Knowledge that Transforms

Standards are central to many information technology (IT) applications, and the development processes for these standards play a key role in the evolution of information systems (IS). We model the development of IT standards by technology suppliers as a coevolutionary technological search process under supply-side network effects, and we examine how the characteristics of the standards development process influence its outcomes. In line with common intuition and prior research, we find that perfect coordination among suppliers generally facilitates convergence on the best available standard. However, for complex IT standards, we make a novel contribution and find that this “best available” standard may be inferior to alternative, undiscovered solutions because coordination may lead to an overly narrow search. Consistent with prior research, we also find that either highly influential organizations or highly influential alliances and consortia can coordinate standard selection in order to prevent network effects from generating lock-in to an inferior option and to help set the best of the known alternatives as the standard. However, in contrast to the previous literature, we find that when coordination is imperfect and controlled by a moderately influential organization or consortium, it may lead to a technological lock-in dynamic in which suppliers adhere to an inferior solution and are subsequently unable to reverse this commitment, even when a technologically superior alternative emerges later in the search process. Further, we reveal the following paradox involving intellectual property rights (IPR) and related imitation costs: Although imitation costs can lead to the emergence of multiple standards, thereby reducing social welfare in the short term, this effect may have long-term benefits by broadening the search for future generations of a standard.

Collecting and displaying product reviews written by consumers is a common practice for many retail websites. These websites, however, differ in their choice to reveal aggregate review statistics on the product list displayed while consumers browse or search to make initial product selections. This study proposes an analytical model to examine the conditions in which revealing average star ratings on the product list is more profitable than not revealing this information. Noting that consumers differ in their valuations of products sold on a firm’s website, this study finds that if a firm sets prices to maximize total profits, it suffers less profitability from disclosing average star ratings if two products do not differ significantly in their average value and consumers’ valuation of the low-value product is more heterogeneous. If products sold on the website instead are priced by third-party sellers that seek to maximize each product’s own profit, it is less profitable for the firm to reveal average rating information when the two products do not differ significantly in average value and consumers’ valuation of the high-value product is more heterogeneous. These results suggest guidelines that retail websites can use to evaluate their information revelation policies, based on three important factors: the difference in the average value of different products, relative heterogeneity in consumers’ valuation of different products, and the firm’s ability to coordinate prices across products.

Many companies have adopted technology driven social learning platforms such as social customer relationship management (crowdsourcing customer support) to support knowledge sharing among customers. A number of these self-evolving, online customer support communities have reported the emergence of a core– periphery knowledge sharing network structure. In this study, we investigate why such a structure emerges and its implications for knowledge sharing within the community. We propose a dynamic structural model with endogenized knowledge-sharing and network formation. Our model recognizes the dynamic and interdependent nature of knowledge seeking and sharing decisions and allows them to be driven by knowledge increments and social status building in anticipation of future reciprocal rewards from peers. Applying this model to a fine grained panel dataset from a social customer support forum for a telecom firm, we illustrate that a user in this community gains value from being linked to other individuals with higher social status. As a result, a user is more inclined to answer the questions of those who are in the core (well connected) than questions from those who are in the periphery (not well connected). We find that users are taking into account the expected likelihood of their questions receiving a solution before asking a question. With the emergence of a core–periphery network structure, peripheral individuals are discouraged from asking questions as their expectation of receiving a solution to their question is very low. Thus, the core–periphery structure has created a barrier to knowledge flow to new customers who need the knowledge the most. Our counterfactuals show that hiding the identity of the knowledge seeker or making the individual contributions obsolete faster helps break the core–periphery structure and improves knowledge sharing in the community.

How do IT-enabled capabilities influence firms’ ability to leverage customer involvement and shape the amount of firm innovation? This study theorizes that effective processing and management of customer information flows requires organizations to possess “relational information processing capability” (RIPC) and “analytical information processing capability” (AIPC). Drawing on and extending the theories of absorptive capacity and complementarities in the context of innovation, we posit that RIPC and AIPC complement product-focused customer involvement (PCI) and information-intensive customer involvement (ICI) practices, respectively, to enhance the amount of firm innovation. To test our hypotheses, we collected archival data from more than 300 large U.S. manufacturing firms and mapped their RIPC and AIPC to specific IT applications. Consistent with our theorizing, we find that RIPC positively moderates the relationship between PCI and amount of firm innovation and that AIPC positively moderates the relationship between ICI and amount of firm innovation. In further exploratory analysis, we find a positive three-way interaction between AIPC, RIPC, and PCI. Taken together, the results suggest that configurations of IT-enabled capabilities alone are not enough for innovation; instead, firms benefit more when specific configurations of IT-enabled capabilities are leveraged in unison with specific types of customer involvement. The study contributes to theory and practice by shedding light on important complementarities between specific types of customer involvement (PCI and ICI) and specific IT-enabled capabilities (RIPC and AIPC).

Rapid and pervasive digitization of innovation processes and outcomes has upended extant theories on innovation management by calling into question fundamental assumptions about the definitional bo...

In this paper, we argue that the use of technology is structured not only by users, technology, and social context, but also by onlookers (i.e., actors for whom the use is visible, but who are not directly involved in the activities of use themselves). Building on the “technology-in-practice” lens and insights of an ethnographic study in operating rooms where nurses used mobile technology for various work-related and recreational purposes, we show how onlookers contribute to structuring collective patterns of technology use. We concep-tualize their role as the onlooker effect, which means that onlookers’ inferences, judgments, and reactions trigger users to reflect on consequences and adjust the use in front of others, a phenomenon which is activated by the cues unintentionally given off when using technology. By identifying the role of onlookers in technology use, this study goes beyond user-centric and feature-centric perspectives on information technology use, illustrating that it does not happen in a physical vacuum, but often draws in unintended audiences. The onlooker effect provides a more in-depth explanation for unexpected patterns of technology use emerging in the workplace.

Recent studies have documented that the contagion of information and behaviors in social networks is generally quite limited. We examine whether this pattern characterizes exogenous demand shocks diffusing in a product network. To this end, we analyze a unique series of demand shocks induced by mass-media book reviews on the Oprah Winfrey television show and in The New York Times. Our identification strategy is based on a difference-in-differences model estimated using two different groups as control, based on propensity-score-based matching and network proximity to a reviewed book, respectively. Our results show that the diffusion of exogenous demand shocks in the Amazon.com product network is relatively shallow, typically about three edges deep into the network, although the economic impact of this diffusion can often be significant. We link our results to recent findings in the context of diffusion in social networks and discuss managerial implications.

This study documents variation across industries in creditors’ perceptions of the risk of information technology (IT) investments. The associations we document between IT investments and both initial bond ratings and yield spreads suggest that credit-rating agencies and bond investors consider IT investments in automate and informate industries less risky than those in transform industries. We document that IT investments are associated with more volatile future cash flows in transform industries than in automate or informate industries. The findings indicate that bond investors prefer IT investments in automate industries, where the cash flow payoffs to IT investment are smaller but more stable than in transform industries. Overall, these findings provide the important insight that bondholders’ perceptions of IT investments vary across industries based on bondholders’ aversion to the riskiness and the lack of collateralizability of IT investments. Senior managers should recognize that IT investments have implications for both operational performance and financing costs (e.g., costs of debt) of the firm, and they should consider the potential financial benefits of increased IT capabilities, such as the willingness of corporate bond investors to accept lower financing costs.

Multiple regression has a previously unrecognized “statistical blind spot” because when multicollnearity and measurement error are present, both path estimates and variance inflation factors are biased. This can result in overestimated t-statistics, and excessive false positives. PLS has the same weakness, but CB-SEM’s estimation process accounts for measurement error, avoiding the problem. Bringing together partial insights from a range of disciplines to provide a more comprehensive treatment of the problem, we derive equations showing false positives will increase with greater multicollinearity, lower reliability, greater effect size in the dominant correlated construct, and, surprisingly, with higher sample size. Using Monte Carlo simulations, we show that false positives increase as predicted. We also provide a correction for the problem. A literature search found that of IS research papers using regression or PLS for path analysis, 33% were operating in this danger zone. Our findings are important not only for IS, but for all fields using regression or PLS in path analysis.