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Journal Articles | 2020

Capacitated multi-period maximal covering location problem with server uncertainty

Amit Kumar Vatsa and Sachin Jayaswal

European Journal of Operational Research

We study the problem of assigning doctors to existing, non-operational Primary Health Centers (PHCs). We do this in the presence of clear guidelines on the maximum population that can be served by any PHC, and uncertainties in the availability of the doctors over the planning horizon. We model the problem as a robust capacitated multi-period maximal covering location problem with server uncertainty. Such supply-side uncertainties have not been accounted for in the context of multi-period facility location in the extant literature. We present an MIP formulation of this problem, which turns out to be too difficult for an off-the-shelf solver like CPLEX. We, therefore, present several dominance rules to reduce the size of the model. We further propose a Benders decomposition based solution method with several refinements that exploit the underlying structure of the problem to solve it extremely efficiently. Our computational experiments show one of the variants of our Benders decomposition based method to be on average almost 1000 times faster, compared to the CPLEX MIP solver, for problem instances containing 300 demand nodes and 10 facilities. Further, while the CPLEX MIP solver could not solve most of the instances beyond 300 demand nodes and 10 facilities even after 20 hours, two of our variants of Benders decomposition could solve instances upto the size of 500 demand nodes and 15 facilities in less than 0.5 hour, on average.

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Journal Articles | 2020

stochastic loss reserving: A new perspective from a Dirichlet model

Karthik Sriram and Peng Shi

Journal of Risk and Insurance

Forecasting the outstanding claim liabilities to set adequate reserves is critical for a nonlife insurer's solvency. Chain–Ladder and Bornhuetter–Ferguson are two prominent actuarial approaches used for this task. The selection between the two approaches is often ad hoc due to different underlying assumptions. We introduce a Dirichlet model that provides a common statistical framework for the two approaches, with some appealing properties. Depending on the type of information available, the model inference naturally leads to either Chain–Ladder or Bornhuetter–Ferguson prediction. Using claims data on Worker's compensation insurance from several U.S. insurers, we discuss both frequentist and Bayesian inference.

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Journal Articles | 2020

Why do institutions revert? Institutional elasticity and petroleum sector reforms in India

Kshitij Awasthi, K. V. Gopakumar, and Abhoy K. Ojha

Business and Society

The institutional change literature has predominantly focused on successful changes and sparsely on failed changes, but the idea of institutional fields reverting to their pre-change or near pre-change state, after change attempts, remains underexplored. Although recent studies have explored similar phenomenon from the perspective of actors resisting change and trying to restore status quo, a field-level understanding of the processes and the dynamics associated with it remains underexamined. The present study, using the case of reforms in the field of petroleum exploration and production in India, examines an institutional change where the institution, once modified, gradually reverted near to its prechange state. We suggest the concept of institutional elasticity to explain such reverting of institutions, and elaborate on three boundary conditions—scope of change, pace of change, and field-level actor constellations—which have implications for the relationship between institutional elasticity and reverting of institutions.

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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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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

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

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

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

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

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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