To Be Unified or Divergent? The Performance Implications of Information Variance across Multiple E-Sellers Offering an Identical Product

Project: Research

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As e-commerce proliferates, consumers increasingly find multiple e-sellers offering the same product. Imagine that you want to purchase a Dyson hairdryer. Your online search returns about 40 e-sellers offering this product: Dyson, Amazon, Sephora, and many others. Each e-seller’s page features a slightly different description of the Dyson hairdryer and associated services (see Figure 1 for an illustration). Will variance in these descriptions for the same product affect your interest in purchasing this product? This question matters for not only the individual e-sellers but also the manufacturer that cares about its collective product sales from all e-stores.Variance in the information provided by different e-sellers about the same product (for short,information variance) is understandable from an e-seller’s perspective. As recommended by conventional marketing wisdom, e-sellers purposely differentiate their descriptions to outcompete others selling the same product, leading to the information variance encountered by consumers. But, collectively, is information variance beneficial for the product manufacturer’s collective sales?The autonomous differentiation strategy adopted by e-sellers might be a double-edged sword to the product’s collective sales. On the one hand, variance makes it difficult for consumers to process the information and may evoke skepticism about product quality and/or authenticity. On the other hand, differentiated information enables consumers to compare each seller’s services and may thus entice purchases.Accordingly, the net effect of information variance on the collective sales of a product remains unclear. To answer this question, we identify two types of information variance—in the product description and service descriptions—and examine their differential effects on the collective click-through rate (CTR), a first-stage purchase interest metric. Drawing on information processing theory, we propose that a)productdescription variancedecreases CTRbecause it raises authenticity/quality concerns and increases the information processing difficulty, while b)servicedescription varianceincreases CTRby increasing perceived differentiation, even though it also increases the information processing difficulty. Also, we investigate three moderators: product price, product complexity, and market concentration.Empirically, we plan two studies to test our hypotheses. The first study will use the large-scale clickstream data of electronic products in a dominant e-marketplace in China to test the main and moderation effects. The second study will provide an experimental test of the mediation effects. The findings will not only enrich our understanding of online channel coordination but also provide important guidelines with which manufacturers, e-sellers, and e-platforms can optimize their approach to information provision.


Project number9043225
Grant typeGRF
Effective start/end date1/08/2129/06/22