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3846 items in total found

Journal Articles | 2025

A note on income risks and their implications for wealth concentration

Mohsen Mohaghegh

Income risks are not accurately captured by standard AR processes that are common in the literature. This paper proposes a simple stochastic process which matches several moments in the data including the cross-sectional distribution of income and the distribution income risk, and can be easily used in models with uninsurable income risk. Incorporating this process into an off-the-shelf OLG model leads to a rise in wealth concentration narrowing the gap between traditional models and the data. However, the right tail of the wealth distribution remains significantly thinner than the data.

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Journal Articles | 2025

Synergistic associations of ambient air pollution and heat on daily mortality in India

Jeroen de Bont Ajit Rajiva Siddhartha Mandal Massimo Stafoggia Tirthankar Banerjee Hem Dholakia Amit Garg Vijendra Ingole Suganthi Jaganathan Itai Kloog Bhargav Krishna Kevin Lane R.K. Mall Jyothi Menon Amruta Nori-Sarma Dorairaj Prabhakaran Abhiyant Sur

Limited studies have evaluated the interaction between ambient air pollution and heat on mortality, especially in regions such as India, where extreme levels of both exposures occur frequently. Accordingly, we aimed to investigate the potential synergistic effects between ambient air pollution and heat on daily mortality in India.

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Journal Articles | 2025

New here? Lawyer up, please: Differences in external legal expenditure between new ventures and established firms in emerging economies

Bibek Bhattacharya

This study examines the differences in external legal expenditure between new and established firms in emerging economies and nuances the dominant view that firms in emerging economies primarily rely on relational strategies to tackle legal and regulatory challenges. Unlike established firms, new ventures lack legitimacy, making relational strategies less viable. Consequently, I theorize that relative to established firms, new ventures in emerging economies will invest more in formal legal strategies, such as hiring external legal services. However, due to financial constraints, their ability to do so will be contingent on financial slack. Analyzing a longitudinal dataset of 23,039 firms in India (1989–2022) using linear panel regression models, I confirm the presence of a positive relationship between new ventures and external legal expenditure, moderated by financial slack. This study contributes to the literature on emerging economies as well as the legal and regulatory aspects of entrepreneurship.

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Journal Articles | 2025

Pace of pro-market reforms, performance feedback, and strategic renewal actions of emerging economy firms

Manish Popli, Mehul Raithatha

How do firms in emerging economies react to competitive contexts shaped by the temporal advancement of pro-market reforms? With multi-country analysis, this research shows that as the pace of reforms increases in emerging economies, the incumbent firms engage in strategic renewal actions of internal development and external sourcing through acquisitions. Furthermore, this study integrates the problemistic search perspective and finds that facing a faster pace of pro-market reforms, firms with performance above the aspiration level prioritize augmentation in internal capabilities. In contrast, firms performing below the aspiration level prioritize either domestic or cross-border mergers and acquisitions. We test our hypotheses using 55,068 firm-year observations from 37 emerging economies from 1998 to 2019. This study contributes by providing a better understanding of 'when', 'how,' and 'why' firms from emerging economies take specific strategic renewal actions as their home markets evolve.

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Journal Articles | 2025

Navigating international entry via strategic alliances: Comparison of family and non-family firms

Sumit Chakraborty, Chitra Singla

International strategic alliances (ISAs) serve as an important vehicle for growth, international expansion, and access to technology and other resources. The choice of governance structure in ISAs—specifically, whether to form an international joint venture (IJV) or an international non-equity alliance (INEA)—is a pivotal decision for firms. However, despite the importance of this choice, the influence of firms' ownership heterogeneity on the choice remains underexplored. In order to address this gap, this study compares family-owned and non-family-owned firms to examine their differing preferences between IJVs and INEAs. Drawing on an integrated risk perspective and the mixed-gamble socioemotional wealth perspective, we argue that family firms exhibit a greater propensity to choose IJVs over INEAs than non-family firms. Moreover, we posit that this preference is amplified by two factors: (1) the industry-relatedness of the alliance partners and (2) the focal firm's prior experience in the partner's home country. Empirical analysis of 1216 cross-border dyadic alliances formed by publicly listed Indian firms between 2000 and 2022 provides robust support for our hypotheses. This study contributes to the literature on international strategic alliances and family firms' internationalization by shedding light on the nuanced governance preferences of family firms in cross-border collaborations.

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Journal Articles | 2025

Does location matter? A study of automotive clusters in India

Andreas Offenloch, Hans Sebastian Heese, Amit Karna

Researchers have become increasingly interested in the agglomeration of firms into industry clusters and the effects of such clusters on firms. We analyze the effects of exposure to original equipment manufacturers (OEMs) and industry clusters on supplier performance, focusing on the avoidance of operations disruptions and the support of a smooth production ramp-up at the OEM, by assessing the suppliers of a multinational automotive OEM in India. We study how the exposure of suppliers to the focal OEM and to clusters affects the ability of suppliers to continuously provide their parts to the OEM within pre-agreed schedules and specifications.

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Journal Articles | 2025

Men in beauty work and feminization of digital labor platforms

Sai Amulya Komarraju, Manisha Pathak-Shelat, Payal Arora, Usha Raman

Extant research on the gendered dynamics on digital labor platforms and care work is divided in terms of focus: (migrant) men involved in supposedly “masculine” work such as driving and delivery, and home-based repair work, and the feminized invisible work performed by women in home-based care-work such as domestic work and beauty work. While such scholarship has merit, it completely dismisses the particularities of the South Asian context where beauty work, considered to be ritually impure work, has historically been performed by men from the marginalized Nai caste. Foregrounding the views of men in beauty work, particularly Nai-barbers (on and off platform), our findings reveal that Nai-barbers find the relocation of work from barbershop to customer’s home by platforms particularly humiliating. The transition from being entrepreneurs, in charge of their barbershops, to mere workers supervised by both platforms and customers, evokes memories of the servitude their ancestors endured. The humiliation and degradation of work they experience are rooted in caste and colonial histories. Our findings underscore the need to go beyond the immediate temporal context to identify the conditions of work that workers find degrading, and situate the feminization of platform economy within the context of coloniality and casticization of power, thus bringing a necessary intersectionality that recognizes but goes beyond gender.

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Journal Articles | 2025

Fiber-to-the-home passive optical distribution network design: A new formulation and valid inequalities using polar duality

Y. K. Agarwal, Sachin Jayaswal

We study the problem of the optimal design of fiber-to-the-home (FTTH) optical access networks. Given a network of nodes and edges rooted at an optical distribution point (ODP) with a given demand for optical fibers at a subset of these nodes, the problem entails finding the optimal placement of splitters, which allows multiple demand points to share a common fiber between ODP and a splitter, such that sum of the costs of the fiber cables and the splitters is minimized. Additionally, it needs to decide on the optimal selection of a cable type of appropriate capacity on each edge of the network to carry the required traffic. The existing literature on FTTH access network design typically assumes the same number of splitting stages for all demand points—specifically, one in case of a single splitting problem (SSP) or two in case of a double splitting problem (DSP). We provide a mixed-integer programming (MIP) formulation of a mixed splitting problem (MSP), wherein some demand points can be served through one stage of splitting, whereas others can be served through two stages of splitting. We further propose several valid inequalities (VIs), with or without a pre-specified template, to strengthen the formulation. Through our computational experiments on large instances, we demonstrate the efficacy of our proposed VIs, which help improve the lower bound of the problem from 79% to 86.9% of the MIP optimal cost, on average. For the special cases of SSP and DSP, we show that our formulation produces much tighter lower bounds compared to the existing formulation in the literature. On top of that, our proposed VIs are comparatively much more effective in tightening the bounds. Specifically, our proposed formulation with our VIs consistently outperforms that available in the literature, being as much as 500 times faster in some instances.

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Journal Articles | 2025

A graph theoretic approach to assess quality of data for classification task

Payel Sadhukhan, Samrat Gupta

The correctness of predictions rendered by an AI/ML model is key to its acceptability. To foster researchers’ and practitioners’ confidence in the model, it is necessary to render an intuitive understanding of the workings of a model. In this work, we attempt to explain a model’s working by providing some insights into the quality of data. While doing this, it is essential to consider that revealing the training data to the users is not feasible for logistical and security reasons. However, sharing some interpretable parameters of the training data and correlating them with the model’s performance can be helpful in this regard. To this end, we propose a new measure based on Euclidean Minimum Spanning Tree (EMST) for quantifying the intrinsic separation (or overlaps) between the data classes. For experiments, we use datasets from diverse domains such as finance, medical, and marketing. We use state-of-the-art measure known as Davies Bouldin Index (DBI) to validate our approach on four different datasets from aforementioned domains. The experimental results of this study establish the viability of the proposed approach in explaining the working and efficiency of a classifier. Firstly, the proposed measure of class-overlap quantification has shown a better correlation with the classification performance as compared to DBI scores. Secondly, the results on multi-class datasets demonstrate that the proposed measure can be used to determine the feature importance so as to learn a better classification model.

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Journal Articles | 2025

Trading off travel distance and fatigue. The effect of storage, order batching, and pod selection in robotic mobile fulfillment systems

Zhongqiang Ma, René de Koster, Debjit Roy, Guohua Wu

Many e-commerce warehouses use robotic mobile fulfillment system (RMFS), where humans collaborate with robots to pick the orders. The performance of such systems depends on the joint performance of robots and humans. The performance of the workers is affected by fatigue, or the energy that it takes them to pick the items. In this paper, we study the effect of scattered storage assignment, order batching, and pod selection to minimise the total picker energy expenditure and the total robot transport distance. We introduce a mixed-integer programming formulation (called JIOPP) and introduce the NSGAII-ILS algorithm to heuristically solve it for real-world instances. Extensive numerical experiments on real-world instances show that NSGAII-ILS is competitive compared to state-of-the-art algorithms and can find Pareto solution sets that are closer to the true Pareto frontier. We evaluate the effects of batch sizes, the number of pod layers, and different pod selection policies. The results show that batching orders can save more than 35% of the picker's energy expenditure and more than 70% of the robot's transportation distance. Using the ‘golden zone’ layers on the pod selecting the right pod for retrieval are important for striking a balance between worker fatigue and order picking efficiency.

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