Economic Confidence and the Relationships between
Customer Equity Drivers and Loyalty Intentions:
A Study in the Dutch Banking Sector.
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Economic Confidence and the Relationships between
Customer Equity Drivers and Loyalty Intentions:
A study in the Dutch banking sector.
Written by: Lisette de Vries.
Department of Marketing, Master thesis. Completion date: April 26th, 2010. Address: Korreweg 79a,
9714 AD Groningen. Telephone: +0031(0)6-12613611 Email: lisettede_vries@hotmail.com
Supervised by: Prof. dr. Peter C. Verhoef Dr. Thorsten Wiesel
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MANAGEMENT SUMMARY
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PREFACE
This thesis is the last part of the MScBA Marketing Research. I had the opportunity to assist in setting up and conducting a large field study for a project named the Customer Performance Awards1. During this project I learned how to conduct a large scale survey and experienced cooperation between the three parties. I have used the data that has been gathered with this research for this master‟s thesis.
Thanks to my two supervisors, Prof. Dr. Peter C. Verhoef and Dr. Thorsten Wiesel, I have been able to write this thesis. I would like to thank them for their advice and support during the time I have worked with them, which I enjoyed very much.
Lisette de Vries.
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TABLE OF CONTENTS
MANAGEMENT SUMMARY ... 3
PREFACE ... 4
TABLE OF CONTENTS ... 5
1.INTRODUCTION... 6
2.CONCEPTUAL FRAMEWORK AND HYPOTHESES ... 10
2.1LOYALTY INTENTIONS ... 11
2.2VALUE EQUITY ... 11
2.3BRAND EQUITY ... 13
2.4RELATIONSHIP EQUITY ... 14
2.5RELATIONSHIPS BETWEEN CUSTOMER EQUITY DRIVERS ... 16
2.5.1 Value Equity and Brand Equity ... 16
2.5.2 Value Equity and Relationship Equity ... 17
2.5.3 Brand Equity and Relationship Equity ... 18
2.6MODERATING EFFECTS OF ECONOMIC CONFIDENCE ... 19
3. METHOD ... 22
3.1MEASUREMENT SCALES ... 22
3.2RELIABILITY AND VALIDITY OF MEASUREMENT SCALES ... 23
3.3REGRESSION ANALYSIS ... 24
4. RESULTS ... 25
4.1DESCRIPTIVE STATISTICS ... 25
4.2RESULTS RELIABILITY ANALYSIS ... 26
4.3RESULTS FACTOR ANALYSIS ... 27
4.4RESULTS REGRESSION ANALYSES ... 28
4.4.1 Relationships between Customer Equity Drivers and Loyalty Intentions ... 28
4.4.2 Moderating Effects of Economic Confidence ... 30
5.DISCUSSION OF RESULTS ... 35
5.1CUSTOMER EQUITY DRIVERS ... 35
5.2ECONOMIC CONFIDENCE ... 35
6. MANAGERIAL IMPLICATIONS ... 37
7. FUTURE RESEARCH ... 38
REFERENCES ... 39
APPENDIX ... 45
Appendix 1: Measurement and latent variables ... 45
Appendix 2: Final measurement and latent variables (deleted items) ... 46
Appendix 3: Rotated factor matrix for relationship equity ... 47
1.INTRODUCTION
With increasing pressure on companies to increase firm value and attain constantly higher financial stock returns, the emphasis of companies goes to finance and accounting departments. Not surprisingly, it still is the easiest way to evaluate businesses in terms of money (Lehmann, 2004). Also companies need to market good products and services constantly. Lots of money will be pumped into marketing programs such as advertising, increasing brand awareness, and loyalty programs. But what is actually the output of these marketing actions? It is necessary that there are metrics which can make marketing more accountable and put marketing back on the agenda of companies next to finance and accounting. Marketing does have an impact on the behaviour of consumers2 which ultimately leads to higher firm value and is not only a cost department. It is important that marketing actions will be rated on long-term performance measures, such as brand equity and the value of customers (Lehmann, 2004). By the development of long-term marketing performance measures marketing managers will be able to show what their inputs pay off.
Although many companies nowadays have difficulties with linking marketing actions to customer attitudes and customer behaviour, Gupta and Zeithaml (2006) state clearly that “customers are the lifeblood of any organization”. Because, without customers the company will not sell anything, earn no revenue, and make no profits. Several researchers have tried to make a link between marketing actions and (customer) performance measures in order to make marketing more accountable.
There are different methods of making marketing more accountable. One way is to see customers as assets for the company (Berger et al. 2002; Bolton, Lemon, and Verhoef, 2004). When these assets (customers) will be managed systematically, a firm can identify the most appropriate marketing actions to acquire, maintain, and enhance customer assets and thereby maximize financial returns (Berger et al. 2002). Bolton, Lemon, and Verhoef (2004) developed the Customer Asset Management of Services (CUSAMS) framework in which they identified how marketing instruments influence purchase behaviour of consumers. They use the relationship length, depth and breadth as determinants of customer lifetime value (CLV). CLV is a way to determine the value of the customers to the company. It is the present value of the net cash flows the firm expects to receive from the customer over the lifetime with the company (Berger and Nasr, 1999), thereby focusing on long-term profits
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7 instead of short-term profits (Gupta and Zeithaml, 2006). When a firm knows the CLV‟s of individual customers it can better select profitable customers, make better customer segmentation, and allocate marketing resources more effectively (Kumar, Lemon, and Parasuraman, 2006), which ultimately improves the financial performance of a firm (Gupta and Zeithaml, 2006). Furthermore, customer retention or lifetime duration is one of the most important drivers of CLV (Reichheld and Sasser, 1990; Gupta and Zeithaml, 2006). At the aggregate level, customer equity is the total of the discounted lifetime values summed over all current and potential customers of a firm (Rust, Lemon and Zeithaml, 2004).
When looking from the perspective of the consumer, the term customer value is an interesting concept (Woodruff, 1997; Parasuraman, 1997). Customer value is about considering what customers want, and how they value the offerings from a company (Woodruff, 1997). Parasuraman (1997) states customer value is a customer‟s perceived preference for and evaluation of the product and consequences of the product when consumers use it. The concepts of customer value and customer satisfaction are correlated, as they both describe evaluative judgements about product experiences (Woodruff, 1997).
8 metrics to customer lifetime value and projected financial returns. Companies can make marketing actions much more accountable by using this framework.
Vogel, Evanschitzky, and Ramaseshan (2008) relate customer equity drivers to customer loyalty intentions and ultimately to future sales. They state that although customer lifetime value is a valuable measure, in practice companies find it much more difficult to use and many calculations are needed to determine CLV. Customer loyalty intentions and future sales are less complicated metrics to use. They find that customer equity drivers indeed have a positive influence on customer loyalty intentions and future sales.
What is missing in the current literature is that none of the authors discussed above, examine relationships between the customer equity drivers. Although, Vogel, Evanschitzky, and Ramaseshan (2008) mention briefly that customer equity drivers are not mutually exclusive and Lemon, Rust, and Zeithaml (2001) state that “these [customer equity]3 drivers work independently and together”, they do not explain how they work together and only analyze the drivers independently. Furthermore, Rust, Lemon, and Zeithaml (2004) mention it is important for a company to identify in which customer equity driver it is best to invest in. They take into account only one customer equity driver at once, while it seems logical to invest in different customer equity drivers at the same time. So, focusing on two (or three) customer equity drivers simultaneously might have larger effects on firm growth or loyalty than focusing on these separately. For example, when the brand is perceived as strong, quality of the offerings is perceived highly, which allows the company to ask a higher price (Hoeffler and Keller 2003; Zeithaml, Berry, and Parasuraman 1996). Consumers sometimes feel as if they have a strong relationship with a brand, especially when they can identify with the brand and it contributes strongly to the self (Fournier, 1998). So, when focusing on only one customer equity driver at the time, additional or synergy effects of the customer equity drivers can be missed. Interaction effects between the customer equity drivers need to be taken into account.
Because of the economic downturn and recent developments in the banking industry, it is interesting to investigate the moderating effects of consumer confidence in the economy. Research (from CBS) has already shown that consumers have less confidence in the economy and buy less, but save more. Differences in loyalty intentions between consumers with high
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9 and low economic confidence are interesting to investigate. It might be the case that value equity becomes more important as consumers watch prices when there is a economic downturn and confidence in the economy is low (Leeflang and Van Raaij, 1993). During such times, companies may focus more on the value of their offerings, and for example focus less on increasing brand awareness.
In this research I will answer the following questions:
1. What are the relationships between customer equity drivers and loyalty intentions? 2. Do there exist significant interaction effects (synergistic effects) between the customer
equity drivers, and how are these related to loyalty intentions?
3. Does one of the customer equity drivers (value equity, brand equity, or relationship equity) become more important for keeping customers loyal in times when economic confidence is low?
The contribution of this research to the literature in marketing consists of answering questions two and three, because these issues have, to my knowledge, not yet been investigated. Therefore, the answers of these questions are interesting for researchers, both in the field of marketing as well as more general economic fields. The research is also useful for managers at banks, because more efficient ways of approaching consumers under different circumstances (during periods of low or high economic confidence) will be available.
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2.CONCEPTUAL FRAMEWORK AND HYPOTHESES
The conceptual framework used for this research is shown in figure 1. Value equity, brand equity and relationship equity are positively related to loyalty intentions of consumers. Value equity is about perceptions of the consumer about the product or service4, prices and quality of the services. Brand equity constitutes of customer perceptions about the brand. Perceptions of customers about their relations with the company are captured in relationship equity. When perceptions of consumers are high, they value the company, its services, the brand, and relationships with the company as high, which leads to satisfaction. Satisfaction results in loyalty or loyalty intentions (Rust, Lemon and Zeithaml, 2004; Vogel, Evanschitzky, and Ramaseshan, 2008). Loyalty (intentions) is important to measure as there is a positive relationship between loyalty and profitability of the firm (Reichheld and Sasser, 1990).
Figure 1: Conceptual Framework
Because of the economic downturn, it might be interesting to investigate the moderating effects of consumers‟ confidence in the economy. Research (from CBS) has already shown that consumers have less confidence in the economy and buy less, but save more. When consumers have low confidence in the economy, relationships between the customer equity drivers and loyalty intentions might be changed.
On the next pages I will explain the variables in the model, and I will describe in more detail the hypothesized relations between variables.
4 In this research mainly the term services instead of products will be used, since the research has been conducted in the banking sector.
11 2.1LOYALTY INTENTIONS
Much research has been done about customer loyalty in the field of marketing. According to Zeithaml et al. (1996) loyalty can mean different things; consumers‟ preference for a company over other companies, consumers continuing to buy from the company, or by increasing business with it in the future. There exist a difference between attitudinal loyalty and behavioural loyalty. Attitudinal loyalty is a subjective measure of loyalty of the customer itself, whereas behavioural loyalty is about the buying behaviour (repeated purchases) of the customer (Reinartz and Kumar, 2002).
There are some contradictions in literature about the effects of loyalty on profitability. Reichheld and Sasser (1990) find that customer retention, or loyalty, has a strong positive effect on profitability. As a customers‟ relationship with the company becomes longer, profits rise incredibly. Retaining customers can be achieved by making sure there are no defections in service quality and to outperform competition. Also, companies can ask higher prices for long-term customers, can serve them more efficiently, and long-term customers engage in a lot of positive word-of-mouth communication which is free advertising for the company (Reichheld and Sasser, 1990). Reinartz and Kumar (2002) found that the relationship between loyalty and profitability is much subtler and weaker than stated above. They found that customers who are customers for a long time are not cheaper to manage than short-term customers, and some long-term customers are even more expensive to serve. Also, long-term customers in B2B industries often know their value to the company and ask for price discounts when purchasing high volumes, but similar results have been found in B2C industries. Loyal customers did engage in more word-of-mouth activities, however, they did more when they were attitudinal loyal (Reinartz and Kumar 2002). So, companies do not only need to look at the loyalty of customers, but also to the frequency of purchase and the money they spend, which better identify the relationship between loyalty and profitability.
In this research consumers are asked to identify their loyalty intentions. This is something different than measuring observed loyalty, as loyalty intentions and actual behaviour are not always equal. However, as Vogel, Evanschitzky, and Ramaseshan (2008) showed in their research, loyalty intentions might be a good predictor of future sales.
2.2VALUE EQUITY
12 (2004) as consumers‟ objective assessment of the utility of a brand based on perceptions of what is given up for what is received. In other words, what receive consumers for their money? Value equity can be measured by perceptions of consumers about quality and price of a service, and convenience in using and buying. Perceived quality can be defined as the consumers‟ judgments about a service‟s overall excellence or superiority (Zeithaml, 1988). So, this is different from the actual quality of a product or service. Consumers derive (emotional) benefits from specific intrinsic and extrinsic product/service attributes, which differ per person.
Price can be used as an indicator for quality as well; a higher price means higher quality. The variable price is what the consumer gives up to obtain the product or service. Often there is a difference between the objective price and perceived price; how the consumer experiences the price of a product or service (Zeithaml, 1988). Consumers do not always pay attention to prices when buying products or services, but attention to prices is likely to be greater for services. Monetary price is often not the only price paid to obtain a product or service. Also search costs, time costs, and physic costs play a role in the buying process (Zeithaml, 1988).
Value equity appears to be most important for consumers in markets where products/services are differentiated. By changing the product or service a company can attain a competitive advantage (Rust, Lemon and Zeithaml 2001). It is likely that in the banking services context, where services can be differentiated or customized per customer, value equity might play a large role for consumers. Also in complex decision making contexts value equity plays a role. When a company can make it easier for a consumer to make a decision and/or to buy a product, value equity will increase.
13 When value equity is high, the quality, price and convenience aspects of the service meet expectations of the customer, which leads to satisfaction and loyalty intentions. Also, when value equity or perceived value is low, customers would be more inclined to switch to another company, which means a decrease in customer loyalty (Lin and Wang, 2006; Keaveney, 1995). Rust, Lemon, and Zeithaml (2004) and Vogel, Evanschitzky, and Ramaseshan (2008) state and test that value equity has a positive effect on loyalty intentions. Therefore:
H1: Value equity is positively related to loyalty intentions.
2.3BRAND EQUITY
Brands become more and more important and are one of the most important intangible assets for companies (Keller and Lehmann 2006). For customers brands state something about the level of quality, and simplify the choice for a certain product, thereby reducing risk. According to Keller (2003) brand equity is defined as the consumer‟s awareness and image of the brand. There are three perspectives of looking to the brand, from the customer perspective, the company perspective and the financial perspective (Keller and Lehmann 2006). When looking from the customer perspective, brand equity is based on associations with the brand, above the attributes of the offering. Yoo and Donthu (2001) define this as consumers‟ different response between a focal brand and an unbranded product or service when both have the same level of marketing stimuli and attributes. The difference in response may be caused by the brand name. Therefore, brand equity from the company perspective is the additional value generated because of the brand name. This additional value would not have been made with an equivalent unbranded product. Last, brand equity from the financial perspective is the value of the brand on the balance sheet. In this research the focus will be on the customer perspective; the value customers derive from the brand. Because, in the end it are the consumers who decide with their purchases which brands have more equity than other brands (Hoeffler and Keller 2003).
14 Lemon, Rust, and Zeithaml (2001) state that corporate ethics is also an important aspect of brand equity. Corporate social responsible activities influence customer perceptions about the brand and the company. CSR initiatives from companies have directly or indirectly effects on consumer product responses, consumer-company identification (Sen and Bhattacharya 2001), consumers‟ donations to NGO‟s and consumers‟ product attitude (Luo and Bhattacharya, 2006).
Strong brands have different advantages, such as more effective advertising and promotion, and differentiation (the ability of the brand to stand apart from competitors (Mizik and Jacobson 2008)) (Hoeffler and Keller 2003). Consumers notice information about strong brands more easily and pay more selective attention, so that advertising may create favourable associations (Hoeffler and Keller 2003). Strong brands are perceived as qualitatively better and consumers prefer them more than other brands. Furthermore, as Yoo and Donthu (2001) summarize, a product‟s brand equity delivers value to the firm by positively affecting future profits and long term cash flow, willingness of consumers to pay higher prices, stock prices, sustainable competitive advantage and marketing success. Also, brand equity delivers value to consumers because consumers can more easily interpret information about the brand, make more confident decisions and are more satisfied. Vogel, Evanschitzky, and Ramaseshan (2008) determined that brand equity has a positive impact on customers‟ loyalty intentions.
When brand equity is high, when consumers think the brand is strong, unique and innovative, they prefer the focal brand over other brands and will be more inclined to buy the focal brand (Vogel, Evanschitzky, and Ramaseshan 2008). Vogel, Evanschitzky, and Ramaseshan (2008) also test the relationship between brand equity and loyalty intentions and find a positive effect, therefore:
H2: Brand equity is positively related to loyalty intentions.
2.4RELATIONSHIP EQUITY
15 companies and these find several ways to increase relationships with customers. The most important ways are loyalty programs, special treatment programs, and knowledge building programs (Lemon, Rust and Zeithaml, 2001). Furthermore, Sääksjärvi et al. (2007) define relationship marketing as “a process of identifying and establishing, maintaining, enhancing, and when necessary terminating relationships with customers and other stakeholders, at a profit, so that the objectives of all parties involved are met, where this is done by a mutual giving and fulfilment of promises.”
Rust, Lemon and Zeithaml (2004) define relationship equity as the customer‟s assessment of interactions with the brand and to stick with the brand, above and beyond objective and subjective assessments of the brand. This would depend on salesperson and serviceperson relationships, loyalty programs, customer communities/networks and knowledge of the customer. Only focusing on value equity (good products) and brand equity (strong brand) is not enough to keep the customer loyal (Lemon, Rust and Zeithaml, 2001).
An important aspect of building relationships is the importance to generate customer commitment (Sääksjärvi et al. 2007). Moorman, Zaltman and Deshpandé (1992), define commitment as “an enduring desire to maintain a valued relationship”. Morgan and Hunt (1994) take about the same approach and state that the committed party is willing to work on the relationship to maintain and endure it infinitely. A distinction can be made between affective and calculative commitment. Calculative commitment is a rational commitment based on product benefits. Affective commitment refers to the emotional involvement a consumer has with a company. Another construct related to commitment is trust in the relationship. Trust exists when the consumer has confidence in the reliability and integrity of the company (Morgan and Hunt, 1994). Commitment and trust are very important for successful relationship marketing. Verhoef (2003) showed in a financial services context, that affective commitment has a direct effect on relationship maintenance or retention.
If perceived relationship equity is high, customers believe they are well treated and feel a strong connection with the company. Rust, Lemon, and Zeithaml (2004) showed that relationship equity has a negative effect on the switching behaviour of consumers. Also Vogel, Evanschitzky, and Ramaseshan (2008) examined there is a positive effect between perceived relationship equity and loyalty intentions, therefore:
16 2.5RELATIONSHIPS BETWEEN CUSTOMER EQUITY DRIVERS
In this paragraph I will discuss relevant literature regarding value equity, brand equity and relationship equity in order to come up with sound reasoning about relationships between these constructs. As Vogel, Evanschitzky, and Ramaseshan (2008) mentioned briefly that customer equity drivers are not mutually exclusive and Lemon, Rust and Zeithaml (2001) stated that “these drivers work independently and together”, I will investigate how the drivers work together and reinforce each other.
2.5.1 Value Equity and Brand Equity
Strong brands are perceived as qualitatively better and consumers prefer them more than other brands (Hoeffler and Keller 2003). Furthermore, a product‟s brand equity delivers value to the firm by positively affecting future profits and long term cash flow, willingness of consumers to pay higher prices, stock prices, sustainable competitive advantage and marketing success (Yoo and Donthu 2001). So, when a consumer perceives a brand as strong, the company can ask a higher price for the branded product. This relation has also been found by Swait et al. (1993); consumer reservation prices are higher for high quality brands, which allow them to charge higher prices. Also, a higher price often has an association with higher quality. Companies offering superior service quality can ask higher prices for their offerings (Zeithaml et al, 1996). Furthermore, a strong brand (for example A-brand) also has intensive distribution, which means that consumers may rate convenience in buying and using as high; higher than for example for a B-brand.
Lai, Griffin, and Babin (2009) posit that a positive corporate image, or brand image, has a positive effect on perceived value. According to Hu, Kandampully, and Juwaheer (2009) the image of the firm, or image of the brand, is determined by service quality, customer satisfaction and perceived value. A company will have a strong [brand] image if customers believe they are getting high value when buying from that company.
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H4: When brand equity is perceived highly, value equity becomes of less importance to
consumers for their intention to stay loyal (i.e. negative interaction effect of brand equity and value equity).
2.5.2 Value Equity and Relationship Equity
When consumers are satisfied with the company‟s offerings, they might feel committed to the company (Sharma and Patterson, 2000). Wuyts, Verhoef and Prins (2009) state, that when a company and a consumer are in a good relationship objective measures, such as value, become less important. On the other hand, Reinartz and Kumar (2000) mention that long-term customers are more price sensitive than short-term customers and therefore pay lower prices. But Reichheld and Sasser (1993) posit that long-term consumers pay higher prices than short-term consumers. It is not straightforward whether consumers in a long-short-term relationship with the company pay less attention to prices and would like to pay for the less risk they are exposed to, since they are more familiar with the company‟s offerings and brand(s). Alternatively, consumers might be more inclined to negotiate about price, because they know how to value the products and know their own value to the company, which gives customers a strong negotiation position. An interesting finding from Jones et al. (2000) is that although consumers are not satisfied, for example with the company‟s offerings, they stay with the company because of strong interpersonal relationships. In that case, relationships are more important than value for the consumer.
18 The discussed theory suggests that when the strength of the relationship between the company and consumers increases, value equity might become less important to consumers and they give less attention to value. This leads to the following hypothesis:
H5: When relationship equity is perceived as high, the relationship between value equity and
loyalty intentions will be weakened (i.e. negative interaction effect of relationship equity and value equity).
2.5.3 Brand Equity and Relationship Equity
Brand equity and relationship equity are defined as separate constructs, but is it possible for a consumer to have a relationship with the brand? To engage in a relationship there has to be interdependency between the partners. As the brand is not human, this seems quite difficult. However, it appears that consumers do not have difficulties with assigning personalities to brands or see brands as if they had human characters (Fournier, 1998). Also the spokesperson of an advertising or commercial can fit the brand that well that consumers identify with that person as being the brand. The acting of the brand constitutes of the set of marketing actions which are executed every day (Fournier, 1998). Fournier (1998) finds in her research that people who have a strong relationship with the brand, have affective feelings, such as love, for the brands. This appears especially to be the case when the brand delivers a strong contribution to the self. When people can identify with the brand, feel like they cannot live without it (make-up, perfume), and also when using it often, when there is much interdependence (Fournier, 1998). Consumers engage in certain types of relationships with brands, similar to personal and intimate relations they form with other people (Esch et al. 2006; Aggarwal, 2004), which is also called emotional loyalty with the brand (Rozanski, Baum, and Wolfsen, 1999). This theory can be seen clearly in everyday live. Many fan sites or clubs for different products or brands (some extreme examples: Harley Davidson, MacIntosh, VW Beetle) have been set up. Moreover, a strong relationship or connection with the brand strongly predicts how often the brand was purchased in the past and will be purchased in the future, which corresponds to the intention to stay a customer from the company (Esch et al. 2006).
In conclusion I can state that when consumers value the relation highly, the brand becomes of more importance. Or, when consumers attach high value to the brand, it becomes important to them to engage in a valuable relationship with the company.
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H6: When relationship equity (brand equity) is perceived as high, the relationship between
brand equity (relationship equity) and loyalty intentions will be strengthened (i.e. positive interaction effect of relationship equity and value equity).
2.6MODERATING EFFECTS OF ECONOMIC CONFIDENCE
There are several things that could harm relationships between customers and the company and also things that will change perceptions of consumers about brands and services of firms. Often this will be caused by triggers. A trigger is a factor or an event that changes the basis of a relationship (Roos, Edvardsson, and Gustafsson, 2004). In 2009 this was certainly the case, the economy was in a recession (already started at the end of 2007) and many people lost their jobs. Customers‟ confidence in the economy was very low and consumption decreased (www.cbs.nl). In the banking sector, several banks suffered from bad performance, and some went bankrupt or merged. Because of these triggers, especially apparent in the banking industry, I will investigate what the effects of consumer confidence in the economy are on the relationships between customer equity drivers and loyalty intentions.
20 phones and beauty care (Zurawicki and Braidot, 2005). Allenby, Jen, and Leone (1996) showed that consumers‟ confidence in the economy substantially influences retail fashion sales. Also, shopping habits alter; self-service, discount stores and large hypermarkets become more popular during recession years (Zurawicki and Braidot, 2005). Since all consumers spend less and alter shopping habits during a recession, I assume that loyalty intentions of consumers become lower when confidence in the economy is low. Consumers might search more for valuable products and services, and might feel less committed to one specific company, which decreases loyalty. Based on this reasoning I propose the following hypothesis regarding a main effect of economic confidence on loyalty intentions:
H7a: Consumers with low economic confidence will have lower loyalty intentions than
consumers with high economic confidence.
Furthermore, consumers tend to buy more private labels, imported, low-priced brands, B-brands, and unbranded products (Leeflang and Van Raaij, 1993). The popularity of private or local labels during recessions has been acknowledged by several authors (Nandan and Dickinson, 1994; Lamey et al., 2007; Zurawicki and Braidot, 2005). When the economy recovers, consumers will buy national brands again (Nandan and Dickinson, 1994; Lamey et al., 2007), although this increase is asymmetrical. This means that the private label wins in importance relative to the national brands (Lamey et al., 2007). Zurawicki and Braidot (2005) find also that during recessions consumers go for a favourable price-to-quality ratio, durability and watch for cheaper prices (Ang, Leong, and Kotler, 2000).
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H7b: When economic confidence is low, the relationship between value equity and loyalty
intentions will be strengthened.
H7c: When economic confidence is low, the relationship between brand equity and loyalty
intentions will be weakened.
H7d: When economic confidence is low, the relationship between relationship equity and
loyalty intentions will be strengthened.
The behaviour of consumers appears to be influenced by income during a recession. When incomes decrease as a cause of the recession, consumers tend to cut expenses on telephone, car, clothing, sports, hobbies and holidays. When incomes increase again, consumers will spend more on clothing, food, sports, hobbies and holidays. Some product categories which are not affected by fluctuations in income are utilities, insurance, study costs and pets (Leeflang and Van Raaij, 1993). Additionally, Zurawicki and Braidot (2005) found that all consumers consumed less, in almost all product categories. But, it appeared that during a recession consumers with higher incomes decreased consumption less and in less categories than consumers who fall in the middle income groups. Therefore, it can be assumed that consumers with higher incomes have higher loyalty intentions than consumers with lower incomes during periods of low confidence. Furthermore, consumers react differently on prices during a recession. Low-income households tend to buy cheaper and lower-quality products or buy less. High-income households, on the other hand, buy higher quality products, which are generally more expensive and stand for higher durability (Leeflang and Van Raaij, 1993). This leads to the last hypothesis:
H7e: During a recession (economic confidence is low), consumers with higher incomes will
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3. METHOD
In this chapter I will discuss how the data of this research are obtained, what the sample looks like, what measurement scales are used and whether these are reliable, and how the stated hypotheses will be tested.
First, a pre-test of 27 respondents has been conducted to check wording and understanding of the interview questions about banks. None of the respondents had comments on the questions or problems with filling in the questionnaire. Also distribution (answers range from 1 to 7, or from 0 to 100) and face validity of the items appear to be good.
Second, a survey has been conducted under 407 consumers of banks in the summer of 2009. Only 393 of them filled in the questionnaire completely. There are in total 584 observations, as some consumers evaluated more than one bank. The respondents needed to evaluate banks they are a customer of. Each customer evaluates a maximum of three banks.
3.1MEASUREMENT SCALES
I will discuss which measurement scales have been used to measure value equity, brand equity, relationship equity, loyalty intentions, and economic confidence. As said, these questions have been tested on wording and understanding in a pre-test.
To measure value equity perceived price, price to quality ratio, and convenience in buying and using are used in this research. In total four items are used, which are measured on 7-point Likert scales ranging from 1 = much too low, 7 = much too high or 1 = very strongly disagree, 7 = very strongly agree. To measure brand equity, metrics about the strength, uniqueness, innovativeness and corporate social responsibility of brands. These are measured on a 7-point Likert scale ranging from 1 = very strongly disagree, 7 = very strongly agree. Relationship equity is based on dialogue/communication, intimacy/passion and commitment between the customer and the firm. These will be measured on a 7-point Likert scale ranging from 1 = not at all, 7 = to a very large extent.
23 The measurement questions for economic confidence have already been discussed in the previous chapter. These questions will be measured on a 7-point Likert scale ranging from 1 = worse, 4 = the same, 7 = better.
The measurement items for value equity, brand equity, relationship equity, loyalty intentions, and economic confidence can be found in appendix 1.
3.2RELIABILITY AND VALIDITY OF MEASUREMENT SCALES
To assess the reliability and validity of the measurement items for value equity, brand equity, relationship equity, and economic confidence reliability analysis and a factor analysis will be used.
Reliability analysis can be used to check internal consistency of the items, which is measured with Cronbach‟s alpha (α) (Lattin, Carroll and Green, 2003). The alpha measures the extent to which the items or variables measure the same thing, so whether they form one single latent construct. Cronbach‟s alpha ranges from 0 to 1, and the higher the α, the greater the inter-item correlation and thus the internal consistency of the items (Lattin, Carroll and Green, 2003). The value of Cronbach‟s alpha needs to exceed 0,7 in order to obtain good scale reliability and internal consistency.
Factor analysis (FA) will be used to define the underlying structure among the variables in the analysis and to determine which questions form the identified constructs best (Hair et al. 2006). More specific, common factor analysis (principal axis factoring) will be used in this research, as the goal is to identify the latent constructs in the data. Rotation method Varimax, which is an orthogonal rotation method, will be used for this research. When using an orthogonal rotation method the estimated factors will have no correlation with each other. This might be useful for conducting additional analyses with the factors as independent variables, such as regression analysis, because multicollinearity will be no issue (Hair et al., 2006).
24 whether an underlying structure in the data exists and the statistical issue is about whether there is enough correlation between the variables to conduct an appropriate factor analysis. Tests are the Bartlett test of sphericity and the Kayser-Meyer-Olkin (KMO) measure, which should be above 0.6. Items that load highest on the factors/constructs will be the best items to use for the research. Items need to load at least 0.3, but better would be above 0.5 (Hair et al., 2006).
3.3REGRESSION ANALYSIS
Value equity, brand equity and relationship equity will be used as independent variables in the regression analysis, with the logit of loyalty intentions as dependent variable. The customer equity drivers will be computed by saving the factor scores from the factor analysis. Interaction effects need to be included, which might cause multicollinearity, but by saving orthogonalized factor scores this is not a problem anymore (Hair et al., 2006). Because the variable „loyalty intentions‟ consists of percentages, and only positive values and values between zero and one are valid outcomes of the regression, multinomial logistic or logit regression need to be conducted (Hair et al. 2006). However, the relationships between loyalty intentions and the independent variables can also be modelled linearly by taking the logits, natural logs of the odds, of loyalty intentions. The formula to be estimated will be: 𝑙𝑜𝑔𝑖𝑡 𝐿𝐼 = ln 1−𝐿𝐼𝐿𝐼 = 𝛼 + 𝛽1𝑉𝐸 + 𝛽2𝐵𝐸 + 𝛽3𝑅𝐸 + 𝜀 (1)
Where LI (loyalty intentions) is the probability of staying loyal to a bank and VE is „value equity‟, BE is „brand equity‟ and RE is „relationship equity‟.
25
4. RESULTS
In this chapter the results of the analyses will be discussed. First, I will give a general description of the population and the data of the survey. Second, I will discuss the results of the factor analysis and determine which items measure the underlying constructs best. Furthermore, several regression analyses are conducted to determine which model estimates the relations between customer equity drivers and loyalty intentions best.
4.1DESCRIPTIVE STATISTICS
Respondents received a monetary amount for filling in and completing the questionnaire. The number of respondents was 407, but the number of complete filled in questionnaires is 393. These 393 respondents have been used for the analyses. The 393 respondents evaluated in total 584 banks, so 584 observations can be used for conducting analyses (data is aggregated over banks).
Of the respondents are 175 men, which is 44,5% and 218 women, which is 55,5% of the respondents. The average age is 41,72 years, and ranges from 15 till 94 years old. Furthermore, the respondents come from all regions of the Netherlands.
In table 1 means and standard deviations of the measurement items can be found. These values are based on the 7-point Likert scales.
Table 1: Means and standard deviations measurement items
Variable Mean Std. Deviation Variable Mean Std. deviation
26 All the answers on the questions are ranging from 1 to 7. Standard deviations are quite large (most above 1), which means that respondents answered quite differently. Also the means are around 3 or 4, which indicates that none of the items is evaluated very low (which would be very low mean, low standard deviation), or very high (which would be very high mean, low standard deviation). The average score for loyalty intentions is 50%, which means that consumers indicate there is a 50% change they will do business with the same bank again.
4.2RESULTS RELIABILITY ANALYSIS
Reliability analyses have been conducted over the latent constructs (value equity, brand equity, relationship equity, and economic confidence), which are reported in table 2.
Table 2: Results reliability analysis Item Cronbach’s alpha whole
construct
Cronbach’s alpha if item deleted
Value equity VE1 0,667 0,764
VE2 0,604
VE3 0,449
VE4 0,481
Brand equity BE1 0,889 0,875
BE2 0,871 BE3 0,868 BE4 0,855 BE5 0,856 Relationship equity Intimacy/passion RE1 0,935 0,925 RE2 0,924 RE3 0,922 Communication/dialogue RE4 0,932 RE5 0,934 RE6 0,934 RE7 0,923 Commitment RE8 0,924 RE9 0,923 Economic confidence (ICS) EC1 0,699 0,662 IEC EC2 0,614 EC3 0,603 IWB EC4 0,625 EC5 0,683
27 Also in the correlation table (in SPSS output5) can be seen which item has the lowest correlation with the other items. A low correlation would indicate that this item measures something else, and does not fit with the latent construct. Based on these analyses one item will be deleted, which is: “VE1. How would you rate the price of this product/service from this company?”. This variable has a very low correlation (all below 0.2) with the other value equity items and Cronbach‟s alpha will increase when deleting this item. The remaining items for value equity can be found in appendix 2. All the other items remain in the analysis, since deleting these would not improve Cronbach‟s alpha (see table 2).
4.3RESULTS FACTOR ANALYSIS
A factor analysis has been conducted to check whether the pre-specified constructs also appear as factors in the data.
First, it will be checked whether factor analysis indeed is statistically appropriate. The Bartlett‟s test of sphericity is significant, which means that the correlation matrix of the items is not an identity matrix, which makes factor analysis appropriate, since correlations between the items exist. The Kayser-Meyer-Olkin (KMO) measure is 0,923 which is far above the critical value of 0,6. These results indicate that factor analysis is appropriate in this case (Hair et al. 2006).
Factor analyses for the separate constructs have been conducted and it appears that the items indeed form one construct. For brand equity however, it appeared that the CSR items form a separate factor, therefore I excluded those two items from the analysis. The remaining items for brand equity can be found in appendix 2. Furthermore, relationship equity appears to consist of a commitment construct and a dialogue/communication construct (see appendix 3). But, since the largest construct for relationship equity consists of seven items, I will exclude the dialogue and communication items from the further analysis.
After the separate factor analyses a total factor analysis with all variables has been conducted (see appendix 4), with exclusion of five items, namely two items from CSR, the price item from value equity, and the two communication items from relationship equity. As the number of constructs is known beforehand, I indicate in SPSS that I will extract three factors (a priori criterion), namely for relationship equity, brand equity and value equity6. For these three factors the total variance explained is 69% and the variance explained per factor is
5 Correlation table is too large to include. All SPSS output is available by the author.
28 more than 6,7%. The eigenvalue criterion cannot be met, because the eigenvalues of the factors are not all greater than 1, only the first two are (Hair et al., 2006). Communalities are all high, which means that the fit of the factors is good. The rotated factor loadings and measurement items for the constructs can be found in appendix 4. It can be seen in appendix 4 that the items of the constructs all load high on their own factors.
4.4RESULTS REGRESSION ANALYSES
In this paragraph I will first identify how the customer equity drivers are related to loyalty intentions. Second, I will investigate the relationships between the customer equity drivers by estimating the interaction effects of these variables, and relate these to loyalty intentions. After that, I will test whether economic confidence moderates the relationships between customer equity drivers and loyalty intentions.
4.4.1 Relationships between Customer Equity Drivers and Loyalty Intentions
In order to test hypotheses 1, 2 and 3, equation 1 has been estimated. The constructs for value equity, brand equity, and relationship equity are computed by saving the factor scores of the factor analysis with orthogonal rotation, which makes the variables uncorrelated. These variables have been used as independent variables in the analysis. The logit transformation of loyalty intentions is the dependent variable. The formula (from chapter three) to be estimated is:
𝑙𝑜𝑔𝑖𝑡 𝐿𝐼 = ln 1−𝐿𝐼𝐿𝐼 = 𝛼 + 𝛽1𝑉𝐸 + 𝛽2𝐵𝐸 + 𝛽3𝑅𝐸 + 𝜀 (1)
To investigate the interaction effects of value equity, brand equity and relationship equity on loyalty intentions (hypotheses 4 to 6), a new model has been estimated. The model to be estimated is shown in equation (2):
𝑙𝑜𝑔𝑖𝑡 𝐿𝐼 = 𝛼 + 𝛽1𝑉𝐸 + 𝛽2𝐵𝐸 + 𝛽3𝑅𝐸 + 𝛽4 𝑉𝐸 ∗ 𝐵𝐸
+𝛽5 𝑉𝐸 ∗ 𝑅𝐸 + 𝛽6 𝐵𝐸 ∗ 𝑅𝐸 + 𝜀 (2)
29 The first model is significant as a whole (F-value 63,613), which means that at least one beta in the estimation will be significantly different from zero. The F-value of the second model is 31,913, which makes the model also significant as a whole.
Table 3: Estimated coefficients linear regression on logit of LI I. Model equation 1 II. Model equation 2
b (unstand.) b (unstand.) Constant (β0) -0,294* -0,292* VE (β1) 0,314* 0,306* BE (β2) 0,390* 0,407* RE (β3) 0,499* 0,496* VE * BE (β4) - -0,016 VE * RE (β5) - -0,066 BE * RE (β6) - 0,049 R2 0,278 0,280 Adj. R2 0,274 0,271 F-value Δ R2 - 0,52
* p-value < 0,01; ** p-value < 0,05; *** p-value <0,10
The R2 of model I is 0,278 and the adjusted R2 is 0,274. These R2 values approach each other closely. The adjusted R2 is a variable which adjusts for the number of parameters in the model. This number is not very high; this might be caused by the gap between perceptions of consumers and their actual behaviour. The R2 value of model II is 0,280 and the adjusted R2 0,271. The R2 values of the second model are only slightly higher, and none of the interaction effects is significantly different from zero. Therefore, model II is not better than model I. Whether model II is better than model I can also be done statistically by computing whether the change in R2 value is significant. This can be done by using an F-statistic to test for the improved fit (Lattin, Carroll, and Green, 2003; Hair et al., 2006):
𝐹 − 𝑣𝑎𝑙𝑢𝑒 =(𝑅𝑓
2− 𝑅
𝑟2)/(𝑑𝑓𝑟− 𝑑𝑓𝑓)
(1 − 𝑅𝑓2)/𝑑𝑓 𝑓
30 the numerator), whereby the degrees of freedom are the number of observations minus the number of parameters (Hill, Griffiths and Judge, 2001).
Since the F-value for the change in R2 is far less than the critical value, model II is not performing significantly better than model I.
Multicollinearity is no issue for both models I and II, because the VIF-values are between 1,5 and 2,0. This means that the independent variables of the model are linearly independent (Hill, Griffiths, Judge, 2001).
When looking at table 3, model I, it can be seen that the parameters are all significant and positively related to (the logit of) loyalty intentions. Relationship equity has the strongest relation to loyalty intentions since it has the largest parameter value. Value equity is of least importance and brand equity is second most important for consumers to intent to stay loyal. All parameters for the customer equity drivers are significant at the 1% level. These results indicate that hypotheses 1, 2 and 3 can be confirmed; value equity, brand equity and relationship equity are all positively related to loyalty intentions.
When looking at the parameter estimates of model II in table 3, the first thing that attracts the attention is that none of the interaction effects of the customer equity drivers appears to contribute positively and significantly to loyalty intentions. This means that hypotheses 4, 5, and 6 cannot be supported. Furthermore, the customer equity drivers appear to have the same relation with loyalty intentions as in model I; they are all positively related to loyalty intentions, with relationship equity contributing the most.
4.4.2 Moderating Effects of Economic Confidence
In this paragraph the variable economic confidence will be added to model I, to see whether it moderates the relationships between the customer equity drivers and loyalty intentions.
The mean score for economic confidence is 3.8, which means that most respondents are not really positive about the economy at the moment and in the future (expected average on a 7-point scale is 3.5), but also not extremely negative. In order to come up with meaningful results in the regression analyses, I recoded the questions for economic confidence so that all values are reversed (i.e. 1=7, 2=6, etc.). Then, I saved the factor score from the factor analysis to form the construct for economic confidence.
31 loyalty intentions as dependent variable. To test for the moderating effects of economic confidence on the relations between customer equity drivers and loyalty intentions, I included interaction effects for the customer equity drivers and economic confidence (denoted with „EC‟ in the equations). The model to test hypotheses 7a, 7b, 7c, and 7d is:
𝑙𝑜𝑔𝑖𝑡 𝐿𝐼 = 𝛼 + 𝛽1𝑉𝐸 + 𝛽2𝐵𝐸 + 𝛽3𝑅𝐸 + 𝛽4𝐸𝐶 + 𝛽5 𝐸𝐶 ∗ 𝑉𝐸 + 𝛽6 𝐸𝐶 ∗ 𝐵𝐸 +
𝛽7 𝐸𝐶 ∗ 𝑅𝐸 + 𝜀 (3)
Moreover, in chapter two I also discussed that consumers with high or low income will behave differently when economic confidence is either high or low, which resulted in hypothesis 7e. The model to test this hypothesis requires the addition of interaction effects of income and economic confidence in equation 3. This looks as follows:
𝑙𝑜𝑔𝑖𝑡 𝐿𝐼 = 𝛼 + 𝛽1𝑉𝐸 + 𝛽2𝐵𝐸 + 𝛽3𝑅𝐸 + 𝛽4𝐸𝐶 + 𝛽5 𝐸𝐶 ∗ 𝑉𝐸 + 𝛽6 𝐸𝐶 ∗ 𝐵𝐸 +
𝛽7 𝐸𝐶 ∗ 𝑅𝐸 + 𝛽8𝑖𝑛𝑐𝑜𝑚𝑒 + 𝛽9 𝐸𝐶 ∗ 𝑖𝑛𝑐𝑜𝑚𝑒 + 𝜀 (4)
The results from these regression analyses are reported in table 4.
There are four different income groups (see x-axis figure 3); group 1 has a yearly income below €30.000, group 2 has a yearly income around €30.000, group 3 has a yearly income between €30.000 and €60.000, and group 4 has a yearly income of €60.000 or more. There was also a fifth income group, but I deleted this group from all the regression analyses with economic confidence since these respondents indicated they would rather not tell their income level. This makes the number of observations 413 for the two estimated models.
Models III and IV are both significant as a whole, since the F-values are 22,799 and 20,862 respectively. I will look at the change in R2 values to investigate whether models III and IV perform better than the previous model. I compared model III with model I, and model IV with model III. The change in R2 for model III is significant, which indicates that the more advanced model III does outperform model I. Model IV, which also includes an interaction term of income and economic confidence, does improve model fit significantly compared to model III.
For models III and IV VIF-values are all below 2, which means multicollinearity is not an issue. However, for model IV the variables „income‟ and „EC * income‟ show VIF-values around 10, so multicollinearity might become an issue. But, when looking at the parameter estimates and significance levels, results seem robust.
32
Table 4: Regression Analyses Moderated by Economic Confidence
III. Model equation 3 IV. Model equation 4
b (unstand.) b (unstand.) Constant (β0) -0,251* 0,253 VE (β1) 0,371* 0,360* BE (β2) 0,378* 0,366* RE (β3) 0,534* 0,555* EC (β4) 0,113 -0,516** EC * VE (β5) 0,197** 0,167*** EC * BE (β6) -0,216** -0,184** EC * RE (β7) -0,066 -0,077 Income (β8) - -0,180* EC * income (β9) - -0,211* R2 0,314 0,352 Adj. R2 0,301 0,335 F-value Δ R2 7,47* 16,625*
* p-value < 0,001; **p-value < 0,05; ***p-value < 0,10
NOTE: the economic confidence construct has been recoded for better interpretability, see beginning of paragraph 4.4.2
First, the customer equity drivers in model (III and) IV appear to have the same relation with loyalty intentions as in model I, which indicates results are stable.
Second, when looking at the main effect of economic confidence, the parameter is negative, which is as expected and in confirmation of hypothesis 7a. Consumers with low economic confidence have lower loyalty intentions than consumers with high confidence in the economy.
Third, it appears that the interaction effects of value equity and economic confidence as well as of brand equity and economic confidence are significant and with the expected signs. It appears that when economic confidence is low, value equity becomes more important to consumers, in confirmation of hypothesis 7b. It also appears that when economic confidence is low, the brand becomes less important, which confirms hypothesis 7c. The interaction effect of economic confidence and relationship equity is not significant, and the sign is negative, opposed to as expected. So, hypothesis 7d cannot be confirmed.
33 represents loyalty intentions of consumers with low economic confidence for different values of value equity (x-axis). The green line represents loyalty intentions of consumers with medium economic confidence for different values of value equity. And the red line represents loyalty intentions of consumers with high economic confidence for different values of value equity. The values for low, medium, and high economic confidence are determined by the minimum, mean, and maximum values for the factor (see appendix 5).
From graph 2 it can be seen that when economic confidence is low, the line in the graph is upward sloping and steeper than for medium economic confidence, which indicates that value equity becomes of more importance for the intention to stay loyal for consumers with low confidence in the economy. The graph also shows the main effect of economic confidence: consumers with low confidence have in first instance lower levels of loyalty intentions than consumers with medium or high confidence in the economy. However, when value equity is highest, loyalty intentions for consumers with low confidence in the economy are highest.
In figure 3 the moderating effect of economic confidence on the relationship between brand equity and loyalty intentions is shown graphically. It can be clearly seen that consumers with low confidence pay less importance to the brand, since the red line is downward sloping. For consumers with medium and high economic confidence, the relationship between brand equity and loyalty intentions is positive and is larger positive for higher values of brand equity (shown on the x-axis).
-4 -3 -2 -1 0 1 2 3 4 1 2 3 4 5 6 7 Log it of LI
Levels of value equity
Figure 2: Moderation of EC on relationship between VE and LI
34 The last finding is that with low and medium economic confidence, consumers with higher incomes will have lower loyalty intentions than consumers with lower incomes (β9). This is
contrary hypothesis 7e. However, consumers with high confidence in the economy, and higher incomes, have higher loyalty intentions. This result is shown in figure 4.
In the next chapter I will discuss all important findings from the different regression analyses.
-6 -4 -2 0 2 4 6 8 10 12 1 2 3 4 5 6 7 Log it of LI
Levels of brand equity
Figure 3: Moderation of EC on relationship between BE and LI
High EC Low EC Medium EC -6 -4 -2 0 2 4 6 1 2 3 4 Logi t o f LI Levels of income
Figure 4: Moderation of EC on relationship between income and LI
35
5.DISCUSSION OF RESULTS
A study in the Dutch banking sector has been conducted by asking almost 400 consumers about their perceptions of value and the brand of a service and the relationships they have with the bank. In the introduction I stated three questions, which have all been answered by this research. I will discuss these into detail in this chapter. I will start with a discussion of the relationships between customer equity drivers and loyalty intentions, and the interaction effects between the customer equity drivers and how these are related to loyalty intentions. Second, the moderating effects of economic confidence on the relations between customer equity drivers and loyalty intentions will be discussed.
5.1CUSTOMER EQUITY DRIVERS
This research in the Dutch banking sector confirmed existing literature about the relationships between customer equity drivers and loyalty intentions. Value equity, brand equity and relationship equity all have a positive effect on loyalty intentions. From these customer equity drivers, relationship equity has the strongest effect on loyalty intentions.
The investigated relationships between the customer equity drivers, measured by their interaction effects, appear not to explain loyalty intentions better than their main effects. None of the interaction effects between the customer equity drivers appears to be significantly related to loyalty intentions.
5.2ECONOMIC CONFIDENCE
36 consumers with low incomes decrease consumption more than do consumers with high incomes during recession (Zurawicki and Braidot, 2005). It might be the case that consumers with low incomes cannot take the risk of switching to another company, and have therefore higher loyalty intentions than consumers with higher incomes. Whereas consumers with higher incomes will not be affected that much when they buy badly and can take the risk of switching to another company, even during a recession. Last, no confirmation could be found for a positive interaction effect between relationship equity and economic confidence, which could have been reasonable because a good relationship with the company might reduce uncertainty for consumers which could lead to higher loyalty intentions.
37
6. MANAGERIAL IMPLICATIONS
For managers of banks it is important to focus on the value and convenience of the services, the innovativeness, strength and uniqueness of the brand(s), and the relationship with the consumer in order to make consumers more loyal. The relationship is the most important factor. Managers can focus on the specific items of relationship equity; commitment has to do with the trustfulness of the relation and whether the consumer is enthusiastic about the bank, feels at home, attaches value to the relation, and has a confidential relationship with the bank. All these factors are factors that managers of banks can focus on in order to win consumers‟ loyalty.
38
7. FUTURE RESEARCH
This research is not conclusive, and many areas still can be investigated. The first extension for further research is to link loyalty intentions to actual behaviour or sales to improve the model fit and state more accurate conclusions. For example, it could be investigated whether consumers indeed decrease consumption during periods when their confidence in the economy is low. This can be accomplished by linking the data from this research with data from the specific banks and/or CBS data. In this way, the actual behaviour of consumers can be observed and more firm conclusions can be drawn.
Second, it would be interesting to conduct the same research in more sectors and over more companies. Generalizations about the conclusions in the research could be made when extending the scope. Therefore, this research will be extended into seven more sectors, namely; insurance (general and health), energy, supermarkets, telecom, transport, retail, and travel. Because these sectors are all different (regarding the nature of the offerings, ways of doing business) it would also be interesting to see whether there are differences in conclusions. Also, in some sectors (e.g. supermarkets and retail) the consequences of a recession might be more visible than in other sectors (e.g. insurance, transport, and energy), since cutting consumption is easier in the former than in the latter sectors.
Third, going a step further would be to conduct the research in several countries to make international comparisons. Especially for international or global companies this would be attractive, because they might need different ways of approaching consumers across boundaries.
Fourth, because economic confidence is a dynamic measure; i.e. it changes during and over years; it might be a nice extension to compare economic confidence figures with previous and/or later years. At the moment most consumers have low confidence in the economy, and it would be interesting to investigate whether conclusions are different when confidence in the economy is rising.
39
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