Multi-criteria decision making with fuzzy TOPSIS:a case study in Bangladesh for selection of facility location

Abstract. The choice of an ideal facility location becomes essential as businesses work to streamline their processes and increase efficiency. In this study, the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is applied to choose the best facility location for Rokomari.com, a well-known Bangladeshi online book seller. The goal is to compare Fuzzy TOPSIS’ effectiveness and efficiency to expert judgment when choosing a facility location. The research begins by examining the existing fulfillment center of Rokomari.com located in Motijheel, south Dhaka, and the company’s desire to establish a new branch in north Dhaka for faster service expansion. Eleven potential alternatives are evaluated using the Fuzzy TOPSIS method, which incorporates fuzzy set theory to represent criteria values and preferences as fuzzy numbers. This approach enables the consideration of uncertainty and vagueness in decision-making, offering a more comprehensive evaluation of the facility location alternatives. The study incorporates the expert opinion of four managerial experts from Rokomari.com in addition to the Fuzzy TOPSIS analysis. To gain a thorough understanding of the decision-making process, their observations and viewpoints are contrasted with the Fuzzy TOPSIS findings. The study aims to compare the analyses produced by Fuzzy TOPSIS and expert judgment in order to assess the efficacy and efficiency of each method for choosing a facility location. The results of this study offer insightful information about the use of Fuzzy TOPSIS in the context of choosing a facility location. Additionally, it adds to the body of knowledge by contrasting the results of Fuzzy TOPSIS with professional judgment, highlighting the advantages and drawbacks of each method. The outcomes can help decision-makers at Rokomari.com and other comparable organizations choose a facility location in a knowledgeable and efficient manner

Enhancing the cosmetics industry sustainability through a renewed sustainable supplier selection model

The cosmetics industry requires a long-term sustainable strategy to balance its continuously growing trend worldwide and its resources consumption. In this view, the suppliers' selection process is gaining more attention affecting products' overall sustainability. The objective of this contribution is hence to develop and validate the Cosmetics Sustainable Supplier Selection (C-SSS) model allowing the selection of sustainable suppliers for the cosmetic industry, evaluating them in an objective and balanced manner. The model was built relying on both scientific and grey literature, by incorporating the characteristics of existing SSS models usually used separately. The C-SSS enabled to integrate the EMM approach (to reduce the subjectivity), the ANP approach (to evaluate criteria interconnections), and the TOPSIS and ELECTRE models (to create a hybrid compensation model) to support managers in objectively selecting the most sustainable suppliers. The C-SSS model was applied and validated through an industrial use case in a cosmetics Italian company

ADDRESSING THE INHERENT LIMITATIONS OF TRADITIONAL MODELLING FRAMEWORK FOR SUSTAINABLE ENERGY DEVELOPMENT IN A DEVELOPING ECONOMY

This article addresses the literatures in respect of the inherent limitations of traditional modelling techniques forsustainable energy planning in a Developing Economy (DE). DE are undergoing socio-economic changes in theirenergy settings - socio-economic policies such liberalisation, financial sourcing and climate change implication ofenergy projects. This article describes a critical review of the inherent dynamics of Sustainable Energy Development(SED) and reveals the limitations of traditional planning tools such as optimisation, econometric and generalsimulation models. It argues that traditional approaches are inadequate for SED in the DE due to its inherentweakness in guiding future policy decisions. Optimisation based models may be suited for well-defined solutions,however, the macro-energy scene at a decision support level in most DE do not lend itself to simplified modellingtechnique that are rooted on past algorithms. Econometric models has seen applications across many economies,sadly, they fail to consider the technological nature of energy supply (production) and demand (consumption) in arapidly changing DE. Further, they fail to demonstrate the path taken and erroneously assumed conditions ofequilibrium for energy planning and policy formulation. This article bridge the gaps in literatures by showcasing theinherent weaknesses of traditional planning approaches and the urgent need to seek an alternative paradigm shift forsustainable energy planning and policy formulation in the DE.Keywords: Energy, Developing Economy, Frameworks, Optimization, Modelling

Integrated modelling for sustainability assessment and decision making of alternative fuel buses

In this paper, a hybrid life cycle sustainability assessment (LCSA) model integrating multi region input–output analysis with novel multi-criteria decision-making techniques is proposed to assess three different fuel alternatives: compressed natural gas (CNG), electric buses (EBs), and diesel buses (DBs). A global hybrid LCSA model first quantified the environmental, economic, and social impacts of alternative fuel buses. The results were investigated in terms of multiple combinations of manufacturing and end-of-life scenarios by encompassing impacts embedded in the global supply chains taking Qatar as a case applied to the proposed model. The Interval-Valued Neutrosophic Fuzzy (IVNF)-Analytic Hierarchy Process with the Combined Compromise Solution (CoCoSo) approach is used to rank the alternative fuel buses based on their corresponding sustainability performance. The proposed model will help in quantitatively capturing the macrolevel life cycle socioeconomic and environmental impacts along with optimally selecting alternatives to support sustainable urban transport policy towards a net-zero transportation system globally

Prioritizing Offshore Vendor Selection Criteria for the North American Geospatial Industry

The U.S. market for geospatial services totaled US $2.2 billion in 2010, representing 50% of the global market. Data-processing firms subcontract labor-intensive portions of data services to offshore providers in South and East Asia and Eastern Europe. In general, half of all offshore contracts fail within the first 5 years because one or more parties consider the relationship unsuccessful. Despite the high failure rates, no study has examined the offshore vendor selection process in the geospatial industry. The purpose of this study was to determine the list of key offshore vendor selection criteria and the efficacy of the analytic hierarchy process (AHP) for ranking the criteria that North American geospatial companies consider in the offshore vendor selection process. After the selection of the initial list of factors from the literature and their validation in a pilot study, a final survey instrument was developed and administered to 15 subject matter experts (SMEs) in North America. The SMEs expressed their preferences for one criterion over another by pairwise comparisons, which served as input to the AHP procedure. The results showed that the quality of deliverables was the top ranked (out of 26) factors, instead of the price, which ranked third. Similarly, SMEs considered social and environmental consciousness on the vendor side as irrelevant. More importantly, the findings indicated that the structured AHP process provides a useful and effective methodology whose application may considerably improve the quality of the overall vendor selection process. Last, improved and stabilized business relationships leading to predictable budgets might catalyze social change, supporting stable employment. Consumers could benefit from derivative improvements in product quality and pricing

Decision support models for supplier development: Systematic literature review and research agenda

The continuing trend towards sourcing components and semi-finished goods for less vertically integrated manufacturing systems globally leads to a dramatic increase in supply options for companies. To ensure that companies benefit from the potentials global sourcing offers, supplier-buyer relationships need to be managed efficiently. Due to the decreasing share of value-adding activities provided in-house, suppliers are more and more considered as an essential contributor to the buying company's competitive position. Consequently, to realize and sustain competitive advantages, companies try to establish institutionalized long-term relationships to their most important suppliers and to actively improve the productivity and performance of their supplier base. To support supplier development in practice, researchers have developed decision support models that provide assistance in selecting and implementing suitable supplier development activities. The aim of this paper is to provide a comprehensive and systematic overview of decision support models for supplier development and to develop a research agenda that helps to identify promising areas for future research in this area. First, typical applications for supplier development as well as potential development measures that can be adopted to improve the performance of suppliers are identified. Secondly, a systematic literature review with a focus on decision support models for supplier development is conducted. Based on the analysis of the literature, we define a research agenda that synthesizes key trends and promising research opportunities and thus highlight areas where more decision support models are needed to foster supplier development initiatives in practice

Reprint of "Decision support models for supplier development: Systematic literature review and research agenda"

The continuing trend towards sourcing components and semi-finished goods for less vertically integrated manufacturing systems globally leads to a dramatic increase in supply options for companies. To ensure that companies benefit from the potentials global sourcing offers, supplier-buyer relationships need to be managed efficiently. Due to the decreasing share of value-adding activities provided in-house, suppliers are more and more considered as an essential contributor to the buying company's competitive position. Consequently, to realize and sustain competitive advantages, companies try to establish institutionalized long-term relationships to their most important suppliers and to actively improve the productivity and performance of their supplier base. To support supplier development in practice, researchers have developed decision support models that provide assistance in selecting and implementing suitable supplier development activities. The aim of this paper is to provide a comprehensive and systematic overview of decision support models for supplier development and to develop a research agenda that helps to identify promising areas for future research in this area. First, typical applications for supplier development as well as potential development measures that can be adopted to improve the performance of suppliers are identified. Secondly, a systematic literature review with a focus on decision support models for supplier development is conducted. Based on the analysis of the literature, we define a research agenda that synthesizes key trends and promising research opportunities and thus highlight areas where more decision support models are needed to foster supplier development initiatives in practice

Integrative model for the selection of a new product launch strategy, based on ANP, TOPSIS and MCGP: a case study

New product launch strategy is a key competitive advantage for a new product development. A new product launch is a multiple criteria decision-making problem, which involves evaluating different criteria or attributes in a strategy selection process. The purpose of this paper is to develop a qualitative and quantitative approach for the selection of a new product launch strategy. The current study proposes an integrated approach, integrating analytic network process, the technique for order preference by similarity to an ideal solution and multi-choice goal programming, which can be used to determine the best launch strategy for marketing problems. The advantage of this integrated method is that it enables the consideration of both tangible (qualitative) and intangible (quantitative) criteria as well as both “more/higher is better” (e.g., benefit criteria) and “less/lower is better” (e.g., cost criteria) in the launch strategy of a new product selection problem. To show the practicality and usefulness of this method, an empirical example of a watch company is demonstrated. First published online: 03 Nov 201