Can location-based mobile promotion (LMP) trigger contemporaneous and delayed sales purchases? As mobile technologies can reach users anywhere and anytime, LMP becomes a promising new channel. We unravel the dynamic sales impact of LMP on the basis of a randomized field experiment with 22,000 mobile users sponsored by one of the largest mobile service providers in the world. Our identification strategy is to gauge the marginal increases in consumer purchases of the geo-fenced treatment group of users who received LMP, above and beyond the baseline control groups. There are two controls: one group who received the same LMP but not in the virtual geo-fencing locational range (nongeo-fenced control), and the other who did not receive the LMP but in the geo-fencing range (geo-fenced control). The latter control serves as an organic holdout baseline from the similar population, i.e., counterfactual test of what if without the mobile LMP intervention, to identify the actual ÒliftÓ of incremental purchases caused by the treatment with the mobile LMP intervention. Findings suggest that LMP treatment has a significantly stronger impact on contemporaneous (same-day) purchases and delayed (subsequent-days) purchases than the controls. The randomized experiment design renders these findings robust to alternative explanations such as mobile usage behavior heterogeneity, product effects heterogeneity, nonrandomized sample-selection bias, and endogeneity concerns. Follow-up surveys with the field experiment users explore the nuanced mechanisms via which LMP may induce the impulsive, same-day purchases, and create product awareness for the planned subsequent-days purchases. LMP can generate six times more purchases than nongeo-fenced control with the LMP intervention, and 12 times more than geo-fenced control without the LMP intervention. LMP has a delayed sales effect for 12 days after the mobile promotions. The total sales impact of LMP could be underestimated by 54% if excluding the delayed sales impact and only including the contemporaneous impact. These findings are new to the literature and often neglected in mobile promotion practices, proffering novel implications on the sales value of LMP in the mobile era.
This paper presents and extends Latent Growth Modeling (LGM) as a complementary method for analyzing longitudinal data, modeling the process of change over time, testing time-centric hypotheses, and building longitudinal theories. We first describe the basic tenets of LGM and offer guidelines for applying LGM to Information Systems (IS) research, specifically how to pose research questions that focus on change over time and how to implement LGM models to test time-centric hypotheses. Second and more important, we theoretically extend LGM by proposing a <i>model validation</i> criterion, namely “<i>d</i>-<i>separation</i>,” to evaluate <i>why</i> and <i>when</i> LGM works and test its fundamental properties and assumptions. Our <i>d</i>-separation criterion does not rely on any distributional assumptions of the data; it is grounded in the fundamental assumption of the theory of conditional independence. Third, we conduct extensive simulations to examine a multitude of factors that affect LGM performance. Finally, as a practical application, we apply LGM to model the relationship between word-of-mouth communication (online product reviews) and book sales over time with longitudinal 26-week data from Amazon. The paper concludes by discussing the implications of LGM for helping IS researchers develop and test longitudinal theories.
Millions of people participate in online social media to exchange and share information. Presumably, such information exchange could improve decision making and provide instrumental benefits to the participants. However, to benefit from the information access provided by online social media, the participant will have to overcome the allure of <i>homophily</i>—which refers to the propensity to seek interactions with others of similar status (e.g., religion, education, income, occupation) or values (e.g., attitudes, beliefs, and aspirations). This research assesses the extent to which social media participants exhibit homophily (versus heterophily) in a unique context—virtual investment communities (VICs). We study the propensity of investors in seeking interactions with others with similar sentiments in VICs and identify theoretically important and meaningful conditions under which homophily is attenuated. To address this question, we used a discrete choice model to analyze 682,781 messages on Yahoo! Finance message boards for 29 Dow Jones stocks and assess how investors select a particular thread to respond. Our results revealed that, despite the benefits from heterophily, investors are not immune to the allure of homophily in interactions in VICs. The tendency to exhibit homophily is attenuated by an investor’s experience in VICs, the amount of information in the thread, but amplified by stock volatility. The paper discusses important implications for practice.
Virtual communities continue to play a greater role in social, political, and economic interactions. However, how users value information from these communities and how that affects their behavior and future expectations is not fully understood. Stock message boards provide an excellent setting to analyze these issues given the large user base and market uncertainty. Using data from 502 investor responses from a field experiment on one of the largest message board operators in South Korea, our analyses revealed that investors exhibit confirmation bias, whereby they preferentially treat messages that support their prior beliefs. This behavior is more pronounced for investors with higher perceived knowledge about the market and higher strength of belief (i.e., sentiment) toward a particular stock. We also find a negative interaction effect between the perceived knowledge and the strength of prior belief on confirmation bias. Those exhibiting confirmation bias are also more overconfident; as a result, they trade more actively and expect higher market returns than is warranted. Collectively, these results suggest that participation in virtual communities may not necessarily lead to superior financial returns.
Online word-of-mouth (WOM) such as consumer opinions, user experiences, and product reviews has become a major information source in consumer purchase decisions. Prior research on online WOM effect has focused mostly on low-involvement products such as books or CDs. For these products, retailer-hosted (internal) WOM is shown to influence sales overwhelmingly. Numerous surveys, however, suggest consumers often conduct pre-purchase searches for high-involvement products (e.g., digital cameras) and visit external WOM websites during the search process. In this study, we analyze the relative impact of external and internal WOMs on retailer sales for high-involvement products using a panel of sales and WOM data for 148 digital cameras from Amazon.com and three external WOM websites (Cnet, DpReview, and Epinions) over a four-month period. The results suggest that a retailer's internal WOM has a limited influence on its sales of high-involvement products, while external WOM sources have a significant impact on the retailer's sales. The findings imply that external WOM sources play an important role in the information search process.
This study examines the incentives for content contribution in social media. We propose that exposure and reputation are the major incentives for contributors. Besides, as more and more social media Web sites offer advertising-revenue sharing with some of their contributors, shared revenue provides an extra incentive for contributors who have joined revenue-sharing programs. We develop a dynamic structural model to identify a contributor's underlying utility function from observed contribution behavior. We recognize the dynamic nature of the content-contribution decision-that contributors are forward-looking, anticipating how their decisions affect future rewards. Using data collected from YouTube, we show that content contribution is driven by a contributor's desire for exposure, revenue sharing, and reputation and that the contributor makes decisions dynamically.
Extant research considers the IT governance choice to be a trade-off between the cost-efficiency of centralization and the responsiveness provided by local information processing. This view predicts that firms tend to decentralize IT governance in more uncertain environments. We investigate this issue by studying the relationship between environmental uncertainty and IT infrastructure governance in a sample of business units from Fortune 1000 companies. The key proposition in this paper is that the relationship between environmental uncertainty and decentralization in IT infrastructure governance is best characterized as a curvilinear relationship. That is, when environmental uncertainty increases from low to high, firms tend to first decentralize their IT infrastructure decisions to the business units to enhance their responsiveness; and then centralize their IT infrastructure decisions to the headquarters as uncertainty increases further, to achieve the benefits of coordination and to mitigate the potential agency problem in uncertain environments. Moreover, the study proposes that business unrelatedness between business units and their headquarters moderates the curvilinear relationship between environmental uncertainty and IT infrastructure governance. We find that both the propositions are supported by the data.
Online users often need to make adoption decisions without accurate information about the product values. An informational cascade occurs when it is optimal for an online user, having observed others' actions, to follow the adoption decision of the preceding individual without regard to his own information. Informational cascades are often rational for individual decision making; however, it may lead to adoption of inferior products. With easy availability of information about other users' choices, the Internet offers an ideal environment for informational cascades. In this paper, we empirically examine informational cascades in the context of online software adoption. We find user behavior in adopting software products is consistent with the predictions of the informational cascades literature. Our results demonstrate that online users' choices of software products exhibit distinct jumps and drops with changes in download ranking, as predicted by informational cascades theory. Furthermore, we find that user reviews have no impact on user adoption of the most popular product, while having an increasingly positive impact on the adoption of lower ranking products. The phenomenon persists after controlling for alternative explanations such as network effects, word-of-mouth effects, and product diffusion. Our results validate informational cascades as an important driver for decision making on the Internet. The finding also offers an explanation for the mixed results reported in prior studies with regard to the influence of online user reviews on product sales. We show that the mixed results could be due to the moderating effect of informational cascades.
Virtual communities are a significant source of information for consumers and businesses. This research examines how users value virtual communities and how virtual communities differ in their value propositions. In particular, this research examines the nature of trade-offs between information quantity and quality, and explores the sources of positive and negative externalities in virtual communities. The analyses are based on more than 500,000 postings collected from three large virtual investing-related communities (VICs) for 14 different stocks over a period of four years. The findings suggest that the VICs engage in differentiated competition as they face trade-offs between information quantity and quality. This differentiation among VICs, in turn, attracts users with different characteristics. We find both positive and negative externalities at work in virtual communities. We propose and validate that the key factor that determines the direction of network externalities is posting quality. The contributions of the study include the extension of our understanding of the virtual community evaluation by users, the exposition of competition between virtual communities, the role of network externalities in virtual communities, and the development of an algorithmic methodology to evaluate the quality (noise or signal) of textual data. The insights from the study provide useful guidance for design and management of VICs.
Executives need to master different mechanisms for analyzing their firms' investment opportunities in uncertain, difficult times. Rapidly changing business conditions require firms to move quickly, with total commitment and the rapid deployment of capital, resources, and management attention, often in several directions at the same time. However, high levels of strategic uncertainty and environmental risk, combined with limits on available funding, require firms to limit their commitment. In brief, we require high levels of strategic commitment to numerous projects, while simultaneously preserving our flexibility and withholding commitment. Whereas achieving both is clearly impossible, techniques exist that enable executives (1) to identify and to delimit their range of investment alternatives that must be considered, and to do so rapidly and reliably, (2) to divide investments into discrete stages that can be implemented sequentially, (3) to determine which chunks can safely and profitably be developed as strategic options, with value that can be captured when subsequent stage investments are made later; and (4) to quantify and to estimate the value of these strategic options with a significant degree of accuracy, so that selections can be made from a portfolio of investment alternatives. This paper also avoids restrictions of common option valuation models by providing a technique that is general enough to be used when the data required by common models are not available or the assumptions are not satisfied.
We describe the emerging competition between music companies and their star acts and the role of online distribution in this industry. We then contrast this with the lack of competition newspapers will face from their reporters, writers, and photographers, but identify other possible competitors for newspaper publishers. We examine what resources have previously enabled record companies to lock in their star acts and ways in which technology has altered artists' abilities to reach the market independently and thus their dependency upon record companies. We examine which resources have seen their value eroded in the newspaper industry and the remaining value that the newspaper company still creates, other than building stories, adding advertising, and printing and selling the papers. We consider what part of the newspaper business is vulnerable, if any, and where threats may arise. We combine the resource-based view of competitive advantage to examine which industry may have become newly easy to enter, and the theory of newly vulnerable markets to assess which industry may actually have become vulnerable as a result. Our analyses are then used to create a computer simulation model to make the implications more explicit under a range of assumptions.