Investigating and identifying reasons for brand loyalty of the Apple-iPhone brand in Germany

Bachelor Thesis 2013 115 Pages

Business economics - Marketing, Corporate Communication, CRM, Market Research, Social Media


Table of contents

I. Statement of authorship

III. List of abbreviations

IV. List of illustrations

V. Abstract

1. Introduction

2. Theoretical background
2.1. Theory of reasoned action (TRA)
2.2. Technology acceptance model (TAM)
2.3. TAM
2.3.1. Social influence processes
2.3.2. Cognitive instrumental processes
2.4. Identity theory (IT)
2.5. Social identity theory (SIT)
2.6. Customer-company identification (CCI)
2.7. Customer-brand identification (CBI)
2.7.1. Conventional perspective
2.7.2. SIT perspective
2.8. Hypotheses

3. Methodology
3.1. Data gathering
3.2. Data analysis
3.2.1. Descriptive analysis
3.2.2. Reliability analysis (Cronbach’s alpha)
3.2.3. Descriptive statistics after items were excluded
3.2.4. Correlation and regression analysis

4. Analysis and discussion of results

5. Conclusions
5.1. Scientific implications
5.2. Practical implications
5.3. Critical evaluation

VI. Bibliography

VII. Appendix

III. List of abbreviations

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IV. List of illustrations

I. Statement of authorship

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I herewith declare that I have authored the present thesis independently making use only of the specified literature. Sentences or parts of sentences quoted literally are marked as quotations; identification of other references with regard to the statement and scope of the work is quoted. The thesis in this form or in any other form has not been submitted to an examination body and has not been published.

Place, date and signature

V. Abstract

The aim of this thesis is to investigate and identify reasons for brand loyalty of the Apple-iPhone brand in Germany and to make recommendations for customer relationship and brand managers. The methods used are secondary and primary, quantitative research, with a cross-sectional online survey consisting of a 5-point Likert scale.

Brand loyalty is operationalized as switching intention, based on prior research. The theoretical background shows that there are two contrary views when investigating switching intention. On the one side, there is the conventional perspective with the motivation of functional utility maximization. People are motivated to switch a brand, when they believe they will gain perceived value, which is the customer’s overall assessment of the utility of a product based on perceptions of what is received and what is given. On the other side, there is the social identity theory perspective with social mobility as motivation. Social mobility refers to a person’s attempt to part him- or herself from a group. With regard to brands, this implies that customers switch brand identities, when they believe they identify themselves more with another brand.

Those two perspectives have been tested using two hypotheses with an online survey and 111 valid responses of Apple-iPhone users in Germany. The independent variables perceived value, customer brand identification and procedural switching costs were investigated using items from prior research. Items by an advanced theory of the technology acceptance model were used for perceived value. To analyze the data descriptive, reliability, correlation and regression analyses have been applied.

In conclusion, customer brand identification and procedural switching costs shows an equally strong significance for predicting switching intention. Perceived value could not be measured, since it did not pass the stepwise multiple regression analysis.

Apple Inc. is an American multinational corporation that designs and manufactures consumer electronics, computer software and personal computers. The company was started by Stephen Gary Wozniak and Steven Paul Jobs in 1976 with headquarters in Cupertino, California. Apple’s best- known hardware products include Macintosh computers, the iPod, the iPhone and the iPad (Sahoo 2012, p.39). 76,100 employees are working for Apple Inc. worldwide and the company generated worldwide revenues of $157 billion in 2012 with a change of 44.6% compared to the previous year. This makes it the 19th largest corporation in the world (CNNMoney 2013).

Interbrand (2013a) voted Apple the most valuable brand globally with a rise of value of +28% to $98 billion from 2012 to 2013. This is especially impressive, since the brand value of the technology sector only rose +15% to $37 billion during the same time period (Figure 1). It is not the products that define Apple; it is really a certain kind of thinking, a certain set of values and an unmistakable human touch that pervades everything Apple does - which is why the connections of the consumers to the brand transcend commerce. In a world where consumers are often overwhelmed with information, the role a brand plays in people’s lives has become all the more important to ensuring a business’ overarching success. This is what Steve Jobs understood better than anyone else (Interbrand 2013b).

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Figure 1 : Brand value Apple vs. Technology Sector (Interbrand 2013a)

What Jobs understood as well, is that for a company to achieve sustainable competitive advantage like Apple, it needs loyal emotional association of the customers towards the brand. These loyal customers will continue buying the company’s products on the one hand and act as advocates of the products on the other (Arora 2009, p.7). Loyal customers also share their satisfaction with prospective and existing customers. This tendency of sharing makes them come closer to the brand and to the existing customers of the brand. These again form a community and in marketing, this is called brand community (Arora 2009, p.11).

Kilambi et al. (2013, p.51) state that Apple has the highest brand loyalty of any computer manufacturer, due to its strong brand community. Apple knows about the importance of brand communities and actively supports the formation of customer-run Macintosh user groups. Although these groups are founded by volunteers and enthusiasts, the company encourages customers to join and participate in them. By strengthening customers to join this community, Apple aims to foster greater loyalty among its customers (Thompson and Sinha 2008, p.65).

iPhone, iPad and iPod sales worldwide

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Figure 2: iPhone, iPad and iPod sales worldwide, 2006-2013 (in million units) (Statista 2013a)

When looking at the sales numbers and the value of the Apple brand, the question arises how Apple could have become this strong and what other brands can learn from it. This research work will investigate the main reasons why Germans do own iPhone for private use since it is the most sold Apple product compared to the iPad and iPod worldwide (Figure 2; Statista 2013a). This investigation is based on the Social Identity Theory (Tajfel and Turner 1979, pp.34-39) and the Theory of Reasoned Action (Fishbein and Ajzen 1975) and consists of a questionnaire of iPhone users in Germany with a Likert scale.

The following research question is examined:

What are the reasons for brand loyalty of the Apple-iPhone brand in Germany?

In order to investigate thoroughly investigate potential reasons for brand loyalty of the iPhone brand in Germany; this research paper examines this issue from the brand and the technological perspective.

2.1. Theory of reasoned action (TRA)

TRA is one of the most fundamental and influential theories of human behavior and takes as a starting point the theory of social psychology (Hammami and Affes 2013, p.28; Venkatesh et al. 2003, p.428). This model developed by Fishbein and Ajzen (1975) defines the bonds between the social beliefs, attitudes, standards, intentions and behaviors of the individuals. According to this model, the behavior of a person is determined by adopted behavioral intention (BI) Figure 3). This intention is then identified by the attitude of the person towards the target behavior (A) (Davis et al. 1989, p.983; Fishbein and Ajzen 1975, p.216; Hammami and Affes 2013, p.28; Venkatesh et al. 2003, p.428) and the person’s perception of what most people who are important to him think about the target behavior, the subjective norm (SN) (Davis et al. 1989, p.983; Fishbein and Ajzen 1975, p.302; Hammami and Affes 2013, p.28; Venkatesh et al. 2003, p.428). Moreover A is determined by the person’s behavioral beliefs multiplied by its evaluation of these consequences of the action (Davis et al. 1989, p.984; Hammami and Affes 2013, p.28).

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Figure 3: Theory of Reasoned Action (TRA) (Davis et al. 1989, p.984)

2.2. Technology acceptance model (TAM)

Davis (1986) introduced an adaptation of TRA, which is specifically tailored for explaining computer usage behavior (Davis et al. 1989, p.983). The goal of TAM is to provide an explanation of the determinants of computer acceptance. This explanation has to be general and capable of explaining user behavior across a broad range of end-user computing technologies and user populations (Davis et al. 1989, p.985). Throughout the years, TAM has become well-established as a robust, powerful and parsimonious model for predicting user acceptance (Venkatesh and Davis 2000, p.187).

TAM uses TRA as a theoretical basis for specifying the causal linkages between two key beliefs: perceived usefulness (PU) and perceived ease of use (EOU) and users' attitudes, intentions and actual computer adoption behavior. TAM is considerably less general than TRA, designed to apply only to computer usage behavior. However, because it incorporates findings accumulated from over a decade of IS research, it may be especially well-suited for modeling computer acceptance (Davis et al. 1989, p.983).

A key purpose of TAM is to provide a basis for tracing the impact of external factors on internal beliefs, attitudes and intentions. TAM posits that two particular beliefs, PU and EOU use are of primary relevance for computer acceptance behaviors (Figure 4). PU is defined as the prospective user's subjective probability that using a specific application system will increase his or her job performance within an organizational context. EOU refers to the degree to which the prospective user expects the target system to be free of effort (Davis et al. 1989, p.985; Venkatesh and Davis 2000, p.187). TAM theorizes that the effects of external variables on BI are mediated by PU and EOU. According to TAM, PU is also influenced by EOU because, other things being equal, the easier the system is to use the more useful it can be (Venkatesh and Davis 2000, p.187).

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Figure 4: Technology Acceptance Model (TAM) (Davis et al. 1989, p.985)

TAM2 is considered a theoretical extension of TAM and develops and tests PU and BI in terms of social influence processes (SN, voluntariness and image) and cognitive instrumental processes (job relevance, output quality, result demonstrability and EOU). The extended model was tested using longitudinal data collected regarding four different computer systems at four organizations (Figure 5; Venkatesh and Davis 2000, p.186).

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Figure 5: Extension of the Technology Acceptance Model (TAM2) (Venkatesh and Davis, 2000 p.188)

Venkatesh and Davis (2000, p.193) sought naturalistic research sites that closely mirrored the target situation, where a new system was about to be introduced in the workplace. The four field sites covered a range of industries, organizational contexts, functional areas and types of system being introduced. There were two sites of participating organizations, some where the usage of the system was voluntary and somewhere usage was mandatory. The questionnaires were distributed to potential users after the initial training, one month, three and five months after implementation, using a 7-point Likert scale (Venkatesh and Davis 2000, p.193).

2.3.1. Social influence processes

TAM2 reflects the impacts of three interrelated social forces influencing an individual who is facing the opportunity to adopt or reject a new system: SN, voluntariness and image (Venkatesh and Davis 2000, p.187).

Consistent with TRA, SN is subordinated to social influence processes. It is defined as a “person’s perception that most people who are important to him think he should or should not perform the behavior in question” (Fishbein and Ajzen 1975, p.302). Venkatesh and Davis (2000, p.195) found that when usage of a computer system at a company was mandatory, SN did have a positive direct effect on BI. When usage was voluntary SN had no direct effect on BI. To distinguish between mandatory and voluntary usage settings, the model of Venkatesh and Davis (2000, p.188) posits voluntariness as a moderating variable defined as the extent to which potential adopters perceive the adoption decision to be non-mandatory.

Whereas the direct relationship between SN and intention in TRA is based on compliance, TAM2 encompasses two additional theoretical mechanisms by which SN can influence intention directly through PU: internalization and image (Venkatesh and Davis 2000, pp.188-189). Internalization is equivalent to what Deutsch and Gerard (1955, p.629) refer to as informational social influences, defined as “influence to accept information from another as evidence about reality” (Deutsch and Gerard 1955, p.629; Venkatesh and Davis 2000, p.189). For example: if a superior or co-worker suggests that a particular system might be useful, a person may come to believe that it actually is useful and in turn form an intention to use it. In the case of internalization, SN has an indirect effect on BI through PU, as opposed to direct compliance effect on intention. Internalization, unlike compliance, occurs whether the context of system use is voluntary or mandatory (Venkatesh and Davis 2000, pp.189-191).

Moore and Benbasat (1991, p.195) define image as “the degree to which use of an innovation is perceived to enhance one’s ... status in one’s social system”, drawing from research on diffusion of innovations (Venkatesh and Davis 2000, p.189). Venkatesh and Davis (2000, pp.189-191) researched that the positive influence of image on PU is significant whether the context of system use is voluntary or mandatory. The reason is, if important members of a person’s social group at work believe that he or she should perform the behavior, then performing it will tend to elevate his or her standing in the group (Venkatesh and Davis 2000, pp.189-191). Pfeffer (1982, p.85) argues that by performing behaviors that are consistent with group norms, an individual will achieve membership and the social support that such membership offers, as well as possible goal attainment which can occur only through group action or group membership. The increased power and influence resulting from increased status provides a general basis for greater productivity. An individual may therefore perceive that using a system will lead to improvements in his or her job performance, which is defined here as PU, indirectly due to image enhancement (Venkatesh and Davis 2000, p.189).

After implementation, when more about the system’s strengths and weaknesses are known through direct experience, the normative influence decreases (Venkatesh and Davis 2000, p.190). Thus, TAM2 researched that the direct effect of SN on intentions for usage is strong prior to implementation and during early usage, but weakens over time (Venkatesh and Davis 2000, pp.190-194). The effect of SN on PU (internalization) weakened as well over time as increasing direct experience with a system provides a growing basis for intentions toward ongoing use (Venkatesh and Davis 2000, pp.190-194).

2.3.2. Cognitive i nstrumental processes

Beyond the social influence processes discussed above, Venkatesh and Davis (2000, p.190) theorized four cognitive instrumental determinants that affect PU and BI: job relevance, output quality, result demonstrability and EOU. These instrumental determinants are based on recent developments in the reference paradigms upon which TAM’s PU construct was originally formulated (Venkatesh and Davis 2000, p.190). These recent developments cutting across action theory, work motivation theory and behavioral decision theory share the view that the impetus for engaging in specific behaviors originates from a mental representation linking instrumental behavior to higher-level goals or purposes. According to this line of argument, TAM2 theorizes that people use a mental representation for assessing the match between important work goals and the consequences of performing the act of using a system as a basis for forming judgments about the use-performance contingency, i.e. PU (Venkatesh and Davis 2000, p.191).

One key component of the matching process is a potential user’s judgment of job relevance. Job relevance is a function of the importance within one’s job of the set of tasks the system is capable of supporting. Over and above considerations of what tasks a system is capable of performing and the degree to which those tasks match the job goals, people take into consideration how well the system performs those tasks, which Venkatesh and Davis (2000, p.191) refer to as perceptions of output quality (Venkatesh and Davis 2000, p.191).The influence of job relevance and output quality on PU was significantly positive in Venkatesh’s and Davis’ research (2000, p.196).

Even effective systems can fail to be accepted if people have difficulty attributing gains in their job performance specifically to the use of a certain system (Venkatesh and Davis 2000, p.192). Result demonstrability is defined by Moore and Benbasat (1991, p.203) as the “tangibility of the results of using the innovation” (Venkatesh and Davis 2000, p.192). TAM2 maintains EOU from TAM as a direct determinant of PU, since, all else being equal, the less effortful a system is to use, the more using it can increase job performance (Davis et al. 1989, p.983; Venkatesh and Davis 2000, p.192). Result demonstrability and EOU have a significant direct influence on PU (Venkatesh and Davis 2000, p.196f.).

At a micro level, IT (Stryker 1968, p.559) focuses on the social roles of people in various social settings (Lam et al. 2010, p.130). The self must be seen as complex and differentiated parts. The parts, which can be used to comprise the self, are discrete identities. You can speak for example, of familial identities, political identities and occupational identities, which are all incorporated into the self. Identities exist because persons are subjects in structured social relationships (Stryker 1968, p.559). The discrete identities are organized hierarchically and these that are high on hierarchy are more salient and form the basis for action (Lam et al. 2010, pp.130-134; Stryker 1968, p.560).

SIT (Tajfel and Turner 1979, pp.34-39) posits that people define their self-concepts by their connections with social groups or organizations (Lam et al. 2010, p.130). Three components typically constitute the identification stage: a cognitive component, an evaluative component and an emotional component. This means a person is aware of a membership, the sense of this awareness is related to some value connotations and there is an affective investment in the awareness and evaluations (Lam et al. 2010, p.130; Tajfel 1982, p.2).

SIT posits that people derive their identity from their affiliations with social groups. They value such membership and differentiate themselves from those who did not share such affiliations, forming the in-group and the out­group. When a social identity is threatened somehow, in-group members will likely respond by choosing one of the three basic strategies: social mobility (SM), social creativity or social change. SM refers to a person’s attempt to part him- or herself from the group. Moving from a lower-status group to a higher­status one is an example (Lam et al. 2010, p.133; Tajfel and Turner 1979, pp.41-43). Social creativity describes a person’s attempt to strive to find positive characteristics for the in-group by redefining or altering the elements of the comparative situation (Lam et al. 2010, p.133; Tajfel and Turner 1979, p.43). Finally, social change refers to direct competition with the out-group to achieve higher status (Lam et al. 2010, p.133; Tajfel and Turner 1979, pp.41-43).

Bhattacharya and Sen (2003, p.77) draw from SIT (Tajfel and Turner 1979, p.34-39) and IT (Stryker 1968, pp.559-564) to propose that customers may develop CCI when sharing the same self-definitional attributes with a company (Lam et al. 2010, p.129). Defined as the extent to which customers perceive themselves as sharing the same self-definitional attributes with the company, CCI builds the substrate for the kind of deep, committed and meaningful relationships that marketers are increasingly seeking to build with their customers (Bhattacharya and Sen 2003, p.76; Lam et al. 2010, p.129).

Some of the strongest consumer-company relationships are based on consumers’ identification with the companies that help them satisfy one or more key self-definitional needs (Bhattacharya and Sen 2003, p.77). CCI suggests that in addition to the number of typical utilitarian values that arise when consumers form a relationship with a company, CCI functions as a higher-order and thus far unarticulated source of company-based value (Bhattacharya and Sen 2003, p.77; Lam et al. 2010, p.129). This value increases the importance of the relationship and results in certain company-directed behaviors that are qualitatively distinct from those typically received in the marketplace (Bhattacharya and Sen 2003, p.77). Identification with organizations can also occur when there is an absence of formal membership (Bhattacharya and Sen 2003, p.76). Furthermore, on the basis of the well-documented, strong, positive consequences of identification, it can be claimed that customers become champions of the companies they identify with (Bhattacharya and Sen 2003, pp.76-77).

Although SIT and IT evolved in different fields (social psychology and sociology, respectively) both theories are closely related to the self-concept literature and both examine the connection between the self and social entities. These theories share several similar concepts that have been introduced into the marketing literature (Bhattacharya and Sen 2003, pp.76-87; Lam et al. 2010, p.130). These theories are appropriate for examining customer-brand relationships because identification has important implications for maintaining relationships (Lam et al. 2010, p.129).

Lam et al. (2010, p.130) draw from these two theories to conceptualize CBI. In doing so, a brand is regarded as a relationship partner that is important to the private self. Individual customers use the brand to define who they are and their social self and consider themselves part of an in-group of customers who identify with the same brand (Lam et al. 2010, p.130). CBI is an extension of CCI to a more micro level research domain - namely brands. This extension is possible because, as concrete realization of the otherwise abstract companies, brands can represent self-relevant social categories with which customers identify and because meaning can be transferred between brands and the self. CBI is defined as a customer’s psychological state of perceiving, feeling and valuing his or her belongingness with a brand (Lam et al. 2010, p.130). According to Ashforth and Mael (1989, p.21) belongingness is used to refer to psychological oneness with a social entity stemming from an actual membership or a symbolic membership (Lam et al. 2010, p.129).

Economists view consumer choices as means to achieve functional utility maximization (FUM) (Lam et al. 2010, p.133). Perceived value (PV) captures a customer’s overall assessment of “the utility of a product based on perceptions of what is received and what is given” (Zeithaml 1988, p.14) and is an important factor for brand loyalty, but not enough to create long-term brand loyalty (Lam et al. 2010, p.128). Therefore, consumer utility and brand switching include not only a brand’s function, but also sociopsychological attributes (Lam et al. 2010, p.133). The branding literature claims that brands can provide self-definitional benefits beyond utilitarian benefits and therefore play an important role in predicting brand switching (Lam et al. 2010, p.129). Building on Tajfel and Turner’s (1979, pp.41-43) theorization of SM, Lam et al. (2010, p.133) propose that customers may switch to another brand for self-enhancement purposes to maximize sociopsychological utility rather than functional utility.

Lam et al. (2010, p.128; Figure 6) therefore proposed a conceptual framework of how the market disruption of the introduction of a radically new brand affects customer-brand relationships and brand switching. The authors diverted from the conventional economic perspective of treating brand switching as FUM to propose that brand switching can result from customer’s SM between brand identities as well. Longitudinal data was collected during the initial launch of the iPhone in Spain to research how relative CBI and relative PV inhibit switching behavior, which is an essential indicator for brand loyalty (Lam et al. 2010, p.128).

The iPhone’s launch was particularly suitable for Lam et al.’s (2010, p.136) research questions for several reasons. First of all, Apple adopted a sequential launch of this new smartphone in various European countries and entered into an exclusive distribution contract with a national service provider in each country. Thus, this launch provided a natural starting point of the disruption to all Spanish customers. Secondly, the reputation of the iPhone brand and the publicity surrounding its launch were unequalled. To generate buzz, Apple and Telefonica engaged in a multiple-communications campaign to promote the new brand. Telefonica is a is a Spanish broadband and telecommunications provider. Third, the cell phone market in Spain was highly competitive and switching costs were high because of long-term contracts. The survey was implemented in five waves. The first wave was conducted two months before the actual launch of the iPhone in Spain and the other four waves were carried out at two-month intervals. The questionnaire was prepared using a 7-point Likert scale (Lam et al. 2010, p.136).

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Figure 6: Conceptual framework of CBI (Lam et al. 2010, p.132)

The conceptual framework of CBI (Figure 6) shows that the introduction of a radically new brand disrupts customer-brand relationships with already existing brands. It represents an attractive alternative, in terms of either brand identity or functional value. When having to choose between the new brand and existing ones, SIT places emphasis on identity-based comparison, while conventional economic and marketing theory focuses on the comparison of functional attributes (Lam et al. 2010, p.133). Lam et al. (2010, p.133) combine these two perspectives to recommend that when a radically new brand is introduced, customers will engage in functional and identity-based comparisons on either functional or sociopsychological value. These two forms of comparison may improve or affect PV and CBI of the incumbent relative to those of the new brand, respectively (Lam et al. 2010, pp.133-134).

2.7.1. Conventional perspective

Lam et al. (2010, p.134) define relative PV as the extent to which the utilitarian value of the functional benefits of a branded offering exceeds those of alternative products.With its relevance to functional utility, relative PV influences switching behavior as FUM (Lam et al. 2010, p.134). PV was measured using four items, tapping into consumer’s perceptions about the benefits after considering the price and other costs incurred for their cell phone (Lam et al. 2010, p.137).

In general, previous research suggested that PV and willingness to buy are positively related (Dodds et al. 1991, p.312; Lam et al. 2010, p.134). However, because a functional utility-based relationship does not reflect a high level of internalization of brand values, it may be more sensitive for change (Lam et al. 2010, p.134). Lam et al. (2010, p.135) suggest that the introduction of a radically new brand motivates customers to engage in functional comparison to compare PV of the incumbent brand with that of the new brand. It is relative PV rather than PV by itself that drives customer switching. Customers base their expectations and following satisfaction on previous experience. Therefore, customers who are familiar with incumbent brands use their existing relationships with those brands as a reference to evaluate new brands (Lam et al. 2010, p.135). Only brands that exceed that reference point on the gain side can cause customers to switch to the new brand. Plus, a great relative PV of the incumbent brand causes a low switching intention (Lam et al. 2010, pp.135­140).

The effect of relative PV on switching does not increase over time even after several repetitions of functional comparison because of resolvability and availability heuristic (Lam et al. 2010, pp.134-140). Resolvability implies that customers believe they can change the situation (Lam et al. 2010, p.134). Judgment based on analytical thinking, such as maximizing functional utility, is likely to be impartial rather than top down in nature. Thus, the current brand is not able to enjoy the biased comparison that would otherwise be available because of identity-driven reasoning (Lam et al. 2010, p.135). Because functional utility is not bonded with the self-identity, it is easier for customers to resolve a relationship that is merely based on a brand’s functional benefits. Availability heuristic refers to the frequency of an event or the likelihood of its occurrence. When customers experience difficulty in generating positive information about a brand, they may conclude that the amount of positive information is quite limited and may reverse their attitude toward the chosen brand (Lam et al. 2010, p.134). In general, information about the new brand is more readily available and more positive than about a longer existing brand. In the course of time, customers may come to think that the positive attributes of the incumbent are limited. This process could affect PV of the incumbent relative to the new brand, making the solvability of the functional utility-based relationship even more obvious after multiple repetitions of functional comparison (Lam et al. 2010, p.135).

2.7.2. SIT perspective

Lam et al. (2010, p.134) draw from Stryker’s (1968, p.560) work to define CBI as the extent to which a customer perceives a focal brand’s identity as having higher self-relevance than the identity of another brand in the same product category. When a customer identifies more strongly with a certain brand than with a competing brand, relative CBI of the focal brand is strong and this brand’s identity is more salient. As SIT and IT posit, only the most salient identity forms the basis for action (Stryker 1968, p.560; Lam et al. 2010, p.134). With its relevance to the self and self-identity, relative CBI influences switching behavior as SM (Lam et al. 2010, p.134).

CBI was measured using six items. The cognitive dimension consisted of two items (Lam et al. 2010, p.136). A Venn diagram that shows the overlap between consumer identity and brand identity and a verbal item to describe the identity overlap in words (Lam et al. 2010, pp.136-137). Lam et al. (2010, p.137) measured consumers’ affective identification with the brand using two items and another two items to evaluate whether the consumer thinks the psychological oneness with the brand is valuable to him or her individually and socially.

The introduction of a radically new brand creates an identity threat to current brands. Even when customers who have identity-based relationships with the incumbents decide to endure, they will cope with the disruption by engaging in identity-based comparison (Lam et al. 2010, p.135). In doing so, these customers are driven by social creativity (Lam et al. 2010, p.135; Tajfel and Turner 1979, p.43). Customers of an incumbent brand engage in motivated reasoning that is biased in favor of the current brand. Social creativity increases the desirability of the incumbent brand’s identity while playing down the attractiveness of the new entrant’s identity. As long as social creativity is successful, customer’s identification with the present brand will dominate their identification with the new brand. When customers experience stronger relative CBI with the incumbent brand, they will consider the incumbent’s identity more salient (Lam et al. 2010, p.135). Because a salient identity forms the basis for behavior in congruence with the identity, these customers remain supportive of their current brand and are less likely switching to the new brand (Lam et al. 2010, pp.135-140; Stryker 1968, p.560).

The effect of the owned smartphone brand’s relative CBI on switching grows stronger over time after several repetitions of identity-based comparison because of irresolvability and social creativity. It is difficult for customers to change their association with a brand identity (Lam et al. 2010, p.134). Customers who identify with the incumbent brand more strongly than with the new brand are likely to attribute their brand choice to the self rather than to superficial functional benefits (Lam et al. 2010, p.135). Because of irresolvability of identity-based relationships with a brand, customers are more likely to bear an existing brand identity and resort to social creativity (Lam et al. 2010, p.134). By repeatedly engaging in social creativity in favor of the incumbent’s brand’s identity, customers maintain the consistency of their self, maintain the identity they deduce from being associated with the current brand and regain their self­esteem without needing to engage in SM (Lam et al. 2010, pp.135-136). Furthermore, although social creativity begins as an illusion of objectivity that biases customers into justifying the superiority of the incumbent brand’s identity to the new brand’s identity, these customers will continue to support the incumbent. This continued supportive behavior makes them believe that the current brand’s identity is indeed superior (Lam et al. 2010, p.136).

Over time, the effect of relative CBI of the incumbent brand on resistance to brand switching grows stronger while that of PV remains stable (Lam et al. 2010, p.136). This leads to the research conclusion of Lam et al. (2010, pp.136­140) that the effect of the relative CBI of the incumbent brand on customer switching to the new brand is stronger than the effect of relative PV of the incumbent brand over time.

2.8. Hypotheses

Based on the research of Lam et al. (2010, pp.134-143) and Venkatesh and Davis (2000, pp.188-200) research on brand loyalty of smartphones and BI of computer systems the research question can be divided in the conventional perspective with the motivation of FUM and the SIT perspective with SM (Lam et al. 2010, p.132).

What are the reasons for brand loyalty of the Apple-iPhone brand in Germany?

Brand loyalty is measured as switching intention, since it is an essential indicator for the loyalty to a brand (Lam et al. 2010, p.128). As described above, the effect of the relative CBI of the incumbent brand on customer switching to the new brand is stronger than the effect of relative PV of the incumbent brand over time (Lam et al. 2010, pp.136-140). Therefore, the assumption arises that CBI has a stronger influence on switching intention than PV:

H1: The lower the switching intention to another smartphone brand,

the greater is the CBI of the Apple-iPhone brand.

H2: The greater the switching intention to another smartphone brand,

the lower is the PV of the Apple-iPhone brand.

Variables can be differentiated as independent and dependent. An independent variable is the assumed cause in a study, while the dependent variable is the assumed effect (Goodwin and Goodwin 1996, p.24). Therefore, switching intention is presumed as being the dependent variable that is affected by the independent variables.



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Title: Investigating and identifying reasons for brand loyalty of the Apple-iPhone brand in Germany