Customer Perceived Value of Credit Card Rewards

Transcription

1 Faculty of Education and Economic Studies Department of Business and Economics Customer Perceived Value of Credit Card Rewards - A study on Canadian Consumers Lisa Smedley 2013 Thesis, C-level, 15 credits Business Administration Bachelor s thesis in Business Administration Bachelor of Business Administration Supervisor: Jonas Kågström Examiner: Lars-Torsten Eriksson 0

2 Abstract Title: Customer Perceived Value of Credit Card Rewards - A study on Canadian Consumers Level: Final assignment for Bachelor s Degree in Business Administration Author: Lisa Smedley Supervisor: Jonas Kågström Date: January Aim: The aim of this study is to investigate what influences Customer Perceived Value; where Canadian consumers preferences lie in terms of rewards in the Canadian credit card industry. Method: After researching previous studies and determining what constructs have been utilized prior on similar research topics, I implement a quantitative, and to some extend iterative, research approach. Through survey research, I investigate Canadian consumer preferences through a survey sample of 124 Canadian consumers in Calgary, Alberta, Canada. Result & Conclusions: One finding in the study indicates that utilitarian benefits, which provide financial gain for the card holder, are perceived by respondents as the most valuable reward. Another finding is that inexperienced credit card holders see significantly greater value in symbolic benefits than experienced card holders do. The present study does not support the theory that customer involvement influences the customer s perception of rewards. 1

3 Suggestions for future research: More extensive research is needed on the subject of whether Canadian consumers perceived value of rewards is influenced by their level of involvement in their credit card. Also, studies involving additional factors that could possibly determine a consumer s perception of rewards, such as income and ethnicity should be investigated for a more wellrounded understanding of customer preferences. Contribution of the thesis: The present study contributes with new findings that can be of substantial significance for Canadian financial institutions as it provides insight into what credit card rewards Canadian consumers perceive as being valuable to them. Key words: Rewards programs, credit cards, customer loyalty, perceived customer value, timing of reward, type of reward, dimension of benefit, utilitarian, hedonic, symbolic 2

4 Acknowledgements First, I would like to thank my Supervisor Jonas Kågström, for his contagious optimism, ambition and passion for research. With invaluable insight he has guided me through composing this thesis at long-distance from Gävle, Sweden. I would also like to thank Jenni M. Karl for helping me to gain access to the Brain and Behaviour class at the University of Lethbridge. Thank you, also, to everyone in Calgary who participated in my survey investigation Lethbridge, Canada Lisa Smedley 3

5 Table of Contents 1 Introduction The effects of credit card rewards on businesses and consumers Customer rewards as firms marketing tools and profit boosters Research question Purpose Theory and Literature overview Literature outline Customer Perceived Value Potential constructs Involvement Type of reward Timing of reward Target of attitude Dimension of benefit Summary of theory The four constructs selected for use in the current study and my first model of their expected correlation with each other A first model of the correlation between the chosen constructs for Customer Perceived Value Methodology Ontological and epistemological considerations Research methods for the present study Approach Building the theoretical foundation Data collection and respondent selection Pearson Correlation Factor Analysis Reliability, validity and generalizability Possible methodology errors

6 3.5.1 Errors in quantitative research Errors in survey research Empirical findings Findings from the survey investigation Level of Involvement: High versus low Timing of rewards: Immediate versus delayed Type of rewards: Direct versus indirect Dimension of benefit: Hedonic, Utilitarian and symbolic benefits Additional comments about compilation of survey results Analysis Pearson s Correlation between constructs Level of Involvement Type: Direct versus Indirect rewards Timing: Immediate versus Delayed rewards Dimension of benefits: Utilitarian, Hedonic and Symbolic Additional, strong, correlations between constructs Factor Analysis Component Component Component Component Component A revised model of Customer Perceived Value 80 6 Conclusions Managerial Implications 82 7 References Appendix

7 Table of figures Figure 1. Increase in Loyalty Program research Figure 2. Map of references; Rewards programs...14 Figure 3. Map of references; Means of payment...15 Figure 4. Compilation of Zeithaml s definition of Customer Perceived value 16 Figure 5. Zeithaml s definition of Customer Perceived Value (as cited in Ravald & Grönroos, 1996, p. 21).. 16 Figure 6. Ravald & Grönroos definition of Customer Perceived Value (1996, p. 23) 16 Figure 7. Potential constructs for the present study. Displays formerly used means of categorization of rewards.19 Figure 8. Types of Reward schemes (Dowling & Uncles, 1997, p. 12).26 Figure 9. Perceived Benefits of Loyalty Programs. (Mimouni-Chaabane & Volle, 2010, p. 33) 29 Figure 10. The four constructs selected for use in the present study.33 Figure 11. A first model of the correlation between the chosen constructs for Customer Perceived Value.36 Figure 12. Deductive approach (Bryman & Bell, 2003, p. 12)..39 Figure 13. Inductive approach (Bryman & Bell, 2003, p. 12) 39 Figure 14. KMO and Bartlett's Test...45 Figure 15. Bryman and Bell s four sources of error in social survey research (2003, p. 110)..49 Figure 16. Each respondent s age in relation to their level of experience of holding at least one credit card 51 Figure 17. Question 1.52 Figure 18. Responses to level of involvement in relation to each respondent s age..53 6

8 Figure 19. Male and female responses to level of involvement.53 Figure 20. Question 2.54 Figure 21. Question 4.55 Figure 22. Question 3.56 Figure 23. Question 5.57 Figure 24. Question 6.58 Figure 25. Question 7.58 Figure 26. Question 8.59 Figure 27. Question 9.60 Figure 28. Question Figure 29. Question Figure 30. Question Figure 31. Question Figure 32. Question Figure 33. Question Figure 34. Question Figure 35. Question Figure 36. Question Figure 37. Differences in answers between men and women 66 Figure 38. Similarities in answers between men and women 67 Figure 39. Answers to question 12 in relation to age.67 Figure 40. Similarities in responses between ages.68 Figure 41. Rotated Component Matrix...76 Figure 42. A revised model of Customer Perceived Value 80 7

9 1 Introduction In this chapter, the effects that credit card rewards have on the economy, businesses and consumers will be discussed, as well as reasons as to why businesses decide to implement them. Research questions and the purpose of the present study will also be presented here. 1.1 The effects of credit card rewards on businesses and consumers Loyalty programs have two general aims: to increase sales revenues and to maintain existing customers (Uncles, Dowling, & Hammond, 2003, pp ). Uncles et al. claim that the foundation for loyalty programs popularity lies in the idea that business profits can be increased by accomplishing either one of these two aims. Stereotypically, loyalty programs offer customers financial and social rewards to reinforce purchasing behavior (Uncles et al., 2003, p. 294) and rewards used in the credit card industry are no different: credit card firms adopt rewards programs to promote consumer usage of their credit card. Ching & Hayashi (2010, p. 1783) found that consumers who s primary method of payment is credit and debit card would all reduce their usage of the card if their payment card rewards were removed. They also found that consumers were more enticed to use their rewards payment card for larger transactions. Carbó-Valverde and Liñares-Zegarra's study also suggested that removing rewards from consumers payment cards can make consumers reduce their payment card usage (2011, p. 3276), and thus retrogress to start using cash as their primary payment method. Additionally, earlier studies performed individually, by both Feinberg and Soman, have shown that consumers are more prone to use credit cards to pay for more durable products in relation to products with a shorter shelf-life (as cited by Carbó-Valverde & Liñares-Zegarra 2011, p. 3276). Furthermore, studies performed by Bolton, Kannan, & Bramlett (2000, p. 106) have 8

10 shown that consumers who are members of credit card rewards programs tend to overlook negative experiences with their card issuing financial institutions, as well as resulting in them paying less attention to competing firms offers (2000, p. 105). Wirtz, Mattila, & Lwin, (2007, p. 332) suggest that because consumers rarely have a psychological attachment to their credit card issuer, presenting credit card holders with a desirable rewards program is probable to increase customer loyalty. Maritz Canada s 2012 report on Customer loyalty programs showed that 92% of Canadians are members of at least one loyalty program of some kind. The same study showed that 31% of all Canadians, 49 % of them being high income Canadians, would switch credit card providers if it wasn t for the loyalty program their card issuer offers (2012, p. 2-4). In 2006, the annual revenue for MasterCard and Visa credit cards was estimated at $30 billion USD, solely from interchange fees. Of those fees, rewards were estimated to account for 44% of the total amount (Ching & Hayashi, 2010, p. 1775). However, credit card rewards are not only affecting credit card firms economy. Using payment cards as a primary payment method, instead of cash or cheques, can possibly reduce the overall cost of our world economy and at the same time increase overall sales (Ching & Hayashi, 2010, p. 1773). The transition from cash to card payments has thus become one of the main ambitions of both financial planners and financial institutions today (Carbó-Valverde & Liñares-Zegarra, 2011, p. 3286). Research has shown that one of the positive effects that credit card rewards programs have on consumers method of payment is that it encourages, and increases, the total number of transactions made each day in relation to paper based payment (Simon, Smith & West, 2010, p. 1771; Carbó-Valverde & Liñares-Zegarra, 2011, p. 3286). Another positive outcome of credit card rewards is that being rewarded for using payment cards appears to increase consumers spending overall (Ching & Hayashi, 2010, p. 1773). Both of these effects can thus be interpreted as important not only in a business economy perspective but for long-term national and international economy planning as well. 9

11 Although the subject of credit card rewards programs can be viewed as an international development issue, the present study will focus on credit card rewards from a general business perspective, in an attempt to investigate consumer s perceived value of credit card rewards. 1.2 Customer rewards as firms marketing tools and profit boosters Rewards as customer marketing tools have been used in the credit card industry for more than 25 years (Ching & Hayashi, 2010, p. 1774) but loyalty programs in general have been around for much longer. The original loyalty programs in fact started at least as early as the in 1950 s (Davis, 1959, p. 141) and consisted of trading stamps. The program was referred to as the gold stamp program (Shugan, 2005, p. 188), enabling families to receive quantity discounts by collecting stamps at the time of purchase which could later be traded in for goods. In 1958, approximately two thirds of American families belonged to at least one such program (Shugan, 2005, p. 186). With the increasing popularity of rewards programs, it did not take long for curious researchers to take on the task of determining their proclaimed efficiency. According to Davis (1959, p. 141), several articles had already been written on the subject of loyalty programs by the time he published his own in the late 1950 s. The stamps, however, disappeared when new owners took over the stores that had first implemented them. The new stores offered lower prices overall and the trading stamp loyalty programs disappeared. During the 1970 s researchers in Europe found that merchants in B2B-businesses who established close professional bonds with their customers had more loyal customers who gave their supplier a larger share of wallet, i.e. a large portion of their spending (Dowling & Uncles, 1997, p. 3). This spiked a strong interest in marketers and would increasingly be the target of future customer loyalty research. More current studies have shown that customers who are satisfied with the reward program they are participating in are willing to give the company a larger share of wallet than those customers who are not 10

12 satisfied with their rewards program (Demoulin & Zidda, 2008, p. 11). Shugan (2005, p. 191) states that: True loyalty programs invest now for the future and trust rather than demand trust. But further claims that instead of creating assets by following these rules, many loyalty programs create long-term liabilities for the company. Dowling and Uncles note six general reasons as to why businesses adopt loyalty programs: Maintaining sales, profits and margins; adding value for existing customers; increasing existing customers cross-product sales; separating the brand from competitors ; and lastly preventing competitors from presenting the brand s customers with other comparable service or product loyalty proposals (Dowling & Uncles, 1997, pp. 4 5). Additionally, they suggest that loyalty programs can help the brand stand out to customers as well as aid them in standing strong in a market place that is nowadays highly influences by loyalty rewards. The author s refer to this as the Me-too pressure (Uncles et al., 2003, p. 310). Customer loyalty programs discriminate against non-loyal customers and because it is believed that non-loyal customers generally burden the brand with higher average service costs, this can be viewed as a positive side effect. Loyalty programs can funnel out those customers and thus aid the company in being more profitable with existing and loyal customers (Shugan, 2005, p. 191). The idea of targeting loyalty programs to a company s most valuable customers is supported by Yi & Jeon (2003, p. 231). They suggest that by discouraging customers who do not add as much value to the company, the program turns into a self-improving tool for the brand. While the reasons as to why credit card companies decide to implement reward programs might to some extent differ between firms it is likely that adoption of rewards programs is, partly, a result of the firms battles against competitive parity in a fiercely competitive industry (Dowling & Uncles, 1997, p. 5; Agarwal, Chakravorti, & Lunn, 2010, p. 19). 11

13 1.3 Research question As mentioned earlier, several studies have shown that a rewards program that is perceived as valuable to the customer will not only increase their loyalty to the firm but will increase their overall spending habits. It is thus clear that credit card rewards affect consumers purchasing decisions, but do consumers settle for just any kind of reward or do they have a strong preference for one certain type of reward? And when do they want to receive that reward, immediately at the time of their purchase or later on? Mimouni-Chaabane & Volle (2010, p. 32) noted that the majority of existing research focuses on how the businesses finances benefit from such a program. In other words, a gap had been left for the question of customer perceived benefits. But in order to achieve an increase in profits, credit card firms must offer their customers rewards that those customers perceive as valuable. This study will thus, from a business economics perspective, concentrate on questions such as how do buyers value rewards in the credit card industry? What types of rewards are most generally preferred among consumers in the credit card industry? What factors affects consumer preferences for credit card rewards? Is there a distinct difference in preferences between male and female cardholders? Is there a difference in preferences in relation to cardholders ages? 1.4 Purpose The purpose of this study is to investigate what credit card rewards Canadian consumers perceive as being valuable to them. By utilizing a business researching method I will be describing, analyzing and comparing today s consumers perceived value of credit card rewards through a survey investigation. I hope to be able to conclude whether credit card firms should incorporate drastic changes into their rewards programs to catch consumers interests, increase their loyalty to the firm and thus increase firm profit. 12

14 2 Theory and Literature overview In this chapter, the theory used for the empirical study will be presented. The chapter begins with a summarizing literature review, followed by the concept of customer perceived value. Constructs used in prior research to determine perceived customer value of loyalty programs will then be presented, as well as the constructs that have been selected for use in the current study. 2.1 Literature outline The amount of available research on the subject of loyalty programs has increased immensely over the last three decades. A search on ISI Web of Science provides several hundreds of articles on the subject. Figure 1. Increase in Loyalty Program research (ISI) The vast majority of prior research on loyalty programs has been written from firms financial perspectives and thus entails instructions on how to avoid negative financial implications during and post 13

15 implementation. There is, however, some research encompassing consumer preference and bias towards credit card rewards. In order to determine what components in loyalty programs that are most often preferred by consumers, authors have organized rewards into different categories. The following text entails a short presentation of some of these categories. Dowling and Uncles (1997) and Yi and Jeon (2003) categorized rewards into type of reward and timing of reward. To these categories, they also added the construct of customer involvement as a determining factor. Other authors, such as Keh and Lee (2006) who performed similar research, chose to exclude the construct of involvement completely. Kristof de Wulf et al. (2003) divided rewards into hard versus soft benefits in their research, taking consumer inputs and outputs into consideration. To provide some insight into how perplexing research on the subject of customer rewards is the first schedule below presents some of the authors referenced in the present study and how they reference each other in their respective research on the subject of investigating the relationship between consumers and rewards programs. Do rewards programs build loyalty for services? Keh, Lee Self-control for the righteous. Kivetz, Simonson The valkue concept and relationship marketing. Ravald, Grönroos Behavioral learning theory: It's relevance to marketing and promotions. Rothschild, Gaidis Measuring consumer involvement profiles. Kapferer, Laurent Do customer loyalty programs really work? Dowling, Uncles Customer satisfaction with services. McDougal, Levesque Credit where credit is due. Parahoo Modelling the relationship between perceived value, satisfactionand repurchasing intentions Patterson, Spreng What drives consumer participation to loyalty programs? De Wulf et al. Perceived benefits of loyalty programs Mimouni-Chabaane, Volle Effects of loyalty programs on value perception, program loyalty and brand loyalty. Yi, Jeon Zaichkowsky: 1985, 1986, 1994 Consumer perceptions of price, quality and value. Zeithaml Implications of loyalty program membership and service experience for customer retention and value. Bolton et al. Figure 2. Map of references; Rewards programs A collection of other articles have been written on the subject of what promotes consumer s means of payment, and whether receiving 14

16 rewards affects that choice. The second schedule below presents some insight into how the authors, whose research is referenced in the present study, connects and refers to one another. Price incentives and consumer payment behavior. Simon, Smith, West The economics of credit cards, debit cards and ATMs: A survey and some new evidence. How do you pay? The role of incentives at the point-of-sale. Arango et al. How effective are rewards programs in promoting payment card usage? Empirical evidence. Carbo - Valverde Why do banks reward their customers to use their credit cards? Agarwal et al. The failure of competition in the credit card market. Ausubel Payment card rewards programs and consumer payment choice. Ching, Hayashi An empirical analysis of payment card usage. Rysman Why use debit instead of credit? consumer choice in a trillion-dollar market. Zinman Debit or credit? Zinman Figure 3. Map of references; Means of payment Throughout the process of finding and reading articles on the topic of credit card rewards, all whilst critically examining their research methods and results, a selection of constructs and determining factors have been compiled for use in the present study. A presentation of all these constructs will follow in the coming chapters. However, first, a discussion about what the constructs will be leading up to in the study: Customer Perceived Value. A selection of researchers opinions on, and previously created definitions of, Customer Perceived Value will thus be presented forthwith. 2.2 Customer Perceived Value Customer perceived value is defined differently by different authors. It is thus difficult to come by a consistent definition of the term but according to Dowling and Uncles it is the customer s perceived value that creates price insensitivity, not brand loyalty (1997, p. 14). However, depending on the context in which it is being studied, value can take on different meanings: Patterson and Spreng noted that in an 15

17 economic context, value can be synonymic with function or desirability, whilst in a marketing context it is most often defined from the consumer s perspective (1997, p. 416). Zeithaml (1988, p. 14) defined perceived value as: The consumer s overall assessment of the utility of a product based on perceptions of what is received and what is given : Customer Perceived Value = Utility of Product (Received Given) Figure 4. My compilation of Zeithaml s definition of Customer Perceived value Zeithaml s definition is similar to that of Kent B. Monroe, which suggests that customer perceived value is the difference between consumer benefits and consumer sacrifice. Here, benefits represent the physical attributes of the product or service, and sacrifice the financial cost. Customer-perceived value = Figure 5. Zeithaml s definition of Customer Perceived Value (as cited in Ravald & Grönroos, 1996, p. 21) Ravald and Grönroos suggest that differences in consumers perceived value is dependent on the consumer s personal values, preferences, needs and on their personal financial situation. According to the authors, establishing what value the customer is requesting must be the firm s first aim in delivering customer satisfactory value (1996, p. 22). Furthermore, the relationship between the firm and customer must be taken into account when calculating perceived value, stating that the components of the episode (the core product and the firm s surrounding services) alone, is not enough. Grönroos and Ravald thus provide a model that differs from Monroe s. Total Episode Value = Perceived Benefits Perceived Sacrifice Episode Benefits + Relationship Benefits Episode Sacrifice + Relationship Sacrifice Figure 6. Ravald & Grönroos definition of Customer Perceived Value (1996, p. 23) 16

18 Bolton et al. found that members of loyalty programs of financial services were less sensitive than other customers to perception of both lower services and price disadvantages of their company (2000, p. 105). However, the authors also note that for a program to have a long-term positive effect on its customers their experiences with the programs must be mostly pleasant (2000, p. 96). McDougall and Levesque found that perceived value, together with service quality, was the most important driver in determining customer satisfaction (2000, p. 407). The authors conducted a study in the purpose of investigating the connection between core service quality (consisting of perceived value and relational service quality), customer satisfaction and future intentions. They based their theory on the idea that customer satisfaction is a direct result of customer perceived value, and that level of satisfaction is what determines consumers future intentions. Customer Perceived Value Customer Satisfaction Future Intentions Customer Perceived Value Customer Satisfaction Future Intentions Figure 6. My compilation of McDougall & Levesque s definition of Customer Perceive value (2000, p. 395) Summary Each customer s perceived value of a product or service is believed to influence their loyalty to a brand (Dowling & Uncles, 1997, p. 14). However, the definition of what customer perceived value is differs between researchers. Zeithaml believed perceived value was the consumer s overall impression of the product based on what had been received and what had been given. Kent B Monroe, similar to Zeithaml, thought of customer perceived value as the difference between the physical attributes of the product or service and the financial cost of the purchase. Ravald and Grönroos created a model that was based on the belief that customer perceived value is dependent on the consumer s personal values, preferences, needs and on their personal financial situation. 17

19 The definition of customer perceived value that will be employed in the current study is that of McDougall and Levesque, where customer perceived value is the connection between core service quality, customer satisfaction and future intentions. The theory that a customer s satisfaction with his or her credit card rewards will predict whether they will be loyal to their credit card firm in the future is thus employed throughout the present study. 18

20 2.3 Potential constructs Many constructs have been developed to determine wherein the optimal key to customer loyalty lies and according to Della Porta and Keating, the more widespread a concept is, the less informative it turns out (2008, p. 92). Here, five of the constructs used in prior research of customer rewards will be presented in their most concentrated form, four of which will be selected for use in the present study. Customer Perceived Value Involvement: *High vs. Low Type of Reward: *Direct vs. Indirect *Advertised vs. Unexpected Timing of Reward: *Immediate vs. Delayed Target of Attitude: *Deal vs. Brand loyalty Dimension of Benefit: *Utilitarian, Hedonic or Symbolic *Hard vs. Soft *Primary vs. Secondary Figure 7. Potential constructs for the present study. Displays formerly used means of categorization of rewards Involvement Customer involvement is generally measured through high versus low levels of involvement, reflecting the level of interest that the customer has in selecting and knowing their brand or product (Dowling & Uncles, 1997, p. 16; Yi & Jeon, 2003, p. 234). A customer with high a 19

21 level of involvement knows their brand and what it has to offer very well. High involvement customers are well educated about their brand s loyalty program, observant towards promotions and will thus fully benefit from all that is offered to them by their brand (Parahoo, 2012, p. 5). Parahoo noted that customer involvement plays a highly important role in determining consumer behavior to the credit card industry (2012, p. 5) and suggested that there is a great need for credit card firms to concentrate on increasing levels of involvement in their customers (2012, p. 14). Customer Involvement Profile Laurent and Kapferer developed CIP, the Customer Involvement Profile in It states that the five facets of involvement are (1985, p. 43): 1. The consumer s perceived significance of the item 2. The perceived risk linked to purchasing the item 3. The sign/symbolic value of the item ascribed by the consumer 4. The Hedonic value of, or the consumers emotional appeal for, the item 5. The perceived undesirable outcome of making a poor purchasing decision According to the authors, not only would the Customer Involvement Profile create a better understanding for involvement dynamics but it could be used to segment the market: instead of just measuring high versus low levels of involvement, customers could show high involvement on some facets and low on others (Laurent & Kapferer, 1985, p. 52). Personal Involvement Inventory Judith Lynne Zaichkowsky disapproved of the CIP model, claiming it suggested that involvement could be measured as a stable state (1994, p. 59). Zaichkowsky also found that the construct of involvement had been measured in several different fields: advertisement, products and purchases, by authors using different measures and thus providing results with major spread (1985, p. 341). Zaichkowsky s own 20

22 objective was thus to develop a measure that would include all aspects of involvement and allow researchers in all divergent fields to use one reliable method. In 1985, Zaichkowsky introduced a context-free 20 item scale, measuring the motivational state of involvement, calling it the PII: Personal Involvement Inventory (1994, p. 59). It was based on this three factor conceptualization of involvement: 1. Personal: interests, values and needs 2. Physical: differentiating traits in an item that appeals to consumers 3. Situational: factors that momentarily increase consumers interest in the item Each individually, two or all three of these factors together were claimed to show the level of involvement with stimulus for an item. The author (1985, p. 342) concluded that high involvement is generally a result of a consumer s personal relevance to an item. One year after the personal involvement inventory was released there was still no clear definition of involvement (Zaichkowsky, 1986, p. 4). However, Zaichkowsky could confirm that involvement as a construct is a natural motivator and that when humans are involved they comprehend magnitude and listen and behave in a different manner than when uninvolved (1985, p. 12). In 1996, Zaichkowsky published a new article, defending, revising and reducing the PII after it had received criticism saying that it did in fact not provide equal validity for different fields of involvement study (1994, p. 59) High versus low involvement Grahame R. Dowling and Mark Uncles studied involvement for product types and involvement for customer types (1997, p. 10). In their study, products and brands could have a high or low involvement status. As examples of low involvement brands the authors mentioned gas stations and every-day-food brands, whilst for high-involvement products they referred to the car manufacturer General Motors. Typically, low involvement brands, or me-too brands as Dowling and Uncles referred to them, should have less extensive rewards programs attached to them because low involvement products are often bought out of consumer habit. High involvement products, on 21

23 the other hand, should offer more extensive incentives (Dowling & Uncles, 1997, p. 16) as it is expected to take more effort to entice the customer to choose a certain brand over competitors when the customer finds the purchase to be highly important to them. Furthermore, Dowling & Uncles suggest that there are two decisions for the buyer to make at the time of any purchase. One is the category decision, which the authors exemplify as deciding whether to take the bus or plane to a destination, and the other is brand decision; what air transport service company should I fly with? For highinvolvement purchases the authors believed that consumers are highly involved in both decisions, whilst for low involvement purchases the involvement level for both decisions is low, although slightly higher for the category decision (1997, p. 16). Youjae Yi and Hoseong Jeon s study also shows that involvement effects how customers react to rewards programs (2003, p. 229). Their study was drawn on that of Dowling and Uncles with the exception of adding the construct of time frame for rewards. As far as the construct of involvement goes, Yi and Jeon s study suggests that involvement moderates the effect of both type of reward as well as that of timing (2003, p. 237). For high involvement situations direct rewards proved to be more efficient for consumers to build loyalty to a brand than indirect rewards. In the low involvement situation, the type of reward did not impact the relationship between consumer and brand but timing of reward did: immediate rewards proved to be more effective for low involvement customers than delayed rewards (Yi & Jeon, 2003, p. 229). In high involvement situations, direct rewards were a greater success than indirect rewards but timing of rewards made no difference in perceived value of the loyalty program (Yi & Jeon, 2003, p. 236). Summary For many years, the construct of involvement was undefined but researchers were still aware that it could act as a determining factor in how consumers perceived loyalty programs. Zaichkowsky (1985) divided consumer involvement up into several possible levels while Laurent and Kapferer (1985) created the five facets to establish 22

24 consumers levels of involvement. Other, more recent, studies conducted by authors such as Parahoo (2012), Yi and Jeon (2003) and, although not as recent, Dowling and Uncles (1997) measure consumers levels of involvement as either high or low. However, they all agree that the consumer s level of involvement affects their perceived value of, and satisfaction with, a product or service Type of reward Primary versus secondary reinforces Michael L. Rothschild and William C. Gaidis divided reward-types into primary (core products) and secondary (coupons and tokens) reinforcers. Rothschild and Gaidis noted that primary reinforcers were initially much more powerful than secondary but that over time consumers noticed that the secondary reinforcers could be converted for primary ones and thus developed a relatively better liking for the secondary reinforcers (1981, p. 73). Direct versus indirect rewards Dowling and Uncles version of the construct is to some extent comparable to the promotional strategy categorization created by Rothschild and Gaidis. Here, the construct consists of direct rewards, which are directly linked to the brand or product bought; and indirect rewards which are not in any way connected to what the object or service was or where it was purchased (1997, p. 10). Dowling and Uncles suggested that direct rewards should be more efficient in building customer loyalty than indirect rewards are because they encourage the value proposition of the product. However, because the authors do not provide readers with any empirical research information, it is unclear what their conclusions are based on. Yi and Jeon (2003, p. 234) concur with Dowling & Uncles in that direct rewards are better suited to enhance loyalty marketing. Yi and Jeon furthermore claim that direct rewards are prone to be given more attention by the customer because they are linked to the product or 23

25 service that the customer found important enough to purchase. Their study also showed that consumer value perception of direct rewards programs surpassed that of programs with indirect rewards for consumers who were highly involved in a purchase (2003, p. 239). Yi and Jeon thus claimed that perceived customer value of rewards can be lessened if an indirect reward is given to consumers with high involvement for the product or service. However, for consumers who had low levels of involvement in their purchase there was no difference in perceived value between direct and indirect types of rewards. Hard versus soft rewards Kristof De Wulf et al. utilized the categorization of hard benefits: i.e. pricing or gifts, versus soft benefits: consisting of additionally provided product information, together with the construct of timing of rewards (Wulf, Odekerken-Schroder, Canniere, & Van Oppen, 2003, pp ). Attempting to prove that consumers prefer to receive both soft and hard benefits immediately, the authors asked 2000 Belgian consumers to answer 16 questions on their preferences for incentive programs (Wulf et al., 2003, p. 77). The results of the study showed that consumers preferred hard, immediate benefits over all other combinations of benefits and soft benefits were only found valuable in combination with hard benefits. Moreover, results showed that consumers found cost of participation and program benefits to be of most significance in determining their participation in a program (Wulf et al., 2003, p. 78). Advertised versus unexpected rewards Patrali Chatterjee performed laboratory experiments on 391 students to investigate how consumers interpret advertised rewards versus unexpected rewards (2007, p. 63). Chatterjee found that those who received unexpected coupons were more satisfied with their overall purchasing experience than those who received advertised coupons. However, those who had received unexpected coupons experienced a higher perception of retailer injustice. The author suggested this was 24

26 because the consumers would perceive handing out unadvertised coupons to be a manipulative move performed by the retailer. Another of Patterjee s findings was that the perceived value of the coupon was lower when received unexpectedly. The authors explained this to be the result of consumers feeling that they had already missed the opportunity to use their unexpected coupon because their purchase had already been completed. Furthermore, value denomination was considered to be most significant when the coupon did not state a specific future start date (2007, p. 65). Summary Several authors have attempted to categorize rewards by separating and dividing them into Types. Rothschild and Gaidis divided them up into primary (core products) and secondary (coupons and tokens) reinforcers. Dowling and Uncles and Yi and Jeon divided rewards up into direct: directly linked to the product or service bought, and indirect: rewards with no link to the product or service bought. Kristof de Wulf et al. separated rewards by categorizing them as either hard: gifts or pricing, or soft: additional product information, whilst Chatterjee categorized rewards into whether the rewards were expected by the consumer or not, and referring to them as advertised or unadvertised Timing of reward Immediate versus Delayed Timing of rewards, also referred to as timing of redemption, is a construct used to separate rewards effect on consumers depending on at what point in time the consumer receives the reward (Rothschild & Gaidis, 1981, p. 73; Wulf et al., 2003, p. 75; Yi & Jeon, 2003, p. 230). The construct of timing of rewards is divided into immediate rewards, which are rewards received upon every visit or at every purchase, and delayed rewards, which are received upon every other-, third-, tenth visit or with accumulation of points (Dowling & Uncles, 1997, p. 12; Yi & Jeon, 2003, p. 230). 25

27 Rothschild and Gaidis found that immediate rewards were almost always preferable to delayed rewards. They suggested that delayed rewards would not necessarily reinforce the consumer s desired behavior but rather their most recent behavior. A delayed reward which the consumer receives through mail will, according to the authors, reinforce the behavior of opening their mail box rather than their previous purchasing behavior (Rothschild and Gaidis, 1981, p. 73). Dowling and Uncles, too, suggested that immediate rewards be used over delayed rewards, stating that psychology research had shown that delayed rewards had a less motivational effect than immediate rewards (Dowling & Uncles, 1997, p. 11). The authors created a matrix showing the connection between direct, indirect, immediate and delayed rewards. Their conclusion was that delayed, indirect rewards were the least efficient for both consumers and firms in attempting to build customer loyalty but was surprisingly still the most often used form of reward program. Directly supports The Product s Value Proposition Type of Reward Other, Indirect Types of Reward Timing of Rewards Immediate Delayed 1 Retailer/Brand 2 Airline Frequent Manufacturer Flyer Clubs, Promotions Coupons & Tokens (Price Promotions) (The GM Card) 3 Competitions 4 Multi-Product & Frequent-Buyer Clubs Lotteries (Fly Buys) (Instant Scratches) Figure 8. Types of Reward schemes (Dowling & Uncles, 1997, p. 12) Yi and Jeon performed experiments where the immediate reward was a scratch-and-win lottery ticket with a 10% chance of winning, and the delayed reward was given at every 10 th visit (2003, p. 235). Their results showed that under low involvement conditions, 26

28 immediate rewards proved to make a greater impact on customers than delayed rewards (2003, p. 237). Hean Tat Keh and Yih Hwai Lee conducted experiments of how type of reward, timing of reward and satisfaction from service interacted in a bank and a restaurant setting (Keh & Lee, 2006, p. 130). Their results differed slightly from prior studies in that when a customer was satisfied with the overall service experience, direct delayed rewards were most efficient in enhancing customer loyalty (Keh & Lee, 2006, p. 133). They suggested that only when customers are dissatisfied with the service experience are direct immediate rewards most efficient. Summary The construct of timing of rewards is divided into immediate and delayed rewards. Immediate rewards being those that the consumer receives upon their first visit or purchase and delayed are those that the consumer must wait to receive. Rothschild and Gaidis concluded, from their study, that immediate rewards were almost always preferred by consumers over delayed rewards. Dowling and Uncles believed that immediate rewards were of greater worth in creating customer loyalty whilst Yi and Jeon determined that preference to either immediate or delayed rewards depended on the consumers levels of involvement. Keh and Lee stated that consumers preferences depended on their levels of satisfaction with a service. 27

29 2.3.4 Target of attitude Deal versus brand loyalty Target of attitude, or deal versus brand loyalty, determines what area of interest has captured the consumer s attention (Yi & Jeon, 2003, p. 233). Some consumers will be interested in a brand because they are enticed with the brand and genuinely like it. Other consumers main focus will be the loyalty program in and of itself because the consumers enjoy shopping for deals and not for specific brands. The target attitude theory consists of categorizing consumers into brand loyal versus deal, or program, loyal. Brand loyal consumers are more likely than program loyal consumers to stay loyal to the brand even after the loyalty program has ended. High involvement consumers are thus more likely to be brand loyal simply because they have put more effort into knowing their brand and already perceive a greater value from the brand or product itself than from the rewards that come with it. Yi and Jeon s study suggested that when consumers perceive that a rewards program is valuable to them, what initially started as program loyalty for low-involvement products can result in a long-term brand loyalty (2003, p. 238). Summary The construct of Target of attitude deals with where a consumer s interest lies. If the consumer s main interest and loyalty is in the actual brand and what it stands for, then that consumer is brand loyal. If the consumer is only willing to buy a product or service because of the rewards that come with the purchase, then that customer is program loyal. According to Yi and Jeon a customer s Target of attitude is, just like type and timing of rewards, dependent on their level of involvement. 28

30 2.3.5 Dimension of benefit Utilitarian, hedonic or symbolic Aida Mimouni-Chaabane and Pierre Volle's study was performed on French members of loyalty programs, investigating preferences for reward benefits (2010, p. 32). Utilitarian, hedonic and symbolic dimensions of perceived benefits were studied. In rewards programs, utilitarian benefits are associated with financial gain and convenience, hedonic benefits are those of entertainment and exploration, whilst symbolic represent a feeling of community and a sense of belonging to an exclusive group (2010, p. 33). The authors found that the perceived benefits and motivations were diverse among consumers (2010, p. 36) and thus consequently suggested that both monetary as well as non-monetary incentives should be integrated into all loyalty programs. Dimensions of Sub dimensions of Definition: Benefits: Benefits: Utilitarian Monetary savings: To spend less and save more money Convenience: To reduce choice and save time and effort Hedonic Exploration: To discover and try new products sold by the company Entertainment: To enjoy collecting and redeeming points Symbolic Recognition: To have a special status, to feel distinguished and be treated better Social: To belong to a group that shares the same values Figure 9. Perceived Benefits of Loyalty Programs (Mimouni-Chaabane & Volle, 2010, p. 33) Kivetz and Simonson (2002, p. 203) conducted multiple studies on the differences in preferences of rewards among consumers. The participants were a total of 5700 passengers, between the ages of 18 and 80, in an airport. All participants were asked to rate non-cash and 29

31 cash lottery prices on five-point scales according to sense of utility (practicality and necessity) and hedonic (pleasure and luxury), some of the studies included a difference in timing of rewards as well. Their results showed that hedonic luxury rewards are generally more effective than utilitarian cash-rewards (2002, p. 212). They suggested that the reason for this was that cash-rewards would likely be spent on necessities, making consumers decline utilitarian rewards and instead pre-commit to hedonic luxuries as rewards (2002, p. 209). Summary Research on Dimension of benefit aims to investigate what aspects of their lives consumers prefer to be rewarded in. When research is focused on rewards programs, utilitarian benefits are associated with financial gain and convenience, hedonic benefits are those of entertainment and exploration and symbolic benefits represent a feeling of community and a sense of belonging to an exclusive group. Mimouni-Chabane and Volle found that preferences were diverse among consumers because motivation for rewards differed. Kivetz and Simonson, on the other hand, found that hedonic rewards were preferred by most consumers and believed that was because consumers felt obligated to spend utilitarian benefits (monetary rewards) on necessities before luxury. 30

32 2.4 Summary of theory Each customer s perceived value of a product or service is believed to influence their loyalty to a brand (Dowling & Uncles, 1997, p. 14). Although four different definitions of customer perceived value have been presented (Zeithaml, Monroe, Ravald and Grönroos, and McDougall and Levesque), the definition that will be employed in the current study is that of McDougall and Levesque. They presented the theory that customer perceived value is the connection between core service quality (consisting of perceived value and relational service quality), customer satisfaction and future intentions. The theory that a customer s satisfaction with his or her credit card rewards will predict whether they will be loyal to their credit card firm in the future is thus employed throughout the present study. The present study is created to determine what rewards are preferred by Canadian consumers and what influences their preferences. A high preference for a specific reward will thus be recognized as one that the customer perceives as being of high value to them. Perceptions of rewards and preferences for rewards will be utilized interchangeably in the present study. Empirical emphasis will be placed on those rewards which Canadian consumers find are of the highest perceived value to them because they are theoretically expected to result in product loyalty. In the theory chapter, five constructs that have previously been used in research on customer reward programs in general and on reward programs in the credit card industry, are presented. The first of these five constructs is that of Involvement, measuring the consumer s level of interest in a product. The second construct presented in the theory chapter is the construct of Type of rewards which, in past research has divided rewards into primary and secondary, direct and indirect and advertised and unadvertised. The construct of Timing of rewards is the third construct presented and divides rewards into immediate and delayed depending on whether the consumer must wait for their reward or not. The fourth construct is that of Target of attitude which deals with where a consumer s interest lies; in the brand or in the rewards program. All three of the latter mentioned constructs; Type and Timing of rewards and Target of attitude have been argued to be greatly influenced by a customer s levels of involvement in a product. 31

33 The fifth, and final, construct presented in the theory chapter is that of Dimension of benefits which aims to investigate what aspects of their lives consumers prefer to be rewarded in: the utilitarian, hedonic or symbolic dimension. In the next chapter, I will explain my reasoning in including only four of these five presented construct in the study. I will also explain how, and in line with which theories, each construct will be utilized. 32

34 2.5 The four constructs selected for use in the current study and my first model of their expected correlation with each other Involvement: High vs. Low Timing of Reward: Immediate vs. Delayed Customer Perceived Value Dimension of Benefit: Utilitarian, Hedonic, Symbolic Type of Reward: Direct vs. Indirect Figure 10. The four constructs selected for use in the present study Construct 1: Involvement. High versus low Dowling and Uncles, Yi and Jeon and Parahoo believe that a customers level of involvement is a determining factor in their perceived value of rewards. The construct of involvement will thus be regarded as an important component in the analysis of the survey sample in the present study. One area of focus in the study will be put on investigating whether involvement is a determining factor in perceived value of credit card rewards too. To be able to measure a possible relationship between involvement and the other constructs, the correlation between respondents levels of involvement with each of their answers to the other constructs will be compared. Construct 2: Timing of reward. Immediate versus Delayed Timing of rewards will be measured as immediate versus delayed rewards because it is a categorization of rewards that is commonly 33

35 reoccurring in previous research about rewards programs as well as applicable in investigating credit card rewards. Immediate rewards in the present study are rewards that can be redeemed instantly upon use of the credit card, whilst delayed rewards will be represented by any rewards that cannot be redeemed at the time of credit card use but for which the consumer must wait. Construct 3: Type of reward. Direct versus Indirect Type of reward is another construct that is commonly reoccurring in previous research and applicable to research on credit card rewards. In investigating types of rewards, those that will be utilized in the current study are direct versus indirect rewards, in line with Dowling and Uncles and Yi and Jeon s research. Direct rewards will be represented by those that are strongly connected to the credit card in and of itself, i.e. concern credit card fees and/or credit card debt. Indirect rewards are all kinds of rewards not directly linked to the credit card, for example department store vouchers or movie tickets. Construct 4: Dimension of benefit. Hedonic, Utilitarian and Symbolic In order to provide Canadian credit card firms with information about where Canadian consumers interests lie, the construct of dimension of benefit will also be included in the study. To investigate in what dimension, or area, of consumers lives in which they prefer to be rewarded, the construct investigates consumers preferences for utilitarian (necessity, financial gain), hedonic (pleasure) and symbolic (feeling part of a group) benefits. Difference between direct rewards and utilitarian benefits in the study Utilitarian benefits are often symbolized by items of financial gain. Because the object of this study is credit card rewards, a clear distinction must be made between direct rewards and utilitarian benefits. In order for the two constructs not to overlap, Utilitarian 34

36 benefits (representing necessities) will be associated with items of financial gain such as vouchers and coupons for Groceries and cash. Direct rewards, however, will be strongly connected solely to rewards of financial gain that are in relation to the actual credit card such as CC fees and CC debt. Construct not included in the empirical study: Target of attitude As mentioned earlier, the construct target of attitude determines whether the consumer is interested in a product or brand because of the product or brand itself or if their interest has been spiked strictly from the appealing idea of the rewards that come with it. Because credit card rewards are not a temporary or time sensitive factor but are instead a highly permanent part of the card, target of attitude is not regarded significant in the present study. The object of this study is not to recognize what any other factors of credit cards are preferred by consumers but for that of its customer rewards. 35

37 2.5.1 A first model of the correlation between the chosen constructs for Customer Perceived Value The model presented below represents the relationships that I expect to find in the empirical findings of the present study. The model is based entirely on the previous research mentioned in the theory chapter: Each respondent s level of involvement is expected to influence their preference for all other constructs. Furthermore, the consumer s overall opinion of the factors contained in each of the selected constructs is expected to conclude what their perceived value of each reward is and thus, to some extent, predict their future intentions of loyalty to their credit card provider. Involvement: High vs. Low Timing of Reward: Immediate vs. Delayed Type of Reward: Direct vs. Indirect Dimension of Benefit: Utilitarian, Hedonic, Symbolic Customer Perceived Value of Rewards Figure 11. A first model of the correlation between the chosen constructs for Customer Perceived Value 36

38 3 Methodology In this methodology chapter, epistemology and ontology is discussed, and execution of collecting prior research and survey data for the current study is presented. Furthermore, my choice of researching method, the study s generalizability as well as attempts to increase both validity and reliability in the study are explained. 3.1 Ontological and epistemological considerations In order for others to accurately interpret my empirical findings, I must give insight into how my research and findings should be interpreted. It is thus necessary that I share what my own interpretations of what reality and knowledge is. Bryman et al. refer to this as double and third level interpretations (2012, p. 10). Discussions about ontology can concern whether a social reality exists or not: objectivists believe that it does exist whilst constructionists do not (Bryman et al. 2012, p. 11). Instead, constructionists believe that reality consists only of individual interpretations. I do not fully agree with either of these standpoints but rather take a soft constructionist position (Bryman et al. 2012, p. 11), agreeing that the existence of a social reality is possible but that our individual perceptions and opinions are not necessarily completely dependent on it, or at all times connected with it. Epistemology is concerned with what knowledge is. Those who take a positivistic stance make clear distinctions between theory and research and support the development of new theories from research which has not taken pre-existing ideas into consideration. Their research often includes both deductive and inductive elements but believe that prior to referring to a theory as knowledge it must be thoroughly tested. Others take on an interpretivistic stance, which means that they focus on understanding peoples individual reasoning behind their actions, interpreting their ever-changing human behaviors. In interpretivism, actions are perceived as being based on 37

39 individually perceived meanings in the social environment (Bryman et al. 2012, pp. 8-9). In the attempt to generalize how Canadian consumers perceive credit card rewards, and using both inductive and deductive approaches in my research, it could be argued that I have taken a positivistic stance. However, I also take pre-existing ideas into consideration in my research and believe that each individual has diverse motivational factors which make one perceive value differently than another. That said I also believe that the concept of a majority vote exists and that although individuals have different perceptions of one and the same reward, consistently there is a majority of consumers who all perceive rewards in a similar manner. The difficulty in recognizing whether said majority is mostly the same, consisting of the same individuals or not, will be investigated through my statistical analysis. In this study, I thus attempt to analyze what the perceptions of that majority is in order to aid credit card companies in learning in what and where to focus their efforts in building high value rewards programs. Consequently I do not only intend to interpret my own interpretations of this study, but the respondents interpretations too. 3.2 Research methods for the present study The aim of the current study is to acquire information about what credit card rewards the Canadian population generally prefers. Using a quantitative research strategy (Bryman, 1997, s. 20), the current study is carried out through a survey investigation administered to a fitting population segment: a random selection of Canadian consumers in Calgary, Alberta Approach A quantitative research strategy is one in which statistical measurements of the empirical findings are used as the basis for the analysis (Bryman et al. 2012, p.13). Although many quantitative studies are constructed alongside the author s own hypothesis, 38

40 Bryman and Bell argue that hypotheses do not have to be part of a quantitative study but are rather more occurring in studies that are carried out through an experimental research approach (2003, p. 68). The current study thus entails research questions rather than hypotheses. The study follows a deductive research theory approach as it was started by researching previous theories on the subject of rewards and loyalty programs which lead me towards a survey investigation and my own empirical findings. In a deductive research strategy, theories are empirically tested in order to be either confirmed or rejected and revised (Bryman et al. 2012, p. 8). The theory that stands to be tested in the present study is that a consumer s level of involvement in their credit card influences their perceptions of type and timing of credit card rewards, and their preference for dimension of the benefits. The constructs are thus expected to collectively determine what the consumers overall perceived value of credit card rewards are. Deductive approach: Theory Observations/findings Figure 12. Deductive approach (Bryman & Bell, 2003, p. 12) However, the study also has an inductive segment to it as I am forced to revise my initial theory after analyzing my empirical findings. A new theory, or generalization, is thus created as my findings contradict some of those of previous research, leading me to draw new conclusions about what influences customer perceived value. Inductive approach: Observations/findings Theory Figure 13. Inductive approach (Bryman & Bell, 2003, p. 12) According to Bryman et al. it is not possible to only keep to one of the two strategies: deductive or inductive, but instead researchers move back and forth between the two strategies throughout all practically implemented studies, the present study being no exception. 39

41 The two research strategies combined is referred to as iterative research (2012, p. 9) Building the theoretical foundation By searching key words such as loyalty programs, consumer + rewards and rewards + credit on academic search engines such as Google Scholar, Scopus, ISI Web of Science and Emerald a good foundation of previous research to build the present study on was created. To keep constructs used in the different studies separate they were listed in a structured word document (appendix 9). Additionally, reference maps were created in an Excel spreadsheet to simplify an overview of what authors referenced each other (see 2.1 Literature overview). Working this way enabled easy re-tracking to look at what had been read earlier in order to discuss observations between results of previous studies, the authors conclusions and their personal opinions. Whilst each article was read, parts that had been noted to be of potential future use were highlighted, notes were also scribbled in the margins whenever one article was contradicting, or agreeing with, another. Through creation of the questionnaire, I focused my research on what survey questions other authors, who had written about similar topics, had utilized. Another area that I concentrated my research on was previous authors methodology chapters in preparation for the process of data collection with high levels of validity. Survey questions that were considered fitting for the previous study were listed, some of them edited, and lastly compiled into a finished questionnaire. The majority of authors who had performed similar research utilized a 7-point likert scale in their survey research. However, in an attempt to increase precision in respondents answers, I chose to utilize a visual analogue scale (VAS) in the present study. The VASscale consists of a ten centimeter, straight line anchored by continuums such as Unappealing to me on one end and Highly appealing to me on the other. Each respondent is subjected to a question or statement and then asked to put an X where in the linear 40

42 spectrum that they believe they fit. Each answer is then measured with a ruler, resulting in a high precision answer between 1 and 100, as opposed to those answers entered in to a 7-point likert scale where there are only 7 options for the respondent to choose between Data collection and respondent selection Pinsonneault and Kraemer claim that even the most different types of survey research have three common characteristics. The first characteristic is the most basic purpose of the survey research: gathering quantitative information from a population segment which represents the target population of the study, to investigate e.g. relationships between variables. The second characteristic is the manner in which survey research data is collected: confronting a sample group made up of individuals, and/or organizations, and asking them controlled, predetermined questions. The answers collected from the sample group are what will later be the basis of the survey research analysis. The last characteristic is that the sample group is of sufficient size and represents the target population well enough to be generalizable for a larger population segment than was employed in the actual study (1993, pp. 5 6). All three of these features are fulfilled in the current study. After having had my questionnaire for the current study approved by my Supervisor, Jonas Kågström, I decided to visit a larger city to collect a random sample of respondents, consisting of Canadian consumers. The city that was decided to be satisfactory for this purpose was Calgary, Alberta. Calgary s population in April of this year was, according to a 2012 civic census, just over 1, persons ( The first location in which an attempt to find respondents was made was the CrossIron Mills mall. Because of unawareness of their mall policy only a small number of respondents were collected here before being asked to approach the Administration Office to apply for permission to conduct research in the area. The second choice of a location for survey administering was thus based on the ambition of finding an area that would not be subject to any such policy. Steven Avenue Walk located in the downtown area of Calgary was selected for a second attempt to find respondents. 41

43 Steven Avenue Walk is a pedestrian-only street, directly linked to the main train tracks in the city of Calgary, with a large part of the city s population passing through each day. The avenue offers many different types of stores, a small market and live music. One Tuesday morning had already been spent at Cross Iron Mills mall and two half days were spent at Steven Avenue mall: a Friday and the following Saturday, all three days within the same week of each other. By utilizing Sullivan s systematic sampling technique in order to retrieve a truly random sample, every 5 th person passing by was approached (Sullivan, 1994, p. 1297). In total, 184 persons were asked to participate in the research and 130 of them agreed to complete the questionnaire. This resulted in a response rate of 70,65%, however six of the respondents had not entered their answers in a measurable manner and could thus not be included in the study. The final survey sample thus consisted of 124 respondents. According to Pinsonneault and Kraemer, the precision of a study substantially increases with a sample of responses. The survey sample selected for the study must represent the population that is of focus in the study at the specific point in time when the survey was administered (1993, p. 10). The successfully collected survey sample was thus regarded to be of satisfactory size and type. In an initial attempt to compare the preferences of the current generation of Canadian consumers with that of the next generation of consumers (i.e. today s students) a second survey sample was collected. The second survey sample was found at the University of Lethbridge and administered to students in the Brain and Behaviour class. There, permission was given to come in to the class on a Tuesday morning to present the research and its purpose and to ask students to participate. To raise the response rate in the class, everyone who completed the survey were offered the option of participating in a draw for five gift cards to a popular Canadian fast food restaurant; Tim Hortons. According to their professor, the class was supposed to have around 140 students in attendance but attendance was lower than usual and only about 100 students were in the class on the day that I had been given permission to. However, 42

44 only 60 responses, out of which 59 could be used in the study, were given. Response rate for the student sample thus ended up at an unsatisfactory 60 %. To collect more answers from students, University of Lethbridge s staff informed me about their University research pool. However, to utilize the pool, Human social ethics clearance of the study and its purpose was needed. Applying for such clearance included filling out extensive but mandatory paperwork explaining the research and then waiting to get approval by the researching pool faculty. Administration of the survey would take place in a classroom at the University, rented by the author, in the hope that students would chose to fill out the questionnaire. Because of a limited timeline to finish the research, and uncertainty in response frequency, their offer was refused. In the end, the student sample ended up being much too small and focus of analysis was instead put solely on the on the random sample of consumers from Calgary. However, because the study would now consist of an analysis of only the one sample, more time could be invested in performing a more in-depth graph- and statistical analysis. 3.3 Tools for statistic measurement and interpretation of findings Because of the limited timeline involved in conducting this study, I was unable to require enough knowledge about the statistics program SPSS to correctly enter my empirical results into it myself. Instead, I measured, organized and entered all my answers to the survey into an excel spread sheet after which my Supervisor, Jonas Kågström, entered the answers into the program. Jonas then supplied me with a print-out of the automated findings. However, I emphasize that Jonas did not take any part in interpreting the results but simply instructed me in what is being measured in Pearson s correlation and what the program looks for in a rotated component matrix. All interpretation and all analysis for this study have been performed by me, the author, only. To aid me in my analysis, I have utilized The SSPS survival 43

45 manual written by Julie Pallant. In the text that follows, I will explain how these statistical tools work Pearson s Correlation The empirical findings will be presented through interpretation of a Correlation Matrix created through SPSS, in combination with graphs and tables that I have created in Windows Excel. Pallant writes that correlations are different from causality in that correlations do not reveal whether one factor caused the other. In the two questions that are highly correlated with each other it is thus, with only the correlation at hand, not possible to determine whether a high rating of question A prompted a high rating for question B, or if B prompted high ratings for question A. Nor is it possible to tell whether there was a third question influencing both answers (2005 p. 124). Only those correlations that have a significance at the 0,01 level (indicated with **) and at the 0,05 level (indicated with *) have been included in the analysis. The Correlation matrix which was created in SPSS from my survey sample and that I have used for interpretation in the empirical study can be found in appendix Factor Analysis To analyze the empirical data further all answers to the survey were run through a factor analysis in the statistical program SPSS, using a Rotated Component Matrix. This process allowed me to recognize what additional factors the respondents had in common in their answers. KMO The Kaiser-Mayer-Olkin (KMO) value and Bartlett s test measure the adequacy of a random survey sample. The KMO value is measured on a scale from 0 to 1. 1 is not a realistically possible result but the value must be higher than 0,6 for the sample to be considered viable for analysis (Pallant, 2005 p. 183). My sample of 124 respondents obtained a very strong Kaiser-Mayer-Olkin value of 0,805. Bartlett s 44

46 test should be presented as significant (at a value of 0,05 or smaller), which the testing of my survey sample does, showing that it supports factorability of the correlation matrix. Below is the KMO value and Bartlett s test for my survey investigation. Kaiser-Meyer-Olkin Measure of Sampling Adequacy.,805 Bartlett's Test of Sphericity Approx. Chi-Square 987,3 19 df 153 Sig.,000 Figure 14. KMO and Bartlett's Test Total Variance Explained Total Variance Explained is a way to group data into components to find patterns and explain results. For the present study, this meant that SPSS organized the original 18 questions in the survey into five components that all had an Eigenvalue of 1 or more (Pallant, 2005, p. 192). Together these five components represent 67,77% of the results from the survey. The components each contribute to the results to different degrees portrayed through their individual percentage portions with component 1 being the highest, in this study at 32,388% and component 5 being the lowest, in this case at 5,944%. The reasoning behind converting the 18 questions into five components is that it aids the analysis process by telling me that all questions in the same component have something in common. It is, however, up to me to understand and determine what that common factor could be. Rotated Component Matrix The five highlighted components in the Total Variance Explained table are, as mentioned earlier, also organized in a Rotated Component Matrix which can be found in the analysis chapter of this thesis. The Rotated Component Matrix clearly states what questions belong in each of the five components. The components and the questions that they each entail are what will be the core discussion in the analysis 45

47 chapter. To make the Rotated Component Matrix easier for readers to interpret, I have created a color scheme for each construct which is continually used throughout both the empirical findings chapter as well as throughout the analysis. 3.4 Reliability, validity and generalizability Reliability concerns whether the results of the study can be replicated by performing another, comparable study and is an area that is of especially large concern in quantitative research (Bryman & Bell, 2003, p. 33). The theoretical ground of this study is based on previously published scientific articles written on similar topics, their results and their findings. The articles referenced in the present study have all received several quotations, some as many as over a thousand, indicating that they can be regarded reliable sources. The questions for the present study s survey were all collected from these highly referenced articles. To increase reliability, data collection was carried out in a manner similar to that of the data collection of reliable previous research. The survey sample was collected by two persons: the author and one helper, administering the questionnaires to Canadian consumers in Calgary, Alberta. The first questionnaires were administered by both administers together to ensure that both were communicating the same instructions to each respondent. To reach a higher level of reliability, all 124 surveys and each response to each question was controlled and measured by the author only. Della Porta and Keating state that validity is one of research s most vulnerable points and that neither accuracy of observations, level of comparability or how replicable the research is, if it does not have strong validity the study will have collapsed (2008, p.282). Internal validity concerns the level of generalizability, or lack of bias, in the study sample while external validity represents the level to which the findings of the study can be generalized, outside of its sample context (Bryman & Bell, 2003, p. 33). To increase validity in the current study, a random sample of consumers was utilized as respondents for the survey research. In an attempt to increase reliability, the 7-point 46

48 likert scale that was utilized in a majority of the previous research material was exchanged with a Visual Analogue Scale for higher precision in answers in the present study. The VAS scale has previously proved to provide both high reliability and high validity (Lingjærde & Regine Føreland, 1998, p. 392). The results of a survey can only be generalized to the population in which, and in the location where, the survey took place (Bryman & Bell, 2003, p. 109; Della Porta & Keating, 2008, p. 92). According to Della Porta and Keating the only sampling that can be generalized and still be true is a probability sample, namely: the random sample (2008, p. 244), indicating that generalizability is fairly high in the present study. My survey sample of 124 respondents cannot reliably be viewed as representative of the entire Canadian population but does fulfill its purpose in contributing to Canadian credit card rewards research. Pinsonneault and Kraemer believe that authors should be more careful when generalizing their findings and focus on strengthening the relationship between the respondents and the population that is under analysis. By better defining what population is the desired subject of analysis and then ensuring that the survey sample accurately represents that population, the results of the research will be stronger (1993, p. 28). The target population for analysis in the present study was Canadian consumers. Although the survey sample is too small to be generalizable for the entire Canadian population, generalizability was increased by the fact that respondents were asked to fill out their resident status so that it was possible to know how many were actually Canadian. Out of the final sample of 124 respondents, only 5 persons were neither a Citizen nor a Permanent resident. 47

49 3.5 Possible methodology errors Errors in quantitative research According to Bryman and Bell (2003, p. 87), two reasons as to why research in general is not always carried out in an ideal practice are that, 1: Teachers of research methodology cannot possibly cover all eventualities that may occur during the researching process and some inaccuracy is thus likely to take place in many research papers. 2: good practice of researching methods is not always followed by researchers, not necessarily because of the researchers incompetence but rather because of matters such as time, cost and feasibility. Some of the critique that has been directed towards quantitative research (Bryman & Bell, 2003, p. 86) is that: It is not customized to the social world but expects measures that are created for the natural world to apply to social interactions. It does not take into account that respondents do not all comprehend and interpret questions in the same way. It often ignores that the respondent may not have the knowledge necessary to correctly answer the questionnaire Errors in survey research Bryman and Bell consider four areas of error in social survey research (2003, p ). The first is the Sampling error, which constitutes that it is highly unlikely that the researcher will succeed in collecting a completely representative sample. The second is the Sampling-related errors which are related with the actions associated with the sampling procedure and external validity of research results. The authors provide examples of such errors: inaccurate sampling frames and nonresponse. The data-collection error is the third area and is represented by inadequate or weak language in the questionnaire. The fourth area; the data processing error, is that of incorrect coding of questions and mistakes in managing the collected data. 48

50 Error Sampling error Samplingrelated error Data collection error Data processing error Figure 15. Bryman and Bell s four sources of error in social survey research (2003, p. 110) In order to avoid as many of these errors as possible I have tested my random survey sample by running it through KMO and Bartlett s test. Non-response and inaccurately filled out questionnaires were not included in the final sample of 124 responses and to aid consumers in understanding the language in the questionnaire, my assistant and I were present, ready and available to answers any of their questions during their participation in the survey. Finally, the survey data was measured and organized by me, the author only, to decrease risk of possible interpretation bias. 49

51 4 Empirical findings In this chapter, the most basic findings from the survey investigation will be presented, in preparation for a more thorough examination in the Analysis chapter. Here, in the Empirical findings chapter, respondents answers to each question will be presented through distribution histograms, standard deviations and means. I have created all graph, tables and histograms in this chapter in Windows Excel A random sample of Canadian consumers was collected in the city of Calgary, Alberta, Canada. By visiting the Cross Iron Mills mall and Steven Avenue, 124 responses to the questionnaire were gathered, of whom 96% were Canadian citizens, 56 percent were women and 44 percent were men. 97,6 percent of respondents had between two and fifty years of experience of holding at least one credit card. The average amount of experience among experienced respondents was 18,6 years, showing that the majority of respondents had substantial experience of holding credit cards. All questions used in the questionnaire were either quoted from, or based on, prior studies performed on similar topics, as were the continuums verbage anchoring the questions: unappealing to me etc. The order of the questions in the survey was also carefully considered: To highlight the difference between the two options presented within each construct and allow respondents to compare them to each other, questions about timing and type of rewards were clumped together. To aid comprehension of the survey results, I have organized the respondents answers into frequency histograms, rounding them off to fit into 0, 10, and so on up to 100. Answers to each question will thus be presented by portraying the frequency with which the respondents distributed their answers from 0 to 100 on the VAS-scale. From this point on, all questions within the same construct will be presented in the same color: Involvement will be presented in the color dark blue; Timing of rewards will be presented in green; Type of reward in red; and Dimension of benefits in purple color. 50

52 Findings from the survey investigation This first graph presents each respondent s age in relation to their level of experience of holding at least one credit card. The blue line represents age and has been organized from Each respondent s age has been paired with their level of experience, which is represented by the blue area located directly underneath the line Experience Age group Figure 16. Each respondent s age in relation to their level of experience with holding at least one credit card. Although there are a couple of exceptions, as was expected the graph shows that the older the respondent is the more experience they generally have with holding at least one credit card. 51

53 4.1.1 Level of Involvement: High versus low Question 1: I researched and carefully considered my options before choosing my credit card Figure 17. Question 1 Distribution histogram for Q1 Mean=53,6 Std. Dev=33, Question 1 Frequency % 0 Unappealing Highly appealing This question was created to measure each respondent s level of involvement in choosing their credit card. Because prior research in rewards programs has shown that involvement does affect a person s bias to type and timing of rewards, this question was placed first in the questionnaire. The results show that the majority of respondents found that this statement at least somewhat applied to them, signaling that many had a medium to high level of involvement in their choice of credit card. The outcome of this question is highly satisfactory as it allows for more extensive analysis about the relationship between perceived value in each construct and the consumers level of involvement. In the graph below, each respondent s level of involvement has been measured in relation to their age group. The purpose of this graph is to investigate whether there is a connection between the age of the respondent and their level of involvement. The graph shows that there generally is no connection. However, more of the very youngest respondents (18-25) had a higher level of involvement whilst all the other age groups showed a more varying result. This could be an indication that more effort needs to be directed towards the younger population in order to earn their business. But, it could also be a result of the younger population having gone through the process of 52

54 choosing their credit card more recently and thus have a better memory of the experience Answer to Q1 Age group Figure 18. Responses to level of involvement in relation to each respondent s age This next graph (below) shows the similarities between male and female respondents in level of involvement. The results show that men in the survey sample generally had a slightly higher level of involvement in their choice of credit card than women in the sample did. It also shows that more women than men participated in the study: Out of the entire random sample of 124 respondents, 55 were men and 69 were women Q1 Men Q1 Women Figure 19. Male and female responses to level of involvement 53

55 4.1.2 Timing of rewards: Immediate versus delayed Immediate rewards Question 2: A 1% discount on my current purchase Distribution histogram for Q2 Mean=43,0 Std. Dev=31, Question 2 Frequency % 0 Unappealing Highly appealing 11 9 Figure 20. Question 2 This immediate reward was one that the majority of respondents perceived as one of low value and the average response among respondents was 43. The 1% discount was created as a comparison to the question of a delayed reward of 5% (in Q3). In relation to other rewards mentioned in the survey, question 2 has a percentage rebate amount stated in it, which must to be taken into account when analyzing the result. In other words, respondents could have partly had the amount of the rebate in mind (1%) when they stated their perceived value of the reward, skewing their answers and this study s investigation of perceived value of timing of rewards. 54

56 Question 4: I collect reward points and I find out how many points I have collected immediately after my purchase Figure 21. Question 4 Distribution histogram for Q4 Mean=39,4 Std. Dev=32, Question 4 Frequency % 0 Unappealing Highly appealing This immediate reward also received a low rating by a majority of the respondents: only 29 percent of respondents gave it a rating of >70. Just like in question 2, question 4 was created as a comparison to another question (to Q5). It must thus again be taken into account that some respondents may have answered this question with idea of collecting points in mind rather than only the timing of those points. It was not at all unusual that respondents commented on the idea of point systems at the time of data collection. Comments such as I just love collecting points were often stated. This is something that could have had an influence on respondents answers to question 4. 55

57 Delayed rewards Question 3: A 5% discount on a purchase of the same value as in question #2 on my fifth visit Distribution histogram for Q3 Mean=44,4 Std. Dev=33, Question 3 Frequency % 0 Unappealing Highly appealing Figure 22. Question 3 Although there is a small spike at 70 and 100, the majority of respondents found this delayed discount unappealing. Interestingly, the result of this 5 percent delayed reward is very similar to that of the immediate 1 percent reward mentioned earlier (Q2). The average response for the immediate version of this reward (question 2) was 43, and the average for question 3 is

58 Question 5: I collect reward points and at the end of every month I find out how many points I have collected Figure 23. Question 5 Distribution histogram for Q5 Mean=44,7 Std. Dev=35, Question 5 Frequency % 0 Unappealing Highly appealing In question 5, 44 percent of respondents gave the delayed reward of finding out how many points have been collected at the end of the month a low rating of <30. However, as with question 4, many other respondents found the delayed points reward highly appealing and 36 percent gave it a rating of >70. The remaining 20 percent of respondents gave it a fairly equal spread of

59 4.1.3 Type of rewards: Direct versus indirect Direct rewards Question 6: For every $100 spent on the credit card, a rebate of $1 is credited to my credit card debt Figure 24. Question 6 Distribution histogram for Q6 Mean=50,6 Std. Dev=33, Question 6 Frequency % 0 Unappealing Highly appealing This question portrays an interesting result: As portrayed in the histogram respondents perception of this reward varied greatly. The average response to this question is 50,6. 37 percent of respondents gave this direct reward a rating of <30, and 44 percent of respondents gave it a rating of >70. Question 7: For every $100 spent on the credit card, my credit card fee is lowered by $ Figure 25. Question 7 Distribution histogram for Q7 Mean=48,5 Std. Dev=34,52 Question 7 Frequency % 0 Unappealing Highly appealing

60 The results for question 7 are similar to those of question 6 in that perceptions varied: many consider this particular reward to be very unappealing while many others found this reward highly appealing. The average response to question 7 is 48, percent of respondents rated it <30 and 42 percent rated it >70. The results imply that perceived value for direct rewards in the credit card industry highly varies with individuals. Indirect rewards Question 8: For every $100 spent on my credit card, I get a $1 shopping voucher at select department stores Figure 26. Question 8 Distribution histogram for Q8 Mean=36,5 Std. Dev=29, Question 8 Frequency % 0 Unappealing Highly appealing 10 8 The majority of respondents found the indirect reward of vouchers in department stores (Q8) unappealing. 52 percent of respondents gave it a <30 rating and only 22 percent rated it at 70 or over. Interestingly, the histogram for question 9 which also measures customer perceived value for indirect rewards looks very similar to that of question 8. Because a monetary value is included in both of these questions, it must be taken into account that consumers may have had the amount of the voucher in mind when answering both of them. 59

61 Question 9: For every $100 spent on my credit card, I get a $1 voucher at select restaurants Figure 27. Question 9 Distribution histogram for Q9 Mean=33,4 Std. Dev= 30, Question 9 Frequency % 0 Unappealing Highly appealing 9 7 Although there is a spread in responses in question 9 and some respondents found this indirect reward medium-highly appealing, the vast majority found it unappealing. A whole 62 percent gave it a rating of <30 while only 21 percent rated it >70. Answers to this question are also quite similar to those of question 8: again I believe it is fair to make the assumption that respondents found these questions to be quite similar to each other. 60

62 4.1.4 Dimension of benefit: Hedonic, Utilitarian and symbolic benefits Hedonic benefits Question 10: A $5 coupon for gourmet foods Distribution histogram for Q10 Mean=37,4 Std. Dev=31, Question 10 Frequency % 0 Unappealing Highly appealing Figure 28. Question 10 To receive a coupon for gourmet foods was rated unappealing (<30) by the majority (approximately 57 percent) of the respondents. However there are also spikes at 70 and 100: In total only 27 percent of respondents gave it 70 or higher. To get more clarity in who rated this reward higher, we must look at its correlation with questions representing other constructs in the Analysis chapter. 61

63 Question 14: I discover new products Distribution histogram for Q14 Mean=31,8 Std. Dev=27, Figure 29. Question 14 Question 14 Frequency % 0 Unappealing Highly appealing 5 4 Discovering new products was rated unappealing by the vast majority (72 percent) of respondents, only 17 percent of all respondents gave it a >70 rating. Question 17: I try new products Distribution histogram for Q17 Mean=34,2 Std. Dev=29, Question 17 Frequency % 0 Unappealing Highly appealing 10 8 Figure 30. Question 17 Similar to the result of question 14, trying new products was not something that was perceived as valuable to many respondents. Although the amount of ratings towards unappealing are not as extreme in Q17 as they are in Q14, 57 percent of respondents gave the reward of trying new products a rating of 30 or less. 62

64 Utilitarian benefits Question 11: A $5 coupon for groceries Figure 31. Question 11 Distribution histogram for Q11 Mean=51,2 Std. Dev=32,16 Question 14 Frequency % 0 Unappealing Highly appealing Receiving a $5 coupon for groceries had a large spread in respondents perceived value. Although the tallest spike is at 10, with 18 percent of responses, strong spikes were also found at both 70 (14 percent) and 100 (15 percent). Overall, slightly more respondents found this reward more appealing than not with an average response of 51%. Question 13: I shop at a lower financial cost Distribution histogram for Q13 Mean=64,2 Std. Dev=30, Question 13 Frequency % 0 Unappealing Highly appealing Figure 32. Question 13 Shopping at a lower financial cost was considered one of the most valuable rewards offered in the survey with an average response at 64,2. As much as 62 percent of respondents gave this reward a 70< rating and only 20 percent rated it <30. 63

65 Question 16: I save money Distribution histogram for Q16 Mean=74,5 Std. Dev=26, Question 16 Frequency % 0 Unappealing Highly appealing Figure 33. Question 16 Question 16 had, by far, the highest amount of ratings of highly appealing out of all of the rewards mentioned in the survey. With 78 percent of respondents giving the reward of saving money a 70+ rating, it can be considered a reward that is generally perceived as being of very high value to many Canadian consumers. Symbolic benefits Question 12: A $5 voucher for a membership in a customer club Figure 34. Question 12 Distribution histogram for Q12 Mean=24,0 Std. Dev=25, Question 12 Frequency % 0 Unappealing Highly appealing 8 6 Receiving a voucher for as membership club was regarded one of the rewards in the survey with the least appeal. With an average response of only 24, 78 percent rated it 30 or lower. 64

66 Question 15: I receive better treatment than other customers Distribution histogram for Q15 Mean=42,5 Std. Dev=31, Question 15 Frequency % 0 Unappealing Highly appealing Figure 35. Question 15 Although there is some spread in perceived value for being rewarded with better treatment than other customers, many of the respondents (43 percent) gave it a low rating of <30. Some consumers comments about this reward at the time of data collection were I don t like it when they treat me differently and I want to be left alone when I am shopping. Question 18: I belong to a community of people who share the same values Figure 36. Question 18 Distribution histogram for Q18 Mean=37,9 Std. Dev=31, Question 18 Frequency % 0 Unappealing Highly appealing Just like Q12 and Q15, this symbolic reward received one of lowest ratings out of all the rewards in the survey. The average response for question 18 is higher than for any other symbolic reward in the survey, although overall symbolic rewards were by far given the lowest ratings of perceived value in the survey. Belonging to a 65

67 community of likeminded people got a <30 rating from 54 percent of respondents whilst a >70 rating was only given by 27 percent. 4.2 Additional comments about compilation of survey results The distribution histograms for question 2 and 4 shows that the two options are similarly unpopular, signaling that preferences for immediate rewards are likely not perceived as the most valuable rewards among credit card holders. It must however be mentioned that both questions could be affected by the rewards that were offered (a discount and points) rather than the actual timing of those rewards. Although, because question 4 was rated lower than question 5, a question which only offers a delayed version of Q4, results indicate that credit card holders do prefer delayed rewards even though the reward received is, relatively, no greater when received later. With few exceptions, throughout the entire survey results showed that there was no obvious difference in perceived value between women and men or between respondents age groups. The only questions that showed any difference between males and females were question 3 and question 18. Men had a slightly stronger preference to the delayed, 5 percent discount (Q3) and women had a slightly higher preference for belonging to a community of likeminded people (Q18) Q3 Men Q3 Women Figure 37. Differences in answers between men and women All other graphs displayed results very similar to those of questions 9 (indirect type) and 14 (hedonic dimension of benefit). These are Q18 Men Q18 Women

68 typical examples of what the remaining graphs looked like, showing no differences in perceived value in credit card rewards between women and men Figure 38. Similarities in answers between men and women Only one of the questions showed any difference in perceived value of rewards in relation to respondent s ages. The question of receiving a $5 voucher for a membership in a customer club was not found appealing for any respondents over the age of 57 (Q12: hedonic dimension of benefit), although results for a higher perceived value of this reward were also very scattered among remaining age groups Q9 Men Q9 Women Answer to Q12 Age group Q14 Men Q14 Women Figure 39. Answers to question 12 in relation to age 67

69 No other graphs created to investigate possible links between perceived value of rewards and respondents ages showed any obvious patterns. The two graphs, for Q2 (immediate timing) and Q11(utilitarian dimension of benefit), below portray typical examples of this. Answer to Q2 Age group Answer to Q11 Age group Figure 40. Similarities in responses between ages 68

70 5 Analysis In this chapter, findings from the empirical findings will be analyzed and compared to previous research. Using Pearson s Correlation and a factor analysis, I reflect on how the rewards in the survey were perceived by the respondents as well as what affects customer perceived value. 5.1 Pearson s Correlation between constructs The highest correlation of all in the present study is that between age and the consumers experience with credit cards, with a statistically significant value of 0,889. This shows that the older the respondent the more experience they have with holding at least one credit card Level of Involvement In expecting involvement to have a significant influence on the constructs of type and timing as that is what previous research has shown, it was surprising to find that in the current study the opposite was true. Contradictory to previous research, involvement did not have noticeably strong correlations with any other constructs in the study. Correlations between involvement and Q5 (delayed points) were stronger than any other correlations with involvement, at a relatively weak value of 0,372. Other statistically significant correlations with involvement were those of shopping at a lower financial cost (Q13), at a value of 0,248 and the hedonic reward of discovering new products (Q14) at 0,234. Again, these correlations are too weak to allow me to draw any further conclusions. A counter argument to the low correlation would be that credit cards are low involvement products. However, Dowling and Uncles suggest that there are high involvement products and low involvement products. They refer to low involvement products as those that are purchased out of the consumer s own habitual patterns (1997, p. 10). Because it takes extensive paper work, collecting information about the consumer s prior credit history and a waiting period applies before 69

71 one can retrieve their credit card from their credit card firm or bank, it would thus seem wrongful to assume that credit cards are easily attainable and that they can fall into the low involvement product category. Furthermore, because the distribution histogram clearly shows that a number of respondents did show high levels of involvement in their credit card, these findings were not a result of lack of involvement in respondents. According to Dowling and Uncles there are two decisions made by the consumer in each purchasing decision: the category and the brand decision. I expect that these two categories translate to the credit card industry and that the consumer will have made their category decision already when they decide to make a payment with their credit card rather than with cash or cheque. The decision that is most interesting of the two, in the present study, is thus the brand decision. In the present study, the brand decision is expected to correctly translate into the consumer s choice of credit card firm. Dowling and Uncles argue that a high involvement consumer will show high involvement in both the category and the brand decision (1997, p. 16), in other words they would have high levels of involvement in their choice of payment and in their choice of credit card firm too. Previous studies have shown that involvement affects the customer s perceived value in a service or product (Yi & Jeon, 2003, p. 229; Parahoo, 2012, p. 13). In Yi and Jeon s study, it was concluded that a consumer s level of involvement did affect the consumer s perceived value in both type of reward as well as in timing of reward. A high level of involvement made the consumer more sensitive to being rewarded with the accurate type of reward: direct rewards, whilst low involvement consumers perceived the timing of the reward to be more crucial to determine its value and preferred immediate rewards. In summary, the findings in the present study do not support those of previous research about the influence of involvement on a customer s perceived value of rewards. If these findings study would have followed Dowling and Uncles, Yi and Jeon s and Parahoo s predictions about the consumer s level of involvement, the present 70

72 study would have shown much higher correlations between involvement and direct rewards and immediate rewards Type: Direct versus Indirect rewards Yi and Jeon propose that direct rewards are more beneficial in regards to building customer loyalty than indirect rewards because they support the service or product in question (2003, p. 234). In the present study, questions on direct rewards, both those that reduced the credit card holder s debt (Q6) and their fees (Q7), had a fairly strong correlation of 0,446. Interestingly, indirect rewards for vouchers for department stores (Q8) and indirect rewards for restaurants (Q9) also had a high correlation, of The correlations between indirect and direct rewards, however, were noticeably lower (Q6 to Q8: 0,376 and Q7 to Q9: 0,359). This could mean that respondents either prefer to receive direct rewards that are linked to their credit card finances or indirect rewards not connected to their credit card at all. One and the same individual did thus generally not perceive an equally high value for direct and indirect rewards in the survey. As mentioned earlier, Yi and Jeon suggested that consumers with high levels of involvement showed tendencies of a higher perceived value from direct rewards than from indirect rewards whilst low level involvement consumers showed no preference. In the present study, however, both direct and indirect rewards showed statistically insignificant results in correlation with involvement, meaning that no further interpretations can be made Timing: Immediate versus Delayed rewards The correlation between immediate and delayed discount rewards was very strong and portrayed an interesting finding: The correlation between the immediate discount (Q2) and the delayed discount (Q3) was a statistically significant high value of 0,634, indicating that timing of the reward made very little difference in perceived value of discount rewards in the present study. 71

73 The same pattern is clear with immediate and delayed points as rewards. The correlation between immediate points (Q4) and delayed points (Q5) was a strong value of 0,575. The respondents who took part in the survey were thus interested in either receiving rewards in the form of discounts or interested in collecting points, but not both. The timing of said rewards: immediate or delayed did thus not seem to have any effect on the respondents in this study Dimension of benefits: Utilitarian, Hedonic and Symbolic Agarwal et al.'s research showed that cash-back rewards significantly (2010, p. 18) increased both spending and debt accumulation on consumer s credit cards. In the same study, the authors could determine that cash-back rewards programs are a fiscally efficient tool for banks to increase return as the average card holder only redeemed a fragment of their prior spending in cash. Cash-back rewards were thus crowned the best revenue generator for credit card firms when consumers had not used their payment card at all before the reward program was implemented. In the present study, all questions about utilitarian rewards had high correlations with each other. Shopping at a lower financial cost (Q13) and saving money (Q16) were both, according to the distribution histograms, perceived as high value rewards. The two questions also had a very strong correlation value of 0,564 with each other, indicating that a reduction in cost is a reward that the respondents generally found appealing in relation to the other rewards in the survey. However, the highest correlation between any two questions from different constructs was that between question 10 and 11 where consumers rated $5 coupons for groceries and gourmet foods. It had been my prediction that most consumers who were interested in utilitarian benefits would choose the reward consisting of groceries but the statistical results instead showed that consumers generally found gourmet foods to be a just as attractive as a reward with a correlation value of 0,715. This finding contradicts that of Simonson 72

74 and Kivetz, who concluded that hedonic rewards were considered more appealing than utiliarian because the hedonic rewards would allow consumers to commit to guilt-free luxury (2002, p. 212). Except for the high correlation found between the hedonic reward of gourmet foods and the utilitarian reward of groceries, discovering new products (Q14) and trying new products (Q17) also had a very strong correlation: 0,725. The latter finding could be a result of the two rewards being quite similar to each other. Q17, unlike Q14, measures not only the consumers interest in new products but also their willingness to purchase them as they would otherwise be unable to try them. The strong correlation could thus both mean that the respondents would be prepared to spend money to try new products because new products had a strong enough appeal, or that respondents assumed they would have to spend money in order to discover new products as well. To some extent, the findings from the present study also contradicts Mimouni-Chaabane and Volle s findings which concluded that perceived value of dimension of benefits differed largely among consumers (Mimouni-Chaabane & Volle, 2010, p. 36). In the present study, consumers instead tended to perceive rewards as being of high value depending on what the reward consisted of, rather than depending on what dimension of their life the reward was focused on. Preferences were thus not fluctuating over all three dimensions but were rather heavily weighted towards utilitarian benefits and hedonic benefits, whilst symbolic benefits were not perceived as nearly as valuable. Interestingly, the correlation between number of years of experience of holding at least one credit card and a $5 voucher for a customer club (Q12) had a very strong negative value of -0,201. It thus appears that the less experienced the credit card holder is, the more interested they are in symbolic rewards and a feeling of belonging. Reversely, it also means that the more experienced the card holder is, the less interested in symbolic rewards they are. As mentioned earlier, the correlation between age and experience is very strong, which means that the result of question 12 and experience could be related to age as well, although the statistical analysis for those particular questions 73

75 (age and Q12) were insignificant. However, the finding that inexperienced credit card holders are more interested in symbolic rewards than those with many years of experience is very interesting. It could potentially be telling credit card firms that they need to focus more attention in form of symbolic rewards towards new credit card holders Additional, strong, correlations between constructs Correlations for question 9, the indirect reward of a voucher for select restaurants also had a high correlation with the other food-related rewards such as a voucher for groceries (Q11) as well as the hedonic reward of a voucher for gourmet foods (Q10). The strongest of these correlations was that between groceries and gourmet foods (0,715) but the rewards gourmet foods and a restaurant voucher rewards had a correlation of 0,595 and that between groceries and a restaurant voucher was 0,497. This indicated that consumers were either interested in food-related rewards or they were not. In other words, there was little indecisiveness with food-related rewards among the respondents in the survey sample. Other, very strong, correlations were found between gourmet foods (Q10: hedonic) and a voucher for a customer club (Q12: symbolic), these two questions had a correlation of 0, 615. A reward consisting of a voucher for department stores (Q8) had a correlation of 0,672 with that of a voucher for groceries (Q11) and a correlation of 0,605 with that of a voucher for gourmet foods. These results are assumed to have to do with the value of the vouchers, since Q10, Q11 and Q12 are all rewards that were suggested at an individual value of $5. I will discuss these correlations further in the factor analysis, next. 74

76 5.2 Factor Analysis For further reflection upon the survey findings, a factor analysis of the consumers answers was carried through. The factor analysis divided the 18 questions in the survey into five components, or factors. All the questions that are included in the same component have something in common with each other. In a perfect world where theory is consistent with practice, each component would entail only one construct but because reality rarely follows theoretical rules, some components will consist of two or more constructs. Here, I will analyze one component at a time in order to gain more clarity in how consumers perceive credit card rewards. The color scheme is the same as earlier in the thesis: The construct of Type of rewards is presented in red; Dimension of benefits in purple; Timing of rewards in green; and Involvement in blue. 75

77 Component Q6: Direct to debt,766,195 Q13:Utilitarian financial cost,760,307 Q16:Utilitarian: saving money,704,200 Q2:Immediate discount,676,227,153,345 Q7: Direct to fee,600,316 Q3:Delayed,595 discount,190,172,250,561 Q10:Hedonic gourmet foods,116,827,240,114 Q8:Indirect dep. stores,295,819 Q11:Utilitarian groceries,346,774 Q9:Indirect restaurant,206,694,165,281 Q12:Symbolic,458,649 customer club,165 Q17:Hedonic trying new,190,843 products Q14:Hedonic: discover products Q18:Symbolic belonging to community Q15:Symbolic better treatment Q5:Delayed points Q4:Immediate points Q1: Involvement,133,800,185,212,193,647 -,164,116,523,474,252,162,107,163,824,841 -,188 -,331,267,159 -,738,129 Figure 41. Rotated Component Matrix Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. A rotation converged in 7 iterations. 76

78 5.2.1 Component 1 Component one has the strongest effect on the survey results out of all five components, it accounts for 32,39 percent. This first component consists of both direct rewards: reductions in consumer debt and in credit card fees, both discount rewards: immediate and delayed discounts of 1% and 5% each, and the two utilitarian rewards that had to do with decreased spending: saving money and shopping at a lower financial cost. What this tells me is that out of all the different rewards in the survey, the rewards with the highest perceived value were those that provided consumers with financial benefits. It did not matter to respondents what the timing of their discount was, it did not matter where their reduction in credit card cost went: towards fees or debt, not did it matter whether they were saving their money or shopping at a lower financial cost. All of these rewards that provided consumers with financial gain were rated high on the VAS-scale and were thus perceived as important and of high value to the consumers. This finding adds to Agarwal et al. s theory about rewards promoting financial gain generating the most revenue for the brand (2010, p. 18). By implementing rewards that promote financial gain, both credit card firms and their customers will likely be more satisfied and thus increase their perceived value of the reward program Component 2 The second component includes all food-related rewards and the concept of receiving vouchers as a reward. A voucher for groceries, a voucher for gourmet foods and a voucher for select restaurants are all included in component number two. However, this component also includes a voucher for select department stores and a voucher for a membership in a customer club. There is a substantial decrease from component one to component two as to how much the components account for the results of the survey. The first component accounted for 32,4% whilst component two only accounts for 11,9%. However, judging by what rewards the second component includes, there is quite a clear pattern in 77

79 preferences. All rewards in this component consist of vouchers and many consist of food-related items. Although some of the vouchers are useful in completely different settings, i.e. a voucher for gourmet foods and a voucher for select department stores, it must not be forgotten that all of the vouchers suggested in the survey were of about the same value ranging from $1-$5. In other words, the similarity of said rewards could have had an impact on the consumers perceived value of them. However, component two consists of two constructs: dimension of benefits and the indirect type of rewards. There is a clear explanation for that; Indirect rewards cannot possibly be perceived by respondents as a category that is separate from the others. They are constructed to measure a consumers perceived value of rewards that have nothing at all to do with their credit card and in that sense, indirect rewards are, to the consumer, similar to those rewards which fall under the construct of dimension of benefits. To the consumer, an indirect reward in the survey is just another reward that is completely unrelated to any aspect of their credit card such as their credit card debt or credit card fees. In the case of the present study those unrelated rewards are represented by vouchers for restaurants and department stores Component 3 The third component consists of parts from only one construct: dimension of benefits. The two hedonic rewards that have to do with trying and discovering new products are situated in this component, together with the two symbolic rewards of belonging to a community of likeminded people and receiving better treatment than other customers. This third component accounts for 10,6 percent of the results, in other words only 1,3 percent less than component two which means it does pull some weight to the results of the survey but not a crucial amount. All suggested rewards in this component were given a very low rating by the respondents. It does, however, show that there is a distinction in how consumers perceive rewards that have to do with new products and being part of a social community: they 78

80 are not perceived to be as valuable as the constructs in component 1 and Component 4 The fourth component consists solely of two rewards: the only two that had to do with collecting points: immediate points and delayed points. This indicates that collecting points was something that the respondents in the survey sample perceived to be different or special, in terms of their overall comprehension of all the rewards in the survey. This fourth component accounts for only 6,9% of the results from the survey. Although collecting points is highly common in rewards programs in Canada today, it was not, neither immediately nor with some delay, a reward that was perceived as highly valuable among consumers in the survey sample. The finding that respondents perceived point collection rewards to be rather unappealing, and that timing made no difference in their perceived value of the reward contradicts findings in similar previous research which has shown that immediate rewards are preferable to delayed rewards. Yi and Jeon s study showed that there was a difference between a customer s perceived value of immediate and delayed rewards when that customer s level of involvement was high and when it was low. They claimed that under low involvement, customers perceived immediate rewards to be of greater value than delayed rewards (2003, p. 237). Because there is no such pattern (no high correlation between involvement and timing) in the present study, I suggest that additional, more recent research is necessary to conclude whether such a connection is present in Canada today Component 5 Involvement is alone in component number five, and accounts for only 5,9 percent of the results. This shows that the consumers levels of involvement had little impact on the results from the survey overall. Additionally, the fact that it shows a negative value (-0,738) indicates that the consumers in this study did not show the same connections between high involvement and high perceived value in certain rewards 79

81 that other respondents have shown in previous research. Determining whether this has to do with Canadian consumers regarding credit card rewards differently than consumers in other countries, where similar studies have been carried out, or to do with the fact that some of the previous studies are at least ten years of age and views on credit cards overall have changed, will require further research. 5.3 A revised model of Customer Perceived Value The model below portrays the survey sample s perceived value of rewards. It was highly influenced by the rewards that most clearly offered them financial gain. The survey sample s level of involvement was not a determining factor but delayed discounts (as opposed to points), direct rewards and utilitarian benefits were given the highest ratings out of all the rewards offered in the survey. Timing of Reward: Delayed (Discounts) Type of Reward: Direct Dimension of Benefit: Utilitarian Increased Financial Gain High Customer Perceived Value of Rewards Figure 41. A revised model of Customer Perceived Value 80

82 6 Conclusions In this chapter, the most significant findings from the study will be presented. Conclusions that are drawn here are concentrated around my research questions and the purpose of the study. This study was aimed at determining what factors influence Canadian consumers perceived value of credit card rewards. Four constructs were used in the study: Involvement, Type and Timing of rewards, and Dimension of benefits. For each question, a numeric table was created to see where most consumers found themselves fitting into the VAS-scale. The table portrayed response frequencies and percentages, along with a frequency histogram visually portraying the answer frequency to each question. For a more in-depth analysis, a correlation matrix and factor analysis were performed to discover additional connections in respondents perceived value of the rewards that were suggested to them in the survey. The rewards that were, by far, rated most valuable by consumers in the survey sample were those that supplied credit card holders with obvious financial gain: The utilitarian rewards of saving money and shopping at a lower financial cost. The direct rewards suggested in the survey also offered rewards of obvious financial gain and were given higher ratings than indirect rewards which offered vouchers for use in association with additional future spending. Also, when investigating timing of rewards, it became clear that respondents rated discounts more appealing than collecting points, regardless of the reward s timing. Being offered a discount may also be related with obvious financial gain whilst points are usually associated with spending more money to attain points over time. The idea of collecting points is that over time they culminate in a discount but in order to retrieve that discount the consumer must first spend more money and point collection is often a slow process. Not until the consumer redeems enough points will they get access to a discount. The survey sample rated the delayed discount as more valuable than the immediate discount, indicating that they would not mind waiting for a discount 81

83 that was, in relation to the immediate discount, of the same size but appeared larger at point of redemption. It was surprising to find that collecting points was regarded unappealing to so many respondents since points collection is a widely used form of rewards systems in Canada. At the time of data collection, those who did give additional comments about their view on rewards often communicated that collecting points was something they enjoyed doing. However, the respondents who did enjoy collecting points also expressed that they rarely used their points but found more pleasure in collecting than in redeeming points. Another, very prominent finding between two very different constructs was that the less experience the credit card holder had, the more interested they generally were in symbolic rewards of customer clubs. This is a significant finding in that it communicates to credit card firms that efforts of symbolic rewards should be aimed towards new credit card holders. As mentioned in the theory chapter, according to prior research the construct of Involvement highly influences Customer Perceived Value so it was a surprise to find that this was not the case in the present study. Although the respondents levels of involvement in their credit card were often rated a medium to high, the correlations matrix showed that there was no clear connection between involvement and other constructs. However, one conclusion that can be drawn from the findings in terms of the construct of involvement is that younger respondents generally showed higher levels of involvement than the older respondents did. Another finding is that men in the survey sample generally had a slightly higher level of involvement in their credit card than women in the sample did. Because of insignificant statistical values regarding correlations between involvement and the remaining constructs in the correlation matrix, as well as its placement in the Rotated Component Matrix, additional conclusions cannot be drawn from the construct of involvement in the present study. The last of my research questions was if there were any differences between men and women s preferences for credit card rewards and whether there were any age related differences. The present study 82

84 shows that there were no distinct differences in preferences for credit card rewards between men and women in the survey sample. 6.1 Managerial implications The Canadian credit card industry is highly affected by fierce competition between credit card suppliers. Credit card firms not only have to entice new customers but have to assure that their current customers are brand loyal in order to contain profitability. One credit card rarely differs from another in its most basic functions and thus one of the few ways in which credit card suppliers can differentiate themselves is to offer credit card rewards that are of high value to their customers. The findings in this study imply that in order for firms to reach customer loyalty and thus firm profitability, some changes should be made to the rewards that are being offered to credit card holders today. The finding that is perhaps the most important one of all in the present study is that customers highest perception of value lies in receiving rewards that provide them with financial gain: more than anything, credit card holders want to know that they are saving money by using their credit card. Currently, a vast majority of Canadian credit card rewards consist of point collection. The survey sample, however, clearly stated that with few exceptions, little interest is found in redeeming points and instead they preferred the traditional percentage discounts as rewards. This indicates that in order to reach increased firm profitability and customer loyalty, credit card issuers must revise their rewards systems; point collection rewards are outdated and no longer of much interest to the majority of consumers. Because there were no obvious differences between men and women and few differences between age groups, I believe more extensive research needs to be conducted to investigate possible influences of more particular factors. Studies involving questions of consumers annual income and ethnicity could perhaps show clearer patterns of customer perceived value of rewards. 83

85 7 References 7.1 Printed Sources: Agarwal, S., Chakravorti, S., & Lunn, A. (2010). Why Do Banks Reward Their Customers to Use Their Credit Cards? SSRN elibrary. Retrieved from Bolton, R. N., Kannan, P. K., & Bramlett, M. D. (2000). Implications of Loyalty Program Membership and Service Experiences for Customer Retention and Value. Journal of the Academy of Marketing Science, 28(1), Bryman, A. Kvantitet och kvalitet I samhällsvetenskaplig forskning Studentlitteratur AB, Lund. Bryman, A. & Bell, E. Business Research Methods, Oxford University Press Inc., New York. Bryman, A., Bell, E. & Teevan, J.J. Social research methods, 3rd Canadian edition Oxford University Press, Canada. Carbó-Valverde, S., & Liñares-Zegarra, J. M. (2011). How effective are rewards programs in promoting payment card usage? Empirical evidence. Journal of Banking & Finance, 35(12), Chatterjee, P. (2007). Advertised versus unexpected next purchase coupons: consumer satisfaction, perceptions of value, and fairness. Journal of Product & Brand Management, 16(1), Ching, A. T., & Hayashi, F. (2010). Payment card rewards programs and consumer payment choice. Journal of Banking & Finance, 34(8), Davis, O. A. (1959). The Economics of Trading Stamps. The Journal of Business, 32(2), Della Porta, D & Keating, M. Approaches and methodologies in the social sciences a pluralist perspective Cambridge University Press, United States. Demoulin, N. T. M., & Zidda, P. (2008). On the impact of loyalty cards on store loyalty: Does the customers satisfaction with the reward scheme matter? Journal of Retailing and Consumer Services, 15(5), Dowling, G. R., & Uncles, M. (1997). Do customer loyalty programs really work? Sloan management review, 38,

86 Keh, H. T., & Lee, Y. H. (2006). Do reward programs build loyalty for services?: The moderating effect of satisfaction on type and timing of rewards. Journal of Retailing, 82(2), Kivetz, R., & Simonson, I. (2002). Self Control for the Righteous: Toward a Theory of Precommitment to Indulgence. Journal of Consumer Research, 29(2), Laurent, G., & Kapferer, J. N. (1985). Measuring consumer involvement profiles. Journal of marketing research, Lingjærde, O., & Regine Føreland, A. (1998). Direct assessment of improvement in winter depression with a visual analogue scale: high reliability and validity. Psychiatry Research, 81(3), McDougall, G. H. G., & Levesque, T. (2000). Customer satisfaction with services: putting perceived value into the equation. Journal of Services Marketing, 14(5), Mimouni-Chaabane, A., & Volle, P. (2010). Perceived benefits of loyalty programs: Scale development and implications for relational strategies. Journal of Business Research, 63(1), Pallant, Julie. SPSS survival manual, 4th edition Open University Press, United Kingdom. Parahoo, S. K. (2012). Credit where it is due: drivers of loyalty to credit cards. International Journal of Bank Marketing, 30(1), Patterson, P. G., & Spreng, R. A. (1997). Modelling the relationship between perceived value, satisfaction and repurchase intentions in a business-tobusiness, services context: an empirical examination. International Journal of Service Industry Management, 8(5), Pinsonneault, A., & Kraemer, K. L. (1993). Survey research methodology in management information systems: an assessment. Journal of Management Information Systems, Ravald, A., & Grönroos, C. (1996). The value concept and relationship marketing. European Journal of Marketing, 30(2), Rothschild, M. L. & Gaidis, W. (1981). Behavioral Learning Theory: Its Relevance to Marketing and Promotions. Journal of Marketing (pre-1986), 45(2), Shugan, S. M. (2005). Editorial: Brand Loyalty Programs: Are They Shams? Marketing Science, 24(2),

87 Simon, J., Smith, K., & West, T. (2010). Price incentives and consumer payment behaviour. Journal of Banking & Finance, 34(8), Sullivan, T. A. (1994). Methodological Realities: Social Science Methods and Business Reorganizations. Wash. ULQ, 72, Uncles, M. D., Dowling, G. R., & Hammond, K. (2003). Customer loyalty and customer loyalty programs. Journal of Consumer Marketing, 20(4), Wirtz, J., Mattila, A. S., & Lwin, M. O. (2007). How Effective Are Loyalty Reward Programs in Driving Share of Wallet? Journal of Service Research, 9(4), Wulf, K., Odekerken-Schroder, G., Canniere, M., & Van Oppen, C. (2003). What Drives Consumer Participation to Loyalty Programs? Journal of Relationship Marketing, 2(1), Yi, Y., & Jeon, H. (2003). Effects of Loyalty Programs on Value Perception, Program Loyalty, and Brand Loyalty. Journal of the Academy of Marketing Science, 31(3), Zaichkowsky, J. L. (1985). Measuring the involvement construct. Journal of consumer research, Zaichkowsky, J. L. (1986). Conceptualizing involvement. Journal of advertising, 15(2), Zaichkowsky, J. L. (1994). The personal involvement inventory: Reduction, revision, and application to advertising. Journal of advertising, Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. The Journal of Marketing, Electronic Sources: City of Calgary Retrieved Maritz Canada oyaltyreport2012.pdf Retrieved

88 8 Appendix Appendix 1. Questionnaire What credit cards rewards do you perceive as valuable? I am a: Male Female Student Yes No Canadian: Citizen Permanent resident Other I have. years of experience of holding at least one credit card Please circle your age group: Please mark the line with a small X where in the spectrum you fit: Example: 1. I will/did research and carefully consider(ed) my options before choosing my credit card (Involvement, Aurifeille et al Edited) Does not apply to me completely applies to me Please rate your preference for the following credit card rewards: 2. A 1% discount on my current purchase (Immediate, Yi, Jeon) Unappealing to me Highly appealing to me 3. A 5% discount on a purchase of the same value as in question #2 on my fifth visit (Delayed, Yi, Jeon) Unappealing to me Highly appealing to me 4. I collect reward points and I find out how many points I have collected immediately after my purchase (Immediate, Rothschild & Gaidis. Edited) Unappealing to me Highly appealing to me 87

89 5. I collect reward points and at the end of every month I find out how many points I have collected (Delayed, Rothschild and Gaidis, Edited) Unappealing to me Highly appealing to me 6. For every $100 spent on the credit card, a rebate of $1 is credited to my credit card debt (Direct, Keh and Lee, edited) Unappealing to me Highly appealing to me 7. For every $100 spent on the credit card, my credit card fee is lowered by $1 (Direct, Keh and Lee, edited) Unappealing to me Highly appealing to me 8. For every $100 spent on my credit card, I get a $1 shopping voucher at select department stores (Indirect, Keh and Lee, edited) Unappealing to me Highly appealing to me 9. For every $100 spent on my credit card, I get a $1 voucher at select restaurants (Indirect, Keh and Lee, edited) Unappealing to me Highly appealing to me 10. A $5 coupon for gourmet foods (Hedonic, Mattila, 2010) Unappealing to me Highly appealing to me 11. A $5 coupon for groceries (Utilitarian, Mattila, 2010) Unappealing to me Highly appealing to me 12. A $5 voucher for a membership in a customer club (Symbolic, Mattila, 2010) Unappealing to me Highly appealing to me 88

90 The credit card rewards program that would be optimal for me ensures that: 13. I shop at a lower financial cost (Utilitarian, Mimouni, Volle 2010) Unimportant to me Very important to me 14. I discover new products (Hedonic, Mimouni, Volle 2010) Unimportant to me Very important to me 15. I receive better treatment than other customers (Symbolic, Mimouni, Volle 2010) Unimportant to me Very important to me 16. I save money (Utilitarian, Mimouni, Volle 2010) Unimportant to me Very important to me 17. I try new products (Hedonic, Mimouni, Volle 2010) Unimportant to me Very important to me 18. I belong to a community of people who share the same values (Symbolic, Mimouni, Volle 2010) Unimportant to me Very important to me Thank You for your participation! 89

91 Appendix 2. Compilation of Respondents Answers Respondent Sex (m=0, w=1) Status (Citizen=1, Age group PR=2, Years (18-25=1, Oth=3) of holding 26-33=2, Q1: Involvement credit 34-41=3, Q2: card Immediate 42-49=4, Q3: Delayed 50-57=5, discount Q4: discount 58-65=6, Immediate Q5: 66-73=7, Delayed pointsq6: 74+=8) points Direct to Q7: debt Direct to Q8: fee Indirect Q9: dep Indirect stores Q10: restaurant Hedonic Q11: gourmet Utilitarian Q12: foods Symbolic groceries Q13: customer Utilitarian Q14: club Hedonic: financial Q15: cost discover Symbolic Q16: products better Utilitarian: Q17: treatment Hedonic saving Q18: money trying Symbolic new products belonging to commu

92

93

94 Appendix 3. Pearson Correlation Matrix (SPSS) Sex (m=0, w=1) Status (Citizen=1, Age group PR=2, Years (18-25=1, Oth=3) of holding 26-33=2, Q1: Involvement credit 34-41=3, Q2: card Immediate 42-49=4, Q3: Delayed 50-57=5, discount Q4: discount 58-65=6, Immediate Q5: 66-73=7, Delayed pointsq6: 74+=8) points Direct to Q7: debt Direct to Q8: fee Indirect Q9: dep Indirect stores Q10: restaurant Hedonic Q11: gourmet Utilitarian Q12: foods Symbolic groceries Q13: customer Utilitarian Q14: club Hedonic: financial Q15: cost discover Symbolic Q16: products better Utilitarian: Q17: treatment Hedonic saving Q18: money trying Symbolic new products belonging to commun Sex (m=0, w=1) Pearson Correlation1-0,162 0,112 0,14 0,014-0,103-0,036 0,055 0,02 0,028-0,13 0,037-0,113-0,081 0,046-0,037-0,023-0,028-0,052 0,038 0,028 0,116 Sig. (2-tailed) 0,072 0,217 0,122 0,88 0,253 0,688 0,545 0,829 0,758 0,149 0,682 0,213 0,37 0,611 0,685 0,8 0,758 0,569 0,673 0,756 0,199 N Status (Citizen=1, Pearson PR=2, Correlation Oth=3) 1-0,117-0,14 0,001-0,015 0,072-0,039-0,078 0,071 0,063 0,1 0,157,248(**) 0,156 0,099 0,044-0,017-0,063 0,022-0,059-0,028 Sig. (2-tailed) 0,197 0,122 0,993 0,866 0,426 0,667 0,39 0,436 0,488 0,27 0,082 0,006 0,084 0,273 0,628 0,851 0,487 0,805 0,512 0,754 N Age group Pearson (18-25=1, Correlation 26-33=2, 34-41=3, 42-49=4, 50-57=5, 1,889(**) 58-65=6, 66-73=7, -0, =8) -0,163-0,103 0,099 0,089-0,067-0,056-0,091-0,165-0,142-0,063-0,155-0,028 0,136-0,102-0,134-0,032 0,001 Sig. (2-tailed) 0 0,666 0,07 0,256 0,272 0,326 0,462 0,535 0,315 0,067 0,115 0,487 0,085 0,753 0,131 0,258 0,137 0,725 0,992 N Years of holding Pearson credit Correlation card 1 0,029-0,103-0,042 0,032 0,114-0,023-0,031-0,057-0,084-0,15-0,04 -,201(*) -0,006 0,105-0,087-0,099-0,023-0,006 Sig. (2-tailed) 0,75 0,253 0,642 0,728 0,207 0,8 0,736 0,528 0,354 0,097 0,658 0,025 0,948 0,247 0,338 0,273 0,801 0,946 N Q1: Involvement Pearson Correlation 1 0,051-0,098,203(*),372(**),192(*) 0,17 0,051-0,106-0,096-0,049 0,05,248(**),234(**) 0,165,178(*),180(*) 0,034 Sig. (2-tailed) 0,577 0,278 0, ,033 0,059 0,575 0,241 0,291 0,591 0,579 0,005 0,009 0,067 0,048 0,046 0,706 N Q2: Immediate Pearson discount Correlation 1,634(**) 0,084,178(*),453(**),400(**),403(**),368(**),277(**),341(**),294(**),438(**) 0,043 0,17,419(**) 0,114 0,115 Sig. (2-tailed) 0 0,351 0, , , ,638 0, ,208 0,204 N Q3: Delayed Pearson discount Correlation 1,264(**),208(*),454(**),366(**),337(**),412(**),329(**),393(**),273(**),422(**) 0,162,309(**),392(**),262(**),278(**) Sig. (2-tailed) 0,003 0, , , ,003 0,002 N Q4: Immediate Pearson points Correlation 1,575(**) 0,115 0,151 0,097 0,092,207(*) 0,156,217(*) 0,132,326(**),348(**) 0,142,218(*) 0,142 Sig. (2-tailed) 0 0,204 0,094 0,286 0,31 0,021 0,084 0,015 0, ,117 0,015 0,117 N Q5: Delayed Pearson pointscorrelation 1 0,131 0,133 0,174 0,069 0,052 0,133,183(*),244(**) 0,166,288(**),181(*) 0,148 0,061 Sig. (2-tailed) 0,146 0,14 0,054 0,446 0,569 0,141 0,042 0,006 0,066 0,001 0,044 0,1 0,503 N Q6: Direct to Pearson debt Correlation 1,446(**),376(**),284(**),259(**),448(**) 0,121,497(**) 0,121 0,1,469(**),196(*),254(**) Sig. (2-tailed) 0 0 0,001 0, , ,182 0, ,029 0,004 N Q7: Direct to Pearson fee Correlation 1,362(**),359(**),288(**),382(**) 0,16,370(**) 0,11 0,083,343(**) 0,061,193(*) Sig. (2-tailed) 0 0 0, , ,226 0,36 0 0,501 0,032 N Q8: Indirect Pearson dep stores Correlation 1,584(**),605(**),672(**),559(**),260(**) 0,145 0,132,373(**),270(**) 0,175 Sig. (2-tailed) ,004 0,108 0, ,002 0,052 N Q9: Indirect Pearson restaurant Correlation 1,595(**),497(**),467(**) 0,136,189(*),284(**),316(**),290(**),280(**) 93

95 Sig. (2-tailed) ,131 0,036 0, ,001 0,002 N Q10: Hedonic Pearson gourmet Correlation foods 1,715(**),615(**),239(**),286(**),243(**),275(**),299(**),339(**) Sig. (2-tailed) 0 0 0,007 0,001 0,007 0,002 0,001 0 N Q11: Utilitarian Pearson groceries Correlation 1,432(**),319(**),207(*) 0,101,394(**),254(**),289(**) Sig. (2-tailed) 0 0 0,021 0, ,004 0,001 N Q12: Symbolic Pearson customer Correlation club 1,217(*),373(**),328(**),209(*),472(**),432(**) Sig. (2-tailed) 0, , N Q13: Utilitarian Pearson financial Correlation cost 1,207(*),293(**),564(**),299(**),307(**) Sig. (2-tailed) 0,021 0, ,001 0,001 N Q14: Hedonic: Pearson discover Correlation products 1,376(**) 0,115,725(**),353(**) Sig. (2-tailed) 0 0, N Q15: Symbolic Pearson better Correlation treatment 1,195(*),388(**),261(**) Sig. (2-tailed) 0,03 0 0,003 N Q16: Utilitarian: Pearson saving Correlation money 1 0,151,209(*) Sig. (2-tailed) 0,095 0,02 N Q17: Hedonic Pearson trying Correlation new products 1,429(**) Sig. (2-tailed) 0 N 124 Q18: Symbolic Pearson belonging Correlation to community 1 Sig. (2-tailed) N ** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed). 94

96 Appendix 4. Descriptive Statistics (SPSS) Mean Std. Deviation N Sex (m=1, w=2) 1,5565, Status (Citizen=1, PR=2, Oth=3) 1,1371, Age group (18-25=1, 26-33=2, 34-41=3, 42-49=4, 50-57=5, 58-65=6, 66-73=7, 74+=8) 3,3871 1, Years of holding credit card 18, , Q1: Involvement 53, , Q2: Immediate discount 43, , Q3: Delayed discount 44, , Q4: Immediate points 39, , Q5: Delayed points 44, , Q6: Direct to debt 50, , Q7: Direct to fee 48, , Q8: Indirect dep stores 36, , Q9: Indirect restaurant 33, , Q10: Hedonic gourmet foods 37, , Q11: Utilitarian groceries 51, , Q12: Symbolic customer club 24, , Q13: Utilitarian financial cost 64, , Q14: Hedonic: discover products 31, , Q15: Symbolic better treatment 42, , Q16: Utilitarian: saving money 74, , Q17: Hedonic trying new products 34, , Q18: Symbolic belonging to community 37, ,

97 Appendix 5. Total Variance Explained (SPSS) Co mp on Extraction Sums of Squared Rotation Sums of Squared ent Initial Eigenvalues Loadings Loadings % of Cumulativ % of Cumula % of Cumula Total Variance e % Total Variance tive % Total Variance tive % 1 5,830 32,388 32,388 5,830 32,388 32,388 3,260 18,110 18, ,150 11,946 44,335 2,150 11,946 44,335 3,247 18,038 36, ,903 10,574 54,908 1,903 10,574 54,908 2,539 14,108 50, ,245 6,917 61,825 1,245 6,917 61,825 1,912 10,620 60, ,070 5,944 67,769 1,070 5,944 67,769 1,241 6,894 67,769 6,786 4,368 72,138 7,733 4,072 76,210 8,679 3,773 79,983 9,637 3,540 83,523 10,514 2,856 86,379 11,486 2,701 89,080 12,417 2,319 91,398 13,346 1,921 93,319 14,307 1,708 95,027 15,285 1,583 96,611 16,240 1,335 97,946 17,204 1,132 99,078 18,166, ,000 Extraction Method: Principal Component Analysis. 96

98 Appendix 6. Rotated Component Matrix (SPSS) Component Q6: Direct to debt,766,195 Q13:Utilitarian financial cost,760,307 Q16:Utilitarian: saving money,704,200 Q2:Immediate discount,676,227,153,345 Q7: Direct to fee,600,316 Q3:Delayed discount,595,190,172,250,561 Q10:Hedonic gourmet foods,116,827,240,114 Q8:Indirect dep stores,295,819 Q11:Utilitarian groceries,346,774 Q9:Indirect restaurant,206,694,165,281 Q12:Symbolic customer club,649,458,165 Q17:Hedonic trying new,190,843 products Q14:Hedonic: discover products Q18:Symbolic belonging to community Q15:Symbolic better treatment Q5:Delayed points Q4:Immediate points Q1: Involvement,133,800,185,212,193,647 -,164,116,523,474,252,162,841,107,163,824 -, ,267,159,331,129,738 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. A Rotation converged in 7 iterations. 97

99 Eigenvalue Appendix 7. Scree Plot (SPSS) Scree Plot Component Number Appendix 8. Graph showing increase in research in loyalty programs Timeline: Loyalty Program ca ca ca ca ca ca 85 98

100 Appendix 9. Overview of the process of selecting constructs for the preset study Construct Content Explanation Arguments for Arguments against Authors using/menti oning construct Timing of reward/rede mption: Dimension of benefits: Type of Rewards: Target of Attitude: Immediate vs Delayed Rewards Utilitarian, Hedonic, Symbolic Value Direct vs Indirect Rewards Brand vs Program Loyalty Preferred timing of received rewards: Immediate=Received upon every visit. Delayed= Received upon every X- nth visit Preferred goods or services in L-P s. Utilitarian= Financial advantages. Hedonic= experimental, emotional, personally gratifying. Symbolic= Personal expression, self-esteem, social approval. Direct= Supports the product s value proposition. Indirect=Refers to incentives that are not relevant to a given product. Brand loyalty: Customer is loyal to brand and its products (good for business). Program loyalty: Customer is loyal Easy to understand, fits well with what I want to study, well used by authors who have studied loyalty programs Divides different types of rewards into helpful, easy-tounderstand categories which in turn would give result/conclusion body. It is perceived brand value, not brand loyalty which drives price insensitivity. Dowling & Uncles Very commonly mentioned in studies about LP s. Often used in combination with Immediate/Delayed in matrix form. Term is mentioned often in prior loyalty program/customer loyalty research. Has been concluded already that Delayed rewards are preferred only if they are of higher value than the immediate rewards. Prior studies have shown that consumers are strongly divided in their opinions. One category is not generally preferred over another. Could result in vague conclusions. Examples of Direct rewards would be very limited in the credit card industry; cash back or lowered card fees? Canadians hardly pay fees in relation to their rewards as is. Whether my test group is attracted to the rewards or is brand loyal has little meaning since credit card rewards are Keh & Lee (2006), Dowling & Uncles (1997) Yi & Jeon (2003) Mimouni- Chabane & Volle (2008) Yi & Jeon (2003) Dowling & Uncles (1997), Keh & Lee (2006) Yi & Jeon (2003) Dowling & Uncles (1997) 99

101 Involvement: High vs Low Promotional Strategy: Primary vs Secondary to good rewards programs and will lose interest in brand once program has ended. Reflects how interested customers are in knowing their brand/product well Primary= Core product or service. Secondary= Coupon or tokens that need to be converted Very often referred to in prior research. Is said to have great impact on preferred target attitude Could fit well into study as it would work as a separator for different rewards programs, just like timing of rewards does. not temporary programs but an unchanging part of the card. Whether my test group knows their own credit card rewards well is insignificant in my study. They will all have equal knowledge of the fictional rewards. Not sure if it would perhaps be excessive. Have only seen method mentioned in two articles, never used. Does anyone really want coupons rather than a core product? And if so, isn t that covered in Utilitarian vs hedonic value? Is said to be conceptually consistent with the Direct vs Indirect rewards. (Yi & Yeon) S. K Parahoo (2010). Dowling & Uncles (1997) Yi & Jeon (2003) Keh & Lee (2006) Yi & Jeon (2003) 100