Document Type

Conference Proceeding

Conference Track

Social Media/ Internet/ Mobile/ Direct Marketing

Publication Date

2013

Abstract

With the increasing popularity of multichannel strategies, many retailers actively encourage their customers to undertake purchasing activities across various retail channels. Extant literature on multichannel strategies advances our understanding of why and how consumers select channels, but our knowledge is limited on how different channel characteristics affect consumer behavior, decision-making across channels and channel choice. In this paper, we focus on one such channel characteristic, called media richness of the retail channels, and investigate the effects of media richness of channels on consumer decision-making and channel choice. Media richness, as originally described by Media Richness Theory, is a set of objective characteristics such as feedback and communication capability, language variety, and personal focus, which determine a channel’s ability to communicate richness of information. We present related predictions based on media richness theory and cognitive cost (behavioral decision theory) on what level of channel richness is favorable for various purchase tasks. Findings of an experiment provide evidence that consumers prefer channels with medium to high levels of media richness for carrying out decision-making tasks. Consumers indicate that they are unlikely to return to channels that incorporate low levels of media richness, as these channels are not suitable for complete decision-making tasks. The study further finds that product type moderates the effect of media richness on perceived channel-task fit, post-purchase evaluation and channel choice. These insights should prove helpful to retailers in managing content across different channels.

About the Authors

Moutusy Maity (mmaity@iiml.ac.in) is assistant professor of marketing at the Indian Institute of Management, Lucknow, India. She holds a Ph.D. in Business Administration from the University of Georgia. Her research focuses on issues regarding human-computer interaction, and adoption of technology.

Mayukh Dass (mayukh.dass@ttu.edu) is assistant professor of marketing at the Rawls College of Business, Texas Tech University. He holds a Ph.D. in Business Administration, an M.S. in Statistics and an M.S in Artificial Intelligence from the University of Georgia. His research focuses on statistical and analytical methods with applications to valuation issues in dynamic economies and brand management.

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Digital Commons@Georgia Southern License

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