Abstract Objective The objective was to understand how people respond to COVID-19 screening chatbots. Materials and Methods We conducted an online experiment with 371 participants who viewed a COVID-19 screening session between a hotline agent (chatbot or human) and a user with mild or severe symptoms. Results The primary factor driving user response to screening hotlines (human or chatbot) is perceptions of the agent’s ability. When ability is the same, users view chatbots no differently or more positively than human agents. The primary factor driving perceptions of ability is the user’s trust in the hotline provider, with a slight negative bias against chatbots’ ability. Asians perceived higher ability and benevolence than Whites. Conclusion Ensuring that COVID-19 screening chatbots provide high quality service is critical, but not sufficient for widespread adoption. The key is to emphasize the chatbot’s ability and assure users that it delivers the same quality as human agents.

Information systems researchers have drawn on the resource-based view (RBV) and dynamic capabilities theory to offer a sharper theoretical lens to study the impact of information technology (IT) enabled capabilities on organizational performance. In this study, we propose a new conceptualization of IT-enabled production capability, based on the ability of a manufacturing plant to use its mix of resource inputs to maximize its process outputs. Our approach extends the literature on firm capability using data envelopment analysis (DEA), a nonparametric approach for estimating relative efficiencies of decision-making units. We tested our models using plant-level data collected from a sample of U.S. plants. Our study makes a key contribution by developing a new methodology to measure IT business value with respect to the role of IT-enabled production capability. We operationalize a new DEA-based measure of capability using the relative efficiency of converting plant inputs into process outputs, a significant departure from extant research that has primarily focused on subjective and absolute measures to conceptualize capability.

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Objectives: Despite substantial attention on hospital readmission rates, the impact of the Hospital Readmission Reduction Program (HRRP) on a comprehensive set of Triple Aim goals has not been studied: improve hospital quality, reduce cost, and improve patient experience. Methods: We analyze inpatient claims data from 2006 to 2015 from the Dallas Fort Worth Hospital Council Foundation with a panel of 27,397 patients with chronic obstructive pulmonary disease and congestive heart failure. We deploy a quasi-natural experiment using a difference-in-difference specification to estimate the effect of HRRP effect on readmission rates, length of stay (LOS), and hospital satisfaction. Results: We find that the likelihood of 30-day readmissions declined by 2.6%, average LOS decreased by 7.9%, and overall hospital rating increased by 2.1% among hospitals that fell under the scope of the HRRP, compared to non-HRRP hospitals. Our results provide evidence of a spillover effect of the HRRP in terms of its impact not only on Medicare patients, but across all insurance types, and other performance measures such as cost and patient experience. Conclusion: Our findings indicate that HRRP hospitals do not trade-off reductions in readmission rates with lower quality across other patient health outcomes. Rather, we find evidence that the HRRP has affected all 3 dimensions of the Triple Aim with respect to patient and hospital outcomes.

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