The effects of reward schemes on customer loyalty : investigating the moderating effects of age & gender

M

ASTER

T

HESIS

‘’T

HE EFFECTS OF REWARD SCHEMES ON CUSTOMER LOYALTY

:

I

NVESTIGATING THE MODERATING EFFECTS OF AGE

&

GENDER

’’

Author Niels Alandt

Student no. 11414235

Date June 23th, 2017

Submission Master Thesis | Final version

Qualification MSc Business Administration – Marketing

Institution Amsterdam Business School, University of Amsterdam

This document is written by Niels Eric Alandt who declares to take full responsibility for the contents of this document. I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

TABLE OF CONTENTS | Page| 2

TABLE OF CONTENTS

2.CUSTOMERLOYALTYPROGRAMS ...13

CONCEPTUAL FRAMEWORK ______________________________________________________________________ 18 3.1EXPLANATIONOFRELATIONSHIPSINTHECONCEPTUALMODEL ... 19

3.2HYPOTHESES ...22 METHODOLOGY _____________________________________________________________________________________ 27 4.1RESEARCHAPPROACH ... 27 4.2RESEARCHDESIGN ... 28 4.3DATASOURCES ...29 4.4RESEARCHSTRATEGY ...29

4.5DATACOLLECTIONMETHOD ... 30

4.6MEASUREMENTSCALES ...31 4.7SAMPLE ... 33 4.8SAMPLINGMETHOD ... 33 4.9STATISTICALPROCESS ... 33 RESULTS ______________________________________________________________________________________________ 36 5.1DESCRIPTIVEANALYSIS ... 36 5.2CORRELATIONANALYSIS... 38

5.3THEEFFECTSOFREWARDSCHEMESONCUSTOMERSATISFACTION ... 42

5.4THERELATIONSHIPBETWEENCUSTOMERSATISFACTIONANDLOYALTY ... 47

5.5THEEFFECTSOFREWARDSCHEMESONCUSTOMERLOYALTY ... 55

5.6MODERATIONANALYSISOFGENDERANDAGE ... 58

DISCUSSION __________________________________________________________________________________________ 62 MANAGERIALIMPLICATIONS ... 71 CONCLUSION ... 75 LIMITATIONS ... 75 FUTURERESEARCH... 77 REFERENCES _________________________________________________________________________________________ 78 APPENDIX ____________________________________________________________________________________________ 83 A.1QUESTIONAIRRE(DUTCH) ... 83

A.1QUESTIONAIRRE(ENGLISH) ... 90

LIST OF TABLES | Page| 3

LIST OF TABLES

TABLES

Table 1. Reliability analysis of measurement scales 34

Table 2. Computation process of measurement scales 35

Table 3. Level of involvement – Doing groceries 36

Table 4. Frequency – Doing groceries 37

Table 5. Pre-measurement customer loyalty towards Albert Heijn 38

Table 6. Pre-measurement customer satisfaction Albert Heijn 38

Table 7.1 Means, Standard Deviations, Correlations & Reliabilities Pre-Measurements 41

Table 7.2 Means, Standard Deviations, Correlations & Reliabilities Post-Measurements 41

Table 8. Multiple regression analysis of customer 48

Table 9. Multiple regression analysis of customer loyalty 49

Table 10. Moderation analysis of Reward scheme & Customer Satisfaction (gender) 58

Table 11. Moderation analysis of Reward scheme & Customer Satisfaction (generation) 59

Table 12. Moderation analysis of Customer Satisfaction & Customer loyalty (gender) 60

ABSTRACT | Page| 4

ABSTRACT

Previous studies acknowledged the effect of customer loyalty differentials caused by gender, generation and culture (Ndubisi, 2006 ; Gurău, 2012 ; Melnyk & van Osselaer, 2012 ; Thompson & Chmura, 2015). However, no extensive research was conducted about the effects of these characteristics on loyalty programs.

This study will therefore reveal whether the relationship between loyalty program rewards and customer loyalty, is moderated by gender and/or age (generation Y vs generation X). In order to investigate this potential moderating effect, a 2x2x2 online experimental design was conducted. Data was collected by using an online questionnaire whereby the subjects were randomly assigned to one of the conditions (loyalty program with immediate reward or delayed reward). In total, 412 Dutch inhabitants of The Netherlands between the age of 23 and 57, were included into the dataset.

Customer loyalty was measured on both dimensions: (1) attitudinal loyalty and (2) behavioral loyalty. Customer satisfaction was included into the framework as a predictor of customer loyalty and was determined by measuring the antecedents of customer satisfaction (1) perceived service quality, (2) perceived trust and (3) perceived value. To measure the effects of the loyalty program reward condition, all variables were measured before(pre-measurement) and after(post-measurement) the manipulation took place.

Extensive analyses revealed that the relationship between loyalty program rewards and customer loyalty was moderated by age and gender. Furthermore, the relationship between loyalty program rewards and customer satisfaction was also moderated by age and gender. The results showed that immediate and delayed reward schemes differed in affecting customer satisfaction and customer loyalty when taking into account the gender and age of the subjects. These results imply that the effectiveness of loyalty program rewards differs between generation and gender.

Keywords: Customer loyalty, Customer satisfaction, Loyalty Programs, Reward schemes, Customer Relationship Marketing

INTRODUCTION | Page| 5

INTRODUCTION

Customer loyalty is a topic that has received a lot of attention of both managers and the academic research field (Breugelmans et al., 2015). Nowadays technology enables firms to interact directly with individual customers. This direct personalized interaction with customers has become extremely important as customers developed the need to interact deeply with companies and build strong relationships with companies that fully satisfies their needs (Rust et al., 2010). Customers have become more demanding and will switch easily between brands when a competitor is able to fulfill their customer needs more effectively (Sharma & Zareen, 2016).

In order to compete in today’s aggressive and interactive business environment, companies should maximize customer lifetime value by building strong and deep relationships with their customer base(Rust et al., 2010). Focusing on building strong and deep relationships is proven to be extremely important in hypermarkets (e.g. supermarkets) since empirical evidence showed that loyal customers are more profitable compared to regular customers (Huddleston et al., 2004).

However, the establishment of long-term relationships with customers is only feasible when customers become loyal to the company. Customer loyalty programs are commonly used tools for the marketing principle called ‘Customer Relationship Management’. This principle focus on establishing profitable and personalized long-term relationship with valuable customers. Loyalty programs are extremely effective at increasing customer lifetime value, since these programs offer their members gratification for their re-purchase behavior (Meyer-Waarden, 2007).

The positive effect of loyalty programs is acknowledged by many studies that found empirical evidence for the positive effects of loyalty programs on business performances. Members of loyalty programs showed significantly higher purchase intensities, increases of order size and order rates. Furthermore, customer loyalty programs were found to be significantly related to the growth of store loyalty (Liu, 2007 ; Meyer-Waarden, 2007 ; Bridson et al., 2008).

The implementation of loyalty programs remains popular and the amount of loyalty program memberships grows annually. In 2012, approximately 2,6 billion loyalty program memberships were held by consumers in the United States and more than 90% of European consumers belonged to at least one grocery loyalty program (Kang et al., 2016).

INTRODUCTION | Page| 6 But why should customer loyalty programs be analyzed for further research? Regarding the current literature, a lot of research was conducted about optimizing the design of loyalty programs to improve its effectiveness. For example, Drèze & Nunes (2009) investigated the design differentials of loyalty programs. The effects of reward schemes on store loyalty was studied by Leenheer et al.(2007). Furthermore, Bridson et al. (2008) conducted research to investigate the relationship between loyalty programs and store based loyalty. Most of the studies were focused on explaining the effects of reward schemes on customer loyalty. However, no extensive research was conducted about investigating the effects of rewards scheme differentials on customer loyalty when taking into account personal characteristics like age and gender.

Studies published in leading journals of both the marketing and psychology research field, found that individuals of different cultures, generations and gender differ in terms of their social norms, relational expectations and need for reinforcement. (Ndubisi, 2006 ; Gurău, 2012 ; Melnyk & van Osselaer, 2012 ; Thompson & Chmura, 2015). Since, these individuals differ in terms of their norms and values, these personal characteristics may also cause differentials in terms of loyalty program preferences. These differentials in terms of their social norms, relational expectations and need for reinforcement, may also affect the effectiveness of loyalty programs.

Therefore, this study will investigate whether personal characteristics like generation and gender potentially affect the effectiveness of a loyalty program. This study will reveal whether generation Y (i.e. millennials) and generation X show different loyalty patterns regarding the proposed reward scheme (immediate rewards vs. delayed rewards) of the loyalty program. The same process will also be executed for gender to investigate whether males and females differ in terms of their loyalty pattern, regarding the proposed loyalty program. Hereby the following research question will be answered:

Do different type of reward schemes (immediate vs. delayed) differ in affecting customer loyalty and is this relationship moderated by gender and or age?

INTRODUCTION | Page| 7 The findings of this study will create theoretical understanding about the effects of loyalty program rewards on customer loyalty and explains how this relationship is moderated by gender and age. These findings contribute to the current literature since they clarify the effects of loyalty program rewards on customer loyalty and show how these loyalty programs can be optimized to improve its effectiveness. Furthermore, this study also provides interesting findings about customer differentials that could be applied for future academic research of other related marketing principles.

In terms of managerial relevance, this study provides valuable practical implications that could help managers to improve their business performance by optimizing Customer Relationship Management. Furthermore, the findings of this study will explain managers how loyalty programs with different reward schemes affect customer loyalty when taking into account personal characteristics like age and gender. These implications may create better understanding about how loyalty programs could be utilized more effectively for particular customer groups. The optimization of loyalty programs may result in an increase of business performances and efficiency of marketing expenditures.

LITERATURE REVIEW | Page| 8

LITERATURE REVIEW

1.

CUSTOMER

LOYALTY

Customer loyalty is a topic that has received a lot of attention by both researchers and managers. As the marketing landscape changed over time due to technological innovations, consumers became more sophisticated and developed the need to interact deeply with brands that fully satisfies their wants and needs (Rust et al., 2010). Customers have become more demanding and switch easily between brands in their quest for a brand that offers the ultimate experience of need-fulfillment (Sharma & Zareen, 2016).

In order to survive in these aggressive and competitive marketing landscapes, companies should focus on maximizing customer-lifetime value to build sustainable relationships with their customers (Rust, Moorman & Bhalla, 2010). Customer loyalty is hereby extremely important because increasing customer-lifetime value and building long-term relationships is only feasible when companies possess a loyal customer base (Blut et al., 2014). The importance of customer loyalty is addressed by many studies.

Studies by Hallowell(1996), Reinartz & Kumar (2002) and Huddleston et al. (2004) found empirical evidence between customer loyalty and business profitability. Companies that possessed a loyal customer base were proven to be more profitable compared to companies with lower levels of customer loyalty. These companies were found to be more profitable due to the fact that loyal customers increased their order size and order rate compared to customers that weren’t loyal (Blattberg & Deighton, 1996 ; Huddleston et al., 2004). Customer loyalty is therefore really important, but what is customer loyalty exactly?

In previous studies, many researchers struggled to find an universally agreed definition of the phenomena (Uncles et al., 2003). Dick & Basu (1994) for example defined customer loyalty as ‘’the strength of the relationship between the relative attitude and repeated patronage of an individual whereby this relationship is mediated by social norms and situational factors’’.

According to Oliver (1999) this definition was not properly formulated as it did not took into account the theory of polygamous loyalty by Ehrenberg et al.(1995). According to this theory, customers are claimed to be multi-brand loyal and hold favorable attitudes towards different competitive brands whereby their repeated patronage behavior may be influenced by the occasion (e.g. convenience, price discounts). When customer X hold favorable attitudes towards brand A,B & C and buys products of brand A, the customer is labeled as a loyal customer of brand A.

LITERATURE REVIEW | Page| 9 However, this perception is misleading as their behavior is affected by the occasion and the ‘’loyal’’ customer may switch to brand B or C in the future due to the occasion (Ehrenberg et al., 1995).

Therefore, Oliver (1999) developed a definition that is universally accepted by todays literature as it takes into account congruency between attitude and repeated patronage that remains consistent in the future. Oliver (1999) defines customer loyalty as ‘’A deeply held commitment to rebuy or repatronize a preferred product/service consistently in the future, thereby causing repetitive same-brand or same brand-set purchasing, despite situational influences and marketing efforts having the potential to cause switching behavior’’

1.1 DIMENSIONS OF CUSTOMER LOYALTY

In order to successfully understand how customer loyalty arises, a distinction should be made between attitudinal loyalty and behavioral loyalty (Rogers & Peppers, 2004).

Attitudinal loyalty refers to the loyalty of a customer towards a brand, that is established in their state of mind. Attitudinal loyalty arises when people process certain information about a product, service or brand and form favorable preferences for that product, service or brand. For example, customers who hold more favorable attitudes or feelings towards a brand compared to other brands (even when the other brands offer better attributes), are claimed to be loyal in an attitudinal sense.

Behavioral loyalty refers to the dimension whereby loyalty is derived from the actual behavior of customers and not by taking into account their attitudes. When customers continuously buy products from the same brand over a period of time, these people are claimed to be loyal towards the brand in a behavioral sense. Roger & Peppers (2016) acknowledge the importance of increasing loyalty on both the attitudinal and behavioral dimension in order to create true customer loyalty. Creating only attitudinal loyalty will offer no financial benefits to the company because the attitude is not followed by behavior and the possession of only behavioral loyalty will not be sustainable as the drivers behind their behavioral loyalty may be based on convenience and can therefore easily copied by competitors (Rogers & Peppers, 2016).

LITERATURE REVIEW | Page| 10 1.2 DIFFERENT TYPES OF CUSTOMER LOYALTY

According to Dick & Basu (1994) customer loyalty can be divided into different categories as consumers may differ in terms of relative attitude towards a particular brand and their repeated patronage behavior. The level of relative attitude is formed by the attitude strength and the attitude differentiation. When customers hold a strong favorable attitude towards a brand that is differentiated from other brands, the customer will hold a high relative attitude towards the brand. Considering the level of the relative attitude of customers and their repeated patronage, four specific conditions of customer loyalty could be described according to the following framework (see: figure 1) (Dick & Basu, 1994).

Figure 1. Customer loyalty framework, Dick & Basu (1994)

‘No loyalty’ is the most unfavorable condition of customer loyalty as relative attitudes towards the brand are often low and not differentiated from competitors. Customers may perceive no product differences and purchases are purely incidental whereby the chance of repeated patronage is significant low.

‘Spurious loyalty’ occurs when the level of relative attitude is low and the repeated patronage is high. Hereby, the customer is unable to differentiate the brands and repeatedly buys the products from a brand due to situational cues or social influences (e.g. convenience, availability, familiarity). This condition of loyalty often occurs at companies that sell low-involvement products to their customers.

‘Latent loyalty’ is a problematic condition of loyalty for marketers as the customer holds favorable attitudes towards a product, service or brand but the repeated patronage is interfered by subjective norms and situational factors.

The fourth and most favorable condition for marketers is ‘True loyalty’ whereby the customer holds a favorable attitude towards the brand and will repeat his/her purchase behavior. It is necessary for the supplier to keep the customer in this position (Dick & Basu, 1994).

High Low High Low Repeated patronage behavior Relative attitude towards the brand

True Loyalty Latent Loyalty Spurious Loyalty No Loyalty

LITERATURE REVIEW | Page| 11 1.3 DEVELOPING CUSTOMER LOYALTY

As mentioned by Dick & Basu (1994) ‘True Loyalty’ is the most favorable condition of customer loyalty as this form of loyalty is a full commitment of the customer towards the brand that is not based on situational cues (Sivadas & Baker-Prewitt, 2000). However, obtaining loyal customers has to be developed overtime by building valuable relationships with the customer base (Oliver, 1999). In order to create understanding about how customer loyalty will arise overtime, Oliver(1999) introduced a framework that explains the process of developing customer loyalty. According to Oliver (1999) customer loyalty is developed by following four loyalty phases.

Cognitive loyalty is the first phase whereby the customer develops preferences for a specific brand based on available information about attributes or beliefs of a brand.

The second phase is called ‘Affective loyalty’ whereby customers begin to like the brand and form favorable attitudes towards the brand, based on cumulatively satisfying experiences with the brand.

The third phase of loyalty development is ‘Conative loyalty’. In this phase the loyalty is increased by repeated experiences of positive affect toward the brand. In this phase the customer develops a brand-specific attitudinal commitment to repurchase the brand’s products or services.

The final phase of customer loyalty development is ‘Action loyalty’ whereby the favorable intentions are now converted into actions of the customer. In this phase the customer becomes committed to a brand in such a way that it purchases the preferred brand product or service against all odds and at all costs (Oliver, 1999).

1.4 CUSTOMER SATISFACTION AND CUSTOMER LOYALTY

As mentioned earlier, customer loyalty occurs when a customer holds a more favorable attitude towards a particular brand and shows repeated patronage that is congruent with that attitude. According to Oliver (1999) affective and behavioral commitment arises only when a customer experiences a cumulative amount of satisfying events with a brand over a period of time. In order to create customer loyalty, it is therefore extremely important to create customer satisfaction. Kotler & Keller (2006) define customer satisfaction as ‘’a person’s feeling of pleasure or disappointment which resulted from comparing a product’s perceived performance or outcome against his/ her expectations” (Kotler & Keller, 2006).

LITERATURE REVIEW | Page| 12 The importance of customer satisfaction as a necessary antecedent for increasing customer loyalty is addressed by many researchers. Hallowell (1996) for example found a positive effect between customer satisfaction, customer loyalty and firm profitability. Cronin & Taylor (1992) found that customer satisfaction had a significant positive effect on repurchase intentions. This claim was also supported by Grönroos (2000) who found that satisfied customers were more likely to repurchase a product and share this experience with at least five other people.

Furthermore, Shanka (2012) found that high levels of customer satisfaction resulted in increased repurchase intentions and positive word-of-mouths whereby customer satisfaction is indicated as a determinant of customer loyalty (Shanka, 2012). According to the literature, the level of customer satisfaction is determined by service quality, trust and perceived quality (Kim et al., 2008 ; Al-Hawary et al., 2011 ; Shanka, 2012).

THEROLEOFSERVICEQUALITY,VALUE&TRUSTONCUSTOMERSATISFACTION

Service quality is defined as ‘’the overall evaluation of a specific service firm that results from comparing that firm’s performance with the customer’s expectations of how firms in that industry should perform’’ (Parasuraman et al., 1988). Studies of Gilbert & Veloutsou (2006), Taylor & Baker (1994) and Caruana (2002) have acknowledged the relationship between perceived service quality and customer satisfaction. Service quality is proven to be a predictor of customer satisfaction (Kuo et al., 2009). According to Taylor & Baker (1994), higher levels of service quality will increase customer satisfaction significantly and may stimulate customer loyalty.

Another determinant of customer satisfaction is perceived customer value (Fornell, 1992). Perceived customer value is ‘’the consumers’ overall assessment of the utility of a product based on perceptions of what is received and what is given” (Zeithaml, 1988). Kuo et al. (2009) showed that the level of perceived customer value has significant effects on customer satisfaction. Their study showed that customers who perceive higher value (emotional and functional) of the product/service are more satisfied and will experience more satisfaction towards the product/service.

The final determinant of customer satisfaction is trust (Ranaweera & Prabhu, 2003). Trust is defined as ‘’the willingness of a party to be vulnerable to the actions of another party based on the expectation that the other will perform a particular action important to the trustor, irrespective of the ability to monitor or control that other part’’ (Mayer et al., 1995). The relationship between trust and increased customer loyalty is supported by a variety of studies (Sirdeshmukh et al., 2002 ; Shanka,

LITERATURE REVIEW | Page| 13 2012) about brand trust and customer loyalty. In these studies, trust was treated as an direct predictor of customer loyalty.

Furthermore, extensive comparative research between trust and customer satisfaction on customer loyalty showed that customer satisfaction is a significant stronger/precise predictor of customer loyalty compared to trust (Ranaweera & Prabhu, 2003). The level of trust only increases repurchase intentions indirectly by increasing customer satisfaction. According to Ranweera & Prabhu (2003) trust acts as an complement of customer satisfaction, whereby customer satisfaction has an direct effect on predicting customer loyalty.

2.

CUSTOMER

LOYALTY

PROGRAMS

Due to a change in the marketing landscape, customers have become more demanding and critical in their quest for a brand that offers the ultimate experience of need-fulfillment (Sharma & Zareen, 2016). Companies have to fully satisfy the customer’s needs in order to develop and maintain long-term profitable relationships with them (Meyer-Waarden, 2007 ; Palmer & Bejou, 2016). In order to optimize the relationships with customers, a marketing practice called ‘Customer Relationship Management’ is used which provides better understandings about a customer’s wants and needs of their relationship with the brand. The practice of CRM can lead to valuable customer insights that help keeping their customer base satisfied to increase the customer-lifetime value (Payne & Frow, 2005).

Loyalty programs can be defined as a marketing tool for managers to help executing Customer Relationship Management successfully (Uncles et al., 2003). Meyer-Waarden (2007) defines loyalty program as ‘’an integrated system of marketing actions that aims to make customers more loyal by developing personalized relationships with them.’’ Loyalty programs are designed to reward re-purchasers with extra products or supplementary goods and services (Oliver, 1999). Bolton et al. (2000) claim that firms make use of loyalty programs to increase customer retention by increasing customer satisfaction and offer more value to profitable customer segments. Customer loyalty programs are believed to function as an effective tool of CRM that helps increasing customer’s share-of-wallet by establish more profitable and long-term relationship (Meyer-Waarden, The influence of loyalty programme membership on customer purchase behaviour, 2008).

The effectiveness of loyalty programs in terms of increasing business profitability, have received a lot of attention by the research field. However the empirical evidence about the effectivity of customer loyalty programs are often conflicting (Leenheer et al., 2007). Some experts claim that

LITERATURE REVIEW | Page| 14 loyalty programs seems ineffective as these programs would increase operational costs as loyal customer expect better services (Reinartz & Kumar, 2002). Bolton et al. (2000) also criticizes the effectiveness of loyalty programs on customer lifetime value. They found that loyalty programs only marginally decreased customer’s sensitivity on competitive offerings but had no effects on increasing customer retention on the long run (Bolton, Kannan & Bramlett, 2000).

However, many studies have also proven the effectiveness of loyalty programs on sales performances and customer loyalty. Howard (1994) found that loyalty programs would lead to more frequent purchases, purchases in greater volume, and purchases of other goods and services offered by the firm. Meyer-Waarden (2008) showed that loyalty programs significantly increased purchase intensities, purchase frequencies and inter-purchase times. Liu (2007) also found support for the positive effects of loyalty programs and showed that loyalty programs increased the order size and order rate of consumers with low and moderate purchase frequencies. Furthermore, Bridson et al. (2008) discovered that loyalty programs are a significant predictor of store loyalty and therefore offering support for the contention that loyalty programs are capable of engendering customer loyalty.

2.1 TYPES OF CUSTOMER LOYALTY PROGRAMS

According to Berman (2006) there can be made an distinction between four types of customer loyalty programs whereby each type has its advantages.

‘Type 1’ is the most basic form of a loyalty program and is most often used by firms who operate in hypermarkets (e.g. supermarkets). Customers receive a customer card which provides them with immediate rewards (i.e. discounts, coupons) when the card is presented at the cashier. This type of loyalty program is in essence not successful in creating customer loyalty because membership to the program is open to all customers and each member receives the same reward regardless of his/her purchase history. Also no personal data (demographic data, name, purchase history) is collected so the firm is not able to create special offerings or make distinctions between the level of loyalty of their consumers. Examples: ‘AH Bonuskaart’ from the Dutch supermarket Albert Heijn, which provides customers with discounts when they present their Bonuskaart at the cashier.

The ‘type 2’ loyalty program is a program whereby customers receive a reward after a certain amount of purchases are established. The reward scheme of this program is delayed whereby the reward itself, can be either direct (product-related) or indirect (non-product related). These programs however do not collect detailed customer data and can therefore make no distinction

LITERATURE REVIEW | Page| 15 between behavioral loyalty or true loyalty. An example of this type is a stamp card whereby customers get a free cup of coffee after they visited the store for the fifth time.

‘Type 3’ loyalty programs are programs whereby customers receive a reward after a certain level of purchases is achieved. These programs often work with tier structures (bronze, silver, gold) to stimulate purchase behavior as premium tiers offer more exclusive rewards. The presented rewards are often delayed and indirect from nature as many of these programs involve partnerships with complementary products or services to increase program value by offering a larger variety of rewards. These programs collect detailed customer data but often lack the ability to personalize relationships as communication takes place on tier-base instead of individual base. An example of this program is The ‘ANWB ledenpas’ that provides users with discounts for amusement parks, hotels, train tickets etc. The amount of discount that is provided to the customer is hereby based upon the tier (Blue, Bronze, Silver, Gold, Platinum) they belong to.

Type 4 loyalty programs reward their members by giving them points for their purchases. Customers can collect these points and change them for either direct or indirect rewards, whereby exclusive rewards require more points. These programs collect valuable customer data professionally to personalize communications and offerings based on their purchase history. An example of this program is ‘KLM Flyingblue‘ whereby members collect points when a flight at KLM is purchased. These points can be used for different (travel-related) rewards and specialized offerings will be communicated based on their purchase history or interests.

2.2 OPTIMIZING LOYALTY PROGRAMS

Previous studies have dedicated much effort in order to gather knowledge about how loyalty programs can be optimized and become more effective. Therefore, a lot of research is conducted about different aspects that could determine the effectiveness of a loyalty program. Dréze & Nunez (2009) for example, found that differences in tier-structures of loyalty programs had a significant effect on customer loyalty. They found that customers have the need of feeling superior compared to others and by implementing different tiers will stimulate the urge to become part of the elite-tier (e.g. Gold) which positively affect sales.

Furthermore, Berman (2006) researched the effects of program eligibility on the effectiveness of the loyalty program. He found that ‘open’ programs were more successful in increasing sales and ‘closed’ programs were performing better in terms of program profitability. As ‘open’ programs are really successful in increasing the amount of members, ‘closed’ programs often only focusing on loyal

LITERATURE REVIEW | Page| 16 customers and prevent firms of wasting marketing budget on customers that are in essence not loyal (Reinartz & Kumar, 2002 ; Berman, 2006).

Another important aspect that received a lot of attention by the literature are loyalty program rewards. The importance of program rewards is addressed by many researchers. Dowling & Uncles (1997) claim that program rewards are essential as they determine the program value which is a necessary condition for developing loyalty throughout the program. Furthermore, program rewards can lock-in customers and increase customer loyalty as these special privileges and personalized offerings can increase the perceived switching costs of customers. These switching costs will prevent customers from switching to other brands or programs (Blut et al., 2014). Meyer-Waarden (2008) found that rewards positively stimulate purchase and re-purchase behavior whereby behavioral loyalty increased on the short term.

As a result, a lot of research was conducted about optimizing reward schemes to increase customer loyalty. For example, Yi & Jeon (2003) found that direct (product-related) rewards were perceived as more valuable under high involvement compared to indirect (product-unrelated) rewards. Furthermore, they also found that reward timing affected the value of the program. Immediate rewards were perceived as more valuable compared to delayed rewards under a low involvement condition (Yi & Jeon, 2003). This finding was also supported by Leenheer et al. (2007) who found that behavioral loyalty of non-members significantly increased when immediate (financial) rewards were provided to the customers. Their study showed that delayed rewards had a significant positive effect on both behavioral and attitudinal loyalty of existing program members (Leenheer et al., 2007).

However, in order to design a successful customer loyalty program, companies still have to consider the individual needs of their customers as they have become more demanding and will switch more easily between brands when a competitor is able to better fulfill the customer’s needs. (Sharma & Zareen, 2016). Therefore, Dowling & Uncles (1997) claim that a company should use different reward schemes for members and non-members in order to maximize effect.

2.3 DIFFERENCES AMONGST INDIVIDUALS

There has been conducted a lot of research about optimizing the effectiveness of loyalty programs. However, only minor studies take into account that loyalty programs should be tailored for a specific target market as each customer segment can differ in terms of preferences. For example, Leenheer et

LITERATURE REVIEW | Page| 17 al. (2007) found evidence about preference differences in terms of rewards between member and non-members.

Furthermore, Thompson and Chmura (2015) found evidence for differences amongst individuals caused by cultural aspects. Their study showed that the cultural values of an individual, plays a significant role in their program choice as certain cultures preferred different reward structures.

Melnyk & van Osselaer (2012) found preference differentials based on gender. Their study showed that males and females respond differently towards reward schemes of loyalty programs. According to their study, males would respond more favorable towards loyalty programs where the obtained reward for their action is easily visible to others. However, females will react more favorable towards loyalty programs whereby the reward is presented in a relatively private way and enhances the feeling of personalization and individualism. The claim that gender may influence customer loyalty is also supported by the research of Ndubisi (2006). He found that women were more loyal compared to men when a brand enhanced the feeling of trustworthiness.

Furthermore, research conducted by Gurâu (2012) found evidence for possible preference differentials determined by age. His study showed that generations differ in terms of values, behavior and characteristics that may influence the effectiveness of loyalty programs (Gurâu, 2012). He found that generation X and Y show important variabilities of loyalty patterns in different market and economic contexts.

Leiter et al. (2010) found that younger generations have a stronger need for regular reinforcement and feedback compared to older generations. Furthermore, generations may differ in terms of expectations of social norms and relationships (Leiter et al., 2010). This may imply that generations may react differently towards customer loyalty programs as their social norms, need for reinforcement and relational expectations differ.

CONCEPTUAL FRAMEWORK | Page| 18

CONCEPTUAL FRAMEWORK

The conceptual framework (see: figure 2) illustrates the expected relationship between the reward scheme of a loyalty program and its effect on customer loyalty. Since customer loyalty has to develop overtime and is built by following four loyalty phases (Oliver, 1999), measuring changes in customer loyalty with a cross-sectional study would be problematic. However, previous literature has shown that customer satisfaction may be perceived as a precise predictor of customer loyalty. Different studies have shown that customer satisfaction was significantly related to increased repurchase intentions and positive word-of-mouth (Hallowell, 1996 ; Grönroos, 2000 ; Shanka, 2012).

Since measuring customer loyalty is somewhat problematic and customer satisfaction functions as a precise predictor of customer loyalty, the effects of reward schemes will be measured on both customer satisfaction and customer loyalty.

Furthermore, all the other important constructs like the moderators and control variables are included into the framework. The framework functions as a guideline to explain whether and how reward schemes affect customer loyalty and which variables may moderate the relation itself.

CONCEPTUAL FRAMEWORK | Page| 19

3.1

EXPLANATION

OF

RELATIONSHIPS

IN

THE

CONCEPTUAL

MODEL

Regarding the conceptual model, this research will explain whether immediate and delayed reward schemes will have different effects on customer satisfaction and customer loyalty. The relationship between reward scheme differentials and customer loyalty is acknowledged by previous studies. Leenheer et al. (2007) found evidence about the effects of reward scheme differentials and customer loyalty. Loyalty programs with immediate reward schemes were significant more effective at increasing behavioral loyalty than delayed reward schemes.

Furthermore, research conducted by Berman (2006) indicated that immediate rewards were significant more effective in stimulating behavioral loyalty whereas delayed rewards would increase customer loyalty more on the attitudinal dimension. The differentials between reward schemes were also addressed by the study of Yi & Jeon (2003). These researchers found that the timing wherein a reward was provided, affected the value perception of the loyalty program of low involved people. Immediate rewards were perceived as more valuable compared to delayed rewards under a low involvement condition (Yi & Jeon, 2003).

Based on the current literature, the assumption is made that reward schemes (delayed vs. immediate) could have different effects on customer loyalty. However, in order to measure the effects of reward schemes on customer loyalty, a measurement of customer satisfaction have to be taken into account. Many studies have included customer loyalty in their conceptual framework as their only dependent variable. However, this is often problematic since customer loyalty is a phenomenon that has to develop over time. In order to measure customer loyalty correctly, both the attitudinal and behavioral dimensions of customer loyalty should be measured independently (Rogers & Peppers, 2016).

Attitudinal loyalty refers to the loyalty of a customer towards a brand, that is established in their state of mind. Attitudinal loyalty arises when people process certain information about a product, service or brand and form favorable preferences for that product, service or brand (Rogers & Peppers, 2016).

Furthermore, behavioral loyalty refers to the dimension where loyalty is derived from the actual behavior of customers and does not take into account the attitudinal preference of the customers. When measuring attitudinal loyalty no major problems occur during the measurements since attitudinal loyalty only represents the attitudinal preferences of the subject.

CONCEPTUAL FRAMEWORK | Page| 20 However, behavioral loyalty measures the actual behavior of the subject and can explain whether the subject can be labeled as loyal when the attitude and behavior are congruent with each other.

As this study will be cross-sectional from nature, no precise measurements can be made about the behavioral loyalty of the subjects, since the actual purchase behavior of the subjects cannot be observed due to the lack of time and financial resources. In order to tackle this measurement problem, the variable of customer satisfaction is included in the framework since customer satisfaction is proven to be a precise predictor of customer loyalty (Hallowell, 1996 ; Grönroos, 2000 ; Shanka, 2012). According to Oliver (1999) affective and behavioral commitment (i.e. customer loyalty) arises only when a customer experiences a cumulative amount of satisfying events with a brand over a period of time. This may imply that when a reward scheme increases the level of customer satisfaction, the level of customer loyalty will also be positively affected. Since the level of customer satisfaction is determined by service quality, trust and perceived quality (Kim et al., 2008 ; Al-Hawary et al., 2011 ; Shanka, 2012) these antecedents of customer satisfaction are also included in the conceptual framework.

Furthermore, two moderating variables (gender and age) are included into the conceptual framework, since the expectation is that either one or both of the variables will moderate the relationship between the reward schemes of a loyalty program (independent variable) and customer loyalty (dependent variable).

3.1.1 MODERATING VARIABLES IN THE CONCEPTUAL MODEL

The moderating variable of gender is included into the framework since previous literature has shown that customer loyalty can differ between gender. For instance, Melnyk & van Osselaer (2012) found that males and females responded differently towards loyalty program reward schemes. Males responded more favorable towards loyalty programs where the obtained reward for their action was easily visible to others. On the other hand, females reacted more favorable towards loyalty programs that provided the reward in a relatively private way. The presumption that gender may influence customer loyalty was also supported by Ndubisi (2006). He found empirical evidence about gender differentials and his study indicated that females were more loyal compared to males when a brand enhanced the feeling of trustworthiness.

The moderating variable of age is included into the framework since previous literature has shown that customer loyalty can differ between age-groups (i.e. generations). Research conducted by Gurâu (2012) found evidence that generations differ in terms of values, behavior and characteristics

CONCEPTUAL FRAMEWORK | Page| 21 that may influence the effectiveness of loyalty programs (Gurău, 2012). His study indicated that millennials and generation X customers showed an important variability of loyalty patterns in different market and economic contexts. Furthermore, Leiter et al. (2010) found that younger generations had a stronger need for regular reinforcement and positive feedback mechanisms compared to older generations. Besides, generations may also differ in terms of their expectations about social norms and relationships (Leiter et al., 2010). This may imply that generations may react differently towards customer loyalty programs since their social norms, need for reinforcement and relational expectations may be potentially different.

3.1.2 CONTROL VARIABLES IN THE CONCEPTUAL MODEL

The first control variable is affective commitment towards the loyalty program. This variable measures how much the subject feels emotionally attached towards the loyalty program. When people feel more emotionally attached to a particular loyalty program, they may also show higher levels of customer loyalty (Thompson & Chmura, 2015). In order to measure whether the increase of customer loyalty is purely caused by the reward schemes, this variable will be controlled during the data analysis.

The second control variable is behavioral commitment towards the loyalty program. Dowling & Uncles (1997) claim that higher levels of perceived value of the loyalty program not necessarily transform into brand loyalty, due to the fact that a customer may hold program loyalty instead of true customer loyalty. The concept of program loyalty was acknowledged by Yi and Jeon (2003) based on the Polygamous loyalty theory, which is built upon the fact of consumers being loyal towards different brands at different occasions (Ehrenberg A. , 1988). Yi and Jeon (2003) defined program loyalty as the situation where customers show high repeated patronage behavior but only hold high relative attitudes towards the loyalty program and not particular towards the brand. In order to measure whether the increase of customer loyalty is purely caused by the reward schemes and not by their behavioral commitment towards the program, this variable will be controlled during the data analysis.

The third variable that was controlled, is product category involvement. This variable measures how involved a subject is with a particular product category. When subjects are more involved in particular product categories, this may influence their perception about particular brands or loyalty programs and can affect their customer loyalty (Boonghee & Donthu, 2001). Yi & Jeon (2003) showed that customers react differently towards certain reward schemes under different levels

CONCEPTUAL FRAMEWORK | Page| 22 of involvement. They found that direct (product-related) rewards were perceived as more valuable under high involvement compared to indirect (product-unrelated) rewards. Furthermore, they also found that reward timing affected the value of the program. Immediate rewards were perceived as more valuable compared to delayed rewards under a low involvement condition (Yi & Jeon, 2003).

Therefore, subjects may react differently towards a reward schemes based on their product category involvement and may affect the effects of reward schemes on increasing customer loyalty. In order to measure whether customer loyalty is purely affected by the reward schemes, this variable was controlled during the data analysis.

3.2

HYPOTHESES

This chapter briefly introduces and states the hypotheses that were defined based upon the research question that will be investigated. More elaborate covering of the theories related to these hypotheses can be found in the literature review.

3.2.1 THE EFFECT OF REWARD SCHEMES ON CUSTOMER SATISFACTION

The current literature has shown that different reward schemes may differ in terms of affecting the level of customer loyalty. Leenheer et al. (2007) found evidence about the effects of different reward schemes (immediate rewards vs. delayed rewards) on customer loyalty. Furthermore, research conducted by Berman (2006) found that immediate rewards were significant more effective in stimulating behavioral loyalty whereas delayed rewards would increase attitudinal customer loyalty. Yi & Jeon (2003) also found that reward timing affected the value of the program. Immediate rewards were perceived as more valuable compared to delayed rewards under a low involvement condition.

This finding was also supported by Leenheer et al. (2007) who found that behavioral loyalty of non-members significantly increased when immediate (financial) rewards were provided to the customers. Their study also showed that delayed rewards had a significant positive effect on both behavioral and attitudinal loyalty of existing loyalty program members.

Regarding the findings of previous studies, this research will investigate the effects of different reward schemes on customer loyalty. Since customer satisfaction is indicated as a determinant of customer loyalty (Shanka, 2012) the effects of reward scheme differentials on the antecedents of customer satisfaction are investigated by testing the following hypotheses:

CONCEPTUAL FRAMEWORK | Page| 23

H1a: Reward schemes have a positive effect on customer satisfaction

H1b: Loyalty programs with immediate reward schemes will elicit higher levels of perceived brand value compared to programs with delayed reward schemes.

H1c: Loyalty programs with immediate reward schemes will elicit higher levels of perceived brand trust compared to programs with delayed reward schemes.

H1d: Loyalty programs with immediate reward schemes will elicit higher levels of service quality compared to programs with delayed reward schemes.

3.2.2 THE EFFECT OF CUSTOMER SATISFACTION ON CUSTOMER LOYALTY

The importance of customer satisfaction as a necessary antecedent for customer loyalty is addressed by many researchers. Oliver (1999) claimed that affective and behavioral commitment only arises when a customer experiences a cumulative amount of satisfying events with a brand over a period of time. Hallowell (1996) also found a positive effect between customer satisfaction, customer loyalty and firm profitability.

Research conducted by Cronin & Taylor (1992) indicated that customer satisfaction had a significant positive effect on repurchase intentions. Grönroos (2000) found that satisfied customers were more likely to repurchase a product and will share this experience with at least five relatives.

Furthermore, Shanka (2012) found that high levels of customer satisfaction resulted in increased repurchase intentions and positive word-of-mouths whereby customer satisfaction was indicated as a determinant of customer loyalty (Shanka, 2012). Since the literature has acknowledged perceived service quality, perceived trust and perceived quality as the antecedents of customer satisfaction (Kim et al., 2008 ; Al-Hawary et al., 2011 ; Shanka, 2012), the following hypotheses were formulated to test the potential effects between customer satisfaction and customer loyalty:

H2a: Customer satisfaction has a positive effect on customer loyalty

H2b: High levels of perceived brand value will elicit higher levels of customer loyalty towards the brand compared to lower levels of perceived brand value

H2c: High levels of perceived brand trust will elicit higher levels of customer loyalty towards the brand compared to lower levels of perceived brand trust

H2d: High levels of perceived service quality will elicit higher levels of customer loyalty towards the brand compared to lower levels of perceived service quality

CONCEPTUAL FRAMEWORK | Page| 24

3.2.3 THE MODERATING EFFECTS OF GENDER

The moderating variable of gender is included into the framework as previous literature has shown that customer loyalty can differ between gender (Ndubisi, 2006 ; Melnyk & van Osselaer, 2012). The studies conducted by Ndubisi (2006) and Melnyk & van Osselaer (2012) showed that males and females responded differently towards loyalty program reward schemes. According to their studies, males would respond more favorable towards loyalty programs whereby the obtained reward for the action was easily visible to others. However, females reacted more favorable towards loyalty programs whereby the reward was presented in a relatively private way and enhanced the feeling of personalization and individualism.

Since males responded more favorable towards loyalty programs where the obtained reward for their action was easily visible to others, the assumption is made that they also would react more favorable towards loyalty programs with immediate reward schemes. Immediate rewards (e.g. discounts, vouchers, presents) are often presented at the cash registers which increases the possibility of other people being present at the moment the reward is presented to the customer. On the other hand, females will therefore react more favorable to rewards that are presented in a private and personal setting. Since delayed rewards are often presented after a certain amount of purchases/store visits, the assumption is that females react more favorable towards delayed rewards schemes compared to males.

H3a: The relationship between reward schemes and customer satisfaction is moderated by gender

H3b: Loyalty programs with immediate reward schemes will elicit higher levels of perceived brand value at males compared to females

H3c: Loyalty programs with immediate reward schemes will elicit higher levels of perceived brand trust at males compared to females

H3d: Loyalty programs with immediate reward schemes will elicit higher levels of service quality at males compared to females.

Furthermore, the research conducted by Ndubisi (2006) showed that customer loyalty may differ between gender. He found empirical evidence about gender differences and showed that women were more loyal compared to men when a brand enhanced the feeling of trustworthiness. However, when the perceived trustworthiness of the brand was low, males showed more loyal behavior towards the brand.

CONCEPTUAL FRAMEWORK | Page| 25 Yavas et al. (2004) showed that females have stronger needs for interpersonal relationships and communication with brands compared to males. When these needs are satisfied, female customers were more inclined to share positive word of mouth with relatives compared to men (Yavas et al., 2004). Based on these findings the assumption is made that when females perceive higher levels of customer satisfaction, this will result into higher levels of customer loyalty compared to men.

H3e: The relationship between customer satisfaction and customer loyalty is moderated by gender

H3f: Females will show higher levels of customer loyalty compared to males when the perceived brand value is high. H3g: Females will show higher levels of customer loyalty compared to males when the perceived brand trust is high. H3h: Females will show higher levels of customer loyalty compared to males when the perceived service quality is

high.

3.2.3 THE MODERATING EFFECTS OF AGE /GENERATION

The moderating variable of age is included into the framework as previous literature showed that customer loyalty can differ between generations. Gurâu (2012) found evidence that generations differ in terms of values, behavior and characteristics that may cause preference differentials and may influence the effectiveness of loyalty programs. Millennials (i.e. generation Y) and generation X individuals show an important variability of loyalty patterns in different market and economic contexts (Gurău, 2012). Furthermore, Leiter et al. (2010) found that younger generations have a stronger need for regular reinforcement and feedback compared to older generations and may differ in terms of expectations of social norms and relationships (Leiter et al., 2010). This may imply that generations may react differently towards customer loyalty programs as their social norms, need for reinforcement and relational expectations differ.

Millennials have stronger needs for regular reinforcement and feedback compared to older generations and therefore the assumption is made that millennials show higher degrees of customer satisfaction when they participate into a program that makes use of immediate reward schemes. The reason for this is that loyalty programs with immediate reward schemes offer more frequent short-term benefits to their users to compared to loyalty programs with delayed reward schemes.

On the other hand, consumers of generation X are expected to react more favorable to loyalty programs with delayed reward schemes. As these consumers are less driven by mechanisms of reinforced feedback compared to millennials, subjects of generation X are expected to show higher degrees of customer satisfaction compared to millennials when the loyalty program offers delayed

CONCEPTUAL FRAMEWORK | Page| 26 rewards to its members. Regarding these assumptions, the following hypotheses were formulated to investigate whether age is moderating the relationship of reward schemes and customer satisfaction.

H4a: The relationship between reward schemes and customer satisfaction is moderated by age

H4b: Loyalty programs with immediate reward schemes will elicit higher levels of perceived brand value at generation Y customers compared to generation X customers.

H4c: Loyalty programs with immediate reward schemes will elicit higher levels of perceived brand trust at generation Y customers compared to generation X customers.

H4d: Loyalty programs with immediate reward schemes will elicit higher levels of service quality at generation Y customers compared to generation X customers.

Furthermore, millennials (generation Y) are described as self-centered, innovation-driven individuals, who have higher purchase intensities compared to older generations and display lower levels of brand loyalty (Greenberg, 2011). This generation is also harder to satisfy since they do not tolerate bad brand experiences (Bowen & Chen McCain, 2015). However, the loyalty towards a brand of millennials may only increase when they have satisfying experiences with a company. Those brands that can connect with the Millennials in an authentic, trustworthy and valuable way, can develop a strong emotional connection with these individuals (Sahay & Sharma, 2010). Based on the previous literature the assumption is made that age can have a moderating effect on the relationship between customer satisfaction and customer loyalty.

Since the current literature describes millennials as less brand loyal towards brands compared to older generations, the assumption is made that therefore millennials will show lower levels of customer loyalty compared to generation X customers. These assumptions will be investigated by testing the following hypotheses:

H4e: The relationship between customer satisfaction and customer loyalty is moderated by age

H4f: Generation X will show higher levels of customer loyalty compared to Generation Y when the perceived brand value is high.

H4g: Generation X will show higher levels of customer loyalty compared to Generation Y when the perceived brand trust is high.

H4h: Generation X will show higher levels of customer loyalty compared to Generation Y when the perceived service quality is high.

METHODOLOGY | Page| 27

METHODOLOGY

In this section an extensive explanation will be given about how the study was executed in order to answer the research question properly.

4.1

RESEARCH

APPROACH

According to Bryman and Bell (2011) the research approach defines how the research problem is going to be investigated in this thesis. The requirements for a master thesis should meet certain quality standards since it needs to be relevant and rigorous. By relevance, Bryman and Bell (2011) mean that a research needs to create findings that contribute in a managerial and theoretical manner. Furthermore the research should be executed within a certain amount of time and the results and execution should be written down in an understandable manner (Bryman & Bell, 2011). In order to execute a research in such manner that creates reliable and valid data, the right research method should be selected. According to Bryman and Bell (2011) researchers can either executing their research by using an inductive or deductive research approach.

4.1.1 DEDUCTIVE RESEARCH APPROACH

The inductive research approach is an approach to generate new theories as a result of thorough observations and is not build upon theories of previous literature (Lancaster, 2005). This study is however deductive from nature since the foundation of this study is built upon empirical evidence that is collected by previous studies. These studies have contributed to create a solid foundation of knowledge about customer loyalty, customer satisfaction and loyalty programs. Based upon these important theories, 24 different hypotheses were formulated and tested to create more empirical knowledge about the effects of reward schemes on customer loyalty and whether this relationships is potentially moderated by age and/or gender.

METHODOLOGY | Page| 28 4.1.2 QUANTITATIVE RESEARCH APPROACH

Researchers have the choice between a qualitative and quantitative research approach. A qualitative research approach is beneficial when researchers want to gather deep and rich information about a particular phenomenon or when the current literature lacks understanding about the phenomenon. On the other hand, a quantitative research approach is often used to draw conclusions about bigger populations that are statistically supported.

For this study a quantitative research approach was used, as it was more appropriate since the purpose of this study is to test whether particular theories of customer loyalty programs are applicable to a particular situation. The advantage this research approach is that the execution occurred in a controlled and structured environment that enabled easier replication of the study (Bryman & Bell, 2011) This enables generalization towards the population when the findings were statistically supported.

4.2

RESEARCH

DESIGN

A descriptive research design helps to provide answers to questions like: who, what, when, where and how. These designs are often used to gather information about the current status of a phenomenon and helps to describe what happens to the phenomenon at certain occasions or conditions.

Since this study was conducted to gather information about what happens to customer loyalty at certain occasions or conditions, the research design was designed as a combination between a descriptive and experimental 2x2x2 between-groups research design. This design helps to explore what would happen with the level of customer loyalty towards the brand when the conditions of reward schemes were manipulated (immediate reward & delayed reward). Furthermore this design enabled to ability to test the potential moderating effects of the variables gender (female & male) and age (generation x & generation y) on the relationship between reward schemes and customer loyalty.

METHODOLOGY | Page| 29

4.3

DATA

SOURCES

In order to conduct research, a researcher can consult primary data sources and secondary data sources (Saunders et al., 2009). Primary data is data collected by the researchers themselves whereas secondary data sources are sources of data collected by previous conducted studies. In most cases, the usage of secondary data is more attractive as this source if often less expensive and time consuming. However, researchers should be very concise with the usage of secondary data as the context whereby the data is collected, should be in line with the context of their own study (Bryman & Bell, 2011).

For this study, a combination of both primary and secondary data was used to investigate the research topic. The secondary data was used since it functioned as an efficient source to build a solid foundation of knowledge about customer loyalty and customer loyalty programs. During the secondary data collection, data of relevant and leading studies was used to build a solid foundation of knowledge. This knowledge was used to optimize the gathering process of primary data, which was collected by myself by using an online experimental survey.

4.4

RESEARCH

STRATEGY

As earlier mentioned a combination of both primary and secondary data was gathered to answer the research question properly. According to Saunders et al. (2009) different research strategies can be conducted in order to gather this data. Examples of these research strategies are experiments, case studies, surveys, archival analysis, interviews & observations.

The aim of this study was to explore what would happen with the level of customer loyalty when the subjects were proposed to different reward schemes. In order to measure these effects, the reward schemes needed to be manipulated to measure the potential different effects of reward schemes on customer loyalty. One of the most applicable research strategies that enabled the possibility of manipulation the conditions of reward schemes, was an experiment. Furthermore, surveys, are extremely practical in terms of collecting quantitative data that can potentially generalized towards the population. Therefore, a combination of two strategies was applied (experiment & online survey) to gather the primary data.

METHODOLOGY | Page| 30

4.5

DATA

COLLECTION

METHOD

As the goal of this study is to collect quantitative data that can be statistically analyzed, the primary data was collected by using an online questionnaire (see: appendix A.1). Questionnaires allow gathering data about the sample that is both valid and reliable when it is gathered correctly. Aspects like validity and reliability were extremely important during the execution of this study, as the goal of this study was to obtain data that can be generalized towards the population. Furthermore, an online questionnaire was the most feasible option available when considering the available time and financial resources during the execution of this study.

The online questionnaire was designed with Qualtrics, a special online platform that enables researchers to produce effective surveys that can be easily distributed online. Qualtrics has a very user-friendly interface which increases the level of convenience for both the researcher and its subjects. Furthermore, the input given by subjects, was easily exported to software for conducting statistical analyses.

The content of the questionnaire was built by using relevant and leading measurement scales of previous studies, whereby the reliability of these scales was significantly high (see appendix A.2). The questionnaire consisted out of a brief introduction about the topic and instructions about how to conduct the questionnaire. During the online questionnaire, subjects were first asked to answer some specific questions about the proposed brand. These questions were used to generate a baseline about their level of customer satisfaction and customer loyalty towards the brand. Thereafter the subjects were randomly assigned to a condition (immediate reward or delayed reward scheme). During the manipulation, a new loyalty program of the particular brand was proposed which is congruent with the assigned condition. Thereafter, the subjects were again asked to answer some questions about their level of customer satisfaction and customer loyalty towards the brand and some questions about the proposed loyalty program.