Academic journal article Journal of Electronic Commerce Research

The Moderating Role of Cognitive Fit in Consumer Channel Preference

Academic journal article Journal of Electronic Commerce Research

The Moderating Role of Cognitive Fit in Consumer Channel Preference

Article excerpt

ABSTRACT

Past studies showed that, to deploy the best possible consumer interface, companies must pay close attention to the factors and the consumer behavior that lead to channel preference. This study presents the results of an experiment designed to improve our knowledge of consumer channel preference by testing cognitive fit theory in a commercial context. Data from two different samples (749 students dealing with the process of buying a computer from a well-known electronic goods retailer and 290 union members attempting to buy an airplane ticket from a well-known travel agency) were analyzed. Our results show that the cognitive fit level, or the fit between how information is presented to the consumer (i.e., online store vs. bricks-and-mortar store of the same retailer) and the nature of the problem to be solved (i.e., the information search task), moderates the relationship between the individual characteristics and product characteristics identified in past studies and consumer channel preference. The findings of this research support cognitive fit theory in a commercial context and open up a new way of explaining consumer channel preference. Theoretical and managerial implications, limitations on the study and future research directions are discussed.

Keywords: electronic commerce, consumer channel preference, consumer interface, consumer behavior, multi-channel.

1. Introduction

In the last two decades, many new technologies such as the Internet have been invented and used by companies to do business. The use of these technologies has radically transformed commercial practices (Yao and Liu 2005). The fast growth of technological innovations, the impressive number of technologies available and their multiple functionalities have increased the complexity of managers. tasks and raised new challenges and problems for companies that want to design an effective and efficient consumer interface (Madlberger 2006; Rosenbloom 2007).

Many studies concerned with the strategic dimensions of electronic commerce have concluded that one key factor for the success of e-commerce practices is the deployment of a consumer interface focused on consumer needs (Lin 2003; Stone et al. 2002; Willcocks and Plant 2001). The choice of a channel is the first decision that consumers make, and it shapes their entire shopping process (Keen et al. 2004). This means that companies must pay close attention to the factors and the consumer behavior that lead to channel preference. The development of such knowledge would help businesses make better decisions about implementing e-commerce practices and designing effective and efficient channel interfaces geared to consumers. Such knowledge could enable them to stand out from the pack and enhance the value of their products and services (Currie and Parikh 2006).

This paper presents the results of an empirical design to develop an understanding of consumer preference by testing cognitive fit theory in a commercial context. More specifically, our objective is to link the antecedents of consumer channel preference identified by past studies with cognitive fit. Accordingly, we first present the factors identified in past studies as impacting consumer channel preference. We then examine cognitive fit theory. Third, we describe the methodology used to test the proposed hypotheses. Next, we present the analyses and results and, finally, we discuss the theoretical and managerial implications of these results, their limitations and avenues for future research.

2. Literature Review

2.1. Antecedents of Consumer Channel Preference

Factors identified in previous studies provide vital input in explaining consumer channel preference. Based on the results of meta-analyses presented by Constantinides (2004), Chang et al. (2005), and Zhou et al. (2007), we can summarize these factors in two major categories. The first category is related to individual characteristics. …

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