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743 items in total found

Journal Articles | 2022

The Influence of status on evaluations: Evidence from online coding contests

Swanand J. Deodhar, Yash Babar, and Gordon Burtch

MIS Quarterly

 

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Journal Articles | 2022

Evaluating the efficacy of demand-side communication interventions on claiming rights: evidence from an action research field experiment in India

Akshay Milap, and Ankur Sarin

Human Communication Research

Communication-based interventions increasingly characterize attempts to strengthen policy implementation, especially policies targeting disadvantaged populations who despite their eligibility often fail to access potential benefits. However, factors that determine their effectiveness remains an open empirical question. To examine elements of effective communication in the exercising of rights, we designed and implemented a randomized field experiment around a public informational assistance campaign, spanning an entire urban district in India as part of a larger action research initiative. Situated within the context of India’s ambitious “Right to Education” Act, our intensive campaign employed distinct instruments varying in terms of trustworthiness, expertise, and media richness—frontline public health workers, trained student volunteers, and an interactive voice response system—to assist individuals in the claiming process. While our results reiterate the value of information, we find these effects to be less pronounced for the most disadvantaged. Our results also emphasize the role of expertise in navigating complex administrative processes. However, our analysis points to the necessity of complementing communication-based interventions with other supply-side enabling measures that ensure they aid the most disadvantaged.

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Journal Articles | 2022

Sparsistent filtering of comovement networks from high-dimensional data

Arnab Chakrabarti, and Anindya S. Chakrabarti

Journal of Computational Science

Network filtering is a technique to isolate core subnetworks of large and complex interconnected systems, which has recently found many applications in financial, biological, physical and technological networks among others. We introduce a new technique to filter large dimensional networks arising out of dynamical behavior of the constituent nodes, exploiting their spectral properties. As opposed to the well known network filters that rely on preserving key topological properties of the realized network, our method treats the spectrum as the fundamental object and preserves spectral properties. Applying asymptotic theory of high-dimensional covariance matrix estimation, we show that the proposed filter can be tuned to interpolate between zero filtering to maximal filtering that induces sparsity via thresholding, while having the least spectral distance from a consistent (non-)linear shrinkage estimator. We demonstrate the application of our proposed filter by applying it to covariance networks constructed from financial data, to extract core subnetworks embedded in full networks.

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Journal Articles | 2022

Fairness over time in dynamic resource allocation with an application in healthcare

Andrea Lodi, Philippe Olivier, Gilles Pesant, and Sriram Sankaranarayanan

Mathematical Programming

Decision making problems are typically concerned with maximizing efficiency. In contrast, we address problems where there are multiple stakeholders and a centralized decision maker who is obliged to decide in a fair manner. Different decisions give different utility to each stakeholder. In cases where these decisions are made repeatedly, we provide efficient mathematical programming formulations to identify both the maximum fairness possible and the decisions that improve fairness over time, for reasonable metrics of fairness. We apply this framework to the problem of ambulance allocation, where decisions in consecutive rounds are constrained. With this additional complexity, we prove structural results on identifying fair feasible allocation policies and provide a hybrid algorithm with column generation and constraint programming-based solution techniques for this class of problems. Computational experiments show that our method can solve these problems orders of magnitude faster than a naive approach.

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Journal Articles | 2022

Cross-border environmental regulation and firm labor demand

Pavel Chakraborty, Anindya S. Chakrabarti, and Chirantan Chatterjee

Journal of Environmental Economics and Management

In 1994, due to environmental concerns, Germany banned a chemical called ‘Azo-dyes’, a primary input for the leather and textiles firms in India (a key exporter). Exploiting this as a quasi-natural experiment, we examine the effects of this cross-border regulatory change on labor compensation, particularly managerial, for both Indian upstream (dye-producing) and downstream (leather and textile) firms. We find that the regulation increased compensation of managers by 1.3%–18% in dye-producing firms compared to other chemical firms. This is due to the combination of changes such as investing in R&D, product churning, import of high-quality intermediates, due to the ban, which led to this change in within-firm labor composition. This increase in overall compensation is driven only by fixed component (wages), consistent with the effects of a long-run shock. We find no such effects for downstream firms. We believe, our study is one of the first to show that just like tariff, non-tariff barriers (NTBs) can also significantly affect within-firm labor composition.

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Journal Articles | 2022

Understanding “reverse” knowledge flows following inventor exit in the semiconductor industry

Mayank Varshney, and Amit Jain

Technovation

Organizational learning research suggests that employee exit lowers firm performance by eroding its human and social capital. We have a rather limited understanding of the conditions under which exit from a focal firm, defined as the firm from which exit takes place, may stimulate learning and reverse knowledge flows from the hiring firm. We developed a model of learning-by-exit to address this gap and tested it using a long panel of data (1985–2012) from the semiconductor industry. Our model suggests that the focal firm is likely to benefit more from reverse knowledge flows from the hiring firm when it is less aware of the latter. A focal firm is less aware of the hiring firm when there have been no prior inter-firm interactions between them, and when they are separated by a larger geographic and technological distance. Econometric analysis of our data using zero-inflated Poisson regressions provides empirical support for our model. This research contributes to our understanding of knowledge spillovers by highlighting the criticality of firm heterogeneity in the relationship between employee exit and reverse knowledge flows.

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Journal Articles | 2022

Intervening on impostor phenomenon: prospective evaluation of a workshop for health science students using a mixed-method design

Shine Chang, Hwa Young Lee, Cheryl Anderson, Kava Lewis, Devasmita Chakraverty, and Melinda Yates

BMC Medical Education

Unaddressed impostor feelings that impede developing interest in science and self-efficacy in conducting research have a dispiriting effect that perpetuates unsatisfactory diversity in the health science workforce when such feelings are experienced more by those historically underrepresented in the workforce. This warrants effective interventions to reduce the impact of impostor feelings and related factors that diminish career resilience. We examined the effects of a 90-minute workshop on impostor perceptions and growth mindset to raise awareness of impostor phenomenon (IP) and develop skills to manage IP successfully for students attending a 10-week summer research experience program.

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Journal Articles | 2022

Faculty experiences of the impostor phenomenon in STEM fields

Devasmita Chakraverty

CBE- Life Sciences Education

Successful people experiencing impostor phenomenon consider themselves less competent and less worthy of their positions or achievements. They attribute their success to luck, deceit, fraudulence, and others being kind to them instead of their own competence. Prior research has focused primarily on students in higher education; faculty experiences of impostor phenomenon in science, technology, engineering, and mathematics (STEM) fields are not well understood. The research question guiding this inquiry was: “What kind of academic events or activities could contribute to faculty experiences of impostor phenomenon in STEM?” Using a qualitative analysis of 56 interviews, this U.S.-based study examined occurrences and experiences among faculty who self-identified as experiencing impostor phenomenon. A prior survey from the same participants revealed that they were predominantly White and female, experiencing moderate, high, or intense impostor phenomenon. Thematic interview analysis revealed that impostor phenomenon could be related to the following: 1) peer comparison, 2) faculty evaluation, 3) public recognition, 4) the anticipatory fear of not knowing, and 5) a perceived lack of competency. A comparison with findings from the larger study revealed that there are commonalities among faculty, PhD student, and postdoctorate experiences of impostor phenomenon in STEM. This necessitates professional development opportunities that could address self-limiting beliefs across the academic pipeline.

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Journal Articles | 2022

Pay-for-performance, procedural justice, OCB and job performance: a sequential mediation model

Vishal Gupta, Shweta Mittal, P. Vigneswara Ilavarasan, and Pawan Budhwar

Personnel Review

Building on the arguments of expectancy theory and social exchange theory, the present study provides insights into the process by which pay-for-performance (PFP) impacts employee job performance.

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Journal Articles | 2022

Research and market structure: Evidence from an antibiotic-resistant pathogenic outbreak

Mayank Aggarwal, Anindya S. Chakrabarti, Chirantan Chatterjee, and Matthew J. Higgins

Research Policy

We provide causal evidence that upstream research shocks impact unconnected downstream product markets. Focusing on the Indian pharmaceutical market, we use a natural experiment involving a publication that identified a pathogenic outbreak involving a carbapenem antibiotic resistant superbug. Consistent with theory, we find that this upstream research shock caused multinational firms selling carbapenem antibiotics in India to reduce their downstream market exposure. Rational antibiotic stewardship implies that we should observe a similar response by domestic Indian firms. Surprisingly, we observe the opposite, domestic Indian firms filled the void in the market left by multinational firms. We confirm this aggregate finding with prescription level data; Indian physicians prescribed fewer focal multinational products relative to domestic firm products. Results are robust to alternate control groups and placebo testing. Implications for antibiotic resistance, global health policy and innovation policy are discussed.

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