In pursuit of notable reputations, organizations commonly engage their stakeholders using various online mechanisms. While “reputation signaling” via online user engagement is commonplace, its implications in the context of user-generated content (UGC) remain largely unaddressed. This study empirically explores the impact of UGC on hospital reputational dynamics. A unique panel dataset was analyzed using a lagged model approach to determine the effects of signals of quality, awareness, and content variance on hospital prominence and quality as well as the impact of reputation on financial performance. The findings suggest that quality signals significantly impact patient-perceived quality ratings, and signals of awareness and content variance significantly impact prominence rating. Also, in contrast to prominence, perceived quality significantly impacts financial performance. Given the ready availability of user-generated feedback, these findings can inform patient-provider online engagement strategies and related budget allocations. Furthermore, they highlight the unique role of Facebook ratings as an antecedent to quality and prominence dimensions of reputation.

A burgeoning stream of sustainability research explores the role of companies’ top management team (TMT) characteristics in corporate sustainability efforts, while another stream investigates the effect of a company’s supply chain position on its likelihood of engaging in sustainability. This study shows the importance of integrating the two research streams by demonstrating that supply chain position moderates the relationship between TMT characteristics and sustainability and thus establishes boundary conditions for this relationship. By matching 758 corporate sustainability initiatives with control observations, our results show that the size of the top executive team and the average age of its members, two well-known predictors of corporate sustainability, are distinctly moderated by supply chain position. While business-to-business (B2B) companies are less likely to report a sustainability initiative compared to business-to-consumer (B2C) organizations, we found that B2B TMT size has a greater positive effect on sustainability initiative likelihood than B2C TMT size. Conversely, average B2C TMT age has greater predictive power in explaining sustainability initiative likelihood than average B2B TMT age. The implications of these findings in advancing corporate sustainability and organizational change are discussed.

Background: Opioid-related deaths constitute a problem of pandemic proportions in the United States, with no clear solution in sight. Although addressing addiction—the heart of this problem—ought to remain a priority for health practitioners, examining the community-level psychological factors with a known impact on health behaviors may provide valuable insights for attenuating this health crisis by curbing risky behaviors before they evolve into addiction. Objective: The goal of this study is twofold: to demonstrate the relationship between community-level psychological traits and fatal opioid overdose both theoretically and empirically, and to provide a blueprint for using social media data to glean these psychological factors in a real-time, reliable, and scalable manner. Methods: We collected annual panel data from Twitter for 2891 counties in the United States between 2014-2016 and used a novel data mining technique to obtain average county-level “Big Five” psychological trait scores. We then performed interval regression, using a control function to alleviate omitted variable bias, to empirically test the relationship between county-level psychological traits and the prevalence of fatal opioid overdoses in each county. Results: After controlling for a wide range of community-level biopsychosocial factors related to health outcomes, we found that three of the operationalizations of the five psychological traits examined at the community level in the study were significantly associated with fatal opioid overdoses: extraversion (β=.308, P<.001), neuroticism (β=.248, P<.001), and conscientiousness (β=.229, P<.001). Conclusions: Analyzing the psychological characteristics of a community can be a valuable tool in the local, state, and national fight against the opioid pandemic. Health providers and community health organizations can benefit from this research by evaluating the psychological profile of the communities they serve and assessing the projected risk of fatal opioid overdose based on the relationships our study predict when making decisions for the allocation of overdose-reversal medication and other vital resources.

The Centers for Disease Control and Prevention promoted the Test-to-Stay (TTS) program to facilitate in-person instruction in K-12 schools during COVID-19. This program delineates guidelines for schools to regularly test students and staff to minimize risks of infection transmission. TTS enrollment can be implemented via two different consent models: opt-in, in which students do not test regularly by default, and the opposite, opt-out model. We study the impacts of the two enrollment approaches on testing and positivity rates with data from 259 schools in Illinois. Our results indicate that after controlling for other covariates, schools following the opt-out model are associated with 84% higher testing rate and 30% lower positivity rate. If all schools adopted the opt-out model, 20% of the total lost school days could have been saved. The lower positivity rate among the opt-out group is largely explained by the higher testing rate in these schools, a manifestation of status quo bias.

During the COVID-19 pandemic, online auction markets gained significant importance for their efficient and transparent handling of the shift in economic activity. Renowned digital car auction platform Bring a Trailer (BaT) experienced remarkable growth, with its revenue reaching $828 million in 2020. This study investigates the factors contributing to BaT's success, focusing on the role of its unique community comment feature, which leverages the collective intelligence of its users, known as wisdom of the crowd (WOC) in IS literature. Analyzing a dataset of 13,451 car listings, the study explores how WOC elements such as information quality and user identity impact auction performance. The analysis reveals that helpful WOC content positively influences auction outcomes, reducing information asymmetry and increasing market efficiency. The impact of WOC contributor reputations, however, showed less consistent results. These findings are relevant for stakeholders in the automotive market, providing insights to inform decision-making in online auction markets.

Can educational institutions open up safely amid COVID-19? We build an epidemiological model to investigate the strategies necessary for institutions to reopen. The four measures that are most relevant for in-person opening are: (i) wide-spread rapid testing, possibly saliva-based, (ii) enforcement of mask wearing, (iii) social distancing, and (iv) contact tracing. We demonstrate that institutions need to test at a relatively high level (e.g., at least once every week) in the initial phases of reopening. Contact tracing is relatively more important when the positivity rate from random testing is relatively low, which is likely during the initial phases. A Bayesian adaptive testing strategy based on positivity rates can help institutions optimally manage the costs and risks of reopening. Finally, we provide empirical estimates of some of the educational institutions opening up experience and comment on mitigation strategies. We also provide an estimate of locational effects of institution on mitigation strategies. This paper contributes to the nascent literature on combating the COVID-19 pandemic and is especially relevant for large-scale organizations. This work is motivated and guided by the SHIELD program of UIUC.