Consumer Product Consideration and Choice at Purchase Time at Online Retailers

In this study, we analyze consumers’ product consideration and choice at purchase time. We leverage a popular feature provided by online retailers: “What Do Customers Ultimately Buy After Viewing This Item?” We show that information contained in this feature can be used to identify consumers’ product consideration and choice at purchase time when combined with product sales data. The identification is exact in analyzing competition between two products. For analysis of three products, identification is feasible under the assumption of a discrete choice process. For analysis of more than three products, the information provides a lower bound of consumers that consider only one product at purchase time. We apply the model to 7,000 products from Amazon. The results show that more than 78 percent of consumers purchase a product without considering any other products at the purchase time

Online Retailer vs. Click and Mortar Retailer: Who Performs Better?

Retail business is characterized by different business models: pure-play model and dual channel approach, which uses both physical and online channels to reach customers. There is conflicting evidence regarding the relative value of these business models to the consumers. We take a market valuation approach to evaluate the relative merits of both business models. We consider a panel of publicly traded US retailers and evaluate how their sales performance impacts their Tobin’s q. We find that the dual channel retailers receive a market premium for their sales revenue as compared to the pure-play retailers. This higher valuation can be associated with higher customer satisfaction with dual channel firms leading to a higher intangible value as compared to the pure-play firms. Our results have important implications for retailers as we demonstrate the value of different channels. Our work also contributes to the existing literature on online consumer retailing and multichannel research

A Study of Search Attention and Stock Returns Cross Predictability

This study investigates a novel application of correlated online searches in predicting stock performance across supply chain partners. If two firms are economically dependent through supply-chain relationship and if information related to both firms diffuses in the market slowly (rapidly), then our ability to predict stock returns increases (vanishes). Using supply-chain data provided by Bloomberg and weekly co-search network of supply-chain partners from Yahoo! Finance, we find that when investors of a focal stock pay less attention to its supply-chain partners, we can use lagged partner returns to predict the future return of the focal stock. When investors’ co-attention to focal and partner stocks is high, the predictability is low. We contribute to the growing literature on aggregate search and economics of networks by demonstrating the inferential power and economic implications of search networks

Pricing of Information Services Using Real-Time Databases: A Framework for Integrating User Preferences and Real-Time Workload (Best Paper Runner Up)

Many revolutionary information products are being offered or envisioned in electronic commerce setting. Since an economic paradigm and mass customization are implicit in electronic commerce, these products must be produced and delivered at appropriate prices with user desired service characteristics such as response time, correctness, and completeness. In this research, we investigate the information services pricing with response time (or delay) as the only service characteristic since response time can implicitly characterize other quality attributes such as correctness. In order to recognize customers’ preferences, real-time databases, where transaction processing is time-cognizant, are central to information providers and can be thought of as “manufacturers” of customized products. We propose to capture user preferences by a priority pricing mechanism based on economic theory. This pricing is concerned with database access and is independent of content pricing. Our approach has a natural overload1 management and admission control2 techniques that can potentially increase collective benefits. Our model is evaluated using simulation and is shown to outperform a system without access pricing mechanism with respect to both system wide benefits and RTDB performance

Online Search: Identifying New Investment Habitats

Researchers often refer to investment habitats/categories to explain the patterns of co-movement in asset returns that cannot be fully clarified by fundamentals. Many factors determine these habitats including investor preferences to size, industry, price-levels and risk-levels. This paper investigates a unique method to explore investment habitat based on the search behavior of investors on the Internet without actually using proprietary trading data. Using Yahoo! Finance data on investors’ frequently co-viewing stocks of Russell 3000 stocks between September 15, 2011 and February 24, 2012, we evaluate the return co-movement within investment search habitats/clusters. We find that stocks within a search cluster show strong co-movement with other stocks in the same cluster that is not fully explained by other traditional habitat characteristics. The behavior persists even when a stock moves from one cluster to another. The study provides direct empirical evidence that investors prefer to search among stocks that have similar co-movement

Asset Characteristics and The Impact of IT on Firm Scope and Performance

The literature in IS suggests that IT affects firms’ vertical and horizontal boundaries. This research examines how the nature of firms’ assets and information technology interact to influence the level of vertical integration and horizontal diversification. Using panel data from 2001 to 2004, the analysis suggests that the negative relationship between IT and vertical integration identified in the literature is attributable to IT’s role in coordinating firms’ tangible assets. On the other hand, the positive relationship between IT and firms’ horizontal diversification is attributable to IT’s role in leveraging a firm’s intangible assets across different businesses. The analysis also indicates that for less vertically integrated firms, IT increases the contribution of tangible assets to performance. And for more diversified firms, IT may increase the contribution of intangible assets to performance. The general implication of this research is that firms with more tangible assets may use information technology to become more vertically specialized, whereas firms with more intangible assets may deploy information technology to become more horizontally diversified