Research & Articles

European Journal of Operational Research, Elsevier | Volume 298, Issue3, 1 May 2022, Pp. 967-978.

The value efficiency approach is one possible way of incorporating information preferences into performance analysis of Decision-Making Units (DMUs). In this paper, we propose a novel geometric interpretation of value efficiency while plugging it into radial and non-radial DEA (Data Envelopment Analysis) models under the assumption of variable returns to scale. In addition, this novel geometric interpretation of value efficiency is extended to Additive Slacks-Based Measure (ASBM) modeling. This is achieved by linearization of non-radial DEA models using multi-objective programming. Performance of such proposed approaches in terms of reliability and discriminatory power are compared through a case study involving Finish bank branches. Research implications are then derived and conclusions are drawn.

https://doi.org/10.1016/j.ejor.2021.07.036

International Journal of Management Science and Engineering Management, 2023. 18:1, pp. 51-64

This study examines critical success factors (CSFs) for supply chain resilience regarding the selection of transportation service providers. Due to extensive global sourcing, many companies are dependent on multiple suppliers and service providers. Using a Delphi approach, this article identifies the CSFs relevant to the resilience of transportation service providers in supply chains. A novel approach using Multiple Criteria Decision-Analysis (MCDA) is then developed to rank a group of CSFs. In particular, the Best-Worst Method (BWM) and Multi-attributive Border Approximation Area Comparison (MABAC) methods are used to rank resilience-related CSFs for transportation service providers in uncertain environments using Hesitant Fuzzy Sets (HFS). Based on our results, hybrid MCDA methods can be applied in order to develop an effective method for determining resilience-related CSFs when selecting transportation service providers in uncertain environments.

https://doi.org/10.1080/17509653.2022.2098543

Mathematics. 12(12) 1865, 2024

Utilizing Multi-Criteria Decision Analysis (MCDA) methods based on environmental, social, and governance (ESG) factors to rank countries according to these criteria aims to evaluate and prioritize countries based on their performance in environmental, social, and governance aspects. The contemporary world is influenced by a multitude of factors, which consequently impact our lives. Various models are devised to assess company performance, with the intention of enhancing quality of life. An exemplary case is the ESG framework, encompassing environmental, social, and governmental dimensions. Implementing this framework is intricate, and many nations are keen on understanding their global ranking and avenues for enhancement. Different statistical and mathematical methods have been employed to represent these rankings. This research endeavors to examine both types of methods to ascertain the one yielding the optimal outcome. The ESG model comprises eleven factors, each contributing to its efficacy. We employ the Performance Contribution Analysis (PCA), Clifford algebra method, and entropy weight technique to rank these factors, aiming to identify the most influential factor in countries’ ESG-based rankings. Based on prioritization results, political stability (PSAV) and the voice of accountability (VA) emerge as pivotal elements. In light of the ESG model and MCDA methods, the following countries exhibit significant societal impact: Sweden, Finland, New Zealand, Luxembourg, Switzerland, Denmark, India, Norway, Canada, Germany, Austria, and Australia. This research contributes in two distinct dimensions, considering the global context and MCDA methods employed. Undoubtedly, a research gap is identified, necessitating the development of a novel model for the comparative evaluation of countries in relation to prior studies.

https://doi.org/10.3390/math12121865