Samir selimi thesis- online grocery shopping

The influence of hurdles and
benefits on the diffusion of online
grocery shopping
Retailing Beyond Borders

Foreword
Sipko Schat, Member Executive Board Rabobank
The ‘Anton Dreesmann Leerstoel voor Retailmarketing’ Foundation - supported by a group of
leading retailers in the Netherlands - has chosen Rabobank as its partner to host and co-organise its
annual congress. The initial partnership was for a period of three years (2011-2013), but based on the
success of our cooperation we have agreed to extend it for at least three more years (2014-2016). We
appreciate this opportunity to share views on retail with key players in the sector.
The January 2013 congress, ‘Retailing Beyond Borders - Cooperation´ took place in the Duisenberg
Auditorium in Utrecht. During this congress the ´Rabobank Anton Dreesmann Thesis Award´ was
granted to Samir Selimi for his thesis on ´The influence of hurdles and benefits on the diffusion of
online grocery shopping´. Part of this award is the publication of the thesis as a book. The result is
now in front of you.
Capturing and embedding knowledge is important, both for Rabobank as a knowledge driven
financial organisation and for retailers. We therefore support the initiatives of the Foundation to
combine scholarly knowledge with retail practice. The ´Rabobank Anton Dreesmann Thesis Award´ is
one of these initiatives.
The thesis of Samir Selimi discusses an actual, relevant and interesting issue. The online food retail
industry is underdeveloped compared to other online businesses. Various hurdles and benefits from
the perspective of the online consumer are investigated. The thesis concludes that the hurdles are
more important than the benefits, so retailers should focus on taking away the hurdles in order to
drive online shopping. Furthermore the thesis provides some insights on different online market
segments that are driven by different consumer preferences. Although the thesis is focussed on food
retail, we think that the conclusions are also valuable for non-food retailers.
I trust that the thesis will energise and inspire you to go out and grab the opportunities in the
(online) retail market.
Kind regards,
Sipko Schat
Member Executive Board Rabobank
February 2013

3
Foreword

4
The influence of hurdles and benefits on the diffusion of online grocery shopping

The influence of hurdles and benefits on the
diffusion of online grocery shopping:
How to improve the adoption rate in the Dutch market?

Samir Selimi1

under supervision of

Prof. dr. L.M. Sloot2
Dr. M.C. Non2

1

Samir Selimi is an MSc student at the Faculty of Economics and Business, University of Groningen, The
Netherlands. The research was conducted as a graduation project for the studies Business Administration in
Marketing Management and Marketing Research. Address for correspondence: Samir Selimi, Hereweg 104, 9725 AJ
Groningen, The Netherlands; Tel. +31 622614931; E-mail: samir@selimi.nl; student number: s1912801.
2
Laurens Sloot is Professor of Retail Marketing and Mariëlle Non is Assistant Professor of Marketing at the
Department of Marketing, Faculty of Economics and Business, University of Groningen, The Netherlands

5

6

Summary
Most retailers in the Netherlands have already been offering multiple channels to their customers
for many years . Although the beneficial effects of a multichannel approach are clear from literature,
not all Dutch industries have managed to apply the approach successfully. An example of this can
be found in the Dutch food industry, which, until recently, did not offer an online channel. However,
take-up has increased in the past few years and many food retailers now offer an online channel for
sales purposes. Nevertheless, it is still not widely used by the Dutch consumer. Therefore, this master
thesis investigates what food retailers can do to encourage the usage of online grocery shops. By
understanding the entire adoption process of innovations food retailers are able to invest in the most
important aspects of the online environment. Not only are the characteristics of the online channel
important, but the characteristics of consumers also play a great role. Even though food retailers are
not able to influence consumer characteristics and how they feel or react to certain things, it can
provide insight into potential target groups. To understand the entire adoption process in this case,
the following problem statement was investigated:
“Which characteristics of online grocery shops cause resistance or increase the rate of adoption towards
online grocery shopping and are different strategies necessary in order to meet the needs of different
consumer (groups)?”
In order to enhance further insights into this question several research questions were formulated,
which served as an outline for finding relevant literature. The findings led to the following conclusion
and recommendations for management:
The decision path of Rogers (1995) showed that the adoption depends on several stages. Therefore,
food retailers should understand each step in order to enhance the adoption and decrease the
resistance to online grocery shopping.
The conclusions of the consumer characteristics, which are also part of the decision path of Rogers
(1995), indicate that not all characteristics affect the resistance of the adoption. Table 1.1 shows the
significant effects of the consumer characteristics on the resistance and adoption.
•

Some consumer characteristics have an effect on both the adoption and the resistance,
while others only influence one of the two; for example, shop enjoyment. This indicates that
if people dislike shopping in general they will not per se resist online grocery shopping. But if

7
Summary

Table 1.1
The effect of consumer
characteristics on the
resistance and
adoption of online
grocery shopping

they do like shopping in general the probability is higher that they
will adopt online grocery shopping faster than consumers who
dislike shopping in general.
•

The results in table 1.1 also indicate that the characteristics, which
are related to someone’s beliefs and values, have a higher effect

8

on the resistance. Characteristics, which are related to beneficial aspects of online grocery
shopping influence the adoption more. Finally, more general consumer characteristics have an
effect on resistance as well as on adoption.
The second stage of the decision path of Rogers (1995) relates to the characteristics of the online
channel itself. Unlike consumer characteristics, the food retailer can influence these characteristics
directly.
•

The results of the aggregated conjoint analysis have shown that the hurdles are indicated as
more important than the benefits.

•

The time taken to order online is perceived as the most important attribute, but the quality
of delivered goods, delivery fee and the delivery options are also seen as very important. The
most significant change in usage is when the delivery option for receiving the goods in the
afternoon is also added.

•

The segmented CBC analysis indicates that there are three segments:

(1) the price benefit,

(2) the quality and delivery options and

(3) the time benefit.

The first segment comprises mainly lower educated people who are more often unemployed, the
second segment consists mainly of women who are responsible for the grocery shopping. The
final segment includes the most highly educated, who have the highest income and like grocery
shopping the least.
Finally, the insights above have enabled us to answer our initial problem statement. The three
characteristics which create resistance are: 1) delivery options, 2) delivery fee and 3) quality of ordered
goods. The three characteristics, which increase the adoption are: 1) price benefits, 2) time benefit
and 3) the order procedure. Of course the effect of each (utility) differs from each other. Overall the
hurdles have a higher effect (utility) on resistance than the benefits have on the adoption.
However, the effects do differ between the three segments and therefore, one strategy is not
sufficient to meet the needs of all potential segments.

9
Summary

10

Preface
Our environment is changing rapidly. We are fully dependent on our smart phones, Internet and
social media. As a consumer I can fully relate to these changes. They influence my daily life and offer
many benefits. However, these changes also have a large effect on my work as a marketer. Consumers
react differently across all the channels and are more demanding. This thesis has helped me to better
understand the effect of the online channel on the consumer’s preference and vice versa.
The input, which I have received from my supervisors, Laurens Sloot and Mariëlle Non, was of great
value and provided me with new insights regarding this topic and academic research in general.
Therefore, I would like to thank them for their support during this research. Moreover, I am also very
grateful for their comments and suggestions, which have added significantly to the value of this
thesis. Finally, I would also like to thank my friends and family for motivating me and providing me
with very useful tips.
Without the support of the above, writing this thesis would not have been as interesting as it was.
Samir Selimi

11
Preface

Table of contents
Foreword 3
Summary 7
Preface 11
Table of contents

12

1. Introduction

15

§1.1 Research questions

17

§1.2 Relevance & uniqueness of thesis

18

§1.3 Outline

19

2. Diffusion of innovations

21

§2.1 Online shopping (e-shopping)

21

§2.2 Innovations

21

§2.3 Diffusion of innovations

23

§2.4 Diffusion path

25

§2.5 Resistance vs. Adoption

26

§2.6 Conclusion

28

3. Factors influencing the resistance and adoption

29

§3.1 Factors, underlying antecedents and adoption path

29

§3.2 Innovation characteristics

30

§3.3 Consumer characteristics (moderator)

33

§3.4 Adoption path- willingness to retry and degree of resistance

36

§3.5 Conceptual model for conjoint study

36

§3.6 Conclusion

39

12

4. Methodology

41

§4.1 Study one – qualitative study

41

§4.2 Study two – top six attributes

44

§4.3 Study three – quantitative study

47

5. Results

53

§5.1 Sample and sample characteristics

53

§5.2 Measurement purification

57

§5.3 Regressions

61

§5.4 Conjoint analysis

72

6. Conclusions & managerial implication

87

§6.1 Conclusion

87

§6.2 Managerial implications

91

§6.3 Implications for Truus.nl and Appie.nl

93

7. Limitations and directions for further research

97

References 99
Colofon 111
Disclaimer 112

13
Table of Contents

14

1. Introduction
The enhancement of customer value has become very important for retailers (Neslin et al., 2006).
To achieve this it is important that retailers improve their customer acquisition, retention and
development processes (Neslin et al., 2006). Geyskens, Gielens and Dekimpe (2002) state that
enabling consumers to choose from multiple channels can enhance customer value as well.
The channels typically include the store, web, catalogue, sales force, third party agencies and call
centres (Neslin & Shanker, 2009). Besides the increase in customer value, a multichannel strategy
also offers other benefits, for example, to counteract competitor’s actions (Grewal, Comer, & Mehta,
2001), to decrease the costs per transaction (Dutta, Heide, Bergen, & John, 1995) or to increase their
scope within the market (Friednamdn & Furey, 2003). Besides these benefits, other studies argue
that offering multiple channels could also lead to disadvantages, such as less information, search
costs for consumers, lower switching costs and better insight in the price developments within a
market (Wallace, Giese & Johnson, 2004; Verhoef, Neslin & Vroomen, 2007). This can result in higher
competition as well as to force retailers in investing more in acquiring and retaining customers
(Brynjolfsson & Smith, 2000; Tang & Xing, 2001).
Even though negative aspects are present when a multichannel strategy is used, it seems that its
organisational benefits outweigh the disadvantages. Moreover, offering multiple channels also has
beneficial effects on consumer behaviour. For example, it leads to the improvement of the brand
image, the improvement of customer experience and the enhancement of customer loyalty across
all channels (Danaher, Wilson & Davies, 2004; Bailer, 2006; Harvin, 2000; Shanker, Smith & Rangaswamy,
2003; Wallace, Giese & Johnson, 2004). This is mainly caused by the increase in customer convenience
since consumers are able to choose their preferred channel for each purchase and each channel
satisfies different needs. For example, stores enable face-to-face contact, instant gratification and
physical examination, while the web increases the accessibility for consumers and access to product
and price information. Thus, when combined all the different channels enable retailers to meet more
complicated consumer needs (Wallace, Giese & Johnson 2004; Bucklin, Ramaswamy & Majumar, 1996).
Even though the beneficial effects of a multichannel approach are clear from literature, not all Dutch
industries have been able to profit from it. While most Dutch retailers within different industries (e.g.
fashion, travel, electronics and furniture industry) already apply the multichannel strategy, the Dutch
food industry has not paid the same amount of attention towards the multichannel strategy. This is
mainly due to their lack of attention towards the online channel for sales purposes (Twinkle, 2011).
The online channel was mainly used to provide customers with information (e.g., C1000.nl, 2011;
Jumbo.nl, 2011, Plus.nl, 2011) and not as an online channel for sales purposes. Therefore, it does not

15
Introduction

fit the definition of an online grocery shop, which is; “an online grocery shop offers the ability for
consumers to order groceries from home electronically (i.e. Internet) and have them delivered at
their own preferred location” (Burke, 1997; Gillett, 1970; Peterson, Balasubramanian & Bronnenberg,
1997). While most Dutch food retailers did not use a multiple channel approach, only one Dutch
food retailer offered an online channel, which best fits this definition. From 2010 until the beginning
of 2011 Albert Heijn (AH) was the only Dutch food retailer to offer the ability to purchase groceries
online (Ah.nl, 2011; Twinkle, 2011). However, other supermarket chains like Coop, Dekamarkt, Plus and
Boni have adapted their online channel and since 2011 have enabled their customers to purchase
groceries online as well (Twinkel, 2011). Since most Dutch food retailers have only started using
the online channel for sales purposes recently, it can still be characterised as an innovation (Rogers,
1995; Gatignon & Robertson, 1989). A comparison between general and food related online sales
developments confirm this conclusion.
In 2010 the total online spending in the Netherlands, for products, increased by 10% to €4.2 billion
(Thuiswinkel.org, 2011; ING, 2011). This is approximately a share of 5% of the total Dutch retail
market in 2010. However, a comparison with food related figures show that less than 1% of the total
spending on groceries is done online (ING, 2011). Albert Heijn, for example, which had a monopoly
until the beginning of 2011, had an online turnover of ±€150 million in 2010. This was approximately
1.49% of their total turnover (ING, 2011; Ahold.nl, 2011). While in the Netherlands online spending is
quite low, in other countries, for example the UK, the online grocery market already accounts for 3.2%
(€5.55 billion) of their total food sector in 2010 (IGD, 2011) and is expected to grow to €10 billion
by 2015. These figures and the previously mentioned figures regarding the general online market in
the Netherlands, indicate that the online channel can still offer many opportunities for Dutch food
retailers and can still be expected to grow.
Alongside the literature and market related figures, several studies (e.g. Verhoef & Langerak, 2001)
also indicate that consumers have a generally positive attitude towards online grocery shopping.
They indicate that consumers expect shopping via an electronic channel to be more convenient and
time saving. Other studies also state that time pressure (Srinivasan & Ratchford, 1991), the increase
of Internet usage and situational factors (Hand, Riley, Harris, Singh & Rettie, 2009) positively influence
the adoption of online grocery shopping. Interestingly, market research (e.g. GfK, 2010) shows that
only 5% of Dutch Internet users indicated to have purchased groceries online in 2010 and in addition
57% show high resistance and have even indicated to be unwilling to purchase groceries online at
all; which is quite odd as general consumer figures characterise Dutch consumers as the most active
users of the online channel (Twinkle, 2010). In addition 72% of them have, at least once, purchased
goods online, which makes shopping the 4th most important activity online (GfK, 2010).
16

This leads to the conclusion that there is a large discrepancy between the intended consumer
behaviour and the actual behaviour regarding online grocery shopping. This conclusion is drawn
from the fact that literature has shown many positive consumer intentions towards online grocery
shopping. However, the actual sales figures and market research indicate the opposite. It seems that
studies which have found positive intentions towards the adoption of the online channel for grocery
shopping have been performed in situations in which the respondents had little or no experience
with online (grocery) shopping (e.g. Verhoef & Langerak, 2001; Wilson & Reynolds, 2006). Also, during
these studies the intention to shop online for groceries was measured based on more general
metrics and combined with the limited experience of the participants this might have led towards
a biased conclusion. Another reason for the discrepancy between the positive consumer intentions
and the actual online grocery sales might be the fact that many factors, which have been found to be
beneficial, for the adoption of online grocery shopping (e.g. time restraints and increase of Internet
usage) are not controllable by food retailers. Therefore, food retailers are not able to control the
situation in order to increase the rate of adoption of the online channel for grocery shopping.
Hence, the aim of this study will be to find out which characteristics of an online grocery shop
have negative and which have positive influences on the intention for consumers to engage in
online grocery shopping. It has been decided to study the effects of the online grocery shop itself,
in order to provide Dutch food retailers with insights, which are more controllable. Contrary to
non-controllable aspects (e.g. time restraints) our findings enable food retailers to assess their own
situation and if needed adapt their strategy and online environment to better meet customer needs.
However, this does not mean that the non-controllable aspects will be omitted, as they are needed
to provide insight as to whether differences exist between consumers and thus, whether there are
different adopter groups. If this is the case, food retailers will have to use different strategies to attract
different adopter groups.

§1.1 Research questions
In order to gain more insight into aspects that influence the usage of the online grocery shop,
negatively or positively, the following main research question will be covered in this paper:
“Which characteristics of online grocery shops cause resistance or increase the rate of adoption towards
online grocery shopping and are different strategies necessary in order to meet the needs of different
consumer groups?”

17
Introduction

An answer to this question will give food retailers better insight as to how to adapt their online
grocery shops in order to diminish hurdles and increase the rate of adoption. Therefore, to answer the
problem statement five research questions have been formulated:
1.

What does the adoption process of new innovations look like?

2.

According to literature, which consumer characteristics cause resistance and which increase
the rate of adoption of online grocery shopping?

3.

According to literature, which characteristics of online grocery shops cause resistance or
increase the rate of adoption of online grocery shopping?

4.

What are the three most important characteristics to create resistance and what are the three
most important characteristics to increase the rate of adoption?

5.

What is the degree to which the six most important characteristics affect the choice to resist
or adopt online grocery shopping?

6.

What is the best strategy per adopter group to diminish the resistance and increase the
adoption of online grocery shopping?

These research questions serve as an outline in to finding relevant literature regarding hurdles and
benefits towards online grocery shopping. Hurdles and benefits of regular online shopping will also
be taken into account, because it is expected that more literature and knowledge is available on
this topic. This will lead to a better understanding of aspects that influence online grocery shopping
either positively or negatively. Next, the six most important hurdles will be determined, which will
be tested by a Conjoint Analysis to enhance the insight in the degree of importance per hurdle and
benefit. Finally, options to diminish hurdles and increase the awareness of benefits regarding online
grocery shopping will be determined by the use of findings from literature and practice. This will lead
to the formation of different strategies in order to meet the needs of different consumers (consumer
groups). All steps will lead to answers to the research questions, which will contribute to the answer
of the problem statement.

§1.2 Relevance & uniqueness of thesis
Considering the information and arguments, which have been presented above, this study’s main
contribution to existing literature is to provide insight into the degree of importance of the three
most important hurdles and the three most important benefits of online grocery shops. These
insights enable food retailers to fully benefit from the opportunities of an online grocery shop and to
build the most ‘ideal’ online grocery shop. Moreover, by taking the non-controllable aspects (e.g. time
restraints) into consideration, information can be provided on whether or not these aspects impact
the relative importance of the hurdles and benefits .
18

In the past the main interest in marketing literature regarding online grocery shopping, has been on
the socio-demographic profile of home shoppers (Cunningham & Cunningham, 1973, Darian, 1987;
Gillet, 1976; Peters & Ford, 1972; Reynolds, 1974). Only a few studies have investigated the influences
of both personal characteristics and innovation characteristics on the adoption of innovations (e.g.,
Hirschman, 1980; Labay & Kinnear, 1981; Verhoef & Langerak, 2001; Wilson & Reynolds, 2006). However,
these studies were only able to measure the intention to purchase groceries online when online
grocery shopping was not available for consumers (e.g. Verhoef & Langerak, 2001: Wilson & Reynolds,
2006). This might be the reason why there is a large discrepancy between positive consumer
intention and the actual behaviour towards online grocery shopping. Since online shopping and
online grocery shopping is more common and consumers now have better knowledge of it, it
is expected that our study will be able to better capture consumers’ intentions regarding online
shopping for groceries. Also, our main focus will be on the characteristics of the online grocery shop
itself in order to fill the gap in literature, as the consumer characteristics and other non-controllable
aspects have been studied extensively in the past.
For food retailers, our findings will enable them to better control the situation in order to fully
benefit from the positive effects of a multichannel strategy (e.g. Danaher, Wallace, Giese & Johnson,
2004; Bailer, 2006; Harvin, 2000; Shanker, Smith & Rangaswamy, 2003). In order to do so, food retailers
need to better understand which characteristics of the online grocery shop are perceived as most
important and how they influence the adoption process. Moreover, by studying the differences
between adopter groups, food retailers are provided with insights which enable them to choose the
correct strategy for each adopter group. This is needed as different groups might have different needs
regarding the online environment itself.

§1.3 Outline
This paper will offer more information with regard to innovations and the diffusion of innovations.
Also, a more detailed view of resistance and adoption is provided in chapter two. In chapter three
a theoretical framework will be presented. This initial framework is used to form the methodology
in chapter four which will be followed by the results of the three statistical analyses in chapter five.
Finally, the results from chapter five will be used to formulate the conclusion and the managerial
implications in chapter six. In chapter seven the limitations and directions for further research are
provided.

19
Introduction

20

2. Diffusion of innovations
This section will deal with literature regarding the diffusion of innovations. Since online grocery
shopping is relatively new in the Netherlands it can be considered as an innovation (Rogers,
1995; Gatignon & Robertson, 1989). Therefore, by providing more insight into this topic a better
understanding can be formed of how online grocery shops can be diffused throughout the market.
In paragraph 2.1 more information is provided regarding online grocery shops, followed by insights
originating from previous literature regarding innovations and its diffusion in paragraphs 2.2, 2.3 and
2.4. In paragraph 2.5 the difference between resistance and adoption are provided and finally the
conclusion in 2.6. The different insights, which are provided in this chapter will aid in the formation of
a conceptual model.

§2.1 Online shopping (e-shopping)
Online shopping is defined as: “the ability for consumers to order from home electronically (i.e.,
Internet) and have it delivered at their own preferred location” (Burke, 1997; Gillett, 1970; Peterson,
Balasubramanian & Bronnenberg, 1997). Even though this definition also concerns other channels
such as the fax and telephone, in this study the emphasis will only be on the Internet.
Leeflang and van Raaij (1995) state in their study that a reason for food retailers to introduce an
online grocery shop could be the ability of online shops to better anticipate changes in consumers’
shopping behaviour and differences in social demographic profiles, for example, the increased need
for convenience (Burke, 1997). On the other hand, online grocery shopping is also beneficial for
consumers, as it enables them to save time by shopping online from a preferred location (Verhoef &
Langrak, 2001). Despite the benefits on both sides, online grocery shopping is relatively new in the
Netherlands and is not used by many consumers.

§2.2 Innovations
The introduction of new products and services is necessary for retailers in order to ensure future sales
and growth (Hoyer and MacInnis, 2008). However, many commercial organisations are still faced with
high failure rates, as many innovations are not adopted by consumers (Moore, 2002; Tauber, 1973;
Rogers, 1983). Therefore, in order for innovations to be successful a better understanding is needed of
what an innovation is and how it diffuses throughout the market (Hoyer and MacInnis, 2008). First of
all a definition of innovations provides us with a better view of what an innovation is; ‘an innovation is

21
Diffusion of innovations

an idea, practice, or object that is perceived as new by an individual’ (Rogers, 1995; Gatignon & Robertson,
1989). It is thus not important whether the idea, practice or object is new, as long as its (potential)
users perceive it as new. Moreover, changes regarding the way an innovation is used or produced
can also be used to characterise innovations (Robertson, 1971; Gatignon & Robertson, 1989). However,
the degree of change can vary between innovations and with the use of the ‘Innovation Continuum’
of Robertson (1971) innovations can be classified according to the degree in which a change in
consumer behaviour is required. Innovations that do not require a dramatic change (e.g. a wireless
mouse instead of a non-wireless one) are characterised as continuous innovations (Robertson, 1971).
On the other hand, a discontinuous innovation requires a drastic change in the consumption pattern
of consumers (Robertson, 1971). Thus, while continuous innovations are often comparable to existing
alternatives, discontinuous innovations are totally new products or services (Moreau, Lehman &
Markman, 2001). The features of discontinuous innovations are often new to the market and cause a
discontinuity in the existing market or technology-base and that causes the need for a radical change
in consumer behaviour (Garcia & Calantone, 2002; Moreau, Lehman & Markman, 2001).
For online grocery shopping a significant change in consumer behaviour and habits is required, as in
the online channel consumers would have to purchase their groceries in a new way when compared
to the current way of grocery shopping. Moreover, they are not able to perform some tasks, which are
possible in the offline channel; e.g. feeling and smelling the products (Darian 1987; Tauber, 1972). This
is in line with findings from Jager (2003) who states that when an action is performed very often a
habit occurs, which is also the case for the traditional way of grocery shopping in the offline channel.
Thus, Dutch consumers who switch to online grocery shopping require a change in their current
habits regarding grocery shopping and even need to use new technologies to perform the same task
(e.g. use of internet and online payment). This leads to the conclusion that online grocery shopping
can be categorised as a discontinuous innovation (Robertson, 1971; Hansen, 2005; Moreau, Markman
& Lehman, 2001; Molesworth & Suortti, 2001).
Besides the degree of required behavioural change, innovations can also be divided into product
and service innovations. According to Alba et al., (1997) product and service innovations differ (e.g.
tangibility (Lovelock & Wirtz, 2011; Lovelock & Gummesson, 2004)) and therefore, should not be
treated equally. However, to the contrary Dolfsma (2004) argues that the differences between service
innovations and product innovations are only present from a managerial perspective. Consumers
may not even perceive any differences at all, because for them the importance lies only in the added
benefit of products or innovations (Drucker, 1974). The findings of Dolfsma (2004) and Drucker
(1974) are in line with the statement of Fagerberg, Mowery, and Nelson (2005), who state that service
innovations do not follow significantly different diffusion paths compared to product innovations.

22

Therefore, even though online grocery shopping can be considered a service innovation, based on
the previous arguments no distinction is made between literature focused on service innovations
and literature focussed on product innovations.

§2.3 Diffusion of innovations
Besides the importance of understanding what an innovation is, it is also important to know why
innovations do (not) diffuse, because it is necessary for an innovation to diffuse properly in order for
it to be successful (Hoyer & MacInnis, 2008). Several studies have investigated the successful diffusion
of innovations (e.g. Rogers, 1995; Mahajan, Muller & Bass, 1995) and the challenges that are present
when an innovation diffuses (Moore, 1991; Moreau et al. 2001; Rogers, 1995). While some studies have
been more focused on high-tech innovations and their technological discontinuities (Moore, 1991;
Linton, 2002), others have focused on low-tech innovations (Atkin, Garcia & Lockshin, 2006). High-tech
innovations are often related to technological discontinuities while low-tech innovations are more
often related to discontinuities regarding consumers and their behaviour (Atkin, et al. 2006). Aspects
from both sides influence online grocery shopping as the technological discontinuities arise due
to the necessity to use new technologies; e.g. new distribution systems, Internet and a web shop.
Behavioural discontinuities are present due to consumers’ strong habits in the offline grocery channel.
Therefore, it is necessary for Dutch food retailers to understand how innovations diffuse throughout
the market in order to improve the diffusion of online grocery shopping as well (Hoyer & MacInnis,
2008).
The traditional diffusion theory of Rogers (1995) is widely used to better understand how innovations
diffuse in a market. According to Rogers’ (1995) theory there are four main concepts that influence
the diffusion of innovations, these are: (1) the innovation, (2) the communication channels, (3) time
and (4) the social system. The innovation was already mentioned in the previous paragraph and
therefore, only the other three concepts will be discussed in this section.
The second concept is the ‘communication channel concept’ in which Rogers states that not all
channels are equally effective in the diffusion of innovations. Mass media is, for example, more
effective for simple (continuous) innovation, while more difficult (discontinuous) innovations require
a more personal channel (Rogers, 1995; Robertson, 1971). Therefore, more information is needed to
aid in the diffusion of discontinuous innovations and to counteract resistance, which is also the case
for online grocery shopping.

23

The ‘time’ concept, the third concept of Rogers (1995) is a good method
to understand the diffusion of an innovation by looking at its pattern of
adoption over time (Hoyer & MacInnis, 2008; Bass, 1969). Several diffusion
patterns have been identified in literature (Hoyer & MacInnis, 2008; Bass,
1969). However, one of the most common patterns is the S-shaped diffusion
curve (see figure 2.1) (Bas, 1969), which is often found in cases where
consumers perceive risk (e.g. social, psychological, economic, performance
and physical risk) in using the innovation (Hoyer & McInnis, 2008).
Finally, the diffusion of innovations can also differ between consumers or
consumer groups. The adopter categorisation framework of Rogers (1995),
which is also the final concept; i.e. the social system, provides insight into the
different stages of innovativeness per adopter group (see figure 2.1). The five
different stages are adoption categories and are defined as: ’a classification of
individuals within a social system based on their innovativeness’ (Rogers, 1995).
In this concept the diffusion rate is determined by the match between the
innovation and the norms, values and the degree of interconnection within
the social system. The better the fit the higher the diffusion rate (Hoyer &
McInnis, 2008). An important note regarding the adopter categorisation
Figure 2.1: Stages of
innovativeness
(Rogers, 1995) and
S-shaped diffusion
curve (Bass, 1969)

framework of Rogers (1995) is the critique that some studies have shown
towards the number of adoption categories. They state that the amount of
categories differs per innovation (e.g. Shih & Venkatesh, 2004; Peterson, 1973;
Darden & Reynolds, 1974; Baumgarten, 1975). Also, the division of consumers

24

across the categories is not always bell-shaped. This means that the largest group is not always in the
middle or at the end, in that case only the ‘more’ innovative consumers should be targeted.
Thus, in the case of online grocery shopping, food retailers should understand the norms, values
and the interconnectivity of the different adopter groups within their market. An understanding
of the division of adopter groups is necessary as well as the amount of adopter groups. Moreover,
the channel through which information is provided should be chosen wisely in order to enhance
the diffusion rate. Finally, a comparison of the diffusion over time increases the awareness of an
innovation’s diffusion performance and whether extra action is needed to enhance the adoption rate
or whether it just needs more time.

§2.4 Diffusion path
Insight which is provided by Rogers’ (1995) concepts aid us in better understanding innovations
and what has to be done in order to have a successful introduction and diffusion of an innovation.
However, besides insight into the innovation itself, some insight into consumers and how they adopt
an innovation (adoption path) is needed. According to Rogers (1995), the diffusion of an innovation
follows a specific path and is divided into five stages, i.e. (1) knowledge, (2) persuasion, (3) decision,
(4) implementation and (5) confirmation (see figure 2.1). The knowledge stage refers to the moment
that a consumer becomes aware of the innovation, when no information is gathered yet. During the
persuasion stage an individual is more interested in the innovation and gathers information, which
is used in the third step to form an attitude in order to make a decision as to whether the innovation
will be rejected or adopted. A positive attitude in step three can result in the trial of the innovation in
step four. Eventually, in the fifth and final stage it is decided whether the innovation will become part
of an individual’s routine and thus if the innovation will be used again.
Hoyer & McInnis (2008), on the other hand, state that the diffusion path (route) is influenced by the
consumer’s motivation, ability and opportunity (MAO) and therefore might differ per individual. If the
perceived risk (e.g. physical, social, economic financial or safety) is high then individuals are most likely
to choose the so-called ‘high-effort hierarchy route’ (Hoyer & McInnis, 2008). This is often the case for
discontinuous innovations, as these kinds of innovations are relatively new and different from existing
alternatives (Moreau, Lehman & Markman, 2001). Therefore, individuals require additional information
regarding the innovation (Moreau, Lehman & Markman, 2001). Individuals who follow the ‘high-effort
hierarchy route’ will gather information first, after they have become aware of an innovation, and
then form an attitude towards the innovation. In case of a positive attitude it can result in trial and
finally, this can lead to the adoption of an innovation. However, individuals who do not perceive any

25

risks and follow the ‘low-effort hierarchy route’ will try the innovation first,
then form an attitude to consider the adoption of the innovation. Thus,
by providing consumers with enough information, their perceived risk
could be lowered, which can result in trial. This is important as trial enables
consumers to better evaluate their self-efficacy or ability and this can lead to
a higher chance of adopting the innovation (Davis, Bagozzi & Warshaw, 1989;
Hansen, 2005).
Thus, the diffusion of an innovation depends on many factors and the
consumer’s perception regarding these factors. Most important in the
diffusion process is the attitude of the consumer and whether or not it is
Figure 2.2: Five stages
of the decision path
(Rogers, 1995)

positive towards the innovation, which is formed in the third stage (see
figure 2.2). Therefore, extra insight into resistance and adoption is provided
in the next sub-chapter.

§2.5 Resistance vs. Adoption
As figure 2.2 shows, consumers decide at the third step, after evaluating
the gathered information, whether they resist or try an innovation. The
decision at this step is important as it can lead to the adoption of the
innovation. However, an individual is not automatically willing to adopt an
innovation if there is no resistance towards it and therefore also benefits
are needed in order to persuade the consumer to try and adopt the
innovation (e.g. Gatignon & Robertson, 1989; Herbig & Day, 1992; Ram &
Sheth, 1989). Still many studies often do not differentiate adoption from
resistance and consider them as opposites. This statements would leade
to the fales conlsuion that consumers who have no resistance towards
an innovation will automatically adopt it (Nahib, Bleom & Poiesz, 1997).
According to Rogers (1995) the main reason for this assumption has been

26

the ‘pro-innovation bias’ of researchers, who have often assumed that an innovation should diffuse
and therefore, resistant individuals have not been taken into account. Instead, individuals who did
not adopt the innovation or did this in the latest stage of Rogers’ adoption categorisation theory
were seen as ‘laggards’, instead of resistant consumers. However, different studies have concluded
that resistance is not the mirror image of adoption, but a different form of behaviour (e.g. Gatignon
& Robertson, 1989; Herbig & Day, 1992; Ram & Sheth, 1989). Moreover, adoption only occurs if there is
no resistance (e.g. Ram, 1987; Ram & Sheth, 1989; Hoyer & MacInnis, 2008). This leads to the conclusion
that resistance and adoption are influenced in a different manner.
The understanding of resistance is crucial for successful innovation diffusion; therefore insight into
the reasoning of consumers in resisting innovations is necessary (O’Conner, Parsons, Liden & Herold,
1990; Midgley & Dowling, 1993; Szmigin & Foxhall, 1998). According to Moore (2002) the lack of
consumer insights, before the introduction of innovations, leads to resistance from consumers, as
innovations do not meet their needs (Garcia & Atkin, 2002; Molesworth & Sourtti, 2002). Hoyer and
McInnis (2008) even state that innovations need to appeal to every adopter group of Rogers’ (1995)
adoption categorisation framework, in order to diffuse throughout the market. The mismatch that
occurs due to little consumer insight, prior to the launch of an innovation, is the main reason for the
high failure rates of innovations (Moore, 2002). This is because consumers compare the innovation
with existing alternatives and consciously choose to be resistant (Szmigin & Foxall, 1998), which is in
line with the following definition of resistance: ‘the resistance offered by consumers to an innovation,
either because it poses potential changes from a satisfactory status quo or because it conflicts with their
belief structure (i.e. barrier/hurdles)’ (Ram & Sheth, 1989; Hirschheim & Newman, 1988; Ram, 1987). It also
suggests that resistance is based on the consumer’s beliefs, values and their status quo, rather than
the benefits of the innovation in comparison to existing alternatives. The latter, on the other hand, is
needed to attract consumers to adopt the innovation (Mahajan et al, 1995).
Therefore, it can be concluded that adoption of an innovation can only occur if consumers do not
feel resistant towards it. However, as previously stated, adoption only occurs if an innovation offers
more benefits when compared to existing alternatives (Ram, 1987; Ram & Sheth, 1989; Hoyer &
MacInnis, 2008) and is not automatically the result of non-resistance (e.g. Gatignon & Robertson,
1989). Consumers who perceive no resistance may still refuse or postpone the use of an innovation,
for example, due to the lack of added benefits or due to financial reasons (Greenleaf & Lehmann,
1995). This leads to the conclusion that resistance can lead to more than simply not trying the
innovation, which is in line with findings of Ram and Sheth (1989) and Szmigin and Foxall (1998) who
suggest that innovation resistance is not a single form, but it consists of three types of behaviour; i.e.
(1) rejection, (2) postponement and (3) opposition.

27

In the rejection type consumers have really evaluated the innovation, which has resulted in rejecting
(Rogers, 2003). Thus, the rejection does not simply occur because consumers ignore new innovations
or because they are not aware of them, but they have consciously made the decision. Also, according
to Lee and Clark (1996-1997) consumers who reject an innovation are often suspicious of new
innovations and are not willing to change their status quo (Hirschheim & Newman, 1988). In the
second option consumers might have overcome the resistance, but they still can decide not to
adopt the innovation at that time and simply postpone the use of it (Greenleaf & Lehmann, 1995).
Finally, consumers who choose to oppose the innovation have not only decided not to use it, but
are even trying to sabotage the innovation (e.g. negative WOM) (Davidson & Walley, 1985). All three
behaviours occur for different reasons (Kleijnen, Lee & Wetzels, 2009). The weakest form of resistance is
postponement (Szmigin & Foxall, 1998), followed by the rejection. Both postponement and rejection
mainly occur because of perceived risk, while the strongest form of resistance, opposition, is mainly
driven by an individual’s personal and societal environment (Kleijnen et al., 2009).
In conclusion it can be stated that the approach to decrease resistance is different from the approach
to increase the adoption rate (Gatignon & Robertson, 1989; Herbig & Day, 1992; Ram & Sheth, 1989).
Moreover, the negative aspects (hurdles) have a far stronger impact on resistance than the benefits
have on adoption (Mizerski, 1982). Therefore, the adoption rate cannot be increased by simply adding
other benefits and thus, the resistance should be decreased first in order to increase the adoption
rate (Fortin & Renton, 2003).

§2.6 Conclusion
The information, which is provided in this chapter, has shown that not all innovations are the same
and that different approaches are needed in order to increase the adoption rate. Moreover, aspects,
which are not directly related to the innovation, also require the attention of retailers when the
online channel is launched or adapted; aspects such as the channel through which the innovation is
introduced or the information which is necessary to decrease potential resistance. Furthermore, the
final part has shown that resistance is not the opposite of adoption and therefore, should be treated
differently. Therefore in chapter three insights will be provided into the aspects that create resistance
towards online grocery shops and aspects, which can ensure that consumers adopt the online
channel for grocery shopping. Using these insights a model will be built, which will aid in the search
for theory based hurdles and benefits towards online grocery shopping.

28

3. Factors influencing the resistance and adoption
The theory regarding innovations and their diffusion discussed in the previous chapter is used
here to form a better understanding of the decision stage in the decision process model of Rogers
(1995). These insights are used to enhance our understanding of the influential factors in this stage.
Therefore, in sub-chapter 3.1 a model is formed, which indicates the different factors, the underlying
antecedents and the adoption path of innovations. This model is based on several relevant theories
on the diffusion of innovations. Next, further explanation of the different steps and analyses in
the model, which are needed to better understand the entire adoption process of online grocery
shopping, are discussed. Finally, in sub-chapter 3.3, the theory based hurdles and benefits for the
conjoint analysis are provided, resulting in a preliminary conceptual framework, which will be tested
with the use of a qualitative study in chapter four.

§3.1 Factors, underlying antecedents and adoption path
We already know that adoption and resistance are influenced in a different manner and that
adoption only occurs if the resistance is overcome, a framework will be built to visualise which
antecedents influence the resistance and the adoption of an innovation (see figure 3.1). The
framework is based on various relevant theories on the diffusion of innovations e.g. the Diffusion
model of Rogers (1995), the (TRA) Theory of Reasoned Action (Ajzen & Fishbein, 1980; Sheppard,
Hartwick and Warshaw, 1988), the (TAM) Technology Acceptance Model (Davis, 1989), the (TPB)
Theory of Planned Behaviour (Ajzen, 1991) and the Innovation resistance theory of Ram (1987).
The theory of Ram (1987) is one of the few who explicitly mentions the difference between
resistance and adoption, even though his model corresponds with most of the before mentioned
models. Based on the previously mentioned theories it has been decided to use the (1) innovation
characteristics and (2) the consumer characteristics as the two main factors in our model (see figure
3.1). The underlying antecedents have also been formed based on several theories. The choice for
each antecedent is further explained in the next parts. Finally, the degree of resistance, the willingness
to (re)try online grocery shopping and the process for both aspects is also mentioned. Insight into the
process of both aspects is needed. Insight into the influence of the consumer characteristics on the
degree of resistance and the willingness to (re)try online grocery shopping can aid in the detection
and selection of potential segments.

29
Factors influencing the resistance and adoption

Figure 3.1:
Innovation Adoption
framework (adapted
from e.g. Ram, 1987;
Rogers, 1995; Kleijnen
et al., 2004)

§3.2 Innovation characteristics
The first and main dimension that influences the resistance and adoption
is the consumer’s perception of innovation characteristics (Mahajan et
al, 1995), which is also the only dimension that is controllable by food
retailers. The traditional diffusion theory of Rogers (1995) mentions five
innovation characteristics, which determine the rate of the adoption; i.e.
(1) relative advantage, (2) compatibility, (3) complexity, (4) divisibility and (5)
communicability. The relevance of these characteristics and their influence
on the diffusion process have been confirmed by different studies (e.g.
Verhoef & Langerak, 2001; Meuter, Bitner, Ostrom & Brown, 2005; Kleijnen
et al., 2004). Moreover, other models like the TAM (Davis, 1989) and TRA

30

(Ajzen & Fishbein, 1980; Sheppard, Hartwick and Warshaw, 1988) have used
antecedents that are the same or correspond with the ones mentioned
by Rogers (1995). Therefore, these characteristics have been used in our
framework. In table 3.1 a short explanation is given of each characteristic
and what each characteristic stands for.

Table 3.1:
Innovation
characteristics

Characteristics

Definition

Source

Relative advantage

‘The degree to which an innovation is being perceived
as better than the idea it supersedes (added value)’

(Rogers, 1995)

Compatibility

‘The degree to which an innovation is perceived as
consistent with the existing values, past experiences and
needs of potential adopters’

(Gatignon & Robertson,
1991)

Complexity

‘The degree to which an innovation is perceived as
relatively difficult to understand and use’

(Hoyer & MacInnis, 2008)

Divisibility/
trialability

‘The degree to which an innovation can be tried on a
limited basis’

(Rogers, 1995)

Communicability/
observability

‘The degree to which an innovation is visible and can be
shared with other within a social group’

(Hoyer & MacInnis, 2008)

Perceived risk*

the consumer’s perceptions of the uncertainty and
adverse consequences of buying a product or service

(Dowling and Staelin,
1994)(Ram & Sheth, 1989)

*(Not mentioned by Rogers (1995), but added based on findings of Ram & Sheth (1989))

Where Rogers’s (1995) framework measures the antecedents that influence
the adoption of an innovation, the framework of Ram and Sheth (1989)
measure the opposite, namely the resistance. However, most of the barriers
that are mentioned by Ram and Sheth (1989) show large resemblances to
the framework of Rogers (1995). The differences and resemblances will be
mentioned in the next part.
According to the study of Ram and Sheth (1989) resistance occurs from
two main barriers; i.e. (1) the psychological barrier and (2) the functional
barrier (see figure 3.2). The psychological barrier requires psychological
change, while the functional barrier requires behavioural change (Gatignon
& Robertson, 1989; Herbig & Day, 1992; Martinko, Henry, & Zmud, 1996; Ram &
Sheth, 1989).
The sub-barriers that form the (1) psychological barrier are related to
consumers and their psychological mindset. For example, the traditional
barrier occurs if the usage of an innovation requires a cultural change
for the consumer; e.g. their current norms and values do not allow them

31

Figure 3.2:
Innovation resistance
framework (Ram &
Sheth, 1989).

to use the innovation. The image barrier occurs if the innovation does
not fit with the current ‘image’ that an individual might have within their
social environment. Disapproval towards the innovation from the social
environment could lead to uncertainty and resistance. Both the sub-barriers
of the main psychological barriers show resemblance with the compatibility
barrier of Rogers (1995). Even though it is a barrier related to psychological
aspects, these aspects might be related to characteristics of the online
grocery shop itself and therefore, this barrier is also taken into account.
The second main barrier; i.e. (2) the functional barrier is also influenced
by sub-barriers. The first one is the usage sub-barrier, which increases
if the innovation is not compatible with existing habits, patterns or the
way consumers perform the same task. This sub-barrier is in line with
the compatibility characteristic of Rogers (1995). Next, the value barrier
occurs when the use of new innovations requires higher monetary and
non-monetary costs (Aylott and Mitchell, 1998; Cassill et al., 1997), which
shows resemblance with the relative advantage characteristic of Rogers
(1995). Finally, the risk barrier occurs if consumers feel uncertainty towards
trying the innovation (Dowling and Staelin, 1994). A comparison with
Rogers’s framework shows that this characteristic is not yet represented
and therefore, it will be added to our model. According to the Innovation
Resistance theory of Ram and Sheth (1989) the perceived risk is an
important influencer of resistance.

32

A more detailed look at the risk barrier shows that different sub-risks influence the main risk barrier:
the (a) economic risk, (b) functional risk, (c) social risk and (d) physical risk. The consumer’s trust in the
innovation and the producer is the main influencer of the sub-risks (Verhoef & Langerak, 2001).
Consumers question the ability of the innovation and its producer to deliver an alternative effectively
and reliably (Doney & Cannon, 1995). Additionally, Kleijnen et al. (2009) state that risk is one of the
most important drivers that form resistance towards an innovation. A remedy for risk perception
might be the information that is provided regarding the aspects that are perceived as risky, by
doing so an individual’s perception can be counteracted (Dowling & Staelin, 1994). This is also in
line with the ‘high effort hierarchy’ statement of Hoyer and MacInnis (2008), in which they show that
information affects the chosen route towards adoption and the consumers’ perception.

§3.3 Consumer characteristics (moderator)
While the innovation characteristics are fully controllable by the food retailers, the consumer
characteristics are not at all controllable. This means that food retailers can only use this information
to better understand the formation of an attitude by consumers towards online grocery shopping.
All characteristics will provide separate insights as to their influence on the degree of resistance
and the willingness to (re)try online grocery shopping. Moreover, a better understanding can be
formed on the importance of the innovation characteristics and potential differences between
consumer(groups). With this information food retailers are better able to understand customers and,
if necessary, adapt innovations to meet their needs (Zaltman, Duncan & Holbek, 1973). In our conjoint
analysis the consumer characteristics will be taken into account as a moderating effect, in order to
identify potential segments. This will enable food retailers to better understand which adopter groups
like and which dislike shopping online for groceries. This is necessary in order to make the innovation
appealing to the most important adopter groups (Rogers, 1995), and in order for the innovation to
diffuse throughout the market properly (Hoyer & McInnis, 2008). In appendix A an overview is given
of the consumer characteristics, which will be taken into account in our studies. The consumer
characteristics are selected by comparing different sources regarding the diffusion of innovations (e.g.
Meuters et al., 2005; Dabholkar, 1996). Additionally, a further explanation will be given in this part for
each characteristic.
Technology readiness: The technology readiness depends on a person’s innovativeness, attitude
towards technology and their anxiety to using technology. Thus, what is a person’s attitude towards
new technologies and the usage of it in daily life (Bobbit & Dabholkar, 2001: Parasuraman, 2000)? For
this study it is therefore, important to know whether the consumer’s degree of technology readiness
influences the usage and adoption of online grocery shopping.

33

Motivation: A consumer’s motivation for using online grocery shopping depends on the degree
in which they need grocery shopping to be more convenient (extrinsic/utilitarian) (Braczak, Ellen &
Pilling, 1997: Davis, 1989). This is also the case of the usage of an e-commerce environment (Bridges
& Florsheim, 2008: Pagani, 2004). Therefore, in our case, it is important to understand whether the
motivation of a person influences the degree of resistance and adoption of online grocery shopping.
Need for interaction: The personal interaction between consumers and employees is of course
lower in an online environment. Contrary to a regular supermarket, consumers are less able to
interact with employees. The degree to which a consumer needs personal interaction is referred to as
‘need for interaction’ (Dabholkar, 1996). Thus, the resistance towards trying online grocery shopping
increases if a person has a higher need for personal interaction (Meuters et al., 2000). For this study it
means that food retailers should understand the effect of interaction on the resistance and adoption
of online grocery shopping. If this is indeed an important aspect then alternatives should be offered
for the interaction.
Time pressure: Consumers with a higher time pressure are more likely to look for alternatives
(Childers, Carr, Peck and Carson, 2001). This is also acknowledged by the study of Rogers (1995). In
his study he states that consumers with a lower satisfaction are more likely to look for alternatives.
However, shopping for groceries in an online environment also depends on several other hurdles (e.g.
delivery issues and less interaction). Therefore, it is important to understand whether the time aspect
is more, equally or less important than the hurdles.
Attitude towards the online channel: Whether a consumer will use an online channel also
depends on their attitude towards information sharing and online payment (Childers et al., 2001).
A negative attitude towards information sharing and online payment can influence the willingness
of consumers to try and adopt online grocery shopping. Insight into the effect and influence of the
privacy concerns can help food retailers to better shape the online environment and to decrease the
resistance towards trying online grocery shopping.
Current usage/knowledge (online channel): Studies in the innovation diffusion area and
the adoption have shown that consumers with more knowledge of the online environment or
experience react more positively towards the adoption of new technologies and service (Meuters
et al., 2005; Mahajan et al., 1990; Reinders, Dabholkar & Frambach, 2008). If this is the fact for online
grocery shopping, then food retailers could use this information to attract consumers who already
use other online services as well.

34

Need for convenience: Convenience is becoming more and more important for consumers. Verhoef
and Langerak (2001) already stated in their study that the most important factor for a consumer to
shop online is the convenience that the online channel offers. Therefore, it might also be interesting
to know the effect of this variable on the resistance and the adoption for grocery shopping.
Travel costs/time: The Netherlands has a very high density of supermarkets (CBL, 2008). Therefore,
a better understanding is needed of the effect of travel costs and travel time of Dutch grocery
shoppers. Thus, this characteristic measures whether consumers perceive the monetary costs and
time to visit a regular supermarket as high.
Shopping enjoyment: The general shopping enjoyment (hedonic) of a consumer can influence
consumers in a positive way and increase the chance of trying new shopping services (Childers
et al., 2001; Davis, 1989; Arnold & Reynolds, 2003). Therefore, it is expected that consumers who like
shopping in general have a higher chance of trying online grocery shopping, even if it is solely for fun.
General innovativeness: The technology readiness characteristic is based on a person’s general
innovativeness towards technologies (Bobbit & Dabholkar, 2001: Parasuraman, 2000). However, a
consumer’s general innovativeness influences the degree to which they are open to gathering
information and using new products and services (Baumgartner & Steenkmp, 1996). This is not related
to technologies, but it gives an indication of whether someone is open to gathering information
or using alternatives. In combination with the study of Rogers (1995) this can give an indication on
whether a consumer is an early adopter of actually a laggard.
Satisfaction with general online shopping and general grocery shopping: As it was previously
stated, it is expected that consumers who already have experience with shopping in an online
environment are more likely to try other online shopping services (Meuters et al., 2005; Mahajan et
al., 1995; Reinders et al., 2008). However, it is also expected that the degree of trying additional online
services depends on a person’s current satisfaction with the online environment (Lijander et al., 2006).
Therefore, the satisfaction toward general online shopping is measured as well. Moreover, the study
of Rogers (1995) states that consumers who are not satisfied with a specific product or service will,
more likely, look for alternatives. Therefore, an understanding is needed of whether consumers are
unsatisfied with the current way of grocery shopping and whether they are indeed more likely to try
online grocery shopping (Lijander et al., 2006; Mittal, Kumar & Tsiros, 1999).
Demographics and shopping behaviour: Finally, demographics and grocery shopping behaviour
are taken into account. Aspects such as age, gender and household composition might influence the

35

degree of resistance and adoption (e.g. Rogers, 1983; Venkatraman, 1991). Additional aspects such as
the frequency of grocery shopping, time spent on each visit to regular supermarket and the person
who is responsible for the grocery shopping within a household are also important. These aspects
can all provide more information and help food retailers to target segments with the lowest degree
of resistance and the highest chance of adoption online grocery shopping.

§3.4 Adoption path- willingness to retry and degree of resistance
Alongside the influencing antecedents and the moderators our framework also shows the adoption
path, which is adapted from Ram (1987) and (Kleijnen et al., 2009), as our framework indicates a too
high degree of resistance might lead to one of the resistance forms (i.e. postponement, opposition
and rejection). However, if an individual decides to resist an innovation and the innovation is
adaptable, then the entire process can start all over again. However, a perquisite is that an individual
should be willing to re-evaluate the innovation. If this is the case then a re-evaluation of the adapted
innovation might lead to not resisting the innovation and maybe even adopting it (Ram, 1987;
Zaltman, Duncan & Holbek, 1973). Nevertheless, if the innovation is not adapted well enough, it can
again lead to one of the resistance forms. While the opposition and rejection lead to not using the
innovation at all, postponement might still lead to the adoption of the innovation at a later stage
(Kleijnen et al., 2009).
Therefore, both the degree of resistance and the willingness to retry online grocery shopping will also
be analysed. This is done in order to provide insight into the influence of the consumer characteristics
on both variables. In chapter two it has been mentioned already that no resistance does not directly
lead to the adoption of a product of service (e.g. Gatignon & Robertson, 1989; Herbig & Day, 1992; Ram
& Sheth, 1989) and adoption only occurs if there is no resistance (e.g. Ram, 1987; Ram & Sheth, 1989;
Hoyer & MacInnis, 2008). Therefore, a better understanding is needed of the influence of consumer
characteristics on the resistance and the adoption.

§3.5 Conceptual model for conjoint study
As previously mentioned, consumer characteristics are not controllable and therefore, only
used to better understand potential users. Food retailers, however, can influence the innovation
characteristics. Therefore, the antecedents of this dimension are further investigated in this subchapter and are used to form a preliminary conceptual model (see figure 3.3). In table 3.2 theory
based hurdles and benefits of online grocery shopping are provided. The consumer characteristics
will only be used in our conjoint analysis to identify whether different adopter groups are present
36

and if they react differently towards the innovation characteristics. It also
provides information on how food retailers should attract and target
potential adopters.
Theory based hurdles and benefits: The importance of the innovation
characteristics will be studied in our conjoint model. In order to depict the
most important characteristics, first an overview is given of the hurdles
and benefits of online (grocery) shopping, which have been found in prior
studies (e.g. Verhoef & Langerak, 2001; Hand, Riley, Harris, Singh & Rettie,
2008; Kurnia & Chien, 2003). Through the use of these and other studies a
conceptual framework is formed in which the six innovation characteristics,
mentioned in table 3.1, function as a base for the framework. Additionally, a
short explanation is provided for each aspect in table 3.2 and the sources of
each aspect are also provided.

Table 3.2:
Theory based hurdles
and benefits of online
grocery shopping

Park, Perosio, German & McLaughlin, 1998;
Wilson-Jeanselme & Reynolds 2006

Convenience due the ability to receive the groceries at
home.

Darian, 1987; Grewal et al. 2004; WilsonJeanselme & Reynolds 2006

Time saving (e.g. less wait time & planning time).

Burke, 1997; Park et al. 1998; Peterson et al.
1997; Verhoef & Langerak, 2001; Darian 1987

Larger assortments compared to bricks-and-mortar
grocery shops and easier to compare.

Grewa et al., 2004; Chu et al. 2010; WilsonJeanselme & Reynolds 2006; Alba et al. 1997;
Darian 1987

Shopping enjoyment is less possible during online
grocery shopping (hedonic motivations).

Compatibility

Sources (e.g.)

Price advantage compared to an offline store.
Relative advantage

Aspect

Alba et al. 1997; Verhoef en Langerak, 2001,
Bruner & Kumar 2005; Childers et al. 2001;
Mathwick et al. 2001

The quality of the online shop (quality of interface,
usability and information quality).

Ahn, Ryu & Han, 2004; Wolfinbarger & Gilly,
2003; Wilson-Jeanselme & Reynolds, 2006

The quality of the delivered groceries should not differ
from offline purchased groceries.

Baker, 2000; Ernst & Young, 1999; Citrin et al.
2003; Kurnia & Chien, 2003

Consumers are not able to feel, smell, touch and try the
groceries (sensory attributes).

Chu et al. 2010; Morganosky & Cude, 2000;

A consumer has to be at home when the groceries are
delivered (delivery options).

Wilson-Jeanselme & Reynolds 2006

Consumers have to pay a delivery fee.

Huang & Oppewal, 2006; Småros,
Holmström & Kämäräinen, 2000

37

Complexity
Communicability

The possibility to try online grocery shopping on a
limited base in order to better understand how it works
and to enhance the trust towards it.

Verhoef & Langerak, 2001

Order and fulfilment procedure should be easy (order
time).

Verhoef & Langerak, 2001; Wilson-Jeanselme
& Reynolds 2006

Shopping online should be done in a setting that
matches the offline environment (Virtual reality- 3D
shop- Interface).

Freeman et al., 1999

The online shop(ping) should not differ too greatly from
current online shops (non grocery products).

Reinders et al. 2008

Communication with others is less personal in the
online environment and also not as easy as in the offline
environment.

Verhoef & Langerak, 2001; Chu et al. 2010;
Freeman et al. 1999

Zeithaml et al. 2002; Wolfinbarger & Gilly,
2003; Gefen & Straub, 2003; Ha & Stoel, 2009;
Park et al. 1998

The risk of receiving groceries with a lower quality.

Baker, 2000; Ernst & Young, 1999; Citrin et
al. 2003; Kurnia & Chien, 2003; Forsynthe &
Shi, 2003

The delivery of products takes too long (time slots)

Kurnia & Chien, 2003; Wilson-Jeanselme &
Reynolds 2006

The online grocery shop is not working/offline (fails to
work/ not robust).

Curran & Meuter, 2005; Meuter et al., 2000

Not being able to ask questions to employees (no
interaction possible).

Perceived Risk

Sources (e.g.)

The perceived risk of doing business over the internet
(Payment, information sharing)

Divisibility

Aspect

Reinders et al. 2008; Shankar et al., 2002

38

§3.6 Conclusion
The different aspects, which are presented above, are used to form the
conceptual model in figure 3.3. The conceptual model in 3.3 is, however,
a preliminary model and its completeness will be tested in chapter four.
This will be done through the use of a qualitative study in which the
current aspects will be presented during individual interviews and group
discussions and, if necessary, additional aspects will be added to ensure a
complete conceptual model.

Figure 3.3: Preliminary
conceptual model

39

40

4. Methodology
In the previous chapter a preliminary conceptual framework was presented (see figure 3.2).
However, this framework is solely based on insights gathered from literature. In order to be sure
that all important hurdles and benefits are taken into account a qualitative study is conducted to
check our findings and if necessary, to enhance our model with new insights. In a second study
the same participants from the first study and ten additional participants are asked to rank the six
most important hurdles and benefits from the final conceptual model. This is the model which is
derived from literature and study one (see figure 4.1). This will lead to the formation of the final six
attributes, which are tested in the third study. These outcomes provide insight into the importance
of each hurdle and benefit. Additionally, the moderating effects will be tested, as well, to see whether
they affect the hurdles and benefits. Finally, possible segments will be identified in order to better
understand potential differences between customers and their needs.

§4.1 Study one – qualitative study
As was mentioned above, the preliminary conceptual framework (see figure 3.2) is a result of a
literature study in chapter three. In order to determine whether or not it is complete a qualitative
study is conducted in this section, which will test whether the 19 attributes of the conceptual model
are in line with hurdles and benefits according to consumers. The qualitative study consists of two
parts. In the first part individuals are interviewed and in the second part we have conducted groups
discussions.

4.1.1. Method
Participants: For study one we have conducted seven individual and three group discussions
(three individuals per group). During the group discussion both active and non-active (online)
shoppers were interviewed at the same time in order to create a better discussion and to gain
insight into whether there are differences between the two groups. These differences would
also aid in understanding the completeness of our conceptual model in figure 3.2. Differences
between active and non-active (online) shoppers have also been taken into account during the
individual discussions. Moreover, participants were also selected on the following criteria: household
composition, gender, age and innovativeness. This is done in order to ensure that a representative
group is interviewed and that different needs are taken into account.

41
Methodology

Procedure: Participants in the individual discussion were asked questions regarding (online)
shopping and (online) grocery shopping. These questions (e.g. what do you think of grocery shopping
in general or can you explain your first thoughts if I mention online grocery shopping) were mainly used
to get a discussion started and in order to gain insights into whether there are additional hurdles
or benefits regarding online grocery shopping. The discussion was focused on characteristics of
the online grocery shop and its perceived relative advantage, compatibility, complexity, divisibility,
communicability and risks.
During the group discussions a different approach was used. This time the participants received
different quotes (e.g. if online grocery shopping is cheaper than shopping in a regular supermarket,
then I will probably shop online for groceries or the benefits of online grocery shopping are…),
which they had to share with the rest of the group and explain whether or not they agreed with
the quotes and why this was the case. The quotes were used to gain insight into the different
characteristics of online grocery shopping and its perceived relative advantage, compatibility, trial
ability, communicability and perceived risk as well. However, in some cases additional questions were
asked to the group, because the discussion of the quotes did not always lead to sufficient insights.

4.1.2 Conclusion
Conclusion individual discussions: During the individual discussions most participants indicated
that they did not really think about shopping for groceries in a different way, as their current way of
grocery shopping was part of their life. They were simply used to shopping for groceries in a certain
way. Additionally they stated that grocery shopping in a regular supermarket offers hedonic aspects
as well and is not always only for utilitarian purposes (e.g. I like to just visit the supermarket and I do
not perceive it as only something that is necessary). On the other hand, they also acknowledge that
their satisfaction with shopping in the offline channel for groceries is low (an average of 6.8 on a scale
of 1-10). Moreover, the satisfaction (average of 6) is even lower for participants who work full-time
and/or have children. They even see online grocery shopping during the week as a burden. Overall,
people are willing to try shopping online for groceries, but they would still prefer to visit the offline
channel as well as using the online channel.
Comparing the aspects, which are mentioned in our preliminary conceptual model and the findings
of the different discussions, it can be stated that most of our aspects are confirmed. The participants
state that the basics of the online grocery shop should work and should continue to work properly.
If not, their trust in the online channel would decrease and they most probably will switch back to
the offline channel again. The same holds for the ordered groceries. They should all have the same
quality as in the offline channel and the orders should always be complete (no missing articles).

42

Moreover, the main focus for the advantage should be on the large assortment, delivery convenience
(delivery fee, delivery time & delivery slots), it should be easy to use and comparable to offline grocery
shopping (e.g. 3D environment). It was very interesting to see that most perceived hurdles were
based on the delivery convenience and whether the online shop was reliable (server stability) than
on payment or online information sharing. This was even the case for the participants who did not
shop online at all.
Based on the individual study it can be stated that there are three additional aspects, which can be
added to our preliminary conceptual model. The first one is the ability to shop at all supermarkets
online (e.g. AH, C1000, Lidl, etc.). Participants have indicated that they shop for groceries at multiple
supermarkets. This means that if one of their preferred supermarkets does not offer the ability to
shop online for groceries they would have to go to a regular supermarket for some products. This
will probably create resistance towards online grocery shopping. The second one is the ability
to purchase food and non-food products at the same time at one retailer. This option might be
interesting for consumers as more and more products are purchased online and the necessity for
them to be at home for deliveries is seen as a hurdle for online shopping. Therefore, by delivering all
food and non-food products together this will save time and counteract the hurdle to shop online.
The final one is the ability to receive the ordered groceries at home at the same time with other
non-food products, even if they are not purchased at the same retailer. Both benefits indicate a need
for convenience during the delivery phase.
The main conclusion that can be drawn from the individual discussions is that consumers prefer
the hedonic aspect of offline shopping and the control they have on the quality of the goods they
purchase. However, the time restraint and the decreasing satisfaction in the offline channel (average
satisfaction in our case of 6.8 on a 1-10 scale) offer opportunities for online grocery shopping as well.
By counteracting the main hurdles; i.e. the quality of the received goods should not be lower than
in an offline environment (e.g. lower quality tomatoes), the delivery phase should be convenient (i.e.
delivery fee & delivery options) and an online shop should be easy to use (time to order), the usage of
online grocery shops could be increased. Moreover, to make it even more attractive to use, an online
grocery shop should offer additional benefits compared with a regular supermarket e.g. convenience,
price and a larger assortment.
Conclusion group discussions: The group discussions led to almost the same conclusions as the
conclusions of the individual interviews. However, it is important to note that during the group
discussions the less innovative and less active shoppers were quite easy to convince by the other
participants. Initially some participants showed distrust towards the payment and information sharing

43
Methodology

risks. However, the distrust would diminish if other more experienced and innovative participants
counteracted these arguments with positive examples gained from experience. This might indicate
that positive WOM could increase the rate of adoption as well. Another noticeable observation is the
fact that the participants within the group discussions were less convinced of the price benefits they
would receive from online grocery shopping. They also indicated that online shopping in general
had a lower service level, as it is more difficult to contact employees in case of problems. The effort
to solve the problem will cost additional time, which will overrule the “small” price benefit. Moreover,
they argue that at this moment the prices between offline and online do not differ greatly for general
products as well. This statement is formed by prior experience with online shopping. Finally, no
additional hurdles or benefits, which are not mentioned in the preliminary conceptual model or in
the individual discussions, are found.
General conclusion: Most participants are willing to try the online channel for grocery shopping.
Their main concern is more towards the quality difference of the received goods and convenience
of ordering groceries via the online channel (e.g. delivery and order time) than on online payment or
information sharing. Positive WOM and time restraint might also positively influence the adoption of
the online channel.

§4.2 Study two – top six attributes
The first study has provided insight into whether there are additional hurdles or benefits, which have
not been taken into account in the literature part. Based on these findings we have adapted our
preliminary conceptual model and have added three new hurdles and benefits (see figure 4.1). In
order to determine the three most important hurdles and the three most important benefits we have
conducted a second study in which all of the hurdles of figure 4.1 have been presented.

44

Figure 4.1: Final
conceptual model
conjoint analysis

4.2.1 Method
Participants: For the second study we have asked the same participants
from the first study and ten additional participants to choose their top six
hurdles and top six benefits. The same criteria are used for the additional ten
participants as the criteria mentioned in study one (e.g. active/non active
(online) shoppers, household composition, gender, age and innovativeness).
The additional ten respondents are added in order to increase the sample,
as the study is a more quantitative one than the first study.
Procedure: Two main questions were presented to the participants. In order
to find the top six benefits we have stated the first question in a positive
way: i.e. I would certainly shop online for groceries if… After the main
questions all hurdles and benefits are presented in a sentence form: e.g.
if online grocery shopping is cheaper than grocery shopping in a regular
supermarket, or: if the order procedure in the online environment would be
short. Participants were asked to choose and rank (1 to 6) the top six most
important reasons for them to shop online for groceries. The same was done
to find the top six hurdles, however, this time the main question and the
choice were presented in a negative form: e.g. I would certainly not shop
online for groceries if… and again the hurdles and benefits were presented

45
Methodology

in a sentence form: e.g. if online grocery shopping is more expensive than
shopping in a regular supermarket, or: if the procedure to order online takes
Table 4.1:
Theory based hurdles
and benefits of online
grocery shopping
Rank

a long time. This has resulted in the following ranking:

Hurdles

Benefits

1

Delivery fees

Time saving

2

Delivery options

Price

3

Quality of ordered goods

Order procedure

4

Delivery time


5

Price

Delivery time

6

Convenience

Delivery options

The ranking in table 4.1 is formed in the following way. If a participant would
rank a benefit or hurdle as the most important one, the hurdle or benefit
would receive 6 points. The second most important hurdle or benefit would
receive 5 points and so on until the sixth most important hurdle or benefit.
If a hurdle or benefit would not receive a ranking at all it would receive 0
points. At the end the sum of all points has lead to the top six as presented
in table 4.1.

4.2.2. Conclusion
It is clearly visible that the entire delivery process of grocery shopping is
really seen as a large hurdle. Not only are the costs of the delivery important,
but also the number of delivery possibilities per day and the time that it
takes to receive the groceries. Moreover, it seems that consumers do not
want the ability to choose their own products, but they do indicate that the
quality of the order goods should be at least as equally high as the offline
channel. This is in line with the most important benefit, namely the fact that
online grocery shopping should really be time saving. If they would have to
choose each product themselves, it would simply cost too much time. This
also indicates that the benefit of online shopping should not only concern
monetary benefits, but also non-monetary benefits, which are perceived
as more important than monetary benefits. Next, the third most important
benefit again indicates that time is very important. Thus, the time it takes

46

for consumers to order and pay their groceries online should be as short as possible. It is however
remarkable that the online payment and information sharing is not seen as an important hurdle. The
same can be concluded for the assortment. It was expected that a larger assortment would be an
important reason for consumers to purchase online.
It can be concluded that consumers need the online grocery shopping process to be as simple and
quick as possible. This is also the case for the order procedure and the entire delivery process. Thus, by
only offering cheaper products the online channel cannot increase the adoption rate. These findings
are in line with the findings of the individual and group discussions in which the respondents have
indicated that the basics of the online grocery shop should work properly in order for them to
consider adoption.

§4.3 Study three – quantitative study
In this study the findings from the first two studies will be used to form a questionnaire (see appendix
A) in order to conduct the final and quantitative study. First, it will be explained why a Choice Base
Conjoint is used, followed by the survey development, the data collection and finally the data analysis.

4.3.1. Research method
Conjoint analysis: In this study we intend to explain what the perceived value of online grocery
shopping is for consumers. Hair, Black, Babin, Anderson and Tatham (2010) state that consumers
evaluate the value of an object by combining the separate amounts of value provided by each
attribute in the object, which are in our case the hurdles and benefits. The value in turn determines
whether the service is adopted or resisted by the consumer. Hence, in our study consumers evaluate
the different sets of attributes and form a perceived value based on the separate values of the
attributes. Therefore, for our research a conjoint analysis is most appropriate (e.g. Hair et al, 2010;
Malhotra, 2010), especially if we compare our description with the definition of a conjoint analysis
according to Malhotra (2010): “a conjoint analysis attempts to determine the relative importance
consumers attach to salient attributes and the utilities they attach to the levels of attributes”.
However, there are different forms of conjoint methods e.g. traditional conjoint analysis, adaptive
conjoint analysis and the choice based conjoint analysis and not all are suited for our study (Hair
et al., 2010; Orme, 2009). In our study we have chosen to use the Choice-Based-Conjoint (CBC)
method, because compared to the standard conjoint and an adaptive conjoint analysis the tasks
in a choice based conjoint analysis represent the market behaviour more directly. Furthermore, it is
recommended to use no more than six attributes in a CBC analysis (Hair et al., 2010; Malhotra, 2010).

47
Methodology

Regression: Besides finding the importance per hurdle and benefit and potential segments, we are
also interested in the degree of resistance and the willingness to (re)try online grocery shopping.
Both are measured at an individual level (Leeflang, Witting, Wedel & Naert, 2000). The willingness to
(re)try is measured with the use of a Likert-scale (i.e. 1-very unlikely to 5 -very likely) and the resistance
is measured based on the following choices; (1) whether someone is likely to try online grocery
shopping very soon, (2) in the future, (3) not at all or (4) not at all and will use negative WOM in order
to stop others from using it as well.
The willingness to (re)try is measured with three items all on a five-point Likert scale. Initially this
could be analysed by using an Ordered Multinomial Logistic Regression (Leeflang et al., 2000).
However, as we intend to take the average of the three items to form one construct, an Ordinary Least
Squares (OLS) method will suffice. The reason is because the five categories on which the items are
measured disappear and the output becomes a scale variable (Hair et al., 2010; Leeflang et al., 2000).
The degree of resistance is measured by using four categories. Initially the use of a Multinomial
Logistic Regression would seem a proper way to analyse this. However, the different options contain
a specific order, as the first option contains no resistance and the other three options increase in
resistance ending with the highest in the fourth option. Therefore, the resistance will be analysed by
using an Ordered Multinomial Logistic regression (Hair et al., 2010; Leeflang et al., 2000).
For both regressions the consumer characteristics and the demographics will be used as covariates
to better understand which consumer characteristics lead to resistance and which to adoption. The
data is cross sectional in both cases (Leeflang et al., 2000).

4.3.2 Survey development
After choosing the research design and conjoint method we developed the questionnaire, which
consists of three sections. The first section of the questionnaire concerns the measures with regard
to consumer characteristics. These measurements will provide insight into the moderating effects
of the different consumer characteristics, it will enable segmentation and the respondents are
triggered to think about their (online) grocery shopping behaviour. The latter is necessary in order to
prepare respondents for the stimuli part, as they have to think about it in the first part. Moreover, the
consumer characteristics will also be used as independent variables in order to study whether they
influence the degree of resistance and the current willingness to (re)try online grocery shopping. In
the second section of the questionnaire, the stimuli are presented. Respondents can choose their
most preferred online grocery shop, which resulted from the top three hurdles and top three benefits.
Finally, section three will provide insight in the degree of resistance towards online grocery shopping

48

and the willingness to re(try) an online shop. Each section is further explained below.
Section one- consumer characteristics: Section one contains the measures with regard to
consumer characteristics, which are: technology readiness, motivation, need for interaction, time pressure,
attitude towards online channel (privacy), current usage of online shops, current knowledge of online
shopping, travel costs/time, shopping enjoyment, grocery shopping behaviour and demographics. These
questions have been presented on a 5-point Likert scale (1- totally disagree to 5- totally agree),
as it is a proper scale to measure consumer attitudes (Malhotra, 2008) and is perceived as easier
when compared to a 7-point Likert scale. The questions for the characteristics are formed by using
existing measurements, which have been found in literature. In some cases we have formed our
own questions to enable the measurement of all characteristics. Each measurement and its source is
explained in appendix A.
Section two- stimulus presentation: This section is formed with the use of study two. In table 4.2
the different hurdles and benefits are shown. Each one is further divided into three attribute levels.
The levels are formed by using real life examples and literature (e.g. AH.nl, 2012; Wilson & Reynolds,
2006).
The formation of the questions for the conjoint part is performed with the use of Sawtooth software
(sawtoothsoftware.com, 2012). To limit the amount of questions, Sawtooth calculates which
combination of questions makes sure that the efficiency per level is at least 0.80. This ensures that
each level is properly represented in the calculation of the utility. The combination of questions is
based on the amount of attributes, amount of levels, amount of respondents and the amount of
versions used in the questionnaire. In our case we have six attributes and three levels per attribute.
To limit the amount of questions we have used three versions of the conjoint questions. This means
that we have three different sets of questions in the conjoint part of our questionnaire. This also
allows us to achieve an efficiency of at least 0.80 for each level with approximately 200 respondents
(N=200). Each set comprises seven questions, which in turn consists of two stimuli. The stimuli are
the combination of the different levels mentioned in table 4.2. Each stimulus consists of six levels
(see appendix B2). The efficiency score for each level is, in this case, at least 0,87, thereby fulfilling the
requirement for a conjoint design (Hair et al., 2010). Next to the seven randomly selected questions
with the use of Sawtooth software, we will present one hold-out question as well. In this question we
have formed two stimuli, which allows us to check how accurate the estimated model predicts the
hold-out sets (Hair et al., 2010).

49
Methodology

Table 4.2
Online Grocery Shop
design elements

Only in the afternoon

No items below quality

€ 4,99 delivery fee

Afternoon and evening

1 out of 20 items is below
quality

€9,99 delivery fee

Free choice

1 out of 10 items is below
quality

Time saving

Price

Order procedure

Saves no extra time
Benefits

Deliver options

No delivery fee
Hurdles

Delivery Fees

No price difference

20 minutes to place and order

Saves 5% of total
shopping time

5% cheaper than regular
supermarket

40 minutes to place an order

Saves 10% of total
shopping time

10% cheaper than regular
supermarket

1 hour to place an order

During the questionnaire respondents are thus offered two options each
time. The none-option is left out, because it is expected that consumers
might choose for the none-option too often as they have little experience
with online grocery shopping. The tasks and the efficiency of each level are
provided in appendix B2 and the different conjoint questions are provided
in appendix B1.
Section three- demographics and shopping behaviour: In the final
section the following measurements are used; willingness to (re)use online
grocery shopping (5-point scale from 1-very unlikely to 5-very likely), satisfaction
with current offline grocery shopping and general online shopping (grade from
1-very dissatisfied to 10-very satisfied), degree of resistance (four categories) and
finally the socio demographic characteristics and the current (online) shopping
behaviour. The demographics and shopping behaviour questions range
from gender and age to the frequency of grocery shopping in a general
supermarket. The overview of all questions is provided in appendix A.

50

Samir selimi thesis- online grocery shopping

Samir selimi thesis- online grocery shopping

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