Sanjib Biswas
57209413922
Publications - 5
Evaluation of Fim Performance under Merger and Acquisition Effect: An Integrated LOPCOW-PIV Approach
Publication Name: Decision Making Applications in Management and Engineering
Publication Date: 2025-01-01
Volume: 8
Issue: 1
Page Range: 588-614
Description:
Merger and Acquisition (MA) is one of the critical strategic decisions for the firms that impact the existence and growth of the organizations. The present paper undertakes the context of MA and aims to compare performance of some of the recent acquirers using fundamental financial ratios and market indicators. The study period spans over four consecutive financial years (FY 2019-20 to FY 2022-23). To carry out a comprehensive evaluation of firm performance, the current work uses a multi-criteria decision-making (MCDM) framework of LOPCOW (Logarithmic Percentage Change-driven Objective Weighting) and PIV (Proximity Index Value) methods. To aggregate the year wise rankings of the firms, Borda Count and Rank Index Method (RIM) is used. It is observed that ROE (C1), Net Profit Margin (C4) and EPS (C9) obtained the highest weights over the study period. On aggregate, we find that Infosys (A4), HUL (A3) and ITC (A1) show top performance while Vodafone (A11), PVR Inox (A9) and IDFC First Bank (A13) remain in the bottom bracket. The comparative analysis with other MCDM models reveals that the ranking results are consistent while the outcome of the sensitivity analysis reflects the stability. The present work provides a new perspective to the investors, policy makers and analysts.
Open Access: Yes
Technology adaptation in sugarcane supply chain based on a novel p, q Quasirung Orthopair Fuzzy decision making framework
Publication Name: Scientific Reports
Publication Date: 2024-12-01
Volume: 14
Issue: 1
Page Range: Unknown
Description:
The present paper contributes to the literature in two ways. First, it develops a novel p, q Quasirung Orthopair Fuzzy (p, q QOF) based group decision making framework to modify a recently developed multi-criteria decision making (MCDM) model such as Comparisons between Ranked Criteria (COBRAC). Second, the paper ruminates on the Strength-Weakness-Opportunity-Threat (SWOT) of the sugarcane supply chain (SSC) in India vis-à-vis adaptation of the advanced technologies featuring Industry 4.0. To set the sub-factors of various dimensions of SWOT, the theoretical ground of Technology-Organization-Environment (TOE) framework has been used. The sub-factors of SWOT have been derived through an informal in-depth discussion with the experts of the sugar industry. Then using a Likert five-point linguistic scale the experts rated the sub-factors based on their relative importance. To determine the weights the modified COBRAC method has been applied. In subsequent stages the reliability of the model has been tested and sensitivity analysis has been carried out to check the stability of the result. The analysis reveals that while experience, by-product utilization and high demand provides strength and create opportunities for SSC, the areas of concern are lack of variety, fragmented nature of supply chains, shortage of next-gen talent and inadequate infrastructure. However, there are enough promises for SSC. The paper shall provide impetus to strategic decision makers for the sugar industry and puts forth a new decision-making framework for the analysts.
Open Access: Yes
Preference using Root Value based on Aggregated Normalizations (PROVAN): A data-driven method for socio-economic and innovation assessment
Publication Name: Socio Economic Planning Sciences
Publication Date: 2026-02-01
Volume: 103
Issue: Unknown
Page Range: Unknown
Description:
Socio-economic development (SED) remains a critical priority for policymakers aiming to foster inclusive growth and drive national progress. This study presents a comprehensive multi-criteria assessment of regional SED across 16 Indian states, focusing on the influence of innovation (INV) performance and foreign direct investment (FDI) on achieving sustainable development goals (SDGs). A new multi-criteria decision-making (MCDM) method, called Preference using Root Value based on Aggregated Normalisations (PROVAN), is introduced in this paper to enhance decision accuracy by integrating five different normalization techniques. Criteria weights are determined using an extended version of Weights by ENvelope and SLOpe (WENSLO) method, which incorporates multiple normalization strategies to improve robustness. The evaluation considers nine SED and seven INV criteria derived from secondary data sources. The causal relationships are statistically analyzed using Somer's δ test, and the model's reliability is confirmed through comparative and sensitivity analyses. Results reveal that Maharashtra emerges as the top-performing state in both SED (1.5572) and INV (1.5473), followed by Tamil Nadu and Karnataka, indicating strong performance across socio-economic and innovation indicators. The findings highlight significant inter-state disparities and confirm that states with stronger innovation capabilities tend to achieve better socio-economic outcomes. FDI is shown to positively influence sustainable economic development, reinforcing the strategic importance of attracting capital to advance SDGs. The proposed PROVAN-WENSLO framework offers a robust and adaptable tool for regional development planning and policy formulation.
Open Access: Yes
A Multi-Criteria Decision Analysis Framework to Explore Determinants of Catastrophic Healthcare Expenses
Publication Name: Societies
Publication Date: 2025-12-01
Volume: 15
Issue: 12
Page Range: Unknown
Description:
Despite significant advances in the medical sciences, out-of-pocket (OOP) healthcare costs have remained a concern, especially for lower-middle-class and poor people. The current study aims to investigate the critical factors that notably contribute to catastrophic healthcare expenses (CHCEs). To this end, the ongoing research is conducted through two phases. The first phase aims to identify the key determinants of CHCEs through expert and household evaluations. A multi-criteria decision analysis (MCDA) framework using the FullEX method is developed to analyze expert and household opinions. In the second phase, the experts investigate the hierarchical relationships among key determinants. Interpretive structural modeling (ISM) and MICMAC analysis are carried out to examine the structural relationships among the determinants. The findings of the FullEX analysis reveal that experts and households are in consensus. It is found that low-income level, number of dependable members, frequent birth rate, high child mortality, and lack of job security and risk pooling mechanisms notably contribute to the higher CHCEs. The ISM analysis indicates the strong driving power of income, education, and job security, leading to disparities in rural economic conditions, reflecting the need for holistic development. The MICMAC analysis confirms the hierarchical relationships among the key determinants of CHCEs. The findings necessitate formulating an inclusive strategy to reduce financial distress and improve the healthcare outlook for rural households, leading to sustainable development.
Open Access: Yes
DOI: 10.3390/soc15120353
An interval-valued triangular fuzzy decision analytics model for analyzing surface water quality of urban lakes for sustainable management
Publication Name: Water Reuse
Publication Date: 2025-12-01
Volume: 15
Issue: 4
Page Range: 684-700
Description:
We present a comparative assessment of the surface water quality (SWQ) of two prominent lakes in Udaipur, India: Pichola Lake (PL) and Fateh Sagar Lake (FS), during two distinct seasons, pre-monsoon (PM) and post-monsoon (POM). We measure the physicochemical parameters for assessing the SWQs of PL and FS during the PM and POM seasons. The physicochemical parameters are evaluated (in accordance with the standard specifications) within specified intervals, categorized as excellent, allowable, and unsuitable. For a precise discrimination among the alternatives in a scalable modeling framework while offsetting the uncertainty (imposed due to sample collection and seasonality), the present work uses interval-valued TFNs (IVTFNs). We utilize a hybrid multi-criteria decision-making (MCDM) framework, incorporating the opinion weight criteria method (OWCM) and root assessment method (RAM), to rank the SWQs of the lakes. The OWCM method provides a reliable outcome under imprecision and limited data, while avoiding the oversimplification of diverse alternatives. RAM offers a realistic treatment of contributions by inferior criteria while rewarding superior performance. We observe that FS demonstrates an inseparable SWQ for both the PM and POM seasons. At the same time, PL reports a significant effect of seasonal changes, where PM performance is found to be better.
Open Access: Yes
DOI: 10.2166/wrd.2025.067
