University of Amsterdam
Executive Program in Management Studies
Customer loyalty and customer
lifetime value: The roles of
motivations, experiences and price
Author: Anna Grossenbacher Student number: 10730559
Date of submission: 31st January 2016
Qualification track: Executive Programme in Management Studies - Marketing Track Institution: ABS
Statement of Originality
This document is written by Student Anna Grossenbacher who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document are 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.
Signature:
Acknowledgement
I would like to thank all respondents who filled in the survey and allowed me to analyse such a good sample size. In addition a special thanks goes to my thesis supervisor Prof. Dr. E. Peelen for his guidance, valuable feedback and support throughout my master thesis. Last but not least I would like to thank my family and friends for feedbacks, language check, encouragement, support and understanding.
Tables of contents
1. Introduction ... 7
2. Literature review ... 10
2.1. Concept of customer lifetime value ... 10
2.1.1. Creating on-going relationships ... 11
2.1.2. Determining customer lifetime value ... 12
2.1.3. Calculation of customer lifetime value ... 14
2.2. Customer loyalty ... 15 2.2.1. Cognitive loyalty ... 16 2.2.2. Affective loyalty ... 17 2.2.3. Conative loyalty ... 17 2.2.4. Action loyalty ... 18 2.3. Drivers of loyalty ... 19 2.3.1. Motivation ... 19 2.3.2. Motivation to travel ... 20 2.3.3. Experiences ... 21 2.3.4. Tourist experiences ... 22 2.3.5. Price ... 23
2.3.6. Role of currency exchange rate ... 25
2.4. Conceptual model and hypotheses ... 26
3. Data and method ... 30
3.1. Survey ... 30
3.3. Statistical procedure ... 31
4. Results ... 33
4.1. Preliminary steps of analysis ... 33
4.2. Factor and reliability analysis ... 35
4.3. Correlation analysis ... 38
4.4. Select cases ... 40
4.5. Regression ... 45
5. Discussion and conclusion ... 53
5.1. Theoretical and practical implications ... 53
5.2. Limitations and further research ... 59
6. References ... 60
7. Appendices ... 65
7.1. Questionnaire ... 65
List of figures
Figure 1: Framework for Customer Metrics (Gupta & Zeithaml, 2006) ... 13
Figure 2: Calculation of CLV (Gupta & Zeithaml, 2006) ... 14
Figure 3: Conceptual Model ... 28
Figure 4: Exploratory Factor Analysis for Motivations: Structure Matrix ... 36
Figure 5: Exploratory Factor Analysis for Experiences: Structure Matrix ... 37
Figure 6: Means, Standard Deviations, Correlations ... 40
Figure 7: Select cases Loyalty, Price and CLV for high and low Motivations and Experiences . 42 Figure 8: Select cases CLV for low and high Loyalty ... 43
Figure 9: Select cases Loyalty for low and high Price conscioussnes ... 44
Figure 10: Select cases Price, Motivations and Experiences in relation with age ... 45
Figure 11: Hierarchical Regression Loyalty on CLV ... 46
Figure 12: Hierarchical Regression Motivations on Loyalty ... 48
Figure 13: Hierarchical Regression Price on Loyalty ... 49
Abstract
The aim of this study is to examine the extent to which affective, cognitive, conative and action loyalty influence customer lifetime value and in what way specific experiences enhance the effect of motivations and price on cognitive, affective, conative and action loyalty. Despite its significance, only limited research has been conducted to determine and understand who the most profitable customers with the least price consciousness in a travel context are. This study, therefore, explores the role of motivations, experiences, price and loyalty on CLV. Data was collected from 486 respondents. Results of the analysis show that affective and action loyalty strongly increase CLV. The strengths of motivations (New Experiences Motivations and Holiday Motivations) positively influence cognitive, affective, conative and action loyalty. Price correlates significantly and negatively with cognitive, conative and action loyalty. Affective loyalty exhibits no influence of price. Finally, specific experiences (Nature Experiences and Social Relaxation Experiences) enhance the effect of motivations and price on loyalty. Older people (55 years and older) are less price conscious than younger people. This research assists in segmenting and targeting those most profitable customers with the lowest price consciousness and discloses practical and theoretical suggestions for managerial decisions. Implications of the study are discussed.
Key words: CLV, cognitive, affective, conative and action loyalty, motivations, experiences, price, and tourism
For simplicity's sake, the male form is used in the entire text; naturally, the female form is included.
1. Introduction
The exchange rate continues to be the key-influencing factor affecting the development of tourism in Switzerland. If the Swiss franc continues to hover around parity with the euro, the Swiss tourism sector must expect to see figures declining sharply. The most significant impact will be felt by seasonal rural and alpine tourism (European Commission, 2014). Swiss tourism's primary problem is not related to its product; it rather has a price problem, which in turn creates a demand problem.
Switzerland Tourism, the Swiss national tourist office, generates enthusiasm for Switzerland as a holiday, travel and congress destination and triggers the desire to travel. Switzerland Tourism as a firm focuses on different customer segments to offer the best prospects for success in stimulating national tourism. Europe continues to be the most important foreign market source for visitors travelling to Switzerland. The option of diversification into the long-haul markets (e.g. China) is not available to many alpine or rural destinations. Retaining European visitors will be the major challenge in the coming years (Switzerland Tourism, 2015). Knowing its customers enables a company to predict the traveller's behaviour more accurately and to conquer price consciousness more effectively and actively.
According to academic studies, targeting profitable customers via relationship marketing involves analysis of loyalty, searching for distinguishing patterns to determine why they stay or leave, what creates value for them and understanding who they are (Berry, 1995). It is also widely accepted that highly satisfied customers are less price sensitive, less influenced by competitors’ attack and more loyal to the firm than other customers (Nam et al., 2011 & Dimitriades, 2006). Customer loyalty is viewed as the strength of the relationship between an individual relative attitude and a repeat patronage (Dick & Basu, 1994). Loyal customers are
defined as frequent repeat purchasers who feel a sense of belonging to an organization and who are reluctant to change even in the presence of similar offerings from other firms (Henry, 2000).
Gupta et al. (2004) define the customer as the most critical aspect of a company. They demonstrate that valuing customers make it feasible to value firms. They define the value of a customer as the expected sum of discounted future earnings, which results in the CLV. The CLV has received increased attention in marketing and can be seen as a starting point for customer valuation and its relationship to the value of firms. Prior research shares the same conclusion: a high relational bond with the customer is vital to successfully influence the repeat behaviour of the customer and generate long-term business success to maximize the CLV (Yuksel et al., 2010).
To understand how loyalty grows and how to convert into a higher CLV, individual motivational drivers and experiences have to be examined. Successful marketing of a tourism destination depends on a clear understanding of tourists’ motivations and their impact on subsequent behavioural intentions (Leong et al., 2014). Travel experiences influence future experiences and stimulate a repeat choice behaviour (Scarinci & Pearce, 2012). The constructs of motivations and experiences play a major role in the tourism industry, as more loyal and satisfied customers are more likely to return and result in a higher CLV.
The role of the currency exchange rate influences the price of a holiday. The relationship between international tourism and exchange rates has a direct influence on visitors spending patterns. However, when used as a driver to determine the attractiveness of a destination, the exchange rate is not as important as first thought. The quality of the product and the value for money has to be present to smooth the transition between consumer expectations and experiences (Greenwood, 2007).
However, regarding all those relationships, little research has been done in the tourism industry so far. Within tourism research extensive studies have been done on loyalty to a destination in relation to specific travel motivations or experiences. The mainstay concept of CLV has widely filled the field of marketing research, but never appeared in tourism research. The role of currency exchange rate has not yet been connected specifically to those variables. This research is a contribution to understanding who the most profitable customers with the lowest price consciousness in a travel context are, and to disclose implications and suggestions for managerial decisions. This leads to the following research questions: “To what extent do affective, cognitive, conative and action loyalty influence customer lifetime value? In what way can specific experiences enhance the effect of motivations and price on cognitive, affective, conative and action loyalty?”
In order to reach a comprehensive conclusion, the study is structured as follows: The next section reviews current literature. This is followed by a section that outlines the data collection procedure and research methods; then the results based on collected data are examined. In the final section the most important conclusions and implications of this study are discussed, together with the limitations of this study and a number of suggestions for further research.
2. Literature review
This section discusses the most relevant findings from the current literature of CLV, loyalty, motivations, experiences and price. The key concepts that provide the theoretical foundation are discussed. The chapter ends with a research model, which graphically illustrates the stated hypotheses.
Retaining European visitors will be the major challenge for Switzerland Tourism in the coming years, as the number of visitors has basically collapsed since the Swiss franc became significantly stronger (Business Plan Switzerland Tourism, 2015). By placing the customer at the centre, Switzerland Tourism can create experiences and link that explicitly to the customer’s motivations at any given interaction. As well as understanding which customers indicate the best prospects of success in generating enthusiasm and triggering desire to travel to Switzerland (Lemon et al., 2001).
2.1. Concept of customer lifetime value
With a view to the current development of the Swiss franc, attracting new European visitors to Switzerland is not a primary goal for Switzerland Tourism. Hence, the target is focusing on returning customers from Europe.
The concept of the CLV received increasing attention in marketing in the last years. It can be seen as a starting point for customer valuation to retain and grow the right customer in customer relationship management in order to adapt the customer experience and create the highest possible value (Venkatesan & Kumar, 2004). CLV begins to view customers in terms of on-going relationships, rather than only in transactions (Berger & Nasr, 1998). The outcome of
calculating the CLV will show what customers are worth and how companies can keep their value. Furthermore, it predicts to what extent both CLV and demand will be influenced by price (Gupta et al., 2004).
2.1.1. Creating on-going relationships
To understand the concept of CLV, an on-going relationship is a requirement for the calculation of CLV. A relation starts to develop when the connection goes beyond discrete transactions reflecting an on-going process (Dwyer et al., 1987). Or as Rust et al. (2004) state: “It is the customer's tendency to stick with the product, above and beyond objective and subjective assessments of the product”. Several theories of relationship marketing propose that customers vary in their relationships with a firm on a continuum from transactional to highly relational bonds (Garbarino & Johnson, 1999).
Dwyer et al. (1987) identify five general phases in the relationship development process: (1) awareness, (2) exploration, (3) expansion, (4) commitment and (5) dissolution. Each phase represents a major transition. When the most prepotent phase is realized, the next higher level emerges. The interaction between the customer and the company has neither transpired in the awareness phase nor in the exploration phase, which refers to the search and trial phase. The expansion phase refers to continual increase in benefits. Still customers are more sensitive to price changes and the relationship is not fully developed. However, at the most advanced commitment phase the customer has achieved a level of satisfaction from the relationship that virtually precludes other companies, or in this research other countries that could provide similar benefits. The customers have not ceased to look for alternatives, but maintain their awareness of alternatives without constantly and frenetically testing. Finally, customer loyalty is achieved. In
the phase of dissolution the possibility of withdrawal or disengagement has been implicit through the relationship development framework. Termination of personal relationship is a significant source of psychological, emotional and physical stress (Dwyer et al., 1987). For example a tourist that has travelled to Switzerland several times already, and who has an on-going relationship and a bond to the country can suffer as the currency exchange rate interrupts the relationship. Relationship marketing requires a structure that makes termination and disengagement of the association unattractive even if the price of the product or service has risen.
2.1.2. Determining customer lifetime value
CLV has been a mainstay concept in relationship marketing for many years. Since the early 1980s, marketing has undergone a major directional turn toward relationship marketing in both its theory and practice. At the core of relationship marketing is the development and maintenance of a long-term relationship with customers, rather than simply a series of discrete transactions. It is achieved by creating superior customer value and satisfaction, ideally a loyalty that benefits both parties when foster. Determining the CLV or economic worth of a customer is a straightforward exercise. To calculate CLV, the net cash flows, that the company expects to receive from the customer over time, need to be projected, followed by calculation of the present value of the stream of cash flows. In practice estimating the net cash flow can be very challenging. Therefore, taking a holistic view of what may come of the relationship with the customer while addressing the issue is important. Profits per customer are not necessarily constant per cycle. A major advantage in retaining the customer is that the profits generated by them tend to accelerate over time. Revenues from customers typically grow over time. Existing customers are more efficient to serve, as they do not request services the company does not offer.
Their familiarity with the product makes them less dependent on its employees for advice and help. Satisfied customers act as referrals who recommend the business to others. In some industries, old customers pay effectively higher prices than new ones (Berger & Nasr, 1998).
To compete in this aggressively interactive environment, companies must shift their focus from driving transactions to optimizing customer’s lifetime value (Rust, Moorman & Bhalla, 2010). Figure 1 shows the framework of customer metrics and the link between the marketing actions and the financial performance. The unobservable metrics as perceptual measures are customer satisfaction, service quality, loyalty and intentions to purchase. The observable metrics as the behavioural outcomes are customer acquisition, margin, customer retention and cross selling.
2.1.3. Calculation of customer lifetime value
Marketing decisions based on observed customer metrics improve a firm’s financial performance. According to Gupta & Zeithaml’s (2006) research, customer retention is one of the key drivers of CLV and profitability. The customer metrics provide a good basis to assess the market value of a firm and to abandon unprofitable customers.
Figure 2 shows in detail the calculation of CLV, understood as the present value of the future cash flow attributed to the customer relationship (Gupta & Zeithaml, 2006).
Figure 2: Calculation of CLV (Gupta & Zeithaml, 2006)
Customers that indicate a pattern of returning or having a relationship with the company are more interesting and usually result in a higher CLV. As mentioned above, a major advantage in retaining the customer is that the profits generated by them tend to accelerate over time and revenues typically grow over time. Satisfied customers act as referrals who recommend the business to others. The basic insight that comes from looking at CLV begins to view customers in terms of on-going relationships (Berger & Nasr, 1998). To understand this dimension, the
2.2. Customer loyalty
Customer loyalty is indicated by an intention to perform a diverse set of behaviours that signal a motivation to maintain a relationship with the focal firm (Zeithaml et al., 1996). It is a dynamic process and grows over time. Loyalty models have been developed to understand the psychology of the customer and improve marketing activities or customer relationship programs to make customers even more loyal. As aforementioned, a relation starts to develop when the connection goes beyond discrete transactions reflecting an on-going process (Dwyer et al., 1987). Rust et al. (2004) state it as the customer's tendency to stick with the product, above and beyond objective and subjective assessments of the product. In the case of this research almost half of the European customers (47 %) are recurrent (established) visitors with at least six holiday stays in Switzerland. Almost a third are regular customers (30%) with two to five holiday stays (Switzerland Tourism, 2015).
According to Oliver (1999) and many other practitioners and academics, customer loyalty and satisfaction are linked inextricably. Although loyal customers are most likely satisfied, satisfaction does not universally translate into loyalty. His analysis concludes that satisfaction is a necessary step in loyalty formation but becomes less significant as loyalty begins to set through other mechanism, such as personal determinism and social bonding at a personal level.
Loyalty is a deeply held commitment to patronize a preferred product or service consistently in the future, despite situational influences and marketing efforts having the potential to cause switching behaviour (Oliver, 1999). Loyal customers are defined as frequent repeat purchasers who feel a sense of belonging to an organization and who are reluctant to change even in the presence of similar offerings from other firms (Henry, 2000). Loyalty has been studied extensively, also within the tourism and hospitality sector, and remains a complex
and subtle concept. Within the tourism context, a range of different factors can influence loyalty, for example repeat behaviour, distance travel, destination, lifecycle stage and relationship with other organizations or destinations (McKercher et al., 2012).
Oliver’s (1997) framework follows the cognition-affect-conation design but differs in the way that he argues that customers can become loyal at each attitudinal phase relating to different elements of the attitude development structure. This varies from Dwyer (1987) and his five phases where customer loyalty only is achieved in the commitment phase. Oliver (1997), on the other hand, states that customers can become loyal in a cognitive sense first, then later in an affective sense, still later in a conative manner and finally in a behavioural manner described as action inertia. Loyalty develops through those different phases. In the following paragraphs this concept will be explained.
2.2.1. Cognitive loyalty
Cognitive loyalty is the first loyalty phase and based on costs and benefits. It is referred on brand belief only that one brand is more preferable to its alternatives. Cognition is based on prior or vicarious knowledge or on recent experience-based information. Loyalty is directed towards the brand because of this information and no deeper than mere performance. If satisfaction is processed, it becomes part of the customer experience and begins to take on affective overtone (Oliver, 1999). According to Yuksel et al. (2010) cognitive loyalty was reported to be the weakest form of loyalty on a destination choice.
Cognitive loyalty has a significant influence on affective and conative loyalty. The path between affective and conative loyalty seems to be stronger compared to the path between cognitive and conative loyalty. Correlation analysis of Yuksel et al. (2010) study shows the
following results of 0.40 versus 0.25, p < 0.000. It provides a degree of support for the sequential process of loyalty in which tourists become “loyal first in a cognitive sense, then later in an affective sense, and still later in a conative sense” (Oliver, 1997, Yuksel et al., 2010).
2.2.2. Affective loyalty
Affective loyalty at the second phase of loyalty is based on cumulative satisfactory experiences and loyalty development. Commitment at this phase is referred to affective loyalty and is encoded in the customer's mind as cognition and affect. Similar to cognitive loyalty, this form remains subject to switching. Thus is would be desirable if customers were loyal at a deeper level of commitment (Oliver, 1999). Yuksel et al. (2010) conclude that affective loyalty is not the perfect predictor of behavioural loyalty in terms of a destination choice, as the customer might be satisfied with the destination; hence he or she might become affectively loyal to another destination in the same category (e.g. winter sport, Alpine region) as well.
2.2.3. Conative loyalty
Conative loyalty is the next phase of loyalty development in behavioural intention as it is influenced by repeated episodes of positive affection towards the brand. Conation implies a brand-specific commitment to repurchase. Conative loyalty is a loyalty state that contains at first, what appears to be the deeply held commitment to buy. This commitment is the intention to rebuy the brand and is more akin to motivation. In effect, the customer desires to repurchase, but similar to any good intention, this desire might be an anticipated but unrealized action (Oliver, 1999). Yuksel et al. (2010) prove that conative loyalty is argued to be a stronger predictor of behavioural loyalty on a destination choice than cognitive or affective loyalty.
2.2.4. Action loyalty
Action loyalty is the last phase in which intentions are converted into actions. The motivated intention in the previous loyalty stage is transformed into readiness to act and to overcome obstacles that might prevent the act. Readiness to act is the deeply held commitment to repurchase a preferred product or service in the future. Action loyalty only exists when individual fortitude (brand identification/adoration) and social support (active or passive pressure from others) are present (Oliver, 1999).
Completing the preceding cognitive-affective-conative framework with the fourth action phase, it will bring the attitude-based loyalty model to the behaviour of interest. Cognitive loyalty focuses on the brand performance aspects, affective loyalty is more directed towards the brands likeableness, conative loyalty is experienced when the customer focuses on wanting to rebuy the brand and action loyalty is commitment to rebuying and in this case being loyal towards a destination choice (Oliver, 1999).
However, loyalty has become a critical part of destination marketing in tourism and management research due to increasing competition and recognition of the importance of loyal visitors (Yuksel at al., 2010). To understand how loyalty grows, individual drivers need to be examined. The constructs of motivations and experiences play a major role in the tourism industry, as loyal customers are more likely to return and result in a higher CLV. These will be further discussed in the next section.
2.3. Drivers of loyalty
As mentioned above personal factors and individual drivers have to be examined in order to understand the full concept of loyalty. The theoretical backgrounds of motivations and experiences are introduced in the following paragraphs.
2.3.1. Motivation
Psychologists and social psychologists generally agree that motivations are an internal factor that arouses, directs and integrates a person’s behaviour. This factor can be compared to an awareness of a potential satisfaction in a future situation. It is also closely linked to the stimulus-cognition-response model of human behaviour, which is influenced by stimulus inputs and thus influences behaviour (Iso-Ahola, 1982).
Maslow’s (1943) theory of human motivation is one of the most relevant theories in sociology. He believes that all people have needs to be satisfied and that they will work towards satisfying those needs. Needs are seen as requirements that people have. In regard to his theory, there are five sets of goals that are related to each other and arranged in a hierarchy. When the most prepotent goal is realized, the next higher need emerges. His hierarchy remains a very popular framework in sociology. Level one is the physiological need and contains simply needs as air, water, food, rest and exercise. Level two involves safety, security, protection and freedom from fear. Level three contains the social needs; love, belongingness and affection. Level four is about the esteem needs, its strengths, status and respect. The last and highest level in the pyramid is about self-actualization and its need for personal growth, development and fulfilment. These different levels of the Maslow pyramid influence travel motivations that the underlying levels have to be fulfilled before one is able to travel.
2.3.2. Motivation to travel
In the recent decades there has been an increased interest in finding out what motivates tourists to behave the way they do (Todd, 1999). The first representing stream was an indirect approach, as respondents were asked to share positive and negative holiday experiences. Reactions were content analysed with descriptions in terms of Maslow’s (1943) hierarchy of needs theory. The second stream of research asked respondents to rate the importance of various reasons for travel. The third stream was a comprehensive review of the destination choice literature. The importance of different reasons for travelling indicated the importance of each attribute in their decision making to infer underlying motives (Todd, 1999). Motivation in tourism has been conceived in a one-dimensional manner, as such, it was either seen as a behavioural or a cognitive construct. Recent papers have questioned the theoretical basis of this one-dimensionality of motivation. Early key motivation elements were the need to escape mundane home or work and seek pleasurable new experiences. Nowadays the interaction between motivations and symbolic consumption of tourism experiences is more of a social or hedonic value rather than functional utility (McCabe, 2000). Travel researchers have to understand how and why consumers make travel decisions about domestic or international travel by focusing on push and pull motivational factors. According to the push and pull approach consumers are likely to be pushed to travel by intangible factors (e.g. escape, relax, exploration) and can be pulled to decide upon destinations by tangible factors (e.g. attractions, facilities) (Kim, 2008).
Successful marketing of a tourism destination depends on a clear understanding of tourists’ motivations and their impact on subsequent behavioural intentions. To understand tourist’s motivations, individual intrinsic desires and destinations’ unique attributes must be examined. The study of Leong et al. (2014) seeks to understand if individual intrinsic motivations (e.g.
motivation nostalgia = push motivations) and destinations attributes (e.g. historical & heritage attractions or rest & relaxation facilities = pull motivations) eventually influence tourists’ loyalty. The level of loyalty is measured by the willingness or intention to revisit the destination and the supportive behaviour for the destination. The result of the study is a strong case for attracting tourists with special motivations (e.g. nostalgia) to visit the destination even though the motivation does not directly impact loyalty. In order to generate loyalty, a destination should provide a place for families and friends to share quality time together. Examining motivations individually provides better insights into segmenting tourists’ markets for a particular destination.
To understand how loyalty grows and convert into a higher CLV, we examined individual motivational drivers. A motivation to travel might not be enough to stimulate return behaviour of a customer. Therefore, research about experiences, especially tourism experiences, will follow in the next paragraph.
2.3.3. Experiences
An experience refers to the nature of events someone or something has undergone and is happening permanently to all human beings. Humans have different expressions, behaviours, languages and emotions that characterize and convey those different experiences. There is also a philosophical notion of an experience as one’s experience in actually seeing something is not the same thing as one’s (experience of) actually seeing it. There is an element in this: the sensing, contrasted with the interpretation. The experience is thought of as being or involving in a sort of bonus event in addition to everything that happens physically (Hinton, 1967). Conforming to Dewey (1938) cumulative experience either shuts one down or opens one's access up to possible
future experiences. Experiences influence future experiences and therefore a repeat choice behaviour.
2.3.4. Tourist experiences
Tourist experiences cannot be bought. They can only take shape in the mind of the tourist. No one but the tourist can have control over those experiences and in many cases, not even the tourist is fully able to have such control (Andersson, 2007). There has been little investigation on how different types of visitors evaluate their travel experiences associated with a particular destination and the effects of these attributes on post-consumption behaviour, especially in nature-based settings. Kim & Brown’s (2012) study seeks to examine the impacts of perceived travel experiences (e.g. enjoying the scenery and landscape, being close to nature, discovering new places, relaxing with family and friends, improving health, experiencing adventure, learning about culture, meeting local people) on loyalty. The findings revealed that discovering new experiences and adventure experiences have the potential to enhance tourists’ novelty-seeking experiences and influence return behaviour. Additional findings also indicated that previous experiences with the destination and lengths of stay were important determinants of the satisfaction. The results of the research revealed that loyalty is driven by a combination of both the perceived quality of travel experiences and individual characteristics. The research found that people with previous experiences at the destination were more likely to be satisfied with the previous tourism experiences (e.g. overall enjoyment and unique experience) rather than first-time visitors. This implies that repeat visitors are more aware of new experiences and participate in different tourism activities when they return to the destination. Taking this point into
consideration, this study focuses on determining which aspects of perceived evaluation of specific experiences in Switzerland strengthen customer loyalty.
The discussion above shows that most studies on tourist behaviour investigate behavioural variables or psychological constructs (e.g. motivation, satisfaction) individually. However, linear relationships are insufficient in presenting an overall picture of factors and the interaction of factors leading to a specific behaviour or loyalty. Travel experiences can significantly influence a tourist's behaviour of possible revisiting a destination. Gomez-Jacinto, Martin-Garcia, and Bertiche-Haud’Huyze (1999) assume that tourist experiences include intercultural interaction, activities, service quality and satisfaction. Experiences remain a blurred concept, as they are something very personal. Being aware of tourist experiences in Switzerland, can help management of tourism companies strengthen and translate these experiences into successful marketing.
It is valuable to understand what occurs to customer loyalty and individual motivations and experiences behaviour if the price rises. This knowledge about the customer enables a company to predict the traveller's behaviour more accurately and to conquer price consciousness more effectively and actively. This will be further discussed in the next paragraph.
2.3.5. Price
The exchange-rate developments continue to be the key-influencing factor on the development of tourism in Switzerland (Switzerland Tourism, 2015). Touristic products are more expensive for European tourists, even though the product remains the same. In this research price is determined by what a buyer is willing to pay, a seller is willing to accept, and the competition is allowing to be charged (Business Dictionary, 2016). It is crucial to overcome the price consciousness in a
way that a tourist is willing to pay the price of a certain holiday again, even though the price is higher. Previous research on price, its beliefs and the currency exchange rate will be summarized in the following paragraph.
The article of Frank et al. (2014) states, that it might not be enough for higher-priced products and services to simply convey greater functional value. Higher-priced products should also stimulate greater hedonic value in order to reach consumer satisfaction and help them emotionally justify higher expenses. The authors draw on psychological information processing theories to extend marketing knowledge by suggesting that the chain from perceived quality to customer loyalty is mediated by product beliefs. In order to illuminate how these processes vary across customers with distinct experiences, the authors examined the moderating effects of various dimensions of experience as breadth of experience, time since purchase and the relative price. A more precise knowledge of the processes connection perceived quality with customer loyalty enables marketers to improve their customer relationship management. Knowledge of a greater importance of hedonic (association of product or service with emotional benefits) versus utilitarian (association with goal-orientated benefits) benefits for products with a higher relative price in the same product category would enable marketers to adapt product design and marketing communication priorities accordingly. This helps to compete more successfully in specific market segments. In the initial experience stage, consumers use products and services after purchase, learn their objects external characteristics, capabilities and limitations and thus form a perception of their quality for later memory retrieval. In the product beliefs stage consumers build on product usage experience to construct beliefs about the usage benefits of products. This concerns beliefs about the ability of a product to make life more convenient or enjoyable. The evaluative judgement deals with the consumer's internal fulfilment responses to
the products or services. Evaluative judgement is captured by customer satisfaction. The final behavioural intention stage deals with the attitudinal manifestation of repurchase behaviour, which is customer loyalty. Those four stages flow from more objective and external assessments as perceived quality towards more subjective, experience-based judgements and intentions. Products in a higher range of affordable purchases within a product category tend to convey a subjective feeling of luxury to consumers. Spending on expensive luxury products, compared with inexpensive products, should be more emotionally and less rationally motivated.
Frank et al. (2014) examines the role of relative price, which refers to the price relative to personal disposable income, and positions the product within the range of affordable product experiences, thereby expressing the degree of sophistication in the product experience. Its results have served as a justification for providing high-quality products and services. Experiences positively moderate the mediating role of product beliefs. The relative price positively moderates the effect of hedonic product beliefs on affective customer satisfaction.
Holiday planning might be considered as a truly economic activity. The overall criterion for planning a holiday is usually value for money. Tourists will consider the potential experience judging it against the price of the good or service. The expected value of a certain experience differs from one consumer to the other and these differences vary both, in the long term and over the lifetime (Andersson, 2007).
2.3.6. Role of currency exchange rate
Currency exchange rates influence the price of holidays. The relationship between international tourism and exchange rates does have a direct influence on visitors spending patterns. However when used as a driver to determine the attractiveness of a destination, the exchange rate is not as
important as first thought (Greenwood, 2007). Long haul visitors usually plan their trips in advance and are committed to visit the chosen destinations regardless of exchange rate at the time of their trip. Needless to say, consistently high exchange rates cause a destination to shift from high volume to niche tourism attracting only the dedicated or wealthy visitors. For short haul visitors the exchange rate has a much greater impact, as the impulse traveller might consider the relative value of goods from its home country compared to the potential destination. There are many factors that altered the traditional models of tourism including ease and liberalisation of travel (growth of low-cost airlines, online travel booking), issues of security (growths of global terrorism) and economic fundamentals (low historic interest rates, fuel prices, the country's economic and globalisation). In conclusion, there is a fundamental correlation between exchange rate and tourists’ visits. However, other consumer and economic drivers also influence the relationship of exchange rate and tourism. Exchange rates will always be part of international tourism and travel; therefore quality product and value for money have to be present to smoothen the transition between consumer expectations and experiences (Greenwood, 2007).
We introduced and examined the relevant theoretical concepts in the aforementioned paragraphs to proceed with the conceptual model of this research. Following the conceptual model and hypotheses will be presented.
2.4. Conceptual model and hypotheses
Targeting profitable customers via relationship marketing involves analysis of loyalty and what creates value in terms of motivations or experiences (Berry, 1995). It is widely accepted that highly satisfied customers are less price sensitive, less influenced by competitors’ attack and more loyal to the firm than other customers (Nam et al., 2011 & Dimitriades, 2006). All authors
share the same conclusion: a high relational bond with the customer is vital to successfully influence the repeat behaviour of the customer and generate long-term business success to maximize each CLV (Yuksel et al., 2010).
To understand the formation of loyalty, different antecedents have to be examined. In case of travelling, a certain motivation to travel and experiences significantly influence a tourist's behaviour of revisiting a destination (Andersson, 2007). Tourists travelling internationally often deal with currency exchange rates. A fundamental correlation between exchange rate and tourists’ visits is found. Tourists will consider the potential experience judging it against the price of the product or service (Greenwood, 2007). This research is a contribution to understanding who the most profitable customers in terms of specific motivations and experiences and the lowest price consciousness in a travel context are. Successful marketing of a tourism destination depends on a clear understanding of its visitor’s.
The review of relevant literature shows the need to further look at and answer two questions: “To what extent do affective, cognitive, conative and action loyalty influence customer lifetime value? In what way can specific experiences enhance the effect of motivations and price on cognitive, affective, conative and action loyalty?”
In order to address the construct of the research question, this study is framed into a model as seen in Figure 3. It exhibits the research model that guides the research. The actual design of this study can be captured as following:
Figure 3: Conceptual Model
The following hypotheses can be derived from the conceptual model.
CLV begins to view customers in terms of on-going relationships, rather than only in transactions (Berger & Nasr, 1998). Customers that indicate a pattern of returning or having a relationship with the company are more interesting and usually relatively loyal and thus result in a higher CLV. Therefore it is hypothesised that:
H1: Affective, cognitive, conative and action loyalty have a positive influence on customer lifetime value.
It is assumed that if a customer indicates stronger motivations (like pleasure and symbolic motives like self-presentation) he is more loyal (Gehlert et al., 2013). This hypothesis tries to prove causal relation. The study of Leong et al. (2014) seeks to understand if individual intrinsic motivations (e.g. motivation nostalgia) and destinations attributes (e.g. historical & heritage attractions or rest & relaxation facilities = pull motivations) eventually influence tourists’ loyalty. This is summarized in the following hypothesis:
H2: The strengths of motivations positively influence cognitive, affective, conative and action loyalty.
Exchange rate is one of the external factors that influence the decision to travel abroad. A fundamental correlation between exchange rate and tourists’ visits is found. It is assumed that price is an antecedent for loyalty and directly influences loyalty. Tourists will consider the potential experiences judging it against the price of the good or service (Greenwood, 2007). This leads to the following hypothesis:
H3: An increase in price negatively effects cognitive, affective, conative and action loyalty. It is assumed that if a customer has more positive travel experiences, he is more loyal. In accordance with Dewey (1938) cumulative experience can open one's access up to possible future experiences. Experiences influence future experiences and can therefore influence a repeat choice behaviour. In terms of travelling experiences influences the repeat choice behaviour (Scarinci & Pearce, 2012). Therefore the following hypothesis is made:
H4: Specific experiences enhance the effect of motivations and price on cognitive, affective, conative and action loyalty.
The aforementioned hypotheses and the appertaining conceptual model will be tested in chapter 4 on its significance and explanatory power. The next chapter shows data and method used in this research.
3. Data and method
This chapter represents the start of the empirical part of this research. First, the most evident characteristics of the collected sample are outlined. Afterwards, the variables included in the questionnaire and corresponding reliabilities are discussed. Finally, a brief description is given, regarding the statistical approach that is taken in order to test the expected relationships discussed in the previous chapter.
3.1. Survey
We designed a questionnaire survey to empirically validate the conceptual model and to test the hypotheses. All items used in the questionnaire were derived from English studies. Since not all respondents to the survey were native Dutch speakers, the original items remained in English.
To answer the questions we made use of a five-point Likert scale. The questionnaire was designed in four sections. The set of questions in the first section attempted to understand travel motivations and experiences of the respondents. Motivation items were derived from Tourism Monitor 2013 (Switzerland Tourism, 2013) and studies from Hendriks (2010) and Kluin & Lehto (2012). Experiences items were also borrowed from Kluin & Lehto (2012). The second section was designed to assess loyalty levels of the respondents. Those statements were borrowed from the study of Yuksel et al. (2010). The third section attempted to understand what happens to travel intentions and price consciousness if the currency exchange rate changes. The last section dealt with personal and demographic details of the respondents. The CLV was answered by asking the respondents if they had plans to visit Switzerland in the future (options for yes, no or maybe), how much money they spend during their holiday (four answer possibilities) and how
many times they have been to Switzerland (seven answer possibilities). This calculation is based on the RFM (Recency, Frequency, Monetary Value) marketing model, a method used for analysing customer value. Recency stands for how recently the customer purchased. Frequency stands for how often the customer purchases. Monetary Value stands for how much the customer spends (Columbo & Jiang, 1999). The results of the current study were controlled for age and gender. These items were included in the last section of the questionnaire.
3.2. Sample
For the study, we chose European tourists travelling to Switzerland to understand whether the hypothesized effects can be explained. The data sample consisted of people living in Europe (mainly in the Netherlands and Belgium). These people have already travelled to Switzerland or have the intention to travel to Switzerland for a leisure holiday. They are recurrent customers. This choice of sample was appropriate as the research questions focus on answering if loyalty and its drivers can compensate the price issue (currency exchange rate CHF/EUR).
The survey is distributed via different communication channels of Switzerland Tourism. The monthly leisure newsletter sent to 38’000 subscribers (in the Netherlands) and 50’000 Dutch and Flemish followers on Social Media platforms (Facebook and Twitter) in order to reach a good sample size. The survey participants represent highly qualified contacts. If someone is a follower or a subscriber of the newsletter there is an interest or interaction with Switzerland.
3.3. Statistical procedure
Data was analysed in SPSS (Statistical software Package for Social Sciences). First frequencies check; computing scale reliability, exploratory factor analysis, select cases analysis and
descriptive analysis. After analyses on the construct level, compiling a correlation matrix and a regression analysis tested the hypotheses. Direct relationships were examined by the use of hierarchical regression.
The following chapter will discuss the results and findings of this study and evaluates the hypotheses of the conceptual model in their validation.
4. Results
First the preliminary steps of data analysis are discussed, afterwards the analysis on the construct level. The results from the factor analysis, select cases analysis and correlation matrix are outlined followed by the regression analyses. All hypotheses are tested separately.
4.1. Preliminary steps of analysis
Data was collected by means of an anonymous online survey. The survey started on October 28th 2015 and was closed two weeks later on November 10th 2015.
The survey resulted in 516 responses, whereas 486 respondents fully completed the questionnaire. 486 usable questionnaires for the analysis were found. No missing data was found. Of those 486 respondents 52.9 % were female, 47.1 % male. Most respondents were aged between 35-54 years (42 %) followed by 55-64 years (27.4 %) and 65 years or older (15.4 %). The age range was from 13 years to 65 or older. The majority of the respondents were Dutch (92.8 %), followed by Belgium's (3.7 %), other countries (1.4 %), French (1.0 %), Italian (0.8 %) and Luxembourg (0.2 %). The sample covered different ranges of educational background. A Bachelor's degree was the most stated one with 41.2 %, followed by a College degree with 28.4 % and a Master’s degree with 24.7 %.
76.1 % of the respondents answered that they have visited Switzerland already more than 10 times. Only 1.6 % was a first time visitor and no respondents have ever been to Switzerland. 78.8 % have the intention to visit Switzerland again in the future. An average stay in Switzerland lasts seven or more days (70.4 %) followed by 26.7 % for four to seven days. Most of the respondents stated that the budget they spend during a holiday in Switzerland is more than 1’200
euros (45.1 %) followed by 28.0 % between 800 - 1’200 euros. Most respondents liked to visit Switzerland in the summer, followed by winter, autumn and spring. Their preferred holiday accommodations are rented holiday houses or apartments, followed by hotels, camping, private housing, and finally privately owned holiday houses or apartments.
After checked for skewness and kurtosis distribution of data, normality test was computed. From all the variables only some items within motivations, cognitive and action loyalty were normally distributed. Relatively high scores were obtained on the scales for experiences, price and affective loyalty. The absence of a normal distribution on the other variables can be explained by the fact that the respondents are relatively loyal (76.1 % with more than ten visits to Switzerland). Experiences listed by respondents are numerous; otherwise they would not have visited Switzerland again. Furthermore the sample consisted of mostly Dutch inhabitants with similar travel motivations and experiences.
All questions in the survey were checked for recoded behaviour. One question “Do you have plans to visit Switzerland in the future?” was reverse coded and recoded in the following manner Yes = 1 -> 3, Maybe = 2 -> 2, No = 3 -> 1. The idea was to recode this counter-indicative item to the same pattern as the rest of the questions, where the higher value represents a stronger behaviour.
The preliminary steps are completed and accurate, therefore we continue with reliability, factor analysis to understand underlying patterns.
4.2. Factor and reliability analysis
We decided to run an additional exploratory factor analysis to understand the clusters of the variables motivations, experiences, loyalty and price.
Within the ten different motivations items KMO (Kaiser-Meyer-Olkin) test showed (0.5 < 0.73 > 1.0) and proved factor analysis (see Figure 4). The ten items of motivations have three underlying factors. All three factors had eigenvalues greater than one. A significant dip in the screen plot followed the third factor. The five-factor solution explained a high level of variance in motivations (53.4 %). Component 1 consists of the items (2) “To try new things”, (4) “To enlarge my travel experience and to become a more experienced traveller”, (8) “To visit places I have never been before”, (9) “To meet new people” and (10) “To explore and evaluate myself (self-perception). Those items can be summarized in variable “New Experience Motivations”. Component 2 consists of the items (1) “To rest and relax”, (3) “To do things with family and friends”, (5) “To have fun” and (6) “To experience nature”. The items can be summarized as variable “Holiday Motivations”. The last component consists of only one item (7) “To improve sport skills” and can be named as variable “Sport Motivation”. The grouping of these questions forms a reliable construct to measure motivations. In order to understand the different clusters of motivations in the correlation analysis the three groups were tested separately. Compute variables ware used in SPSS to make those new variables.
Figure 4: Exploratory Factor Analysis for Motivations: Structure Matrix
The same construct factor analysis is performed to test if the eleven items of experiences measure the same (see Figure 5). Within the eleven experiences items KMO Test showed (0.5 < 0.84 > 1.0) and proved factor analysis. All items together have three underlying factors. All three factors had eigenvalues greater than one. The five-factor solution explained a high level of variance in experience (58.9 %). Component 1 consists of the items (7) “I was pleased to improve my health and well-being, (8) “I felt excited about adventure activities”, (9) “I was excited discovering new places” and (11) “I was proud to experience unique moments of joy after a great achievement (e.g. climb or cycle a mountain)”. Those items can be summarized as variable “Sport and Adventure Experiences”. The second component consists of the items (3) “I was fulfilled spending time with my family and friends”, (4) “I was glad that I had time to relax”, (5) “I was pleased to meet local people” and (6) “I was glad that I had time to escape my normal routine”. They can be summarized in variable “Social Relaxation Experiences”. The last component consists of the items (1) “I felt happy enjoying the wonderful scenery and landscape”, (2) “I felt one with the nature (close to nature)” and (10) “I had times that I just felt very happy”. It can be summarized as variable “Nature Experiences”. In order to understand the
different clusters of experiences in the correlation analysis the three groups were tested separately. Compute variables were used in SPSS to make those new variables.
Figure 5: Exploratory Factor Analysis for Experiences: Structure Matrix
We wanted to be sure that cognitive, affective, conative and action loyalty do not measure the same constructs. SPSS showed that they load on the same factor. Therefore we used extraction “Fixed number of factors: 4 factors to extract” to make four items again. Within the measurement items of affective loyalty the last item, “I like Switzerland more than other countries”, load for cognitive loyalty. We adapted those items and computed the variables cognitive and affective loyalty new.
One item for measuring price consciousness was deleted since it load on a group, which we did not expect. Its Cronbach’s alpha goes up to 0.91 by deleting it. Therefore the item “I am aware of the current currency exchange rate” was removed and the variable price then consisted of four items instead of five.
The reliability of the measurement items was verified using the Cronbach’s Alpha to assess the internal consistency of the constructs in the proposed model and the newly composed
variables. The Alpha values in this research range from 0.57 to 0.91 (see Figure 6). Most Alpha values exceeded the minimum hurdle of 0.7 (Hair et al., 1995), which is indicated as a good value. Only two items did not reach the minimum hurdle, one was Holiday Motivations (0.57) and the other Social Relaxation Experiences (0.65). Scale adaption with both items was tried, but “Cronbach's Alpha if Item deleted” did not have a positive effect on the total Alpha. In accordance with Field (2013) an Alpha of 0.5 can be seen as a bare minimum, therefore we decide to continue with those Alpha values of (0.57) and (0.65). No Alpha value was calculated for Sport Motivation, because it is only one item. No Alpha value could be calculated for CLV, because not all aspects of the CLV measure the same aspect. In this case the items are complementary; they add up.
Taking all those preliminary adaptations of factor and reliability analysis into account, we can run a full correlation analysis to check how the variables are interrelated.
4.3. Correlation analysis
An overview of the descriptive statistics, correlations and scale reliabilities are presented in Figure 6. Correlation is a statistical technique that can show whether and how strongly pairs of variables are related. A first observation derived from both tables showed that the different loyalty levels (cognitive, affective, conative and action loyalty) significantly correlated with each other.
Figure 6 presents the first construct with many significant correlations found. To analyse the relationship between motivations (New Experiences Motivations, Holiday Motivations and Sport Motivations) and cognitive, affective, conative and action loyalty, we can see that New Experiences Motivations significantly correlate with all loyalty dimensions. Holiday Motivations
indicate even higher values of significant correlations and the highest value on linear relation with affective loyalty. Within Sport Motivation no significant correlation is found. Therefore this motivation item is deleted. Price significantly and negatively correlates with cognitive, conative and action loyalty. This negative correlation has a coefficient of -1, indicating that an increase in price reliably predicts a decrease in the other variables. The correlation coefficient of zero or very close to zero (-0.06) shows no meaningful relationship between the variable price and affective loyalty. All types of experiences (Sport & Adventure, Social Relaxation and Nature) correlate significantly with the different loyalty dimensions. The strongest correlation is found with affective loyalty.
In the second construct there are also many significant correlations found. Cognitive, affective, conative and action loyalty correlate significantly with CLV. Action loyalty correlates significantly stronger with CLV than cognitive, affective and conative loyalty.
The conclusion derived from the analysis is, that the direct lines in the conceptual model are confirmed. Price seems to be an antecedent for loyalty and the different experiences correlate with loyalty.
Figure 6: Means, Standard Deviations, Correlations
4.4. Select cases
To check whether the conditions count for respondents with low or high motivations, low or high experiences, low or high loyalty dimensions and low or high price consciousness, we run select cases. The results are presented in Figure 7, 8, 9 and 10.
Motivations and Experiences
For the items New Experiences Motivations, Holiday Motivations, Sport and Adventure Experiences, Social Relaxation Experiences and Nature Experiences we run the analysis select cases with the current mean value of each variable. First, we selected the case “If condition is satisfied New Experiences Motivations > 3.21” and run a descriptive analysis. Second, we selected the case “If condition is satisfied New Experiences Motivatiosn < 3.21” and run a
descriptive analysis again for each higher and lower value of motivations and experiences items. We were therefore able to compare the items with each other (see Figure 7). In general we can conclude that higher strengths of motivations and experiences indicate a higher loyalty level than lower strengths of motivations and more specific experiences. One exception is found for Sport and Adventure Experiences on action loyalty, which also indicates a high mean for lower values of experiences. It can be concluded, that Sport and Adventure Experiences are less resistant for higher or lower values in executing behaviour. We can conclude that Holiday Motivations are more generic motivations and seem to be more exchangeable. Respondents are probably less loyal to a place if they can get this motivation satisfied in other places. Sport Motivation cannot be computed in the analysis because at least one of the variables is constant.
If we check the higher and lower motivations and experiences on price consciousness, we can see that lower motivations and experiences result in a higher price consciousness. There is one exception found; Nature Experiences, which shows the same price consciousness for lower and higher values. It can be concluded that Nature Experiences are strong enough; not influencing price consciousness at any value.
We also checked how the lower and higher motivations and experiences change the mean of CLV. Most results showed higher means for CLV if higher motivations and experiences are the case. One exception was found; New Experiences Motivations did not show a decrease in the mean of the CLV with lower values. It can be concluded that New Experiences Motivations is a strong motivational indicator for CLV.
Figure 7: Select cases Loyalty, Price and CLV for high and low Motivations and Experiences
Cognitive, affective, conative and action loyalty
To see which high or low loyalties affect the CLV, we run the analysis with select cases for high and low values of cognitive, affective, conative and action loyalty (see Figure 8). Results show that the more loyal a respondent is, the higher the CLV is too. Lower values of loyalty show lower means for CLV.
Figure 8: Select cases CLV for low and high Loyalty
Price
To see if price consciousness goes up in certain cases and if it influences the loyalty dimensions, we also run select cases analysis (see Figure 9). Results show that the higher the price consciousness is, the lower the mean for cognitive, affective, conative and action loyalty is. Price consciousness is influencing the loyalty levels.
Figure 9: Select cases Loyalty for low and high Price conscioussnes
Age
We checked if older or younger people indicate different strengths in motivations, specific experiences and price consciousness (see Figure 10). The mean of the age was 5.3, which are respondents between 35 and 54 years old. Therefore we tested the different means for respondents > 35-54 years old, respondents < 35-54 years old as well as respondents > 55-65 years old. Price consciousness goes down with older age; therefore we can conclude that older people are less influenced by price than younger people. Older people are more driven for New Experiences Motivations than younger people. On the other hand, younger people seek more for Holiday Motivations and Sport & Adventure Experiences and Social Relaxation Experiences than older people. In conclusion our observations demonstrate that age plays a role for the strengths of motivations, specific experiences and price consciousness.
Figure 10: Select cases Price, Motivations and Experiences in relation with age
In the next step of the analysis we want to test the hypotheses on their validation using regression.
4.5. Regression
Hierarchical regressions analysis was performed to investigate the explanatory power of the different variables.
Affective, cognitive, conative and action loyalty on CLV
Hypothesis 1 proposed that affective, cognitive, conative and action loyalty has a positive influence on CLV. SPSS regression analysis was performed to examine this relationship (see Figure 11). First we determined the effect of the control variables age and gender on the relation between cognitive, affective, conative and action loyalty and CLV. Hierarchical regression is performed to investigate the ability of loyalty dimensions to predict the level of CLV, after
controlling for age and gender. In the first step of multiple regressions, two predictors were entered: age and gender. This model was statistically significant F (2, 483) = 9.534; p < 0.001 and explained 3.8 % of variance on CLV. After entering of cognitive, affective, conative and action loyalty at Step 2 the total variance explained by the model as a whole was 27.5 % F (4, 479) = 39.130; p < 0.001. In the final model four out of six predictors were statistically significant. With action loyalty recording a higher Beta value (β = 0.425, p < 0.001) than affective loyalty (β = 0.158, p < 0.01), age (β = 0.105, p < 0.001) and cognitive loyalty (β = - 0.176, p < 0.01). The explanatory effect of the loyalty dimensions shows that cognitive, affective and action loyalty has a significant effect on CLV. Support for the hypothesis was found for cognitive, affective and action loyalty, but not for conative loyalty. Hypothesis 1 is partly supported.
Figure 11: Hierarchical Regression Loyalty on CLV
Motivations on cognitive, affective, conative and action loyalty
Hypothesis 2 proposed that the strengths of motivations positively influence cognitive, affective, conative and action loyalty. Hierarchical regression is performed to investigate the ability of New Experiences Motivations and Holiday Motivations to predict the level of cognitive, affective, conative and action loyalty (see Figure 12). In the first step of the multiple regressions two predictors were entered: New Experiences Motivations and Holiday Motivations. This model was statistically significant F (2, 483) = 36.777; p < 0.001 and explained 13.2 % of
variance on cognitive loyalty. In the final model two out of two predictors were statistically significant. With New Experiences Motivations recording a higher Beta value (β = 0.250, p < 0.001) than Holiday Motivations (β = 0.224, p < 0.001). For affective loyalty the model explained 16.4 % of its variance with two out of two predictors that were statistically significant. With Holiday Motivations recording a higher Beta value (β = 0.351, p < 0.001) than New Experiences Motivations (β = 0.150, p < 0.001). For conative loyalty the model explained 10.6 % of its variance. With two out of two predictors that were statistically significant, showing Holiday Motivations recording a higher Beta value (β = 0.248, p < 0.001) than New Experience Motivations (β = 0.172, p < 0.001). For action loyalty the model explained 10.3 % of its variance. With two out of two predictors that were statistically significant, showing Holiday Motivations recording a higher Beta value (β = 0.235, p < 0.001) than New Experience Motivations (β = 0.182, p < 0.001). Finally hypothesis 2 proposed that the strengths of motivations positively affect cognitive, affective, conative and action loyalty. Support for the hypothesis was found for New Experiences Motivations and Holiday Motivations on cognitive, affective, conative and action loyalty. Hypothesis 2 is supported.
