RIJKSUNIVERSITEIT GRONINGEN
The effect of sampling
chocolate on customer
experience
Customer indulgence, cost or benefit?
By Bibianne RoetertMay ’12
In this study the effect of sampling chocolate on customer experience is examined in a supermarket environment. The experiment provides thorough insight in the do’s and dont’s considering sampling. This thesis will conclude with an advice for retailers how to use sampling in order to improve
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The effect of sampling chocolate on customer
experience
Master thesis
Author
Bibianne Roetert, 1630016 Burmanstraat 7-2 1091 SG Amsterdam Email: Bibianne_r@hotmail.com Tel: 06-45203261University of Groningen
Faculty of Economics and BusinessMsc Business Administration Specialization Marketing Management
Supervisors
Supervisor: Laurens Sloot Co-supervisor: Erjen van Nierop3
Management summary
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Preface
When I was only twelve years old, I already wanted to become a marketeer. Searching for ways to improve people’s everyday rituals and to fulfil needs by making innovative products sounded like the most fun job in the world. Therefore, after successfully finishing my Bachelor’s degree it obviously wasn’t hard to choose which Master I wanted to apply for. Marketing management it was. Finally all courses which were thought attracted my attention and made me a fully dedicated student. To complete my marketing knowledge with some practical experience I learned a lot during my internship at Albert Heijn. During this internship I knew all my choices have been right and marketing is really the part of business which I can accelerate in and where my heart lies. Therefore, I’m happy to finally finish my studies and to start practice ‘real marketing’ in a Marketing traineeship at Unilever.
Finishing this thesis will mean the end of a fun and informative project. I couldn’t have finalised this without the help of a couple of great people. First, I want to thank Laurens Sloot for his endless patience and his useful tips. I also like to thank professor Verbeke for being so helpful and enthusiastic during the entire process. John Macleane has made it possible to collect data in both his supermarkets in Elst, I want to thank him a lot for this possibility and for the samples supplied by his supermarkets. In advance I also want to thank Erjen van Nierop for being my second supervisor and for spending time to read the whole text. Also I would like to thank the supermarket manager of Albert Heijn Jeremy for providing me with some useful insights from Holland’s biggest retailer.
At last I want to thank my parents, brother, sister, friends and boyfriend for supporting me throughout the entire process. They have always paid full attention to my stories and encouraged me to proceed with my ‘fantastic’ ideas.
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Table of content
Management summary ... 3 Preface 4 1. Introduction 7 1.1 Background ... 7 1.2 Customer Experience ... 7 1.3 Cognitive responses ... 8 1.4 Affective responses ... 9 1.5 Conative responses ... 9 1.6 Problem statement ... 10 1.7 Relevance of study ... 111.8 Structure of the study ... 12
2. Theoretical framework ...13 2.1 Sampling food ... 13 2.2 Tasting food ... 18 2.3 Customer Experience ... 21 2.4 Cognitive responses ... 22 2.5 Affective responses ... 26 2.6 Conative responses ... 28 2.6 Conceptual model ... 30 3. Research design...31 3.1 Experimental design ... 31 3.2 Sample ... 32 3.3 Procedure ... 32 3.4 Plan of analysis ... 34 3.5 Extra analysis ... 37 4. Results 38 4.1 Representativeness of sample... 38 4.2 Factor analysis ... 39 4.3 Regression analysis ... 42 4.4 Extra analysis ... 47
4.5 Overview of the results ... 51
5. Conclusion 53 5.1 The effect of chocolate on cognitive response ... 53
5.2 The effect of chocolate on affective response ... 54
5.3 The effect of chocolate on conative response... 56
5.4 The effect of chocolate on customer experience ... 56
6. Limitations and guidelines for future research ...58
7. Managerial implications ...60
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1. Introduction
1.1 Background
In food retail, creating value to your customer is the key to success. Especially in the supermarket industry of today, which is characterized by price wars, all practices of a food retailer are based on persuading consumers to spend money at their place and not at the competition. Where most food retailers focus on price and products in order to differentiate, Dutch consumers are looking for good service and the feeling of ‘to this place I want to return’ (GFK.nl 2012²). Therefore, to maintain and even expand their position in the market, Dutch retailers have to start investing in creating superior customer experience in order to attract customers and differentiate from competition.
1.2 Customer Experience
8 today’s Dutch consumer spends 25 minutes per shopping trip (CBL.nl 2012¹). Hence, retailers can enhance this time and thereby sales by making the customer experience as pleasant as possible. Moreover, in-store promotions lead to enhancement of emotion and experience which is crucial in involving Dutch customers with their supermarket (GFK.nl 2012²). Additionally, a tool to make the customer experience outstand the competition is sampling of food in a supermarket. It is expected that especially the (sweet) taste of chocolate has the ability to influence customer responses in a retail environment (Herz 2007). However, the effect of sampling chocolate on customer responses has never been studied before. Therefore, in this study the effect of sampling chocolate on the perceived customer experience is examined. With the in-store stimulus of chocolate, retailers attract the consumer’s attention. While having their attention, customers get the opportunity to appraise the stimulus which results in cognitive, affective and conative responses (Inman et al. 2009). As Verhoef et al. (2009) claim, these responses ultimately determine the perception of the construct ‘customer experience’.
1.3 Cognitive responses
9 1.4 Affective responses
Affect relates to ones internal status in view of the collection of moods and emotions (Puccinelli et al. 2009). An affective response towards a supermarket is generally considered as the feeling of perceived pleasure in that supermarket (Kaltcheva and Weitz 2006; Donovan et al. 1994; Baker et al. 1992). In addition, positive affective responses cause an increased willingness to buy (Inman et al. 2009; Kaltcheva and Weitz 2006; Donovan et al. 1994; Baker et al. 1992). Consequently, positive affective responses can turn out in an increased share of wallet per customer or maybe even stimulate patronage behaviour. Affective responses are mostly accompanied by cognitive responses (Inman et al. 2009); nevertheless they influence behaviour independently (Donovan et al. 1994).
1.5 Conative responses
10 Figure 1 The relationship between In-store stimuli and consumer response
1.6 Problem statement
It is of great importance to find out what factors make the difference in a retail environment in order to enhance the perceived customer experience. Furthermore, this is what eventually leads to creating customer value and what will differentiate one retailer from another. Additionally, since the degree of perceived customer experience affects patronage intentions and the share of wallet per customer, every possible method should be examined in order to improve this experience. In this study only one method is assessed, sampling of chocolate. The effect of sampling chocolate, which is expected to enhance the perception of customer experience, is studied using the following research question:
Does sampling of chocolate increases the perceived customer experience?
Customer experience is the result of the cognitive, affective and conative responses of a customer towards a retailer. Therefore, the sub questions focus on the effect of chocolate on these three specific constructs.
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1.2.1 Sub questions
The following sub questions are formulated in order to examine the general research question:
1. What is the effect of chocolate on cognitive responses? 2. What is the effect of chocolate on affective responses? 3. What is the effect of chocolate on conative responses?
1.7 Relevance of study
12 Figure 2 Amount spent per transactions in Dutch supermarkets over the last years (GFK.nl 2012 ¹)
Creating excellent customer value is what distinct today’s successful retailers from others (GFK.nl 2012²) today. Therefore, to detect whether the move of focus towards the web can be approved or whether there still lay opportunities inside the supermarket, this study examines the effect of chocolate on enhancing customer experience. If customer experience will be improved by offering something simple as chocolate, chocolate might serve as a ‘secret’ weapon in the battle of the superior Dutch retailer in the near future.
1.8 Structure of the study
The problem which gave rise to this study is formulated above. Besides, the three different constructs which determine (the perception of) customer experience are explained. In the next six chapters, the effect of chocolate on customer experience is stressed in detail. First, the problem will be supported by a theoretical framework in chapter two. Second, in chapter three the research is made more tangible in a research design. This explains both the design of the study and the method of performing the experiment and interpreting the results. Chapter four contains the results and the analysis which are the basis of chapter five, the conclusion. In addition, in chapter six several limitations are stressed and to complete the research, managerial implications are proposed in chapter seven.
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2. Theoretical framework
2.1 Sampling food
2.1.1 Sampling food in food retail environments
The emotional and social responses to environmental stimuli are crucial in affecting purchase behaviour, as mentioned by Verhoef et al. (2009). Sampling food is a tool to influence this response. Hence, offering free food in supermarkets will build excitement in the store and stimulates buying (Levy and Weitz 2009). Moreover, tasting, seeing and smelling the product makes consumers more convinced of their attitudes and provide them stronger beliefs of the benefits of that product (Marks and Kamins 1988). Although Kotler (1973) claims that taste cannot directly be applied to atmosphere, Heiman et al. (2001) contradicts this statement. He states that demonstrations and sampling food have two effects: increasing the probability that a consumer will purchase a product; and increase the formation of goodwill of the consumer. This latter effect is of great importance to food retailers. It would mean that the mood of consumers in the supermarket can be influenced by offering free food samples. This would explain the reason food sampling is a tool already used in supermarkets (Interview Appendix B). However, earlier research provides little evidence about the formation of goodwill after receiving a sample.
Explanations of the formation of goodwill after receiving a free food sample can be the reciprocity effect, people respond positive to favorable treatment (Fennis and Stroebe 2010); or the effect of eating on customers’ mood while shopping (Andrade 2005; Garg et al. 2007; Donovan et al. 1994) or it might be explained by physical responses of individuals to tasting and smelling food (O’Doherty et al. 2000;; Kringelbach et al. 2003;; Pellegrino et al. 2010).
2.1.2 Physical theory about food sampling
14 process which happens in one particular part of the brain. In addition, the part of the brain responsible for influencing human emotional states after tasting food is the orbitofrontal cortex (O’Doherty et al. 2000;; Kringelbach et al. 2003; Pellegrino et al. 2010). After tasting food, the pleasantness evoked by the specific food is evaluated in regions of the orbitofrontal cortex. This part of the orbitofrontal cortex indicates the amount of pleasure one perceives after eating (Kringelbach et al. 2003). In figure 3, the activated part of orbitofrontal cortex which correlates with pleasantness ratings, is indicated as the yellow spot in the left of the picture.
15 Figure 4 An overview of the human brain
16 Figure 5 The human brain, the amygdala and the prefrontal cortex (Neuralmodel.net 2012)
2.1.3 Function of the orbitofrontal cortex
17 one bite could lead to higher interest in the particular product or in products from the assortment in general.
2.1.4 Psychological theory about food sampling
In contrast, the effect of tasting food on the human emotional state has also been examined from a psychological point of view. However from this view people are already in a certain emotional state and eating can contribute to either preserve this emotional state or improve their state. Since the emotional state of shoppers can predict shopping behavior according to Donovan et al. (1994), it is important to facilitate food which can positively influence the mood of customers. However, whether a person perceives food to be either mood lifting or mood threatening depends on the person’s affective state at that time (Garg et al. 2007). For happy people healthy food is mood enhancing, while sad people want to navigate away from their negative emotional state by eating more hedonic products as fattening snacks (Tice et al. 2001). Moreover, only the presence of food is an important factor in psychological studies as well. Providing free food can be perceived as a favourable treatment. According to the principle of reciprocity (Fennis and Stroebe 2010), positive responses follow a favorable treatment. Besides the principle of reciprocity, sampling food in general contains a positive action of the supermarket. Moreover, this action might contribute to consumers’ feelings and perception of the store characteristics.
2.1.5 Food sampling as a tool to evoke both cognitive and affective responses
18 significance to discover what influences this affective response of the consumer. At the same time it is important to determine the factors that influence cognitive responses. Since cognitive responses ultimately increase involvement (Fennis and Stroebe 2010) which results in more word of mouth, liking of the store, and future shopping intentions (Puccinelli 2009).
2.1.6 Effectiveness of food sampling in retail environments
Improving the total evaluation of the supermarket is eventually each retailer’s aspiration in order to improve customer experience. What the influence of the sample is on the total evaluation of the supermarket is examined in the following experiment. Goal of this research is to help supermarkets to (re)evaluate the effectiveness of sampling food and use sampling effectively in order to create the ultimate customer experience. The sum of the customers’ cognitive, affective and the conative response gives insight in whether or not the retailer has succeeded to create this outstanding customer experience, as shown in figure 6.
Figure 6 Cognitive, affective and conative customer responses affect customer experience
2.2 Tasting food
2.2.1 Informational and affective component of consumption
Ultimately, the goal of sampling food is to evoke positive responses from customers. In addition, this positive response is partly based on conscious and unconscious consideration of the food sample. Shiv and Nowlis (2004) claim that the environment, in which the sampled
19 product is tasted, plays an important role in the dominance of conscious or unconsciousness decisions of consumption. They separate an informational- and an affective component of consumption. Of which the informational component is a composition of objective features related to aspects such as the quality of the tasting experience. On the other hand, the affective component is a composition of the subjective, more emotional, reactions to the experience. According to Shiv and Nowlis (2004), distraction will lead to an increased impact of the affective component. This would mean that sampling food in a crowded environment will have a different effect than sampling in a less crowded environment. Since supermarkets are generally crowded, mostly the affective component of consumption overrules the informational component in this setting. Therefore, choices made in supermarkets seem to be more often based on emotion rather than objective features of a product.
2.2.2 Type of food
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2.2.3 Taste and smell
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2.2.4 Chocolate as a treat
In addition, the drive to eat certain food is detectable with people who crave to eat sweets or salty snacks. Hence, craving can be explained as an intense desire to eat a particular food (Herz 2007). Women and men differ in type of food they crave for. While 60% of women crave for sweet food, with chocolate high on that list, 60% of men crave for savory food (Herz 2007). Apart from this gender differences in preference for cravings, eating sweet food is perceived as pleasurable by both men as women. This is both explained by nature, human evolution, as by nurture since most people have initially learned that the taste and smell of sweets are good because it is tasty food (Herz 2007).
2.3 Customer Experience
22 Detecting the influence of chocolate on these three responses is supposed to answer the research question:
Does sampling of chocolate increases the perceived customer experience?
2.4 Cognitive responses
Cognitive responses are responses towards a stimulus or a situation which are processed in a higher-order cognitive manner. In this study, cognitive response is defined as the response following upon a thorough conscious deliberation of the situation (Fennis and Stroebe 2010). The cognitive response can be compared to the informational component of Shiv and Nowlis (2004). Hence, in cognitive responses the focus lies beyond emotion upon the higher-processing level. As Sherman et al. (1997) claim, cognitive responses account for most planned purchases. Therefore, cognitive processes are important to monitor since in most cases they do influence at least one-third of the purchase decisions, since two-third is made in-store (POPAI 1995).
2.4.1 Objectively process information
23 Additionally, relevant interactions in the definition of cognitive responses are the items that are objective and transparent in the manipulated situation. At the same time, the relevant items should drive purchase decisions in order to add value for retailers.
2.4.2 Cognitive responses driving purchase decisions
The items which comply with this are defined by Parasuraman et al. (1988) in their SERVQUAL scale. The SERVQUAL scale measures the consumer perceptions of service quality in retailing organizations. Although it is difficult to measure quality objectively, this scale provides a framework to assess the overall service quality based on attitudes resulting from the comparison between customer’s expectations and their perceptions of actual performance (Parasuraman 1988; Dabholkar et al. 1996). Zeithaml et al. (1996) emphasize the importance of measuring service quality in order to improve it. In addition, they claim that improving service quality can increase favorable behavioral intentions towards the supermarket. Hence, the SERVQUAL scale contains five dimensions: Tangibles; reliability; responsiveness; assurance; and empathy. The average score on each of these five dimensions gives insight in the extent to what the supermarket is complying with customer’s needs. Baker et al. (2002) and Verhoef et al. (2009) confirm the value of this scale by stating that the perceptions of interpersonal service quality, and retail atmosphere affect store patronage intentions. Furthermore, Verhoef et al. (2009) outline the importance of measuring current satisfaction in order to affect future customer satisfaction. Therefore, measuring the quality perception of customers in a supermarket is very relevant in order to determine the effect of chocolate on cognitive responses.
2.4.3 Measuring cognitive responses
24 the main dimensions. Hence, this adjusted scale is more appropriate for examining retail businesses offering a mix of services and merchandise (Dabholkar et al. 1996). Since the up to date measurement instrument of Dabholkar et al.(1996) provided more accurate theorems to assess the retail service quality perception then the SERVQUAL scale of Parasuraman et al. (1988), fifteen theorems from the instrument of Dabholkar et al. (1996) are selected to measure cognitive response. Furthermore, the selection of fifteen theorems is supposed to reflect all relevant items considered by Dutch customers inside a supermarket (GFK.nl 2012¹). Which theorems were selected and eventually will be used to assess cognitive response is outlined in TABLE 1.
TABLE 1 SERVQUAL dimensions (Dabholkar et al. 1996 ; Parasuraman et al. 1988)
Dimensions Definition Theories Tangibles Physical facilities,
equipment, and look of personnel
1. TAN1: The physical facilities at this store are visually appealing
2. TAN2: This store has modern-looking equipment and fixtures
3. TAN3: Materials associated with this store’s service (such as shopping bags, catalogues or statements) are visually appealing
Reliability Ability to perform the
promised service consistently and correctly
1. REL1:This store provides the service right the first time
2. REL2:This store has merchandise available when the customers want it
3. REL3:This store insists on error-free sales transactions and records
Responsiveness Willingness to help the customer and to provide quick service
1. RESP1:Employees in this store give prompt service to customers
2. RESP2:Employees in this store tell customers exactly when services will be performed
3. RESP3:Employees in this store are never too busy to respond to customer’s requests
Assurance Knowledge and politeness of
employees and their ability to instigate trust and confidence
1. ASS1:This store gives customers individual attention
2. ASS2:Employees in this store are consistently courteous with customers 3. ASS3:Employees in this store are
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Empathy Caring, providing
personal service
1. EMP1:This store offers high quality merchandise
2. EMP2:This store provides plenty of convenient parking for customers
3. EMP3:The store has operating hours convenient to all their customers
2.4.4 Assessing cognitive responses
In this study, all fifteen theorems from TABLE 1 are included in the three different questionnaires which are presented in appendices A1, A2, and A3. The responses towards the theorems are measured on a 5-point Likert scale. Respondents can indicate if they totally disagree (1) up to totally agree (5) with the theorem. It is expected that offering free chocolate to customers will enhance each dimension of cognitive response, while customer-employee interaction affects the perception of the 5 dimensions of the SERVQUAL scale (Parasuraman et al. 1988). Hence, everything that influences the customer-employee interaction positively will influence the perception of the five quality dimensions in a positive manner (Baker et al. 2002). Because people associate chocolate with happiness and warmth (Herz 2007), these thoughts are expected to spread out to the perception of the reliability, responsiveness, assurance and empathy of the employees. In addition, in the time when chocolate is sampled, it is believed that consumers are more positive in general because of the presence of chocolate (Herz 2007). However, when chocolate is not sampled the perception of the dimensions relies on objective deliberation which can be either positive or negative. That sampling of chocolate is indeed such a relevant factor in affecting cognitive responses inside a supermarket, is proposed in the following hypothesis:
H1: Sampling of chocolate will evoke a positive cognitive response towards the supermarket.
26 future by offering chocolate (Puccinelli 2009). At the same time, future store selection and most planned purchases are positively influenced by positive cognitive responses (Sherman et al. 1997). In competitive times like these, such positive outcomes makes the effect of ‘chocolate as a marketing tool’ worth examining.
2.5 Affective responses
Customer experience is also based upon affective customer responses, the subjective and personal responses towards a supermarket (Verhoef et al. 2009). According to Kaltcheva and Weitz (2006); Donovan et al. (1994) and Baker et al. (1992), an affective response towards a supermarket can be described as the feelings of perceived pleasure in a supermarket. Perceived pleasure is therefore the overall variable measured in order to determine the affective response of a customer. To measure the effect of chocolate on the variable ‘perceived pleasure’, different items are relevant.
2.5.1 Measuring affective responses
27 internally and externally consistent. Hence, the items are submitted both positively as negatively in order to prevent bias of rehearsal. Whereas feelings of repulsion are not considered relevant in a supermarket environment, this item has been deleted. In addition, also the Happiness-item of Donovan et al. (1994) is added to these 5 items of Baker et al. (1992). Combined with the feeling of being welcome, a very important item when visiting a store (GFK.nl¹ 2012), ten items are used in order to measure affective response. To exclude the limitation of measuring perceived pleasure prior entering the store and after visiting the store, this study only measures the perceived pleasure inside the store.
2.5.2 Assessing affective response
28 the same time, negative affective responses are expected to be weakened when chocolate is sampled because women will respond more favorable towards the chocolate. Therefore, two hypotheses have been separated to determine the effect of chocolate on affective responses of female shoppers:
H2a: Sampling of chocolate will strengthen positive affective responses towards the supermarket.
H2b: Sampling of chocolate will weaken negative affective responses towards the supermarket.
2.6 Conative responses
29 it is that they would recommend the store to friends. Baker et al. (1992) specify this latter question as an indication of approach behavior. In addition, customers are asked to answer these three questions on a five-point Likert scale from very unlikely (1) up to very likely (5). It is expected that respondents who are in the situation where chocolate is sampled are more willing to recommend the supermarket to their friends then others. Subsequently, customers will prefer the supermarket above others and are more likely to visit the store again on their next shopping trip when chocolate is sampled. This positive influence of chocolate results from the assumption that positive experiences lead to positive attitudes which in turn lead to positive conative responses (Baker et al. 1992). Hence, attitude-behavior consistency is higher in the case of trial, if people are able to taste the product and have a positive experience with it (Smith and Swinyard 1983). Since most women hold positive attitudes towards chocolate because of its sweetness (Herz 2007), it is expected that respondents perceive the experience of tasting chocolate to be positive. Therefore a positive conative response is expected to result from the presence of the chocolate. A positive conative response in this study is indicated by: (1) the likelihood of visiting the supermarket again next shopping trip; (2) supermarket preference; (3) and the likelihood of recommending the supermarket to their friends. In addition, to verify the connection between good attitudes and good behavior, a fourth extra conative response is measured. What will be measured is the willingness to donate €0,50 to charity (4). In theory, the reciprocity effect will make respondents more willing to donate after receiving a chocolate (Fennis and Stroebe 2010). However, if this will be supported by research will examined in this study. A positive response is expected on all four conative responses. The hypothesis formulated based on the above is hypothesis 3:
30 2.6 Conceptual model
The conceptual model in figure 6 will help answering the problem statement whether sampling of chocolate can serve as an effective tool in supermarkets to provide the ultimate customer experience. The three sub questions explained in H1, H2a & H2b, H3, support answering the problem. Hence, customer experience is divided in cognitive response; affective response; conative response. Moreover, a positive influence of chocolate on these three constructs is expected based on the previous described theories.
Figure 7 Conceptual model
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3. Research design
In the following chapter the research method of collecting and analysing data is explained in four steps. First, the experimental design of the study will be clarified. This design will be followed by an explanation of the sample which implies a description of the respondents. In addition, the procedure of performing the experiment will be outlined. Moreover, the chapter will conclude with a detailed plan of how the results will be analysed after collecting the data. In other words, this chapter will serve as a guide through the process of starting the experiment all the way to the end of the experiment when the necessary data is collected.
3.1 Experimental design
In order to get insight in how customer experience is enhanced through sampling of chocolate, a field experiment is conducted in the supermarket. The goal of this experiment is to detect differences between the situation with chocolate, and the situations without chocolate.
Analysing the experiment results is expected to give insight in the causality between the independent variable ‘tasting of chocolate’ and the dependent variables: cognitive response;; affective response; and conative response as outlined in TABLE 2.
TABLE 2 Sampling chocolate and its expected relationship with customer response
Cognitive response Affective response Conative response Sampling chocolate H1: + H2a positive affect: +
H2b negative affect: -
H3: +
32 possible. Random assignment of respondents has to be guaranteed in order to use a between-participant design (Malhotra 2007).
3.2 Sample
In order to reach the goal of enhancing the customer experience by sampling chocolate, it is important to determine who your target group is (Kotler 1973). In case of a supermarket, this target group is extremely varied. Therefore a clear distinction is made in the customers who are targeted and which are not. In this study only women are included because of their apparent preference for the taste of chocolate (Herz 2007). Data is collected from a total of 300 respondents (n=300). Additionally, respondents are not aware of the hypotheses or the goals of the study. In general, respondents which are not biased by foreknowledge are most objective and reliable (Malhotra 2007). The sample of respondents includes all women who happen to be in the supermarket at the time of the test, men are excluded. Random assignment is guaranteed since respondents are asked on beforehand if they have not participated in the research one of the days before.
3.3 Procedure
33 TABLE 3 – Characteristics supermarkets
Europaplein (Supermarket A)
Westeraam (Supermarket B) Size of supermarket (excl.
storage room)
1.837m² 907m²
Amount of transactions 18.324 a week 9.200 a week Average amount spent per
transaction €20.42 incl. Service corner and €25.68 excl. corner €17.11
Amount of parking places 80 200
Average age of customers 49.2 Years old 48.7 years old Opening date 16th of June 1986 7th of June 2007 Amount of employees +/- 150 65-70
Inside the two supermarkets, exactly the same study is performed. In the first manipulated situation, a big plate full of dark chocolate is placed near the entrance of both supermarkets (Pictures Appendix D). In this situation, the questions from the questionnaire in Appendix A1 are asked by the researcher. To control for the reciprocity effect (Fennis and Stroebe 2010), another non-food product is sampled near the entrance of both supermarkets in the second situation. This product will be a standard C1000 pencil. Offering also a taste and smell lacking non-food item makes it possible to exclude the reciprocity effect on gifts in general, and to focus on the effect of chocolate instead. In this second situation, the questionnaire from Appendix A2 is used. In the third and control situation, all other store characteristics are equal. However, no product is sampled at the entrance. In the third situation, the questions from the questionnaire in appendix A3 are asked. Moreover, results from this last situation tend to be reliable for representing the supermarket in a standard situation. Comparing this third situation with the former two, indicates if offering a product in general will change any response.
3.3.1 Experimental conditions
34 which is presented in TABLE 4. For example, first nothing is sampled for two hours, than chocolate is available for two hours and at last there are pencils at the entrance for a period of two hours. In every two hours per situation, about 15 to 20 respondents are questioned. In total 50 respondents per situation in each supermarket are questioned.
TABLE 4 Order of experiment situations per supermarket, per day
Supermarket Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 A Westeraam 1. Chocolate 2. Pen 3. Nothing 1. Pen 2.Nothing 3.Chocolate 1.Nothing 2.Chocolate 3.Pen B Europaplein 1.Chocolate 2.Pen 3.Nothing 1.Pen 2.Nothing 3.Chocolate 1.Nothing 2.Chocolate 3.Pen Overall, the experiment will take six days to gather the necessary amount of data, three in each supermarket.
3.3.2 Respondents
Customers are approached by the researcher while they are shopping through the aisles. The specific place in the supermarket is unimportant, but in the situations chocolate and pencil respondents have to have passed the display with the samples. Furthermore, approaching a respondent includes a short introduction of the researcher followed by the question whether the customer is willing to participate in an experiment or not. If the customer agrees, the researcher proceeds by running through Appendix A1, A2 or A3 depending on the situation. 3.4 Plan of analysis
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3.4.1 Representativeness of the sample
In order to reassure that this experiment is a thorough reflection of the real world situation, a comparison will be made between the means of the variables in the study and means from up-to-date research. This analysis is supposed to answer the question to what extend conclusions from this research can be generalized over all supermarkets and all customers.
3.4.2 Factor analysis
The effect of chocolate on customers in the supermarket will be examined by analysing the data collected from the questionnaires measuring three different responses. In addition, each response is composed of different attributes which makes it easier to determine the exact effect. These attributes are first tested on their reliability and validity. To determine the extent to what the questions measure the actual attribute, a factor analysis has to be performed per response in order to compare the amount of factors with the amount of attributes. Furthermore, to get insight in the reliability per attribute the Cronbach’s alpha per factor has to be computed (Malhotra 2007). Subsequently, a Cronbach’s alpha perimeter of > 0.5 represents a reliable attribute. In TABLE 5 an overview is given from the expected different attributes per response based on theory. Conative response consists of only one attribute ‘conative response’ and the extra variable ‘donation’.
TABLE 5 Attributes per response
Response Attributes
Cognitive response Tangibles Responsiveness Reliability Assurance Empathy Affective response Positive
emotions
Negative emotions
Conative response Conative
response *Donation
* This is an extra variable which will be measured separately from conative response
3.4.3 Independent variables
36 regression analysis will show the relationship between chocolate and response excluding the influence of other factors. The independent variables measured in the experiment are outlined in TABLE 6, both main as console variables are involved.
TABLE 6 Independent variables
Main independent variables
CHOCTASTE PENPICK 0-Condition
Console independent variables
Day Store Shopper Frequency of visiting p/w Loyalty Age Size of household Income
Choctaste and penpick indicate whether someone, who was in the chocolate or pen situation, took a sample or not. The 0-Condition is the condition where neither a pencil nor chocolate was available. ‘Day’ is indicated as 1, 2 or 3 based on the explanation in TABLE 4. Store speaks for itself. If someone is the shopper, she is responsible for shopping for groceries of the entire family. Frequency indicates how many times she visits a supermarket a week. Furthermore, loyalty gives insight in how many times of the ten, one visits this specific supermarket. In addition, age, size of household and income speak for itself.
3.4.4 Regression analysis
37 attribute. Each p-value is divided by 2 in order to determine its significance because each analysis is a one-tailed test with an expected positive relationship, or an expected negative relationship in the case of H2b (Huizingh 2006). In addition, the corresponding beta of the relationship indicates the positive or negative nature of the causality (Huizingh 2006).
3.4.5 Accepting the hypothesis
After interpreting the results from the regression analysis, a decision will be made to either accept the hypotheses or to reject them. This decision will be made for each response separately based upon the results from the belonging attributes. If the majority of the attributes show a significant connection and a positive beta with tasting chocolate, the hypothesis will be supported. If the attributes significantly connected with tasting chocolate are in a minority, the hypothesis will be rejected. The hypothesis will also be rejected if the majority of causalities show negative beta’s or shows no significant causalities at all. In the case of affective response, a negative beta means accepting hypothesis 2b where a weakened negative affective response after eating or seeing chocolate is expected.
3.5 Extra analysis
In order to measure the effect of chocolate in the most wide-ranging way, also the effect of just seeing the chocolate is measured. Sight is important input for objectively processing information (Shiv and Fedorikhin 1999) and it enhances the ability to smell the sample (Herz 2007). Therefore, the relationship between seeing chocolate and the three different responses will also be examined in a regression analysis. The same independent variables as in the previous analysis will be used, only CHOCTASTE and PENPICK will now be changed into SAWCHOC and SAWPEN. These independent variables indicate whether or not the
38
4. Results
In this chapter, an overview is presented of the results from the analysis accompanied by an interpretation of these results. These results will confirm or deny the statement that chocolate has an effect on customers’ experience in the supermarket. This chapter will begin with the results from the factor analysis. Thereafter, the results from the linear regression are presented. The SPSS output of both analyses can be found in Appendix C. At last, in the conclusion of this chapter a summary is given which provides insight in whether or not the hypotheses are supported by the analyzed data.
4.1 Representativeness of sample
Before proceeding with the results, first the representativeness of the sample will be discussed in this sub chapter. Previously, data from the questionnaire was transformed in an SPSS dataset in order to perform the necessary analysis. From the 300 respondents, a reliable dataset of n=296 remained because of an error in the answers of four respondents. From these 296 respondents, the chocolate situation contained 96 respondents (n = 96), both the pencil- and the control situation contained 100 respondents (n = 100). Figure 9 presents a diagram which gives insight in the behaviour of respondents in both situations.
Figure 9 Respondent behaviour
96 100 70 36 42 3 0 20 40 60 80 100 120 Chocolate Pen
39 The sample consists from a total of 296 women who shop for groceries in two C1000 supermarkets in Elst. The C1000 is a Dutch value-for-money supermarket, offering average service and average prices; they serve 66% primary customers (Supermarkt.nl 2012). Furthermore, the average Dutch consumer visits the supermarket 2.8 times a week and there they spend 25 minutes per shopping trip (CBL.nl 2012). The results from this study show that the average respondent visits the supermarket 3,3 times a week so a little more often than the average. The sample contains women from all ages with 73 women between 18-35, 114 between 36-55 and 109 above 55 years old. These women have an average household consisting of 3 persons. The average income in this study is similar to the average Dutch income ‘modal’. Moreover, the respondents are mostly the ones responsible for shopping for groceries and indicate that they averagely visit these supermarkets 7.59 out of ten times. This implies that they tend to be quite loyal. Furthermore, the average Dutch supermarket scores an 8 based on consumer rates. The value-for-money formula scores a 7.9 which is close to the average (Supermarket.nl 2012). Therefore it is expected that the satisfaction score in this C1000 shows no spectacular differences with other supermarkets which is ideal to measure the effect of the external factor ‘chocolate’.
These results have given insight in the composition of the respondents and show similarities between the experiment situation and the real world situation. In addition, it can be concluded that this study is a relatively reliable reflection of supermarkets and feminine customers in today’s Dutch supermarket industry. Based on this understanding, the following results can be generalized over the majority of Dutch supermarkets.
4.2 Factor analysis
40
4.2.1 Cognitive response
To measure cognitive response, five attributes are discriminated based on theory: Tangibles; responsiveness; reliability; assurance; and empathy. Each attribute contains three questions in the questionnaire. These fifteen questions are all entered as communalities in the factor analysis. The component matrix extracted 5 different components. Hence, the total variance is explained by 5 different factors. This matches the five initial attributes. Additionally, the Cronbach’s alpha per attribute gives us more insight in the reliability of each attribute which is presented in TABLE 7.
TABLE 7 Factor analysis – Cognitive response (1.2 Appendix C)
Attribute Cronbach’s alpha New Cronbach’s alpha Tangibles 0.726 Responsiveness 0.713 Reliability 0.559 0.591** Assurance 0.792 Empathy 0.497 0.562* ***Assortment 0.763
*(EMPNEW) EMP2+EMP3; **(RELNEW) REL1+REL3; ***REL2+EMP1 makes ‘Assortment’
41 different attributes which each measure a different cognitive response. The presence of chocolate might have different effects on each one of them.
4.2.2 Affective response
For affective response, the same analysis is performed as above. The results present that the two attributes from theory were reliable. From the factor analysis, two perfect factors were excluded after entering the ten questions measuring the ‘affective response’ of customers in the supermarket. These two factors could be extracted by combining the 5 positive statements to one factor; and the negative statements to another factor. Combining the five positive statements created the attribute: ‘Positive affective response’ with a Cronbach’s alpha of 0.882. Hence, the other five negative statements make the new attribute: ‘Negative affective response’ with a Cronbach’s alpha of 0.801. Both Cronbach’s alphas are presented in TABLE 8.
TABLE 8 Factor analysis – Affective response (1.3 Appendix C)
Attribute Cronbach’s alpha Positive affective response 0.882
Negative affective response 0.801
4.2.3 Conative response
42 next to ‘donation’ which is ‘recommend’. Taking into account that ‘recommend’ involves only one question the Cronbach’s alpha is 1. From now on, conative response is divided into the three attributes ‘conative’;; ‘recommend’;; and ‘donation’.
TABLE 9 Factor analysis – Conative response (1.4 Appendix C)
Attribute Cronbach’s alpha New Cronbach’s alpha Conative response (CONATIVE) 0.787 0.843*
RECOMMEND 1
DONATION 1
*Conative without the statement “I would recommend this supermarket to my friends or family” 4.3 Regression analysis
Interpreting the results from the linear regression analyses gives insight into the causality of the relationship between sampling chocolate and the three different customers’ responses. The following results are presented per hypothesis. The fit of each regression is presented per attribute
4.3.1 Cognitive response
43 TABLE 10 Regression analysis – Cognitive response (2.1 Appendix C)
MAIN variables Tangibles R²: 0.083 p: 0.015 Reliability R²: 0.080 p: 0.020 Responsiveness R²: 0.094 p: 0.005 Assurance R²: 0.151 p: 0.000 Empathy R²: 0.149 p: 0.000 Assortment R²: 0.180 p: 0.000 CHOCTASTE α: 0.561 α: 0.532 α: 0.782 α: 0.725 α: 0.496 α: 0.429 PENPICK α: 0.694 α: 0.544 α: 0.476 α: 0.333 α: 0.614 α: 0.338 0-Condition α: 0.205 α: 0.416 α: 0.887 α: 0.865 α: 0.795 α: 0.005* β: 0.259 CONSOLE variables Day α: 0.677 α: 0.348 α: 0.363 α: 0.297 α: 0.386 α: 0.067 Store α: 0.507 α: 0.690 α: 0.194*** β: 0.098 α: 0.166 α: .194*** β: -0.075 α: 0.000* β: 0.464 Shopper α: 0.867 α: 0.743 α: 0.623 α: 0.019** β: 0.314 α: 0.204 α: 0.439 Frequency of visiting p/w α: 0.404 α: 0.186*** β: 0.039 α: 0.449 α: 0.703 α: .154*** β: 0.032 α: 0.032** β: -0.071 Loyalty α: 0.000* β: 0.059 α: 0.001* β: 0.052 α: 0.000* β: 0.053 α: 0.000* β: 0.059 α: 0.000* β: 0.057 α: 0.018* β: 0.040 Age α: 0.538 α: 0.981 α: 0.101*** β: 0.005 α: 0.009* β: 0.007 α: 0.041** β: 0.005 α: 0.572 Size of household α: 0.546 α: 0.157*** β: -0.053 α: 0.453 α: 0.642 α: 0.305 α: 0.200*** β: -0.053 Income α: 0.268 α: 0.326 α: 0.425 α: 0.643 α: 0.453 α: 0.057** β: 0.091 * = p/2< 0.01; ** = p/2< 0.05; *** = p/2:< 0.1
Interpreting TABLE 10 provides the insight that neither sampling chocolate nor sampling a pen will affect the cognitive attributes. Only sampling nothing will improve the perception of assortment significantly indicated by the low p-value and the accompanied positive beta β: 0.259 (TABLE 10). Moreover, most attributes are affected by the console variables which can be concluded from the low p-values of those causalities. However, tasting chocolate should have had effect upon the majority of the attributes in order to confirm hypothesis 1 but unfortunately it did not.
44 influence the cognitive response could be examined in future research. Nevertheless, it can be concluded that hypothesis 1 is not supported by the results of this analysis. Positive cognitive responses from customers are not evoked by sampling chocolate.
H1: Sampling of chocolate will evoke a positive cognitive response towards the supermarket.
4.3.2 Affective response
The second hypothesis consists of two parts: Hypothesis 2a assesses the effect of tasting chocolate upon enhancing positive affective responses; and hypothesis 2b assesses the affect of chocolate on weakening negative affective responses. Another regression analysis is performed in order to examine the relationship between the independent variables and the dependent variables which in this case are: positive affective response, and negative affective response. In TABLE 11 the p-values per causality are presented, remember that the significance levels are divided by 2 since this is a one-tailed test.
TABLE 11 Regression analysis – Affective response (2.2 Appendix C)
MAIN variables Positive affective response R²: 0.111
p: 0.001
Negative affective response R²: 0.085 p: 0.012 CHOCTASTE α: 0.068** β: 0.204 α: 0.141*** β: 0.134 PENPICK α: 0.100** β: -0.606 α: 0.406 0-Condition α: 0.967 α: 0.790 CONSOLE variables Day α: 0.422 α: 0.686 Store α: 0.524 α: 0.698 Shopper α: 0.225 α: 0.781 Frequency of visiting p/w α: 0.857 α: 0.046** β: 0.049 Loyalty α: 0.000* β: 0.075 α: 0.000* β: -0.047 Age α: 0.806 α: 0.390 Size of household α: 0.429 α: 0.692 Income α: 0.883 α: 0.069** β: -0.065 * = p/2< 0.01; ** = p/2< 0.05; *** = p/2:< 0.1
45 TABLE 11 also the corresponding Beta values are presented which gives insight in the nature of the causality.
The beta values in TABLE 11 indicate a positive causality between tasting chocolate and both positive (β: 0.204) as negative affective responses (β: 0.134). Hence, tasting chocolate evokes more positive affective responses but evokes more negative affective responses at the same time. Therefore, it can be stated that tasting chocolate makes affective responses more extreme. Furthermore, it is remarkable that picking a pen weakens positive affective responses (β: -0.606). However, since there are only three people in the entire experiment who have picked a pencil, this effect should be examined in future research. Considering the positive beta of the causality between tasting chocolate and positive affect, hypothesis 2a is supported. However, since the causality between tasting chocolate and negative affective response is positive it means that negative affective responses are strengthened instead of weakened. Based on this finding, hypothesis 2b is rejected. Sampling chocolate does not turn negative affect into more positive affect. Instead, tasting chocolate enhances the negative affect felt inside the supermarket. To conclude, customers who eat chocolate indicate their feelings to be more extreme compared to situations when there is no chocolate sampled. Therefore, in order to determine if tasting chocolate could indeed benefit the retailer, the effect of feelings of extreme affect in supermarkets needs to be assessed in future research. Nevertheless, based on the results of the current study hypothesis 2a is supported and hypothesis 2b is rejected:
H2a: Sampling of chocolate will strengthen positive affective responses towards the supermarket.
46
4.3.3 Conative response
In order to support the third hypothesis, again a regression analysis has been performed of which the results are presented in TABLE 12. Considering the main variables, the results in TABLE 12 show only a significant connection between picking a pencil and recommending the store to friends and family (α: 0.037/2< 0.05); and between sampling nothing and making a donation (α: 0.000/2< 0.01).
TABLE 12 Regression analysis – Conative response (2.3 Appendix C)
MAIN variables Conative R²: 0.435 p: 0.000 Recommend R²: 0.136 p: 0.000 Donation R²: 0.232 p: 0.000 TASTECHOC α: 0.281 α: 0.811 α: 0.343 PENPICK α: 0.970 α: 0.037** β: -1.251 α: 0.749 0-Condition α: 0.625 α: 0.947 α: 0.000* β: -0.240 CONSOLE variables Day α: 0.672 α: 0.188*** β: -0.101 α: 0.755 Store α: 0.740 α: 0.879 α: 0.087** β: -0.075 Shopper α: 0.862 α: 0.985 α: 0.258 Frequency of visiting p/w α: 0.970 α: 0.148*** β: -0.070 α: 0.054** β: -0.033 Loyalty α: 0.000* β: 0.216 α: 0.000* β: 0.144 α: 0.645 Age α: 0.595 α: 0.810 α: 0.000* β: 0.006 Size of household α: 0.849 α: 0.637 α: 0.136*** β: 0.032 Income α: 0.959 α: 0.457 α: 0.000* β: 0.149 * = p/2< 0.01; ** = p/2< 0.05; *** = p/2:< 0.1
47 Picking a pen does affect recommending which is specified in TABLE 12 where the beta of this causality is presented.
Moreover, the beta in TABLE 12 for picking a pen is negative (β: -1.255) which indicates that picking a pencil will decrease the chance one will recommend the supermarket to their friends or family. Again, this relationship should be examined in future research since there were only three individuals in the study who have picked a pencil. The causality between making a donation in the situation where nothing is sampled is negative, which implies that less people are willing to make a donation when nothing is sampled. This would mean that there is indeed a reciprocity effect and sampling anything is therefore better then sampling nothing in order to make customers more generous. However, since the other main variables PENPICK and CHOCTASTE show no causality with the dependent variable ‘donation’ it is not clear what a retailer is supposed to sample in order to enhance the willingness to donate. This could be examined in future research. Returning to answering the hypothesis about the effect of sampling chocolate on conative response, this hypothesis is not supported in this study. Therefore Hypothesis 3 will be rejected:
H3: Sampling of chocolate will evoke a positive conative response towards the supermarket
Positive conative responses are not evoked by sampling chocolate. 4.4 Extra analysis
48 the chocolate but have decided not to eat it, then people who have tried a piece. If it is necessary for retailers to make customers eat the sample of chocolate will be examined in this last subchapter before the conclusion. Since theory expects that smell has an important effect on mood and other unconscious processes inside the brain (Herz 2007), insight in the effect of passing the chocolate; seeing it; and likely smelling it, will complete this study.
4.4.5 Cognitive response
Again, a regression analysis is performed. This time the main variables CHOCTASTE and PENPICK have been changed in SAWCHOC and SAWPEN. These variables include all people who were in the chocolate situation and indicated they have seen the chocolate and the same for the respondents in the pencil situation. From the regression analysis concerning the attributes of cognitive response, one significant causality is detected with one of the main variables. TABLE 13 shows that seeing chocolate has had an effect on the perception of reliability. The beta of this causality (β: 0.127) specifies that this causality is positive and that the perception of reliability will increase when customers see that chocolate is being sampled.
TABLE 13 Regression analysis – Cognitive response towards seeing chocolate (3.1 Appendix C)
49 Age α: 0.558 α: 0.938 α: 0.110*** β: 0.005 α: 0.011* β: 0.007 α: 0.038** β: 0.005 α: 0.661 Size of household α: 0.540 α: .139*** β: -0.055 α: 0.453 α: 0.635 α: 0.311 α: 0.116*** β: -0.066 Income α: 0.295 α: 0.303 α: 0.464 α: 0.722 α: 0.493 α: 0.032** β: 0.103 * = p/2< 0.01; ** = p/2< 0.05; *** = p/2:< 0.1
In addition, from this study it can be concluded that retailers cannot improve the total cognitive response by sampling chocolate. However, placing chocolates on a visible location will help increasing the perception of reliability. Whether this effect is the result of conscious deliberation of the store characteristics, or unconscious processes in the brain evoked by seeing and smelling chocolate, should be examined in future research.
4.4.6 Affective response
Next, another regression analysis is performed using the same independent variables as the above analysis but using ‘positive affective response’ and ‘negative affective response’ as dependent variables. The results are outlined in TABLE 14. A significant causality is detected between seeing chocolate and both positive and negative affective responses (α: 0.018/2< 0.01; and α: 0.034/2< 0.05). Again, seeing a pen affects only the positive affective response (α: 0.094/2< 0.05).
TABLE 14 Regression analysis – Affective response towards seeing chocolate (3.2 Appendix C)
MAIN variables Positive affective response R²: 0.123
p: 0.000
50 To determine the nature of the relationship, the beta’s for each of the significant causalities are also computed and presented in TABLE 14.
TABLE 14 shows positive beta’s for seeing chocolate and both positive and negative affective response (β: 0.211;; and β: 0.154). At the same time, seeing a pen will decrease positive affective response (β: -0.208). These relationships, apart from slightly different betas, followed also from the regression analysis with tasting chocolate and picking a pen. Therefore, it can be stated that there is no difference in tasting chocolate or seeing chocolate and there is no reason to make customers try the chocolate, as long as female customers see that it is provided it will already have the same effect of making feelings felt inside the supermarket more extreme.
4.4.7 Conative response
At last, another regression analysis is performed considering conative responses and seeing chocolate and seeing the pen of which the results are presented in TABLE 15.
TABLE 15 Regression analysis – Conative response towards seeing chocolate (3.3 Appendix C)
MAIN variables Conative R²: 0.438 p: 0.000 Recommend R²: 0.121 p: 0.000 Donation R²: 0.180 p: 0.000 SAWCHOC α: 0.374 α: 0.861 α: 0.085** β: 0.092 SAWPEN α: 0.249 α: 0.711 α: 0.024** β: 0.169 CONSOLE variables Day α: 0.480 α: 0.178*** β: -0.104 α: 0.421 Store α: 0.811 α: 0.912 α: 0.191** β: -0.059 Shopper α: 0.908 α: 0.892 α: 0.236 Frequency of visiting p/w α: 0.941 α: 0.188*** β: -0.064 α: 0.095** β: -0.030 Loyalty α: 0.000* β: 0.215 α: 0.000* β: 0.145 α: 0.540 Age α: 0.620 α: 0.923 α: 0.000* β: 0.006 Size of household α: 0.780 α: 0.704 α: 0.134*** β: 0.033 Income α: 0.989 α: 0.549 α: 0.000* β: 0.140 * = p/2< 0.01; ** = p/2< 0.05; *** = p/2:< 0.1
51 The accompanying beta’s presented in TABLE 15 indicate that both relationships are positive.
Seeing that something is sampled has an effect on the willingness to donate unlike tasting it or picking it. This would, support the reciprocity effect that customers are more willing to donate money to charity when they are being offered a ‘gift’ (Fennis and Stroebe 2010). For a retailer, this could mean that he should give customers the idea that he provides them something extra or a gift in order to make these customers more generous. However, if making a donation to charity has a connection to buying more groceries or spending more money in the supermarket can be subject of another study.
4.5 Overview of the results
Before proceeding to the general conclusion a small overview is presented in TABLE 16, which summarizes the results.
TABLE 16 Overview of the results
Hypotheses Supported Yes/No Conclusion H1: Sampling of chocolate will evoke a
positive cognitive response towards the supermarket.
No Chocolate did not affect the
majority of the cognitive attributes
H2a: Sampling of chocolate will strengthen positive affective responses towards the supermarket.
H2b: Sampling of chocolate will weaken negative affective responses towards the supermarket
Yes No
Seeing and eating chocolate enhanced positive affective response. However chocolate also enhanced negative affective response instead of weaken this response.
H3: Sampling of chocolate will evoke a positive conative response towards the supermarket
No No causality is found between
tasting chocolate and conative response
53
5. Conclusion
Following up the results, the next chapter will discuss some concluding remarks comparing the findings of this study with the theory. Each hypothesis will be discussed in their own sub chapter. In the last sub chapter, a conclusion is drawn considering the problem statement: Does chocolate affect customer experience? This conclusion can be very useful for food retailers who are searching for ways to create customer value in order to survive the heavy competition in the supermarket industry.
5.1 The effect of chocolate on cognitive response
54 Merging this theory with the results, it can be concluded that cognitive responses are not influenced by processes inside the orbitofrontal cortex which is activated by chocolate. Therefore, because the effect of sampling chocolate on cognitive responses is not fully proven, there is no guarantee that the profit from enhanced evaluation of the supermarket will be higher than the costs of the sampled chocolate. Hence, it not advised to retailers to sample chocolate in order to enhance objective evaluation because there is no certainty yet about the strength of the relationship between sampling chocolate and enhancing the cognitive response.
5.2 The effect of chocolate on affective response
55 sample. Moreover, whether food lifts mood or threatens mood might indeed rely on the affective state of the customer at that time (Garg et al. 2007). Furthermore, since chocolate is a fat and hedonic food, happy people might want to navigate away from it (Tice et al. 2001). This effect might have caused the strengthened negative affect with happy people. If this effect holds true should be examined in future research. Remarkably, sampling pencils decreased the positive affective response while sampling nothing did have no effect on affective responses. This result confirms the assumption that the orbitofrontal cortex is activated by seeing and eating chocolate since nothing happened when chocolate was unavailable. Hence, the emotions evoked by seeing and tasting chocolate have been evaluated in the orbitofrontal cortex which has resulted in significantly more positive and significantly more negative emotions felt in the supermarket (Bechara et al. 2000; Kringelbach et al. 2003). The effect of taste and sight of chocolate is supported by the fact that sampling pencils did affect the mood of consumers only less extremely. Accordingly, since pencils have no taste it can explain the detail that moods were less extremely formed.
56 5.3 The effect of chocolate on conative response
Conative responses are not affected by sampling of chocolate. In addition, picking a pencil will negatively influence the willingness to recommend the supermarket to others. However, since the amount of respondents who have picked a pen is very low, this effect can be neglected. Nevertheless, the effect of sampling on the extra variable ‘willingness to donate’ is remarkable. The willingness to donate to charity decreases when nothing is sampled. In return, the willingness increases when the respondents have seen the plateau with the chocolates or the pencils on it. However, tasting this chocolate or picking the pencil has no significant effect. Therefore, putting the samples on a visible location will be enough for the retailer to enhance the generosity of customers towards charity. If the willingness to donate spreads over towards the willingness to buy it would comply with the theory of Grewal et al. (2009) who said that favorable attitudes lead to actual sales. Baker et al (1992) confirm this by arguing that affective states influenced by the supermarket environment affect consumer’s willingness to buy. However, only the willingness to donate has increased when chocolate was sampled while the other elements did not change. For a retailer this means that he should not sample chocolate when his goal is to enhance word of mouth, liking of the store, and future shopping intentions. Only when he wants customers to contribute to charity he should consider sampling chocolate at the same time.
5.4 The effect of chocolate on customer experience
