“Shopping motivations and their influences on the relation
between store characteristics and loyalty”
An empirical study within the fashion industry
By
Lotte Oudhuis
“Shopping motivations and their influences on the relation
between store characteristics and loyalty”
An empirical study within the fashion industry
By
Lotte Oudhuis
Rijksuniversiteit Groningen Faculty of Economics & Business Master Thesis BA – Marketing Management
Wenslauerstraat 8-3 1053 BA Amsterdam lotteoudhuis@hotmail.com 06 29512527 S1555359 February 2012
MANAGEMENT
SUMMARY
Retailers face extremely hard times due to the recession, the rise of mass discounters and the arrival of the internet. Especially fashion retailers have been forced to redesign their strategy, since consumers have become more demanding and are seeking for greater variety at increasingly competitive prices. The fashion retailer, H&M Netherlands that is investigated in this thesis has a very strong brand image and a large customer base. However, consumer spending is decreasing. The company should seek for more effective strategies in order to grow a loyal customer base. Get to know your customers starts with questioning their motivations to go shopping. In this research shopping motivations are used to understand the needs of the customers.
The conceptual model developed in this thesis provides a platform that investigates the main effects of shopping motivations, involvement and store characteristics on loyalty. Moreover, moderating influences of motivations and involvement on the relation between store characteristics and loyalty are defined. This enables the company to adapt their store characteristics in a way in which the needs of the customers are satisfied (based on their shopping motivations); simultaneously it will lead to more loyal customers. Therefore the problem statement of this thesis could be defined as follows:
How are store characteristics related with customer loyalty behavior, including the moderating effects of different shopping motivations and fashion involvement, focused on the Dutch customer
base of an international fashion retailer?
Well-known measurements of shopping motivations, loyalty, store characteristics and fashion involvement will be used, based on an extensive literature research. The empirical research is executed on a random sample of 149 respondents of the target population; people between the 10 and 60 years who visited a Dutch H&M store once during the last year.
PREFACE
This thesis has been written to accomplish my Master of Science in Marketing Management at the University of Groningen. Finishing this thesis means for me the end of my time as a student. I have had a great time in which I learned a lot. Besides, I am looking forward to take the next step in my life by bringing all the learned knowledge into practice.
Therefore, I would like to thank my supervisors of the University of Groningen who supported me with writing this thesis. Especially, I would like to thank my supervisor Liane Voerman for her time, patience and constructive feedback and support during the months I worked on my thesis. Moreover, thanks to my second supervisor Stefanie Salmon who gave me some important insights in the used theory
.
Lotte Oudhuis
TABLE
OF
CONTENTS
1 INTRODUCTION ... 7 1.1. BACKGROUND INFORMATION ... 7 1.2. PROBLEM STATEMENT ... 9 1.3. MANAGERIAL RELEVANCE ... 9 1.4. ACADEMIC CONTRIBUTION ... 10 1.5. STRUCTURE... 10 2 THEORETHICAL FRAMEWORK ... 11 2.1. SHOPPING MOTIVATIONS ... 11 2.1.1. DIFFERENT VIEWS... 11 2.2. LOYALTY ... 132.2.1. BEHAVIORAL AND ATTITUDINAL LOYALTY ... 14
2.2.2. CUSTOMER ENGAGEMENT ... 14 2.2.3. WILLINGNESS TO PAY ... 16 2.2.4. SHARE OF WALLET ... 16 2.2.5. REPURCHASE INTENTION ... 16 2.3. STORE CHARACTERISTICS ... 17 2.4. CUSTOMER INVOLVEMENT ... 19 2.5. CONCEPTUAL MODEL ... 21 3 RESEARCH METHODS ... 22 3.1. RESEARCHED COMPANY ... 22 3.2. SURVEY ... 23 3.2.1. BACKGROUND CHARACTERISTICS ... 23
3.2.2. RETAIL STORE CHARACTERISTICS ... 23
3.2.3. STORE LOYALTY ... 23 3.2.4. MODERATING VARIABLES ... 24 3.3. SAMPLING ... 27 3.3.1. SAMPLE SIZE ... 27 3.3.2. SAMPLING TECHNIQUE ... 27 3.4. PLAN OF ANALYSIS ... 27
3.4.1. RELIABILITY ANALYSIS OF SCALES ... 27
4 RESULTS ... 32
4.1. DESCRIPTIVE STATISTICS ... 32
4.2. RESULTS OF MAIN STUDY... 34
4.2.1. CUSTOMER ENGAGEMENT ... 34
4.2.2. CUSTOMER LOYALTY ... 37
4.3. DISCUSSION OF THE RESULTS ... 39
4.3.1. CUSTOMER ENGAGEMENT ... 39
4.3.2. CUSTOMER LOYALTY ... 40
5 CONCLUSIONS, LIMITATIONS AND RECOMMENDATIONS ... 42
5.1. CONCLUSIONS ... 42
5.2. LIMITATIONS AND RECOMMENDATIONS... 44
REFERENCES ... 46
APPENDICES ... 50
APPENDIX 1 QUESTIONNAIRE ... 50
APPENDIX 2 MULTIPLE REGRESSION ... 55
APPENDIX 2.1 CONSTRUCTED INTERACTION TERMS ... 55
1
INTRODUCTION
Retailers could range from street vendors selling hot dogs, to internet retailers, to multichannel retailers that have both an extensive physical store presence and an active internet site (Levy and Weitz, 2009). Each retailer survives and prospers when it satisfies a group of consumers’ needs more effectively than its competitors can. Nowadays, the retailing world is a highly competitive, rapidly changing environment (Levy and Weitz, 2009). The tumultuous character of the retailing landscape leads to changing consumer needs and increased competition, which requires retailers to build a stable customer base in order to stay competitive in the long term. This research aims to get insights in the needs of customers, based on their shopping motivations. Besides, the relation between several store characteristics and different customer loyalty measures will be investigated. The shopping motivations will be included as a moderating factor in this relationship. The empirical study is focused on the Dutch customer base of a large, international fashion retailer.
1.1. B
ACKGROUND INFORMATIONEvans (2010) notes that retailers around the globe have faced extremely turbulent times. Some firms failed and entered bankruptcy and others faced weak sales and performances. In recent years, upcoming online retailers, mass discounters and increased price competition have changed the landscape of the industry (Arnold and Reynolds, 2003). According to Evans (2010), the most important reasons for these tumultuous times are the Great Recession during the 21nd century, a changing landscape due to the arrival of the internet and the evolution of large shopping centers. Levy and Weitz (2009) state that the intensity of competition increased due to the rise of electronic, catalog and direct-mail retailers, which have lead to the arrival of multichannel retailing; retailers that sell merchandise through more than one channel and in this manner increase their (potential) target and share of wallet. Since each channel has its own benefits, combining these advantages into a multichannel approach could lead to the creation of a competitive advantage. In addition, the arrival of internet retailers and the growth of discounters and warehouse clubs has put immense pressure on traditional retailers and significantly increased retail competition (Ailawadi and Keller, 2004). On the other hand, the growth of promotions and private label brands has been seen by many as an indicator of growing retailer power. These tools could be used by retailers in order to stay competitive and survive in the long term.
researched company in this thesis is the Hennes & Mauritz (H&M). This international retailer has implemented the fast fashion strategy, however the competition remains high because almost all their direct competitors follow this strategy idem. The simultaneous need for both a more responsive supply chain with shorter lead times and a global sourcing strategy for lower production costs have put, together with more demanding customers, an enormous pressure on fashion retailers, which the investigated retailer in this thesis faces as well.
Successful retailers would have to understand and capitalize on changes in demographics, values, environmental concerns, information technology, market segmentation and the changing face of competition. Survivors will be experts in their merchandise and understand their customers (Evans, 2010). The need for market information and rapid respond on changes in the environment is emphasized clearly in the literature. In order to remain up to date, retailers need to know the environment very well before they can develop and implement effective strategies (Levy and Weitz, 2009). The most important source of information for the retailer is the customer, or better said, the need of the customer. The need of the customer starts with the question ‘Why do people shop?’ (Tauber, 1972), which refers to the motivations a person has when deciding to go shopping. Shopping motivations have emerged as one of the key concepts in research on consumer shopping behavior due to its high managerial relevance (Wagner & Rudolph, 2010). The buying process is triggered when consumers recognize they have an unsatisfied need (Levy and Weitz, 2009). This unsatisfied need arises when a consumer’s desired level of satisfaction differs from his or her present level of satisfaction. The needs that motivate customers to go shopping and purchasing merchandise are called shopping motivations. The ‘need recognition’ or ‘shopping motivation’ of the customer is the first stage in selecting a retailer and channel, according to Levy and Weitz (2009) and therefore crucial for retailers to react on.
It emerged from the literature that shopping motivations and store loyalty are, despite their relevance in retailing, hardly ever investigated at the same time. The purpose of this research is to investigate the moderating effect of shopping motivations on the straightforward relationship between store characteristics and customer loyalty. It is known from general knowledge that several characteristics of a certain store, e.g. type of assortment, customer service, price level, will influence customer loyalty. However, shopping motivations could have a moderating effect on this relationship. Moreover, it is expected that the customer characteristic ‘fashion involvement’ could moderate this relation as well.
For this research, in order to increase the profitability of the company, the focus will lay on raising store loyalty and thus growing the customer base. The needs of the customer will be investigated by evaluating the founding of all customer needs; the motivations to go shopping.
1.2. P
ROBLEM STATEMENTThe problem statement is derived from the situation outlined above. This thesis will outline how different store characteristics are linked with different forms of loyalty, including the moderating effect of shopping motivations and fashion involvement on this relation. In order to improve the understanding of one firm in particular, this research will focus on the market of one firm in particular. This leads to the following problem statement:
How are store characteristics related with customer loyalty behavior, including the moderating effects of different shopping motivations and fashion involvement, focused on the Dutch customer base of an international fashion retailer?
In order to give a structured answer on the problem statement, the follow research questions are defined;
1. Which different shopping motivations could customers have?
2. What are the differences in portrayed loyalty between several store characteristics? 3. How do the moderators shopping motivations and fashion involvement influence
the leverage between store characteristics and loyalty?
1.3. M
ANAGERIAL RELEVANCE1.4. A
CADEMIC CONTRIBUTIONLike stated before, the two main constructs in this research, shopping motivations and store loyalty, are hardly ever researched simultaneously before. The written academic literature on retailing is replete, however the relationship researched in this thesis has not received enough attention. This is quite surprising, since many authors emphasize shopping motivations as one of the main customer sources of information and loyalty is seen as one of the most important performance measures.
Besides, store characteristics are, for most companies, very easy to adapt. Therefore, it is chosen to use these independent variables. This makes the conceptual model very useful for any (retailing) company that is able to adapt their store characteristics and wants to grow a loyal customer base.
1.5. S
TRUCTURE2
THEORETHICAL
FRAMEWORK
This chapter outlines the used constructs, ‘shopping motivations’, ‘loyalty’, ‘fashion involvement’ and ‘store characteristics’ and the relationship between them, based on academic literature. The composed hypotheses in this chapter are summarized in the conceptual model, which is the basis for empirical research.
2.1. S
HOPPING MOTIVATIONSB
ecause of the straightforward expected relationships between store characteristics and store loyalty, shopping motivations are included in order to find out whether certain shopping motivations could interfere the expected relations.Research supports the existence of two dimensions in the shopping motivations of any customer: hedonic and utilitarian shopping motives (Arnold and Reynolds, 2003); (Cardoso and Pinto, 2010); (Babin et al., 1994); (Jones et al., 2006). Hedonic consumption involves the multi-sensory, fun and emotive aspects of the consumer’s experiences with buying a product. Furthermore, hedonic shoppers have indicated to see shopping as an adventure and also described the enjoyment of bargaining and haggling and the mood-altering qualities of the shopping experience (Arnold and Reynolds, 2003). In conclusion, the need for experiences is often more significant than the acquisition of products when customers are seeking for hedonic fulfillment. Babin et al., (1994) agree on this by stating that hedonic value is more subjective and personal and results more from fun and playfulness than from task completion. Additionally, they argue that hedonically valuable shopping experience is indicated by increased arousal, heightened involvement, perceived freedom, fantasy fulfillment and escapism. Besides this, utilitarian shopping value reflects the acquisition of products and/or information in an efficient manner and can be viewed as reflecting a more task-oriented, cognitive and non-emotional outcome of shopping. In this context, a shopping experience can be evaluated by consumers as an achievement of an intended goal, (Cardoso and Pinto, 2010). Kim (2006) describes that there are two important dimensions measuring utilitarian motivations, which are efficiency and achievement. Efficiency refers to consumer needs to save time and resources, while achievement refers to a goal related shopping orientation where success in finding specific products that were planned for at the outset of a trip is important.
2.1.1. D
IFFERENT VIEWSEarly academic work on shopping motivations is replete, however ‘motivation’ is a highly dynamic construct that is constantly changing in reaction to life experiences; needs and wants could alter in response to the environment, through interaction with others and by the individual’s state of being (Megicks et al., 2008). This means that shopping motivations of a consumer could change over time, due to changes in the environment or in a person’s state of being. Hence, both external and internal factors could influence the shopping motivations for a certain product. Besides this, a lot of written academic work exists on this construct. Therefore, the next part investigates different views of several authors on the concept shopping motivation. Babin et al., 1994
utilitarian shopping motivations. Babin et al., (1994) describes the development of a two-dimensional scale of perceived personal shopping value, which recognizes that consumer value is indicated in both utilitarian and hedonic terms. In other words, the consumer is portrayed as being both intellectual and emotional. The outcome of their research proves that utilizing both value dimensions may better explain general consumer choice. Therefore, in this research both utilitarian and hedonic dimensions will be investigated in order to achieve a clear view on consumers’ motivations.
Arnold and Reynolds, 2003
Arnold and Reynolds (2003) found six broad categories of hedonic shopping motivations. They purely focused on hedonic motivations in order to construct taxonomy of shoppers that have primarily hedonic and non-product motives to go shopping. The study of Arnold and Reynolds (2003) seems quite comprehensive, because the founded categories are mutually exclusive and are used in a lot of studies afterwards. A short explanation of the six categories;
1. Adventure shopping: this refers to the shopping for stimulation, adventure and the feeling of being in another world.
2. Social shopping: refers to the enjoyment of shopping with friends and family, socializing while shopping, and bonding with others while shopping.
3. Gratification shopping: involves shopping for stress relief, shopping to alleviate a negative mood, and shopping as a special treat to oneself.
4. Idea shopping: refers to shopping to shopping to keep up with trends and new fashions, and to see new products and innovations.’
5. Role shopping: reflects the enjoyment that shoppers derive from shopping for others, the influence that this activity has on the shoppers’ feelings and moods, and the excitement and intrinsic joy felt by shoppers when finding the perfect gift for others.
6. Value shopping: refers to shopping for sales, looking for discounts, and hunting for bargains. Kim, 2006
Besides this, Kim (2006) found two dimensions of utilitarian motivations, namely efficiency and achievement. Moreover, the hedonic categories of Arnold and Reynolds (2003) are used in this research in addition to the founded utilitarian categories. The utilitarian motives are explained as follows;
1. Achievement: refers to a goal related shopping orientation where success in finding specific products that were planned for at the outset is important.
2. Efficiency: refers to consumer needs to save time and resource. Goldsmith et al., 2011
moderate hedonic shopping motivations, since these two constructs stimulate shopping enjoyment as well and are not included in the general hedonic motivations. Their research sounds very plausible, however it is hard to use in empirical research, because a distinction should be made between motivations consumers are aware of and motivations consumers are not aware of. Moreover, the concept of materialism is not that straightforward to measure in a fashion retailing world.
McCabe et al., (2008)
McCabe et al., (2008) state that there are three shopping motivations that have shown to be important motivations for contemporary consumers, which are not included in existing scales of shopping motivations. These motivations are;
- the need to alleviate loneliness
- the need to maintain commercial relationships - the need to browse
These motivations seem to be appropriate in this study, because fashion retailers could provide stores in which consumers could browse and alleviate loneliness. Besides, the exclusion of these motivations in existing scales of shopping motivations could be disputed. The need to alleviate loneliness shows some overlap with hedonic motivations, like need to alleviate a negative mood (gratification shopping). Furthermore, the need to browse could be explained in the need to see new products and innovations (idea shopping) as well. Therefore, inclusion of these shopping motivations will not add extra value and are therefore not valid to use.
Decades of research have led to many different views, and still it is hard to state which authors talk about the truth. Shopping motivation is highly influenced by both psychological and economic reasons, while both change during someone’s life. This makes it hard to draw a straight line in this concept. For this research, it is chosen to use the strongest established categorization of shopping motivations, which is found in the work of Arnolds and Reynolds (2003) and Kim (2006). Many researchers used their work in order to research shopping motivations and have proven these to be good measurements.
2.2. L
OYALTYThe cost of acquiring new customers usually far exceeds the costs of retaining an existing customer (Ray and Chiagouris, 2009). This ensures that it is more profitable to create a loyal customer base that remains for the long term, instead of constantly investing in new customers which pass out in a short term. Moreover, Ray and Chiagouris (2009) emphasize that store loyalty is the single most important cornerstone in strategic retail management and success. Sawmong and Omar (2004) agree on this by stating that it is necessary to create, evaluate and retain the loyalty of the customer in order to increase the possibility of success. Academic work proved that loyalty is one of the most important performance measures for marketing retail success and store longevity. At last, a company could help itself by increasing its loyal customer base, because loyal customers advocates for the company; they have more favorable attitude and higher intention to repatronize (Yi and La, 2004).
et al., 2011). This has lead to many different conceptualizations and measurements of this construct. Therefore, it is hard to give an exact definition of this term. But by reviewing the literature, the most clear and comprehensive definition of loyalty is from Knox and Denison (2000); consumer’s inclination to patronize a given store or chain of stores over time.
2.2.1. B
EHAVIORAL AND ATTITUDINAL LOYALTYSome authors define loyalty as a purely behavioral measure, because it refers to the future product repeat purchase commitment. Hence, many researchers define loyalty on the basis of not only behavior but also attitude, since they believe that the simple repeat purchase may be due to external factors (Velázquez et al., 2011). The behavioral perspective places the emphasis on past experience, while the attitudinal perspective is based on future actions. In this research both behavioral and attitudinal loyalty will be measured, because by focusing on behavior alone, the reasons behind the purchases cannot be captured. Besides this, studying solely attitudinal loyalty cannot tell us much about competitive effects, familiarity and situational factors (Baloglu, 2002). The following part explains the used metrics in this research.
Attitudinal measures
Customer engagement, which is introduced recently due to the increased digital society, measures the mere ‘soft’ side of behavior instead of the transactional side that measures immediate cash flows. This construct will be measured by positive word of mouth and the recommendation to friends or family. Customer engagement is explained as being a behavioral measure, however the metrics ‘word of mouth’ and ‘recommendation to others’ are indicated to be attitudinal metrics by many authors (Fitzgibbon and White, 2005); (Anisimova, 2007). Purely behavioral elements are defined as being repeat purchases. On the other hand, attitudinal elements are about commitment (Baloglu, 2002). Therefore, logically, the metrics of customer engagement are attitudinal in nature, since they refer to the amount of commitment a customer has. Furthermore, attitudinal loyalty is measured by the highly accepted construct of willingness to pay. This factor is able to measure commitment to a certain store/product, because it indicates whether the customer is willing to pay a price premium.
Behavioral measures
Moreover, some behavioral measures are added. First, share of wallet, this construct measures the share of spending a customer spends on a particular store within a certain industry. At last, the behavioral measurement ‘repurchase intention’ will be used, because this construct is in almost all research on loyalty evaluated as an effective behavioral measurement.
By using these five constructs, the measurement of loyalty is complete, since it measures different sides using highly accepted variables that are proven to be effective. The first two constructs measure customer engagement, the latter three customer loyalty. All together they measure the overarching construct loyalty.
2.2.2. C
USTOMER ENGAGEMENTbeyond transactions, and may be specifically defined as a customer’s behavioural manifestations that have a brand or firm focus, beyond purchase, resulting from motivational drivers’. Customer engagement focuses more on the ‘soft’ side of the customer’s behaviour, instead of the transactional side which immediately ensures cash flows. Not focusing on non-transactional behaviour should be seen as a lost opportunity for the focused company. In this research this ‘new’ perspective on customer behaviour is very interesting, since the non-transactional behaviour results from motivational drivers and therefore has a direct link with (shopping) motivations. In addition, van Doorn et al., (2010) state that the engagement is considered as a second source of experience beyond the hedonic source of experience resulting from a motivational force to make or not make something happen.
Customer engagement could be classified as negative or positive (van Doorn et al., 2010). Positive engagement includes customer actions that in the short and long run have positive consequences, both financial and non-financial, for the firm. These customer actions could be, e.g. WOM, blogging and recommending the firm to friends and family. Engagement behaviour will be measured in terms of positive WOM and NPS (recommendation of the firm to friends and family), because both constructs are measurable and interesting in the light of this research. Blogging is mentioned as well by van Doorn et al., (2010) as an indicator of customer engagement. However, this construct goes beyond the scope of this research, since the online behaviour of customers will not be measured.
Positive Word of Mouth
Word of mouth is everywhere. Consumers talk about new products and brands, complain about companies and share shopping experiences. In this way, word of mouth could influence product adoption and sales, both negatively and positively. Word of mouth is driven by several psychological drivers like the degree of interest and accessibility (Berger and Schwartz, 2011). They argue that products are interesting, and therefore suitable for WOM, when they offer novel, exciting or violate expectations in some way. In other words, people may talk about interesting products (instead of boring products) because it makes them seem interesting. Moreover, in contrast, WOM is driven by accessibility, or whether products are on top of mind. This means that people love to talk small talk, like talking about the weather instead of technological innovations. In this research, the apparel of H&M seems to be good products for word of mouth, since they are accessible (a lot of store locations and accessible clothing) and of interest (due to new collections every 3-6 weeks). Many academic research linked word of mouth with loyalty and customer engagement (Ray and Chiagouris, 2009); (van Doorn et al., 2010). Since H&M is a good target for word of mouth, this construct is included in order to measure customer engagement and therefore customer loyalty. The expected relation is that ‘the higher the hedonic shopping motivations of the customer, the higher the expected positive word of mouth will be’.
Net Promoter Score
firm) are more likely to repurchase. The expected relation is that ‘the higher the hedonic shopping motivations of the customer, the higher the NPS will be’.
2.2.3. W
ILLINGNESS TO PAYWillingness to pay is the price premium a consumer wants to pay for a certain product/service/brand. Accurately gauging consumers’ willingness to pay is critical for formulating competitive strategies, conducting value audits and developing new products (Miller et al., 2011). Additionally, Ray and Chiagouris (2009) state that the decision to pay higher prices indicates a strong sense of commitment and loyalty to the store.
H&M is defined as a ‘fast fashion’ retailer. Fast fashion is defined in the literature as a retailing system that combines at least two components:
1. Short production and distribution lead times, enabled through a combination of localized production, sophisticated information systems and expedited distribution systems.
2. Highly fashionable, trendy product design, made possible by carefully monitoring consumer and industry tastes for unexpected fads and reducing design lead times (Cachon and Swinney, 2011).
Cachon and Swinney (2011) postulate that enhanced design capabilities result in products that are of greater value for consumers and hence elicit a greater willingness to pay. In this research, this means that people that value enhanced design capabilities, and are thus interested in new trends and innovations (hedonic motivations), will have a greater willingness to pay.
2.2.4. S
HARE OF WALLETCooil et al., (2007) state that researchers and managers have become increasingly interested in consumers’ share of spending as a behavioral measure of loyalty. This share of spending, also named share of wallet or customer share, is defined as the percentage of customer’s total annual expenditure on a particular store type that is spent on a particular store (Ray and Chiagouris, 2009).
Friedman et al., (2011) indicate that a possible driver of share of wallet within specialty stores involves customer perceptions of store expertise. Since H&M is defined earlier in this thesis as a specialty store, this assumption could be used. Store expertise is defined as the ability of the retailer to perform product-related tasks successfully, with a greater level of knowledge and understanding than an ordinary person would have (Friedman et al., 2011). Moreover, store expertise can help shoppers who wish to save time and effort. The savings of time and effort is directly linked to the efficiency motivation to go shopping, which is defined as a utilitarian shopping motivation. Friedman et al., (2011) shows that there is a significant relationship between store expertise and share of wallet, since customers that perceive store expertise will allocate more of their expenditures to that store in order to maximize their advantage from the expertise.
2.2.5. R
EPURCHASE INTENTIONreason, this metric is included as well, in order to give a clear and entire view on store loyalty. According to the literature, repurchase intention has a strong link with customer satisfaction (Hellier et al., 2003); (Cooil et al., 2007); (Voss et al., 2010). Furthermore, it is expected that customers with more hedonic motivations will be more satisfied, because it is expected that the fashion industry will be better evaluated by customers with hedonic compared to utilitarian motivations. Therefore, it is argued that customers with more hedonic shopping motivations will be more satisfied and therefore will show higher repurchase intentions.
2.3. S
TORE CHARACTERISTICSMany authors have shed their light on shopping motivations and almost all agreed on the existent distinction between utilitarian and hedonic motives. However, there are authors that go beyond this generic classification. Wagner and Rudolph (2010) identified different degrees of abstraction when looking at different shopping motives. According to them, shopping motivations can be ordered in a hierarchical structure, ranging from abstract motives (e.g. recreation) to very concrete motives (e.g. convenience in parking). The hierarchical dimensions, defined by Wagner and Rudolph (2010), differentiate in terms of a purpose-specific, activity-specific and demand-activity-specific level of shopping motivations. The purpose-activity-specific level corresponds to the most abstract form of motivation, providing the overall underlying objective of a shopping trip. Besides this, the activity-specific level is more concrete in nature, since consumers’ activity goals and desired behaviors are identified. These motives outline how consumers accomplish the overall aim of a shopping trip. At last, the demand-specific level forms the most concrete and operational level of shopping motivation and relates to consumers’ particular expectations placed upon several retail facilities. The utilitarian (task-fulfillment) and hedonic (recreation) shopping motivations are, according to Wagner and Rudolph (2010), present in each hierarchical level and therefore their findings are complementary to the generic findings on shopping motives.
The study of Wagner and Rudolph (2010) points toward some differences of the interrelationships of shopping motives between shopping contexts, which could be of interest for this research. They argue that the purpose-specific level, which is most abstract, will lead to the activity-specific level, which, in turn, determines demand-specific motivation. Moreover, the base of each motivation is task-fulfillment or recreation (in the purpose-specific level), which corresponds with the generic distinction between hedonic and utilitarian. Furthermore, the activity-specific level (medium abstract/medium concrete) will include mostly hedonic motivations, e.g. inspiration, gratification, socialization, gift shopping etc. Besides this, this level includes one utilitarian motive, namely efficiency shopping. The most concrete level, demand-specific, represent various aspects with regard to retailers’ store facilities, e.g. service convenience, assortment innovation, assortment uniqueness, store atmosphere, personnel friendliness and prices, which are consequences of the specific activities on the activity-specific level.
- Customer service level (incl. service convenience and personnel friendliness) - Type of assortment (incl. assortment innovation and assortment uniqueness) - Store atmosphere
- Price (price level is perceived as being low)
It is proposed that higher values of the above stated retail facilities will lead to higher store loyalty and higher customer engagement, since all factors contribute to the positive evaluation of a store when these are positively evaluated by the consumer. This leads to the following hypotheses;
H1: Higher levels of customer service will lead to higher customer loyalty H2: Higher levels of customer service will lead to higher customer engagement H3: Higher levels of a unique and new assortment will lead to higher customer loyalty H4: Higher levels of a unique and new assortment will lead to higher customer engagement H5: Higher levels of store atmosphere will lead to higher customer loyalty
H6: Higher levels of store atmosphere will lead to higher customer engagement H7: Lower price levels will lead to higher customer loyalty
H8: Lower price levels will lead to higher customer engagement
Besides, it is expected that the existence of (hedonic vs. utilitarian) shopping motivations will interfere these relationships. The next paragraph explains the store characteristics shortly and introduces the other proposed hypotheses, including its moderating effects.
Customer service level
Customer service refers to the quality of service granted in a certain firm. This could be measured in terms of time customers have to wait, friendliness of the personnel, convenience, knowledge of the personnel etc. Wagner and Rudolph (2010) state that efficiency-driven consumers will exhibit elevated needs for service convenience. Furthermore, Kim (2006) argues achievement-driven consumers have a goal related shopping orientation where success in finding specific products is important. Both types of consumers have utilitarian shopping motivations and are seeking for customer service in order to fulfill their needs. This means that consumers with utilitarian shopping motivations will value the existence of a high customer service level more, compared to consumers with hedonic shopping motivations. This will lead to the following hypothesis:
Type of assortment
Innovation is seen as a process of creation, feeding and growth of experience and knowledge accumulated by an organization (Fornari et al., 2009). These factors are transformed into renewable assets and competitive advantage by adding new products and/or trading up existent products in a company portfolio. Wagner and Rudolph (2010) state that assortment innovation is positively linked with inspiration and gratification, but negatively linked with efficiency shopping. Besides this, assortment innovation attracts hedonic shoppers because they like to shop to keep up with new trends, and to see new products and innovations (Arnold and Reynolds, 2003). The uniqueness of an assortment is strongly linked with innovation, because innovative products are mostly introduced because of their unique, new characteristics. Taking these statements into account, the following hypothesis is proposed;
H10: Higher levels of unique and new assortments will be related to higher customer loyalty and engagement for customers with a hedonic, compared to a utilitarian, shopping motivation
Store atmosphere
Store atmosphere is determined by three environment factors, namely design (light), ambient (music) and social (personnel) factors (Baker et al., 2002). These factors seem to attract customers with hedonic shopping motivations, since these customers value multisensory, fantasy, and emotive aspects of consumption (Arnold and Reynolds, 2003). Moreover, Wagner and Rudolph (2010) state that store atmosphere has a positive link with consumers who are shopping for gratification, inspiration and sensory stimulation. This means that store atmosphere will be positively evaluated by consumers with hedonic shopping motivations. Considering the arguments above, consumers with hedonic shopping motivations are attracted by a good store atmosphere, and therefore will this motivation interfere the relation between store atmosphere and loyalty.
H11: Higher levels of store atmosphere will be related to higher customer loyalty and engagement for customers with a hedonic, compared to a utilitarian, shopping motivation
Prices
The retail facility ‘price level’ is, according to Wagner and Rudolph (2010), influenced by bargain hunting, which, in turn, is influenced by both task-fulfillment and recreation. Bargain hunting tends to be a recreational shopping activity for many consumers, but it also serves a purely objective purpose in that money can be saved. This is confirmed by other studies, which indicate that bargaining could be a hedonic shopping motivation, when referring to sales, discounts and seeking for value for money. Besides this, the saving of time and resources (money) is an important utilitarian shopping motivation (Arnold and Reynolds, 2003); (Kim, 2006). Therefore, the following hypothesis is proposed:
H12: Lower price levels will be related to higher customer loyalty and engagement for both customers with a utilitarian and a hedonic shopping motivation
2.4. C
USTOMER INVOLVEMENTInvolvement with fashion
According to the literature, involvement is related to an individual’s needs, values, and self-concept and it implicitly express the person’s beliefs and feelings about an object in a particular situation (VonRiesen and Herndon, 2011). Moreover, consumer behavior research has shown that personal characteristics of the consumers impact their choice and buying behavior (Schramm-Klein et al., 2008). Schramm-Klein et al., (2008) found out that from several demographic and psychographic characteristics, involvement is considered as one of the most important factors of influence on evaluation process of retail stores and on the development of brand loyalty. Assumed from the work of Petty and Cacioppo (1983), the evaluation process of higher involved consumers should be more pronounced and more elaborate than those of low involved consumers. In addition, Vélazquez et al., (2011) state that consumer involvement with the supplier company depends on perceived provider effort and can influence loyalty.
In this research involvement with the product (fashion) will be included. According to the literature above, it is expected that a higher level of involvement will lead to higher levels of store loyalty and engagement, therefore the following is proposed;
H13: Higher levels of fashion involvement will lead to higher levels of customer loyalty H14: Higher levels of fashion involvement will lead to higher levels of customer engagement
Moreover, the moderating effect of fashion involvement on the relation between store characteristics and loyalty and engagement is discussed. According to the literature above, it is expected that involvement will influence the evaluation process of retail stores and loyalty (Schramm-Klein et al., 2008). This process will be more pronounced by higher involved, compared to low involved, consumers. This means that the higher the involvement with the product (fashion), the more critical the store characteristics will be evaluated. This means that when the characteristics will be evaluated lower, the loyalty and engagement will be lower as well. On the other hand, when the characteristics are evaluated higher (better), the loyalty and engagement will be likewise higher. The influence of fashion involvement will strengthen the existing relations. This leads to the following hypotheses;
H15: Higher customer service levels will be related to higher customer loyalty and engagement for customers with higher fashion involvement
H16: Higher levels of unique and new assortments will be related to higher customer loyalty and engagement for customers with higher fashion involvement
H17: Higher levels of store atmosphere will be related to higher customer loyalty and engagement for customers with higher fashion involvement
2.5. C
ONCEPTUAL MODELFIGURE 1
Conceptual model
Customer loyalty - Willingness to pay - Share of wallet - Repurchase intention Customer engagement - Word of Mouth - Net Promoter ScoreShopping motivation
- Hedonic - Utilitarian
Involvement with fashion
Store characteristics
- Customer service level - New and unique assortment - Store atmosphere
3
RESEARCH
METHODS
This chapter outlines the research methods that will be used to collect and analyze the data. The data will be collected from the consumers of a large international fashion retailer, namely the H&M. At first, some information concerning this retailer will be given and it is explained why precisely this concern is chosen to investigate. Secondly, the methods for data collection are explained and a table with the measured constructs and used literature will be given. In the end, the plan of analysis is explicated.
3.1. R
ESEARCHED COMPANYThe researched company, H&M (Hennes & Mauritz) is an international fashion retailer, founded in Sweden, with 2.300 stores spread over 41 markets. The merchandise exists of apparel, cosmetics, footwear and other accessories, all produced under a private label brand. H&M uses a multichannel approach, which means that they sell their products through its retail stores, online stores and catalogue sales. The company is categorized by Levy and Weitz (2009) as a specialty store, producing cheap & chic ‘fast fashion’; each 3-6 weeks the ‘old’ collection is replaced for a new one. This ensures that they offer the most trendy and up-to-date fashion all over the world.
The strategy of H&M is outlined in a few sentences in order to give a clear view of some important strategics;
Target market women, men, teenagers and children, so actually all people up to approximately 55 years.
Merchandise private label brand apparel (sporty to chic), accessories, footwear and cosmetics. Pricing policy accessible price, fashion and quality at the best price.
Promotion program ‘H&M inspires everywhere’, they use all channels in their communication. Moreover, seasonal promotions as well as some smaller local promotions are used.
Stores the store and its display window are the most important communication channel. Each 2-3 years a whole new interiors program is created for a large number of stores. Displays in the windows and most important areas are replaced every ten to 14 days. Some stores use the concept of ‘personal shoppers’ to increase the in-store experience of the customer.
Location the aim is for H&M stores always to be located in the best business location (city centers).
A sustainable competitive advantage is build through the well-established strong brand image and name.
research will give a deep understanding of why customers shop at this store and how these motivations are linked with loyalty. In the end, the most store loyal customers could be defined, which should be the target group of this company in order to remain profitable in the long term.
3.2. S
URVEYThe questionnaire will be a self-administered survey, distributed by email. The aim of the survey is to gather information about the shopping motivations, background characteristics, degree of loyalty and moderating/controlling factors of customers of H&M. Firstly, some introducing questions about demographics will be asked in order to describe the gathered data. After that, questions regarding shopping motivations, loyalty and the moderating factors will be asked. All asked questions in the questionnaire are based on former research. For an example of the questionnaire, see appendix 1.
3.2.1. B
ACKGROUND CHARACTERISTICSBesides the moderating factors described above, some background characteristics could exist that interfere the relationship between shopping motivations and loyalty as well. Therefore the following background characteristics will be included in the questionnaire;
Age
All age groups are included in the target groups of the H&M. However, it is reasonable that each ‘age group’ has different needs and therefore different shopping motivations. Moreover, loyalty towards the H&M could differ as well between these targets. The characteristic age is included in order to describe the formed segments in the end, because it is expected that there are differences in age between the different segments.
Gender
Workman and Lee (2011) state that women score higher on fashion clothing involvement, compared to men. In the proposed hypotheses it is pretended that store loyalty will be higher when involvement is high. Therefore, it is expected that gender will play a moderating role in the relationship between involvement and loyalty. Moreover, Pentecost and Andrews (2010) found significant differences between men and women on the constructs attitude towards fashion and fashion fanship (passion with which someone is significantly conscious and/or involved in the consumption of current fashion). In both cases are the mean of women significantly higher, compared to the mean of men. In addition, Pentecost and Andrews (2010) state that female will shop significantly more frequently than men. Concluding these findings, it seems reasonable to assume that gender plays a moderating role in the relationship between motivations and loyalty in a fashion industry. Therefore, this characteristic is included in this study.
3.2.2. R
ETAIL STORE CHARACTERISTICSThe retail store characteristics are measured based on the study of Wagner and Rudolph (2010). Statements are asked about store characteristics, the participant is asked to rate the importance on a 7-points Likert scale.
3.2.3. S
TORE LOYALTYCustomer engagement
measured on a 7-points Likert scale. Research of Samson (2006) is used to measure the NPS, which will be done by asking just one question. According to the literature, this simple method is appropriate to measure the net promoter score.
Customer loyalty
Willingness to pay
Miller et al., (2011) propose that the willingness to pay could be measured in a direct and indirect way. The indirect way consists of a conjoint analysis in which willingness to pay is calculated on the basis of consumers’ choices among several product alternatives. The direct approach asks the consumer directly to state their willingness to pay, for example, in a questionnaire. For this study, the direct approach seems to be more appropriate, because the quantitative research will be done by a survey. Two measurement items of Ray and Chiagouris (2009) are used in order to measure willingness to pay. Both are measured on a 7-points Likert scale.
Share of wallet
Share of wallet is measured as the share of purchases customers provide to a particular shop in the category (Cooil et al., 2007); (Ray and Chiagouris, 2008); (Friedman et al., 2011). The customer share is measured by simply asking the expenditures in a certain store, in percentage of the whole category (Friedman et al., 2011). In this research, the category is fashion and the store is H&M.
Repurchase intention
The repurchase intention will be measured using the work of Hellier et al., (2003) and Yen and Lu (2008). All questions are asked on a 7-points Likert scale.
3.2.4. M
ODERATING VARIABLESThe moderating variables interfere the proposed relationships between store characteristics and store loyalty, since motivations and involvement could influence the judgment towards the store and therefore lead to more positive/negative evaluated store loyalty.
Shopping motivations
Because of the large amount of research done in this field, measurement items will be derived from existing questionnaires. The measurement items of Arnold and Reynolds (2003) and Kim (2006) are used and combined in order to set up a questionnaire that measures the hedonic and utilitarian shopping motivations of the participants. The questions will be asked on a 7-point Likert scale, this scale is appropriate to measure attitudes. The measurement items are randomly listed, and starts with the question; ‘When shopping at the H&M, the following motivations are strongly present-absent to me’. The participant could choose on a range from 1 to 7, in what degree the motivations are present to them.
Involvement
Involvement with fashion products will be measured using the work of Schramm-Klein et al., (2008). They studied the exclusive involvement in the fashion industry and therefore are these questions highly appropriate to use.
TABLE 1 Measurement scales
Constructs Literature
SHOPPING MOTIVATIONS
Hedonic Shopping Motivations (HM) Arnold & Reynolds
HM1 To me, shopping is an adventure (2003)
HM2 I find shopping stimulating
HM3 Shopping makes me feel like I am in my own universe
HM4 When I am in a down mood, I go shopping in this store to make me feel better HM5 To me, shopping is a way to relieve stress
HM6 I go shopping here when I want to treat myself to something special
HM7 In this shop, I like shopping for others because when they feel good I feel good HM8 I enjoy shopping for my friends and family
HM9 I enjoy shopping around to find the perfect gift for someone HM10 For the most part, I go shopping when there are sales HM11 I enjoy looking for discounts when I shop
HM12 I enjoy hunting for bargains when I shop
HM13 I go shopping with my friends or family to socialize HM14 I enjoy socializing with others when I shop in this store HM15 Shopping with others is a bonding experience
HM16 Here I go shopping to keep up with the trends HM17 Here I go shopping to keep up with the new fashions HM18 Here I go shopping to see what new products are available
Utilitarian Shopping Motivations (UM) Kim (2006)
UM1 It is important to accomplish what I had planned on a particular shopping trip UM2 On a particular shopping trip to this shop, it is important to find items I am looking for UM3 It feels good to know that my shopping trip was successful
UM4 I like to feel smart about my shopping trip
UM5 It is disappointing when I have to go to other stores to complete my shopping UM6 A good store visit is when it is very quickly
CUSTOMER ENGAGEMENT
Positive Word of Mouth (WOM) Jones et al. (2006)
WOM1 I am likely to say good things about this store
WOM2 I would recommend this store to my friends and relatives WOM3 I recommend this store to others
Net Promotor Score (NPS) Samson (2006)
NPS On a scale of 0-10, how likely is it that you would recommend the H&M to a friend or colleague?
CUSTOMER LOYALTY
Willingness to pay (WTP) Ray and Chiagouris
WTP1 I would be willing to pay a higher price at this store over other similar stores (2008) WTP2 I prefer to shop at this store even if another store advertises some deal
Share of Wallet (SW) Friedman et al. (2011)
SW Estimate the percent of your yearly apparel purchases made at the H&M
Repurchase Intention (RI)
RI1 I intend to purchase, at least the same amount of products I purchased last year, Yen and Lu (2008) from the H&M over the next 12 months?
RETAIL STORE CHARACTERISTICS
Please indicate the experience of the following characteristics on your last shopping trip at the H&M
Customer Service Level (CS) Wagner & Rudolph
CS1 Convenient store hours (2010)
CS2 A convenient store location CS3 Fast checkout counters CS4 A convenient store layout CS5 Friendly personnel CS6 Courteous personnel CS7 Helpful personnel CS8 Nice personnel
Type of Assortment (TA)
TA1 Innovative products TA2 Products with new features TA3 Brand new product releases
TA4 Products that express the latest trends and developments TA5 Unique products
TA6 Products that are special TA7 Exclusive products
TA8 Products that you do not see everywhere
Store Atmosphere (SA)
SA1 A pleasant store atmosphere SA2 Attractive store facilities SA3 Appealing store displays SA4 Nice store decor
Prices (P)
P1 Products at reduced prices P2 The best value for money P3 Items on sale
P4 The lowest price for certain products among different stores CUSTOMER CHARACTERISTICS
Involvement with products (IP) Schramm-Klein et al.
Please indicate to what degree the proposed (2008)
statements fit your own thinking
IP1 I buy new clothing fashions earlier in the season than most others/ I buy new clothing fashions later in the season than most others
IP2 I give a great deal of information about new clothing fashions to my friends/ I give very little information about new clothing fashions to my friends IP3 I am more interested in clothing fashions than most others/
I am less interested in clothing fashions than most others
IP4 I am more likely to be asked for advice about new clothing fashions than most others/ I am less likely to be asked for advice about new clothing fashions than most others.
The official questionnaire is placed in appendix 1. In order to ensure that respondents fill in the questionnaire as requested, some items are reverse scored or asked in another sequence. This means that the following action should be undertaken before the data could be analyzed;
- All the IP items should be reverse scored, in order to make sure that a low score means low involvement with the product.
3.3. S
AMPLINGThe population of this research is all male and female that has an age between 10 and 60 years old. The target population is all people within this group that have shopped in a Dutch H&M store in the last year. It is hard to estimate the exact amount of people in this target population, but due to the broad target of H&M this target population is expected to be very large. Therefore a sample, a subgroup of the population selected for participation in the study, is needed.
3.3.1. S
AMPLE SIZEThe restricted time scope of this research, compared with the large target population, makes it impossible to gather information from all the participants in the sample. Therefore, a rule of thumb will be used to determine the amount of respondents; as much as possible within a time scope of two weeks.
3.3.2. S
AMPLING TECHNIQUEA nonprobability sampling technique will be used to select the respondents. A probability sampling technique seems not appropriate in this case, because there is no register of the target population. Respondents will be selected because they happen to be in the right place at the right time, this is called convenience sampling.
3.4. P
LAN OF ANALYSISThis part discusses the statistic tools that will be used to analyze the gathered data. It shortly explains which statistic tests will be used in order to test the proposed hypotheses. Moreover, the reliability analysis of the measurement items is outlined.
3.4.1. R
ELIABILITY ANALYSIS OF SCALESTABLE 2 Cronbach’s alphas
Measurement items Cronbach’s alpha
SHOPPING MOTIVATIONS
Hedonic Shopping Motivations (HM) .914
Utilitarian Shopping Motivations (UM) .649
CUSTOMER ENGAGEMENT
Positive Word of Mouth (WOM) .954
Net Promotor Score (NPS) -
STORE LOYALTY
Willingness to pay (WTP) .721
Share of Wallet (SW) -
Repurchase Intention (RI) .769
RETAIL STORE CHARACTERISTICS
Customer Service Level (CS) .841
Type of Assortment (TA) .894
Store Atmosphere (SA) .863
Prices (P) .760
CUSTOMER CHARACTERISTIC
Involvement with products (IP) .898
TABLE 3
Cronbach’s alphas of the factors
Factor 1 .848
HM1 To me, shopping is an adventure .825
HM2 I find shopping stimulating .764
HM3 Shopping makes me feel like I am in my own universe .775
Factor 2 .907
HM4 When I am in a down mood, I go shopping in this store to make me feel better .825
HM5 To me, shopping is a way to relieve stress .825
HM6 I go shopping here when I want to treat myself to something special .942
Factor 3 .920
HM7 In this shop, I like shopping for others because when they feel good I feel good .872
HM8 I enjoy shopping for my friends and family .831
HM9 I enjoy shopping around to find the perfect gift for someone .947
Factor 4 .913
HM10 For the most part, I go shopping when there are sales .920
HM11 I enjoy looking for discounts when I shop .843
HM12 I enjoy hunting for bargains when I shop .859
Factor 5 .735
HM 13 I go shopping with my friends or family to socialize .519 HM 14 I enjoy socializing with others when I shop in this store .480
HM 15 Shopping with others is a bonding experience .870
Factor 6 .885
HM 16 Here I go shopping to keep up with new trends .757
HM 17 Here I go shopping to keep up with the new fashions .814 HM 18 Here I go shopping to see what new products are available .936
Factor 7 .719
UM1 It is important to accomplish what I had planned on a particular shopping trip .543 UM2 On a particular shopping trip to this shop, it is important to find items I am looking for .602 UM3 It feels good to know that my shopping trip was successful .684
UM4 I like to feel smart about my shopping trip .758
Factor 8 .153
UM5 It is disappointing when I have to go to other stores to complete my shopping trip -
UM6 A good store visit is when it is very quickly -
Looking at the Cronbach’s alphas of the factors, table 3 shows that each factor has a satisfying alpha (>0.6), except factor 8. The ‘if item deleted’ scores are in most cases satisfying as well, but there are a few cases that leads to higher alphas if an item is deleted. Therefore, the underscored items will be removed from the data; HM6, HM9, HM15 and HM18. HM10 will not be removed, since the change in alpha is minimal. The newly calculated alphas and if item deleted scores are presented in table 4.
boundary. However, this alpha is not very high compared to the other alphas. Moreover, the alpha rises to 0.683 when UM6 is deleted and to 0.719 when the items UM5 and UM6 are deleted. Therefore, item UM5 and UM6 will be removed and factor 7 will consist of UM1 till UM4 (table 4). Table 4 shows that the score will be even higher when UM4 is deleted as well, however this is just a small change, and therefore this item will not be deleted.
The factors in table 4 obtained the labels that are proposed in the literature by Arnold and Reynolds (2003) and Kim (2006).
TABLE 4
New Cronbach’s alphas of the factors
Adventure .848
HM1 To me, shopping is an adventure .825
HM2 I find shopping stimulating .764
HM3 Shopping makes me feel like I am in my own universe .775
Gratification .942
HM4 When I am in a down mood, I go shopping in this store to make me feel better -
HM5 To me, shopping is a way to relieve stress -
Role .947
HM7 In this shop, I like shopping for others because when they feel good I feel good -
HM8 I enjoy shopping for my friends and family -
Value .913
HM10 For the most part, I go shopping when there are sales .920
HM11 I enjoy looking for discounts when I shop .843
HM12 I enjoy hunting for bargains when I shop .859
Social .870
HM 13 I go shopping with my friends or family to socialize - HM 14 I enjoy socializing with others when I shop in this store -
Idea .936
HM 16 Here I go shopping to keep up with new trends .757
HM 17 Here I go shopping to keep up with the new fashions .814
Achievement .719
UM1 It is important to accomplish what I had planned on a particular shopping trip .543 UM2 On a particular shopping trip to this shop, it is important to find items I am looking for .602 UM3 It feels good to know that my shopping trip was successful .684
UM4 I like to feel smart about my shopping trip .758
3.4.2. M
ULTIPLE REGRESSIONTwo types of multiple linear regressions will be executed;
- The main effects; these models will measure only the direct relation between the store characteristics and involvement with fashion (independent variables) and the two loyalty measures (dependent variables).
- The second regression models include all the independent variables, as well as the moderating factors, and are therefore able to determine the proposed relations within all the hypotheses. These models will be performed including just the categories ‘hedonic’ and ‘utilitarian’ motivations. After that, the model will be performed with the 7 shopping motivation factors, in order to find out which specific motivation accounts for the influence of hedonic/utilitarian motivations.
The second model will use all the independent variables. Hence, moderating factors should be included as interaction terms within the regression equations. These interaction terms measure the extent to which the relationship between an IV and a DV depends on the level of other IV’s in the model. The variable for the interaction term is constructed by multiplying the value of IV1 by the value of IV2. Before calculating the interaction terms, the independent variables should be mean-centered; this means that for all scores of 1 variable the overall mean of that particular variable is subtracted. This is done for all the independent variables that are involved as an interaction term. The mean-centered independent variables obtain the additive ‘_mean’.
After this, the interaction terms (IT) in the models are constructed by multiplying all the independent variables one by one with the moderating variables. The independent variables are customer service, type of assortment, store atmosphere and price level. The used moderating variables are hedonic motivations, utilitarian motivations, fashion involvement and the 7 shopping motivation factors (adventure, gratification, role, value, social, idea, and achievement). The legend for the constructed interaction terms is displayed in appendix 2.1.
Multicollinearity
Besides, the presence of multicollinearity should be taken into account when performing a regression analysis. This phenomenon is a state of very high intercorrelations among independent variables, which could lead to several problems (Malhotra, 2005). Therefore, first a multicollinearity check will be done in order to find out whether it is present or not. This check includes the Tolerance score and VIF (Variance for Inflation). Within an ideal situation, the tolerance score should be higher than 0.1 and the VIF score should be lower than 10, indicating a low degree of multicollinearity (Field, 2000). Each model should be checked, to make sure that the contribution of one variable in the model is masked by another variable. Subsequently, the regression models are tested and appendix 2.2 shows the outcomes. From this appendix could be concluded that all variables have a low degree of multicollinearity since all the tolerance scores are > .122 and all VIF scores are < 8.205.
4
RESULTS
This chapter describes accurately the gathered data. Moreover, the results of the analyses will be discussed. First, some descriptive statistics concerning the data will be given. Afterwards, the statistical tests that will test the proposed hypotheses are performed and the outcomes will be discussed shortly.
4.1. D
ESCRIPTIVE STATISTICSIn this paragraph a few characteristics of the research sample will be described. The total amount of respondents that have started to fill in the questionnaire is 165. However, due to some respondent bias, the actual response rate is 149.
Gender
The distribution between men and women is as follows;
Women N=96 %=64.6
Men N=53 %=35.4
This was expected, since the questionnaire is sent towards more women compared to men. Moreover, a condition to fill in the questionnaire was that people should have visited a physical store of the H&M once in the last year. It was expected that more women compared to men would satisfy this condition.
Age
Furthermore, the distribution between ages is as follows.
Figure 2: The distribution of ages over the respondents
