is an online shop the future for fresh food retailers in the

Student: Loes van Kempen Student Number: 6330258 Date: 5 November 2012 (Final Version) 1st Supervisor: Tom Paffen 2nd Reader: Mark Leenders

Master Thesis Is an online shop the future for Fresh food retailers in the Netherlands?

An empirical study anticipating on the decreasing

number of Fresh food retailers and the rise of online

shopping in the Netherlands

Master Thesis Universiteit of Amsterdam (Final Version)

Loes van Kempen – November 2012

TABLE OF CONTENT

Acknowledgements................................................................................................................................. 3

Abstract .................................................................................................................................................. 4

Introduction............................................................................................................................................ 5

Research Question ............................................................................................................................. 7

Structure of the Thesis ....................................................................................................................... 8

Literature Review .................................................................................................................................... 8

Dependent variables – Personal Characteristics .................................................................................. 9

Dependent Variables – Shopping Motives ......................................................................................... 11

Sector Analysis - Existing e-Food Concepts in the Netherlands .......................................................... 17

Conceptual Framework .................................................................................................................... 21

Data and Methodology ......................................................................................................................... 23

Method ............................................................................................................................................ 23

Variables .......................................................................................................................................... 23

Sample ............................................................................................................................................. 23

Data Collection ................................................................................................................................. 24

Data Analysis .................................................................................................................................... 26

Results .................................................................................................................................................. 27

Descriptive Statistics......................................................................................................................... 27

Statistical Tests ................................................................................................................................. 29

Hypotheses Testing .......................................................................................................................... 33

Conclusions........................................................................................................................................... 36

Hypotheses ...................................................................................................................................... 38

Theoretical Implications ................................................................................................................... 39

Managerial Implications ................................................................................................................... 39

Limitations ....................................................................................................................................... 40

Future Research ............................................................................................................................... 40



Reference List ....................................................................................................................................... 42

Articles and Books ............................................................................................................................ 42

Websites .......................................................................................................................................... 46

Appendices ........................................................................................................................................... 48

Appendix 1 - Online Survey ............................................................................................................... 48

Appendix 2 - Descriptive Statistics .................................................................................................... 50

Appendix 3 - Statistical Tests ............................................................................................................ 53

ACKNOWLEDGEMENTS

This thesis is written in the scope of the Master Business Studies, intensive program, at

the Amsterdam Business School, part of the University of Amsterdam in the Netherlands.

The work provided in this thesis is original and no other sources than mentioned in the

text and reference list have been used. Before finalizing my education at the University, I

would like to thank several people. Firstly, I would like to thank my thesis supervisor Dr.

Tom Paffen for guiding me and giving me insights and advice in writing this thesis.

Secondly I would like to thank all the stakeholders, respondents and interviewees, for

giving the required input for this research. Finally I would like to thank my family for their

mental support and in particular Thomas for his useful contributions and advice, and

continuous support for the past 2,5 years.



ABSTRACT

The Fresh food retailers in the Netherlands, like the bakery and butcher, are disappearing from the streetscape. Meanwhile, the Dutch are very active Internet users and shoppers within the European Union. Would an online shop perhaps be the solution for Fresh food retailers to survive? In this study the effects of online shopping for the fresh food industry in the Netherlands have been investigated. Based on 173 valid responses of Dutch consumers, an analysis has been done on the decision making process of their choice for shop; supermarket or Fresh food retailer. Even in the Netherlands with a relatively high number of online shoppers, in general food is still the least popular product category bought online, which has been confirmed by this study. The customer is not yet ready for e-food. However, the shopping motive convenience is rated most important as a factor in their decision making process for choice of shop. The retailer should anticipate on this, but according to the results of this study 40% of the customers are interested in e-food, as long as they don’t have to pay extra for it. Is the supplier side ready for the online shopping phenomenon? Based on the results of a sector analysis of the concepts that already exist in the e-food sector in the Netherlands, reflecting the customer perspective results from this study, it can be concluded that they are not, for several reasons. The main threshold for the Fresh food retailers is the rather complicated logistic process in combination with the assurance of high quality and daily fresh food products. The full service concepts; offering a ‘box’ with recipes plus all required high quality ingredients, delivered at the doorstep, seem to be the perfect answer to the need for this shopping motive convenience. Fresh food retailers should anticipate on this in order to prevent themselves for falling behind. There are certainly some steps to be made in establishing the e-food sector further, especially the logistic challenges; however it seems that the question is not ‘if’ e-food will be upcoming, the question will just be ‘when’.



INTRODUCTION

‘It may not always be profitable at first for businesses to be online, but it is certainly going to be unprofitable not to be online.’

- Esther Dyson -

Is Dyson’s statement true?

The main topic of this research is the Dutch attitude towards online shopping for fresh food. As shown in figure 1, the Netherlands is together with Iceland and Norway, among the top 3 countries of Internet users.

Figure 1 - Internet Users (per 100 people) – source: data.worldbank.org

On top of that, according to the latest figures of Dutch Central Buro for Statistics, the number of active Internet shoppers in the Netherlands is far above the EU average (see figure 2) and among the top 4 countries within the EU.

Figure 2 - Online shopping (Internet Users aged 16-75) Figure 3 – Online shopping by age in the in the EU, 2011 – source: www.cbs.nl Netherlands, 2012 – source: www.cbs.nl

Country Name 2010

Iceland 96

Norway 93

Netherlands 91

Luxembourg 90

Sweden 90

Denmark 89

Finland 87

UK 85

Bermuda 85

New Zealand 83

Iceland Norway

Holland



In the last couple of years online shopping has become increasingly popular in the Netherlands. Since 2006 the share of 16-75 year-olds (see figure 3) who bought products online increased by more than 20 percent points. This could be considered as sufficient proof to investigate this online shopping behaviour in the Netherlands in further depth. On the other side, figures from the branch organisations (hoofdbedrijfsschap detailhandel), see figure 4 below, show that the market shares of Fresh food retailers in the Netherlands have decreased since 2007.

Figure 4 – Number of Fresh food retailers (bakery, butcher, greengrocery) in the Netherlands per year – source: www.hdb.nl

Being raised in a family with a long (>60 years) history in the traditional Fresh food retail industry, being a fresh food lover and always conscious of the products I purchase, I am aware of the quality and the experience of shopping at the traditional Fresh food retailers. With these stores disappearing, customers will forget the experience and quality of these specialists. The main conclusion from the previous paragraphs is that on the one hand online shopping in the Netherlands is increasing; on the other hand the number of traditional Fresh food retailers is decreasing.

So far, lots of research has been done on the subject ‘online shopping’ (i.e. Lee 2002,

Vrechopoulos 2001, Dijst 2004); however the majority of these researches were focused

on non-food products. Is the reason why, simply because there is no demand for

shopping fresh food online; or are customers just not aware of existence? These days we

watch Television, we call for free to the other side of the world; we order cloths, books

and toys, all via the Internet. We even get those items delivered at home; why not buy

our fresh food products online and get them delivered at home or collect them from a

convenient time for the customer?

Lee (2002) and Vrechopoulos et al. (2001) confirm that product characteristics also affect

online shopping. Search goods, such as books and CDs, are more suited to be purchased

via the Internet than experience goods, such as fresh vegetables. This also came out of a

recent study by Irvine (2011) on behalf of the Australia Institute on the rise of online retail

in Australia. One of the results was that fresh food was bought least (nr 7) online by

Australian consumers compared to other products such as cosmetics and perfume (6),

sports and leisure goods (5), clothes and shoes (4), electronic goods (3), books (2) and



DVDs and music (1). This was also stated by Dijst (2004) and Li et al. (1999) in their

research on the shopping motives (recreational or functional) which affect the decision

whether to buy online or to buy in-store. The packaging could be one of the factors

influencing the customers’ thoughts about ordering fresh food products online. Can the

customer trust that the packaging method used by the online provider still guarantees the

quality of the food products? According to M. Bongers (2012), E-food expert, owner of

Iceberg Web shop hands, and delivering fresh and frozen food products throughout the

Netherlands for more than five years, this should not be one of the factors influencing the

decision making process. He actually advises supermarkets to step away from centralizing

their distribution channels, like Albert Heijn, and focus more on a de-centralized business

model; selling local products, like Coop and Plus supermarkets do. As stated before food

shopping is considered in general functional, however if the quality of the products is

good and used to prepare good quality, healthy food, it could be considered recreational

as well.

Research on the online purchase process has been done as well, however not specifically for the purchases of fresh food via the Internet. For this particular industry the focus should be on how to attract its customers to the online shops. According to the research done by Aladwani (2006), it was shown that by giving attention to building a technically sound website with effective content and attractive design, an organization could bring in more consumers to its online business and convince them to make purchases. Does this also count for fresh food products?

Chuang & Fan (2011) address the relative importance of system quality and service quality in their effects on a consumer’s trust in online shopping, while information quality is not. This is very likely the case for online food shoppers as well.

The phenomenon of online shopping in general is clearly not new for consumers in the Netherlands; however there seems to be a gap for shopping fresh food products online. Will fresh food be the last product category to start its online journey?

RESEARCH QUESTION

The motives explained in the previous chapter, resulted in the following main research question: What are the influences of personal characteristics and shopping motives in the decision making process of customers in the Netherlands, on where to buy fresh food and what is the effect of an online shop on these relationships?

Personal characteristics, such as age, gender, education and income and shopping motives like convenience, price and taste determine whether people make their purchases at a supermarket or at the Fresh food retailers. Will this relationship be influenced if Fresh food retailers offer an online shopping system?

Customers of both supermarkets and Fresh food retailers, living in the Netherlands, are requested to complete an online questionnaire. This questionnaire consists of both questions about their personal characteristics and their motives for shopping at either a supermarket or at the Fresh food retailer. With questions about the availability of having



an online shop for fresh food products, it is investigated whether this has a significant influence on their choice for shop.

STRUCTURE OF THE THESIS

The research question has been derived from an extensive literature review, which will be explained in further detail in the next section; Literature Review. The Literature review also consists and extensive sector analysis for the Dutch e-food sector. In the Data & Methodology section, every step undertaken in the research has been explained in further detail as well as all the variables chosen and how they have been measured. The assembled datasets and sample will also be exemplified.

The Results section consists of an outline of all descriptive statistics as well as the distribution of the data and a detailed data analysis. Finally the results and conclusions are being discussed, including recommendations for future research and the implications for real-world practice are elaborated in the last chapter. The main purpose of this Master Thesis, is to add to the existing literature on online shopping, focussing on fresh food products and give a better insight for Fresh food retailers on the expectations and needs of their (future) customers. Is it time for fresh food retailers to reinvent their business models and create new opportunities for their future?

LITERATURE REVIEW

Schoenbachler & Gordon (2002) stated ten years ago that many traditional businesses are reacting by going online to remain competitive.

Where do we stand now, ten years later in 2012? When observing shopping behaviours in the researchers’ personal environment, a rapid move from preference for offline shopping to online shopping is clearly noticed. Does this count for the food industry, specifically for fresh food products, as well?

Personal experience could be considered as the starting motive for this research, however after having done the literature review, some interesting findings from previous studies have been found.

First of all it is important that it is clear what is actually considered a Fresh food retailer in this research. It is a business or person that sells fresh food products to the consumer, as opposed to a wholesaler or supplier, who normally sell their goods to another business. In this research when referred to Fresh food retailer, it is considered a bakery, a butcher and a greengrocery, not a supermarket.

Secondly, the following definition for online shopping by Mokhtarian (2004) has been used in this research: Searching and/or purchasing consumer goods and services via the Internet.

Anno 2012, it is a fact, based on the numbers as stated in figure 4 in the previous section, that Fresh food retailers like the bakery, the butcher and the greengrocery on the corner

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of the street are disappearing from the streetscape. Figures from the branch organisations and ‘hoofdbedrijfsschap detailhandel’, see figure 4 in the previous section as well, show that the market shares of traditional Fresh food retailers in the Netherlands have decreased rather quickly since 2007. Supermarkets (offering the complete assortment during convenient opening hours) are expanding. The Central Buro of Statistics (CBS) in the Netherlands states that there are 3,200 supermarkets in the Netherlands on 1 January 2012.

Would it be a way to survive for the Fresh food retailers, if they offer the availability to buy their products online?

In this research personal characteristics such as gender, age, location, education and income as well as shopping motives such as convenience, taste and price are considered to influence the choice for type of shop, supermarket of Fresh food retailers, for buying fresh food in the Netherlands.

DEPENDENT VARIABLES – PERSONAL CHARACTERISTICS

As mentioned in the previous chapter, the following personal characteristics (gender, age, education and income) have been taken into consideration as dependent variables for this research, based on the existing literature.

Gender Weijzen et al. (2009) state that it is well established knowledge that women are more health conscious regarding their food choices than are men. Does the difference in health consciousness influence the choice of type of shop for customers in the Netherlands to buy their fresh food products?

Naseri & Elliott (2011) state that in their study results it is found that online buyers of

food and groceries, clothing and shoes and entertainment services were more likely to be

women as opposed to online buyers of DVDs, CDs, financial services, computer hardware

and software and sporting equipment, who tended to be men.

In a research done by the ‘Familiekenniscentrum’ in April 2011, the results show that in

the Netherlands the women are more involved in the purchase process of grocery

shopping (yellow products) and that men are more involved in the purchase process of

more expensive goods (white and red products). In figure 5 below the different levels of

involvement are shown.

Figure 5 – FCB Matrix – involvement men/women in purchase process (2011) – source: www.familiekenniscentrum.nl



Age Veflen Olsen et al. (2012) show that elderly people are more health conscious than

younger people. This could influence their choice of shop, taking into account the

different assortment and the origin of products sold at supermarkets and Fresh food

retailers. From a study done by Naseri & Elliott (2011) the purchase of food and groceries

is better predicted by age and gender, then by other demographic factors.

Having said that, figures of the Central Buro of Statistics (CBS), displayed in figure 6, show

that the life expectancy for men rises faster than for women. Over the entire period 1985-

2011, life expectancy for men has increased more rapidly than for women. Between 1985

and 2000, life expectancy at birth for men grew by 2.5 years, as against only 0.9 years for

women. In the following years, male life expectancy improved quickly. Over the period

2000-2011, male life expectancy increased by no less than 3.6 years. The increase for

women over the same period was 2.3 years.

Figure 6 – Substantial increase male life expectancy (2012) – source: www.cbs.nl

The Dutch population is anticipated to grow from 16.7 million in 2010 to 17.8 million around 2040. As from 2040, the population will diminish marginally to 17.7 million by 2060.

According to other figures from the CBS, the rate of the demographic ageing process in the Netherlands will double in the years to come. In the period 2011-2015, the over-65 population will grow by half a million versus a quarter of a million in the period 2006-2010. That means our population is getting older, particularly men and if age influences type of shop choice for food purchases, this could have a major influence for Fresh food retailers.

Education Tashiro & Lo (2011) confirm that the time allocation decisions regarding food preparation are largely affected by an individual's luxury preference, nutritional consciousness, and the value of time, all of which are influenced by education. Weijzen et al. (2009) found that high education level increases the healthy intention-behaviour consistency for healthy snacks. In other words the level of education appears to influence consumers’ attitude towards healthy food choices. Veflen Olsen et al. (2012) corroborate this since previous findings indicate that education encourages both the increase of healthy food consumption and convenience consumption. They found a positive link

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between education and likelihood of buying healthy convenience food. Lower educated women are catching up.

If education level is taken into account, according to figures of the Central Buro for Statistics in the Netherlands, the highest proportional increase in e-shoppers is recorded among higher educated women: from 40 percent in 2005 to 67 percent in 2010 followed by higher educated men with an increase from 55 to 74 percent. The smallest increase in e-shoppers (14 percentage points) was among lower educated men and women, but proportionally, the growth is much higher among women than among men, so lower educated women are catching up.

Income In the research of Steenhuis et al. (2011) it was clear that price is an important factor in food choice, especially for low-income consumers. Low-income consumers were significantly more conscious of value and price compared to higher-income consumers. According to Glanz et al. (1998) American consumers reported that taste is the most important influence on their food choices, followed by cost. Does this count for consumers in the Netherlands as well; is taste more important than cost?

DEPENDENT VARIABLES – SHOPPING MOTIVES

Exploring the shopping motives of customers in the Netherlands; the following has been proven in past researches:

Convenience As stated previously, advantages of online shopping are convenience and

cost savings. Convenience is defined as time savings and effort savings, including physical

and mental effort (Rohm & Swaminathan, 2004). It is a crucial attribute for consumers

when shopping online. Shopping online makes it easy for consumers to locate merchants,

find items, and procure offerings (Balasubramanian, 1997) and (Wolfinbarger & Gilly,

2001) mentioned that Internet shopping provides a more comfortable and convenient

shopping environment. Consumers do not have to leave their home and they can also

browse for items by category or online store. Schaffer (2000) argued that a convenient

Internet shop provides a short response time and minimizes customer effort. According

to figures from the Central Buro of Statistics (2011), the number of two-income couples in

the Netherlands is growing. The number of couples in the age category 15–65 with two

working partners has grown from 51 percent in 2005 to 57 percent in 2009. In absolute

figures, more than 2 million households are involved. They purchase their groceries at a

supermarket which is convenient and in a lot of cases convenience in this context counts

more than quality. According to the results of a research performed by Hoofdbedrijfschap

Detailhandel (HBD) en de Koninklijke Nederlandse Slagersorganisatie (KNS) (2008), for

special occasions, like Christmas, consumers pay more attention to the products they buy

and take the time to visit the traditional bakery, greengrocery and butcher.

Taste As mentioned previously, one of the results from the research done by Glanz et al. (1998) was that the American consumers reported that taste is the most important influence on their food choices, followed by cost. Is taste of fresh food products like



bread, meat, fruit and vegetables considered the same when purchased at the supermarket or at a Fresh food retailer?

Price This shopping motive is related to the personal characteristic income. Steenhuis et al. (2011) stated that price is an important factor in food choice, especially for low-income consumers. Low-income consumers are significantly more conscious of value and price compared to higher-income consumers. Miller (2000) indicated that the virtual online stores allow vendors to save expenditure that e-tailers enable consumers to purchase at a lower price. Moreover, it is relatively facile for Internet buyers to make price comparisons via Internet at any time.

Internet Use The shopping motives (recreational or functional, for example) of individuals affect the decision whether to buy online or to buy in-store (Dijst, 2004; Li et al., 1999). Recreational shoppers are usually attracted more to `the real thing', whereas time-pressed functional shoppers are more inclined to shop via the Internet. Product characteristics also affect online shopping. Search goods, such as books and CDs, are more suited to be purchased via the Internet than experience goods, such as fresh vegetables (Lee, 2002; Vrechopoulos et al., 2001). According to Garrett & Parrott (2005) Internet has strongly influenced the lives of everyone in the recent years and has impacted behaviour of consumers. The use of Internet in daily lives will influence their motives whether to shop online or not. According to Lepkowska-White (2004) three types of consumers in regard to their shopping habits can be classified: the Online shoppers, i.e. those who purchase regularly online, the Online browsers, who mainly use the Internet as a source of information but prefer to conduct their transactions in traditional stores and the Hardcore offline shoppers comprised of the continuously diminishing group of individuals, who do not use the resources of the Internet either for information gathering or for shopping purposes. It depends which type of product consumers are shopping for; do you purchase it online or physically visit a shop? Zhou et al. (2004) emphasizes that consumer acceptance of online shopping may vary when shopping for different products. This is confirmed by the findings of Thirumalai & Sinha (2011) that highlight the significance of recognizing the differences in the customer purchase behaviour across product types in configuring the order fulfilment processes in electronic retailing.

As mentioned previously, a research done by Irvine et al., for an Australian research institute, (2011) on the rise of online retail, shows that fresh food is the product least considered to be bought online by the Australian consumers. Figures are shown in figure 7 below.

Figure 7 – What do you shop online? Australian Research Institute, The rise and rise of online retail (2011)

Male Female

DVDs & Music 84% 79%

Books 74% 83%

Electricals 79% 62%

Clothes & Shoes 52% 69%

Sports & Leisure Goods 54% 46%

Cosmetics & Perfume 41% 56%

Fresh Food 11% 14%



Does this mean there is no chance of success for online shops selling fresh food in the

Netherlands as well? The fact that the Netherlands are among the top 4 countries in the

EU for Internet shoppers and far above the EU average could be considered as an

indication to further investigate the attitude of the Dutch towards shopping fresh food

online. The quality of the online purchase process has been found to affect customers’

purchase decisions, satisfaction, and loyalty in electronic retailing (Zeithaml et al., 2002;

Wolfinbarger & Gilly, 2001). This could be a reason for the difference per country, but

certainly explains the difference between different online shop providers.

Motivations of consumers to engage in online shopping include both utilitarian and

hedonic dimensions. Hedonic dimensions result from sensations derived from the

experience of using products. Utilitarian dimensions derive from functions performed by

products (Voss, Spangenberg & Grohmann, 2003). According to the findings of Kim &

Easton (2011), online shopping behaviours affected by hedonic shopping motivation

affect pre-purchase browsing time and that the pre-purchase browsing time has a

positive relationship with online buying frequency. Their study also shows the positive

relationship between perceived credibility of product information and pre-purchase

online communication, and the positive relationship between perceived credibility of

product information and online buying frequency. Vazquez & Xu (2009) state that

depending on their shopping motivation or orientation, consumers show different

patterns. For example, utilitarian consumers—those with a specific goal, probably our

target group as they are shopping for food and daily utensils—directly seek the most

relevant information about a brand, a product, or a product category they are interested

in. Hedonic consumers—those who enjoy the act of shopping itself—tend to explore

websites as they would shop in a traditional shopping mall. These shoppers are seeking

exposure to various shopping stimulations. As such, they are more likely to make more

frequent, longer, and experiential visits to websites. In this research the focus group is the

utilitarian consumers; those shopping with a goal.

Ganesh et al. (2010) found results which reveal that there are more similarities than

differences among traditional and online store shoppers. Does this mean that traditional

food shoppers are willing to move to the online shopping, but they are just not offered

the possibility to do so for fresh food products?



As stated previously, the Netherlands is among the top 3 countries in Europe of Internet users and among the top 4 of online shoppers within Europe. This means more and more

people prefer the ‘clicks’-format above the ‘bricks’-format to place their orders. Consumers are only one click away from shopping their fresh food products on-line and get it delivered at home.

Figure 8 – Frequent e-shoppers by gender and age (2011) – source: www.cbs.nl

In figure 8 it is illustrated that compared to 2005, the largest increase in Internet use is observed among 25 to 44-year-old women, followed by men in the same age group. The largest relative growth was recorded among 65 to 74-year-old men followed by women in the

age category 45-64. Swaminathan et al. (1999) reported that male Internet buyers were more convenience oriented and less motivated by social interaction than female Internet buyers. Alreck & Settle (2002) indicated that women have more positive attitudes towards offline shopping, whereas, men prefer shopping via Internet (Alreck & Settle, 2002). Does this count for the customers shopping for their fresh food necessities in the Netherlands as well? According to Maes, Guttman & Moukas (1999) there are two sub-processes; the decision making sub-process and the transaction sub-process. The latter consists of the purchase of the product or service, the delivery and the evaluation. These findings are visualised in figure 9 below from Thirumalai & Sinha (2011), which documents the findings from behavioural experiments using student subjects as to how customer purchase behaviour and customer expectations associated with online purchase vary across well-established product types (convenience, shopping, and specialty goods), and how this variation, affects customer value for customization across the three product types in the context of electronic retailing; (ii) Kumar & Benbasat (2006), which uses laboratory experiments with student subjects to assess the role of personalization features such as product recommendations and consumer reviews on the perceived usefulness and the social presence of a website; and (iii) Chellappa & Shivendu (2006) and Chellappa & Sin (2005), who address issues such as privacy concerns, trust building, customer value for customization, and customer willingness to participate in the customization efforts of an online retailer.



Figure 9 - Online Purchase Process (Thirumalai and Sinha (2011)

To make an online shop successful, it is very important to include certain aspects in the design. According to the research done by Aladwani (2006), it was shown that by giving attention to building a technically sound website with effective content and attractive design, an organization could bring in more consumers to its online business and convince them to make purchases.

The study of Lee et al. (2011) shows that it is very important to provide functional,

reliable and easy-to-use systems that enable enjoyable online purchase experiences.

Customers will be happy to repurchase products and services from an online store that

offers an excellent functional store front that is free of hick-ups and other constraints that

could frustrate potential customers. Lee’s study also concludes that ethical and relational

variables namely privacy, reputation and trust are very important factors to pay close

attention to. Chuang & Fan (2011) address the relative importance of system quality and

service quality in their effects on a consumer’s trust in online shopping, while information

quality is not. Their research also shows that trust in an online retailer is positively related

to consumers’ purchase intention. Trust takes a long time to build, can easily be

destroyed, and is hard to regain. Also, since breaking trust gives rise to distrust,

maintaining trust requires careful attention from management. Trust and quality go

together. If e-tailers want to have trust on a sustained basis, they must have quality on a

sustained basis as well. In the end, trust based on quality is the most durable condition

for building for company survival and success. The above mentioned characteristics of a

successful Internet shop, are all applicable for fresh food stores, they are just simply

hardly available on the current fresh food market.

According to Naseri & Elliott (2011), another important factor is living in a geographically remote area and factors that restrict consumers ’ participation and physical presence in the community such as disability and limited accesses to motor vehicles. These factors would reduce exposure to word-of-mouth and social signals, and as a result, are expected to have negative impacts on the adoption of online shopping. This is also confirmed by the research done by Farag et al. (2005) in which it is indicated that Internet use and online buying are still largely urban phenomena in the Netherlands, but that there is a trend towards diffusion to the weakly urbanised and rural areas. Not only the innovation



diffusion hypothesis, but also the efficiency hypothesis is confirmed by our findings. People living in a (very) strongly urbanised area have a higher likelihood of buying online, but people with low shop accessibility buy more often online. The analysis also shows that the support for the two hypotheses depends on the type of product. Airline tickets are still mainly bought in very strongly urbanised areas, whereas compact discs, videos, DVDs, and clothing are bought relatively more often in weakly urbanised areas. In conclusion, geography seems to matter for e-shopping.

Another important question is whether shops, currently offering offline shopping only, survive in the recent online shopping culture? What about the bricks-and-clicks format, which uses both traditional outlets and virtual storefronts when engaging in purchase behaviour, as discussed in Verhagen & Van Dolen (2009)? Results show that offline and online store perceptions directly influence online purchase intention. This could be the solution for the Fresh food retailers as well.

PWC in cooperation by Frost & Sullivan performed recently (July 2012) a research within Australia and New Zealand, investigating the Australian online shopping market and digital insights. The results from this study show that the Australian online shopping expenditure is predicted to be worth $26.9 billion by 2016, with a Compound Annual Growth Rate (CAGR) of 14.1%. This growth is likely to be stimulated by a number of factors including: the entry of more online retailers, an increasing number of manufacturers going direct to consumer, product and service expansion by current online retailers and pure plays, continual growth in consumers using mobile devices to browse and purchase products anywhere, any time and any device. The research also stated that the retail categories predicted to display the strongest growth over the next five years are the clothing, footwear, jewellery and fashion accessories. These are driven by the proliferation of specialist online stores and traditional bricks and mortar retailers improving their online offerings. However growing categories include Food & Groceries and Alcohol – indicating a change within the consumer online shopping habits, where common place tasks such as buying groceries are increasingly being transacted through digital channel use of social media by both consumers and retailers to drive brand awareness. Over the past year, online shopping has received significant mainstream media attention, particularly with regard to substantially lower pricing from international retailers representing a threat to local multi channel retailers. This has undoubtedly raised consumer awareness about online shopping locally and overseas. Retailers are also now giving more prominence to online channels through various marketing efforts, which is also likely to be contributing to consumer awareness and uptake. This will continue to drive future growth in this channel. The most important reasons for shopping online in Australia were found: Lower prices online than in a store (55%), convenience of shopping from home (avoid queues, crowds) (15%), more comprehensive product range/ I can purchase goods which I can't get at a physical store (15%), easier to locate product I am looking for (11%) and I can shop when physical stores are closed (2%).

Mark Zuckerberg, founder and CEO of Facebook, even stated in 2011: If I had to guess, social commerce is the next area to really blow-up (Knight 2011). More and more people are into Social Shopping; Social Media + Online Shopping. These might be the marketing channels for the Fresh food retailers in the Netherlands to bring their new service to peoples’ minds.



SECTOR ANALYSIS - EXISTING E-FOOD CONCEPTS IN THE NETHERLANDS

Currently there are already several concepts, with many different formats, offering the possibility to shop fresh food products online, in the Netherlands. A broad range of different concepts is offered; buy fresh food products directly from the farmer, supermarkets cooperating with local producers, an online ‘market’ connected with individual fresh food specialists or a subscription for a delivery of fresh food products, including recipes, on a weekly base. A sector analysis, investigating all different kind of services already available on the Dutch online food market has been done, in order to connect the findings of this research to the existing market at a later stage in this research process.

Graaggedaan – www.graaggedaan.nl

Graaggedaan is a website which offers a web shop for Fresh food retailers and an online marketplace for customers in the Netherlands looking for a Fresh food retailer with an online service in their region. Currently approximately 50 Fresh food retailers are associated to www.graaggedaan.nl. Customers select their region, select a Fresh food retailer, order their products online and get their groceries delivered at home or pick-it up from the Fresh food retailer directly. The Fresh food retailers pay Euro 250 per year for which they get a web shop at the platform, but also a link from their own website. www.graaggedaan.nl also takes care of the marketing of their online shop in the format of online marketing campaigns, flyers and a banner to be placed in the store itself. They charge 4,5% of the expenses for costs such as the URL and costs for the Ideal payment service. M. Lambooy, one of the founders of this concept explains in an interview on 29 October 2012 that he is convinced that the Dutch customer is ready to order their food online; however there seem to be 2 challenges for his business model. Firstly there is a gap in the computer skills of Fresh food retailers. The CRM system has been designed in a way that Fresh food retailers sign up for the service, then they can upload their own assortment with prices and pictures to the CRM and Lambooy only needs to activate their account. It seems however that they have underestimated the computer skills of the Fresh food retailers. Many of the web shops are not complete yet and therefore do not gain the traffic and orders as expected. At this point Lambooy and his companion are investing in attracting more Fresh food retailers and assist the retailers with the set-up and implementation of the web shops. The retailers offer both pick-up and delivery service once the order is placed. 80% of the on-line orders are picked-up by the customers in the store. Only 20% makes use of the delivery service. Lambooy and his companion highly recommends the retailers to use ‘fast-lanes’ with a message for the customers ‘bestellen is sneller – www.graaggedaan.nl’ to offer customers who pre-order online the benefit of no need to wait in the queue. However the retailers are not yet convinced on implementing a fast-lane, as they are worried for the reactions of their other customers.

HelloFresh – www.hellofresh.nl

HelloFresh, an originally English concept, delivers every week on Monday or Tuesday a box with recipes and all the necessary ingredients at home. No need to think about what you will be eating, this choice will be made for you, and no need to go to the supermarket anymore. HelloFresh ensures that you eat from a great variety and healthy products. The

http://www.graaggedaan.nl/




http://www.hellofresh.nl/



recipes, composed by professional nutrition specialists, are simple and ready within 30 minutes. HelloFresh delivers the Netherlands. The biggest investors of this concept are venture capitalists. HelloFresh distinguishes themselves from competitors by delivering the full package; not just the ingredients or some of the ingredients plus the recipes; but the full package; all ingredients plus the recipes. The Marketing Director, E. Boyes, wrote about HelloFresh’ social media strategy on Affiliates4U (2012). He stated that the food industry is perfectly suited for social media interaction; purchase decisions are significantly influenced by social referral. HelloFresh has utilised social media as a vehicle to enhance and grow all aspects of their customer experience. HelloFresh was among the first adopters of Face book’s new ‘Offers’ feature. In an interview with M. Frederiks, CEO of HelloFresh the Netherlands, in an interview on 29 October 2012, she explained that they have quadrupled their number of clients to more than 1,000 since the launch of their website. This rapid growth allowed them to benefit from economies of scale. HelloFresh is also a success in the UK, Germany, Austria, France and Australia. The goal for HelloFresh Netherlands is to expand to the Belgium and Luxemburg as well. In each country HelloFresh has its own production team; however they share the rather complicated ICT systems and knowledge based on experience. Interesting to see is that for example the French order much more boxes for 4-6 people (the entire family), as compared to the Dutch who mostly order boxes for 2 people. Recipes are also designed per country taken into account each country’s habits and needs. Frederiks also mentions that the biggest challenge is the rather complex logistic part of the service delivery. Products should be good quality, fresh and perfectly chilled at the time of delivery. Hello Fresh is establishing contracts with some large employers and gyms to cooperate with; the employer is happy that its employee lives a healthy lifestyle, the employee is happy that the box can be picked up from a convenient location. Some of their clients rather collect their box from a convenient location compared to get it delivered at home at a certain time. HelloFresh also considers offering a family box for the future, which includes more accessible recipes for families with younger kids. www.zinnerdinner.nl is a similar concept, offering a similar service, at a lower scale and at a higher price.

De Keurslager; Association of certified butchers in the Netherlands – www.keurslager.nl

The Keurslager association in the Netherlands is an overarching organisation for butchers in the Netherlands, offering, if meeting all the high professional standards, the opportunity for individual butchers to become a member and use the brand ‘Keurslager’ (a certified trademark for butchers). De Keurslager was voted best Fresh food specialist by the public in the ‘ING best retailer of the year’ award, in the category Fresh food specialist in 2009, 2010, and 2011 and is nominated for 2012. Based on requests from the members and the urgent need for food online, the association has designed an online web shop, which is available for their members. The association assists with the implementation and effectuates in this way a relative easy access for their members to the e-food market. Currently 22 Keurslagers are using the web shop. In 2007 the association of Keurslagers has founded the versplatform Nederland organisation (www.versplatformnederland.nl), which advises all fresh food retailers, not only butchers, in the Netherlands on marketing developments in the fast changing retail world. The consumers are more and more in search of a one-stop-shop, and with the consultancy of the versplatform Nederland, it is easier to combine forces between the Fresh food retailers and create a stronger position against the large supermarket chains. The versplatform Nederland has 1,700 members.

http://www.zinnerdinner.nl/

http://www.keurslager.nl/

http://www.versplatformnederland.nl/



The web shop option has been also expanded to retailers associated with the versplatform as well; 4 are using it.

Ko-Kalf – www.ko-kalf.nl

Ko-Kalf is a biological meat provider with farms in the Nature reserve ‘de Veluwe’. Ko-Kalf breeds its own meat, the race ‘Blonde d’Aquitaine, a highly qualified type of meat. It offers its clients to order the meat online via the web shop in packages of 5, 10 or 20 kilograms. Besides these standard packages Ko-Kalf also offers some specialties, like veal croquettes etc. All orders are shipped by mail directly from the farm to the consumers. Since Ko-Kalf keeps the chain from the animal till the consumer within their own management, it seems to overcome the biggest part of the challenge of logistics, which many of the food web shops have to deal with. www.meerdanvlees.nl is a large online web shop for meat products; they deliver their orders in a special developed Styrofoam box, which proves to keep the content chilled for 48 hours. Their biggest challenge is the logistics of the products from the producer to the web shop within a short time frame.

Landmarkt – www.landmarkt.nl

Landmarkt is a roof covered marketplace. They select the best products from local farmers and producers and sell them at Landmarkt. You buy fresh products directly from the producers on one central location. Many tastings are offered and there is also a restaurant and coffee bar featuring all their fresh and local products. It is all about the experience. Landmarkt is located in Amsterdam, currently not offering an online shop, however plans are ready to be launched later this year.

Ruud Maaz – online supermarket – www.ruudmaaz.nl

Ruud Maaz is an online supermarket offering fresh, local products. You can make your own product selection online, or you could choose for one of the standard ‘baskets’ filled with products for a household with 2-5 people sufficient for an entire week. Ruud Maaz tries to recycle all the packaging materials and tries to reduce the amount of trash we produce. Ruud Maaz delivers in Amsterdam and surroundings.

Another example of an online supermarket is www.smaak.nl; this company did however not succeed and paused its activities until further notice since April 2012, due to an unexpected withdrawal from a big investor, just after Ahold took over the 2nd biggest (non-food) web shop in the Netherlands bol.com. www.smaak.nl suffered big logistic challenges and was not able to keep the business at break-even. In their press release (19 April 2012) they refer to a recent investigation done by consultants of Ronald Berger to the purchase behaviour of 160.000 European households. From this research they conclude that parties with a strategic position within the Dutch retail industry yet have a rather passive and cautious attitude towards developing an online strategy. According to Frank van Oirschot, the founder and CEO of NFR, the company behind www.smaak.nl, this is surprising, since it is not the question if, but when online food will rise. He expects that the market share of online supermarkets will increase to more than 30% in the upcoming 10 years. This means that up to now the big players like Ahold have the optimal space to strengthen their leading position in the market.

http://www.ko-kalf.nl/

http://www.meerdanvlees.nl/

http://www.landmarkt.nl/

http://www.ruudmaaz.nl/

http://www.smaak.nl/





De Krat – www.dekrat.nl

De Krat (the Crate), also called ‘farmers’ delivery service’ offers the service to get a crate filled with biological, locally produced ingredients, delivered at the customers home. De Krat contains not-every-day ingredients and a booklet with recipes is downloadable from their website. Not all ingredients required for these recipes are included in the crate; therefore you still have to buy these ingredients from the supermarket or local food retailer. De Krat delivers in Amsterdam and surroundings. Similar concepts are Streekbox (only local products), Kistje vol smaak, de Groen Lekkerbek (started in 2006 with standard boxes, but has now changed to custom made boxes); customers can pick and chose) and Beebox (NRC Handelsblad, 27 October 2012).

Iceberg Web shop Hands – www.icebergwebshophands.com

Iceberg is an e-fulfilment company for food web shops. Iceberg takes care of storage, packaging, delivery and acceptance of goods for web shop owners. The owner M. Bongers, calls himself an e-food expert, and he explains that the biggest challenge for online food providers seems to be the logistics part; get the products from the supplier to the web shop distribution centre within a very short timeframe. The delivery chain for food products is completely different and much more complicated than the delivery chain for e.g. clothes. He has witnessed many companies failing this process, with a bankruptcy as a result. Bongers expects the Dutch food retail market to change more towards the markets in countries like France, Austria and Switzerland. Fresh food retailers and supermarkets will disappear from the city centre and move more towards the edge of the city / village. Large fresh food markets, all under one roof, might be part of this change as well. Perhaps a more luxury version of the SRV (SeRVice) wagon, a supermarket on wheels, might come back. The online world is a reflection of the real world. At this point in time there are many more food stores and clothes stores than any other type of store; that means in a couple of years this will be the same on the Internet. It is not the question if there is a market for online food; it is the question when it will take its enormous rise. At this moment the biggest challenge is the logistics part, but as soon as this has been established it will be a big step forward for online food shops, said Bongers in an interview on 28 October, 2012.

http://www.dekrat.nl/

http://www.icebergwebshophands.com/



CONCEPTUAL FRAMEWORK

Based on the above mentioned outcomes from the literature review and field research among food shoppers performed by consultancy firms in the Netherlands, in this research the demand of customers of fresh food for online shopping possibilities will be investigated. Both customers and non-customers of traditional food retail stores in the Netherlands have been asked for their shopping motives and their opinion on the possibility of having an online shop to purchase their fresh food products and get it delivered at home or collect it at any convenient time for them. Perhaps this research will be the first step to prevent Fresh food retailers from vanishing of the retail environment in the Netherlands.

To find the answer to the previously stated research question: What are the influences of

personal characteristics and shopping motives of customers in the Netherlands in their

decision making process on where to buy fresh food and what are the effects of an

online shop on these relationships? Based on the extensive literature review done, the

following research model appears:

The independent variables are personal characteristics and shopping motives of the

customer in the Netherlands when buying fresh food. The dependent variable is the

choice for the type of store to buy their fresh food; supermarket or Fresh food retailer.

The variable Internet use has been used as control variable, since it is expected that this

variable does have an effect on the influence of an online shop. All these factors will

determine whether the availability of an online shop for the Fresh food retailers has an

effect; in other words, whether this will increase the number of people that will buy their

fresh food products from the Fresh food retailers instead of the supermarket. Based on

the above the following hypotheses for this research have been set:



Hypothesis 1: The choice for the type of shop, supermarket or Fresh food retailer, to buy fresh food products for customers in the Netherlands is influenced by;

- age (H1a) - gender (H1b) - education (H1c) - income (H1d)

Hypothesis 2: The choice for the type of shop, supermarket or Fresh food retailer, to buy

fresh food products for customers in the Netherlands is influenced by;

- convenience (distance and time) (H2a) - price(H2b) - taste (H2c)

Hypothesis 3: The availability of an online shop for Fresh food retailers has a positive

significant effect on the preference for the Fresh food retailer, for customers in the

Netherlands.

After incorporation of these hypotheses the conceptual model is as follows:



DATA AND METHODOLOGY

METHOD

Based on the extensive literature review a research method has been established to

explore the influence of the availability of an online shop on the choice for type of shop,

supermarket or Fresh food retailer, for fresh food of inhabitants of the Netherlands.

Research can be conducted either deductive or inductive (Saunders, Lewis, & Thornhill,

2009). Both terminologies are explained as follows: Deductive research: the testing of a

theoretical proposition by the employment of a research strategy specifically designed for

the purpose of its testing. Inductive research: involves the development of a theory as a

result of the observation of empirical data. Based on these definitions this research can

be considered a deductive approach and primary data have been collected.

VARIABLES

Based on the established conceptual model the following variables have been measured:

Independent variables: - Personal Characteristics (age, gender, education & income)

- Shopping Motives (convenience, taste, price, online shop

available)

Dependent variables: - Type of store for fresh food Fresh food retailer (i.e.

bakery, butcher and greengrocery) or supermarket

Control variable: - Internet Use

This is summarized in figure 10 below:

Figure 10 – Summary of research variables

Independent Variables Dependent Variable

Personal Characteristics Shopping Motives Type of store for fresh food

Age Education Convenience Taste Fresh food retailer

Gender Income Price Supermarket

Online shop for Fresh food retailers Control Variable

Internet Use

SAMPLE

The research population is a blended group of consumers buying their fresh food

products either at the Fresh food retailers or at the supermarket. It is a blended sample

consisting of students, people with and without a job, entrepreneurs and employed by a

company, housewives, retirees, high and low educated people, from different age groups



and gender. This could be considered a realistic reproduction of the consumption society

in the Netherlands.

The snowballing sampling method has been used to achieve the objective of targeting a

population of approximately three hundred (P=300) inhabitants of the Netherlands. The

snowballing sampling method is a widely used method in Internet-based research. A

response rate of at least 45% was expected, based on the average outcome of 55.7 with a

standard deviation of 19.7 for the study conducted by Baruch (1999).

Taken into account a 95% confidence level (5% margin of error); the expected sample size

was 135.

The survey has been distributed on-line among a personal network counting on the

snowball effect. The researcher has approached 60 direct contacts, requested them to

forward the link to the online survey among their networks, to gain a sample with the

widest variety possible. When distributing the online survey the main goal was reaching

out to a broad public, which is diverse and measurable on several personal characteristics

and shopping motives. The total sample size is 173 (S=173) inhabitants of the

Netherlands, residential in the provinces as shown in figure 12 in appendix 1. It is

important that the sample is well represented spread over the different provinces, since

according to the research of Farag et al. (2005) the location of where people live

influences their online shopping behaviour.

The average age of the sample is 37,59 years old and most of them have finished an HBO

(47%) or WO (35%) education and belong to the income category of Euro 3,001- 4,500 net

per month (32%). If you compare this to the Netherlands, the mode income is Euro 1,800

net, per month. The average number of adults is 1,87 and 0,73 children per household.

DATA COLLECTION

The survey consisted of 31 questions of different types; 15 multiple choice questions, 4

open questions and 12 statements which had to be rated by a five-point-Likert-style scale

and semantic differential rating scale which is often used in consumer research to

determine underlying attitudes (Saunders, Lewis, & Thornhill, 2009).

The five-point-Likert-scale measured from:

1 strongly disagree, 2 disagree, 3 neutral, 4 agree to 5 strongly agree

As well as

1 no, never, 2 seldom, 3 sometimes, 4 mostly, 5 yes, always

Previous researchers like Lin & Sun (2009) and Wang et al. (2009) are some of the studies

which have found this scale to be an effective measure.



All questions were compulsory, except for the last question which offered the respondent

the possibility to enter any feedback or remarks.

Before the official survey had been sent out; a pilot test was conducted. A pilot test is a

small-scale study to test the survey; to minimize the likelihood of respondents having

problems in answering the questions and of data recording problems as well as to allow

some assessment of the questions’ validity and reliability of the data that will be collected

(Saunders, Lewis & Thornhill, 2009). The pilot survey was sent to five samples:

- One person with a high academic background and experience with surveys for final theses (Masters degree);

- One person with high educational background (at least a Bachelor degree);

- One person with low educational background (no degree);

- One person with the age above 50 years (retiree);

- One person with the age below 30 years (student)

Based on the feedback received from these five samples, the initial survey had been

adjusted and prepared for final distribution.

One week before the actual survey was sent out, a personal e-mail, with the advance

notice, the announcement and purpose of the survey and the request for the assistance,

was sent out by personal e-mail to 60 personal connections of the researcher. This

procedure was followed since according to Duncan (1979); Harvey (1987); Heberlein &

Baumgartner (1978); Linsky (1975); Martin, Duncan, Powers, & Sawyer (1989) and

Nowack (1990), higher response rates are associated with sending an advance notice to

subjects.

One week after the advance notice was sent out, a personal e-mail with the link to the

online survey (set-up in Google docs), stating the purpose and content of the research,

the time it would cost to complete the survey (5 minutes), and the request to complete

the survey and forward it to as many people as possible, living in the Netherlands, within

their network, the survey was officially open.

One week after the survey had been distributed among the personal contacts of the

researcher, a follow up e-mail was sent out to thank everyone for completing the survey

so far and for those who did not yet completed a kind reminder to do so. Higher response

rates are also associated with follow-up reminders to respond according to many

different researchers (Duncan, 1979; Harvey, 1987; Heberlein & Baumgartner, 1978;

Kanuk & Berenson, 1975; Linsky, 1975; Salant & Dillman, 1994).

The respondents stayed anonymous; since the contact details of participants will not add

any value to the results and are therefore not required for the research. Yammarino

(1991) has shared the thought that anonymity affects response rates associated with



increases of two percentage points over conditions that identified subjects in marketing

and public opinion measurement. Yammarino (1991) also suggested offering an incentive

to one of the respondents, since meta-analyses suggest that monetary incentives can be

associated with markedly higher response rates, however since this research was

executed on an anonymous base, it is impossible to offer such an incentive.

The date the on-line survey remained open for completion was two weeks after it has

been distributed.

The first questions were questioning personal characteristic details, to investigate the

backgrounds of our survey participants and possibly determine any differences between

Fresh food retailer customers and supermarket customers.

The second part of the survey contained questions to determine the Internet use of the

individual. The variable Internet Use had been considered the control variable in this

research.

The section on Internet Use of respondents was followed by the third part which focused

on the shopping motives of customers on why they do their grocery shopping at certain

types of shops. Samples of questions are: Select the answer that is most applicable to you:

The final part of the survey focused on the influence of the availability of an online shop for

fresh food products on the relationship between personal characteristics and shopping

motives on the choice for type of shop to buy fresh food in the Netherlands.

DATA ANALYSIS

Both categorical and numerical data have been collected with the previously described

online survey. After all data were received, a coding scheme has been developed.

Firstly the mean, standard deviation, minimum and maximum for the continuous variables

have been calculated.

Secondly, the data collected have been assessed by several tests both the continuous and

categorical data, which will be explained below:

Pearson’s Correlation Test

The correlation tests are assessed to describe the strength and direction of the linear

relationship between two variables. The outcomes of these tests have been used to answer

the hypotheses 1 and 2 set for this research.



Multiple Regression Test

A multiple regression test, to explore the predictive ability of a number of independent

variables (personal characteristics and shopping motives) on the dependent variable

(choice for type of shop; Fresh food retailer or supermarket).

Age

Sex

Education

Income

Convenience

Price

Taste

RESULTS

In this chapter the data of the research are analyzed. The findings of the online

questionnaires held are examined. All hypotheses are tested and analyzed.

The total sample consists of 173 valuable respondents. All questions were compulsory,

except for the last question which offered the respondent the possibility to enter any

feedback or remarks.

After all results were analysed, these were reflected with some of the owners /

representatives of the concepts as specified in the existing concepts of online fresh food in

the Netherlands section at the end of the literature review chapter. Their insights have

been taken into account in the managerial implications section in the Conclusions chapter

at the end of this research.

DESCRIPTIVE STATISTICS

Personal Characteristics

First looking at the descriptive statistics, the following data have been found:

Analysing the number of males and females we can conclude that 55 males and 118

females participated in the survey. This is a fair distribution compared to the findings by

the Familiekenniscentrum (2011), stating that in the Netherlands the women are more

involved in the purchase of grocery shopping.

Looking at age, the youngest person participating in this research was 19 years old, the

eldest 78 years old. The majority was between 26 and 35 years old. The average level of

education is HBO (Bachelor WO). The majority, 50% of the respondents, are full-time

employed. 22% is part-time employed and 13% is self employed. Besides these working

people, 4% of the sample is a full-time student, and 4% is retired. 7% are unemployed of

Choice of shop

Choice of shop



which 2 are housewives. The majority earns between Euro 3.001 and Euro 4.500 net, per

month, per household. All different categories are specified in the appendix 2 -

descriptives.

Shopping Motives

The first shopping motive we have considered is convenience. We have touched on this

variable in several ways within the online survey.

The majority of the respondents are living on less than 2 km from the closest supermarket,

bakery, butcher and greengrocery. After that the following statement was provided to the

respondents: ‘There are no Fresh food retailers in my shopping area’. They answered

according to a 5-Point-Likert-Scale; the majority answered ‘Totally Disagree’.

The length of the queues at the shops play a big role in the decision making process for the

choice of shop if you consider convenience. Respondents were asked whether they found

the queues at the Fresh food retailers in general longer then at the supermarket. Most of

them disagreed. The respondents were also asked whether they were in the understanding

that it ‘takes too much time to visit the Fresh food retailers’, besides their visit to the

supermarket. The majority agreed with this statement. The other shopping motives tested

in this research are Price and Taste. Do respondents feel that the prices at the Fresh food

retailers are higher compared to the supermarket? And do they find the fresh food

products sold at the Fresh food retailers more tasteful then at the supermarket? The

majority agreed with both these statements. The price image of the Fresh food retailers is

expensive, but on the other hand are the products they sell more tasteful.

Internet Use

The variable Internet Use of the respondents has been considered as control variable, since

it is assumed that the regularity respondents have with the use of Internet will influence

their preference for an online shop for fresh food products. This variable has been

investigated with the help of several questions touching upon different parts of the

variable Internet Use.

86% of the respondents has access to a computer with Internet on their workplace, 3% has

not. 46% of the sample says they use Internet less than one hour per day. 47% states using

Internet one to three hours per day. Only 7% uses it more than 3 hours per day. This

question referred to Internet Use for private purposes only. The use of social media has

also been investigated among the respondents. Only 13 respondents do not have one

single social media account. The remaining 163 have at least 1 of the accounts, such as

Face book, LinkedIn, Twitter or Hyves.

In the questionnaire respondents were also asked which type of products they purchased

online in the last 6 months. Several different categories were provided, of which more than



one option could be selected. The items most purchased are Travel (airfares and hotels),

Clothing, shoes & accessories; the least purchased was Food & Beverages.

If we compare these results to the results of the research done by the Australian Institute

on the rise of online shopping within Australia, it is interesting to see that also in the

Netherlands the food category can be found among the bottom of the list. DVDs, music and

books are among the top 3 just like in Australia. The Dutch are obviously more used to

purchase travel tickets and accommodation and clothing online then the Australians.

If we look at the online shopping behaviour respondents were also asked whether they

purchase the following items online. They answered that they hardly ever buy groceries

and meals online. Mostly they buy books, clothes etc. The answers to these questions are

consistent with the items purchased online which they could select from the list.

Respondents were also asked whether they bought all their groceries at the Supermarket

or at the Fresh food retailers (like bread at the bakery, meat at the butcher and vegetables

and fruit at the greengrocery or market). The majority answered that they seldom or

sometimes buy their fresh food products at the Fresh food retailer. The majority mostly

visits a supermarket to buy all their groceries, including fresh food products. Based on

these results, it would be interesting to see whether the respondents that say seldom or

sometimes shop at the Fresh food retailers, will be influenced by the availability of an

online shop for the Fresh food retailers.

The last questions of the survey were related to the availability of an online shop for the

Fresh food retailers. The respondents were asked whether they would order their fresh

food products online if this service was provided by the Fresh food retailers at no extra

costs and at extra costs (5-10% of the total amount spent). The answers could be

summarized as follows: 37% of the respondents would consider ordering their fresh food

products if the online service was offered at NO extra costs. This percentage nearly halved

to 20% as soon as the service was offered AT extra costs (5-10% of the amount spent). It

would be interesting to see if the respondents who answered ‘yes’ to these questions were

already purchasing most of their groceries at the Fresh food retailers, or if their shop

choice will be influenced by the availability of the online shop.

STATISTICAL TESTS

In this part, the statistical tests used in this research are explained. The hypotheses 1 and 2 are tested with a correlation, multiple regression and chi-square analysis. The effect of the availability of an online shop on the choice for shop has been analyzed by checking whether the effect is significant and positively related.

Pearson’s Correlation Test

The Pearson’s correlation test can be used to find out whether there is a positive

relationship between two random variables. Firstly the scores of the respondents will be



ordered and after that the difference in order per respondent on both variables will be

calculated; this is defined in the height of the correlation. In this research the dependent

variable ‘choice for shop’ and the independent variables age, gender, education, income,

convenience, taste and price are measured. The coefficient r can vary in value between -1

and 1 by which -1 and 1 are perfectly negative and positive relations and indicate the

strength and direction of the relationship between this two variables. Based on Cohen

(1988) r=.10-.29 indicates a small correlation, r=.30-.49 indicates a medium correlation and

r=.50-1.0 indicates a large correlation. If a value is negative this indicates a correlation in a

different direction. Since the sample size is large (N=100+), r= .2 may reach statistical

significance according to Pallant (2010).

The table 3.1 in the appendix shows that some of the Personal Characteristics variables

relate to the choice of store to buy fresh food products; supermarket or Fresh food retailer.

By squaring the r-value, r², the coefficient of determination can be calculated. This explains the % of variance both variables are sharing. The most significant findings are outlined below:

- The older people get, the more they prefer shopping at the Fresh food retailer (r=.286, p=.000, r²= 8%) small positive correlation

- Men go less to the supermarket (r= -.207, p=.006, r²= 4%) small negative correlation

- Women rather shop at the supermarket (r=.207, p=.006, r²= 4%) small positive correlation

- People with a higher income go less to the supermarket (r= - .228, p=.003, r²= 5%) Small negative correlation

In table 3.2 in the appendix shows that some of the Shopping Motives, variables related to

convenience, also relate to the choice of store to buy fresh food products; supermarket or

Fresh food retailer.

The most significant findings are outlined below: - The distance from home to the supermarket and Fresh food retailers is not

significantly related to the preference of shop - If people shop at times that the Fresh food retailer is closed they prefer to shop at

the supermarket (r=.154, p=.043, r²=2%) small positive correlation - If people think queues at the Fresh food retailer are long, they prefer to shop at

the supermarket (r=.129, p=.090, r²=1%) small positive correlation - Because people think it costs them too much time to visit the Fresh food retailers,

they shop more at the supermarket (r=.390**, p=.000, r²=15%) medium positive correlation

- Because people think it costs them too much time to visit the Fresh food retailers, they shop less at the Fresh food retailers (r= -.339**, p=.000, r²=11%) medium negative correlation

- Because people think it is not handy to visit the Fresh food retailers, they prefer shopping at the supermarket (r=.261**, p=.001, r²=7%) small positive correlation



- People shop more at the supermarket, because they think there are no Fresh food retailers located in their shopping area (r=.144, r=.059, r²=2%) small positive correlation

In table 3.3 in the appendix, the correlation between the Shopping Motives, variables

related to price and taste, also correlate with the choice of store to buy fresh food

products; supermarket or Fresh food retailer.

The most significant findings are outlined below: - Because people think the Fresh food retailers are expensive, they prefer shopping

at the supermarket (r=.302, p=.000, r²=9%) medium positive correlation - Because people think the Fresh food retailers are expensive, they shop less at the

Fresh food retailers (r= -.236, p=.002, r²=6%) small positive correlation - People shop less at the supermarket if they think the products at the Fresh food

retailers is more tasteful (r= -.141, p=.064, r²=2%) small negative correlation

Regression Analysis

Regression analysis is a multi correlation technique to analyze the relation between a dependent variable and one or more independent variables. With this technique it is possible to predict the value of a variable based on the value of another variable. There is one exception, nominal variables that are dichotomous (two mutual exclusive or contradictory categories). Regression analysis estimates the direct effect of the independent variables on the dependent variables. The formula for regression analysis is always:

In this research the standard multiple regression analysis is used. This test tells us how much variance in the dependent variable could be explained by the group of independent variables (e.g. personal characteristics and shopping motives as groups). In this research tests for independent samples and a confidence level of 95% (α= 0.05) are used. According to Tabachnick and Fidell (2007) a requirement for the standard multiple regressions are a minimum sample size. The formula set by them is N > 50 + 8m (in which m is the number of independent variables). For the personal characteristics test m = 4, for the shopping motives m = 3. With the sample size of 173 it is safe to apply the standard multiple regression. The results of the standard multiple regression analysis is shown in the tables 3.4 – 3.7 in the appendix, specified by Personal Characteristics and Shopping Motives. The latter is separated into convenience – distance, -time, -price and –time. The Beta for Personal Characteristic - Age is the largest, which means that this variable makes the strongest unique contribution to explaining the dependent variable (choice for type of store), when the variance explained by all other variables in the model is controlled for. Looking at the significances, it shows that Personal Characteristic - Gender is the only independent variable making a statistically significant unique contribution to the prediction of the dependent variable (choice for type of store).



There is also no multicollinearity, since the correlation of the independent variables is never 9 or above. This is confirmed by the values of Tolerance and VIF which are respectively not less than .10 and well below the cut-off of 10 in the test run for the ‘Personal Characteristics’ group. Looking at the significances in the 3.4 in the appendix, on Convenience - distance with variables on distances from home to the shop (supermarket or Fresh food retailer); it shows that none of these are making a significantly unique contribution to the prediction of the dependent variable (choice for type of store). The Beta for ‘Distance home to bakery’ is the largest, which means that this variable makes the strongest unique contribution to explaining the dependent variable (choice for type of store), when the variance explained by all other variables in the model is controlled for. In table 3.5 in the appendix are variables related to Convenience – time displayed. The Beta for ‘Cost me too much time to visit FFR’ is the largest, which means that this variable makes the strongest unique contribution to explaining the dependent variable (choice for type of store), when the variance explained by all other variables in the model is controlled for. Looking at the significances, it shows that ‘Cost me too much time to visit FFR’ and ‘There are no FFR in my shopping area’, are the only independent variables making statistically significant unique contributions to the prediction of the dependent variable (choice for type of store). Looking at the significances in the tables 4.6 – 4.7, it shows very clearly that the price image of Fresh food retailers does significantly influence the decision on where to buy fresh food products for customers in the Netherlands. It is also clear from the results that in case people think the products from the Fresh food retailers are more tasteful, this significantly influences the decision on where to buy fresh food products for customers in the Netherlands. In all the above findings, there is no multicollinearity, since the correlation of the independent variables is never 9 or above. This is confirmed by the values of Tolerance and VIF which are respectively not less than .10 and well below the cut-off of 10 in the test run for the ‘Shopping Motives’ group. Finally, the last part of the research question should be answered. What will be the influence of the availability of an online shop for Fresh food retailers? In other words does the availability of an online shop for the Fresh food retailers change the choice of shop for the people who currently shop at the supermarket (in the shop and online)? The outcomes of this regression analysis have been used to answer hypotheses 3 set for this research. Looking at the significances in the tables 3.9 – 3.10 in the appendix, it shows that the availability of an online shop (with and without the need to pay extra for this service) does not make any significant difference for the people who currently shop in at the supermarkets. The availability of an online shop will not make them move from shopping at the supermarkets toward the online Fresh food retailers. The results in tables 3.11 – 3.12 in the appendix show that the availability of an online shop (with and without the need to pay extra for this service) does not make any difference for the people who currently shop in at the Fresh food retailers. The availability



of an online shop will not make them move from shopping physically at the Fresh food retailers towards their online shop. Investigating the interest in an online shop for Fresh food retailers, for those who already order their groceries via the online supermarket, show in tables 3.13 – 3.14 in the appendix clearly that the availability of an online shop (with and without the need to pay extra for this service) will attract the people currently ordering their groceries from the online shops of the supermarkets to the Fresh food retailers’ online shop. Examining the Betas for both, β=.333 and β=.414, which are rather high, it can be concluded that these variables both make a strong unique contribution to explaining the dependent variable (using the availability of an online shop for the Fresh food retailers), when the variance explained by all other variables in the model is controlled for. In all the above findings, there is no multicollinearity, since the correlation of the independent variables is never 9 or above. This is confirmed by the values of Tolerance and VIF which are respectively not less than .10 and well below the cut-off of 10 in the test run for the ‘online shop available’ group.

HYPOTHESES TESTING

In order to test the hypotheses the standard multiple regression analysis is conducted. Each hypothesis has been tested and explained below: H1a: The choice for the type of shop, supermarket or Fresh food retailer, to buy fresh food products for customers in the Netherlands is influenced by age The regression analysis of age shows an r² of 0.082 (F= .060, P= .107), which means that 8,2% of the variances are declared by the model. The results show that the older people get, this positively relates shopping at the Fresh food retailer. Therefore hypothesis 1a is supported, but not significant. H1b: The choice for the type of shop, supermarket or Fresh food retailer, to buy fresh food products for customers in the Netherlands is influenced by gender The regression analysis of gender shows an r² of 0.082 (F= .060, P= .037), which means that 8,2% of the variances are declared by the model. The results show that gender positively relates to choice of shop (e.g. Fresh food retailer). Therefore hypothesis 1b is supported, and significant. H1c: The choice for the type of shop, supermarket or Fresh food retailer, to buy fresh food products for customers in the Netherlands is influenced by education The regression analysis of education shows an r² of 0.082 (F= .060, P= .594), which means that 8,2% of the variances are declared by the model. The results show that the higher people are educated, the more they prefer to shop at the Fresh food retailers. Therefore hypothesis 1c is supported, however far from significant.



H1d: The choice for the type of shop, supermarket or Fresh food retailer, to buy fresh food products for customers in the Netherlands is influenced by income The regression analysis of income shows an r² of 0.082 (F= .060, P= .115), which means that 8,2% of the variances are declared by the model. The results show that the higher the income, the more they prefer to shop at the Fresh food retailers. Therefore hypothesis 1d is supported, however not significant.

H2a: The choice for the type of shop, supermarket or Fresh food retailer, to buy fresh food products for customers in the Netherlands is influenced by convenience (distance and time) The variable convenience is built up from several independent variables (distance and time), which will be discussed individually below: The regression analysis of distance from home to the supermarket, bakery, butcher and greengrocery shows an r² of 0.335 (F= .290, and respectively Psupermarket= .075, PBakery=.174, PButcher=.228 & PGreengrocery=.454), which means that 33,5% of the variances are declared by the model. None of these findings are significant. The regression analysis of ‘Costs me too much time to visit Fresh food retailers’ and ‘There are no Fresh food retailers in my shopping area’ show an r² of 0.201 (F= .177, and respectively P= .000 and P=.004), which means that 20,1% of the variances are declared by the model. The results show that if people think it costs too much time to visit the Fresh food retailers, or that they are not located in their shopping area, they prefer to shop at the supermarket. These findings are significant. H2b: The choice for the type of shop, supermarket or Fresh food retailer, to buy fresh food products for customers in the Netherlands is influenced by price The regression analysis of price shows an r² of 0.107 (F= .102, P= .000), which means that nearly 11% of the variances are declared by the model. The results show that if people think the price image of the Fresh food retailers is too expensive, the more they prefer to shop at the Supermarket. Therefore hypothesis 2b is supported and significant. H2c: The choice for the type of shop, supermarket or Fresh food retailer, to buy fresh food products for customers in the Netherlands is influenced by taste The regression analysis of taste shows an r² of 0.054 (F= .048, P= .002), which means that 5% of the variances are declared by the model. The results show that if people think the products from the Fresh food retailers are more tasteful, the more they prefer to shop at the Fresh food retailers. Therefore hypothesis 2c is supported and significant. H3: The availability of an online shop for Fresh food retailers has a positive significant effect on the preference for the Fresh food retailer, for customers in the Netherlands.



To answer this hypothesis 3 different groups have been investigated; people who currently shop at the supermarket, people who currently shop at the Fresh food retailers and people who currently order their groceries online via the online shop of the supermarkets. For the first two groups, no significant results have been found, however for the latter, those who currently order their groceries online from the online shop of the supermarkets, would move towards the online shop of the Fresh food retailers, should this service become available (this counts for both with and without an extra charge for the service). The regression analysis of ‘online shoppers without an extra cost’ shows an r² of 0.111 (F= .106, P= .000), which means that 11% of the variances are declared by the model. The regression analysis of ‘online shoppers with an extra cost’ shows an r² of 0.171 (F= .167, P= .000), which means that 17% of the variances are declared by the model. Therefore hypothesis 3 is supported and significant for the supermarket customers who currently shop online. After having analyzed the results, this could be summarised as follows: looking at the personal characteristics, we could conclude that the majority of the sample is female, between 26-35 years old, high educated (Bachelor/Masters), with an average income above the modal income. These personal characteristics have to be taken into account when analysing the shopping motives of the sample used for this research. The results show that elderly and higher educated people are more often shopping at the Fresh food retailers. Gender does influence the choice of shop; previous research shows that women are more conscious about healthy food, however from this research women shop less at the Fresh food retailer compared to men. Distance from home to the shop and the possibility of queues at the shop do not influence the choice for type of shop, supermarket or Fresh food retailer, however the idea that it will cost too much time to go to both the supermarket and one or more Fresh food retailers and the fact that this is not handy, have a stronger effect in the decision making process of the customers shopping for fresh food in the Netherlands. The Fresh food retailers have the image of being more expensive then the supermarket; however they also have the image of selling more tasteful products. In the end convenience is rated more important compared to taste. The majority purchases their fresh food products at the supermarket, partly motivated by the factor convenience. It is important to take into account the Internet use of this sample as well. The majority has at least one social media account and is used to shop online. The most popular products that are sold online are travel-related, clothing, accessories, music and DVD’s. Fresh food is the least popular product to be purchased via an online shop. When offering our sample the possibility to make use of an online fresh food store, nearly 40% is interested as long as there are no additional costs associated. As soon as an amount for this online service has to be paid, only 20% is interested. The latter consists mainly of those already using an online service of a supermarket.



CONCLUSIONS

This final chapter discusses the conclusions of this research by giving an answer to the research question. The theoretical and managerial implications will be discussed as well as the limitations and recommendations for future research. On the one hand the Dutch are among the top 3 of Internet users and top 4 of Internet shoppers within the European Union. Internet shopping is a rapidly growing phenomenon worldwide; but why does hardly anyone shop their fresh food products online and get them delivered at home or at another convenient place for collection? On the other hand, the number of Fresh food retailers, like the bakery, butcher and greengrocery, in the Netherlands are disappearing from the streetscape. From the literature it can be concluded that there are different factors influencing peoples decision on where to buy their fresh food products, at the supermarket or at the Fresh food retailers; not only personal characteristics, like age, gender, education and income, but also shopping motives like convenience, price, taste and internet use play a big role in this decision making process. This study has aimed to contribute to the existing literature on online shopping, specifically on shopping fresh food products online. The results give more insight in the decision making process of customers in the Netherlands on where to buy their fresh food products. Besides contributing to the existing literature, another goal of this study is to provide relevant results and recommendations for Fresh food retailers running their store and investigating new innovative solutions to survive this changing market environment. The product characteristics are important for consumers to decide whether they are suitable to be purchased online or not. Some researchers claim that food is an experience good, less suitable to be sold online. From the results of this study it could be inferred that the Dutch in general are using the Internet and especially online shopping a lot, however the only product category that is not popular, similar to findings from an Australian research, are fresh food products. Based on previous findings, women and elderly are more health conscious in their food choices, the same for high educated people. From our results elderly and high educated prefer to buy their fresh food products at the Fresh food retailers; however women prefer to buy it at the supermarkets. These days people are busy, they try to save time and money. Based on the results from this study, in the opinion of the Dutch consumers, one way to save money and time is to visit the supermarket, instead of visiting both the Fresh food retailers and supermarket. According to the respondents it costs too much time to visit the Fresh food retailers besides visiting the supermarket and on top of that in some cases there are no Fresh food retailers located nearby the supermarket, which will only become worse if the trend in number of Fresh food retailers continues to decrease. On the other hand Fresh food retailers do have the image that the products they sell have more taste compared to the supermarket; however in busy times convenience seems to play a bigger role in the consumers’ decision making process.



Most of the respondents have at least one social media account and purchase on regular base products online. The most popular products are travel (tickets and accommodation), clothing and music. The least popular are food products. What if the Fresh food retailers offer an online shop to order your fresh food products from one site and get them delivered at home at a convenient time for the customer? Two options have been investigated; an online shop at no extra cost for the customer and at a small fee (5-10% of the amount spent) for this extra service (including delivery at home The results show that people would consider to use this service), twice as much if the service is offered at no extra cost, however the results are only significant for those customers already shopping their groceries online at the online shop offered by the supermarket.



HYPOTHESES

In order to test the hypotheses, a regression analysis has been conducted. The hypotheses are tested for both personal characteristics and shopping motives of customers in the Netherlands. An overview of these results is shown in the table below:

Figure 13) Overview of hypotheses and results

H1a) The choice for the type of shop, supermarket or fresh food retailer, to buy fresh food products for customers in the Netherlands is influenced by age

Not significant

H1b) The choice for the type of shop, supermarket or fresh food retailer, to buy fresh food products for customers in the Netherlands is influenced by gender

Supported and significant

H1c) The choice for the type of shop, supermarket or fresh food retailer, to buy fresh food products for customers in the Netherlands is influenced by education

Not significant

H1d) The choice for the type of shop, supermarket or fresh food retailer, to buy fresh food products for customers in the Netherlands is influenced by income

Not significant

H2a) The choice for the type of shop, supermarket or Fresh food retailer, to buy fresh food products for customers in the Netherlands is influenced by convenience (distance and time)

Convenience (distance) = not significant Convenience ( time) = Supported and significant

H2b) The choice for the type of shop, supermarket or Fresh food retailer, to buy fresh food products for customers in the Netherlands is influenced by price


H2c) The choice for the type of shop, supermarket or Fresh food retailer, to buy fresh food products for customers in the Netherlands is influenced by taste


H3) The availability of an online shop for Fresh food retailers has a positive significant effect on the preference for the Fresh food retailer, for customers in the Netherlands.

Supported and significant for those already shopping food online



THEORETICAL IMPLICATIONS

This research has contributed to the current literature on online shopping, specifically for the product category fresh food. The logistics for a web shop selling food is much more complex than any other web shop; mainly caused by the tight timeframe and the quality of the products. In practice food is less suitable for online shopping; this seems also the vision of the customer. Based on this research, the Dutch consumers are not yet ready to buy their experience products, like fresh food, online, however according to players in the market we are only just at the start of the e-food era. According to previous research done, women are more health conscious; therefore you would expect them to shop more often at Fresh food retailers. From this research the opposite is true; women are shopping more often at the supermarket, men visit the Fresh food retailers more regularly. Also from this research it has been proven that elderly buy more at the Fresh food retailers, which matches with the existing literature. Education influences the choice for shop; high educated people visit more often the Fresh food retailers. After having investigated the shopping motives of this sample; we can conclude that distance does not influence the choice of shop; time does have a significant impact though. If people are short in time, they rather shop at the supermarket. The food from the Fresh food retailers is considered more tasteful, but also more expensive compared to fresh food products from the supermarkets.

MANAGERIAL IMPLICATIONS

For the Fresh food retailers, this research has contributed to the fact that they could consider the investment of an online shop; however based on the outcomes of this research, at the current market, the mind-set of the customers is not there yet. It will be a big investment for the Fresh food retailers to set-up an online shop, but based on the results from this study, there might not be sufficient interest from the customers at this point. There seems also a problem on the Fresh food retailer side. Are they ready for an innovative change? A certain amount of marketing is required to bring the new service to the customers’ mind. At this stage only a relatively small proportion of the consumers currently shopping online, might consider ordering their fresh food products from the Fresh food retailer web shop. The availability of a web shop for Fresh food retailers would not change the choice of store for consumers currently shopping at the supermarket. Based on the findings of the sector analysis done in the e-food sector, there are two important factors to take into account when considering a web shop for Fresh food retailers. The most important factor is the challenge on the logistics side. All different concepts mention this problem. The logistics part of a web shop that sells food products is much more complicated than a web shop selling clothing. The full service providers like HelloFresh are successful. They anticipate more on the variable convenience, and distinguish themselves completely from the supermarkets and Fresh food retailers. They actually indirectly ‘steal’ customers from those food providers. It is about the full service; not only products, but also the nutrition advise and recipes, all delivered at your



doorstep. The platform Graaggedaan.nl offers an online platform for Fresh food retailers, however based on feedback of some, there is hardly any traffic to their websites via this platform. It seems that there is no demand for such a service yet among the Dutch customers. The association of Keurslagers offers an online web shop to its members since 2012. The overarching marketing and R&D of the association makes it possible to benefit from some economies of scale. At this point there are 25 participating butchers in the online web shop program offered by the Keurslager. Based on this relatively low number and the experience of the founder of the www.graaggedaan.nl concept, it could perhaps be concluded, that the retailer side is also not ready yet for such an innovative change. At least both the customers and retailers should be guided in this process.

LIMITATIONS

A limitation of this research could be the fact that the majority of the respondents are between 26 and 35 years old. Taken into account the expected general ageing of the Dutch this is not the perfect reproduction of the reality. On the other hand; this is the generation that will be the elderly of the future, raised with Internet and online shopping. Another limitation of this research is that the majority of the sample has a relatively high education and income. The mode salary in the Netherlands is Euro 1,800 net per month per household; however the mode salary of this research is higher, starting from Euro 3,100 net per month per household. This is also no perfect reproduction of the reality. A third limitation of this research is that not many details about the type of online shop offered have been included in the questionnaire.

FUTURE RESEARCH

This research has mainly focussed on the personal characteristics and shopping motives of Dutch consumers of the food industry. Future researchers should focus more on the different options of online shopping for fresh food, not only the supermarkets and the Fresh food retailers. As shown in the sector analysis, there are many different concepts available; the full service offered by HelloFresh seems to be successful. The challenge of the logistics part will still play a role in the success of such an online shop; perhaps more research could be done on this part of the service chain. At least the different concepts should be explained in more detail and the demand for these types of services should be questioned. A lot of research can be done on the match between supply and demand, but also on the way it should be placed in the market. How could we change peoples’ minds and let them place their first online food order. Once they have experienced it once, and when they are convinced about the quality and convenience, they will build it into their personal system. A suggestion for a future researcher is to convey a research in cooperation with (some of) the concepts described in the sector analysis. Databases of both customers and retailers could have been used, which will result in a stronger managerial relevance.




Since the shopping motive ‘convenience’ is rated more important than price and taste, a one-stop-shop should be the perfect solution. The concepts offering the full service from the source of the ingredients to the health conscious meals, is one step ahead in the service chain, but perhaps cooperation between Fresh food retailers, a supermarket and such a big logistics provider could be the perfect solution to offer this one-stop-shop and tackling the logistics challenge at the same time. Further investigation could be done on this type of service in order to get more of the current supermarket customers convinced to buy their fresh food products at those specialists, or make use of a one-stop-shop service and make more people conscious about the food they eat on a daily base, not only for special occasions.



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http://www.sciencedirect.com/science/journal/02726963/29/5



WEBSITES

CBS – 31 March 2011

Online shopping increasingly popular

http://www.cbs.nl/en-GB/menu/themas/vrije-tijd-

cultuur/publicaties/artikelen/archief/2011/2011-3335-wm.htm

CBS – 16 May 2012

Dutch among top online shoppers in Europe

http://www.cbs.nl/en-GB/menu/themas/vrije-tijd-

cultuur/publicaties/artikelen/archief/2012/2012-3625-wm.htm

CBS – 6 October 2012

Substantial increase male life expectancy

http://www.cbs.nl/enGB/menu/themas/bevolking/publicaties/artikelen/archief/2012/20

12-3675-wm.htm?Languageswitch=on

CBS – 6 October 2012

Rate demographic ageing process doubles

http://www.cbs.nl/enGB/menu/themas/dossiers/vergrijzing/publicaties/artikelen/archief/2011/2010-083-pb.htm

Familiekenniscentrum – April 2011 http://www.familiekenniscentrum.nl

FBC matrix – involvement men/women in purchase process

Graaggedaan.nl www.graaggedaan.nl

HBD – July 2012 http://www.hbd.nl

Hoofd Bedrijfsschap Detailhandel

HelloFresh – 21 September 2012 www.hellofresh.nl

A4U – performance Marketing Insights (http://www.affiliates4u.com)

Iceberg Web shop Hands www.icebergwebshophands.com

De Keurslager; Association of certified butchers in the Netherlands www.keurslager.nl www.versplatformnederland.nl

Ko-Kalf www.ko-kalf.nl

De Krat www.dekrat.nl (NRC Handelsblad, 27 October 2012)

Landmarkt www.landmarkt.nl

http://www.cbs.nl/en-GB/menu/themas/vrije-tijd-cultuur/publicaties/artikelen/archief/2011/2011-3335-wm.htm




http://www.cbs.nl/enGB/menu/themas/bevolking/publicaties/artikelen/archief/2012/2012-3675-wm.htm?Languageswitch=on

http://www.cbs.nl/enGB/menu/themas/bevolking/publicaties/artikelen/archief/2012/2012-3675-wm.htm?Languageswitch=on



http://www.familiekenniscentrum.nl/


http://www.hbd.nl/

http://www.hellofresh.nl/

http://www.affiliates4u.com/

http://www.icebergwebshophands.com/

http://www.keurslager.nl/

http://www.versplatformnederland.nl/

http://www.ko-kalf.nl/

http://www.dekrat.nl/

http://www.landmarkt.nl/



Meer dan Vlees www.meerdanvlees.nl

Ruud Maaz – online supermarket www.ruudmaaz.nl

Smaak – online supermarket www.smaak.nl

(http://smaak.nl/info/pers/persbericht_03.html)

Worldbank www.data.worldbank.org

On-line shopping figures, Internet Users (per 100 people), and retrieved March 23, 2012

Zinnerdinner www.zinnerdinner.nl

http://www.meerdanvlees.nl/

http://www.ruudmaaz.nl/


http://smaak.nl/info/pers/persbericht_03.html

http://www.data.worldbank.org/

http://www.zinnerdinner.nl/



APPENDICES

APPENDIX 1 - ONLINE SURVEY

1) What is your age? (open question)

2) What is your gender? 1=male, 2=female

3) Where do you live? (city and province, open question)

4) What is your highest completed education? 1=MAVO/VMBO, 2=HAVO, 3=VWO,

4=MBO, 5=HBO, 6=WO, 7=Other

5) To which income category belongs your household? (net in Euro, per month)

1=0-1,800, 2=1,801-3,000, 3=3,001-4,500, 4=4,501-6,000, 5=6,001-7,500, 6= >7,501

6) What is your participation? 1=Student, 2=Full-Time employed, 3=Part-Time

employed, 4=Self-employed, 5=Unemployed, 6=Retired, 7=Other

7) Do you have access to a computer with Internet at your workplace?

1=I am unemployed, 2=Yes, 3=No

8) How many hours per day do you spend on Internet? 1= <1, 2=1-3, 3=3-5, 4= >5

9) Select the social media channels you have an account for

1=LinkedIn, 2=Face book, 3=Twitter, 4=HYVES, 5=Other

10) Select the products/services you ordered online in the past six months

1=Computers & Accessories, 2=Electronics, 3=Telecom, 4=DVD’s, Blue Rays, Films,

5=Music, 6=White good & general appliances, 7=Cosmetics, 8=Interior & garden,

9=Toys, 10=Clothing, shoes & accessories, 11=Sport articles, 12=Insurances,

13=Travel (airfares, hotels etc), 14=Food & beverages, 15=Other

11) Select the answer that is most applicable to you; I do all my fresh food purchases at

the supermarket (including bread, meat and vegetables/fruit) 1= no, never,

2=seldom, 3=sometimes, 4=mostly, 5=yes, always

12) Select the answer that is most applicable to you; I do all my fresh food purchases at

the Fresh food retailer (bread at the bakery, meat at the butcher and

vegetables/fruit at the greengrocery) 1= no, never, 2=seldom, 3=sometimes,

4=mostly, 5=yes, always

13) Select the distance from your house to the supermarket and Fresh food retailers

(bakery, butcher and Greengrocery) 1=<2km, 2=2-5km, 3=>5km

14) Select the answer that is most applicable to the Fresh food retailers in your

neighbourhood; It is not practical for me to visit Fresh food retailers, since that is



not on my route when doing grocery shopping 1=Totally disagree, 2=Disagree,

3=Neutral, 4=Agree, 5=Totally Agree

15) Select the answer that is most applicable to the Fresh food retailers in your

neighbourhood; In the area where I do my grocery shopping are no Fresh food

retailers located 1=Totally disagree, 2=Disagree, 3=Neutral, 4=Agree, 5=Totally

Agree

16) Select the answer that is most applicable to you; The Fresh food retailers are often

closed when I do my grocery shopping 1=Totally disagree, 2=Disagree,

3=Neutral, 4=Agree, 5=Totally Agree

17) Select the answer that is most applicable to you; The queues at the Fresh food

retailers are long 1=Totally disagree, 2=Disagree, 3=Neutral, 4=Agree, 5=Totally

Agree

18) Select the answer that is most applicable to you; It costs me too much time to visit

the Fresh food retailers in addition to my visit to the supermarket 1=Totally

disagree, 2=Disagree, 3=Neutral, 4=Agree, 5=Totally Agree

19) Select the answer that is most applicable to you; Fresh food retailers are expensive

compared to supermarkets 1=Totally disagree, 2=Disagree, 3=Neutral, 4=Agree,

5=Totally Agree

20) Select the answer that is most applicable to you; The products from the Fresh food

retailers are more tasteful compared to these products from the supermarkets

(bread, meat and vegetables/fruit) 1=Totally disagree, 2=Disagree, 3=Neutral,

4=Agree, 5=Totally Agree

21) Select the answer that is most applicable to you; I purchase items like books and

clothing online 1= no, never, 2=seldom, 3=sometimes, 4=mostly, 5=yes, always

22) Select the answer that is most applicable to you; I order my groceries online (i.e.

www.albert.nl) 1= no, never, 2=seldom, 3=sometimes, 4=mostly, 5=yes, always

23) Select the answer that is most applicable to you; I order meals (i.e. Pizza, Thai etc)

online 1= no, never, 2=seldom, 3=sometimes, 4=mostly, 5=yes, always

24) Would you order your fresh food products (bakery, butcher and greengrocery)

online and get hem delivered at home if this services would be available?

1= No, 2=Yes

25) Would you order your fresh food products (bakery, butcher and greengrocery)

online and get hem delivered at home if this services would be available at an extra

cost (5-10% of the total amount spent)? 1= No, 2=Yes



APPENDIX 2 - DESCRIPTIVE STATISTICS

Personal Characteristics

The ages of the respondents are distributed as follows:

19 – 25 Years: 12 (7%) 46 – 55 Years: 10 (6%)

26 – 35 Years: 96 (55%) 56 – 64 Years: 18 (10%)

36 – 45 Years: 31 (18%) > 65 Years: 6 (4%)

The levels of highest finished educations are distributed as follows:

MAVO/VMBO: 5 (3%) HBO: 82 (47%)

HAVO: 4 (2%) WO: 61 (35%)

VWO: 6 (4%) Other: 2 (1%)

MBO: 13 (8%)

The incomes (in Euro, net per month, per household) are distributed as follows:

0 – 1,800: 18 (10%) 4,501 – 6,000: 32 (19%)

1,801 – 3,000: 39 (23%) 6,001 – 7,500: 16 (9%)

3,001 – 4,500: 56 (32%) > 7,501: 12 (7%)

Shopping motives

The distances from home to... are distributed as follows:

Distance to…

Supermarket Bakery Butcher Greengrocery

<2km 166 (96%) 156 (90%) 141 (81,5%) 133 (77%)

2-5 km 6 (3,5%) 17 (10%) 26 (15%) 29 (17%)

>5km 1 (0,5%) 0 (0%) 6 (3,5%) 11 (6%)

‘There are no Fresh food retailers in my shopping area’ resulted in the following

answers:

Totally Disagree: 105 (61%) Agree: 10 (6%)

Disagree: 43 (25%) Totally Agree: 4 (2%)

Neutral: 11 (6%)



‘The queues in the Fresh food retailers are in general longer then in the

supermarkets’. The responses according to a 5-Point-Likert-Scale are:


Disagree: 90 (52%) Totally Agree: 1 (0.5%)

Neutral: 33 (19%)

It ‘takes too much time to visit the Fresh food retailers’, besides their visit to the

supermarket. The answers according to a 5-Point-Likert-Scale are:



Neutral: 28 (16%)

‘The prices at the Fresh food retailers are higher compared to the supermarket’.

The answers according to a 5-Point-Likert-Scale are:



Neutral: 45 (26%)

‘The fresh food products sold at the Fresh food retailers are more tasteful then at

the supermarket’. The answers according to a 5-Point-Likert-Scale are:



Neutral: 21 (12%)

Internet Use

The majority has one or more social media accounts, as distributed below:

Face book: 131 (76%) HYVES: 37 (21%)

LinkedIn: 119 (68.8%) Other: 4 (2%)

Twitter: 58 (34%)



The items purchased online in the last 6 months could be summarized as follows:

Travel (airfares, hotels etc.) 132 (76%)

Clothing, shoes & accessories 111 (64%)

Music & books (including I-store) 71 (41%)

Computers & accessories 51 (30%)

Electronics 50 (29%)

Toys 41 (24%)

Insurances 39 (23%)

White goods & general appliances 34 (20%)

DVD’s and movies 29 (17%)

Sport articles 27 (15.6%)

Telecom 26 (15%)

Cosmetics 24 (14%)

Interior & garden 24 (14%)

Food & beverages 12 (6.9%)

Other 6 (3.5%)

Which items did the respondents buy online, questioned according to the Likert-

scale?

I order online…

Books, clothes etc.

Groceries Meals (i.e. Pizza, Thai)

No, never 9 (5%) 145 (84%) 94 (54%)

Seldom 25 (15%) 18 (10%) 51 (29%)

Sometimes 94 (54%) 9 (5%) 22 (13%)

Mostly 45 (26%) 1 (1%) 5 (3%)

Yes, always 0 (0%) 0 (0%) 1 (1%)

The preference of respondents to buy their groceries mainly from the supermarket

or the Fresh food retailer is shown in the table below:

I buy fresh food products at…

Supermarket Fresh food retailer

No, never 7 (4%) 9 (5%)

Seldom 13 (7.5%) 55 (32%)

Sometimes 17 (10%) 75 (43%)

Mostly 116 (67%) 29 (17%)

Yes, always 20 (11,5) 5 (3%)



APPENDIX 3 - STATISTICAL TESTS

1) Correlation

Table 3.1 Personal Characteristics variables relate to choice of store:

Preference Supermarket

Preference Fresh food retailer

1a) Age Pearson Correlation Sig. (2-tailed)

-0.203** .007

.286**

.000

1b) Male Pearson Correlation Sig. (2-tailed)

-0.207** .006

.082

.283

1b) Female Pearson Correlation Sig. (2-tailed)

.207**

.006 -.082 .283

1c) Education

Pearson Correlation Sig. (2-tailed)

-.119 .120

.015

.845

1d) Income Pearson Correlation Sig. (2-tailed)

-.228** .003

.117

.124

N=173 |**. Correlation is significant at 0.01 level (2-tailed)|

Table 3.2 Shopping Motives - convenience variables relate to the choice of store:



Distance Supermarket


.055

.470 .044 .566

Distance Bakery Pearson Correlation Sig. (2-tailed)

.093

.223 -.015 .849

Distance Butcher Pearson Correlation Sig. (2-tailed)

.074

.333 -.034 .657

Distance Greengrocery


.088

.248 .012 .879

FFR are closed Pearson Correlation Sig. (2-tailed)

.154

.043 -.218** .004

FFR queues are long


.129

.090 -.026 .734

Costs me too much time to visit FFR


.390**

.000 -.339** .000

Not handy to visit FFR


.261**

.001 -.107 .163

There are no FFR in my shopping area


.144*

.059 -.094 .217

N=173 |**. Correlation is sign. at 0.01 level (2-tailed)|*. Correlation is sign. at 0.05 level (2-tailed).



Table 3.3 Shopping Motives – price and taste variables relate to the choice of store:



FFR is expensive

Pearson Correlation Sig. (2-tailed

.302**

.000 -.236** .002

FFR is more taste

Pearson Correlation Sig. (2-tailed

-.141 .064

.121

.114

N=173 |**. Correlation is sign. at 0.01 level (2-tailed)|*. Correlation is sign. at 0.05 level (2-tailed).

The results of the standard multiple regression analysis are shown in the tables below, separated per group:

2) Multiple Regression Table 3.4 Personal Characteristics group

Regression Analysis Choice Type of Store

b (s.e.) β Sig Tolerance VIF

PERSONAL CHARACTERISTICS

Age .008 (.004) .163 .107 .907 1.102

Gender -.169 (.105) -.127 .037 .882 1.133

Education .023 (.043) .042 .594 .875 1.143

Income .059 (.037) .127 .115 .843 1.187

R square (r²) .082 (8%)

Adjusted R square (F) .060 (6%)

Standard Error of Estimate

.602

Table 3.5 Shopping Motives group – distance



CONVENIENCE - DISTANCE

Distance Supermarket -.252 (.233) -.096 .283 .733 1.365

Distance Bakery -.240 (.217) -.115 .270 .534 1.873

Distance Butcher .129 (.140) .102 .359 .471 2.123

Distance Greengrocery

.052 (.105) .049 .621 .601 1.664

R square (r²) .024

Adjusted R square (F) .001


.620



Table 3.6 Shopping Motives group – time



CONVENIENCE - TIME

FFR are closed -.017 (.039) -.034 .663 .784 1.275

FFR queues are long .013 (.059) -.017 .830 .773 1.294

Costs me too much time to visit FFR

-.209 (.042) -.425 .000 .672 1.488

Not handy to visit FFR -.037 (.046) -.069 .415 .667 1.500

There are no FFR in my shopping area

.151 (.051) .241 .004 .716 1.397

R square (r²) .201



.563

Table 3.7 Shopping Motives group – price



CONVENIENCE - PRICE

FFR is more expensive -.199 (.044) -.327 .000 1.000 1.000

R square (r²) .107



.588

Table 3.8 Shopping Motives group – taste



CONVENIENCE - TASTE

FFR is more tasteful .171 (.055) .232 .002 1.000 1.000

R square (r²) .054



.605



Table 3.9 Preference supermarket – online FFR @ no costs

Regression Analysis FFR available online – @ no costs


Preference supermarket

-.026 (.041) -.049 .519 1.000 1.000

R square (r²) .002

Adjusted R square (F) -.003


.485

Table 3.10 Preference supermarket – online FFR @ extra costs

Regression Analysis FFR available online – @ extra costs


Preference supermarket

.079 (.034) -.177 .020 1.000 1.000

R square (r²) .031



.398

Table 3.11 Preference FFR – online FFR @ no costs



Preference FFR -.026 (.042) -.047 .542 1.000 1.000

R square (r²) .002

Adjusted R square (F) -.004


.485

Table 3.12 Preference FFR – online FFR @ extra costs



Preference FFR .037 (.035) .080 .296 1.000 1.000

R square (r²) .006



.403



Table 3.13 Order groceries online – online FFR @ no costs



Order groceries supermarket online

.287 (.062) .333 .000 1.000 1.000

R square (r²) .111



.458

Table 3.14 Order groceries online – online FFR @ extra costs



Order groceries supermarket online

.297 (.050) .414 .000 1.000 1.000

R square (r²) .171



.368

is an online shop the future for fresh food retailers in the

Documents