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Software firms are increasingly adopting an open source strategy, allowing them to leverage the effort exerted by the open source community toward improving software quality. In addition to embracing a proprietary or fully open source strategy, several firms choose a partial openness strategy wherein only certain parts of the code are open source while the rest is proprietary. Specifically, when adopting a partial openness strategy, a firm may choose to make the core software code open source while keeping the extension software code proprietary or keep the core proprietary and make the extension open source. When making decisions related to different openness strategies, firms need to take into account the level of effort they are exerting toward the improvement of the quality of software, the level of engagement of the open source community, and pricing. Hence, the decisions related to a firm's openness strategy are not straightforward. While this is an important question for many firms, it has not been analyzed in the literature. In this research, we attempt to fill this important gap by analyzing different openness strategies in the context of resource allocation for fixing defects. Specifically, using a game-theoretic model, we explore when a firm should make its software fully open source or partially open source and when it should keep it proprietary. Our results show that when the baseline demand for the firm increases with the extent of openness, the firm should either make its software fully open or keep it proprietary and, importantly, should not rely on partial openness. Next, in scenarios where customers are highly sensitive to security risks, the demand loss to efficiency gain ratio has an important role in determining a firm's optimal openness strategies. These findings provide important insights to firms on how to effectively plan their openness strategies and also establish a basis for future research on the topic of partial openness. [ABSTRACT FROM AUTHOR]

This paper summarizes emerging practice and research issues in the health insurance industry. We provide an industry overview, epitomize business analytics applications, and outline current and emerging problems of interest to key stakeholders and researchers in information systems, operations management, and healthcare management. Specifically, we focus on three areas of research that are of importance to the health insurance industry as well as the healthcare system: (i) management and evaluation of intervention programs, (ii) creation of effective provider networks, and (iii) emerging issues such as the impact of a pandemic, patient communication and steering, and technological innovations in health care. We lay out brief details of how each of these problems can be formulated, where the data can be acquired (public and/or proprietary data sets), and provide guidance for solving them. For several of these problems, we provide models that span causal modeling, predictive modeling, and prescriptive modeling. [ABSTRACT FROM AUTHOR]

The economic significance of Internet of Things (IoT) platforms is evident from the proliferation of smart home assistant platforms like Amazon Alexa and Google Home that center themselves around providing unique and connected experiences to users. Customers do not perceive these platforms valuable if they do not experience adequate levels of quality and security from both the platform and applications (apps) they use. Therefore, the IoT platform provider as well as app developers need to go beyond collaboration and cocreate quality and security for each app on the platform. In this setting, we study the dynamics of the financial sustainability of the platform provider and app developers and find that the collaborative nature of the IoT platform has a significant role in the behavior and profitability of all parties. Specifically, a neutral entrant to the platform not only increases the effort levels of all existing parties, but also increases the profits due to network effects that are intertwined with economies of scale. We further find that a substantial number of apps are needed in the platform for an economically viable platform and that a less efficient platform leader needs even a larger application base. However, based on the number of apps on the platform and which party is more effective in the collaboration, the platform provider might need to provide additional incentives, or sometimes, extract additional rent from the app developers to financially sustain the platform. Furthermore, we verify our results in the presence of competition or complementarity among apps and further derive additional interesting results and managerial insights. For example, we find that the entry of a competing app may be beneficial for existing apps under some conditions. [ABSTRACT FROM AUTHOR]

We investigate the impact of health information exchange (HIE) use at the visit level on patient outcomes, such as future visit behavior and the number of procedures performed on the patient, and how the effects differ across patient and visit characteristics, for example, whether a patient has chronic conditions and whether a visit involves a hospital switch. Timely sharing of patient information is expected to decrease the fragmentation of care and improve decision‐making, diagnoses, and care plans, yet previous studies that examine the benefits of HIE use do not focus on these issues and are not unanimous in their findings in general about the benefits of HIEs. Further, prior studies generally focus on average effects with binary HIE measures, either using HIE adoption at the hospital level or whether HIE is accessed at the visit level. We argue that the benefits of HIE stem from the information contained within and are not equal across cases. We utilize a rich dataset of medical records from an HIE provider in New York. Our results show that the depth of information available for the patient in HIE use decreases the overall number of future visits, specifically, HIE use effectively reduces visits that are not preventative in nature while increases adherence to preventative care visits, aiding in the shift from treatment‐based care to preventative‐based care, that public health organizations have urged for. Further, HIE use lowers the number of procedures done at the focal visit. We have several other findings that have important implications for policymakers, healthcare providers, and patients. [ABSTRACT FROM AUTHOR]