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851 items in total found

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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Journal Articles | 2025

Broiler contracting in Punjab: Contract farming or wage work?

Naresh Singla, Sukhpal Singh

The persistence of agrarian crises and failure of crop diversification policies in green revolution regions of India such as Punjab necessitate exploring the role of allied agricultural sectors such as livestock for small farmer livelihood generation. A comprehensive analysis of broiler contract farming in Punjab shows that though broiler contract farming was inclusive, as growers were less resourceful, less literate and less experienced than their non-contract counterparts, value sharing with small growers did not happen. As a result, profitability from broiler rearing was lower in contract farming as compared to non-contract (independent) production. The case study suggests the collectivisation of small growers through cooperatives/producer company mechanisms to negotiate with the contracting agency in terms of prices and the effective regulation of contract farming for the protection of farmer interests.

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Journal Articles | 2025

Impact of virtual presence of others on social media service recovery evaluations: A cross-cultural perspective

Sanchayan Sengupta, Md Rokonuzzaman, Anand Kumar Jaiswal, Raffaele Filieri

With the growing prevalence of social media as a platform for customer complaints, understanding cross-cultural differences in service recovery becomes crucial. This research investigates how the presence of social media observers influences service recovery satisfaction across different cultures. We examine how cultural orientation shapes responses to service recovery efforts through three experiments that compare collectivistic and individualistic consumers. Our findings reveal that collectivists report lower satisfaction and brand loyalty intentions during partial social media recovery attempts compared to email-based recovery. However, when managers provide customized apologies on social media, collectivist consumers show significantly improved service recovery evaluations, particularly due to the role of face concern. We demonstrate the critical interaction between virtual presence, cultural orientation, and face concern in determining behavioral engagement with brands during recovery. Our research contributes to service recovery theory by integrating social impact theory with cross-cultural consumer behavior and offers practical guidelines for managing service failures.

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Journal Articles | 2025

Governance beyond borders: Exploring executive overconfidence and firm performance using meta-analysis

Promila Agarwal, Saneesh Edacherian, Amit Karna, Ashneet Kaur, Sudhanshu Maheshwari

This study examines the complex relationship between executive overconfidence and firm performance, highlighting the moderating role of country-level factors. By conducting a meta-analysis of 116 independent effect sizes from global studies, this research aims to clarify the ambiguous effects of executive overconfidence, emphasizing the significance of national contexts.

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Journal Articles | 2025

Predicting employees’ engagement using a framework of emotional resources and ethical climate

Gurjeet Kaur Sahi, Anand Kumar Jaiswal, Neil Anderson

Organizations are reluctant to hire emotionally exhausted employees. However, current research has partially explored the implications of retaining both emotionally intelligent and emotionally exhausted employees. Hence, the question arises: do emotionally intelligent employees always remain meaningfully engaged in their work? And do emotionally exhausted employees adversely impact the organization? In our study, we empirically examined the role of ethical climate in assessing the impact of employees’ emotional intelligence and exhaustion on their work engagement. We collected data from 450 employees of private sector banks in India. The results showed that an ethical climate was positively correlated with employees’ work engagement. Additionally, we found that the influence of emotional intelligence was positive and emotional exhaustion was negative on employee engagement. Interestingly, in organizations with a strong ethical climate, emotionally intelligent employees did not display significantly higher engagement. However, emotionally exhausted employees appeared more engaged in such environments. These findings underscored the importance of re-evaluating the role of ethical climate and its influence on the work engagement of customer-contact employees with different emotional capacities.

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Journal Articles | 2025

Addressing gender disparities in creative sectors using incentive frameworks under copyright law

Sahana Simha, M P Ram Mohan

Female underrepresentation has been a persistent issue in the creative sector, where contributions by women are consistently under-recognised and neglected. The entertainment industry, in particular, has grappled with this issue, as is discernible from the systemic barriers that perpetuate gender disparities by limiting female professional participation and creative recognition. Copyright law plays a key role in this industry, as it provides a framework for protecting creative works, thereby influencing professional opportunities and recognition of creators. Given the lack of female representation in copyright-associated industries, this study explores the potential of modifying copyright law’s incentive framework to improve gender equality in creative sectors. The study reviews relevant data, and gender dimensions of the Patent (Amendment) Rules, 2019 to determine whether the insights from these can be applied to copyright law. The study explores methods to adapt copyright incentives to increase female participation and facilitate gender diversity across creative fields.

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Journal Articles | 2025

Caste inequality in occupational exposure to heat waves in India

Arpit Shah, Sneha Thapliyal, Anish Sugathan, Vimal Mishra, Deepak Malghan

India is a leading global hot spot for extreme heat waves induced by climate change. The social demography of India is centered on its caste hierarchy rooted in endogamous occupational groups. We investigate the association between caste and climate inequality by studying occupational exposure during the 2019 and 2022 heat waves. We combine high spatiotemporal resolution heat stress information from satellite imagery with a large nationally and regionally representative labor force survey with rich socioeconomic and demographic information (n > 100,000 individuals). The slope of the heat stress dose–workhours curve corresponding to the marginalized caste groups is between 25% and 150% steeper than that for dominant caste groups for UTCI (Universal Thermal Climate Index) thresholds between 26°C and 35°C. Our models control for other economic-demographic confounders, including age, gender, education, and economic status, besides political-geographic controls and fixed effects. Our robust evidence for the association between caste identity and exposure to heat stress shows why adaptation and mitigation plans in India must account for the hierarchical social order characterized by the “division of laborers” along caste lines rather than the mere division of labor. Methodologically, our analysis demonstrates the utility of pairing satellite imagery and detailed demographic data.

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Journal Articles | 2025

Dynamic robot routing and destination assignment policies for robotic sorting systems

Yuan Fang, René de Koster, Debjit Roy, Yugang Yu

Robotic sorting systems (RSSs) use mobile robots to sort items by destination. An RSS pairs high accuracy and flexible capacity sorting with the advantages of a flexible layout. This is why several express parcel and e-commerce retail companies, who face heavy demand fluctuations, have implemented these systems. To cope with fluctuating demand, temporal robot congestion, and high sorting speed requirements, workload balancing strategies such as dynamic robot routing and destination reassignment may be of benefit. We investigate the effect of a dynamic robot routing policy using a Markov decision process (MDP) model and dynamic destination assignment using a mixed integer programming (MIP) model. To obtain the MDP model parameters, we first model the system as a semiopen queuing network (SOQN) that accounts for robot movement dynamics and network congestion. Then, we construct the MIP model to find a destination reassignment scheme that minimizes the workload imbalance. With inputs from the SOQN and MIP models, the Markov decision process minimizes parcel waiting and postponement costs and helps to find a good heuristic robot routing policy to reduce congestion. We show that the heuristic dynamic routing policy is near optimal in small-scale systems and outperforms benchmark policies in large-scale realistic scenarios. Dynamic destination reassignment also has positive effects on the throughput capacity in highly loaded systems. Together, in our case company, they improve the throughput capacity by 35%. Simultaneously, the effect of dynamic routing exceeds that of dynamic destination reassignment, suggesting that managers should focus more on dynamic robot routing than dynamic destination reassignment to mitigate temporal congestion.

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