Multi-Criteria Decision-Making Methods Application in Supply Chain Management: A Systematic Literature Review

Over the last decade, a large number of research papers, certified courses, professional development programs and scientific conferences have addressed supply chain management (SCM), thereby attesting to its significance and importance. SCM is a multi-criteria decision-making (MCDM) problem because throughout its process, different criteria related to each supply chain (SC) activity and their associated sub-criteria must be considered. Often, these criteria are conflicting in nature. For their part, MCDM methods have also attracted significant attention among researchers and practitioners in the field of SCM. The aim of this chapter is to conduct a systematic literature review of published articles in the application of MCDM methods in SCM decisions at the strategic, tactical and operational levels. This chapter considers major SC activities such as supplier selection, manufacturing, warehousing and logistics. A total of 140 published articles (from 2005 to 2017) were studied and categorized, and gaps in the literature were identified. This chapter is useful for academic researchers, decision makers and experts to whom it will provide a better understanding of the application of MCDM methods in SCM, at various levels of the decision-making process, and establish guidelines for selecting an appropriate MCDM method for managing SC activities

Selecting Display Products for Furniture Stores Using Fuzzy Multi-criteria Decision Making Techniques

© 2018, Springer Nature Switzerland AG. Efficient marketing in which the right products are supplied to the right consumer plays a crucial role for a profitable business in the age of highly accessible and competitive global market. This fact enforces producers to clearly identify and analyze the needs of consumers and to display their products respecting locality based on customers’ needs. The position of the business is strengthened within the market and its competiveness increases by supplying and displaying the products suitable to regional consumers’ preferences. In this study, an integral fuzzy multi criteria decision making technique is proposed for an effective decision making process to select the most suitable display products to the consumers’ needs and preferences. The approach has been applied to identify the most suitable set of modular furniture products to be displayed at a local store that locates in Bursa city of Turkey. The approach uses Fuzzy DEMATEL method to work out the interrelations of chosen criteria, which are weighted with Fuzzy ANP and finally suggest a rank-based list of products with Fuzzy PROMETHEE. The results are verified with the expert view and found very useful

Logistics service providers (LSPs) evaluation and selection: Literature review and framework development

Purpose – The purpose of this paper is to provide an insight to the outsourcing decision-making through investigating if the old evaluation/selection criteria and methods still fit with current business priorities or not and, therefore, to identify the appropriate criteria and methods to develop a new selection framework. Since the economic recession of 2008, logistics outsourcing decisions have become more prominent to avoid high fixed costs and heavy investment requirements and to achieve competitive advantages. Design/methodology/approach – This is a focused literature review prepared after analyzing 56 articles related to the logistics service provider (LSP) evaluation and selection methods and criteria during 2008-2013. The academic articles are analyzed based on research focus/area, evaluation and selection methodology/methods and evaluation and selection criteria. Then reviewed result is compared with previous literature studies for the periods (1991-2008) to identify any possible shifts. Findings – The review reveals that: several problems in current LSPs literature have been identified; the reviewed papers can be categorized into seven groups, the usage and importance of evaluation and selection criteria fluctuate during different periods; 12 crucial criteria have been identified, increasing the importance of specific selection methods and the integrated models and fuzzy logic in logistics literature. Then, a comprehensive LSPs’ evaluation and selection framework has been developed. Originality/value – To the best of our knowledge, this is the first focused logistics outsourcing study that reviews the 2008-2013 period in detail, comparing results with previous literature studies, identifies current LSPs literature problems/gaps, new trends and shifts in the way that LSPs are evaluated and selected, identifies crucial selection criteria and proposes a new holistic LSPs evaluation and selection framework. In addition, it identifies important issues for future research. Keywords Supplier or partner selection, Evaluation and selection methods and criteria, Logistics outsourcing, Logistics service provider, LSP framewor

Intelligent Multi-Attribute Decision Making Applications: Decision Support Systems for Performance Measurement, Evaluation and Benchmarking

Efficiency has been and continues to be an important attribute of competitive business environments where limited resources exist. Owing to growing complexity of organizations and more broadly, to global economic growth, efficiency considerations are expected to remain a top priority for organizations. Continuous performance evaluations play a significant role in sustaining efficient and effective business processes. Consequently, the literature offers a wide range of performance evaluation methodologies to assess the operational efficiency of various industries. Majority of these models focus solely on quantitative criteria omitting qualitative data. However, a thorough performance measurement and benchmarking require consideration of all available information since accurately describing and defining complex systems require utilization of both data types. Most evaluation models also function under the unrealistic assumption of evaluation criteria being dependent on one another. Furthermore, majority of these methodologies tend to utilize discrete and contemporary information eliminating historical performance data from the model environment. These shortcomings hinder the reliability of evaluation outcomes leading to inadequate performance evaluations for many businesses. This problem gains more significance for business where performance evaluations are tied in to important decisions relating to business expansion, investment, promotion and compensation. The primary purpose of this research is to present a thorough, equitable and accurate evaluation framework for operations management while filling the existing gaps in the literature. Service industry offers a more suitable platform for this study since the industry tend to accommodate both qualitative and quantitative performance evaluation factors relatively with more ease compared to manufacturing due to the intensity of customer (consumer) interaction. Accordingly, a U.S. based food franchise company is utilized for data acquisition and as a case study to demonstrate the applications of the proposed models. Compatible with their multiple criteria nature, performance measurement, evaluation and benchmarking systems require heavy utilization of Multi-Attribute Decision Making (MADM) approaches which constitute the core of this research. In order to be able to accommodate the vagueness in decision making, fuzzy values are also utilized in all proposed models. In the first phase of the study, the main and sub-criteria in the evaluation are considered independently in a hierarchical order and contemporary data is utilized in a holistic approach combining three different multi-criteria decision making methods. The cross-efficiency approach is also introduced in this phase. Building on this approach, the second phase considered the influence of the main and sub-criteria over one another. That is, in the proposed models, the main and sub-criteria form a network with dependencies rather than having a hierarchical relationship. The decision making model is built to extract the influential weights for the evaluation criteria. Furthermore, Group Decision Making (GDM) is introduced to integrate different perspectives and preferences of multiple decision makers who are responsible for different functions in the organization with varying levels of impact on decisions. Finally, an artificial intelligence method is applied to utilize the historical data and to obtain the final performance ranking. Owing to large volumes of data emanating from digital sources, current literature offers a variety of artificial intelligence and machine learning methods for big data analytics applications. Comparing the results generated by the ANNs, three additional well-established methods, viz., Adaptive Neuro Fuzzy Inference System (ANFIS), Least Squares Support Vector Machine (LSSVM) and Extreme Learning Machine (ELM), are also employed for the same problem. In order to test the prediction capability of these methods, the most influencing criteria are obtained from the data set via Pearson Correlation Analysis and grey relational analysis. Subsequently, the corresponding parameters in each method are optimized via Particle Swarm Optimization to improve the prediction accuracy. The accuracy of artificial intelligence and machine learning methods are heavily reliant on large volumes of data. Despite the fact that several businesses, especially business that utilize social media data or on-line real-time operational data, there are organizations which lack adequate amount of data required for their performance evaluations simply due to the nature of their business. Grey Modeling (GM) technique addresses this issue and provides higher forecasting accuracy in presence of uncertain and limited data. With this motivation, a traditional multi-variate grey model is applied to predict the performance scores. Improved grey models are also applied to compare the results. Finally, the integration of the fractional order accumulation along with the background value coefficient optimization are proposed to improve accuracy

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

Odabir konkurentskih strategija u europskom bankarskom sektoru primjenom pristupa hibridnog odlučivanja

Strategic planning is an eJective tool for long-term planning and utilized by organizations and industries to achieve competitive advantage. Addressing difculties that the European banking sector struggled during and after the global financial crisis (GFC), the purpose of this paper is to raise important questions about the sustainability of the sector and oJers competitive strategy formulations for European policy makers. Empirical findings are accomplished by applying a three phase analysis of SWOT, an integrated model of DEMATEL-ANP (DANP), and fuzzy TOPSIS. Empirical findings from the SWOT analysis suggest a total of twelve factors, which are then incorporated to formulate four strategies. The DANP results illustrate that opportunities dimension has the highest impact and strengths has the lowest among others. The fuzzy TOPSIS results demonstrate that “the European Banking Union (EBU) is expected to remove divergence in the Euro area banking sector” is the most important strategy, whilst “the non-risk based leverage ratio (LR) requirement by Basel III” has the weakest importance among the strategy preferences.Strateško planiranje je učinkovit alat za dugoročno planiranje koje primjenjuju organizacije i industrije za postizanje konkurentske prednosti. S obzirom na poteškoće s kojima se europski bankarski sektor suočava za vrijeme i nakon globalne financijske krize (GFC), svrha ovog rada je podići važna pitanja o održivosti sektora i ponuditi formulacije konkurentnih strategija za europske kreatore politike. Empirijski rezultati postižu se primjenom SWOT analize u tri faze, integriranog modela DEMATEL-ANP (DANP) i ‘fuzzy’ (neizrazitog) TOPSIS-a. Empirijski rezultati SWOT analize ukazuju na ukupno dvanaest čimbenika, koji su potom uključeni u formuliranje četiri strategije. DANP rezultati potvrđuju da faktor prilika ima najveći utjecaj, a snage imaju najniži utjecaj u odnosu na ostala tri faktora. Neizraziti rezultati TOPSIS-a pokazuju da najvažnija strategija jest da “Europska bankovna unija (EBU) ukloni odstupanja u bankarskom sektoru u eurozoni”, dok “zahtjev Basel-a III o nerizičnom omjeru financijske poluge (LR)” ima najmanju važnost medu strategijskim prioritetima

Sustainable Industrial Engineering along Product-Service Life Cycle/Supply Chain

Sustainable industrial engineering addresses the sustainability issue from economic, environmental, and social points of view. Its application fields are the whole value chain and lifecycle of products/services, from the development to the end-of-life stages. This book aims to address many of the challenges faced by industrial organizations and supply chains to become more sustainable through reinventing their processes and practices, by continuously incorporating sustainability guidelines and practices in their decisions, such as circular economy, collaboration with suppliers and customers, using information technologies and systems, tracking their products’ life-cycle, using optimization methods to reduce resource use, and to apply new management paradigms to help mitigate many of the wastes that exist across organizations and supply chains. This book will be of interest to the fast-growing body of academics studying and researching sustainability, as well as to industry managers involved in sustainability management

Modeling and analysing the barriers to the acceptance of energy-efficient appliances using an ISM-DEMATEL approach

Electricity savings from energy-efficient appliances (EEAs) may have a significant impact on reducing global warming. There are several barriers confronted by EEAs, which have lowered their acceptance rate. The current study identifies and highlights key barriers to strengthening domestic sector adoption of EEAs in developing countries. In the current study, thirteen barriers were discovered by an indepth literature review and the judgement of experts as well. Further, integrated “Interpretive Structural Modeling” (ISM) and “Decision Making Trial and Evaluation Laboratory” (DEMATEL) approaches are utilized to evaluate barriers. The ISM technique is implemented to categorize barriers into distinct hierarchy levels, and “Cross-Impact Matrix Multiplication Applied to Classification” (MICMAC) analysis to divide barriers among four clusters “independent, linkage, dependent, and autonomous”. Moreover, the DEMATEL methodology is applied to classify the barriers among cause and effect clusters. The integrated ISM and DEMATEL approach suggests that the topmost influencing barriers to the acceptance of EEAs are the lack of Government policies and initiatives, lack of attractive loan financing, and subsidized energy prices. This study would help researchers, regulators, producers, policymakers, and consumers to comprehend the need for additional developments and understand that the adoption of EEAs is a current need. Overall, the results of this study expedite stakeholders with the key barriers that may assist to enhance the acceptance of EEAs within the domestic sector. An extensive literature survey showed a dearth of studies for the identification, modeling, and analysis of barriers collectively. Therefore, the current work utilized the ISM and DEMATEL approaches to fill the gap and to provide more comprehensive knowledge on barriers related to the acceptance of EEA

An overview of fuzzy techniques in supply chain management: bibliometrics, methodologies, applications and future directions

Every practice in supply chain management (SCM) requires decision making. However, due to the complexity of evaluated objects and the cognitive limitations of individuals, the decision information given by experts is often fuzzy, which may make it difficult to make decisions. In this regard, many scholars applied fuzzy techniques to solve decision making problems in SCM. Although there were review papers about either fuzzy methods or SCM, most of them did not use bibliometrics methods or did not consider fuzzy sets theory-based techniques comprehensively in SCM. In this paper, for the purpose of analyzing the advances of fuzzy techniques in SCM, we review 301 relevant papers from 1998 to 2020. By the analyses in terms of bibliometrics, methodologies and applications, publication trends, popular methods such as fuzzy MCDM methods, and hot applications such as supplier selection, are found. Finally, we propose future directions regarding fuzzy techniques in SCM. It is hoped that this paper would be helpful for scholars and practitioners in the field of fuzzy decision making and SCM