Information & Management最新文献

Two leading digital entrepreneurial firms responded to a digital disruption differently. One adapted, whereas the other stagnated and eventually went bankrupt. In this inductive multi-case study, we strive to understand how they came to do so. Through constant comparison analysis between data, emerging theory, and existing literature, we develop a nuanced theoretical model suggesting that for entrepreneurial firms, having an abstract mission and pursuing diverse digital options actually constrain firms’ ability to respond to a digital disruption. But a specific mission and selective options enable adaptive agility. Overall, our emergent process theory highlights critically overlooked entrepreneurial firms, which are increasingly facing disruptions from powerful, established firms. Our emergent theory also prompts us to reconsider the conventional wisdom that digital options inherently enable agility.

The retention of audiences has become a pressing issue in the paradigm of livestreaming electronic commerce. Embracing the cognitive appraisal theory of emotions, this study develops a research model to gauge the relationship between emotion and audience retention. The results from 1,218,692 bullet comments from 491,348 users in 946 livestreaming sessions indicate that users’ valence and arousal affect retention positively, while the two dimensions of streamers’ emotions exert impacts in opposite directions. We further discover that intimacy has significant moderating effects in the research model. These findings emphasize the importance of understanding emotional dynamics in LSE in promoting audience retention.

With the prevalence of online healthcare communities (OHCs), increasingly more people are seeking health-related information in OHCs. However, the large amount of health-related knowledge of varying quality poses a challenge for people to quickly find truly helpful knowledge. This study proposes a framework for automatically identifying helpful health-related knowledge based on a knowledge adoption model and machine learning techniques. Extensive experiments on the dataset from one of China's largest OHCs have demonstrated the superiority of our framework. This study strengthens the understanding of readers’ value judgments of online health-related knowledge and enriches research in information systems and knowledge management.

This article investigates how a firm's supplier integration influences supply chain risk management (SCRM) practices and how these relationships are influenced by information technology (IT) agility and managerial ties. We further conduct fuzzy set qualitative comparative analysis (fsQCA) as a supplement. Matched survey data were collected from 148 firms in China, our results find that supplier integration influences both SCRM practices positively. Moreover, our results reveal that IT agility strengthens the effect of supplier integration on both supply chain robustness and resilience. Furthermore, business ties weaken the effect of supplier integration on supply chain resilience. In contrast, political ties weaken the effect of supplier integration on supply chain robustness, yet strengthen the effect of supplier integration on supply chain resilience. The results of fsQCA are largely consistent with our regression findings but also provide more interesting insights.

Drawing on the technology–organization–environment (TOE) framework, this article examines the influence of TOE factors on the success of digital transformation (DT) in manufacturing export small and medium-sized enterprises, and how these factors are configured to explain DT success. While PLS-SEM results show the individual effect of TOE factors, fsQCA results reveal five paths with different configurations for DT success. fsQCA results complement and extend the results of PLS-SEM analysis by showing that a condition can be present or absent depending on how it is combined with other factors. The combination of these two methodological approaches provides a more nuanced understanding of DT.

The rise of blockchain technology has sparked interest in decentralized identity management (DIdM). However, DIdM's interdisciplinary nature has led to a fragmented understanding. We propose a “Task Structure-Technological Properties-Fit” framework to clarify the application of DIdM across tasks and contexts. We conducted a comprehensive review of 149 DIdM papers to define task structure (task goals and stakeholder values), task goals (identity value creation and value maintenance), stakeholders (users, service providers, identity issuers, regulators, and infrastructure builders), and DIdM properties (interoperability and self-sovereignty). We explored how these elements could align and then highlight research gaps and present a DIdM research agenda.

Online physician recommender systems alleviate information overload by automatically recommending the best-fit physicians to patients. In contrast to general recommendations, physicians with greater uncertainty (i.e., greater variance in patients’ feedback) may not be preferred as this could affect patients’ treatment. However, most existing recommender systems don't consider uncertainty, reducing systems’ reliability and patients’ readiness to trust. To address this concern, this study leverages Bayesian theory and develops an uncertainty-aware online physician recommender system, including a Bayesian deep collaborative filtering (BDCF) model and a novel uncertainty-aware ranking algorithm. Experiments on real-world data demonstrate the superiority of BDCF and the ranking algorithm.

Time scarcity deals, which offer time-limited discounts, are prevalent in online shopping. These deals have two temporal aspects: deal time and lead time. Deal time, the remaining duration before the discount expires, signals scarcity and enhances the deal's appeal. In contrast, lead time, the delay between purchase and receipt/consumption, postpones gratification and diminishes the deal's attractiveness. This study proposes that as deal time and lead time fluctuate, they progressively bring consumers psychologically closer to the act of purchase/consumption. Drawing on construal level theory, we contend that firms can use image zooming as a digital tool to generate product images at various zoom levels and align with the psychological distances induced by deal time or lead time throughout the deal's availability. This strategy amplifies the positive effects of deal time and mitigates the negative impacts of lead time. Our research model is validated by data from three experiments. We discovered that (1) product image zooming affects consumers’ psychological proximity to an online deal; (2) when a deal with a short (long) deal/lead time is paired with a zoom-in (zoom-out) product image, deal evaluation and purchase intention increase; and (3) these effects are mediated by consumers’ “feeling right” experience during deal evaluation, which arises from a match between the construal levels prompted by the temporal feature and the product image. Theoretical contributions and managerial implications are discussed.

Short video commerce has become increasingly prevalent; however, the factors affecting customer engagement have not been adequately examined. Drawing on social learning theory, attitude transfer theory and relationship norms theory, we explored how social learning behavior from three dimensions of atmospheric cues is associated with customers’ attitudes, how such attitudes mediate these engagement relationships, and also how the relationship norms moderate the mediating effect of attitude. The empirical findings obtained through the PLS-SEM largely support the hypotheses. The fsQCA results illustrate how combinations of antecedents can lead to high customer engagement. This study contributes to the literature on short video commerce, customer attitudes, and relationship norms, and provides influencers and managers with practical strategies to improve customer engagement.

Increasingly, large organisations are turning to cybersecurity leaders to protect their information resources against attack. However, because cybersecurity leadership roles are new, educational literature and practice targeting this role are nascent. In this systematic review, we assess the value of case-based learning (CBL) in educating cybersecurity leaders. We also aim to discover what gaps, if any, exist in this body of research. We find that cybersecurity leaders’ attitudes and metacognitive abilities are important but overlooked elements of their competence, and that CBL has potential to develop these competencies. The article concludes with a competency matrix and agenda for further research.