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Multiple value dimensions spill-over - An experimental approach in a consumption system comprising a product and a service

ACCEPTED FOR PUBLICATION IN THE JOURNAL OF CONSUMER BEHAVIOUR

Dr Arne Floh

Surrey Business School

Marketing & Retail Management Group

Guildford, GU2 7XH, UK

E-mail: [email protected]

Assoc. Prof. Monika Koller

WU Vienna

Department of Marketing

Augasse 2-6, 1060 Vienna, Austria


Dr Alexander Zauner

Consultant at marketmind


Prof. Christoph Teller

Surrey Business School

Marketing & Retail Management Group

Guildford, GU2 7XH, UK


Multiple value dimensions spill-over - An experimental approach in a consumption system comprising a product and a service

Abstract

Through the customer’s eyes, wireless telecommunications are a typical example of a so-called consumption system, comprising a product and a service domain. People consume an entity in which multiple value perceptions from both subsystems (wireless service and cell phone) are gained and affect attitudes, intentions and future behaviour within and across the subsystems. Value perceptions are gained along the dimensions of functionality, economic aspects, emotions and social facets, regarding both service and product. Some of those value perceptions spill over, from product to service and vice versa, while others do not. Those that spill over affect value perceptions and loyalty intentions in the other subsystem. These results provide the basis for deriving practical implications for the marketing management of firms operating in such a consumption system. Given the presence of spill-over effects, both parties involved are advised to revise their marketing activities accordingly.

Keywords: spill-over effect; consumption system; perceived value; loyalty

Introduction

“My cell phone provides security. It is there, if I need help.” “My cell phone gives me the opportunity to talk to my friends.” “My cell needs to be pretty, so that I can enjoy watching it.” “Monthly costs of my wireless service contract? I don’t really wanna think about it. As long as the costs are in an acceptable range, I don’t wanna waste time bothering about it.” These statements emerged in a qualitative pre-study we conducted prior to our main experiment presented in this paper. Eleven qualitative in-depth interviews and three focus group discussions were conducted to gain a more comprehensive knowledge of the role of customer-perceived value (e.g., Sweeney & Soutar, 2001) in the consumption system for wireless telecommunications (for more detailed information, see Table 1).

From a consumer perspective, wireless telecommunications are a typical example of a so-called consumption system comprising two components for consumption and usage (products and/or services). A constituent characteristic of a consumption system is that people consume an entity, in this case mobile communication. In other words, the two different components – here, cell phone and network access to wireless communication – must be used simultaneously in order to consume. The frictionless functioning of both components is a necessity, but what if one of the two does not perform satisfactorily? For example, consider a situation in which one needs to make an urgent phone call but there is poor reception. In our qualitative study, the availability of wireless telecommunications in an emergency situation was one of the key themes that emerged in terms of functional value for consumers. Whom will the consumer blame in this situation? Will they blame only the wireless service provider, due to the poor reception? Or might the lack of adequate performance on the service side also affect the consumer’s value perceptions of the cell phone itself? Might this incident have behavioural consequences regarding loyalty intentions – and will it only affect those towards the service provider or also those towards the cell phone manufacturer? Consider also a positive scenario. If one is extremely happy with one’s new cell phone will this happiness with the phone affect the evaluation of the service provider as well?

If critical incidents also have an impact across subsystems[footnoteRef:1] (that is from product to service or vice versa), we speak of a spill-over effect. This spill-over might be positive or negative, depending on the critical incident experienced during consumption. If it is negative, it might harm loyalty intentions towards the unconcerned party, either directly or mediated by a negative impact on value perceptions. In everyday business, manufacturers and service providers are concerned with the direct effects of incidents and activities occurring in their own subsystem. Knowledge of how those incidents impact customer attitudes, evaluations and intentions regarding other parties, external to the subsystem, seems particularly worthy of research attention if an integrated resource allocation for the entire manufacturer/service-provider system is to be ensured. [1: We use the terms components and subsystems interchangeably. Thus, a consumption system such as wireless communications consists of two components or subsystems (cell phone and service network access).]

Hence, a more comprehensive understanding of how customers’ varying value perceptions spill over between product and service may be a crucial piece of information, helping to leverage the competitive success of both parties involved. This is especially true given that the importance of creating superior customer value has been underlined (Grönroos, 1997; O’Cass & Ngo, 2011; Payne & Holt, 2001) and empirical and theoretical evidence broadly confirms the explanatory power of customer value in forming future consumption-related intentions and behaviour (e.g., loyalty) (e.g., Bolton & Drew, 1991; de Matos & Rossi, 2008; Johnson, Herrmann, & Huber, 2006; Parasuraman & Grewal, 2000; Tam, 2004).

The previous literature does not provide comprehensive information on the spill-over effects of value in a consumption system comprising both product and service. There is a literature on spill-over effects regarding perceptions of brands (see, e.g., Janakiraman, Sismeiro, & Dutta, 2009; Lei, Dawar, & Lemmink, 2008; Roehm & Tybout, 2006) but not on spill-over effects in a consumption system along the perceived value–loyalty chain. Our research builds on the consumption-system approach proposed by Mittal, Kumar, and Tsiros (1999), but our focus is on capturing spill-over effects. Moreover, accounting for the spill-over effects of multiple value dimensions is new to the field. Our experimental design tests the spill-over effects of four single value dimensions (functional, economic, emotional, and social), based on the multidimensional conceptualisation of Sweeney and Soutar (2001). We gain insights into whether the firm in the product or that in the service domain is affected the most. Spill-over effects are analysed in both directions, from product to service and from service to product, providing ample managerial implications for managers of both types of business.

Theoretical framework

The theoretical framework is divided into three parts. We start by explaining the concept of consumption systems, and then provide a discussion of the core variables in this study: perceived customer value and customer loyalty. In the last section of the theoretical framework we merge the concept of consumption systems with perceived customer value and customer loyalty. In doing so, we introduce the research model of our experimental study.

Consumption systems

Mittal, Kumar, and Tsiros (1999) were the first to study and define consumption systems as market offerings “characterised by a product and service component, as well as a pattern of consumption in which consumption occurs in multiple episodes over time”. Whereas they focused on a product and a service component, we claim that this definition is too narrow and can easily be extended to product-product or service-service combinations as well. The first constituent characteristic of a consumption system is the inseparability of its components. Two or more components are necessary for usage and consumption. The second characteristic of a consumption system is the simultaneous usage of its components. For example, a cell phone can only be used if a wireless telecommunications network is available (and vice versa). Usage is only possible if both components work simultaneously. These characteristics make consumption systems different from product, service, and product-service bundles. Bundles only require sequential usage of their components. In order words, a consumption system is a special case of a bundle. Table 1 summarizes the conceptual differences between consumption systems and bundles and gives some illustrative examples.

[INSERT TABLE 1 ABOUT HERE]

Customer-perceived value

The current literature on customer-perceived value accounts for the multilayer effects of value on post-consumption behaviour such as loyalty or word of mouth (Sánchez-Fernández & Iniesta-Bonillo, 2006). The change to a multidimensional conceptualisation of customers’ value perceptions has significantly enhanced the knowledge output gained from value studies. Traditionally, perceived value has been conceptualised as a cognitive trade-off, in which only functional aspects (e.g., price and utility) are considered (Bolton & Drew, 1991; Sinha & DeSarbo, 1998). This conceptualisation of perceived value falls short of tapping into its emotional facets. Recent studies, however, have underlined its multidimensionality, emphasising the relevance of social or hedonic perspectives (e.g., enjoyment) (Petrick, 2002, 2004; Sweeney & Soutar, 2001). The importance of conceptualising value along emotional as well as cognitive dimensions (Holbrook, 1994; Sánchez-Fernández, Iniesta-Bonillo, & Holbrook, 2009; Sheth, Newman, & Gross, 1991) is backed up by recent experimental evidence underlining the predominant role emotions play in forming humans’ attitudinal perceptions (Phelps, 2009). Cognitive aspects of perceived value comprise functional value (performance/quality) as well as economic value (price/value for money). The emotional aspects are emotional value and social value. Whereas there is already ample empirical evidence of the existence of a link between perceived value and loyalty (Cronin, Brady, & Hult, 2000; Ulaga & Chacour, 2001), previous literature has not investigated the effects of multiple value dimensions on loyalty intentions in a consumption system comprising products and services. A better understanding of the complex relations in the value–loyalty link in a consumption system would contribute to better-informed managerial decisions. The various dimensions of perceived customer value are defined in Table 2.


Spill-over effects in a consumption system: The case of mobile communications

In today’s consumption society, there are many products and services that can only be properly consumed in combination, thus representing consumption systems (Mittal, Kumar, & Tsiros, 1999). As pointed out previously, the frictionless interplay of the two or more components is a necessity for a positive consumption experience. Theoretically, these interactions between components are founded on General Living Systems Theory (Miller, 1981). According to the theory, complex phenomena comprise different subsystems, which are integrated, self-regulating, overlapping and, hence, interrelated (Reidenbach & Oliva, 1981).

Based on this notion, we disentangle the spill-over effect into a direct and an indirect effect using the perceived value–loyalty chain. In the context of mobile communications, we propose a direct spill-over effect from product value on to service loyalty, another from service value on to product loyalty, and an indirect effect on loyalty via the corresponding perceived value. In this regard, a product-induced spill-over effect implies that perceived product value affects value perceptions of the service as well as behavioural intentions towards the service provider. Similarly, a service-induced spill-over effect implies that perceived service value affects value perceptions of the manufacturer as well as behavioural intentions towards the manufacturer. The different types of spill-over effects are represented graphically in Figure 1.

[Insert Figure 1 About Here]

The theoretical underpinnings of the assumption of such spill-over effects are grounded in the notion of a preference for consistency, which is inherent in human beings from a psychological perspective. Beckwith and Lehmann (1975) suggest that spill-over effects reflect the individual’s tendency to maintain cognitive consistency. A preference for consistency (Cialdini, Trost, & Newsom, 1995) leads individuals to adjust their perceptions of related attributes so that they appear in a manner perceived to be internally consistent. The existence of spill-overs in consumption systems can be explained by these mental mechanisms. The information or perception transfers ensure that balance is retained among the cognitive and emotional elements throughout the entire consumption system.

Another perspective for explaining spill-over effects is Feldman and Lynch’s (1988) accessibility–diagnosticity framework (see also Janakiraman, Sismeiro, & Dutta, 2009; Roehm & Tybout, 2006). The authors suggest that, if a consumer believes that Product A is informative (diagnostic) about Product B, the consumer will use his or her perceptions of Product A’s value to help infer the value of Product B. This spill-over only occurs when both objects and their value evaluations are retrieved from memory (accessible) simultaneously. Accessibility and diagnosticity, and hence the extent of potential spill-overs, depend on whether the offerings are associated in the consumer’s memory and how strong the association is (Janakiraman, Sismeiro, & Dutta, 2009).

Although we account for spill-overs in both directions (from product to service and vice versa), it is assumed that the spill-over from the product to the service subsystem is much more pronounced than the spill-over in the other direction. This is reflected in the emotional attachment theory regarding products and services (Thomson, MacInnis, & Park, 2005; Yim, Tse, & Chan, 2008).

Services are performances. They are intangible and, compared to products, more difficult to capture directly with human senses. This is especially true for continuously provided services such as wireless telecommunications. Although the sound quality of the voice and the display of visuals are obviously projections of the underlying service delivery, the consumer’s perception of those services is solely enabled through the cell phone. It is much easier to capture the inherent characteristics of products using human senses. Impressions such as texture, sound and shape directly elicit emotions (Hansen & Christensen, 2007). As with cell phones, touch is a very dominant human sensory modality that comes into play. Typing and swiping almost 24/7, carrying the phone as an essential accessory to their daily routines provides consumers with tactile impressions, elicited by their phones, on a continuous basis. As this has grown into almost automated behaviour, those tactile impressions are not always necessarily perceived on a conscious level. However, they are there and shape consumers’ evaluations of the product. Peck and Shu (2009) found that merely touching an object increased perceived ownership of that object. Tightly connected to perceived or actual ownership of a product is emotional attachment to it. Perceived ownership, along with a certain affective reaction, integrates into the concept of emotional attachment to a product. Especially with consumption objects such as products or brands, consumers tend to be emotionally attached (Thomson, MacInnis, & Park, 2005; Yim, Tse, & Chan, 2008). The degree of emotional attachment determines the nature of an individual’s interaction with the object (Thomson, MacInnis, & Park, 2005). At the same time, emotional attachment can be seen as one important driver of loss aversion (Shu & Peck, 2011).

Given the enhanced sensory impressions stemming from the product, as well as the concept of emotional attachment, the spill-over effect from the product to the service side is predicted to be much more pronounced.

Qualitative pre-study

Prior to the main (quantitative) study, a series of qualitative interviews and focus groups with customers of a large European telecommunications company was conducted. All interviews and focus groups were audio-recorded and transcribed afterwards. The main objective of this study was (a) to explore and validate the theoretically derived multidimensionality of customer-perceived value, (b) to adapt the original scale from Sweeney and Soutar (2001) to the context of mobile telecommunications and (c) to develop the scenarios for the experimental conditions. An overview of the qualitative pre-study is given in Table 3.


A key finding of the qualitative pre-work is the substantiation of the relevance of a multidimensional conceptualisation of customer-perceived value in the case of wireless telecommunications. In both the product and service subsystems, functional, economic, emotional and social value facets turned out to be issues. However, when reflecting on the consumption system, interviewees in our qualitative pre-study tended to talk primarily about their cell phones, with statements about their current wireless service only given after the interviewer had actively asked for them. This provides the first empirical indicator that the two subsystems might hold asymmetric relevance for the consumers.

Methodology

In the present study, the multidimensional framework of perceived value is applied as the theoretical underpinning (Sweeney & Soutar, 2001) in an experimental setting. The effects of the four value dimensions (economic, emotional, functional and social), experimentally manipulated in each of the subsystems in turn, on the value perceptions and loyalty intentions in the other subsystem, are investigated. Perceived value is manipulated either positively (providing high value) or negatively (providing low value) along the four dimensions. The rationale for doing so is to draw a holistic picture of possible customer experiences. Following prospect theory, the impact of a negatively framed experience, in terms of a loss in perceived product value, should be much more pronounced than that of a positively framed experience (a gain in product value) (Kahneman & Tversky, 1983). Literature on the negativity effect also substantiates the greater power of bad events over good ones (Baumeister, Bratslavsky, Finkenauer, & Vohs, 2001).

Procedure

The experiment followed a scenario-based approach. The rationale for doing so was to provide a common baseline for all participants. At the beginning of the experiment, all respondents were asked to read a scenario. In this scenario, the participants were told to imagine that they had recently entered into a contract with a wireless service provider and had bought a new cell phone as part of the contract. This usage report about the service provider (or the cell phone, respectively) was presented to the respondents in the experimental groups and control groups alike. The report was framed as either positive (providing high service value in groups 1-5 or high product value in groups 11-15) or negative (providing low service value in groups 6-10 or low product value in groups 16-20). Afterwards, the main stimulus (a specific usage report about the cellular phone or the service, respectively) was presented to the experimental groups only (for an example of the wording of these usage reports, see Appendix A). This stimulus was manipulated for the four value conditions and presented as either positive (high product value / high service value) or negative (low product value / low service value) in a between-subjects design.

[INSERT TABLE 4 ABOUT HERE][

Data collection

Data collection was administered via an online experiment at a large European business school. A total of 1,392 participants were randomly assigned to one of sixteen treatment or four control groups (see Table 4). 51.2% of the participants were female and 48.8% male, with a mean age of 24.56 years (Min: 20.51; Max: 32.82). Participants had to indicate their value perceptions (the dependent variables) along the four dimensions (functional, economic, emotional and social) as well as their loyalty intentions towards the service or product subsystem.

Measurement properties

Perceived value and loyalty were measured with multiple-item scales, adapted from the literature. The items measuring loyalty intentions were based on Johnson, Herrmann, and Huber (2006). Perceived value was measured using a scale based on Petrick (2002) and Sweeney and Soutar (2001). For the answer formats, a nine-point rating scale, with end points verbalised as “strongly agree” (scored 1) and “strongly disagree” (scored 9), was used throughout the experiment.

Regarding the measures of the respective latent constructs, all factor loadings were highly significant (p<0.001) and exceeded the suggested threshold of 0.5, demonstrating a high level of convergent validity in the measurement model (Dunn, Seaker, & Waller, 1994). Complying with the thresholds suggested by Bagozzi and Yi (1988), the average variance extracted and composite reliability scores suggest a high level of internal consistency (see Table 5). Regarding the measures used for the respective value dimensions and loyalty, discriminant validity is of particular importance as measures of perceived value and customer loyalty tend to be highly correlated. Thus, we assessed the discriminant validity between perceived value and customer loyalty, by performing a chi-square difference test, comparing the unconstrained model to the constrained one with the interconstruct correlation set to one. The differences in the chi-squares were significant for all models, indicating that the perceived value measures were empirically distinct from the customer loyalty intentions. As it was an experimental setting, value perceptions in a subsystem were not measured directly but were experimentally manipulated through a verbal stimulus (see Appendix A). Hence, unlike in traditional structural equation modelling approaches, common method bias is not an issue in the present study.


Control checks

A manipulation check of the scenario (general usage report) was conducted to check whether the stimuli generated the intended responses. After reading the scenario, participants had to answer the question “How do you evaluate the situation described?” on a five-point rating scale ranging from positive (scored 1) to negative (scored 5). The ratings given by the different groups were compared. The scenarios for conditions 1 to 5 (high service value) and 6 to 10 (low service value) were manipulated successfully, as shown by the following test results: M high service value = 1.61, M low service value = 4.50; T (647)= - 42.91, p<0.001. The same control check was conducted for the product side, and again the scenarios were manipulated successfully: M high cell phone value = 1.82, M low cell phone value = 4.54; T (704) = - 40.59, p<0.001.

Manipulation checks were also conducted for the main stimuli (specific usage reports). After reading the usage report, participants had to answer the question “How do you evaluate the situation described?” on a five-point rating scale ranging from positive (scored 1) to negative (scored 5). The stimuli for experimental conditions 1 to 4 (low cell phone value) and 6 to 9 (high cell phone value) were manipulated successfully (M low cell phone value = 4.37, M high cell phone value = 1.86; T (499) = 30.75, p<0.001), as were those for experimental conditions 11 to 14 (low service value) and 16 to 19 (high service value): M low service value = 4.46, M high service value = 1.82; T (592) = 35.36, p<0.001).

Results

We calculated sixteen structural models to compare the results of the sixteen manipulations and four corresponding control groups (Baron & Kenny, 1986; Iacobucci, Saldanha, & Deng, 2007). Using James, Mulaik, and Brett’s (2006) procedure, we compared the direct and mediated effects simultaneously within one structural model (mediation analysis). Each manipulation group represented one of the four underlying perceived value dimensions (economic, functional, emotional and social) (see Table 4 for the experimental design). To test for the significance of the mediated effects, we applied the bias-corrected bootstrap approach (MacKinnon, Lockwood, & Williams, 2004; Zhao, Lynch, John, & Chen, 2010) (see Appendix B).

Spill-over of product on to service

The spill-over from the product (perceived value of the cell phone) on to the service (perceived value of the wireless service and loyalty towards the service provider) turned out to be present in five out of eight groups (see Figures 1 and 2).

[INSERT FIGURE 2 ABOUT HERE]

For the high-service-value groups, the manipulations of the economic (ß = -0.15, p = 0.049), emotional (ß = -0.16, p = 0.039) and functional (ß = -0.2, p = 0.015) value of the cellular phone led to significant mediated effects on the loyalty intentions towards the service provider (for the calculations of the mediated effects and the bootstrapping results, see Appendix B). In contrast, social value had no significant impact. The analyses of the structural equation models revealed a marginally significant direct spill-over effect on to loyalty towards the service provider due to the manipulations of emotional value (ß = -0.11, p < 0.1) and functional value (ß = -0.13, p < 0.1). Hence, the impact of economic value on loyalty intentions towards the service provider is fully mediated by service value (complete mediation), and the effects of emotional and functional value on service loyalty are characterised by partial mediation.

For the low-service-value group (see Figure 2), only the mediated effects of economic (ß = 0.18, p = 0.035) and functional (ß = 0.14, p < 0.1) value are significant (for the calculations of the mediated effects and the bootstrapping results, see Appendix B). These results indicate that a poorly performing cell phone may lead to more severe consequences for the service provider than a well-performing cell phone is able to contribute under lousy service conditions. There is also no direct path from either of the cell phone value dimensions to the loyalty intentions towards the service provider.


Under conditions of low service value (see Figure 4), only the cognitive aspects of a well-performing cell phone may be able to enhance service loyalty, and even then they will be mediated by functional and economic service value. A poor wireless service cannot benefit from positive value perceptions of a cell phone when those perceptions are of emotional and social aspects.

Spill-over of service on to product

For the groups with high cell phone value (see Figure 3), only the manipulations of the economic (ß = -0.22, p = 0.001) value of the wireless service led to a significant mediated effect on the loyalty intentions towards the cell phone manufacturer (for the calculations of the mediated effects and the bootstrapping results, see Appendix B).


Interestingly, there is also a significant direct effect from the perceived functional value of the wireless service on to loyalty towards the cell phone manufacturer (ß = -0.15, p = 0.033). These results underline the predominant importance of cognitive value facets in the service subsystem (functionality and price-related aspects). In contrast, none of the remaining value dimensions of the wireless service had a significant impact on the loyalty towards the cell phone manufacturer, either directly or mediated via cell phone value. If the perceived value of the cell phone is high, negatively perceived incidents regarding the emotional or social value of the service components cannot harm loyalty intentions towards the cell phone.

For the groups with low cell phone value (see Figure 4), only the mediated effects of the economic (ß = 0.2, p = 0.005) and emotional (ß = 0.16, p = 0.042) value of the wireless service were found to have a significant impact on loyalty towards the cell phone (see Figure 4; for the calculations of the mediated effects and the bootstrapping results, see Appendix B). None of the value dimensions of the service directly impacted the product side. These results again underline the predominant position of the product in the consumption system of wireless services.


Conclusions and discussion

The results of the online experiment provide evidence of the existence of the assumed spill-over effects from the product subsystem to the service subsystem and vice versa. They also show the conditions under which customer loyalty towards the service provider or the cell phone manufacturer is affected. The findings suggest several theoretical implications. They underline the importance of conceptualising customer-perceived value as a multidimensional concept. The four value dimensions have varying degrees of impact on loyalty intentions. Both cognitive and emotional facets should be included when measuring consumers’ value perceptions and their effects on post-consumption intentions. Regarding research on consumption systems that comprise both products and services, accounting for potential spill-over effects at a multidimensional level is a necessity. As expected, the spill-over from the product side (cell phone) on to the loyalty intentions towards the firm on the service side (wireless service provider) is much more pronounced. Negative experiences with the mobile phone turn out to have a greater effect on the value perceptions and loyalty intentions towards the service provider than positive ones. This product dominance may have harmful consequences for the service provider. Both cognitive and emotional aspects of value, gained in the product subsystem, reflect onto the service side. This is especially the case if the product performs poorly. These findings add an important facet to the field of research on attachment and prospect theory. Our study is the first to provide empirical evidence of the relevance of attachment and prospect theory for explaining the spill-over effect of value on to loyalty in consumption systems. Moreover, we identify the influence of single value dimensions and therefore expand knowledge in the attachment literature stream. In doing so, we have advanced knowledge by combining theoretical aspects of attachment and prospect theory, perceived customer value, and spill-over effects in consumption systems.

The results gained from this approach suggest ample practical implications for marketers. Being aware of these effects could be crucial for a mobile service provider. If the cell phone performs poorly, there is a negative spill-over on to the service side, even when an excellent wireless service is provided. In contrast, the service provider can only benefit from positive perceptions of a cell phone’s economic and functional value and not from the emotional value a consumer gains from his or her cell phone. Overall, the relevance of the cell phone’s economic value is highlighted, whether this value is positive or negative. The results indicate that a service provider has more to lose than win. Poorly performing devices, directly (in two of the groups) and mediated via service value (in three of the groups), were found to have an impact on perceived service value and, even more importantly, on customers’ loyalty intentions towards the service provider. Yet, it is only in terms of functionality/quality that well-performing cellular phones contribute positively to customers’ evaluations of their wireless services.

Regarding the spill-over from the service to the product subsystem, the picture is slightly different. If the service performs poorly in terms of economic aspects, the loyalty towards the cell phone manufacturer is also significantly and negatively altered – not directly but mediated via a negative impact on the perceived economic value of the cell phone. Interestingly, under conditions in which the cell phone performs poorly, a well-performing wireless service (in terms of the economic and emotional aspects) can significantly and positively impact loyalty towards the cell phone manufacturer. Again, these effects are not direct but mediated via the perceived value of the cell phone.

All in all, the online experiment provided evidence of the existence of the assumed spill-over effects within the consumption system of wireless telecommunications. This finding is crucial for all commercial players in this consumption system. There are situations in which the consumer’s value perceptions in the two subsystems interplay and thus may affect loyalty towards the respective counterpart. In general, this may lead to positive effects as long as the subsystems can benefit from the positive aspects of their counterparts. On the other hand, it may have significantly harmful effects if the respective counterpart performs poorly in various value dimensions. Bearing these results in mind, the marketers of a firm offering wireless services should not only strive to offer outstanding service value to the firm’s customers but also always have an eye on how their mobile phones are evaluated. Neglecting the potential spill-over effects in the consumption system of wireless telecommunications could have a long-term negative impact if those spill-over effects alter the loyalty intentions of the customers. From a managerial perspective, a comprehensive knowledge of the dynamics involved in the consumption system of wireless telecommunications will become even more important in the near future. According to the International Data Corporation (IDC, 2011), vendors shipped a total of 100.9 million smartphones during the fourth quarter of 2010. Following a recently published report from Cisco (2011), mobile data traffic is currently increasing by 83% per year in the US and by 92% per year in Western Europe. Given this extremely fast-growing market and increasingly competitive landscape, having a better understanding of the antecedents of customer loyalty is vital from the perspective of a firm operating in the consumption system of wireless telecommunications. Spill-over effects may not only be present between cell phone and service but also between other products, such as tablet PCs or laptop computers, and wireless data services. To conclude, the present study contributes to the literature on the link between perceived value and loyalty. It expands the knowledge of the multidimensional impact of perceived value as well as that of the potential spill-over effects in a consumption system. The results of the present study are based on value perceptions from a consumer’s perspective. Future research might also incorporate the perspectives of the firms operating in a consumption system. Taking firms’ perspectives into account as well as consumers’ may enable us to derive more in-depth implications for corporate strategic marketing within consumption systems.

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2

Table 1 Types of consumption systems

Components

Consumption System (Simultaneous Usage)

Bundle (Sequential Usage)

Product-Product

Compact Disc & Compact Disc Player

Car & Car Repair

Product-Service

Wireless Telecommunications Network & Cell Phone

Computer & Warranty

Service-Service

Software as a Service

Cloud & Third Party Software

Table 2 Dimensions of Customer-Perceived Value

Dimension

Definition

Sample statement from the qualitative study

Emotional Value

The utility derived from the feelings or affect states that a product generates.

“…My cell needs to be pretty, so that I can enjoy watching it…”

Social Value (enhancement of social self-concept)

The utility derived from the product’s ability to enhance social self-concept

“…My cell phone gives me the opportunity to talk to my friends…”

Economic Value (price/value for money)

The utility derived from the product due to the reduction of its perceived short-term and longer-term costs

“… I don’t really care about the price of my cell phone, as long as the costs are in an acceptable range…”

Functional Value (performance/quality)

The utility derived from the perceived quality and expected performance of the product

“…My cell phone is very reliable. It is there if I need help…”

Source: Adapted from Sweeney and Soutar (2001)

Table 3 Qualitative pre-work

Method

Setting

Aim

Key findings (themes that emerged)

Qualitative in-depth interviews

11

6 female, 5 male

Age: 27 to 71

Exploratory approach to gain a more comprehensive understanding of the existence and relevance of the four value dimensions in the consumption system of wireless telecommunications

Cell phones are the predominantly perceived component of the consumption system. Functional, emotional and social value components are important. Moreover, design and aesthetic aspects as well as satisfying curiosity turned out to be issues.

Overall findings: multidimensional conceptualisation existent in wireless telecommunications; phone is predominant; service is more like a commodity: basic values have to be fulfilled, but compared to the product subsystem, no excitement is elicited.

Focus group discussion

(moderated based on semi-structured interview guide)

3

FG 1: 8 participants



Age: 20 to 45

Average duration: 120 minutes; transcribed, analysed with qualitative content analysis

Table 4 Experimental design

Group

Sample size

Scenario: general usage report

Main stimulus: specific usage report

1

n=76

High service value

Low cell phone value - economic

2

n=59

High service value

Low cell phone value - functional

3

n=70

High service value

Low cell phone value - emotional

4

n=66

High service value

Low cell phone value - social

5 control

n=54

High service value

no stimulus

6

n=53

Low service value

High cell phone value - economic

7

n=67

Low service value

High cell phone value - functional

8

n=76

Low service value

High cell phone value - emotional

9

n=63

Low service value

High cell phone value - social

10 control

n=65

Low service value

no stimulus

11

n=77

High cell phone value

Low service value - economic

12

n=65


Low service value - functional

13

n=86


Low service value - emotional

14

n=65


Low service value - social

15 control

n=75


no stimulus

16

n=78

Low cell phone value

High service value - economic

17

n=68


High service value - functional

18

n=81


High service value - emotional

19

n=89


High service value - social

20 control

n=59


no stimulus

Table 5 List of items and measurement properties

Measures

Service value high – product value low

Service value low – product value high

Product value high – service value low

Product value low – service value high

FL

AVE

CR

FL

AVE

CR

FL

AVE

CR

FL

AVE

CR

Economic Value

0.80

0.89

0.94

0.97

0.84

0.91

0.87

0.93

... is fairly priced

0.895

0.983

0.864

0.881

... offers value for money

0.892

0.958

0.966

0.977

Loyalty (induced economic value)

0.78

0.87

0.88

0.94

0.85

0.92

0.80

0.89

I consider the … my first choice

0.850

0.931

0.865

0.846

Likelihood of repurchasing …

0.912

0.946

0.977

0.945

Functional Value

0.71

0.83

0.78

0.87

0.60

0.75

0.78

0.88

... is very reliable

0.743

0.807

0.736

0.784

... is of a high technical standard

0.932

0.949

0.808

0.975

Loyalty (induced functional value)

0.80

0.89

0.87

0.93

0.77

0.87

0.82

0.90


0.841

0.903

0.866

0.922


0.945

0.966

0.884

0.887

Emotional Value

0.83

0.91

0.89

0.94

0.84

0.91

0.88

0.94

... inspires me

0.972

0.927

0.921

0.946

... gives me pleasure

0.845

0.962

0.913

0.929

Loyalty (induced emotional value)

0.77

0.87

0.84

0.91

0.79

0.88

0.81

0.90


0.889

0.930

0.918

0.918


0.871

0.904

0.861

0.884

Social Value

0.66

0.80

0.78

0.87

0.87

0.93

0.89

0.94

... improves the way I am perceived

0.784

0.870

0.978

0.931

... gives its owner social approval

0.842

0.892

0.884

0.957

Loyalty (induced social value)

0.73

0.84

0.83

0.91

0.82

0.90

0.80

0.89


0.804

0.844

0.857

0.942


0.898

0.978

0.950

0.849

Note: FL = factor loading. AVE = average variance extracted. CR = composite reliability.

Figure 1 Research Model

Service spill-over effect on ProductProduct spill-over effect on Service

Note: Solid lines represent direct spill-over effects and dotted lines represent indirect spill-over effects.

Figure 2 High service value – low cell phone value (groups 1–5)

Figure 3 Low service value – high cell phone value (groups 6–10)

Figure 4 High cell phone value – low service value (groups 11–15)

Figure 5 Low cell phone value – high service value (groups 16–20)

Note: Numbers in parentheses are t-values. Solid lines represent significant paths and dotted lines represent non-significant paths. Induced values (economical, functional, emotional, and social) are coded as 0 and no stimulus (control group) as 1. ECV=Economical value, FUV=Functional Value, EMV=Emotional value, SOV=Social value, LOY=Loyalty. This also applies to the other groups, depicted in Figures 2 to 4.

Appendix A General usage reports and main stimuli (examples)

Usage Report - Wireless Telecommunication Service

Main Stimuli - Cellular Phone

High

High - Emotional Value

The service from your wireless telecommunication carrier always works properly and you can rely on the network whenever required. The services are fun and can be used without any worries. You use the services of your provider frequently and with pleasure. Compared to competing offers, the cost of the service is low. Many of your friends are with the same provider and comment very positively on the same aspects. You have the impression that your service provider has a good reputation. On a personal level, you may even benefit from the “hip” reputation of your service provider.

It is truly enjoyable to use your cellular phone. The ability to take pictures and shoot movies of nice moments is fun. You are thrilled by the phone’s multi-functionality, which makes life much easier. You feel better organised, thanks to features such as the calendar or e-mail. The cell phone increases your flexibility and availability. You can hardly live without the device and you like to have it readily available at all times.

Low

Low - Functional Value

The services of your wireless telecommunication carrier are tedious and cannot be used without worry. The service provider does not offer any value-added services, which could improve the user-experience. Compared to competing offers, the cost of the service is high. A lot of your friends discouraged you from using this service provider and their advice was right. You even hesitate to tell them about your decision to subscribe with this service provider. In general, the services of your carrier are unreliable and not user-friendly.

Your cell phone troubles you repeatedly. It often turns off without any warning. You cannot fully rely on it, which is very important for you. Also, the battery life should be better. The device lacks several convenient features which are of increasing interest to you. The cell phone is complicated and not really user-friendly. It is of poor quality and the technical standard is average at best.

Appendix B Results of mediation analysis (bootstrapping)

High Service Value - Low Cellular Phone Value

ECV low

p-value

FUV low

p-value

EMV low

p-value

SOV low

p-value

Induced cell phone value > Service value

-0.180

0.046

-0.233

0.010

-0.190

0.039

-0.120

0.222

Induced cell phone value > Service loyalty

-0.050

0.422

-0.130

0.075

-0.110

0.059

-0.020

0.000

Service value > Service loyalty

0.840

0.000

0.840

0.005

0.860

0.000

0.810

0.764

Induced cell phone value > Service loyalty MEDIATION

-0.154

0.049

-0.195

0.015

-0.161

0.039

-0.101

0.231

BC Lower Bound

-0.276

-0.334

-0.287

0.231

BC Upper Bound

-0.024

-0.064

-0.032

0.037

Low Service Value - High Cellular Phone Value

ECV high

p-value

FUV high

p-value

EMV high

p-value

SOV high

p-value

Induced cell phone value > Service value

0.197

0.032

0.155

0.087

0.108

0.209

0.112

0.235

Induced cell phone value > Service loyalty

-0.023

0.656

0.030

0.528

-0.030

0.466

-0.004

0.937

Service value > Service loyalty

0.896

0.000

0.910

0.000

0.951

0.000

0.924

0.000

Induced cell phone value > Service loyalty MEDIATION

0.176

0.035

0.141

0.084

0.103

0.207

0.104

0.219

BC Lower Bound

0.038

0.007

-0.033

-0.039

BC Upper Bound

0.307

0.276

0.232

0.244

High Cellular Phone Value - Low Service Value

ECV low

p-value

FUV low

p-value

EMV low

p-value

SOV low

p-value

Induced service value > Cell phone value

-0.353

0.005

0.066

0.496

-0.072

0.382

-0.138

0.107

Induced service value > Cell phone loyalty

0.066

0.376

-0.148

0.033

0.027

0.578

-0.073

0.298

Cell phone value > Cell phone loyalty

0.618

0.003

0.848

0.000

0.917

0.000

0.649

0.000

Induced service value > Cell phone loyalty MEDIATION

-0.218

0.001

0.056

0.519

-0.066

0.381

-0.090

0.104

BC Lower Bound

-0.316

-0.084

-0.190

-0.182

BC Upper Bound

-0.133

0.215

0.058

0.001

Low Cellular Phone Value - High Service Value

ECV high

p-value

FUV high

p-value

EMV high

p-value

SOV high

p-value


0.241

0.005

-0.005

0.954

0.175

0.043

0.041

0.629


-0.002

0.969

0.093

0.095

0.002

0.963

-0.042

0.531

Cell phone value > Cell phone loyalty

0.817

0.000

0.862

0.000

0.909

0.000

0.686

0.000

Induced service value > Cell phone loyalty MEDIATION

0.197

0.005

-0.005

0.975

0.159

0.042

0.028

0.719

BC Lower Bound

0.095

-0.133

0.038

-0.067

BC Upper Bound

0.335

0.146

0.314

0.119

Perceived ProductValuePerceived ServiceValueProductLoyaltyProduct SubsystemService SubsystemPerceived ProductValuePerceived ServiceValueService LoyaltyProduct SubsystemService Subsystem

Induced ECV

Cell Phone

ECVWireless

Service

-.18 (-1.992).84(9.362)-.05 (-.803)Induced SOV

Cell Phone

-.12 (-1.222).81(6.615)-.02 (-.300)LOYWireless

Service

SOVWireless

Service

LOYWireless

Service

Induced FUV

Cell Phone

-.23(-2.322).84(7.533)-.13 (-2.027)FUVWireless

Service

LOYWireless

Service

Induced EMV

Cell Phone

-.19 (-2.063).86(11.253)-.11 (-1.885)EMVWireless

Service

LOYWireless

Service

χ2 (df) = 2,285(3)χ2 (df) =2,119 (3)χ2 (df) =5,344 (3)χ2 (df) =1,971 (3)

Induced ECV

Cell Phone

.20(2.144).90(14.786)-.02 (-.446)Induced SOV

Cell Phone

.11(1.188).92(10.384).00(-.079)ECVWireless

Service

LOYWireless

Service

SOVWireless

Service

LOYWireless

Service

Induced FUV

Cell Phone

.16(1.711).91(10.811)

.03(.631)

FUVWireless

Service

LOYWireless

Service

Induced EMV

Cell Phone

.11(1.256).95(16.976)-.03(-.728)EMVWireless

Service

LOYWireless

Service

χ2 (df) = 2,893 (3)χ2 (df) =4,665 (3)χ2 (df) =3,549 (3)χ2 (df) =2,138 (3)

Induced ECV

Service

ECVCell

Phone

-.35(-4.290).62(6.618).07 (.885)Induced SOV

Service

-.14(-1.610).65(7.174)-.07(-1.040)LOYCell

Phone

SOVCell

Phone

LOYWireless

Service

Induced FUV

Service

.07(.680).85(7,397)-.15(-2,127)FUVCell

Phone

LOYCell

Phone

Induced EMV

Service

-.07(-.874).92(15.051).03(.557)EMVCell

Phone

LOYCell

Phone

χ2 (df) = ,750 (3)χ2 (df) =4,886 (3)χ2 (df) =4,235 (3)χ2 (df) =9,476 (3)

Induced ECV

Service

.24(2.800).82(9.559)-.00(-.038)Induced SOV

Service

.04(.483).69(9.313)-.04(-.627)ECVCell

Phone

LOYCell

Phone

SOVCell

Phone

LOYCell

Phone

Induced FUV

Service

-.01(-.058).86(9.986).09(1.670)FUVCell

Phone

LOYCell

Phone

Induced EMV

Service

.18(2.023).91(14.660).00(.046)EMVCell

Phone

LOYCell

Phone

χ2 (df) = ,856 (3)χ2 (df) =4,172 (3)χ2 (df) =6,333 (3)χ2 (df) =1,071 (3)

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