Table4 there were no variables with Pearson correlations

above .50. Therefore, we can see that multicollinearity during the independent variables will

not be a problem in this research.

Name of variables

Question number

Factor Loadings a* 1 2 3

SB

Social Benefits

27 1.001 .83

26 .783

28 .556 CB

Confidence Benefits

18 .754 .74

20 .716

19 .661

17 .433

STB

Special Treatment Benefits

23 .847 .76

24 .677

25 .557

21 .390

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Table4 Means, Standard Deviations, and Intercorrelations of Predictor Variables

Note: ** p< .01, *p< .05.

3-2. Result of multiple regression analyses of confidence benefits, special treatment

benefits and social benefits

Multiple regression analyses were conducted using SPSS 17 to determine the best

linear combination of affective commitment, front-office employees, loyalty program, reason

for using airline, and gender to affect confidence benefits, special treatment benefits and

social benefits respectively.

The combination of variables predicted significant confidence benefits, F (5, 17)

=21.37, p<.001, with affective commitment, front-office employees and loyalty program

having a major influence on the prediction. Special treatment benefits were also predicted, F

(5, 17) =7.98, p<.001, with affective commitment, front-office employees and loyalty program

having a significant impact. Finally, the combination of variables also predicted significant

social benefits, F (5, 17) =13.68, p<.001. (See Table 5-7 for the detail result)

Predictor Variable M SD 1 2 3 4 5

1. Affective

Commitment

3.08 .84 1 .24** .38

** -.01 -.18

*

2. Front-office

Employees

3.06 .99 1 .18* -.11 -.13

3. Loyalty

Program

3.34 .87 1 .07 .02

4. Purpose .48 .50 1 .17*

5. Gender .62 .49 1

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Table5

Multiple Regression Analysis Summary of Affective Commitment, Front-office Employees,

Loyalty Program, Purpose and Gender Predicting Confidence Benefits.

Note: a. Dependent variable: Confidence benefits;

b. =.38; F (5, 17) =21.37, p<.001, ** p< .01.

Table6

Multiple Regression Analysis Summary of Affective Commitment, Front-office Employee,

Loyalty Program, Purpose and Gender Predicting Special Treatment Benefits.

Note: a. Dependent variable: Special treatment benefits;

b. =.19; F (5, 17) =7.98, p<.001, ** p< .01, *p< .05.

Variable B SEB Beta t

Affective Commitment .39 .06 .46** 6.83

Front-office Employees .13 .05 .18** 2.90

Loyalty Program .14 .05 .17** 2.52

Purpose -.02 .09 -.01 -.24

Gender -.03 .09 -.02 -.29

Constant 1.51 .24 6.38

Variable B SEB Beta t

Affective Commitment .22 .09 .19** 2.52

Front-office Employees .20 .07 .21** 2.92

Loyalty Program .18 .08 .17* 2.25

Purpose .01 .13 .01 .07

Gender -.19 .14 -.10 -1.36

Constant 1.47 .35 4.19

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Table7

Multiple Regression Analysis Summary of Affective Commitment, Front-office Employee,

Loyalty Program, Purpose and Gender Predicting Social Benefits.

Note: a. Dependent variable: Social benefits;

b. =.28; F (5, 17) =13.68, p<.001, ** p< .01.

4. Summary of Findings

All of my hypotheses were supported in this research, and it was found that CRM has

a positive effect on customer expectations.

In particular, this research supports the idea that affective commitment, front-office

employees and loyalty programs have positive effects on confidence benefits, special

treatment benefits and social benefit, which customer expecting to receive during the

relationship with service companies. Referring to Jr and Gates (2010), the Beta value or

standardized regression coefficients are estimates of the effect of individual independent

variables on the dependent variable, and the magnitudes of the regression coefficients

associated with the various independent variables can be compared directly when they have

been standardized. The beta weights, presented in Tables 5, 6, and 7, suggest that, when it

comes to customers' expectation of receiving confidence benefits, compared with front-office

employees and loyalty programs, affective commitment has the most important influence

(beta=.46). As to special treatment benefits, front-office employees showed the most

Variable B SEB Beta t

Affective Commitment .25 .09 .20** 2.75

Front-office Employees .32 .07 .29** 4.37

Loyalty Program .30 .09 .25** 3.50

Purpose .17 .14 .08 1.17

Gender -.03 .15 -.01 -.20

Constant -.27 .38 -.72

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significant prediction (beta=.21), followed by affective commitment (beta=.19) and loyalty

program (beta=.17). Moreover, customers' expectation of receiving social benefits was

actually shown to be chiefly affected by front-office employees (beta=.29), with loyalty

programs and affective commitment also showing meaningful results in predicting social

benefits (beta=.25, beta=.20).

Furthermore, I created three multiple regression models by using exactly the same

independent variables to predict different dependent variables. Interestingly, the result of this

research highlights that affective commitment, compared with front-office employees and

loyalty programs, plays the most significant role in influencing the level of confidence benefits

for customers. Front-office employees have the greatest influence on customers'

expectations of receiving both special treatment benefits and social benefits, while loyalty

programs have secondary importance in affecting expect to obtain social benefits.

Additionally, gender and reason for using airline did not show a meaningful result for

predicting confidence benefits, special treatment benefits or social benefits. A summary of

the result of the three multiple regression models is shown in Table 8.

Table 8 Summary of Multiple Regressions:

Note: ** p< .01, *p< .05.

Dependent

Variables

p Beta

CB .38 <.001 .46** .18** 17** -.01 -.02

STB .19 <.001 .19** .21** .17* .01 -.10

SB .28 <.001 .20** .29** .25** .08 -.01

Independent Variables AC FOE LP Purpose Gender

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CHAPTER 6 Conclusion

1. Contribution

The objective of CRM is to bring mutual benefits to both customers and companies. If

companies obtain comprehensive customer data, they will be able to provide customers with

more customized goods and services. This creates customer satisfaction, which in turn leads

to long-term customer retention, and ultimately provides companies with financial benefits.

However, the problem is how to make customers satisfied. Undoubtedly, companies have to

work on attaining, even exceeding, customer’s expectations of the benefits they are

supposed to receive from their relationship with companies. Dimitriadis and Stevens (2008)

proposed that, in the service industry, customers’ expectations of this relationship have to be

given appropriate attention. Gwinner, Gremler and Bitner (1998) highlighted that a reciprocal

influence may exist between relationship strength and relationship benefits. They pointed out

that the continued relationship will result in the receipt of even more relational benefits.

Therefore, in this article, I have used these relational benefits as dependent variables, and

set up some hypotheses that strive for a better understanding as to whether the efforts of

CRM influence customers' expectations of receiving the three types of relationship benefits,

and whether this influence has equal significance across each of the three types of benefits. I

answered the research questions by empirically researching the relationship between CRM

and customer expectations in the service industry from the perspective of the customer.

Affective commitment, front-office employees and loyalty programs were used as the

dimensions of CRM, while confidence benefits, special treatment benefits and social benefits

were used as the measurements of customer expectations. It is empirically proven that

affective commitment, front-office employees and loyalty programs have positive effects on

confidence benefits, special treatment benefits and social benefits respectively.

In particular, this research contributes to the CRM study area in the following aspects.

i. It conducts an empirical research of CRM in the business-to-consumer market. This

research tested customers’ perceptions of CRM efforts, and emphasized the

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importance of paying attention to customer expectations when implementing CRM

strategy in the airline industry.

ii. Although CRM is an extremely complicated construct (Ngai, 2005), based on the

extensive literature on CRM, I obtained and tested three significant CRM dimensions.

These are affective commitment, front-office employees and loyalty programs. This

research empirically proved the possibility of researching CRM in business-to-

consumer market through these three dimensions.

iii. The research tested confidence benefits, special treatment benefits and social

benefits as measurements of customer expectation in the CRM research area. The

operational definitions of the three types of relationship benefits are borrowed from

Gwinner, Gremler and Biter (1998) and Hennig-Thurau, Gwinner and Gremler (2002).

Gwinner, Gremler and Biter (1998) suggested that cultural contexts should be

considered when researching relationship benefits. In this Japan-based research,

their measurement was partly tested and showed acceptable reliability in research.

iv. I compared the importance of affective commitment, front-office employees and

loyalty programs in influencing customers' expectations of receiving the three types

of relationship benefits. Importantly, it was found that affective commitment is the

most significant factor when it comes to customers' expectation of receiving

confidence benefits; front-office employees have the most important effect on social

benefits and special treatment benefits. Although loyalty programs did not show the

greatest contribution in affecting any type of benefits, it still plays a meaningful role in

influencing those relationship benefits. Furthermore, it has the second greatest

importance in influencing customers' expectation of receiving social benefits.

2. Theoretical implication and practical implication

In order to interpret the relationship between the findings of this research and the

important points of previous research (as well as the managerial contributions of this

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research in marketing implementation) there are some theoretical implications and practical

implications to this research which will be discussed in the following paragraphs.

2-1. Theoretical implication

First, the influence of affective commitment on confidence benefits, special treatment

benefits and social benefits should be considered. According to Hennig-Thurau, Gwinner and

Gremler (2002), when customers have received special treatment benefits and confidence

benefits, this will result in customer commitment. However, they could not find a direct

relationship between confidence benefits and commitment, and doubted the possibility of

paths operating in the opposite direction to what they have proven. In other words, it is

possible to use confidence benefits, special treatment benefits and social benefits as

dependent variables, and they may be hypothesized as being affected by affective

commitment. Inspired by their research in this paper, I focused on the future transaction

process. I researched whether affective commitment will affect customers' expect to obtain

relationship benefits. According to Morgan and Hunt (1994), commitment is central to all the

relational exchanges between a firm and its customers, and it is defined as being an

enduring desire to maintain a valued relationship. In line with Verhoef's famous paper on

business-to-consumer CRM research (2003), I also focused on affective commitment, as it

represents the emotional attachment of customers based on affiliation with and loyalty to

airlines. I found out that feeling affective commitment to airlines makes customers more likely

to expect to receive confidence benefits, special treatment benefits and social benefits during

their interaction process with the same company. In particular, affective commitment plays

the most importance role in affecting confidence benefits. Reminding that I used a combined

construct of confidence of trust in this research, this finding supports Margan and Hunt

(1994), who suggested a significant relationship between commitment and trust (confidence

benefits).

Secondly, we must look at the effect of front-office employees on confidence benefits,

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special treatment benefits and social benefits. The significance of personal interaction

between customers and the front-office employees in CRM implementation has been given

increasing attention by scholars in marketing and organizational behavior (Bettencourt and

Gwinner, 1996). Although previous research has pointed out the crucial role of front-office

employees in providing added benefits for customers (e.g. Henning-Thurau and Thurau,

2003, Yim, Anderson and Swaminathan, 2004), the type of benefits that customers look

forward to receiving through interactions with front-office employees in the service industry

has not yet been proven. In this research, front-office employees show a positive effect on

the three types of expected relationship benefits by customers. Specifically, it is empirically

proven that front-office employees play a crucial role in providing customers both special

treatment benefits and social benefits. In other words, front-office employees are likely to

deliver customized services and goods to customers effectively. Additionally, customers tend

to feel a social connection when they are interacting positively with a front-office employee.

This finding echoes Berry (1995), whose research on relationship marketing in service

marketing emphasized that building up a relationship with a service provider makes

customers feel social benefits. Being different from physical goods, service is often based

primarily on personal interaction, and the service provider can adjust to the needs of the

customer as part of that interaction (Rust and Chung, 2006). According to Bowen (1990),

although airline services have moderate customer contact, the importance of front-office

employees in the airline industry is still empirically proven in this research. Also, the opinion

that front-office employees play an essential part in CRM implementation is again confirmed

(e.g. Yim, Anderson and Swaminathan, 2004, Chen and Popovich, 2003, Henning-Thurau

and Thurau, 2003 and Gwinner, Gremler and Bitner, 1998, etc).

Finally, we need to consider the influence of loyalty programs on confidence benefits,

special treatment benefits and social benefits. One of the objectives of loyalty programs is to

provide rewards to customers for repeat purchasing, and to motivate them to consolidate

their purchases with one provider or at least make it their preferred supplier (Winer, 2001,

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Derez and Nunes, 2008, Lovelook and Wirtz, 1996). Although the results of these analyses

do not show that loyalty programs are the most important factor in affecting confidence

benefits, special treatment benefits or social benefits, it is still found that they have a positive

effect on all three. In particular, it highlights the possibility that loyalty programs are able to

make an airline’s best customers feel a perceived sense of social achievement. This finding

confirms the research of Research and Develop, Inc, which found that JAL has recently

utilized its frequent flyer program to enable customers to attain more social benefits, e.g.

convenience, economic efficiency, status, etc. They also mention that, in the future, JAL aims

to work on providing customers with more functional benefits (confidence, special treatment

benefits etc) when implementing its CRM strategy. The findings of this research show that

loyalty programs also have a positive influence in terms of confidence and special treatment

benefits. Also, in contrast to previous research (e.g. Leenheer et al., 2006), this research

followed Wulf, Odekerken-Schroder and Lacobucci (2001) and Dreze and Nunes (2008) in

regarding loyalty programs as a combination program that provides customers with tangible

rewards and intangible rewards. The results clearly demonstrate that tangible rewards need

to be used alongside intangible rewards to provide relationship benefits to customers.

2-2. Practical Implication

Further to the findings showing that CRM does play an important positive role in

affecting customers' expectations of receiving the three types of relationship benefits, it must

be recognized that CRM efforts do not have an equal influence on all three. Based on the

findings I believe that it may be helpful for airlines to learn how to implement CRM strategy

more effectively. There are some significant practical implications to these research findings.

To begin with, the importance of front-office employees needs to be given particular

attention, since it proved to be the most important factor in influencing customers' expect to

obtain both special treatment benefits and social benefits. There are some special

suggestions for airlines. 1. Front-office employees should be hired based on their service

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capabilities, which means not only that they should be service-oriented, but also that they are

equipped with expertise in that service, and that they should be trained to be authentic in

their service domain. 2. Airlines should continue to encourage attendants to maintain active

communication with customers during their interaction process. Hennig-Thurau and Thurau

(2003) suggested that the social skills of employees are crucial for customer-oriented

behavior. Having social skills basically means that “when it comes to developing adequate

solutions for a customer’s needs or problems, the employee is able to take on that

customer’s perspective”. (Hennig-Thurau and Thurau, 2003, p.31) It requires the front-office

employees not only to understand what a customer sees and perceives, but also how the

customer thinks. Although this is not easy to accomplish, I consider it worthwhile for

Japanese airlines to work on educating their front-office employees so that they are

equipped with these social skills. 3. More use should be made of attendants in making

customers place their trust in the airline. This applies especially when it comes to delivering

customized services that make them feel satisfied, and adding continuous social value for

the customer.

Secondly, the importance of loyalty programs needs to be seriously considered.

Some research has emphasized the significance of loyalty programs. Bhattacharya and

Bolton (2000) claimed that RMIs, such as loyalty programs aimed at facilitating the

relationship, are an essential part of CRM strategy since they also lead to affective

commitment among customers. Leenheer et al. (2007) also suggested that loyalty programs

can create affective commitment, by which they meant that loyalty programs could prompt

customers into feeling a generalized sense of positive regard for and attachment to certain

service companies whilst helping those companies earn customer loyalty. Also, Liu (2007)

researched the relationship between loyalty programs and relationship commitment. He

pointed out that, because they reward customers for their purchases and maximize the

benefits they receive, loyalty programs may increase commitment and reduce customer

defection by raising switching costs. This research confirms previous claims of the

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importance of loyalty programs; therefore, it is crucial that airlines still make flexible use of

loyalty programs to provide customers with more benefits.

Furthermore, because the research results show that loyalty programs are an

important factor in providing customers with social benefits, I believe competitive loyalty

programs, which focus more on non-financial rewards, need to be created. It is easy for

loyalty programs to provide customers with financial rewards, for instance, free merchandise,

vehicle upgrades, extra air miles and free hotel rooms, etc. However, the financial based

reward program can be copied very easily by other competitors (Henning-Thurau and Thurau,

2003), and because some customers already hold many loyalty cards in their wallets, a

practical and crucial question that must be considered is how enthusiastic they are about

using them. Therefore, in order to provide a sustained competitive advantage, airlines should

continue trying to build up higher-level bonds with customers by utilizing their loyalty program.

According to Lovelock and Wirtz (1996), there are three types of higher-level bonds available,

which I think Japanese airlines need to work on providing to customers continuously. First,

there is the social bond based on personal relationships between providers and customers.

This requires attendants to pay great attention to effective communication with customers.

The second bond is created through customization, which requires airlines to make use of

their customer database to analyze customers' preferences so that they can provide them

with benefits (e.g. their preferred seats on the plane or a more convenient way of booking

tickets, etc). Lastly, structural bonds, which have been frequently seen in business-to-

business markets, could, I believe, still be considered as applicable to the airline industry.

Examples include a short message service for check-in or email alerts for flight delays to

avoid travelers having to wait at airports for a long time. In conclusion, I consider that

confidence, special treatment and social benefits will be delivered to customers more

effectively when those bonds are combined together through conducting a non-finance-

oriented loyalty program.

Finally, in a fiercely competitive market, driving customers' intentions towards using

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certain airline services over a long period is considered to be the primary goal for airlines. It

has become an inexorable trend for airlines to employ CRM strategy for targeting customers.

To make more effective use of CRM, I believe that airlines need to clarify the relationship

between CRM and customers' expectations of receiving benefits. This would help in terms of

thinking from the standpoint of customers when implementing CRM. While there are a

number of initiatives being recommended to airlines, because of the financial and cost

problems airlines are faced with, I suggest that the priority for airlines lies in providing

customers with expected benefits by utilizing CRM strategy. In other words, because front-

office employees are the people customers will interact with directly when they use an airline,

they should be trained appropriately in the first place. Dowling and Uncles (1997) pointed out

that the potential of a loyalty program to attract members depends not only on the value of

the rewards it offers, but also on when those rewards are available. Reynolds and Beatty

(1999) suggested that long-term customers tend to expect far higher social benefits.

Therefore, when designing frequent-flyer schemes, it is necessary to consider how long

customers have been in the loyalty program. In addition, it may be useful to send the loyalty

program’s members a statement containing accumulated points and various available

rewards to choose from at regular intervals.

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CHAPTER 7 Limitation and Future Research

In interpreting the results of this research, there are some limitations for future

research that must be clarified. Since my interests in this research were to determine

whether CRM efforts affect customer expectation, plus how to affect them, customer

intention factors, such as customer behavior loyalty and word-of-mouth, were not included in

this research. However, it has been argued in some research that relationship benefits may

drive customer loyalty. Examples of this include Berry (1995), who pointed out that social

bonding can drive customer loyalty when competitive differences are not strong. Therefore,

based on this research, future research could be done by utilizing some customer intention

factors to create a more complex structural equation model to test the sequential relationship

between CRM, customer expectation, and customer intention. Furthermore, this research

was conducted purely in the service industry by examining the airline service. Whether CRM

has an effect on customer expectations needs to be duplicated in some other industries,

such as retail, telecommunications, and so on. Additionally, this research was conducted in

Japan only, and according to Gwinner, Gremler and Bitner (1998) it is quite possible that the

perceived benefits are quite different in other cultural contexts. Therefore, it will be

interesting to test these hypotheses in, for example, China, or other countries. Finally,

although I believe it was quite reasonable to use affective commitment, loyalty programs and

front-office employees as the dimensions of CRM in this research, it would be possible to

use other dimensions of CRM for future research, since CRM means different things to

different people.

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Appendix 1

Variables and operational definitions

Name of

Variables

Label Operational Definitions References Scale

Affective

commitme

nt

AC I feel emotionally attached to the

airline.

Bansal et al…

(2004)

Gustafsson,John

son

andRoos(2005)

5

I take pleasure in being a customer

of the airline.

The airline company is the operator

that takes the best care of their

customers.

There is a presence of reciprocity in

my relationship with the airline.

I have feelings of trust toward the

airline.

Front-

office

Employee

FOE Attendants of the airline company

are equipped with authority.

Hart et al (1990);

Baker et al.

(2002);

5

Attendants of the airline company

treat customer well.

Attendants of the airline company

are willing to serve customers

friendly

Attendants of the airline company

are willing to serve customers

helpful.

Loyalty

program

LP

This airline rewards customers by

using both tangible and intangible

rewards for their patronage.

Wulf,

Odekerken-

Schroder and

Lacobucci

(2001);

Dreze and

Nunes (2008)

5

This airline offers customers

something extra (intangible rewards)

because they keep using its service.

This airline offers discounts to

customers for their patronage.

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Name of

Variables

Label Operational Definitions References Scale

Confidenc

e Benefit

CB I know what to expect when I use

this airline.

Hennig-Thruau,

Gwinner and

Gremler (2002);

Gwinner,

Gremler and

Bitner (1998);

5

This airline’s attendants have high

integrity.

I will not feel anxiety when I use the

airline.

I know I am going to get good

service from the airline.

Special

Treatment

Benefit

STB I get faster service than most

customers.

Hennig-Thruau,

Gwinner and

Gremler (2002)

5

I get better prices than most

customers.

I am usually placed higher on the

priority list when there is line to wait

for boarding.

They do services for me that they

don’t do for most customers.

I get discounts or free tickets that

most customers don’t get.

Social

Benefits

SB The attendants know my name. Gwinner,

Gremler and

Bitner (1998);

Hennig-Thruau,

Gwinner and

Gremler (2002)

5

I get personal recognition of the

attendants.

I enjoy certain social aspect of the

relationship.

64 / 65

Appendix 2

English Questionnaire

Demographic Questionings and confirm questions

1. During the past two years, how many flights have you been on?

2. What was the purpose of your flights?

3. Are you in the loyalty program (e.g. My Mileage program) of that airline company?

4. When *using this airline do you think you should receive any benefits from that company?

(e.g., customized service or discounts).

29. Your age.

30. Gender

31. Occupation

32. Your income in a year

Affective Commitment

5. I feel emotionally attached to the airline company.

6. I take pleasure in being a customer of the company.

7. The airline company is the operator that takes the best care of their customers.

8. There is a presence of reciprocity in my relationship with the airline company.

9. I have feelings of trust toward the company.

Front-office Employee

10. Attendants of the airline company are equipped with authority.

11. Attendants of the airline company treat me well.

12. Attendants of the airline company are willing to serve me friendly.

13. Attendants of the airline company are willing to serve me helpful.

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Loyalty Program

14. This airline company rewards customers (provide me with personalized services or free

tickets) for my patronage.

15. This airline company offers me something extra (e.g., priority on boarding or check in)

because I keep using its service.

16. This airline company offers discounts to me for my patronage.

Confidence Benefits

17. I know what to expect when I use this airline company.

18. This airline company’s attendants have high integrity.

19. I will not feel anxiety when I use the airline company.

20. I know I am going to get good service from the airline company.

Special Treatment Benefits

21. I want to get faster service than most customers.

22. I want to get better prices than most customers.

23. I could be placed higher on the priority list when there is line to wait for boarding.

24. They will do services for me that they don’t do for most customers.

25. I could get discounts or free tickets that most customers don’t get.

Social Benefits

26. The attendants will know my name.

27. I will get personal recognition of the attendants.

28. I enjoy certain social aspect of the relationship.