An empirical comparison of market efficiency: Electronic marketplaces vs. traditional retail formats

Electronic Commerce Research and Applications (Impact Factor: 1.48). 01/2013; 13(2). DOI: 10.1016/j.elerap.2013.11.003


Researchers have found that price dispersion and market inefficiency exists in electronic marketplaces. Little attention has been bestowed to explore difference in market efficiency between traditional and electronic marketplaces. This study integrates both product and channel preference factors to analyze differences in market efficiency between electronic and traditional shopping environments. Data Envelopment Analysis (DEA) is applied to calculate market efficiency for single-channel and multi-channel shoppers. Results show that market efficiencies vary across consumer segments and products. In summary, this paper enhances understanding of market efficiency by incorporating behavioral segment and product characteristics into the explanatory framework.

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    • "The last decade has seen an exponential increased in commercial use (buying and selling) of Internet because of its convenience of ordering and paying for the products online and have then delivered to the doorstep. Between 2002 and 2012, retail e-commerce grew at 15-25% per year, following a fairly typical adoption pattern that transformed more mainstream consumers into online shoppers [1]. As one of the developing countries that experience the highest online population growth rates in China. "

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    ABSTRACT: Conventional segmentation efforts usually focus on verbal or behavioral data while ignoring visual cues, which play a significant role in impression management. Drawing on theoretical work regarding motivations for impression management (need to belong and need for self-promotion), we propose that Facebook users differ from each other in the composition of visual elements they portray in their Facebook profile photos (PPs), and thus can be segmented based on this composition. In this exploratory study we present a methodological proof of concept for the visual segmentation of Facebook users. Using a randomly selected international sample of 500 Facebook accounts, we analyze data implicit in PPs and identify visual cues relevant to virtual impression management. Using these cues we segment users into types, and relate the types to demographics, Facebook usage, and brand engagement as reflected in the Facebook profile. At the theoretical level, the findings suggest that the current accepted motivations for Facebook impression management (need to belong and need for self-promotion) should be expanded to include a third motivation, need for self-expression. At the practical level, the findings demonstrate the utility of visual segmentation, which can later be implemented using computerized systems.
    No preview · Article · Nov 2015