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821 items in total found

Journal Articles | 2020

EHR application portfolio and hospital performance: Effects across hospitals with varying administrative scale and clinical complexity

Pankaj Setia, Nirup Menon, and Sankara Subramanian Srinivasan

Information & Management

Electronic Health Record (EHR) has the potential to transform the work required to create and deliver healthcare services. This has triggered large-scale adoption across hospitals. However, whether all hospitals obtain a similar effect from their EHR implementations remains an important question because there are significant differences differences in characteristics of hospitals adopting these systems. To examine differences in effects across hospitals, we examine whether the impacts of EHR applications are contingent on work domains, by assessing performance effects across hospitals with varying administrative scale and clinical complexity. Because EHRs constitute a suite of applications with different functionalities, examining the effects of different sets of applications is challenging due to nonlinear interdependencies between applications. Therefore, we use an archetype approach, identifying synergistic EHR (EHRSYN) archetype as an ideal portfolio—a conceptual anchor for a hospital’s EHR portfolio. We test contingencies by combining this technology archetype with the work domains—administrative scale and clinical complexity. We test our hypotheses using empirical data from 137 hospitals in California, hypothesizing the differences in effects of EHRs on financial, operational, and clinical performances across hospitals with different administrative scales (size) and clinical complexities (case-mix) of work. While hospitals gain the most by implementing a portfolio close to the EHRSYN archetype, our nuanced models reveal that the benefits of such portfolios increase for large hospitals and are greater for hospitals treating less complex cases. These findings underscore how variations in applications used and work domains demarcate boundaries related to the performance effects of EHRs. We present a detailed discussion of the theoretical contributions and practical implications of our findings.

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Journal Articles | 2020

It runs in the family: The role of family and extended social networks in developing early science interest

Devasmita Chakraverty, Sarah N Newcomer, Kelly Puzio, and Robert H Tai

Bulletin of Science, Technology & Society

Research shows that early scientific interest is associated with science degree completion and career selection. However, little is known about the conditions that support early scientific interest. Using a “funds of knowledge” theoretical framework, this study examined the role of parents, family, and extended social networks in fostering early interest in science. Using interview narratives from 116 scientists (physicists and chemists) in the United States, we conducted a qualitative thematic content analysis. Findings suggest that children who become scientists in adulthood often received early, informal opportunities to use and manipulate material objects and discover how the world works. Second, families used a wide variety of scientific terms at home and encouraged children to pursue their interests whether in science or other fields. Third, these future scientists were often networked with extended family members or friends to observe and do science when they were quite young. Collectively, these findings highlight the specific ways in which families fostered early scientific interest and aided in supporting a student-directed learning environment.

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Journal Articles | 2020

Different eyes on the same prize: implications of entry timing heterogeneity and incentives for contestant effort in innovation tournament

Swanand J Deodhar

Journal of Business Research

Purpose

This paper examines an apparent contrast in organizing innovation tournaments; seekers offer contestant-agnostic incentives to elicit greater effort from a heterogeneous pool of contestants. Specifically, the study tests whether and how such incentives and the underlying heterogeneity in the contestant pool, assessed in terms of contestants' entry timing, are jointly associated with contestant effort. Thus, the study contributes to the prior literature that has looked at behavioral consequences of entry timing as well as incentives in innovation tournaments.

Design/methodology/approach

For hypothesis testing, the study uses a panel dataset of submission activity of over 60,000 contestants observed in nearly 200 innovation tournaments. The estimation employs multi-way fixed effects, accounting for unobserved heterogeneity across contestants, tournaments and submission week. The findings remain stable across a range of robustness checks.

Findings

The study finds that, on average, late entrant tends to exert less effort than an early entrant (H1). Results further show that the effort gap widens in tournaments that offer higher incentives. In particular, the effort gap between late and early entrants is significantly wider in tournaments that have attracted superior solutions from several contestants (H2), offer gain in status (H3, marginally significant) or offer a higher monetary reward (H4).

Originality/value

The study's findings counter conventional wisdom, which suggests that incentives have a positive effect on contestant behavior, including effort. In contrast, the study indicates that incentives may have divergent implications for contestant behavior, contingent on contestants' entry timing. As the study discusses, these findings have several implications for research and practice of managing innovation tournaments.

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Journal Articles | 2020

A Note on “The facility location problem with limited distances”

Prahalad Venkateshan

Transportation Science

In this paper, it is shown that the polynomially bounded enumerative procedure to solve the facility location problem with limited distances, originally described by Drezner, Mehrez, and Wesolowsky [Drezner Z, Mehrez A, Wesolowsky GO (1991) The facility location problem with limited distances. Transportation Sci. 25(3):183–187.], and subsequently corrected by Aloise, Hansen, and Liberti [Aloise D, Hansen P, Liberti L (2012) An improved column generation algorithm for minimum sum-of-squares clustering. Math. Programming 131(1–2):195–220.], can still fail to optimally solve the problem. Conditions under which the procedures succeed are identified. A new modified algorithm is presented that solves the facility location problem with limited distances. It is further shown that the proposed correction is complete in that it does not require further corrections.

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Journal Articles | 2020

Unpacking the effects of adverse regulatory events: Evidence from pharmaceutical relabelling

Matthew J. Higgins, Xin Yan, and Chirantan Chatterjee

Research Policy

We provide causal evidence that regulation induced product shocks significantly impact aggregate demand and firm performance in pharmaceutical markets. Event study results suggest an average loss between $569 million and $882 million. Affected products lose, on average, $186 million over their remaining effective patent life. This leaves a loss of between $383 million and $696 million attributable to declines in future innovation. Our findings complement research that shows drugs receiving expedited review are more likely to suffer from regulation induced product shocks. Thus, it appears we may be trading off quicker access to drugs today for less innovation tomorrow. Results remain robust to variation across types of relabeling, market sizes, and levels of competition.

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Journal Articles | 2020

The takeoff of open source software: A signaling perspective based on community activities

Pankaj Setia, Barry L. Bayus, and Balaji Rajagopalan

MIS Quarterly

A few open source software (OSS) products exhibit an abrupt and significant increase in downloads. However, the majority of OSS products fail to gain much interest. Identifying early success is important for catalyzing growth in OSS markets. However, previous OSS research has not examined early product success dynamics and assumes adoption to be a continuous process. We propose OSS takeoff in adoptions as a measure of eventual product success. Takeoff is a nonlinear inflection point separating the early development from the growth phase in the product lifecycle. Using arguments from the signaling literature, we propose that community activities send signals about product quality and reduce information asymmetry faced by potential adopters of OSS products. Estimating a Cox proportional hazard model using a large sample of OSS products from SourceForge, we find that takeoff times are significantly associated with signals of quality deficiency and improvement. Further, we find that target audience and product innovativeness moderate this relationship. Posted online August 10, 2020

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Journal Articles | 2020

Responses to COVID-19: The Role of governance, healthcare infrastructure, and learning from past pandemics

Amalesh Sharma, Sourav Bikash Borah, and Aditya C. Moses

Journal of Business Research

The ongoing COVID-19 outbreak has revealed vulnerabilities in global healthcare responses. Research in epidemiology has focused on understanding the effects of countries’ responses on COVID-19 spread. While a growing body of research has focused on understanding the role of macro-level factors on responses to COVID-19, we have a limited understanding of what drives countries’ responses to COVID-19. We lean on organizational learning theory and the extant literature on rare events to propose that governance structure, investment in healthcare infrastructure, and learning from past pandemics influence a country’s response regarding reactive and proactive strategies. With data collected from various sources and using an empirical methodology, we find that centralized governance positively affects reactive strategies, while healthcare infrastructure and learning from past pandemics positively influence proactive and reactive strategies. This research contributes to the literature on learning, pandemics, and rare events.

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Journal Articles | 2020

Celebrity endorsements in destination marketing: A three country investigation

Subhadip Roy, Wioleta Dryl, and Luciana de Araujo Gil

Tourism Management

The present study extends research on the role of celebrity endorsements in destination marketing by exploring various facets of the effect of celebrity endorsements in destination marketing on the consumer. More specifically, theories of source credibility, congruence, social identity and consumer cosmopolitanism, are used to build research questions that investigate the relative effectiveness of a celebrity endorsed tourism advertisement vis a vis a generic advertisement and the boundary conditions governing the same such as destination type (local/global), celebrity country of origin and consumer level factors. The research questions are addressed using four experimental studies in sequence. The same four experiments are run in three countries with different socio-cultural backgrounds to enhance generalization, with a combined sample size of 1073 respondents. Major findings suggest that a celebrity endorser is effective for a destination advertisement. Significant cross-country differences were observed in consumer affect depending on the choice of celebrity (local or global) and the destination type (i.e., domestic or international). The effects are also moderated by consumer cosmopolitanism. The study has multiple theoretical and managerial implications.

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Journal Articles | 2020

Disentangling shock diffusion on complex networks: identification through graph planarity

Sudarshan Kumar, Tiziana Di Matteo, and Anindya S Chakrabarti

Journal of Complex Networks

Large scale networks delineating collective dynamics often exhibit cascading failures across nodes leading to a system-wide collapse. Prominent examples of such phenomena would include collapse on financial and economic networks. Intertwined nature of the dynamics of nodes in such network makes it difficult to disentangle the source and destination of a shock that percolates through the network, a property known as reflexivity. In this article, we propose a novel methodology by combining vector autoregression with an unique identification restrictions obtained from the topological structure of the network to uniquely characterize cascades. In particular, we show that planarity of the network allows us to statistically estimate a dynamical process consistent with the observed network and thereby uniquely identify a path for shock propagation from any chosen epicentre to all other nodes in the network. We analyse the distress propagation mechanism in closed loops giving rise to a detailed picture of the effect of feedback loops in transmitting shocks. We show usefulness and applications of the algorithm in two networks with dynamics at different time-scales: worldwide GDP growth network and stock network. In both cases, we observe that the model predicts the impact of the shocks emanating from the USA would be concentrated within the cluster of developed countries and the developing countries show very muted response, which is consistent with empirical observations over the past decade.

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Journal Articles | 2020

A new solution approach for multi-stage semi-open queuing networks: an application in shuttle-based compact storage systems

Govind Lal Kumawat and Debjit Roy

Computers & Operations Research

Multi-stage semi-open queuing networks (SOQNs) are widely used to analyze the performance of multi-stage manufacturing systems and automated warehousing systems. While there are several methods available for solving single-stage SOQNs, solution methods for multi-stage SOQNs are limited. Decomposition of a multi-stage SOQN into single-stage SOQNs and evaluation of an individual single-stage SOQN is a possibility. However, the challenge lies in obtaining the job departure process information from an upstream single-stage SOQN to evaluate the performance of a downstream single-stage SOQN. In this paper, we propose a two-moment approximation approach for estimating the squared coefficient of variation of the job inter-departure time from a single-stage SOQN, which can serve as an input to link multi-stage SOQNs. Using numerical experiments, we test the robustness of the proposed approach for various input parameter settings for both single and multi-class jobs. We find that the proposed approach works quite well, particularly when the coefficient of variation of the job inter-arrival time is less than two. We demonstrate the efficacy of the proposed approach using a case study on a multi-tier shuttle-based compact storage system and benchmark our results with an existing approach. The results indicate that our approach yields more accurate estimates of the performance measures in comparison to the existing approach in the literature.

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