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Drivers of retail store loyalty: The moderating

influence of product category involvement

What is the effect of product category involvement on the relationship between retail store image and retail store loyalty?

29-06-2016

Author: Milo van der Zanden (10372288) Bachelor thesis Business Administration

University of Amsterdam, faculty of Economics and Business BSc Business Administration

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Statement of Originality

This document is written by Milo van der Zanden who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

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Abstract

Store image is assumed to be based on a consumer’s perception of the characteristics of a store. How consumers perceive retailers after their purchase is one of the key determinants of consume loyalty. However, with varying levels of product category involvement, a favourable perception of a specific store characteristic might be more or less influential on consumer loyalty. The results of an analysis of survey data from 7.579 respondents and 21.238 rankings and reviews of 206 retailers across 29 sectors suggest that product category involvement has a moderating effect on the store image-consumer loyalty relationship for some of the characteristics of store image. Furthermore, it is found that the strength of the effect varies between two distinct constructs of consumer loyalty, namely repurchase intention and word-of-mouth intention.

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Page | 4 Table of contents 1. Introduction 5 2. Theoretical framework 8 2.1. Consumer loyalty 8 2.2. Store Image 11 2.3. Involvement 13

2.4. Moderating role of involvement 14

3. Methodology 20

3.1. Design and procedure 20

3.2. Data characteristics 21

3.3. Measures 22

3.4. Data analysis and predictions 24

4. Results 25

4.1. Descriptive statistics 26

4.2. Test of hypotheses 27

5. Conclusion and Discussion 38

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1. Introduction

The brick-and-mortar retail industry has suffered from the economic recession. And even though the consumer confidence has been increasing again, some big and well known retailers have been declared bankrupt in the last year (e.g. Circuit City in the US and V&D in The Netherlands) (Gustafson, 2016). Competition is tight and online pure players take away market share from traditional brick-and-mortar retailers (Wahba & Kell, 2016). It seems that retailers who survive and stand out in their market are those with loyal consumers. Only a few retailers per sector have a truly loyal consumer base. For 80% of the retailers it is quite unlikely that their consumers do their next purchase in the same store because very often, consumers easily switch from one store to another (Libbenga, 2014; Quix, 2015). Research to consumer loyalty therefore remains evident.

Researchers believe consumer loyalty is one of the most important factors influencing on the success of retail stores (Reichheld, 1992; Azad, Kasehchi, Asgari & Bagheri, 2014), and it is therefore that a lot of attention has already been given in scientific research to the relationship between consumer loyalty and the long-term financial performance of a firm and more specific, to which factors can be seen as drivers and determinants of consumer loyalty (Dick & Basu, 1994). Store image is one of these drivers (Bloemer & de Ruyter, 1997). In his model of the retail marketing mix, Ghosh (1990) suggests that the store image is formed by consumers’ perception about several characteristics of a store, such as price, merchandise or service. In this sense, a key challenge is to identify and understand how these controllable variables influence loyalty.

A lot of authors already investigated and proved the influence of characteristics of store images on consumer loyalty (Bloemer & de Ruyter, 1997; Macintosh & Lockshin, 1997; Heskett, Jones, Loveman, Sasser, & Schlesinger, 2008). However, most of the studies concentrated on the relationship between one or more store image characteristics on consumer loyalty in general and to a what lesser extent on the differences of this relationship between retail sectors. Carpenter (2008) already named this as a suggestion for future research. One way to distinguish retail sectors from each other is by looking to degree of

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Page | 6 involvement consumers have with the products purchased. Also, involvement is commonly acknowledged as being a key determinant in consumers’ shopping behaviour (Celsi & Olson, 1988). It is therefore even more surprisingly that research on the influence of product category involvement on the relationship between store image and consumer loyalty has remained limited. Involvement with products is expected to lead consumers to search for more information and spend more time searching for the right purchase (Celsi & Olson, 1988). Thus, product involvement is likely to affect the store image-loyalty relation by increasing or decreasing the direct and indirect effects that several characteristics of a store its image have on consumer loyalty (Suh & Youjae, 2006). The identification of these differences is necessary because what holds for one retail sector, might not be the case for another, and this impacts the strategy that retailers should be following in the battle for consumer loyalty. This study will therefore propose a model that describes the relationship between nine individual elements of store image and consumer loyalty, taking into account the moderating effect of product category involvement. Furthermore, rather than measuring consumer loyalty as an universal construct, consumer loyalty will be divided into two distinct constructs, namely repurchase intention and word-of-mouth intention. Söderlund (2006) mentioned that these are the two most important discrete constructs of (attitudinal) consumer loyalty in the retail industry, and Clottey, Collier and Stodnick (2008) already acknowledged that differences in findings in past research to consumer loyalty might be partly explained by the use of different definitions of consumer loyalty, which is why this study will take into account repurchase intention as well as word-of-mouth intention.

This study will use reviews and rankings of retailers given by consumers as a data source to test the hypotheses and to fill the gap as proposed above. Reviews form an excellent way to measure consumers’ perception of retail stores (Barton, 2006). From a scientific perspective this study will add to the existing theories about the effect of store image on consumer loyalty by describing the differences of this effect between retail sectors, which will form a basis upon which future research can build. Authors can for example investigate why several differences do or do not occur. Besides the theoretical implications,

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Page | 7 retail management practice might learn from this study and use the results in their battle of building a loyal consumer base by knowing exactly which characteristics are more important for their product category.

The article is structured as follows. First of all, based on a review of literature, a brief outline of the constructs of loyalty, store image and involvement is offered. Subsequently, the focus will shift to the moderating effect of involvement on the relationship between nine individual characteristics of store image and consumer loyalty. Third, the research method, data characteristics and validation of measures will be described. Then the results of an empirical study that was undertaken to test the research hypotheses will be discussed. In conclusion, the theoretical and managerial implications of our findings will be addressed in the discussion section. The same goes for the limitations of this study and suggestions for future research.

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2. Literature review

To start the literature review, the construct of consumer loyalty and its importance for retailers is explained. Further attention is given to the definition of loyalty and its antecedents. Afterwards the construct of store image and its relationship with consumer loyalty introduced. Involvement is the last construct that will be added and propositions about the moderating effect of involvement on the relationship between each characteristic of store image and consumer loyalty are made.

2.1 Consumer Loyalty

A lot of authors active in the area of marketing and consumer behaviour have given attention to the definition of (consumer) loyalty in the past decades, but a consensus about the definition of loyalty has not yet emerged, yet they seem to have at least one thing in common: they all point at a the continuous relationship between a consumer and a specific object (e.g. a brand, a product, a retailer, etc.). One of the reasons why it is difficult to state a general definition of loyalty is that it knows different constructs (Jacoby, 1971). In a research by Jacoby and Chestnut (1978) the authors tried to capture all of the proposed definitions of loyalty in one literature review in which they cited 53 different definitions of loyalty. More recently Dick and Basu (1994) tried to combine different dimensions of definitions into one integrated conceptual framework. Even though this is difficult, some basic classifications of consumer loyalty can be made. It is important to first make a distinction between actual repeat visiting behaviour and loyalty.

In the beginning, researches such as Ehrenberg (2000) only addressed to behavioural loyalty. Researchers only looked at actual behaviour and the common believe was that repeat purchasing was the only measure of the loyalty of a consumer towards the brand of interest (Bandyopadhyay & Martell, 2007). Loyalty was thus seen as a deeply held commitment to rebuy or patronise a preferred product or service in the future (Oliver, 1997). But actual repurchases is not the only measure of consumer loyalty. Emotional and situational factors also influence the way consumers think about brands or products. These

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Page | 9 factors influence how consumers create an image of- and attitude towards the brand or product of interest (Oliver, 1999). Day (1969) was one of the first authors to acknowledge that this attitude also influenced how loyal consumers actually are and the concept of attitudinal loyalty was introduced. Researchers tried to combine the two constructs into one definition of loyalty. Nowadays, the most used definition of loyalty is the composite definition of brand loyalty, which was first proposed by Jacoby (1971). His definition captures the most important constructs (behavioural and attitudinal) in consumer loyalty (Bandyopadhyay & Martell, 2007). Based on his definition, (Bloemer & de Ruyter, 1997) mention the following definition for retail store loyalty:

“The biased (i.e. non-random) behavioural response (i.e. revisit), expressed over time, by some decision-making unit with respect to one store out of a set of stores, which is a function of psychological (decision making and evaluative) processes resulting in brand commitment.”

Retailers are very interested in research to store loyalty, because loyal consumers really contribute to a retailer its sales and profitability (Reichheld, 1992), and almost every retailer strives for loyal consumers (Reicheild, 1992; Azad et al., 2014). First of all, retaining loyal consumers is economical more favourable because retaining consumers is often less expensive than attracting new consumers (Reichheld & Sasser, 1990, 2000). Moreover, a loyal consumer base has a lot to offer for a retailer. Loyal consumers are less price sensitive, provide a stable income due to repeat purchases, engage in positive word of mouth and can possibly provide a retailer with valuable information (Reichheld & Sasser, 1990; Yin, 1999; Jones, 1996). Besides, it is a fact that companies with loyal consumers grow faster than others (Jones, 1996). Because of these advantages, it is evident to understand why consumers are loyal and how they express this loyalty(Smith, Sparks, Hart, & Tzokas, 2003). Söderlund (2006) stated that consumer can form intentions to express their loyalty by performing several behavioural acts, such as word-of-mouth, repatronage, repurchasing,

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Page | 10 increasing the future purchase volume and providing feedback to a supplier. Two of these constructs have been especially popular indicators of loyalty in existing literature, namely repurchase intention and word-of-mouth intention. Söderlund (2006) mentioned that these are the two most important discrete constructs of (attitudinal) consumer loyalty in the retail industry. Repurchase intention can be described as individual its judgement about to repurchasing a product at the same retailer (Hellier, Geursen, Carr & Rickard, 2003) . And word-of-mouth intention is a consumer its willingness to recommend the retailer to his friends and family (Gruen, Osmonbekov & Czaplewski, 2006). It should be noted that both construct are different measures of consumer loyalty. The main reason is that the behaviours they refer to are different: repurchasing behaviour has to do with a consumer moving himself to get in contact with a supplier again, while word of mouth behaviour has to do with talking with others (Söderlund ,2006).

A lot of academics have already investigated what the drivers and determinants of repurchase intention and word-of-mouth intention in the retail industry are. (Clottey et al. 2008), and one constructs that has often been regarded as an antecedent of consumer loyalty is the construct of store satisfaction. Store satisfaction is key for securing consumer loyalty and generating and maintaining a competitive advantage. (Mittal & Kamakura, 2001; Szymanski & Henard,2001; Heskett et al., 2008). Moreover, consumer loyalty is a direct result from store satisfaction (Heskett et al., 2008), since satisfied consumers are more positive to others about the retailer (word-of-mouth intention) and satisfied consumers are more willing to go back to the same retailer (repurchase intention). Engle, Blackwell & Minuard (1990) defined store satisfaction as follows:

“The outcome of the subjective evaluation that the chosen alternative (the store) meets or exceeds expectations”

This definition flows directly out of the disconfirmation paradigm (Oliver, 1980), which implies that satisfaction occurs through a matching of expectations and perceived performance of a

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Page | 11 retailer. So satisfaction comes as a result of past purchase and is based on a consumer his evaluation of a store. This evaluation results in the consumer creating an overall image of a retailer/store. Store image is therefore also found to be a determinant of consumer loyalty. Store satisfaction is thus a mediator of the store image-consumer loyalty relationship (Bloemer & de Ruyter, 1997).

2.2 Store Image

Store image is expressed as a function of the important characteristics of a particular store that are evaluated and weighted against each other (Keaveney & Hunt, 1992). This definition is in line with research of other authors. As time passed by, different authors have identified different characteristics that are part of the overall image of a store. The combination of these characteristics are also called the retail mix and for each retail store a distinct image may exist within the mind of consumers (Bloemer & de Ruyter, 1997). The characteristics of store image as suggested by Lindquist (1974), Doyle and Fenwick (1974), Bearden (1977) and more recently by Ghosh (1990) in his model of the retail marketing mix are summed up in the following table.

More recently, Quix and van der Kind (2012) also suggested nine characteristics which they consider the most important drivers for consumers evaluating stores (i.e. creating store image). These nine aspects are price-quality ratio, price level, promotions, expertise of staff, customer-friendliness, service, assortment, experience and accessibility of location. Table A

Lindquist (1974) Doyle and Fenwick (1974) Bearden (1977) Ghosh (1990)

Merchandise Assortment Assortment Merchandise

Promotion Price Price Price

Service Styling Friendly personnel Customer service

Physical facilities Location Atmosphere Personal selling

Comfort Product Location Store atmosphere

Store atmosphere Parking facilities Advertising

Institutional satisfaction Quality of merchandise Sales incentive -programs.

Post-transaction satisfaction Location

Clientele

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Page | 12 These characteristics are quite similar to Ghosh (1990) his well-accepted model of the retail marketing mix. They are also in line with Jacoby (1986) his three general factors of store image: merchandise-related aspects (e.g. price, quality, assortment), service-related aspects (e.g. expertise of staff, customer service), and pleasantness of shopping at a store (e.g. ambiance, experience). The characteristics as suggested by Quix and van der Kind (2012) can therefore be seen as valid. Most characteristics explain themselves, but following is how they are defined by Quix and van der Kind (2012). Price quality-ratio is the quality of the products offered by a retailer compared to the price of these products. Price level is the consumer its perception about the product prizes of a retailer compared to its competitors. Promotions are the discounts offered by a retailer. Expertise of staff is the knowledge, experience and qualifications a salesperson has to help the consumer with his purchase. Customer-friendliness is how friendly the salesperson is while interacting with the consumer. Service is the level of service quality, meaning how well a retailer is able to further assist a consumer its needs. Assortment is the quality, range and change of products sold by a retailer. Experience is a consumer its shopping experience, whether he enjoyed it and whether it was fun. Accessibility of location is how easily a store can be reached by a consumer.

A consumers’ intention of expressing loyal behaviour towards a particular store depends on the store image of that particular store. A more favourable perceived store image results in a bigger chance of loyal behaviour from consumers (Bloemer & de Ruyter, 1997). It is also proven that the individual characteristics of store image have an effect on consumer loyalty (i.e. a more positive perception of one of the characteristics results in a more loyal consumer) (Clottey et al., 2008; Jones & Sasser, 1995), and the same results are expected in this study.

Of these characteristics, service quality and assortment are the two characteristics that are mostly mentioned as being the most important for consumer loyalty (Ghosh, 1990; Heskett et al., 2008); Sirohi, McLaughlin & Wittink, 1998). Retailers have to meet the consumers’ expectations on these aspects if they want them to be satisfied, and thus more

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Page | 13 likely to become loyal. But, also the other elements have to meet the expectations of consumers in order for them to become loyal (Bloemer & de Ruyter, 1997).

However, few studies investigating the relationship between one or more characteristics of store image on consumer loyalty account for the differences between retail sectors. Carpenter (2008) already named this as a suggestion for future research. Some researchers say assortment is the most important aspect of store image (Ghosh, 1990) and others say that service is more important (Heskett et al., 2008). But these statements cannot be generalized for all sectors in retailing. In some sectors price is more important than in others, but in others service is more important. Some industries are characterised by convenience shopping while others offer specialty goods. One construct to classify different retail sectors is the level of involvement a consumer has with the products bought at a retailer.

2.3 Involvement

As said the impact of theories applying to consumer behaviour in the retail industry differ per sector, because consumer behaviour differs between purchases which require rational thinking and (extensive) evaluation to make a reasoned decision and those that are relatively standard (Zaichkowsky, 1985). This variance in consumer behaviour is partly due to the degree of involvement and the degree to which involvement differs among brands and categories (Kotler, 2000). Involvement is generally defined as ‘the degree of personal relevance, interest and/or subjective feeling of importance of the product category or purchase decision’ (Petty, Cacioppo, & Schumann, 1983; Zaichkowsky, 1985).

For one sector within retailing, a consumer might be highly involved with the products offered, but the involvement with the products might be low in another sector. Kotler (2000) explained the differences in the consumer decision making process between high and low involvement purchases. Het states that, in general, a consumer is highly involved with the products offered when the product is expensive, not bought frequently, self-expressive and tricky to buy. Purchasing high involvement products require consumers to first gather

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Page | 14 information and develop an image of the product. Consumers will develop an attitude towards the product before they actually make a carefully considered decision. Examples of products which fall in the high involvement category are electronics and jewellery. Contradictory, when consumers easily switch between brands and do only little evaluation before purchases, then consumers are considered to be only little involved with the products offered. This is mostly the case for convenience products such as groceries or gifts.

2.4 The moderating role of involvement

Involvement has already been regarded as one of the important moderators that determine purchase decisions (Celsi & Olson, 1988). However, no research has been done to investigate the moderating role of involvement on the effect that store image characteristics have on consumer loyalty. High involvement with products is expected to lead consumers to search for more information and spend more time evaluation the options (Celsi & Olson, 1988). Therefore, product involvement is likely to affect the relationship between store image and consumer loyalty by increasing or decreasing the direct and indirect effects of the characteristics of store image on satisfaction, repurchase intention and word of mouth intention. The remaining of this section elaborates further on the proposed moderating role of involvement on the relationship between each individual characteristic and consumer loyalty. The direction of the moderating role of involvement is expected to be the same for repurchase intention and word-of-mouth intention. The strength however is likely to vary between the two.

As stated, low involvement with a product category will result in limited information processing with little searching and evaluation (Kotler, 2000; Bennettt Hartel & McColl-Kennedy, 2005; Oliver, 1997). As a result, only a few price dimensions will be relevant for consumers. On the contrary, when consumers feel a high purchase risk, and when involvement with the product is high, they will make complex purchase decisions. In the latter case, more price dimensions will be relevant, when compared to limited

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decision-Page | 15 making. The price dimensions in the model by Quix and van der Kind (2012) are price level, promotions and price-quality ratio.

The first two are purely price related, whereas the last one also has a dimension of product quality. A favourable perceived price level, when measured at a comparative basis, has a direct and positive effect on repurchase intention

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Jiang & Rosenbloom, 2005). In low involvement categories, consumers evaluate prices less, they notice less price differences and care less about those differences. Also due to the generally lower prices, they perceive lower purchasing risk (Lockshin, Spawton & Macintosh, 1997). In high involvement categories consumers compare prices more extensively. As a result consumers experience more favourable differences in price level in high involvement categories. Buying a product with a favourable relative price level compared to other stores therefore results in a greater feeling of satisfaction for high involvement purchases. And since satisfaction is a driver of loyalty intentions (Heskett et al., 2008) it is therefore proposed that:

H1: The effect of a favourable perceived price level on consumer loyalty is more positive in high involvement categories.

Promotions are often used to attract new consumers to the store and to get them acquainted with the store, hoping that consumers return and tell others about their purchases (Buil, De Chernatony & Martínez , 2013). Since consumers who are highly involved with products are expected to search for more information and spend more time searching for the right selection (Celsi & Olson, 1988), these consumers are less prone to have their decision leaded by promotions and discounts. Consumers who are satisfied after performing a low involvement purchase after a promotion are likely to show loyal behaviour because they spend little time evaluating alternatives the next time. On the other hand, since highly involved consumers spend more time searching for information, the effect of the

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Page | 16 promotions will be of less influence on their future behaviour. This leads to the second hypothesis:

H2: The effect of promotions on consumer loyalty is less positive in high involvement categories.

Positively perceived product quality is proven to positively influence consumer loyalty (Sirohi et al., 1998). Consumers do more extensive research about the attributes and price of the products offered when the involvement with the product category is high (Celsi & Olson, 1988; Kotler, 2000). They are therefore more attracted by a particularly favourable price-value ratio than consumers in low involvement categories, who do not have this knowledge to such a large extent (Chandrashekaran & Grewal, 2003). Moreover, consumers have higher expectations about the quality of the products bought in high involvement categories, due to the extent of research beforehand. It is important to fulfill these expectations for consumers to be satisfied (Oliver, 1981; Bloemer & de Ruyter, 1997). The effect on satisfaction of meeting the quality expectations are bigger in high involvement categories. With regard to consumer loyalty it is therefore hypothesized that:

H3: The effect of price-quality ratio on consumer loyalty is more positive in high involvement categories.

Some authors mentioned assortment (or merchandise) as an important factor influencing the image of a store (Lindquist, 1974; Doyle and Fenwick, 1974; Bearden, 1977; Ghosh 1990). But consumers evaluate the assortment differently according to their level of involvement with the product category. It is very unlikely for consumers in low involvement categories to make active assortment perceptions each time they are at a store. They will do so only if there is a major change of products offered (Broniarczyk, Hoyer & McAlister, 1998). It is therefore evident for retailers in low involvement categories to sell the products the

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Page | 17 consumers need. Moreover, those retailers need to have the products their consumers expect them to have. If consumers go to a store which does not offer the products they expect them to offer, consumers will be dissatisfied (Diehl & Poynor, 2010). It is therefore that consumers in low involvement categories will be most satisfied with and loyal to the retailers that meet these basic expectations. Swoboda et al. (2009) already argue that the influence of assortment on retail brand equity is greater for lower levels of involvement. Well-informed (high involved) customers do not to require a particularly wide assortment because their perception is already formed on the basis of the various information they have gathered (Swoboda et al., 2009). In other words, the influence of assortment on a consumer his satisfaction level is smaller in high involvement categories. Thus, the influence of assortment on consumer loyalty is most likely greater in low involvement categories. Consequently:

H4: The effect of assortment on consumer loyalty is less positive in high involvement categories.

The concept of service in the model of Quix and van der Kind (2012) consists of three sub-concepts namely, service quality, expertise of staff and customer-friendliness of staff. These sub-concepts are in line with sub-concepts used in other research (Swoboda et al., 2009). The perceived service quality is found to be a predictor of consumer behaviour and thus, of repurchase and word-of-mouth behaviour. The same goes for sales personnel (Bitner, 1990; Dick & Basu). It is found that in low involvement categories, treating each consumer as a unique individual does not add much to the behaviour of a consumer. Neither does it result in a higher pay off. On the other hand in situations where involvement is high, it does pay off to give a consumer more personal treatment and excellent service (Solomon, Surprenant, Czepiel & Gutman, 1985). Assisting consumers with their needs by means of excellent service provided by friendly and experienced personnel leaves consumers satisfied in both low and high involvement categories. However, the service delivered is more valued

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Page | 18 in high involvement categories and the satisfied feeling of the consumers is greater and stays longer. Consequently, the following relationships are expected:

H5: The effect of service quality on consumer loyalty is more positive in high involvement categories.

H6: The effect of expertise of staff on consumer loyalty is more positive in high involvement categories.

H7: The effect of customer-friendliness of staff on consumer loyalty is more positive in high involvement categories.

It is proven that a satisfactory in-store shopping experience has a direct positive influence on satisfaction and also an indirect positive influence on consumer loyalty (Terblanche & Boshoff, 2006). For high involvement purchases consumers should be more attentive to the quality of the shopping experience (i.e. badness or goodness) (Swinyard, 1993). Highly involved consumers are also more prone to differences in the quality of a shopping experience. A good shopping experience is therefore likely to lead to greater satisfaction for highly involved consumers because they had bigger expectations, and thus:

H8: The effect of experience on consumer loyalty is more positive in high involvement categories.

The accessibility of the location of a store is important for retailers and consumers, but this importance declines when the importance of the other characteristics increase (Swoboda, Berg, Schramm-Klein & Foscht, 2013). Consumers choosing a store for the accessibility of the location are generally seen as fake loyals. They seem loyal to a store but as soon they are at another location, this loyalty erodes. This is typically the case for supermarkets, for whom location is a big part of their strategy and profitability. Supermarkets are an example of a low involvement category. On the other hand, the accessibility of the

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Page | 19 location for a high involvement category such as jewelleries is probably less influential on consumer loyalty. The last hypothesis is therefore quite straightforward.

H9: The effect of accessibility of location on consumer loyalty is less positive in high involvement categories.

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3. Methodology

The methodology section is build up as follows: first the study design and the procedure of data collection will be described. Then some general characteristics of the data will come forward, which is followed by how the variables of this study are measured. To conclude the methodology, the tests that will be used in the analysis are given.

3.1 Design and procedure

To answer the research question and hypotheses, a cross-sectional survey is used. This survey had already been send out by Q&A research & consultancy and the data coming from this survey will be used in this study. The use of this survey is valid, because the use of a survey enables the possibility to explain how factors are related. A survey makes it easy to compare the answers of a large amount of people and is therefore a good strategy to collect data for this study (Saunders et al., 2012, p. 177). The method used to develop the questionnaire is the internet-mediated method. An online questionnaire was used because it is easy to use for respondents and because the gathered data does not have to be entered manually afterwards it will save a lot of time (Sauders et al. 2012, p. 422). A survey makes it easy to reach a lot of different people in a quick manner (Saunders et al., 2012, p. 177). The questionnaire was self-administered because a questionnaire is completed faster when respondents fill in the questions themselves. This was possible because most of the questions were ranking and/or scaling questions. Limitations of using a questionnaire in this study involve the length of the questionnaire. Most people are unwilling to fill in long questionnaires (Saunders et al., 2012, p. 178).

The questionnaire was designed to gather reviews and rankings about more than 200 retailers active in the Netherlands. These reviews and rankings form a great source of information to study aspects influencing consumer loyalty. Only a part of the data gathered will be used to measure the hypotheses. The complete survey was designed as follows: first, respondents had to indicate in which retail sectors they have visited shops within the past twelve months. Respondents then had to pick all the retailers in these sectors with which

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Page | 21 they were familiar enough to give an evaluation about. The system then randomly selected a maximum of four retailers. Respondents had to answer some questions about these stores. To indicate which sectors respondents had visited, they could choose from a set of 29 categories. To identify differences between sectors respondents had to pick from a set of nine store related aspects to indicate which aspects they considered most important while shopping in a certain category. These nine aspects are price-quality ratio, price level, promotions, expertise of staff, consumer-friendliness, service, assortment, experience and accessibility of location. These aspects are considered to the most important shopping aspects (Quix and Van der Kind (2012). These same aspects were also used to ask respondents how they evaluated the performance of retailers. Besides, this evaluation respondents were also asked to what extent they would recommend a retailer to friends and family and how likely it would be that they would shop again at the same retailer for their next purchase. They also had to indicate whether a retailer was distinctive, made them happy, was evident in their shopping area and needed to have a webshop. Furthermore they had to answer questions about how often they visited a retailer, whether this has increased in the last year, what delivery method they preferred and how they interacted with a retailer (e.g. loyalty programs and social media). To conclude, respondents were asked about their gender, age and postal code.

Only the demographics, importance of aspects, scores on aspects, word-of-mouth intention and repurchase intention will be used to test the hypotheses. Additionally, levels of involvement have been identified per sector (high/medium/low involvement) based on the knowledge of retail experts. The next section will first provide some (demographic) characteristics of the data collected.

3.2 Data characteristics

The data required to test the propositions has already been collected by Q&A research & consultancy, a Dutch research company specialized in online research for retail, through the means of a self-administered questionnaire. The questionnaire has been send out to Q&A its

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Page | 22 independent consumer panel, which consists of over 145.000 members with an interest in (online) shopping, which makes it a unique instrument for research regarding (online) retailing. A total of 7.579 valid consumers filled in the questionnaire and gave at total of 21.238 rankings and reviews about 206 retailers across 29 different sectors. The distribution between males and females in the sample was 49,2% males versus 50,8% females

3.3 Measures

This section will describe the measures used for the variables in the order of which the questions have been asked in the questionnaire.

3.3.1. Demographic and additional variables

Demographics should also be accounted for, because they might influence the dependent variables of repurchase intention and word-of-mouth intention. Derived from Saunders et al. (2012) gender is measured on a binary scale in which “1” is male and “0” is female. Age is measured on a nominal interval scale, as it is measured by date of birth. This data had been modified to four age categories. From 16 to 29, from 30 to 44, from 45 to 60 and above 60. Postal code was asked as an open question in which the answer needed to contain 4 digits.

3.3.2. Ranking on store characteristics

To measure the performance of retailers according to consumers scores on nine store aspects have been gathered. These nine aspects are price-quality ratio, price level, promotions, expertise of staff, customer-friendliness, service, assortment, experience and accessibility of location (Quix & van der Kind, 2012). The score for each aspect is measured on a ratio scale ranging from 1 to 10. An example is: give a grade about (retailer) its performance on the aspect of ‘service’. A high score indicating good performance.

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Page | 23 3.3.3. Importance of store charactersistics

To identify which aspects are the most important to consumers while shopping in a certain category, consumers pick a maximum of three (out of nine) aspects which they consider (most) important for shopping in a certain category. These nine aspects are price-quality ratio, price level, promotions, expertise of staff, customer-friendliness, service, assortment, experience and accessibility of location (Quix & van der Kind, 2012).

3.3.4. Word-of-mouth intention

Word-of-mouth intention is measured on a 10 point likert scale ranging from 0 (strongly disagree) to 10 (strongly agree). A high score indicating high word-of-mouth intention. An example is: To what extend do you agree with the following sentence? I will recommend (retailer) to my friends and family. The score for word-of-mouth intention will be measured by the concept of the Net Promoter Score (NPS) introduced by (Reichheld, 2003). Reichheld (2003) identified three classes of consumers, namely promoters, detractors and passives. Promoters are consumers who actively recommend stuff to friends and family. Detractors are consumers who advise against stuff to friends and family. Passives neither recommend or advice against stuff to friends or family. They just do not speak about it. The NPS score is measured such that NPS = % of 9s and 10s minus % of 0s through 6s (Reichheld, 2003).

3.3.5. Repurchase intention

Repurchase intention is measured on a 10 point likert scale ranging from 0 (strongly disagree) to 10 (strongly agree). A high score indicating high repurchase intention. An example is: To what extend do you agree with the following sentence? The next time I need to buy products in this category, I will visit this retailer again. The score for loyalty intention will be measured by the concept of the Net Loyalty Score (NLS) (Quix & van der Kind, 2012). As said, Söderlund (2006) already mentioned that there are two measures of consumer loyalty. Quix and van der Kind (2012) shared this opinion and called for a second net score

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Page | 24 method to measure consumer loyalty, and introduced the Net Loyalty Score (NLS), which measures repurchase intention with the exact same method as the NPS.

The NLS score is measured such that NLS = % of 9s and 10s minus % of 0s through 6s.

3.3.6. Involvement

Levels of involvement have been identified per sector (high versus low involvement) based on the importance of products in these categories for consumers and the impact of these products on the life of consumers. The level of involvement per sector has not been measured in the questionnaire. This question has been asked to a retail expert, who gave each category a 0 (indication low involvement), a 1 (indication medium involvement) or a 2 (indication high involvement).

3.4 Data Analysis

Since the NLS and NPS method is measured on an ordinal scale, ordinal regressions will be conducted to test the hypotheses. To test for involvement the variables have been modified to an individual variable for each level of involvement. To test whether there are significant differences between the estimates of the ordinal regression between levels of involvement, the following test will be used:

𝑍 = 𝐸1 − 𝐸2 √(𝑆𝐷12+ 𝑆𝐷22)

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Page | 25

4. Results

4.1 Descriptive statistics

Before testing the hypotheses, the first step is to explore the data by looking at the descriptive statistics and correlations of all the variables included. Table 1 provides an overview of the mean value and standard deviation of each variable. Additionally, all the correlations between each variable are shown.

For repurchase intention there were in total 7149 detractors, 9679 passives and 4408 promoters. For word-of-mouth intention there were in total 7479 detractors, 10240 passives and 3517 promoters. This teaches us that only 21% would do repeat purchases and only 17% would recommend a retailer to others. The average score for repurchase intention is 1,87. For women this is 1,89 and for man 1,85. The average score for word-of-mouth intention is 1,81. For women this is 1,84 and for man 1,78. So on average, man are slightly less loyal then woman. The average scores on repurchase intention and word-of-mouth intention for the different age groups are respectively 1,66 and 1,69 (15-29) 1,73 and 1,75 (30-44), 1,88 and 1,82 (45-59) and 1,98 and 1,87 (60+). So it seems that the older people get, the more loyal they become.

Table 1

Descriptives statistics overview

Variable M SD 1 2 3 4 5 6 7 8 9 10 11 12 1. Gender ,44 ,496 2. Age category 3,02 1,070 .124** 3. Price-quality ratio 7,41 1,360 -,011 .141** 4. Price level 7,25 1,449 -,012 .151** .780** 5. Promotions 7,22 1,498 ,007 .150** .683** .700** 6. Assortment 7,65 1,338 -.020** .128** .629** .552** .564** 7. Service 7,53 1,456 -,003 .155** .609** .510** .543** .611** 8. Expertise of staff 7,42 1,498 ,010 .153** .577** .465** .509** .599** .805** 9. Customer-friendliness of staff 7,67 1,440 ,008 .167** .586** .495** .518** .592** .815** .805** 10. Experience 7,28 1,474 -.061** .067** .606** .519** .527** .660** .675** .664** .655** 11. Accessibility of location 7,75 1,488 .019** .144** .471** .432** .449** .462** .495** .471** .507** .434** 12. Repurchase intention 1,87 ,726 -.024** .165** .515** .482** .468** .484** .503** .477** .487** .476** .399** 13. Worf-of-mouth intention 1,81 ,695 -.045** .089** .523** .467** .452** .515** .523** .498** .504** .537** .369** .699**

Note. N = 21236 evaluations. Correlation is significant at the p <0.05* level and the p <0.01** level (2-tailed). Almost every correlation can be seen as moderate (>0.40 but <0.60) and significant. Except for the correlations which include gender and age category. These have very weak coëfficients (<0.20) and are not always significant.

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Page | 26 In line with previous research, there is a significant relationship between a consumer its score of a store image characteristic and the level of word-of-mouth/repurchase intention. The statistical estimate show that for a one unit increase in price-quality ratio (i.e., going from 1 to 2), an 0.240 increase in the ordered log odds of being in a higher level of Net Loyalty Score is expected, given all of the other variables in the model are held constant. The estimates of the other variables are 0.253 (price level), 0.139 (promotions), 0.236 (assortment), 0.204 (service), 0.090 (expertise of staff), 0.135 (customer-friendliness of staff), 0.154 (experience) and 0.149 (accessibility of location). For the increase in the ordered log odds of being in a higher level of Net Promoter Score the estimates are as follows: 0.303 (price-quality ratio), 0.163 (price level), 0.074 (promotions), 0.305 (assortment), 0.228 (service), 0.80 (expertise of staff), 0.135 (customer-friendliness of staff), 0.383 (experience) and 0.036 (accessibility of location). All estimates proved to be significant on the p<0.01 level. Table 2 gives an overview of the estimates of all the store related aspects influencing both repurchase intention and word-of-mouth intention.

Although the estimate seems rather low for some store aspects, the found effect does confirm previous research. The results suggest that price-quality ratio, price level,

Table 2

Estimates influencing NLS and NPS of total dataset Variable

Estimate Std. Error Sig. Estimate Std. Error Sig.

Price level ,253 ,018 .000** ,163 ,018 .000** Promotions ,139 ,015 .000** ,074 ,015 .000** Price-quality ratio ,240 ,020 .000** ,303 ,021 .000** Assortment ,236 ,017 .000** ,305 ,018 .000** Service ,204 ,021 .000** ,228 ,021 .000** Expertise of staff ,090 ,019 .000** ,080 ,020 .000** Customer-friendliness of staff ,135 ,020 .000** ,135 ,021 .000** Experience ,154 ,016 .000** ,383 ,017 .000** Accessibility of location ,149 ,012 .000** ,036 ,013 .005**

NLS (repurchase intention) NPS (word-of-mouth intention)

Note. Estimate is significant at the p<0.05* level and the p<0.01** level (2-tailed). These estimates are for the whole dataset and do not account for the level of involvement.

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Page | 27 assortment and service are the most important store aspects for repurchase intention. For word-of-mouth intention the most important store image characteristics seem to be price-quality ratio, assortment, service and experience. The Z-score of the difference between price-quality ratio and customer-friendliness of staff in the NLS measure is 3,64. This represents a significant difference at the p<0,001 level. The Z-score of the difference between price-quality ratio in the NLS measure and the price-quality ratio in the NPS measure is -2,13. This represents a significant difference at the p<0,05 level (p=0.0166). So indeed differences exist between the effect of different store image characteristics on repurchase intention and word of mouth intention. Results also vary between repurchase intention and word of mouth intention. It should be noted that differences between retail sectors have not been accounted for in this test. Therefore, differences in results between retail sectors which have been known to have low product involvement and retail sectors which have been known to have high product involvement have been accounted for in the next section

4.2 Test of hypotheses

Overview results

The strength of the estimates of all the store characteristics on repurchase intention and word-of-mouth intention across the levels of involvement can be found in table 3 and 4. The results show that price-quality ratio, price level, assortment, service, customer-friendliness of staff and experience all have a significant effect on repurchase intention and word-of-mouth intention over all levels of involvement. On the other hand, expertise of staff does not have a significant effect on a consumer his repurchase intention and word-of-mouth intention in sectors where involvement is low. Besides, no significant effect of promotions on repurchase intention and word-of-mouth intention was found for high involvement sectors. The accessibility of location does have a significant effect on the repurchase intention of a consumer, but for medium and high involvement it does not have a significant effect on a consumer his word-of-mouth intention.

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Page | 28 The results suggest that there are differences in the strength of the effect of several store characteristics on repurchase intention and word-of-mouth intention. The next section analyses per characteristic whether these differences are significant between each level of involvement. Table 5 provides an overview of these results.

Table 5

Price level Repurchase intention More postive when Medium vs. Low

Word-of-mouth intention No difference

Promotions Repurchase intention Less postive when High vs. Medium

Word-of-mouth intention No difference

Price-quality ratio Repurchase intention No difference

Word-of-mouth intention No difference

Assortment Repurchase intention More postive when Medium vs. Low & less positive when High vs. Medium

Word-of-mouth intention less positive when High vs. Medium

Service Repurchase intention More positive when High vs. Medium

Word-of-mouth intention More positive when High vs. Medium

Expertise of staff Repurchase intention More postive when High vs. Medium

Word-of-mouth intention More positive when Medium vs. Low

Customer-friendliness of staff Repurchase intention No difference

Word-of-mouth intention Less positive when Medium vs. Low

Experience Repurchase intention More positive when Medium vs. Low

Word-of-mouth intention Less positive when Medium vs. Low

Accessibility of location Repurchase intention Less positive when Medium vs. Low

Word-of-mouth intention Less positive when Medium vs. Low

Note. The results do suggest differences for each characteristics. However, this table only shows the significant differences.

Overview of the significant differences in the relationship between store image characteristics and loyalty across different levels of product category involvement

Table 3

Total Low involvement Medium involvement High involvement

Estimate Std. Error Sig. Estimate Std. Error Sig. Estimate Std. Error Sig. Estimate Std. Error Sig.

Price level ,253 ,018 .000** ,190 ,032 .000** ,290 ,025 .000** ,305 ,049 .000** Promotions ,139 ,015 .000** ,160 ,026 .000** ,129 ,022 .000** ,049 ,036 ,181 Price-quality ratio ,240 ,020 .000** ,275 ,037 .000** ,249 ,028 .000** ,197 ,052 .000** Assortment ,236 ,017 .000** ,181 ,030 .000** ,287 ,024 .000** ,132 ,042 .002** Service ,204 ,021 .000** ,161 ,036 .000** ,174 ,029 .000** ,336 ,051 .000** Expertise of staff ,090 ,019 .000** ,043 ,032 ,177 ,098 ,027 .000** ,206 ,051 .000** Customer-friendliness of staff ,135 ,020 .000** ,133 ,035 .000** ,109 ,029 .000** ,177 ,053 .001** Experience ,154 ,016 .000** ,124 ,026 .000** ,193 ,023 .000** ,231 ,041 .000** Accessibility of location ,149 ,012 .000** ,234 ,021 .000** ,080 ,018 .000** ,082 ,032 .010*

Estimates of the effect of store characteristics on NLS over different levels of involvement.

Note. Estimate is significant at the p<0.05* level and the p<0.01** level (2-tailed).

Table 4

Total Low involvement Medium involvement High involvement

Estimate Std. Error Sig. Estimate Std. Error Sig. Estimate Std. Error Sig. Estimate Std. Error Sig.

Price level ,163 ,018 .000** ,173 ,034 .000** ,152 ,025 .000** ,208 ,049 .000** Promotions ,074 ,015 .000** ,079 ,027 0.003** ,065 ,022 .003** ,056 ,037 ,136 Price-quality ratio ,303 ,021 .000** ,285 ,039 .000** ,313 ,029 .000** ,308 ,054 .000** Assortment ,305 ,018 .000** ,291 ,032 .000** ,334 ,025 .000** ,239 ,044 .000** Service ,228 ,021 .000** ,181 ,038 .000** ,190 ,030 .000** ,391 ,053 .000** Expertise of staff ,080 ,020 .000** -,014 ,033 ,678 ,131 ,028 .000** ,133 ,053 0.01* Customer-friendliness of staff ,135 ,021 .000** ,172 ,037 .000** ,093 ,030 .002** ,171 ,055 0.002** Experience ,383 ,017 .000** ,456 ,029 .000** ,371 ,024 .000** ,318 ,042 .000** Accessibility of location ,036 ,013 .005** ,099 ,022 .000** ,005 ,018 ,776 -,024 ,033 ,458

Note. Estimate is significant at the p<0.05* level and the p<0.01** level (2-tailed). Estimates of the effect of store characteristics on NPS over different levels of involvement.

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Page | 29 Test of hypothesis 1 – Price level

The first found effect of involvement as a moderator is that the influence of price level on repurchase intention is significantly more positive in high involvement categories than in low involvement categories(Z=-1,98 and p<0,05). The significant difference is made between low involvement and medium involvement (Z=-2,48 and p<0,01). From medium involvement to high involvement there is no significant difference (Z=-0,27 and p>0,05). The influence of price level on word-of-mouth intention is not significantly more positive for any level of involvement (for low/med Z=0,49, for med/high Z=-1,01, for low/high Z=-0,59). These results support hypothesis 1 only partially since the influence of price level on word of mouth intention show significant differences between some levels of involvement, but not between all. These results are summarized in figure 1.

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Page | 30 Test of hypothesis 2 - Promotions

The influence of promotions on repurchase intention is less positive in high involvement categories than in low involvement categories (Z=-2,49 and p<0,01). From low involvement to medium involvement there is no significant difference (Z=0,90 and p>0,05).The significant difference is made between medium involvement and high involvement (Z=1,90 and p<0,05). The influence of promotions on word-of-mouth intention is not significantly more positive for any level of involvement (for low/med Z=0,38, for med/high Z=0,23, for low/high Z=0,50). These results support hypothesis 2 only partially since the influence of promotions on repurchase intention show significant differences between some levels of involvement, but not between all. These results are summarized in figure 2.

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Page | 31 Test of hypothesis 3 – Price-quality Ratio

The influence of price-quality ratio on repurchase intention is not significantly more positive for any level of involvement (for low/med Z=0,57, for med/high Z=0,87, for low/high Z=1,23). The influence of price-quality ratio on word-of-mouth intention is not significantly more positive for any level of involvement (for low/med Z=-0,59, for med/high Z=0,08, for low/high Z=-0,36). These results do not support hypothesis 3 since there are no significant differences for the influence of price-quality ratio on repurchase intention and word of mouth intention between any level of involvement. These results are summarized in figure 3.

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Page | 32 Test of hypothesis 4 - Assortment

The influence of assortment on repurchase intention is not significantly less positive in high involvement categories than for low involvement categories (Z=0,94 and p>0,05). But the influence is significantly more positive when involvement is medium than when it is low (Z=-2,73 and p<0,01). The influence is also significantly more positive when involvement is medium than when it is low (Z=3,16 and p<0,01). So the influence of assortment on repurchase intention is most positive for categories where involvement is medium. The influence of assortment on word-of-mouth intention is not significantly less in high involvement categories than for low involvement categories (Z=0,97 and p>0,05), but the influence is significantly less positive when involvement is high than when it is medium (Z=1,88 and p<0,05). These results do support hypothesis 4 only partially. The influence of assortment on repurchase intention and word-of-mouth intention are only supported between some levels of involvement. These results are summarized in figure 4.

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Page | 33 Test of hypothesis 5 - Service

The influence of service on repurchase intention is significantly more positive in high involvement categories than in low involvement categories (Z=-2,80 and p<0,01). From low involvement to medium involvement there is no significant difference (Z=-0,28 and p>0,05).The significant difference is made between medium involvement and high involvement (Z=-2,75 and p<0,01). The influence of service on word-of-mouth intention is significantly more positive in high involvement categories than in low involvement categories (Z=-3,22 and p<0,01). From low involvement to medium involvement there is no significant difference (Z=-0,17 and p>0,05).The significant difference is made between medium involvement and high involvement (Z=-3,31 and p<0,01). These results support hypothesis 5 only partially since the influence of service on repurchase intention show significant differences between some levels of involvement, but not between all. These results are summarized in figure 5.

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Page | 34 Test of hypothesis 6 – Expertise of staff

The influence of on repurchase intention is significantly more positive in high involvement categories than in low involvement categories (Z=-2,71 and p<0,01). From low involvement to medium involvement there is no significant difference (Z=-1,32 and p>0,05).The significant difference is made between medium involvement and high involvement (Z=-1,86 and p<0,05). The influence of expertise of staff on word-of-mouth intention is significantly more positive in high involvement categories than for low involvement categories (Z=-2,35 and p<0,01). The significant difference is made between low involvement and medium involvement (Z=-3,31 and p<0,01). From medium involvement to high involvement there is no significant difference (Z=-0,02 and p>0,05). These results support hypothesis 6 only partially since the influence of expertise of staff on repurchase intention and word-of-mouth intention show significant differences between some levels of involvement, but not between all. These results are summarized in figure 6.

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Page | 35 Test of hypothesis 7 - Customer-friendliness of staff

The influence of customer-friendliness of staff on repurchase intention is not significantly more positive for any level of involvement (for low/med Z=0,52, for med/high Z=-1,13, for low/high Z=-0,70). The influence of customer-friendliness of staff on word-of-mouth intention is not significantly more positive in high involvement categories than for low involvement categories (Z=0,017 and p>0,05). But the influence is significantly less positive when involvement is medium than when it is low (Z=1,66 and p<0,05). These results support hypothesis 7 only partially since the influence of expertise of staff on word-of-mouth intention show significant differences between some levels of involvement, but not between all. These results are summarized in figure 7.

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Page | 36 Test of hypothesis 8 - Experience

The influence of experience on repurchase intention is significantly more positive in high involvement categories than for low involvement categories (Z=-2,20 and p<0,05). The significant difference is made between low involvement and medium involvement (Z=-1,95 and p<0,05). From medium involvement to high involvement there is no significant difference (Z=-0,82 and p>0,05). The influence of experience on word-of-mouth intention is less positive in high involvement categories than for low involvement categories (Z=3,13 and p<0,01). The significant difference is made between low involvement and medium involvement (Z=3,27 and p<0,01). From medium involvement to high involvement there is no significant difference (Z=0,79 and p>0,05). These results support hypothesis 8 only partially. The influence of experience on word-of-mouth intention and repurchase intention are only supported between some levels of involvement. Moreover, the results between repurchase intention and word-of-mouth intention vary in direction. These results are summarized in figure 8.

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Page | 37 Test of hypothesis 9 - Accessibility of location

The influence of accessibility of location on repurchase intention is significantly less positive in high involvement categories than for low involvement categories (Z=3,99 and p<0,01). The significant difference is made between low involvement and medium involvement (Z=5,57 and p<0,01). From medium involvement to high involvement there is no significant difference (Z=-0,06 and p>0,05). The influence of accessibility of location on word-of-mouth intention is significantly less positive in high involvement categories than for low involvement categories (Z=3,13 and p<0,05). The significant difference is made between low involvement and medium involvement (Z=3,27 and p<0,05). From medium involvement to high involvement there is no significant difference (Z=0,79 and p>0,05). These results support hypothesis 9 only partially. There are differences between some levels of involvement, but not between all levels of involvement. These results are summarized in figure 9.

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Page | 38

5. Conclusion and Discussion

The starting point of this study was that consumer loyalty is one of the most important factors influencing on the success of retail stores (Reichheld, 1992) and it is proven that the characteristics of store image influence consumer loyalty (i.e. a more positive perception of one of the characteristics results in a more loyal consumer) (Clottey et al., 2008; Jones & Sasser, 1995; Bloemer & de Ruyter, 1997). Moreover, this study suggested that product category involvement influences the strength of the relationship above, since the degree of searching for information and evaluating products differs between high and low involvement purchases (Celsi & Olsen, 1988), which in turn affects satisfaction, and satisfaction is a driver of consumer loyalty (Heskett et al., 2008). This study adds to the discussion, by showing that product category involvement does have a moderating effect on the store image-consumer loyalty relationship, although differing in direction for some store image characteristics. Before elaborating on these results, the checked relationship between the individual characteristics and consumer loyalty is discussed.

The results from this study are in line with previous research and show that indeed store image has a relationship with consumer loyalty, measured both on the level of repurchase intention and word-of-mouth intention. Söderlund (2006) and Clottey et al. (2008) already mentioned that researchers should look at both measures because differences in findings in past research to consumer loyalty might be partly explained by the inconsistent use of only one of these constructs of consumer loyalty, and indeed the strength of the relationship of the store image characteristics on consumer loyalty does differ between repurchase intention and word-of-mouth intention.

The results show that in order for consumers to perform repeat purchases, a good performance on price-quality ratio, price level and assortment is evident. To get consumers to talk to others about a retailer the importance of good performance of price-quality ratio and assortment becomes even greater in comparison to repurchase intention. The importance of price level drops, and providing consumers with a good shopping experience seems to be the most important when it comes to positive word-of-mouth. For both

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Page | 39 repurchase intention and word-of-mouth intention, delivering good service is also evident. Other researchers also identified service quality and assortment as the most attributes for consumer loyalty (Ghosh, 1990; Hesket et al. (2008). Although it was assumed that price level had an influence on repurchase intention

(

Jiang & Rosenbloom, 2005), the effect of prices level in this study is particularly high, which might be explained by the nature of the Dutch consumers, which are relatively price focused compared to others. Price-quality ratio is also quite influential, especially for word-of-mouth intentions. The fact that price level is less important for word-of-mouth intention suggests that the importance of price-quality ratio is more due to the quality, than the actual price of the product. Of course these are only basic insights and the main focus of this study was to investigate whether the level of involvement has a moderating effect on the relationship between store image characteristics and consumer loyalty, and this study concludes that it does. That is, it does for some of the store image characteristics and for some levels of involvement, not all.

The results show that the height of the level of involvement positively enhances the effect that price level, service, expertise of staff and experience have on repurchase intention. It also weakens the strength of the effect of promotions and accessibility of location. The strength of the influence of price quality-ratio and customer-friendliness of staff on repurchase intentions stay the same over the different levels of involvement. The results also show a rather odd effect of involvement on relationship between assortment and repurchase intention, namely, the influence of assortment on repurchase intention is the most positive for the medium involvement group. When involvement is less or more, the influence is less positive. A possible explanation could be that in low involvement categories differences between the assortment of retailers are smaller than for medium involvement categories. Thus, they have more choice, which decreases possible loyalty intentions. The difference between high and low might be explained because for high involvement purchases, consumers will always evaluate the alternatives (Celsi & Olsen, 1988)

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