Online Shopping consumer behaviour

BEHAVIOUR OF ONLINE BEHAVIOUR OF ONLINE AND NONAND NON-- ONLINE SHOPPERSONLINE SHOPPERS

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TABLE OF CONTENTS

1. Introduction…………………………………………………………………..…...3

2. Online shoppers: products and services…………………………………..…….…4

3. Reasons for not shopping online: non-online shoppers………………...…………4

4. Demographic profile: Online shoppers………………………………………..…5

5. Demographic profile: Non-online shoppers...…………………………………..16

6. Psychographic profiles: Online shoppers…………...…………………………..25

7. Psychographic profiles: Non-online shoppers……………………..…………. .31

8. Promotional strategy: Online shoppers……………………..…………………..37

9. Recommendations based on the study…………………………………………..39

10. References ………………………………………………………………………41

11. List of Figures

Demographic profile of Online shoppers……………………………………….5

Figure.1 Products and services mostly shopped by online shoppers……….……..4

Figure.2 Influence of Age and Gender on online shopping………………………5

Figure.3 Influence of Marital status and Household size on online shopping….....9

Figure.4 Influence of Education and Occupation on online shopping…………..10

Figure.5 Influence of Designation and Income on online shopping ………….…12

Figure.6 Effect of Computer ownership and Years of using Internet on online

shopping………………………………………………………………………….14

Figure.7 Influence of internet usage on online shopping ………………………..15

Demographic profile of Non-Online shoppers………………………………..16

Figure.8 Influence of Age and Gender on online shopping……………………..17

Figure.9 Influence of Marital status and Household size on online shopping…..19

Figure.10 Influence of Education and Occupation on online shopping…………20

Figure.11 Influence of Designation on online shopping………………………....20

Figure.12 Influence of Income on online shopping………………………….…..21

Figure.13 Influence of Computer ownership and Years of internet usage on online

shopping…………………………………………………………………………23

Figure.14 Influence of Internet usage and number of online Non-shoppers……24

Psychographic profile of Online shoppers…………………………….……...24


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Figure.15 Influence of Risk and Innovation on online shopping…………….….25

Figure.16 Influence of Brand and Price consciousness on online shopping…….27

Figure.17 Influence of Convenience and Variety seeking on online shopping….29

Figure.18 Effect of Impulse buying on online shopping………………………...31

Psychographic profile of Online Non-shoppers………………………………32

Figure.19 Influence of Risk and Innovation on online shopping………………..32

Figure.20 Influence of Brand and Price consciousness on online shopping…….33

Figure.21 Effect of Convenience and Variety seeking on online shopping……..35

Figure.22 Effect of Impulse buying on online shopping………………….….….36

Promotional Strategy for Online shoppers…………………………………...37

Figure.23 Influence of Advertisement and Attitude on online shopping……….39

List of Annexure

1. Attached copies of questionnaires filled by online shoppers

2. Attached copies of questionnaires filled by online non-shoppers

Introduction

A random sample was undertaken to ascertain the behavior of online and non-online

shoppers. The sampling method applied guarantees equal chance of selection for each

observation in a population. The assumption is that the population is relatively

homogeneous with respect to the random variable under study, Trevor Wegner (1999, pg

172). This research combines aspects of both formative and summative evaluation (Fox,

Bartholomae, and Lee 2005) and relies on data from quantitative and qualitative methods.

Quantitative data from General Questionnaire section create the bones of the story to be

told from participants' background and experiences in this research, while qualitative data

from Specific Questionnaire section help to put flesh on the bones.

Hypothesis testing and estimation are the two key elements of inferential statistics that

will be applied in analyzing sample data. Questionnaires were randomly distributed to

prospective respondents in Harare, Zimbabwe where many people of diverse

demographic features are domicile. We recognize that the sample population may not be

representative of the Online shopping population since we confined our study to an urban


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set up, geographical location. We are cognizant of the technology gap between rural and

urban areas with more information, communication and technology (ICT) infrastructure

confined to the major cities and towns. Despite this issue, we maintain that the sample is

of interest from a research perspective as results will be salvaged by fair proportions of

rural to urban migration, urbanization. The study will hence produce useful information

that may reflect the behavior of both online and non-online shoppers.

1. Products and services shopped by Online shoppers:-

Product Service

1 Clothing Hotel bookings

2 Cars and car parts News-business, sport

3 Furniture Tutorials

4 Cosmetics Music downloads

5 Groceries Banking-wire transfers

6 Books E-books

7 CDs –Music, Movies Entertainment-golf, chess

8 Electrical gadgets Online phone book

9 Medicines-Drugs Utility bill payments

10 Cell phones Health and Beauty therapy

Figure1. Products and services shopped by On-line shoppers

2. Common reasons given by non-online shoppers for not shopping online:-

• No access to internet

• Perception of high costs associated with online shopping

• Risk aversion emanating from fear of Cyber fraud/terrorism

• Prospective customers lack awareness on availability of online shopping

facility

• Intermittent internet connectivity challenges faced by internet service

providers discourage online shopping


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• Failure by local banks to provide VISA and Master cards making online

shopping not practical.

• Inadequate Information Communication and Technology (ICT)

infrastructure suppressing online shopping desire

3. DEMOGRAPHIC PROFILE – ONLINE SHOPPERS

Demographics exude the different characteristics of shoppers on the market producing

essential information for formulation of an appropriate marketing mix. The target market

which comprises of homogenous clusters of similar tastes and preferences will

undoubtedly influence the type of strategy to implement. Marketing objectives of profit

maximization, customer satisfaction and increased market share will be achieved once we

understand customer expectations and manage to deliver goods and services.

Responses from the sample were recorded accordingly on Questionnaires before any data

analysis and derivation of information. The following are the noted mutually exclusive

demographic profiles of Online and Non-Online shoppers:-

(a) Online Shoppers

Influence Of Age On On-line Shopping

11

5

01

0123456789

10111213

23-32 33-39 39-44 45-54

Age (years)

Num

ber O

f Peo

ple

Influence Of Gender On On-line Shopping

35% 65%

MaleFemale

Figure 2: Influence of Age and Gender on On-line shopping


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Analysis: A sample of 34 people who were interviewed indicated that 65% (11out of

17) of the seventeen online shoppers were Generation Y. Generation Y is a grouping of

people of ages that vary from 14-32 years, represented by 11 of respondents interviewed

as indicated in Fig 2 above. It is composed of people who are innovative, celebrate

diversity, rewrite the rules, assume technology and reflect optimism. The grouping is also

more-skilled and multi-tasking, agile in making decisions, evaluating risks and managing

dilemmas, flexible and persistent in the face of change, highly skilled in social

networking and team activities. Spiro, (2006) referred to this grouping as comprised of

optimists, educated, having collaborative abilities, open-mindedness drive .The group

was referred to as "the first generation of digital natives" by Sarbu (2008) . Studies by

(Club It&C, Anon., 2008a) revealed that there was a heavy influence and rising interest

by Generation Y towards new services and technologies, and greater media flexibility.

On the other hand Generation X (33-44years) is pragmatic, individualistic and rejects

rules. They represent 29% (5 out of 17) of the seventeen online shoppers. Baby boomers

(45-54years) constitute 6% (1 out of 17) of the seventeen online shoppers. They are

idealistic, conform to rules and consider diversity as a cause. The work of Grewal, Levy

(2010,p123) concluded that there are five distinct age groups in a population vis-à-vis

Tweens, Generation Y, Generation X, Baby boomers and Seniors.

Conclusion: The survey under review showed that Generation Y, Generation X and

Baby Boomers actively take part in online shopping. Age is a very important determinant

of online shopping as perceptions, tastes and preferences are intrinsic at particular stages

of human growth and development. Jasper and Lan (1992) found that as age increases,

tendency to catalog shop also increases. Generation Y is composed of people who are

technology savvy and risk takers. As marketers redefine their marketing mix and

strategies, emphasis should be particularly focused on this grouping since they rewrite the

rules, assume technology and reflect optimism. Results obtained reflect that basically

online shoppers are younger in conformity with research work of (Zhang, Prybutok, and

Strutton 2007). Allred, Smith, and Swinyard 2006 also confided that online shoppers are

younger, possess greater wealth, are better educated, and spend considerably more time

on the Internet.


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Since societies are digitized with constant quantum leaps in technology, there is need to

create awareness among all age groups on the advantages of technology initiatives.

Gamble et al., 2007 concluded that organizations should adapt their strategies

accordingly and acknowledge their online consumers' constantly shifting needs and

expectations.

Baby boomers and Seniors should also be targeted in marketing efforts although younger

cohorts are the "computer generations" and will be more likely to purchase online than

older consumers. Online shoppers are younger, possess greater wealth, are better

educated, and spend considerably more time on the Internet (Allred, Smith, and Swinyard

2006; Swinyard and Smith 2003). A recent study by Nicoleta-Dorina Racolta-Paina

(2010, pg. 85) indicated the products that Generation Y are associated with since their

childhood. The products include computers, laptops, digital photo & video cameras,

portable MP3 players, cell phones, iPhones or other gadgets which are part of their

everyday life.

Consumer buying behavior is not only determined by age but other factors should also be

considered as outlined by Bellman et al. (1999) research. The research indicated that

demographic variables such as income and education besides age also have a modest

impact on the decision of whether to buy online (Jayawardhena et al., 2003, p. 124)

Gender

Analysis: As illustrated in Fig 2 above Male represents 65% while female constitute

35% of the total online population. Cultural perceptions and tendencies which had men

dominating in most decision making, taking more part in formal employment , pursuing

with education and earning more salary than female; all result in less women online

shoppers. The drive by the government (Zimbabwe) to ensure gender equality and

employment creation for women seeks to redress the anomaly. A Ministry to that effect

as well as other initiatives is aimed at reducing the imbalances between men and women.

More preference and opportunities are extending to women endeavoring to capture a

secluded lucrative market for consumer, health, beauty, fashion and style industries.

Gender has an influence on online shopping as recent studies have indicated that male are

frequent shoppers than female, Ernst and Young ('Global Online Retailing' 2000) .The


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evidence shows that frequent online shoppers (five or more times) tend to be male, while

infrequent shoppers (less than five times) tend to be female. Respondents answered the

questionnaire basing on the frequency or rate at which they do online shopping.

Conclusion: Capturing the minds and influencing the behavior of women is essential in

extending a market base. Women are presumed repeat buyers exuding loyalty as reflected

through their behavior in buying cosmetics and fashionable clothing. There is need for

marketers to develop their market through reaching out to new markets with new

products by exploitation of the untamed resources.

The nature of the product, lead time and technology conversant can have psychographic

effects in stimulating online purchasing behavior.

Luxury goods that consumers can buy after a longer time frame of familiarization with

marketing mix offering can be compared with consumer goods. Consumer goods are

basically required instantly to satisfy needs hence intolerant to time delays in making

purchasing decisions. Men therefore spend considerable time in shopping online for cars,

electrical appliances and cell phones. Women on the other hand mainly search for

cosmetics and clothing which are now readily available in shops hence less time in online

shopping.

Lead time refers to the time taken for delivery of products once payment has been made.

The higher the lead time the more dissatisfied the consumer and the lesser the desire for

online shopping. Psychographic factors also assist in the decision making and purchasing

function as commitment, patience and endurance are important. Male prove to be more

patient with stretched lead time on purchased capital goods than women. The percentage

of online shopping is thus higher than females’ as a result of the tolerance on lead time by

men.

Some women have a slight tendency of avoiding technical tasks which inevitably

prejudice them from benefiting from the fortunes of Cyber digitization.

Whilst intentions to purchase online for male consumers have been found to be

significantly greater than for female consumers (Zhang, Prybutok, and Strutton 2007),

there is need to encourage women to intensify their efforts. These results provide a reason

for retailers to target advertising at websites heavily patronized by women.


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Marital Status and Household size

Marital status analysis: A significant number of people interviewed were married

0

2

4

6

8

10

12

Num

ber o

f per

sons

1 2_3 4_5 6_7 7> Household size (Number)

Influence of Household size on Online shopping

Figure 3: Influence of Marital status and Household size on On-line shopping

constituting 53% of the total population as highlighted in Fig 3 above. Marital status is

important in online shopping since it is part of the demand for goods and services. There

is a positive correlation between marital status and household size. Since the number of

people per household determines the bargaining power and appetite for market

deliverables, there is need to seriously consider the role marital status plays in online

shopping. In Zimbabwe due to the adverse economic environment, households shrink to

sizes of 4 at most. High costs of living, unemployment, increasing poverty levels, high

infant mortality rates, scourge of HIV/AIDS pandemic and unstable political environment

all contributes to a smaller family size.

Household size analysis: The diagram above also illustrates that on average a

Zimbabwean family that has capacity to shop online is composed of 2 to 3 members.

People have adopted birth control methods to reduce birth rate hence a smaller family

size. There has been a growing desire to pursue with Education in line with the

government initiative of improving literacy rates coupled with a personal desire to secure

Marital Status Frequency Percentage

Single 9 53

Married 8 47

Divorced - -

Widow/r - -

Living together - -

Total 17 100


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better jobs. Products with a bias towards promoting education such as textbooks,

computers, online tuition thus have a ready market.

Education and Occupation

0

1

2

3

4

5

6

7

No.

of p

erso

ns

Ord Level Certificate FirstDegree

Qualification

Influence of Education on O nline shopping

Figure 4: Influence of Education and Occupation on On-line shopping

Education analysis: Ordinary level is considered the basic education qualification in

Zimbabwe based on five passes at C or better grading in any Arts and Humanities,

Human and Social Sciences and Commercial subjects. The duration of studies is mainly

four years before attaining the qualification .Advanced level which is equivalent to

Matriculation level, is a platform slightly above Ordinary level. The duration of studies is

a two year period with areas of specialization in Arts, Sciences or Commercial subjects.

Figure 4 above shows that the majority (71%) of the respondents had at least a Diploma

or better indicating that more educated people appreciate online shopping better.

Conclusion: As people progress in personal growth and development through education,

they have more affinity to technology applying theory to practical situations. There are a

growing number of people who make wire transfers to foreign institutions for tuition

Occupation No of

Persons

%

Agriculture 1 5

Finance 5 29

Tourism 1 6

Health care 2 12

Engineering 1 6

Manufacturing 1 6

Retail 1 6

Distribution 1 6

Services 2 12

Other 2 12

Total 17 100


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purposes. Many Generation Y students are taking studies through ACCA, CIMA, CFA,

IMM and other graduate and postgraduate foreign universities. Universities in UK,

Malaysia, Singapore and South Africa are providing online tuition services serving the

Zimbabwean youths. Respondents to the questionnaire indicated that internet shoppers

are more educated (Zhang, Prybutok, and Strutton 2007).

Occupation analysis: Economy is a broad spectrum of various sectors with the main

objective of ensuring growth and development of the whole nation. All sectors of the

economy are represented as illustrated in Fig 4 above indicating that online shopping is

across the board and not confined to one sector. The Financial sector makes 29% while

Health care and Services make 12% use of online services respectively. The nature of the

industry necessitates use of online services as Finance sector oils the whole online

shopping by providing the platform for use of credit and master cards. Industries in

Retail, Distribution and Tourism rely on the robust framework established by the Finance

department under the auspices of Information technology sector. Online marketing

strategies should be tailor made to suit specific needs of the respective sector.

Conclusion: While both private and industrial buyers are responsible for the global

volume of e-business, these groups differ markedly from each other. Industrial e-buyers

tend to be more informed, more structured in their decision making processes, more cost

conscious, and more responsive to company norms concerning Internet usage (Kennedy

& Deeter-Schmelz, 2001). Private users, on the other hand, tend to be influenced by a

narrower set of specific factors, such as return policy (Wood, 2001) and other general

behavioral variables.

Designation and Income

Designation analysis: The diagram below illustrates that of the seventeen online

respondents, 71% are non-managerial staff whilst management constitute 29%. As we

move the corporate ladder, the ratio of employees at managerial level declines whilst the

more the income received hence more disposable income. The marginal propensity to

consume tend to rise with availability of more income The clerical staff are expected to


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be more price conscious as they receive lesser salaries than their superiors. The pattern

also has effect in online shopping where we expect to find more participation of price

Designation Income

Influence of Income on Online shopping

0

1

2

3

4

5

6

<2700 2701-6000

6001-12000

12001-18000

18000<

Annual Income ($)

No of People

Figure 5: Influence of Designation and Income on On-line shopping

sensitive clerical staff in the electronic field. A strong perception of affordability

stimulates the online mode of shopping by the clerical staff. Managerial staff may tend to

be ignorant of price changes hence inelasticity to variation of prices on traditional

shopping mode.

Conclusion: One may expect managers to be better shoppers online than the clericals

given that they have more access to the internet. In some organizations as we discovered,

Internet is a privilege available only to Managers of higher ranks. In our research we

discovered that 65% of respondents use computers owned by their employers. If as

highlighted earlier, the employer sanctions internet to only higher managerial ranks that

constitute a minority then the number of online shoppers will be reduced. The data

gathered on internet usage per week also clearly demonstrates that respondents had fewer

online surfing hours per week. More time is dedicated in performing business related

Senior Management (1)

Middle Management (3)

Supervisor (3)

Officer (3) Officer (3)

Clerk (3)


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searches depriving users the opportunity to fully benefit from online services. We also

noted that respondents were averse of internet café’s which they considered much

expensive as web browsers take long in connecting hence higher charges. Management

have more time to engage in online shopping at work places as they delegate most of the

work to subordinates. Since management constitutes only 29% of the work force

subsequently we expect the volume of online shopping to slacken as number of users

deplete.

Income analysis: Income plays a crucial role in online shopping as more real disposable

income means more online shopping. Gross Domestic Product Per Capita income is also

very important as it determines standard of living and capability to shop by an individual.

Figure 5 above indicates that 59% of the respondents earn an average annual income of

US$9,300 which converts to a monthly figure of US$775. The grouping has favorable

disposable per capita income to utilize in online shopping. As researched by Zhang,

Prybutok, and Strutton (2007), thus we can deduce that internet shoppers have higher

incomes.

Conclusion: In the study by Darían (1987), in-home shoppers tend to have higher levels

of income, are above average in education, and are younger than in-store shoppers

Computer Ownership and Years of using internet

Computer ownership analysis: A significant number of online shoppers (64%) make

use of computers owned by their employers whilst 36% owns computers as reflected in

Figure 6 below. Computer ownership is important in influencing online shopping as

people make shopping at different convenient time. Employer owned computers are

mainly used for business operations during working hours limiting the time for personal

online shopping. As indicated later on there is a correlation between computer ownership

and hours of internet use per week. Where employer owned computers are used more

hours of internet surfing are committed to business whereas fewer hours are for private

shopping.


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Conclusion: Since most people make use of employer owned computers marketers

should target company websites with banners of their products and services. The users

spend most of their time at work hence less time for personal online shopping.

Consumers mostly make use of employer owned machines for internet as they consider it

cheaper than Internet Cafes. The intranet or extranet system at workplaces should fully

Influence of Computer ownership on Online shopping

0%

36%

0%

64% Owned

Employer's

Internet Café

Rented

Figure 6: Effect of Computer ownership and Years of using Internet on online shopping

Years of using Internet analysis: The table above indicates that 65% of respondents

have more than four years experience in using the internet. In terms of ability to use the

internet in online shopping, most respondents expressed satisfaction. However, inherent

risk and costs associated with online shopping inhibit the full utilization of the service.

There is need to perfect on security issues and improve on connectivity as consumers

desire the best service. A significant number of online shoppers saw low costs and

substantial benefits associated with e-shopping. They were experienced Internet users

Years of Using

Internet

No of

Persons

%

<1year 1 6

1-2years 2 12

2-3years 0 0

3-4years 3 17

4years< 11 65

Total 17 100


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who valued online information searching, Yehoshua Liebermann: (Dec 2009. pg. 316, 16

pgs).

Conclusion: Zhang, Prybutok, and Strutton (2007) concluded that internet shoppers

display higher levels of internet and e-mail usage. We noted that more ISPs are entering

the lucrative market competing extensively in offering the best service at affordable

prices to customers. Internet surfing charges have effectively diminished as the

competition intensifies. Improvements in technology have also seen internet applying not

only to computers and laptops but to cell phones. The trend of committing more time to

online shopping is fast approaching as ISP strive to provide tailor made ICT oriented

products and service. Consumers are set to benefit immensely from removal of Customs

duty on all imported IT hardware and software material. The number of online users will

increase as ISPs also extend their services. If consumers own the computer resource and

have internet access, then the environment will be more conducive to online shopping.

Internet Usage per week (hrs) and Number of Online shoppers

0

1

2

3

4

5

6

7

8

910

Num

ber o

f per

sons

<7 7_14 14_21 21<

Time of internet use per week (hrs)

Influence of Internet usage on Online shopping

PrivateBusiness

Number of Online Shoppers

17

Yes No

Figure 7: Influence of Internet usage on online shopping


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Internet usage analysis: As highlighted in Figure 7 above 82% of respondents spend 7-

14 hours surfing for goods and services on the internet. Costs associated with surfing on

the net hinder online shopping as reflected by the less hours of private use of the internet

as time of use increases over the week. As hours of internet surfing increases more

emphasis will be on business related work depriving time of private use.

Conclusion: In order to increase rate of internet use and online shopping, there is need

for marketers to effectively create more awareness on the benefits of using online

shopping. Whilst more hours may reflect more online shopping, one should understand

that decision making can be effected even where

Number of online shoppers’ analysis: There is equal number of online and traditional

shoppers owing to various reasons such as, costs, connectivity, risks and ignorance on the

part of consumers.

(b) Non-Online Shoppers

Non-online or traditional shoppers do not fully make use of the internet when shopping.

They may be aware of its existence but are reluctant of utilizing the facility in their

consumption pattern. When talking about consumer behavior, there are several factors

that clearly influence it, such as: social (given by culture, subculture, social class,

reference groups, family and roles and status), personal (given by and age and life-cycle

stage, occupation, lifestyle, personality, self-concept and economic circumstances),

psychological (influenced by motivation, perception, learning and beliefs and attitudes)

and situational (Drummond et al., 2008).

Age and Gender

Age analysis: Generation Y age group constitute 82% of non online shoppers as

indicated in Fig 8 below. Although the grouping is endowed with technology acumen,

they expressed reservations on online shopping. There were mixed feelings with regard

the use of internet by non-online shoppers. Most respondents indicated that since they did

not own computers they resort to traditional shopping. Some of the respondents professed

ignorance as they acknowledge availability of the facility but lacked interest in utilizing

the avenue. Failure by retailers to effectively create awareness on availability of their


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Influence of Age on O n-line shopping

0

2

4

6

8

10

12

14

16

<23 23-32 33-39 39-44 45-54

Age (years)

Num

ber o

f Peo

ple

Influence Of Gender on On-‐line Shopping

47%

53%

MaleFemale

Figure 8: Influence of Age and Gender on On-line shopping

products on the internet was also outlined as one reason for not shopping online. Seniors

who are traditional shoppers constitute 6% mainly due to fewer numbers in that group as

life expectance declines to mid forties. Poor health provisions and effects of HIV/AIDS

scourge have adversely distorted this market segment.

Conclusion: There is need to reach out to traditional shoppers selling the benefits of

online shopping whilst adding value through various respective market deliverables.

A Pew Internet &American Life Project "found that those segments remaining

disproportionately unconnected to the Internet included the following: the elderly, rural

residents and the poor " (The Pew Internet &American Life Project, 2002-2005, cited in

Reisenwitz et al., 2007)

Gender analysis: As indicated in Fig 8 above, respondents interviewed comprised 53%

men and 47% women who were non-online shoppers. Ancient societal values regarded

men as bread winners of households thus the higher number of male non-online shoppers.

Most men expressed displeasure in costs associated with online shopping indicating that

their disposable income was inadequate to support the method of shopping. Time and


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financial constraints were the main reason for shunning the system. Modernization

brought awareness and the active participation of women pressure groups redefining the

role of women in society as equals with men. Women are now encouraged to take up

male dominated jobs. Men have thus shown that due to various instant demands, they had

no time and courtesy to engage in online shopping.

Conclusion: Gender is important in both online and traditional shopping methods as taste

and preferences vary respectively. Consideration of the factor is essential in any market

planning as it provides a clue to the expected demand for goods and services.

Marital Status and Household size

Marital status analysis: The ratio of single online non-shoppers to married non-

shoppers is 3:2 as portrayed in Fig 9 below. Single persons generally have fewer

responsibilities than the married hence have more disposable income to afford even

luxuries apart from necessities. Most of the single respondents come from small

households where because of the convenient size has more disposable income for

shopping.

Household size analysis: The household size of non-online shoppers is similar to that of

online shoppers as most respondents have small family units of three members at most as

shown in Fig 9 below owing to reasons already mentioned. It therefore indicates that

there are other factors to consider apart from household size in understanding the

behavior of consumer shopping. Factors such as disposable income, perceptions and

education should also be considered respectively.

Conclusion: The provision of security assurance to risk-averse respondents may convert

traditional to online shopping behavior.


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0123456789

101112

Num

ber of persons

1 2_3 4_5 6_7 7> Household size (Number)

Influence of Household size on Online shopping

Figure 9: Influence of Marital status and Household size on On-line shopping

Education and Occupation

Education analysis: Fig 10 below shows that the majority of traditional shoppers are

better educated just like online shoppers. It is important to note that other factors such as

perceptions and attitudes apart from education should be determined in studying the

behavior of online consumers.

Occupation analysis: The finance sector has the highest number of online non-shoppers

(Figure 10) due to its size on the whole market followed by Retail, Services and Health

care industries. Unavailability of credit cards and lack of confidence in electronic

shopping are among some of the reasons cited by non-online shoppers.

Conclusion: There is need to educate people on the advantages of online shopping as that

area has not been given enough coverage. Consumers are better educated in other

faculties of learning but needs more clarion assistance in accepting internet as a

convenient method of shopping.

Marital Status Frequency %

Single 10 59

Married 7 41

Divorced - -

Widow/r - -

Living together - -

Total 17 100


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0

1

2

3

4

5

6

7

No. of p

ersons

Ord Level Certi ficate Firs tDegree

Qual i fication

Influence of Education on Online shopping

Figure 10: Influence of Education and Occupation on On-line shopping

Designation

Figure 11: Influence of Designation on On-line shopping

Occupation No of Persons %

Agriculture 0 0

Finance 7 41

Tourism 0 0

Health care 2 12

Engineering 1 6

Manufacturing 0 0

Retail 4 24

Service 3 17

Other 0 0

Total 17 100

Senior Management (1)

Middle Management (5)

Supervisor (2)

Officer (2) Officer (2)

Clerk (3)


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Analysis: Middle management constitute 29% of traditional online shoppers as shown in

Fig 11.The grouping has less time for online shopping as they engage in the day to day

running of the organization.

Conclusion: Designation at work plays a role in stimulating demand and participation in

online shopping. The Board of directors formulates strategy which management

implements as operational workforce execute duty. At corporate level executives and

management are very important in internet shopping as they have sole decision making.

Expectations are that as we ride the corporate ladder, management should be more

involved with internet shopping. However it is important to note that time constraints and

perceived costs hinder online shopping.

NB: - One person is self employed while the other is unemployed.

Income

Influence of Income on Online shopping

0

1

2

3

4

5

6

7

<2700 2701-‐6000 6001-‐12000

12001-‐18000

18000<

Annual Income ($)

Num

ber o

f peo

ple

No of People

Figure 12: Influence of Income on On-line shopping

Analysis: The graph above (Fig 12) outlines that of all the non-online shoppers

respondents, 53% earn low income whilst 35% and 12% earn average and high income

respectively. Carr and Schuetz (2001) theorize that lower-income families' nonuse of

traditional financial services occurs for complex reasons including: unfamiliarity with


21

banking and savings services, not writing enough checks to justify an account, and

distrust of mainstream financial services providers. There is a tendency for low income

earners to have relatively high debt payment to income ratios which relatively more

likely to make late bill payments and, as a result, pay more for credit (Aizcorbe et al.

2003 cited in Hogarth and Anguelov 2004)

Conclusion: Overall, mainstream financial institutions' service of low-income

communities continues to lag; however, some financial institutions and other purveyors

of financial products have begun to recognize the potential for capturing these relatively

untapped markets with new products. Financial institutions are investigating whether the

lower cost of service that technology enables makes it worth the institutions' effort to

expend the resources necessary to capture these markets. Banks are now exploring the

potential of information technology (IT) banking tools to serve low-income customers

and to attract the unbanked, (Alderslade 2005).As noted the reduced availability of

financial literacy training for low income persons represents a barrier to achieving

financial literacy. Low incomes also limit the demand for such services among this group

even when available. Therefore, it may be necessary to subsidize financial literacy

programs for low-income persons to bring their level of literacy to an appropriate level.

Such programs may have large returns because previous research has shown that

financial literacy is an important determinant of economic well-being (Bernheim 1998;

Jacob, Hudson, and Bush 2000)

Computer Ownership and Years of using Internet

Computer ownership analysis: Non-online shoppers who uses their employer’s

computers constitute 41%, whilst use of owned, internet café and rented constitute 35%,

18% and 6% respectively (Fig 13 below).

Conclusion: Unavailability of internet access by respondents who use employer owned

computers is a major drawback in online shopping. The costs related to renting computers

were also considered high by most respondents.


22

Years of using internet analysis: Non-online shoppers with more than four years of

using internet constitute 71% indicating that most people are aware of availability of the

service. The need to provide a secure internet system is essential in capturing the large

grouping of non shoppers to actively participate in online shopping. However, some

respondents (17%) were ignorant of the available facility as reflected by their short

period engagement of less than one year.

Conclusion: Bellman et al. (1999) found that the three strongest predictors of Internet

shopping were looking for product information, number of months of online experience,

and number of daily emails received. These variables are somewhat reflective of the

ability to navigate the Internet (i.e., "Internet functional"). On the other hand, the

strongest predictors of shopping online according to Lynch et al. (2001) were site quality

trust in the vendor, and positive affect toward the site.

Influence of Computer ownership on Online shopping

41%

35%

6%

18%

OwnedEmployer'sInternet CaféRented

Figure 13: Influence of Computer ownership and Years of internet usage on online

shopping

Years of

using

Internet

No of Persons %

<1year 3 17

1-2years 1 6

2-3years 0 0

3-4years 1 6

4years< 12 71

Total 15 100


23

Internet usage per week analysis: As indicated in Fig 14 below, non-online shoppers

who use the internet for at least seven hours per week for private online shopping

constitute 71%. When the number of hours of internet use per week increases, the

business use mode rises as shown by the 18% respondents that use the internet for

business for more than twenty one hours per week. Company resources are utilized with

strict measures such as use of internet for business related use only depriving most users

more time to perform online shopping.

Internet usage per week (hrs) and Number of Online Non-shoppers

Conclusion: Loyal internet shoppers are expected to have more hours of accessing the

internet per week. Kwak et al. (2002) identified other predictors of Internet shopping,

including amount of onsite product information, Internet involvement, and product

opinion leadership. These variables reflect a combination of Internet functionality and

affective experience.

Number of online non-shoppers analysis: The number of non-online shoppers and

shoppers is equal due to various reasons mentioned in the foregoing.

0

2

4

6

8

10

12

14

Num

ber of persons

<7 7_14 14_21 21<Time of internet use per week

(hrs)

Influence of Internet usage on Online shopping

PrivateBusiness

Number of Online Shoppers

50%

50%

Yes No

Figure 14: Influence of Internet usage and Number of on online non-shoppers


24

4. PSYCHOGRAPHIC PROFILES-SPECIFIC QUESTIONNAIRE

Attitude is "a psychological tendency that is expressed by evaluating a particular entity

with some degree of favor or disfavor" (Eagly and Chaiken, 1993, p. 1). Attitude has a

strong influence on consumers' buying intention (e.g. Ryan, 1982). Applied to the present

study, attitude toward online purchasing is considered to be a function of the consumer's

beliefs about an e-store's characteristics and the degree of subjective importance a

consumer attaches to those attributes (Fishbein and Ajzen, 1975)

4. (a) Online Shoppers

The behavior of online shoppers can be studied better through understanding their

psychographic tendencies. Responses from the questionnaire were collated, averaged and

utilized in analyzing the data. Ratings were subsequently allocated on a scale of response

of 1-5 vis a vis; Strongly agree -1; Agree -2; Moderate -3; Disagree -4 and Strongly

disagree -5. We deduced the following from our research finding:

Risk taking tendency and Innovativeness Diagrams:-

1

2

3

4

5

6

7

8

9

10

11

No. of p

ersons

Stronglyagree

Moderate Stronglydisagree

Response

Influence of Risk on Online shopping

AverageResponse

01

23

45

67

No. of p

ersons

S.Agree Mod S.Disagree

Response

Innovativeness influence on Online shopping

Av.Response

Figure 15: Influence of Risk and Innovation on online shopping


25

Risk taking tendency analysis: Shopping on the Internet has been associated with

carrying risk. In particular, privacy-related concerns, identity and credit card theft, and

lack of order fulfillment (or order errors) have all been noted concerns (Dubelaar, Jevons,

and Parker 2003). Ease of product returns also troubles some shoppers. All of these issues

increase risk, and subsequently influence the decision to shop online. Perception risk

which is prevalent among online shoppers was defined as the consumer's perception of

the uncertainty and concomitant adverse consequences of buying a product or service

(Dowling and Staelin, 1994). Liebermann and Stashevsky (2002) produced a map of

perceived risks that create a barrier to potential Internet users, which of course could

inhibit e-commerce as well. The leading perceived risks involve the loss of credit card

and other personal information.Bauer (1960) in his seminal work on risk-taking set forth

the idea that consumer behavior involves risk in the sense that any action of a consumer

will produce consequences that he or she views with some degree of uncertainty. In the

psychology literature, perceived risk has been described as consisting of a set of possibly

interrelated components: financial, performance, physical, psychological, social, and time

and convenience, yielding a separate measure of overall perceived risk (Jacoby and

Kaplan, 1972).

Conclusion: The majority of online shoppers (88%) (indicated in Fig 15) interviewed

were strongly risk averse and considered safety a priority. Campbell and Goodstein

(2001) point out that there are various types of perceived risk (financial, performance,

social, psychological and physical) and that often times one or more of these sources may

drive consumers' overall perceptions of risk. The importance of each type of risk will

vary significantly across product/ service categories and national cultures. As with

different cultures ascribing different meanings to the same occurrence or event this will

influence how consumers perceive risk. Nakata and Sivakumar, (2001) concluded that

this leads to significant differences in perceived consumer risk of purchasing

products/services online across national cultures.

Innovativeness analysis: In the context of online consumer behavior, Goldsmith (2000)

and Limayem et al. (2000) found that personal innovativeness is a personality trait that


26

explains consumer online buying intention. Innovativeness is the relative willingness of a

person to try a new product or service (Goldsmith and Hofacker 1991). Following the

rationale of Donthu and Garcia (1999), innovativeness was a key attribute of the online

shopper segments of actualizers and experiences (SRI International 1995). Actualizers as

a consumer segment are active, very discriminating in their purchases, and also rather

adventurous in their activities. Experiencers are innovative and modern, seek stimulation,

and are also considered trend setting or fashionable (SRI International 1995). Donthu and

Garcia (1999) found empirically that online shoppers were more innovative than no

shoppers. Another study by Goldsmith and Flynn (2004) looked at a specific type of

online purchasing (clothing) and found that innovativeness was a significant predictor of

online consumption

Conclusion: Online shoppers interviewed comprise of both Actualisers and Experiencers

who exude innovative shopping characteristics. We therefore predict that Internet

shoppers report more innovative behavior than non-shoppers.

Brand and Price consciousness diagrams:-

01

23

45

67

No. of p

ersons


Response

Influence of Brand on Online shopping

Av. Response

02

46

No. of p

ersons


Response

Influence of Price on Online shopping

Av. Response

Figure 16: Influence of Brand and Price on online shopping


27

Brand consciousness analysis: Brand consciousness is a shopping orientation, which is

characterized by the degree to which a consumer is oriented toward buying well-known

branded products (Shim and Gehrt 19%; Sproles and Kendall 1986). In-flight shoppers

have also been shown to have higher levels of brand consciousness (Huang and Kuai

2006). Donthu and Garcia (1999) suggest that the major forces on the Internet who are

selling products to consumers are well-established and well-known companies. These

companies tend to have very high brand recognition. Research suggests that high brand

recognition will lower the risk to the consumer when purchasing online (Tan 1999). As a

result, individuals will feel more reassured purchasing online if they are buying from an

entity with a name they know and trust. Internet shoppers will be more brand conscious

than non-shoppers.

Price consciousness analysis: The Internet facilitates price comparison, and Internet

shoppers often look for multiple alternatives when shopping due to the lower search costs

of shopping on the Internet (Donthu and Garcia 1999). Prices are therefore more

transparent in that consumers can find out the variety of prices in a market with

considerable ease (Laudon and Traver 2008). One benefit of reduced search costs and

price transparency is that consumers can easily find out the lowest prices available for a

specific product service on the Internet. Our conceptualization of a price-conscious

shopper refers to this ability of the Internet shopper to look for and compare multiple

alternatives due to reduced search costs on the Internet with a view of finding the lowest

available price. The Internet shopper therefore spends less time and money locating the

desired product at the desired price. Given their product search capabilities, online

shoppers are considered to be well-informed consumers (Hoffman and Novak 1997).

Smith (2002) notes that consumers readily utilize shop bots that can search the Internet

for the best price and value. Even though this suggests that online shoppers are more

likely to be price conscious, Donthu and Garcia (1999) did not find this to be the case in

their study. They show that many online buyers are less price-conscious, as they are more

concerned with finding products that satisfy their needs rather than looking for bargains.

Another research effort found that the segment of online shoppers who are focused on


28

utilitarian values such as convenience and time-savings tend to be less price sensitive

(Swaminathan, Lepkowska-White, and Rao 2003). Hence, we propose the following:

Conclusion: We discovered that online Internet shoppers will be more price conscious

than non-shoppers. According to Berry (1969) price is a key attribute for customers when

forming perceptions of retailers

Convenience and Variety seeking:-

Convenience seeking analysis: Similar to other direct shopping methods, using the

Internet to shop is associated with convenience. In-home shoppers enjoy multiple forms

of convenience according to Darian (1987). They include less shopping time, flexibility

with regard to when they shop, less physical effort, and easier response to advertising or

promotions. Similarly, Eastlick and Feinberg's (1999) study of catalog shoppers found

02

46

No. of p

ersons


Response

Influence of Convenience Seeking on Online shopping

Av. Response

01

23

45

67

89

1011

No. of p

ersons


Response

Influence of Variety on Online shopping

Av. Response

Figure 17: Influence of Convenience and Variety seeking on online shopping


29

that convenience was based on consumers finding what they want in a short time period,

with less effort, and shopping at any time of day. Girard, Korgaonkar, and Silverblatt

(2003) found that convenience was one of the highest attractions to shopping online.

Rohm and Swaminathan (2004) found convenience to be a centerpiece when assessing

shopper motivations. Therefore, we propose:

Conclusion: Online shoppers who constitute 53% of the total respondents seek more

convenience than no shoppers. Consumers are more affected by their perceived duration

of download waiting time than by the actual waiting time (Dellaert and Kahn, 1999).

Variety seeking analysis: Variety seeking has been defined as the alternation among

products or brands over a series of choices (Kahn and Isen 1993). Some consumers who

are variety seekers alternate between brands and products even though their most

preferred selection is available (Ratner and Kahn 2002; Ratner, Kahn, and Kahneman

1999). Given the ease of Internet search versus traditional search, it follows that online

shoppers would search more extensively than their offline counterparts. Such search

would lend itself to variety-seeking behavior. In their effort to form a typology of the

Internet shopper, Rohm and Swaminathan (2004) characterized four types of Internet

shoppers, one of which they identified as variety seekers. They found that the variety

seeker is substantially more motivated by variety seeking across retail alternatives and

product types and brands than any other shopping type.

Conclusion: Donthu and Garcia (1999) found that, in general, online shoppers had higher

levels of variety seeking than nonshoppers. This is consistent with other tendencies of the

online shopper, including their recreational nature and their risk aversion. The majority of

online shoppers (88%) as indicated in the diagram above will be more variety seekers

than non-shoppers.

Impulsive

Analysis: The consumer behavior literature refers to impulse buying as extraordinary,

emotion-saturated buying that takes place largely without regard to financial or other

consequences (Wood 2005). Hoffman and Novak (1997) found that heavy Internet users,


30

including shoppers, get into "a flow" on the Web. They become very involved with the

process and it becomes synonymous to a recreational experience (Donthu and Garcia

1999). Recreational shoppers are less traditional, tend to be more innovative, are

information seekers, and are prone to making more impulsive purchases (Bellenger and

Korgaonkar 1980). Similarly, Darian (1987) proposed that in-home shoppers were more

impulsive. Donthu and Garcia (1999) found that online shoppers scored higher on

measures of impulsiveness than did non-shoppers. Zhang, Prybutok, and Koh (2006)

suggest that there exists a positive relationship between consumer impulsiveness and

online purchasing behavior.

Conclusion: Although internet shoppers are expected to make higher levels of

impulsiveness we discovered that 59% were against the practice. Factors to be

considered include availability of disposable income, safety of the system and marketing

strategies of retailers.

01

23

45

67

No. of p

ersons

S.Agree Agree Mod Disagree S.Disagree

Response

Influence of Impulse buying behaviour on Online shopping

Av. Response

Figure 18: Effect of Impulse buying on online shopping


31

4. (b) Non-Online Shoppers

Risk taking tendency and Innovativeness diagrams:-

Risk taking tendency analysis: A significant number (94%) of traditional shoppers are

risk averse as indicated in Fig 19 below. The risk can be categorized into time, social,

physical, psychological and financial risk. Time/ convenience risk relates to the time

spent for the purchase of a product and the time wasted in case of a poor product/service

choice. Social risk reflects the disappointment in the individual by his friends in case of a

poor product/service choice. Physical risk relates to the safety and health of the

individual.

0

1

2

3

4

5

6

7

8

9

10

11

No. of p

ersons

Stronglyagree

Moderate Stronglydisagree

Response

Influence of Risk on Online shopping

A verag e R esponse

01

23

45

67

8

No. of p

ersons


Response

Influence of Innovation on Online shopping

Av. Response

Figure 19: Influence of Risk and Innovation on online shopping

Psychological risk reflects an individual's disappointment in him/herself in case of a poor

product/service choice. Lastly, financial risk pertains to the loss of money in the case of a

poor product/ service choice. Pavlou (2003) alludes to the "implicit uncertainty of the e-

commerce environment. Consumers are thought to have "an inherent predisposition to


32

avoid risk in purchasing situations" (Dowling, 1986). Other potential inhibitors

(Bhatnagar, Misra, & Rao, 2000) include perceived cost of product category,

expectations of functionality, limited or nonexistent return policies, and lack of physical

contact with the item or salesperson. Various transaction costs (Kumar, Lang, & Peng,

2004/2005; Teo & Yu, 2005) are likely inhibitors as well.

Conclusion: Chaudhuri (1998) found that positive and negative emotional factors

contribute as mediators of product class effects on perceived risk. Because luxuries have

large emotional underpinnings, luxuries and necessities function quite differently with

regard to perceived risk. Additionally, intangibility has been shown to be positively

associated with perceived risk (Laroche, Bergeron and Goutaland, 2003)

Innovativeness: Non-shoppers are also innovative as reflected in Fig 19 where 53% of

respondents expressed a keen interest to try new products and services.

Brand and Price consciousness diagrams:-

01

23

45

67

89

No. of p

ersons


Response

Influence of Brand on Online shopping

Av. Response

01

23

45

6

No. of p

ersons


Response

Influence of Price on Online shopping

Av. Response

Figure 20: Influence of Brand and Price on online shopping


33

Brand consciousness analysis: It has been widely suggested that key success factors for

online companies are based on developing brand awareness, building customer loyalty

and reducing operating costs ([75] Porter, 2001; [105] Zeithaml et al. 2002). More

specifically, the findings showed that high quality and satisfaction result in revisiting the

web site. This means that not only the identified e-service quality drivers built loyalty but

that they may convert traditional shoppers to electronic shoppers, thus allowing for

potential operational cost reductions. In fact, in their search of cost reduction and

efficiency most brick-and-mortar companies seek to shift transactions online. Brand

selection might well be more likely to affect customers' buying decisions and subsequent

e-store patronage than merchandise variety (Degeratu et al., 2000).

Conclusion: Online non-shoppers did not resemble more value in brands as reflected in

the Fig 19 above. There is need to consider other issues such as price, variety and

convenience. Donthu and Garcia (1999) did not find brands to be a significant factor.

Likewise, Seo (2005) finds that Internet purchasers tend to have high levels of brand

involvement compared to nonshoppers and high levels of brand consciousness.

Price consciousness analysis: Figure 20 illustrates that there are mixed responses by

non-shoppers with regard value of price on goods and service. Respondents who reflect

negative sentiments on price (47%) were not in agreement that they buy cheap and items

on sale only. The number of respondents who are price conscious is 35% as the shoppers

check prices before purchasing and save on bargains. Consumers are attracted to

technologies because of convenience, increasing ease of use, and, in some instances, cost

savings (Anguelov et al. 2004). Jarvenpaa and Todd (1996) argue that price, quality, and

product type are the three key elements in shaping consumers' perceptions.

Conclusion: The works of Liao and Cheung (2001) and Jarvenpaa and Todd (1996)

postulated that price has a significant impact on online purchasing intention and online

purchasing adoption, respectively. Traditional shoppers also consider seriously the

importance of price on goods and services.

Convenience and Variety seeking:-


34

Convenience seeking analysis: Convenience is measured by effort savings (e.g. ease of

a locating a product in a store) and location convenience (e.g. ease of locating a store and

finding a parking space) (Lindquist, 1974). In online shopping, convenience includes

timely delivery, ease of ordering, and product display (Lohse and Spiller, 1998).

Similarly, Bitner (1990) advocates the effects of time, access to information, money

constraints, and lack of credible alternatives, which may affect service loyalty. Lohse and

Spiller (1998) discerned that several factors can be subsumed under the convenience

attribute of online shopping. Among these attributes, they found that product display has

a significant impact on site visits and sales.

01

23

45

6

No. of p

ersons


Response

Convenience as a determinant of Online shopping

Av. Response

02

46

8

No. of p

ersons


Response

Influence of Variety on Online shopping

Av. Response

Figure 21: Effect of Convenience and Variety on online shopping

Conclusion: Convenience is considered important by non-shoppers as reflected in the

diagram above. Cronin and Taylor (1992) suggest that convenience, good value for

money, and availability might enhance customer satisfaction and subsequently reduce

switching behavior. Athanassopoulos et al. (2001) substantiated this basic suggestion


35

with empirical results, which indicated that customer dissatisfaction leads to switching

behavior.

Variety seeking analysis: A significant (82%) number of traditional shoppers consider

variety as important in their purchasing behavior. However, Lohse and Spiller (1998)

dispute the importance of merchandise variety in e-tailing. In particular, their work

showed that the number of products increases e-store traffic, but it does not affect sales.

Apparently, whether or not an e-tailer has a specific product a customer is looking for is

more important than simply having a large variety of items (Lohse and Spiller, 1998)

Impulsive

01

23

45

No. of p

ersons


Response

Influence of Impulse buying behaviour on Online shopping

Av. Response

Figure 22: Effect of Impulse buying on online shopping

Analysis: There is a strong dissonance with regard impulse buying by traditional

shoppers. The majority of them cited that they were price conscious, favored planned

purchases and relied on making shopping lists before purchases. Donthu and Garcia

(1999) alluded to the fact that Internet shoppers were also more likely to be impulsive


36

than non-shoppers. Moe and Fader (2000) suggest that both planned and unplanned

visit/purchase will affect future purchase decisions.

Conclusion: Purchase intentions refer to the consumer's willingness to buy more through

the internet. In general, a large number of classical researches have substantiated the

relationship between service quality, satisfaction and service switching. For example,

Cronin and Taylor (1992) suggest that convenience, good value for money, and product

availability may enhance customer satisfaction and subsequently decrease switching

behavior.

5. Promotional strategy for online shoppers

Direct Mail and E-Mail marketing campaigns: These should be focused at capturing

the minds of prospective non users of products or promoting repeat purchase by regular

customers. The main target should be Generation Y who are pragmatic, clever, socially

and environmentally aware, and open to new experiences (Schiffman et al., 2008). Since

they are risk takers, new products and services should be tailor made to suit their needs

and wants. It is of an utmost importance that companies take them into consideration

when they define the main traits (product/service, price, place, promotion and so on) of

their offer. Moreover, they are believed to bring an essential contribution to the

technological progress through their constant interest in new media, (Curus, 2008).

Ducoffe found that Internet users have positive attitudes toward advertising and online

advertising in particular as they described it as "informative" and "up to date." High

usage interactive online gamers have positive attitudes toward both online advertising

and the direct communications that lead them to those services (Jones 2007). Donthu and

Garcia (1999) found that online shoppers had more positive attitudes toward direct

marketing and advertising.

Direct mail and e-mail will be more effective in an environment of robust network which

ensure deliverables are accurately provided to the target market. Spiros et al postulated

that marketers should carefully consider their web site's attributes. For example, if


37

marketers want consumers to have a positive experience with their sites, they may want

to adorn their sites with pleasant and enjoyable stimuli to make them attractive. In

addition, they should make their sites easy-to-use and easy-to-navigate. Furthermore,

marketers should place extra emphasis on providing fast, accurate, and uncluttered

information through their web sites. Finally, marketers rather then designing static web

sites, they should design sites that interact with the consumers and adjust to their needs.

Direct mail, e-mailing, web-pages and online advertising promotions should target the

segment. (Darían 1987) concluded that online shoppers tend to have more positive

attitudes toward direct marketing and advertising as cyber-shopping provides

opportunities to make more purchases. Donthu and Garcia (1999) found that online

shoppers will have more positive attitudes toward shopping, advertising and direct

marketing than non-shoppers.

Special promotions, price incentives and exclusive offers: E-managers can induce

consumers to visit their sites more often. This objective can be achieved by different

types of actions. For example, e-consumers can receive price incentives, exclusive offers,

special promotions, and product/service advantages. Spiros et al

Word of Mouth (WOM) activities: Companies should reinforce WOM activities from

satisfied customers. More specifically, companies could enhance its impact and

effectiveness by facilitating or even rewarding such behavior. For instance, they can

make available on their sites possibilities such as "tell a friend" e-mailing, "share your

opinion" sections, "send a discount coupon to a friend" or "let a friend know about a

special offer" actions, and "get a premium service for sending us a new customer". Spiros

et al


38

01

23

45

67

No. of p

ersons


Response

Impact of Advertisements on Online shopping

Av. Response

01

23

45

67

8

No. of p

ersons


Response

Effect of Attitude on Online shopping

Av. Response

Figure 23: Influence of Advertisement and Attitude on online shopping

It is important however important to note that 35% of online shoppers perceive

advertisements as deceptive hence they do not pay attention to them. Andrews and Boyle,

(2008, p. 67) concluded that media reports, particularly television, "have made a

significant, negative impact on the interviewees' affective perceptions of the risk

involved". Brackett and Carr (2001) found that web advertising is "irritating, annoying or

insulting to peoples' intelligence."

There is a correlation between attitude and online shopping as reflected by responses

recorded from the online shoppers. Most respondents (76%) indicated that they enjoyed

shopping which they regarded as fun. Attitudes toward shopping, direct marketing, and

advertising are linked in the online world. Online shoppers, when in "the flow," traverse

the Web seeking recreation and adventure (Hoffman and Novak 1997). To some,

shopping is a recreational activity, and recreational shoppers tend to have more positive

attitudes toward shopping (BeIlenger and Korgaonkar 1980). Donthu and Garcia (1999)

found that online shoppers have more positive attitudes toward shopping, advertising and


39

direct marketing. Swinyard and Smith (2003) found many consumers view online

shopping to be more entertaining than offline shopping.

Privacy of consumers is important in attracting and retaining online shoppers. Online

shoppers indicated that they were more concerned with ethical issues vis-à-vis privacy,

security, respect and responsibility.

Privacy consists of "the rights of individuals and organizations to determine for

themselves when, how, and to what extent information is to be transmitted by others"

(Udo, 2001, p. 165). A significant 47% of the online respondents expressed strong

reservations on phone solicitations and receipt of junk mail which they considered

invasion of privacy and nuisance respectively.

5. Major learning from the assignment

a) There is growing appetite for new products or services by Generation Y.

Since customers need a wide range of unique products to suit their needs

it is an obvious reflection of the vast diversity of needs, values and life

styles of the 3rd Wave Society (Toffler, 1996, p. 159)".

b) Customers have dynamic preference and taste which change with

quantum leaps in technology. In response to these trends, companies

need to globalize their e-business to generate increased business value

because a global virtual presence can be more feasible and less

expensive than a physical presence (Mahmood, Bagchi, and Ford 2004

c) Brand and Price consciousness is important in determining customer

behaviour since it stimulates a desire to purchase a product.

d) Customers are sensitive and delicate with regard the marketing mix

(product, price, place, promotion).

e) Most customers make a planned decision and avoid impulse behaviour

in making purchases.


40

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