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Review Paper

Applications of Operations Research in Sustainable Supply Chain Optimisation

Operations research (OR) is extensively applied to model cost-emission-resilience compromises in sustainable supply chains, yet the previous literature reviews concentrate mainly on a particular methodological or problematic issue. This article provides a bibliometric analysis of 3,521 Scopus journal articles and reviews published between 2016 and 2027. Bibliometrix tools were used to explore the trends and patterns in the selected literature pieces. The number of papers increased significantly during the timeline, from 77 SCOPUS-indexed documents in 2016 to 803 documents in 2025. A few highly cited documents dominate the distribution, while no single group of authors is more productive than the others. Multi-objective and robust optimisation studies have the largest share of keywords, but the central themes are circular economy, artificial intelligence, and machine learning. According to the identified research frontiers, this article offers a research agenda that consists of six thematic areas and directions of OR applications.

Published by: Dr. Richa Kalpesh Saxena, Naavya Maheshwari, Myesha Shah, Nandan Ravikumar, Neil Jain, Ojas Khurana

Author: Dr. Richa Kalpesh Saxena

Paper ID: V12I5-1240

Paper Status: published

Published: October 26, 2026

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Review Paper

Application of Operations Research in Financial Risk Management

Financial risk management has moved from a specialist function to a core part of financial strategy, and operations research (OR) supplies much of its mathematical backbone through optimization, probability modelling, simulation and algorithmic decision support. Existing reviews, however, are organized around a single risk category or industry sector rather than around OR as a methodology, and most stop before the 2024–2026 surge in AI-integrated work. This paper reviews the literature linking OR and financial risk management and complements it with a bibliometric analysis of 260 Scopus documents (227 articles and 33 reviews) published between 2010 and 2026, retrieved with the search string “Risk Management AND Investments AND Analytics” and screened using the PRISMA framework. Performance analysis, keyword co-occurrence and a Callon centrality–density thematic map were produced using Biblioshiny, VOSviewer, Excel and Tableau. The results show a rapidly expanding field, with an annual growth rate of 24.66% and 65.8% of documents published in the last three years. Growth is led by technology rather than by finance-specific themes: machine learning and Industry 4.0 are the motor themes, technology vocabulary accounts for 59.2% of keyword occurrences on the map, and no finance-specific cluster occupies the motor quadrant. The scholarly landscape is also fragmented, with 190 of 218 sources publishing a single document and no author contributing more than three. The paper closes with a future research agenda that calls for structured comparisons of machine-learning models against Value-at-Risk and Conditional Value-at-Risk benchmarks, greater emphasis on explainable AI, sustained interdisciplinary research groups and renewed attention to the OR foundations of risk measurement.

Published by: Dr Richa Kalpesh Saxena, Soumya Pagarani, Srishti Jain, Shreyanshi Surana, Sohan Ahirrao

Author: Dr Richa Kalpesh Saxena

Paper ID: V12I5-1241

Paper Status: published

Published: October 26, 2026

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Research Paper

Application of Operations Research in Customer Satisfaction in E-Commerce

This study combines a systematic literature review with a bibliometric analysis to examine research on customer satisfaction and analytics from an Operations Research (OR) perspective in e-commerce. The authors aim to identify publication trends, dominant themes, and the extent to which analytics support OR-based decisions. Data were retrieved from Elsevier's Scopus database and screened using the PRISMA framework, giving a final dataset of 518 articles and 30 review papers. The findings show that the field has grown rapidly since 2018, with machine learning, big data, and sentiment analysis as its dominant themes, while core OR methods remain largely absent.

Published by: Dr. Richa Saxena, Muskaan Chhabria, Mishti Gopani, Mahika Chheda, Kuvira Kalani

Author: Dr. Richa Saxena

Paper ID: V12I5-1253

Paper Status: published

Published: October 26, 2026

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Research Paper

Supply Chain Management and Industry 4.0

Industry 4.0 has moved from a manufacturing slogan to a central concern of supply chain management (SCM). This review synthesises the literature on the two topics using 1,638 journal articles and reviews indexed in Scopus between 2017 and 2026, and it combines a reading of the most influential studies with the bibliometric evidence produced for this project (science mapping in Biblioshiny). Five conclusions emerge. First, research output has grown from 10 documents in 2017 to 301 in 2025, with a cumulative citation count of 88,572. Second, the field is organised around a motor theme of supply chains, decision-making, and artificial intelligence, surrounded by large clusters on sustainability and the circular economy and by smaller clusters on the Internet of Things (IoT), blockchain and resilience. Third, the most cited work is conceptual, review-based or survey-based, and few studies test technology effects with longitudinal or experimental designs. Fourth, scholarship from emerging economies, above all India and China, now dominates by volume, which has shaped the field's attention to adoption barriers and sustainability. Fifth, the field is moving from Industry 4.0 towards Industry 5.0, where resilience, sustainability and human-centricity are treated together. The paper closes with a future research agenda.

Published by: Dr. Richa Saxena, Jinay Karia, Kavya Gala, Kevin Shah, Krishna Mundra, Kritika Agarwal

Author: Dr. Richa Saxena

Paper ID: V12I5-1243

Paper Status: published

Published: October 26, 2026

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Research Paper

Inventory Management

This study examines the application of Operations Research (OR) techniques to inventory management through a bibliometric analysis of Scopus-indexed literature. The search strategy used the query “inventory management AND operations research” across article titles, abstracts and keywords, producing 1,681 records for the 2000–2026 analytical period. The supplied bibliometric export contains 1,678 article occurrences across 749 source entries, and the distinction between the screened records and exported occurrences is retained transparently. Annual publication output increased from 13 articles in 2000 to 191 in 2025; the 2026 count of 158 is treated as provisional. Source, thematic and conceptual analyses identify inventory control, supply chain management, operations research, optimization and decision-making as central themes. Sustainability is a distinct developed theme, while machine learning and artificial intelligence are increasingly connected with inventory decision support. The paper reviews classical inventory models, mathematical programming, allocation and network methods, supply-chain coordination, and emerging analytics. It concludes with a research agenda focused on integrating prediction and optimization, adaptive control under uncertainty, sustainability, resilient supply chains, real-time data, and empirical model validation.

Published by: Dr. Richa Kalpesh Saxena, Divye Dhamu, Divyam Oswal, Harshit Nathrani, Ishaan Khokhani, Jaideep Choudhary

Author: Dr. Richa Kalpesh Saxena

Paper ID: V12I5-1242

Paper Status: published

Published: October 26, 2026

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Review Paper

Optimisation and Policy in Waste Management

Waste management systems must decide where waste is collected, how it is transported, where it is treated and under which rules, and operations research supplies the quantitative tools for these decisions. This study maps the published research at the point where optimization and waste policy meet. A Scopus search for “waste management”, “optimization” and “policy”, screened in four PRISMA 2020 stages, produced a final sample of 967 journal articles and reviews published from 2016 onwards. The records were examined through performance analysis, title-based thematic counts, keyword co-occurrence mapping, a thematic map and a multiple correspondence analysis, together with a reading of the 167 review papers in the sample. Output grew at a compound annual rate of 25.5% between 2016 and 2025, and almost three in five records were published from 2024 onwards. The literature is dispersed across 425 journals and is highly collaborative. Circular economy, sustainability and artificial intelligence form the dominant motor theme, while optimization of solid waste systems and waste-to-energy form two further well-developed themes. Titles on artificial intelligence and machine learning rose from 1.6% to 15.2% of output between 2016–2019 and 2024–2027. Collection and routing, the classic operations research problem in waste management, appear in only 3.7% of titles, and household, residential, citizen or consumer terms in 1.4%. The paper closes with a six-part agenda for future research.

Published by: Dr. Richa Saxena, Subhaan Merchant, Tathya Patel, Sumeir Ahluwalia, Tisha Gherani

Author: Dr. Richa Saxena

Paper ID: V12I5-1232

Paper Status: published

Published: October 25, 2026

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