Knowledge that Transforms

With the growing number of shoppers entering e-marketplaces, e-retailers commonly use tailoring technology to cater to diverse shopper needs and gain a competitive advantage. However, the impact of shopper heterogeneity in this tailoring competition remains unclear. Focusing on e-retailers’ tailoring practice, we fill the gap by revealing its impact on e-marketplace channel competition and sellers’ coordination decisions. We find that shopper expertise with competing e-retailers and pricing contracts with product sellers significantly alter the downstream landscape, and all stakeholders should rethink e-retailers’ tailoring strategies. We discover that e-retailers may aim to sell to experienced consumers under a sell-to contract, while sellers target inexperienced consumers. Conversely, under a sell-on contract, the seller’s target aligns with the e-retailer of higher tailoring capabilities. Surprisingly, inexperienced consumers influence all market participants more than experienced consumers. Notably, the preferred target consumers of all parties may shift when tailoring is effective only for experienced consumers.

Corporate boards can significantly affect the value generated from information technology (IT) investments. An implicit assumption in the scarce research exploring this relationship is that boards operate as cohesive groups. Departing from the assumption, this study draws upon the literature on fault lines, which suggests that individual director attributes align or misalign, creating hypothetical dividing lines that split the board into multiple subgroups and influence their effectiveness. Based on extensive analyses of a panel of 2,463 firms over 2010-2020, we find that knowledge-based fault lines, which enhance knowledge diversity, enable IT value generation, and this effect is amplified in munificent environments, which motivate and enable the board subgroups to seek and share diverse knowledge. However, identity- and resource-based fault lines do not affect IT value generation. Thus, knowledge diversity on boards should be encouraged, but diversity based on social identities and resources might not matter when seeking IT value.

Are women more likely to shy away from competitive and uncertain environments when considering information technology (IT)-related work options, relative to men? Does gender play a role in the propensity to participate in the marketplace for competitive and uncertain work? The response to this has implications for understanding the participation rate of women within the IT sector, as well as for setting policy aimed at increasing the number of women in the IT industry. Addressing this question using data from organizations is difficult, given the presence of organizational and institutional confounds. In this paper, we investigate this research question through a series of lab experiments using three sets of suitable subjects: graduate students in Information Systems and Business Analytics programs, MTurk, and Prolific respondents with IT backgrounds. Using the experimental context of a competitive online labor market, we study how competition and wage uncertainty affect the decision to bid for a project as well as the wage expectations across gender. Our results across three studies show that (a) women are more likely to bid for projects with higher coordination needs: navigating, communicating across, and managing multiple domains, technological, functional, and geographical boundaries; and (b) women are also more likely to bid when there is higher competition. Our work contributes to a deeper understanding of the role of gender, competitiveness, and uncertainty within the IT industry, and informs managers and policymakers regarding the intrinsic preferences of early-stage IT professionals.

We study the interplay between cyber failures and information technology (IT) capability reputation (ITCAPR). Cyber failures often reveal vulnerable information systems (IS) processes and IT assets at their root that point to firm IT capability weakness. For external stakeholders, firm IT capability is unobservable and therefore a matter of perception or reputation. We theorize about cyber failures’ adverse impacts on firm market value and firm ITCAPR based on how external stakeholders reconcile their ex ante perception of firm IT capability strength, or established ITCAPR, and their perception of an ex post revelation of IT capability weakness by cyber failures. Our analysis of 264 cyber failures finds empirical support for our theory-based predictions. We find that ex post revelation of IT capability weakness leads external stakeholders to adjust downward their ex ante perceptions of firm IT capability proportional to the severity of IT capability weakness. Two ex post consequences are commensurate loss of firm market value and decline in firm ITCAPR. Based on our main finding, that external stakeholders perceive IT capability weakness as an endogenous contributory factor to cyber failures that leads to erosion of firm ITCAPR, we contribute to theory in significant ways. First, we theoretically complement a predominant research focus on IT capability strength as a value-relevant intangible asset by confirming that IT capability weakness is a value-relevant intangible liability as well as adding “vulnerability” or “weakness” as a distinctive process aspect absent from prior literature linking IS processes and IT capabilities. Second, we theoretically add to an almost exclusive focus of research on cyber failures’ short-term adverse effect on firm market value by documenting for the first time a time-lagged eroding effect on firm ITCAPR. Last, we theoretically show IT controls and particularly ones embedded in IS processes as an essential aspect of IT capability strength as well as cybersecurity protection and prevention.

Outsourcing is an important strategic decision of high-tech firms. However, while the research has extensively studied the implications of outsourcing to high-tech clients, its impact on high-tech vendors remains underexplored. This study empirically estimates the impact of government outsourcing contracts on high-tech vendors. Employing the earnings-return analyses framework, we find that, for high-tech vendors engaged in government outsourcing contracts, the stock market places a higher value on each unit of unexpected earnings compared to other firms. Additionally, this impact becomes stronger for contracts with longer terms, for contracts outsourced by the U.S. government or by countries with better political and economical stability. We obtain causal evidence through difference-in-differences (DID) analyses of high-tech firms’ initiations of government contracts. Mechanism analyses uncover two primary drivers behind this impact: increased persistence of future earnings and improved alignment between accrual earnings and cash flows. Overall, our research indicates that when valuing high-tech firms, the stock market incorporates information from supply-chain networks, especially that related to government customers. Our results underscore the importance of obtaining government outsourcing contracts for high-tech firms’ managers. Becoming a vendor to the government helps a high-tech firm reduce the uncertainty faced by its outside investors, who in turn value the high-tech firm’s earnings to a greater extent.

Depression is a growing health and societal problem that has become increasingly prevalent and burdensome. The detection or diagnosis of depression has been very challenging, especially for patients with other comorbidities. Digital phenotyping has emerged as a promising tool for automatic depression detection from user behavior data collected by sensors. However, existing digital phenotyping-based detection of depression has not considered the diagnostic uncertainty caused by similar symptoms shared between depression and other comorbidities, which may negatively affect detection accuracy. We propose a novel deep learning model that processes and fuses data from multiple sensors and addresses the diagnostic uncertainty based on evidence theory. We evaluate the proposed model against state-of-the-art models using sensor data. Our work makes significant contributions to design science research by proposing new artificial intelligence (AI)-based artifacts to deal with uncertainty and to mental health research by improving the accuracy of depression detection in the presence of comorbidity.

Given the imperative to innovate and stay ahead of their competition, organizations—called “seekers”—increasingly rely on the “wisdom of the crowds” to gain business insight. Motivated by monetary incentives, the desire to learn and the opportunity to enhance their reputation, “solvers” from the crowd participate in contests hosted by such seekers on crowdsourcing platforms. While the collective intelligence of the crowd is widely acknowledged to yield a diverse range of innovative solutions, the impact of the factors evoking contest competitiveness on the quality of these solutions remains unclear. Specifically, how competitiveness engendered by the interplay among the contest situational factors such as the nature of the contest’s economic incentives, the number of solving teams involved, their proximities to the winning position (relative position), and the contest’s complexity affects the solutions’ quality is not well understood. To bridge this knowledge gap, our research examines the direct effects of the number of solving teams and prize inequality on performance and clarifies the moderating effect of task complexity. We also investigate how the direct effects change across the relative positions of the solving teams (e.g. high-performing versus low-performing teams). The study extends the boundaries of tournament literature by demonstrating how crowdsourcing contests evoke distinct behavioral responses compared to traditional tournaments. Practically, it provides novel insights for contest designers on crafting effective prize structures to optimize participant performance.

Does it pay to appear unbiased in an attention-based economy where bias sells? We study this question in light of increased consumer partisan polarization and biases alongside greater technology usage and partisanship in journalism. Using a game-theoretic framework that captures the essential properties of the online news market, we show that polarization with biases may constrain neutral and partisan news websites’ engagement-enhancing strategies differently; and online news providers can strategically exploit consumer perceptions to maximize engagement-driven revenues. Our analysis suggests that neutral news outlets depend on polarization imbalance and perceptions of neutrality. Moreover, increased search costs and consumer bias toward partisan outlets can lessen the echo chamber effect in online news consumption. Our work advances discussions on online news neutrality, providing fresh insights into the “marketplace of ideas” view and source versus content neutrality in the face of increasing affective polarization.

This research examines how a firm’s cloud storage implementation affects different types of security breaches in both the short- and long-term. Building on the attention-based view, we find that cloud storage implementation positively relates to a firm’s external breaches and accidental internal breaches in the short-term. However, the positive relationship between cloud storage implementation and external breaches diminishes over time and becomes insignificant long-term. Our results demonstrate a long-term security advantage of cloud storage in reducing accidental internal breaches. We did not find a significant association between cloud storage and malicious internal breaches. Findings highlight the need for firms to direct limited resources to different security risks in the short- and long-term of cloud storage implementation over time. This research contributes to our understanding of cloud storage’s security implications and explicitly theorizes the role of attention in firm IT security management. We contribute to the attention-based view by contextualizing the theory to IT security. We highlight temporal dynamics through distinct attentional mechanisms, including selective attention, attentional flexibility, and attentional vigilance.

Mental health issues are a growing epidemic facing modern society. The Mental Health America Society estimated that nearly a fifth of the adult U.S. population suffered a mental illness in 2019-202...