Browsing by Author "Soni, Gunjan"

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Citation - WoS: 10
Citation - Scopus: 16
A hybrid Bayesian approach for assessment of industry 4.0 technologies towards achieving decarbonization in manufacturing industry
(Elsevier Ltd, 2024) Devesh Kumar; Gunjan Soni; Fauzia Jabeen; Neeraj Kumar Tiwari; Gorkem Sariyer; Bharti Ramtiyal; Ramtiyal, Bharti; Jabeen, Fauzia; Soni, Gunjan; Kumar Tiwari, Neeraj; Sariyer, Gorkem; Kumar, Devesh; Tiwari, Neeraj Kumar
Since the 1st Industrial Revolution the Earth's atmosphere has warmed due to human activities like deforestation burning fossil fuels for energy generation and livestock raising. Without preventative measures the Earth's atmosphere would warm by 2 °C before the next Industrial Revolution. Thus it has become crucial to move toward a low-carbon economy. Reaching carbon neutrality means cutting our carbon footprint to zero. Innovative research methods and technologies can play a significant role in supporting the economy in its carbon reduction efforts. Industry 4.0 (I4.0) technologies hold great potential for decarbonizing the economy. However there is a need to explore and utilize this potential effectively. This study aims to address this by developing a methodology that identifies relevant attributes and critical measures from existing literature mapping them with I4.0 technologies. Using a MCDM approach each measure is prioritized based on importance. To better understand the interrelationships between these attributes and I4.0 technologies the Bayesian Network (BN) method is employed. This approach enables the exploration of dependencies and influences among variables. By implementing this four-stage strategy economies can make informed decisions and prioritize actions contributing to carbon neutrality while leveraging the benefits of I4.0 technologies. This approach offers a comprehensive framework for guiding economies on their path towards carbon neutrality considering the potential of I4.0 technologies and the importance of various attributes identified through literature. © 2024 Elsevier B.V. All rights reserved.
Citation - WoS: 4
Citation - Scopus: 7
A machine learning-based hybrid approach for maximizing supply chain reliability in a pharmaceutical supply chain
(PERGAMON-ELSEVIER SCIENCE LTD, 2025) Devesh Kumar; Gunjan Soni; Sachin Kumar Mangla; Yigit Kazancoglu; A. P. S. Rathore; Rathore, A. P. S.; Kumar, Devesh; Soni, Gunjan; Mangla, Sachin Kumar; Kazancoglu, Yigit
In today's interconnected global economy supply chain (SC) reliability is crucial particularly in sectors like the pharmaceutical industry where disruptions can significantly impact public health. SCs have become important to industries due to a customer-driven shift aimed at improving SC reliability especially in terms of delivery performance. It is crucial to define and find the best strategy for reaching the organizational objectives in SC. While designing a SC supplier selection (SS) and order allocation are two decisions that have to be made separately. This study addresses the critical challenges of SS and order allocation within pharmaceutical SCs. It proposes a novel two-phased hybrid approach the first phase integrates machine learning(ML) and multicriteria decision-making(MCDM) method for robust SS. The second phase develops a mathematical model to optimize order allocation while considering SC reliability. This work employs support vector machine (SVM) as the particular ML method in which the training data are historical corporate data that dictate parameters weights. These weights are then used in the measurement of alternatives and ranking according to compromise solution (MARCOS) method to rank the suppliers. A multi- objective mixed integer programming (MOMIP) model is then formulated to identify the right order quantity from the identified suppliers of a pharmaceutical SC in order to minimize SC cost and maximize SC reliability. The results indicate that by optimizing SC reliability and costs orders are directed to high-priority suppliers. This study provides a comprehensive data-driven decision-making framework to assure SC's reliability and cost-efficiency. The implications of the findings are also profound and contribute valuable insights for industry practitioners to improve the performance of SC. To illustrate the proposed methodology an SC example of a pharmaceutical industry is analyzed using the LINGO solver.
Citation - WoS: 35
Citation - Scopus: 31
Assessing dairy supply chain vulnerability during the Covid-19 pandemic
(Taylor and Francis Ltd., 2024) Kritika Karwasra; Gunjan Soni; Sachin Kumar Kumar Mangla; Yigit Kazancoglu; Karwasra, Kritika; Soni, Gunjan; Mangla, Sachin Kumar; Kazancoglu, Yigit
Frequent occurrence of disruptions in the supply chain due to the Covid-19 pandemic has increased the supply chain vulnerability (SCU) which affects the performance and revenue generation of firms. If the commodity we are dealing with in a supply chain is of a perishable nature then the situation becomes more complicated as such products need restrictive storage and transportation facilities. The dairy supply chain is one such perishable product supply chain. This paper thus proposes a method to identify key drivers of SCU in a dairy SC followed by establishing a model using interpretive structural modeling (ISM) and a graph theory approach (GTA) to calculate the SCU Index. It is important to quantify the SCU for identifying major factors affecting it and then developing techniques to mitigate it. In order to quantify the SCU first the ISM model is used to identify the interrelation between drivers and then an adjacency matrix is formed by using the interdependence thereby adding inheritance of each driver. A variable permanent matrix is formed to calculate the SCU Index for the SC. This proposed approach will help managers in mitigating the adverse effects of COVID-19 on the dairy supply chain. © 2024 Elsevier B.V. All rights reserved.
Citation - WoS: 6
Citation - Scopus: 2
Correction to: Impact of agri‑fresh food supply chain quality practices on organizational sustainability (Operations Management Research (2021) 10.1007/s12063-021-00196-x)
(Springer, 2021) Man Mohan Siddh; Sameer Kumar; Gunjan Soni; Vipul Jain; Charu Chandra; Rakesh Kumar Jain; Milind Kumar Sharma; Yigit Kazancoglu; Chandra, Charu; Soni, Gunjan; Kazancoglu, Yigit; Siddh, Man Mohan; Jain, Vipul; Kumar, Sameer; Jain, Rakesh
In this article the author name Man Mohan Siddh was incorrectly written as Manmohan Siddh. In this article several affiliations were incorrect: the affiliation details for Man Mohan Siddh were incorrectly given as 'Jaupur' but should have been 'Jaipur', the affiliation for Milind Kumar Sharma should have been Department of Production & Industrial Engineering M.B.M. Engineering College Faculty of Engineering & Architecture Jai Narain Vyas University Jodhpur Rajasthan India. The original article has been corrected. © 2021 Elsevier B.V. All rights reserved.
Citation - WoS: 24
Citation - Scopus: 30
Impact of agri-fresh food supply chain quality practices on organizational sustainability
(Springer, 2022) Man Mohan Siddh; Sameer Kumar; Gunjan Soni; Vipul Jain; Charu Chandra; Rakesh Kumar Jain; Milind Kumar Sharma; Yigit Kazancoglu; Chandra, Charu; Soni, Gunjan; Kazancoglu, Yigit; Siddh, Man Mohan; Jain, Vipul; Kumar, Sameer; Jain, Rakesh
The aim of this paper is to present empirical evidence about the relationship between Agri-fresh Food Supply Chain Quality (AFSCQ) practices and Organizational Sustainability (OS) outcomes. Organizational Sustainability embraces economic environment and social sustainability. Based on literature review a set of AFSCQ practices has been identified to create a theoretical model and to setup their relationship to OS as Economic Sustainability (ECS) Social Sustainability (SOS) and Environmental Sustainability (ENS). The measurement scales of AFSCQ practices and measures of OS were established in four stages: initial instrument development, structured interviews and utilization of Q-sort method, wide-ranging data collection by survey questionnaire, and analysis to confirm reliability and validity. Finally Structural Equation Modeling (SEM) was utilized to validate the model with survey data collected from Indian agri-fresh food industry. The study developed relationships between AFSCQ and OS. Specifically Customer Focus (CF) and Supplier Management(SM) both have direct and indirect influence on OS while Top Management Leadership and Commitment to AFSCQ Internal Management(IM) and Supply Chain Integration Management using IT(SCIMIT) have indirect and direct influences on OS respectively. The results also show that AFSCQ practices should be executed as an integrated coordination instead of independent practices wherein they co-operate with each other and enrich OS. The empirical outcomes of this paper give evidence to count the AFSCQ as a reliable medium for OS. The AFSCQ practices are favorable to develop organizational sustainability and then improve economic social and environmental performance indirectly. The suggested model establishes the relationship between AFSCQ and OS. Additionally the model’s justification to utilize the Indian agri-fresh food industry gave significant insights both from theoretic and realistic perspectives. © 2024 Elsevier B.V. All rights reserved.
Citation - WoS: 19
Citation - Scopus: 18
Integrating resilience and reliability in semiconductor supply chains during disruptions
(ELSEVIER, 2024) Devesh Kumar; Gunjan Soni; Sachin Kumar Mangla; Jiajia Liao; A. P. S. Rathore; Yigit Kazancoglu; Rathore, A. P. S.; Soni, Gunjan; Kumar, Devesh; Liao, Jiajia; Kazancoglu, Yigit; Mangla, Sachin Kumar
The semiconductor industry a cornerstone of modern technology has been crucial in driving globalization and supporting various sectors from consumer electronics to automotive industries. However in recent years the industry has faced substantial challenges threatening its ability to meet the surging demand for semiconductor chips. Disruptions at any point in the supply chain from raw material sourcing to end-product delivery can substantially influence the semiconductor ecosystem. The intricate nature of such SCs makes them highly vulnerable to various disruptions emphasizing the critical need for building resilient and reliable supply chain strategies. This article presents comprehensive research aimed at addressing critical gaps in the understanding and management of resilience and reliability within the semiconductor supply chain (SSC). This study proposes a multi-objective mixed-integer non-linear programming (MO-MINLP) model to configure an SSC while considering reliability and resilience measures. It emphasizes and draws attention to the importance of resilience and reliability in managing SSC disruptions during a pandemic and potential future epidemic outbreak. Exploring the precise breakdown of batch transportation between two sites shows how disruption can affect product flow along the SC. The applicability of the proposed method is demonstrated through a numerical example of an SSC solved using the LINGO solver. Finally a sensitivity analysis is conducted on the model's parameters to assess the capability and effectiveness of the results from managerial viewpoints.
Citation - WoS: 107
Citation - Scopus: 113
Investigating barriers to circular supply chain in the textile industry from Stakeholders’ perspective
(Taylor and Francis Ltd., 2022) Ipek Kazançoǧlu; Yigit Kazancoglu; Aysun Kahraman; Emel Kursunluoglu Yarimoglu; Gunjan Soni; Yarimoglu, Emel; Soni, Gunjan; Kazancoglu, Ipek; Kazancoglu, Yigit; Kahraman, Aysun
The objectives of this study are to understand the circular supply chain barriers for textile companies to implement the circular economy. Main contributions of the study were to propose a specific framework that reveals circular supply chain barriers in transition to circular economy with holistic view by encompassing all stakeholders to reveal causal relationships among the circular supply chain barriers within textile industry. Causal relationships between the proposed circular supply chain barriers were identified by Fuzzy-Decision Making Trial and Evaluation Laboratory (DEMATEL) method. The barriers are classified under cause and effect groups and related implications are proposed. The findings of this study are lack of collecting sorting and recycling reluctance for acceptance of CE model and problems related to uniformity and standardisation are revealed as the most important barriers respectively. Moreover lack of technical knowledge is the most influencing factor whereas challenges in product design is the most influenced factor. © 2023 Elsevier B.V. All rights reserved.
Citation - WoS: 3
Citation - Scopus: 3
Modelling and analysis of resilience and reliability in pharmaceutical supply chains
(PERGAMON-ELSEVIER SCIENCE LTD, 2025) Devesh Kumar; Gunjan Soni; Ajay Pal Singh Rathore; Yigit Kazancoglu; Rathore, Ajay Pal Singh; Kumar, Devesh; Soni, Gunjan; Kazancoglu, Yigit
The pharmaceutical industry a massive global sector responsible for pharmaceutical production development and marketing has the problem of developing robust supply chains (SCs). These SCs are becoming more complicated while functioning in a global market making them more vulnerable to disruptions. To ensure that the healthcare system operates efficiently and meets the growing demand healthcare organisations must construct resilient and reliable SCs. In this study we develop a multi-objective optimisation model to address the pharmaceutical supply chain (PSC) problem while simultaneously minimising costs and increasing network reliability. We use three essential SC design indicators: node density node complexity and node criticality as well as a network reliability indicator to improve SC resilience and reliability. Our research findings indicate that in the pharmaceutical business improving SC reliability reducing SC costs and managing total SC orders holistically can effectively reduce the risk of SC interruptions.
Citation - WoS: 4
Citation - Scopus: 3
On the nature of supply chain reliability: models- solution approaches and agenda for future research
(EMERALD GROUP PUBLISHING LTD, 2024) Devesh Kumar; Gunjan Soni; Yigit Kazancoglu; Ajay Pal Singh Rathore; Rathore, Ajay Pal Singh; Kumar, Devesh; Soni, Gunjan; Kazancoglu, Yigit
Purpose - This research aims to update the literature about the importance of reliability in supply chain (SC) and to find out the SC determinants. Design/methodology/approach - This research surveys while contributing to the academic grasp of supply chain reliability (SCR) concepts. The study found 45 peer-reviewed publications using a structured survey technique with a four-step filtering process. The filtering process includes data reduction processes such as an evaluation of abstract and conclusion. The filtered study focuses on SCR and its determinants. Findings - One of the major findings is that most of the study has focused on mathematical and conceptual studies. Also this study provides the answer to a question like how can reliability be better accepted and evolved within the SC after finding the determinants of SCR. Originality/value - The observed methodological gap in understanding and development of SCR was identified and classified into three categories: mathematical conceptual and empirical studies (case studies and survey's mainly). This research will aid academics in developing and understanding the determinants of SCR.
Citation - Scopus: 1
Risk Reliability and Resilience in Operations Management
(Elsevier, 2025) Sachin Kumar Kumar Mangla; Yigit Kazancoglu; Gunjan Soni; Surya Prakash; Soni, Gunjan; Mangla, Sachin Kumar; Kazançoglu, Yigit; Prakash, Surya
Risk Reliability and Resilience in Operations Management examines measurement tools and techniques and their real-world application. The book provides a resource that is needed to help solve complex business operations and global supply chains and their important requirements for the accurate measurement of risk reliability and resilience to inform decisions and reduce risk. In addition the book discusses advancements in technology and data analytics with final sections covering the COVID-19 pandemic and how it has put greater emphasis on the importance of risk reliability and resilience in business operations. This book provides a timely overview of measurement techniques and their application in operations management offering insights into future directions in this field. © 2025 Elsevier B.V. All rights reserved.