The Factors Influencing Customer Loyalty In Internet Retailing
With the adoption and diffusion of the Internet as consumer products retailing channels, the number of online shoppers has been increasing. It seems the profit potential of online retailing is very attractive because the operation costs of selling consumer products online are relatively lower than traditional retailing and the potential market is very large – virtually global market. On the other hand, the competition is extremely intensive because of the large number of competitors all over the world. In order to market their products effectively and efficiently, online retailers should understand how to build customer loyalty and retain customers. It was understood that the costs of acquiring new customers were six times higher than retaining existing customers.
Customer loyalty is a buyer’s overall attachment or deep commitment to a product, service, brand, or organization (Oliver 1999). Dick and Basu (1994) developed a model of customer loyalty which is constituted by two dimensions, relative attitude and repeat patronage. Four types of loyalty by cross classifying the concept of relative attitude with repeat patronage at two levels were identified. Only a favorable correspondence between relative attitude and repeat patronage represents true loyalty. Therefore, two behaviors, including recommending a service provider to other customers and repeatedly patronizing the provider, were treated as loyalty indicators. Customer loyalty has been regarded as a single construct in most of prior studies and measuring instrument basically adapted from the research by Zeithaml et al. (1996). However, Lam, Shankar, Erramilli, and Murthy (2004) argue that customer loyalty should be separated into two dimensions, namely recommendation and patronage. The antecedents of customer loyalty may have various degrees of impact on the two dimensions.
This paper would like to address the following research question:
What are the effects of customer value, satisfaction, and switching costs on customer loyalty, in the online retailing context?
At the initial development of online shopping, most of academic studies focus on the factors that determining customers’ intention to adopt online shopping, online shopping behavior, and service quality. Office of Fair Trading has conducted a comprehensive review of online shopping behavior. They identified the factors affecting online purchasing behavior including consumer demographic characteristics, attitudes, beliefs and personality, and nature of websites. However, consumer attitudes toward online shopping are considered to be the rational factor affecting online shopping adoption. Traditionally, attitudinal theories have been extensively used in consumer behavior research. They have been used for researching online shopping, especially the Technology Acceptance Model.
Despite the fact that theoretical approaches to online shopping are various and diverse, academia has attempted to offer overall frameworks for studying online shopping, integrating previous theoretical work and empirical results. Brown et al. (2007) reviewed three such overall frameworks, which have been empirically tested. They are the integrated framework by Cheung et al. (2005), the Utility Maximization Theory approach by Cao and Mokhtarisan (2005), and Online Buying Model based on the Standard learning Hierarchy by Martinez-Lopez, Luna and Martinez (2005).
The integrated framework developed by Cheung et al. (2005) deserves greater attention. The framework involves not only consumers’ intention to adopt Internet as a sales channel and purchase online, but also the factors influencing their continual usage of online shopping. They have conducted a systematic and exhausted review of online consumer behavior research, which included a total of 351 articles from 1994 to 2002. The Theory of Reasoned Action and its family theories including the Theory of Planned Behaviour and the Technology of Acceptance Model are the dominant theories in the research area of consumer purchasing behavior on the web. Expectation-Confirmation Theory (Oliver 1980) and Innovation Diffusion Theory (Roger 1995) have also been tested repeatedly. The studies largely sought to explore how consumer adopt and use online shopping. Specifically, the emphasis was on the antecedents of consumer online shopping intention and adoption.
Having reviewed the recent work of online shopping from various fields, Cheung et al. (2005) discovered that intention and adoption have been received considerable attention, but continual usage has been under researched. Hence, they proposed an online consumer behavior framework, which consists of intention, adoption, and continuance (MIAC). They claimed that the three concepts – intention, adoption, and continuance – have not been linked together to investigate the process of online shopping as a whole in their reviewed literature. By integrating the attitudinal theories and the Expectation-Confirmation Theory, the unifying model – MIAC – provides a cohesive view of online consumer behavior.
By reviewing the results of the current study, and the studies conducted by Cronin et al. (2000), Yang and Peterson (2004), and Lam et al.’s (2004), the researcher found that all of these studies provide evidence proving the both customer satisfaction and customer value directly influence customer loyalty, and customer satisfaction mediate partially the link between customer value and customer loyalty. The study by Lam et al. (2004) provides evidence that switching costs have direct influences on customer loyalty, both ‘recommend’ and ‘patronage’ dimensions. But the current study and Yang and Peterson’s study do not prove the significant effect of switching costs. It is because e-business has low switching costs that do not establish significant barrier to switch suppliers. Lam et al. (2004) used two dimensions of customer loyalty in their study. They asserted that the decomposition of customer loyalty is intuitively sound because the two loyalty dimensions behave differently with regard to their linkage with their antecedents. In addition, the decomposition relates to managerial goals: repeat patronage pertains to customer retention and recommendation pertains to attracting new customers.
However, the differences are very little indeed. Customer satisfaction totally mediates the relationship between customer value and loyalty (recommend), but partially mediates the relationship between customer value and loyalty (patronage). The evidence is still not very
strong. The validity of the decomposition still needs further examination. Except customer satisfaction and customer value, Cronin et al. (2000) added service quality to their loyalty model and found that it is the most important factor of customer loyalty. Service quality has a total effect of 0.78 on customer loyalty, followed by customer value (0.64) and customer satisfaction (0.41). Service quality does not only have direct impact on customer loyalty, but also have indirect impact via customer value and customer satisfaction. Service quality has not been evaluated in the study. However, the importance of service quality in online shopping should not be ignored. Online retailers who would like to enhance their performance should improve online service quality.
Porter (1980) suggests value-creating activities are sources of competitive advantage. Customer value can be created by implementing either cost-leadership or differentiation strategy. Porter believes service quality is effective differentiator. Customer value can be created through delivering superior service quality, which may be based on the configuration of value-creating activities within the organization’s value chain. The configuration is so complicated that it is not easy for competitors to imitate.
Customer loyalty can be generated through improving customer satisfaction and offering high customer value. Researchers suggest excellent service quality is the key to satisfy customers (Cronin et al. 2000). Parasuraman et al. (2005) suggest the service quality of Internet retailing has the following dimensions: (1) efficiency, (2) fulfillment, (3) system availability, (4) privacy, (5) responsiveness, (6) compensation, and (7) contact. The first four are the core dimensions of electronic service quality. Online retailers should have a Website that is always available to customers and is easy to access and is able to protect customer privacy. The retailers can fulfill orders promptly and correctly. The last three are dimensions of recovery service quality, ensuring customer enquiries and complaints can be handled properly.
Yang and Peterson (2004) also suggest providing quality customer services is key to customer satisfaction. First, online services providers should have the knowledge and capability to handle customer problems and address customer complaints in a friendly manner. Second, they should perform the services correctly by executing transactions accurately, delivering orders promptly, and maintaining error-free customer records.
Third, they should provide user-friendly Web sites. The product information and content should be well-organized. Fourth, they must protect customer privacy and provide secure transaction, ensuring no personal information will be misused or disclosed intentionally or unintentionally. Customers should think online transaction is safe. Yang and Peterson (2004) suggest these are key factors of providing excellent online service quality to customers.
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