Abstract - Customer needs are increasingly fulfilled by a

seamless integration of products and services. Complexity grows for firms to understand customers since their perception of firm performance can be affected by either product manufacturers or service providers. Our study is attempting to identify possible spillover effects of quality and customer satisfaction between products and services. Potential moderators such as affective commitment and consumer knowledge will also be examined. Our discussion shows that firms working closely together in delivering solutions to customers need to consider the influence of their partner’s product or service quality and satisfaction level as well. This may enhance understanding of customer satisfaction and loyalty of their own companies.

Keywords – Associative networks, loyalty, quality,

satisfaction, spillover.

I. INTRODUCTION Companies are constantly searching for better ways to

sustain competitive edge. In their seminal work, Vargo and Lusch [1] claimed that the entire business environment is increasingly shifting from the traditional tangible goods exchange to mostly intangible, knowledge-intensive service offerings. They urge both practitioners and scholars to adopt a service-dominant (S-D) logic, which redefines the role of goods as a distributional mechanism for services and emphasizes that value can only be realized by consumption of products or services or both. Thus, in the cases where the effective use of a product relies on the service as much as on the product itself, it is crucial to ensure the seamless integration of them. Poor quality in either products or services can deteriorate the overall value.

A typical industry is the mobile telecommunications where a communication experience requires both a handset and a network to properly function simultaneously. Moreover, latest advancement has witnessed that a third component, software applications, is increasingly important in this “ecosystem”. Usually installed in a smartphone, these applications can turn a handset into a multipurpose device, such as GPS, music player, web browser and many others which may be beyond our imagination. However, none of these phenomena has been fully addressed in the quality and customer satisfaction literature although this stream of research has been proceeding for nearly three decades. Adequate understanding of the quality, customer satisfaction and loyalty link has mostly been shown in a single firm, or pure service, or pure product context; however, studies on

managing both products and services and their synergy effects are rare. With more parties, either within the same organization or from different organizations, collectively proposing value-in-use, such as recent entrance of mobile applications providers, the complexity of understanding and maintaining customer relationship is sure to magnify. Moreover, the importance of addressing this gap is further underscored by the fact that service elements in an offering is increasing as more product manufacturers have transformed to service providers and firms are now dedicated to creating a holistic delightful experience [2].

Therefore, an urgent need emerges for more scholarly research in this area. This study aims to attain some insights on the spillovers of quality perceptions and customer satisfaction of different parties based on observations from the mobile-telecoms industry.

The remainder of this article is structured as follows. A comprehensive review of relevant key concepts and theoretical foundations is first conducted, followed by hypotheses development. It is concluded with potential contributions and limitations.

II. LITERATURE REVIEW A. Relationship between Quality, Satisfaction and Loyalty

In the early 1990s, results on the causal order of quality and customer satisfaction were mixed. Several studies reported that service quality is an outcome of customer satisfaction [3,4]. However, later on the view that quality precedes customer satisfaction becomes prevalent among researchers [5]. Further studies show that the influence of quality on loyalty intention is indeed mediated (e.g., [5,6]) by customer satisfaction. Such mediation mechanism has its root in consumer behavior research that cognitive evaluations precede emotional responses followed by intentions [7]. This is also consistent with normal decision making process. This model (i.e. customer satisfaction as a mediator) is accepted as a basis for developing our spillover effects framework. B. Spillover Effects

Early explorations of spillover effects between products and services are mostly in the retailing context. Significant influence of in-store services on product quality perceptions was found [6]. Later on researchers began to notice the spillover effects between independent product and service providers. Archer and Wesolowsky [8] concluded that owners tend to be more tolerant to negative

Quality and Customer Satisfaction Spillovers in the Mobile Telecoms Industry

Y. Ding, K. H. Chai

Department of Industrial and Systems Engineering, University of Singapore, Singapore (dy@nus.edu.sg, iseckh@nus.edu.sg)

978-1-4244-4870-8/09/$26.00 ©2009 IEEE 1282

vehicle incidents than negative service encounters; on the other hand, positive service encounters can counteract negative vehicle incidents and build up loyalty. Taking a step further, Mittal et al. [9] found that product satisfaction affects intentions toward service provider more than does service satisfaction after owing the car for some period of time.

Overall, research on spillover effects is not common in extant customer satisfaction literature. However, a considerable amount of studies have been conducted in branding, such as brand alliances, and brand extension. Theories and findings in brand spillovers can shed some lights on quality and customer satisfaction spillovers. First, spillover effects usually occur when a link, either weak or strong, exists between the focal parties. For instance, Votolato and Unnava [10] found that negative cobranding spillover exists only when the host brand was culpable for the misdeeds of its partner brand. Second, spillover effects are characterized by strength and directionality [11]. Three patterns of asymmetries, unidirectionality, unequal magnitude, and positivity or negativity effects, can be expected based on the two features. Moreover, further exploration of possible moderators is critical to enhancing the understanding of the spillover process and providing more precise measure of the outcomes (i.e., spillover effects).

C. Associative Network Theory

One possible way to examine spillover effects is to understand how human brains organize and process information. The predominant theory on this is the associative network theory [12]. According to this theory, our memory is represented by complex networks comprised of nodes and numerous links connecting them (see Fig. 1). Nodes are the basic information storage units, which contains brands, product attributes, evaluations, and many others. A more accurate and comprehensive understanding of any concept requires a search in the networks – not only obtaining information in each node, but also keeping aware of the links between them [12].

Links are characterized by directionality and strength, which is the same as the two features of spillover effects. As the simplified associative network displayed in Fig. 1, linkages between any pair of nodes can point in both directions; and strength of linkages varies as associations differ. In some cases, spillover may just emanate from one node to another but not the opposite. To exemplify, as is shown in Fig. 1, although a strong link exists from Service A to Product A, no significant association from the opposite is observable. In addition, strength of associations depends on both quality (the manner of thinking) and quantity (amount of thinking) of information procession. When a concept is recalled repeatedly and elaborated in every detail, the associations will be strengthened.

Product A

Service AProduct B

Product C

Strong Association Weak Association No Significant Association

Information processing of spillovers includes two

sequential steps: retrieval and updating. Retrieval is facilitated by a process named “spreading activation” from node to node [12]. Activation of one node (referred to as the “source node”) by external information (e.g., a negative or delighting experience) will immediately spread to its connected nodes (referred to as the “destination nodes”), from which further expanding to the nodes linked to them (i.e., destination nodes), and so on. The extent of activation is largely determined by the content of the external information and the manner that those nodes are organized in the network (i.e., directionality and strength of the associations). After retrieval, updating of those activated nodes will finally generate the outcomes of spillover effects [11]. It is a learning and improving process involving the integration of existing information contained in the node with the new valenced message. The updated information can be enduring in the sense that it decays slowly in our memory [13]. This indicates that the aforementioned information processing is not a transient phenomenon; its effects can last long. It is important to clarify this because the conceptualization and measurement of quality, satisfaction and loyalty intentions are from a long-term (global) perspective, rather than based on a specific transaction.

III. HYPOTHESES DEVELOPMENT

A. Spillover Effects

Attitudes can be conceived as a set of related feelings, memories and beliefs about an object [14]. Affection, cognition and behavioral intentions are close correlates of attitudes [15]. Thus, quality, cumulative satisfaction and loyalty intentions are regarded as attitude-like concepts in this study. Consistent with associative network theory, attitudes are represented in memory by (1) an object label, (2) an evaluative summary, and (3) a knowledge structure supporting that evaluation [15]. Such an associative structure of attitudes is further demonstrated in an experiment by Tourangeau et al. [14]. They found that activation of attitudes toward one issue can facilitate activation of attitudes toward other relevant issues (i.e., faster reaction).

Based on these arguments, both handsets and network operators can be conceptualized as connected label nodes. Each label node is strongly associated with quality

Fig. 1. A schematic representation of an associative network

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perception, satisfaction and loyalty intentions nodes. According to the quality-satisfaction-loyalty framework, links also exist pointing from quality node to satisfaction node and from satisfaction node to loyalty intentions node. Observation of the target object (e.g., breakdown of a handset) will spontaneously activate the quality node, and consequently satisfaction node and loyalty node. This is a mental process of establishing the quality-satisfaction-loyalty links within an individual object. On the other hand, due to close associations between handsets and networks as discussed before, satisfaction with the network might also be spreading-activated by quality evaluation of the handset besides the direct influence from quality perception of the network. Likewise, loyalty intentions toward the network are susceptible to change in satisfaction levels with the handset as well. In a similar vein, observation from network-relevant events can also impact handset evaluations. Integrating the positive relationships found between quality and satisfaction and between satisfaction and loyalty [5], following hypotheses are postulated:

H1a: Handset quality positively affects customer

satisfaction with the network. H1b: Network quality positively affects customer

satisfaction with the handset. H1c: Customer Satisfaction with the handset

positively affects loyalty intentions toward the network. H1d: Customer Satisfaction with the network

positively affects loyalty intentions toward the handset.

B. Direct Effects versus Spillover Effects

Relationships between quality, customer satisfaction and loyalty within a single firm (referred to as “direct effects”) have been extensively examined in extant literature in various contexts. However, no one compares the magnitude of direct effects with spillover effects. Research on attitude and information integration [15] argues that the level of updating is determined by message memory (i.e., information from the source node) and prior message in the node. For direct effects, the external information (i.e., original information) directly acts upon the source node (e.g., if a user believes an incident is a result of low handset quality, the handset node will be first activated); while spillover effects is caused by the message spreading along the path from the source node to the destination node. As suggested by Collins and Loftus [12], activation spreads along the links in a decreasing gradient, that is, only part of the message from the source node can be preserved depending on the distance and strength of the paths. Therefore, I postulate that direct effects are larger than spillover effects.

H2a: The direct effect between network quality and

customer satisfaction with the network is larger than the spillover effect between network quality and customer satisfaction with the handset.

H2b: The direct effect between handset quality and customer satisfaction with the handset is larger than the spillover effect between handset quality and customer satisfaction with the network.

H2c: The direct effect between customer satisfaction with the network and loyalty intentions toward the network is larger than the spillover effect between customer satisfaction with the network and loyalty intentions toward the handset.

H2d: The direct effect between customer satisfaction with the handset and loyalty intentions toward the handset is larger than the spillover effect between customer satisfaction with the handset and loyalty intentions toward the network. C. The Moderating Effects of Consumer Knowledge

People naturally search for the causes of events they encounter, which is related to their knowledge of the specific field. We propose that consumer knowledge moderates the spillover effects between quality and satisfaction for two reasons. First, as noted by Payne [16], people tend to utilize heuristics when facing cognitively demanding tasks. Hence, consumer judgment is usually a balance between objective attributes and heuristics. Advanced consumer knowledge can, to some extent, enhance confidence when purchasing or assessing a product or service [17]. Those experienced users may evaluate a service on relatively objective criteria, and less resort to simple heuristics. However, decision making by a mobile user lack of relevant knowledge may heavily rely on cues such as brand reputation and word of mouth. Secondly, more knowledgeable mobile users are supposed to better understand underlying processing mechanism of handsets and networks. Therefore, they are more capable of correctly identifying the reason of a smooth or an awful communication experience. More correct and rational judgment may limit the effect within the boundary of the attributed products or services, thus reducing spillovers.

Since quality usually refers to evaluations of specific characteristics of a product or service, relevant knowledge (e.g., knowledge of handsets and networks in the mobile-telecoms industry) is required. However, no evidence shows such knowledge is necessary in global satisfaction and loyalty formation. Thus, the moderating effects of consumer knowledge are constrained within spillovers between quality and customer satisfaction.

H3a: The spillover effect between network quality and

satisfaction with the handset will be weaker (stronger) when users are highly (less) knowledgeable on mobile telecoms.

H3b: The spillover effect between handset quality and satisfaction with the network will be weaker (stronger) when users are highly (less) knowledgeable on mobile telecoms.

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D. The Moderating Effects of Affective Commitment

Affective commitment is defined as the emotional or psychological attachment to a product or service [18]. It basically addresses the question: How strongly do I feel about my relationship with this brand? Affective commitment is regarded as a close antecedent of loyalty in several studies [19]. Therefore, we hypothesize

H4a: Network commitment positively affects loyalty

intentions toward the network. H4b: Handset commitment positively affects loyalty

intentions toward the handset. More importantly, high commitment can also shield

the target product or service from negative information. As noted in the associative network theory, updating of a node is not only determined by the new information, but also depends on the existing beliefs and attitudes, which actively guide processing of new information. This ensures that attitude has a certain degree of consistency and is psychologically stable. Deviation from an existing attitude may involve a high psychological cost since it requires cognitive reordering and rethinking of a prior knowledge. Hence, consumers tend to pursue cognitive consistency when encountering conflicting information, which constitutes a defense mechanism [20]. Therefore, in an associative network, information from the source node may be prevented from spreading to the end nodes or simply being ignored while updating if it contradicts to consumers’ existing attitudes.

H5a: When handset commitment is high (low),

spillover effects from satisfaction with the network to loyalty intentions toward the handset will be stronger (weaker) given positive information, but weaker (stronger) given negative information.

H5b: When network commitment is high (low), spillover effects from satisfaction with the handset to loyalty intentions toward the network will be stronger (weaker) given positive information, but weaker (stronger) given negative information. E. Control Variables

User type (i.e., prepaid users and postpaid users) is

controlled in this study since it is supposed to significantly affect the results. In an associative network, the strength of the linkage between a handset node and a network node can differ. Specifically for mobile users, those who purchase their handset from the operator retail shop may perceive closer relationship between the handset and operator. As a result, the chance of being spreading-activated is higher and the information preserved from the source node to the end node is more complete. Therefore, spillover effects are likely to be more significant for postpaid users than prepaid users.

Fig. 2. Conceptual framework Fig. 2 presents all the hypothesized relationships.

IV. CONCLUSION Our study aims to obtain a better understanding of

quality, customer satisfaction and loyalty links by introducing spillovers effects. Built on the theory of associative networks and customer satisfaction as a mediator model, it extends the well established quality-satisfaction-loyalty relationships to a multi-firms setting wherein products and services may interact. In addition, possible moderators are proposed to further understand the characteristics of spillovers. Knowledgeable consumers are less likely to be affected by large spillovers; while information of a brand consistent with consumers’ commitment level may be more actively processed.

Although empirical results are yet to be obtained, literature review and our conceptual discussion suggest that firms working closely together in delivering solutions to customers need to consider the influence of their partner’s product or service quality and satisfaction index as well. This may enhance understanding of customer satisfaction and loyalty of their own companies. Besides, dedication to enhancing consumer commitment may not only protect firms’ reputation from their own occasional misdeeds, but also shield off negative information from other relevant firms.

However, some boundaries should be highlighted when interpreting our propositions. First, loyalty is usually defined along two dimensions, namely attitudinal loyalty and behavioral loyalty [18]. However, as many other studies, only the former is considered in this study. The main reason is that our study focuses on psychological process, which may influence but not decisively predict real behavior. Some external factors, such as location, time constraint and promotion can also lead to purchasing behavior.

Second, not every aspect of customers’ experience with handset or network is investigated. As is known to us,

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besides selling mobile phones, handset manufacturers also offer after sale services. Nevertheless, generally only a small portion of customers will use maintenance or repair services since most mobile phones have good quality and their performance is relatively reliable. Hence, after sale services are not included in our study. Smartphone users are also excluded as their usage experience can be very different from ordinary handsets owners. For network operators, although several other types of services can be identified, such as hotline, online, and in-store services, they are mostly supporting services but not the core offerings. Besides, the usage of these supplementary services tends to be highly uneven, which will greatly increase the difficult of sampling and understanding of their impact on the formation of overall quality perception. Moreover, inclusion of all types of services would result in a much more complex model than the current one. Higher model complexity may be not statically and theoretically manageable. For example, an incredibly larger sample size is needed and problems may occur at model estimation. In addition, such a model may be lack of focus because too many latent variables are included.

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