Sensitivity of operational and environmental benchmarks of retail stores to decision-makers' preferences through Data Envelopment Analysis

Within the framework of multi-criteria decision analysis (MCDA), weighting methods are typically used to capture decision-makers' preferences. In this regard, the increasing use of the combined LCA (Life Cycle Assessment) + DEA (Data Envelopment Analysis) methodology as an MCDA tool requires an in-depth analysis of how the preferences of decision-makers could affect the outcomes of LCA + DEA studies. This work revisits a case study of 30 retail stores/supply chains located in Spain by applying alternative weighted DEA approaches to evaluate the influence of decision-makers' preferences (weights) on the final outcomes, with a focus on efficiency scores and operational and environmental benchmarks. The ultimate goal is to effectively capture the view of stakeholders when applying LCA + DEA for the sound, sustainability-oriented management of multiple similar entities. Different weight vectors are separately applied to three types of DEA elements: operational inputs, time terms, and divisions. Besides, preferences from three alternative standpoints are considered: company manager through direct rating, and environmental policy-maker and local community through AHP (analytic hierarchy process). A significant influence on efficiency scores and sustainability benchmarks was found when weighting decision-makers' preferences on operational inputs. Additionally, a moderate influence was observed when weighting divisions according to a policy-maker or local community perspective. Although the results are case-specific, they lead to the general recommendation to enrich LCA + DEA studies by following not only an equal-weight approach but also approaches that include the preferences of the stakeholders effectively involved in the study.publishe

TYPE-2 FUZZY TOPSIS MODEL FOR GREEN THIRD PARTY LOGISTICS PROVIDER PERFORMANCE EVALUATION

Green supplier selection, along with the environmental dimension in the supply chain, has attracted great interest both in the academic and institutional framework however, the supplier selection as well as the evaluation the performance of the current supplier affects the performance of the company and is important. In the real life, uncertainties in decision-making process are an integral part of this process. are things that exist in the nature of decision-making. Fuzzy set theory with the linguistic preferences was used to transform subjective decision-maker perceptions into a tangible net value. In this paper, it is proposed an interval type-2 fuzzy TOPSIS approach for green performance evaluation in GSCM. Then, It is applied in the performance evaluation of 3rd Party Logistics (3PL) providers to validate the presented model

EVALUATION OF IRANIAN SMALL AND MEDIUM-SIZED INDUSTRIES USING THE DEA BASED ON ADDITIVE RATIO MODEL – A REVIEW

Data Envelopment Analysis (DEA) is a prominent procedure in the decision-making process with a pivotal role in the sustainable development assay. Project identification is the first step of sustainability assessment in the Environmental Impact Assessment (EIA) program for the industrial projects prior to complete establishment. The present review research comprised 405 Iranian industries assessment regarding both input and output criteria via DEA integrated with the ratio model of Additive Ratio ASsessment (ARAS) and weighing systems of Kendall and Friedman's tests supported by SPSS software. The findings deployed a classification for Iranian industries pertaining to industries' nominal capacity in certain clusters. Also, the current review paved the pathway towards executing both energy and materials streams in industries

A novel hybrid fuzzy DEA-Fuzzy MADM method for airlines safety evaluation

Safety is a critical element in the air transport industry. Although fatal air accidents are rare compared to other transport industries, the rapid growth in air travel demands has resulted in a growing aviation risk exposure and new challenges in the aviation sector. Although the issue of airline safety is of serious public concern, notably few studies have investigated the safety efficiency of airlines. This paper aims to propose a novel hybrid method using fuzzy data envelopment analysis (DEA) and fuzzy multi-attribute decision making (F-MADM) for ranking the airlines’ safety. In this study, fuzzy DEA is utilized to calculate criteria weights, in contrast to the conventional approach of using DEA for measuring the efficiency of alternatives. A ranking of each airline (DMU) on the basis of obtained weights is then assessed using MADM methods. Six MADM methods including Fuzzy SAW, Fuzzy TOPSIS, Fuzzy VIKOR, ARAS-F, COPRAS-F and Fuzzy MULTIMOORA are implemented to rank the alternatives, and finally, the results are compounded with the utility interval technique. This new hybrid method can efficiently overcome the pitfalls of traditional hybrid DEA-MADM models. The method proposed in this study is used to evaluate the safety levels of seven Iranian airlines and to select the safest one. © 2018 Elsevier Lt

Equitable resource allocation to improve safety: An evaluation based on risk

Transportation safety continues to be a serious issue throughout the world. Proven safety measures have been developed to increase the safety on all roadways, but have not been universally and equitably implemented due to lack of resources, inefficiencies, and understanding. Additionally, the relative level of mobility safety remains higher in certain environments than others, creating an inequitable landscape. In this dissertation, the efficiency of using local and statement resources to improve safety is investigated while controlling for level of safety risk in vulnerable environments and locations using a comprehensive approach. Several methodologies and techniques are employed and developed to examine both systematic resource allocation and location-specific resource allocation methods from the perspective of equitably and efficiently using limited funds to increase safety. The approaches in this research include machine learning and regression methods, key informant interviews, employment of surveys, and the development of a geospatial tool. When combined and employed at the regional level, the methods presented in this dissertation can impact regional safety from a myriad of perspectives. The results and conclusions of this research informs transportation policymakers\u27, officials\u27, and researchers\u27 abilities to equitably increase road safety through informed state and regional systematic and site-specific resource allocation processes

A state-of-art survey on TQM applications using MCDM techniques

In today’s competitive economy, quality plays an essential role for the success business units and there are considerable efforts made to control and to improve quality characteristics in order to satisfy customers’ requirements. However, improving quality is normally involved with various criteria and we need to use Multi Criteria Decision Making (MCDM) to handle such cases. In this state-of the-art literature survey, 45 articles focused on solving quality problems by MCDM methods are investigated. These articles were published between 1994 and 2013.Seven areas were selected for categorization: (1) AHP, Fuzzy AHP, ANP and Fuzzy ANP, (2) DEMATEL and Fuzzy DEMATEL, (3) GRA, (4) Vikor and Fuzzy Vikor, (5) TOPSIS, Fuzzy TOPSIS and combination of TOPSIS and AHP, (6) Fuzzy and (7) Less frequent and hybrid procedures. According to our survey, Fuzzy based methods were the most popular technique with about 40% usage among procedures. Also AHP and ANP were almost 20% of functional methods. This survey ends with giving recommendation for future researches

A Comparison of Multi-Criteria Decision Analysis Methods for Sustainability Assessment of District Heating Systems

Funding Information: Funding: This research was funded by the European Regional Development Fund within the project No. 1.1.1.2/VIAA/4/20/604 “Decision Support Tool for Decarbonisation Assessment of District Heating Systems (START)”. The contribution of E. Dace and R. Soloha to this study was supported by the University of Latvia within the project “Climate Change and its Impacts on Sustainability of Natural Resources” (No. Y5-AZ20-ZF-N-270). Publisher Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland.The sustainability of energy systems is increasingly assessed for development of more resilient, greener district heating (DH) systems. That requires compiling technological, environmental, and economic indicators in a social, political, and institutional context. This work investigates DH system sustainability analysis by five frequently applied multi-criteria decision analysis (MCDA) methods—WSM, TOPSIS, PROMETHEE, ELECTRE and DEA. To compare the sustainability assessment results, a selection of 8 criteria describing 12 DH companies (DHC) was examined. Sensitivity analysis was performed to determine the most credible MCDA method. Criteria weights were changed: (1) individually for evaluation of the range of stability for alternatives (score of DHC performance); (2) individually by a fixed value to compare how each criterion weight change affected the average score of a result; and (3) to compare the AHP weighting method to an equal weight scenario. The results of sensitivity analysis along with literature investigation shows that all methods are suitable for sustainability analyses of DH systems while also having differences in the calculation process and in the interpretation of results. The generalized algorithm for sustainability analysis in the energy sector outlined in this study along with the documented features of the main MCDA methods can be used as a guide for future assessment of energy systems by researchers and industry professionals.publishersversionPeer reviewe