Comparison of decision-making approaches to prioritization of clean air action plans for sustainable development

Background: Clean air action plans have been prepared and are still being implemented in Turkey to control and prevent air pollution, and improve the air quality. The plans reveal a picture of the current situation and available inventory information. However, in order to implement the identified plans in real life, they need to be prioritized. This study aimed to identify and prioritize clean air action plans for Turkey using a framework of both fuzzy and crisp evaluations. Methods: In this study, priorities of the plans were identified and analyzed with a decision-making model. A three-step research methodology was provided. First, literature was reviewed regarding sustainable development and action plans. Second, in order to narrow and specify action plans, the nominal group technique (NGT) was implemented. Finally, fuzzy analytic hierarchy process (AHP) and best-worst method (BWM) surveys were applied to environmental engineers and experts working on sustainable development to prioritize the action plans. Results: It was revealed that heating dimension is considered as the most important criterion with the weight of 0.7469 in fuzzy AHP and 0.758 in BWM. AP1 with a weight of 0.3356 in fuzzy AHP and AP3 with a weight of 0.3289 in BWM were the most important sub-criteria, which are the plans for reducing coal use ranked at the forefront in reducing air pollution. Conclusion: According to the results, there is no significant difference in the priority ranking results. The results of fuzzy AHP and BWM are very similar. For example, traffic criterion has the best performance in both methods in the evaluation of decision makers. In addition, the main and sub-criteria with the lowest priority are the same in these two methods. Keywords: Air pollution, Cities, Decision making, Surveys and questionnaire

Implementing Bounded Linear Programming and Analytical Network Process Fuzzy Models to Motivate Employees: a Case Study

In this research, the factors affectinguniversity employees’ motivation and productivity are identified and classified in seven groups; the impact of each motivation factor on the productivity is presented by ANP fuzzy model.Eight universities in Iran were analyzed in this research work. The aim of this study is to explore the productivity of employees. This paper attempts to give new insights intodesigning the portfolio factors, motivating employees for productivity improvement by implementing BLP and ANP fuzzy models.The research results show that there is a positive and significant relationship among reward system, motivation factors, and human resources productivity. In addition, among the options of reward system, the factors of internal (inherent) reward, non-financial external reward, and financial external reward had the highestimpact on increasing motivation and productivity factors. At the next stage, a BLP model is designed according to the importance and impact of each reward system option on motivation and productivity factors and organization limitations, including budget, facilities, and conditions to design portfolio factors motivating employees with the aim of improving productivity. The research results show that actualizing performance evaluation, receiving the feedback from the results of doing tasks by different ways, providing an opportunity for all employees to progress, coordination between job specifications and employees’ abilities, and a manager competency are very critical for improving the organization productivity

Evaluation of Smart City Logistics Solutions

The negative effects of goods flows realisation are most visible in urban areas as the places of the greatest concentration of economic and social activities. The main goals of this article were to identify the applicable Industry 4.0 technologies for performing various city logistics (CL) operations, establish smart sustainable CL solutions (SSCL) and rank them in order to identify those which will serve as the base points for future plans and strategies for the development of smart cities. This kind of problem requires involvement of multiple stakeholders with their opposing goals and interests, and thus multiple criteria. For solving it, this article proposed a novel hybrid multi-criteria decision-making (MCDM) model, based on BWM (Best-Worst Method) and CODAS (COmbinative Distance-based ASsessment) methods in grey environment. The results of the model application imply that the potentially best SSCL solution is based on the combination of the concepts of micro-consolidation centres and autonomous vehicles with the support of artificial intelligence and Internet of Things technologies. The main contributions of the article are the definition of original SSCLs, the creation of a framework and definition of criteria for their evaluation and the development of a novel hybrid MCDM model

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

An application of fuzzy logic to assess service quality attributes in logistics industry

Differentiation, growing competitive advantage, and excellence has been proved to be the result of service quality. At the same time, measuring attributes of service quality and customer satisfaction is fuzzy and ambiguous, and methods available for their measurement are generally classical. This paper proposes a fuzzy method to identify the service quality attributes. This approach was developed using crisp assessment methods in a logistics company. Applying the proposed fuzzy approach, service quality attributes and indicators are identified and then organized into 8 categories, to see the uncertainty level of each. The proposed method was successfully conducted in a real logistics company. The results show the membership degree of each indicator, suggesting customer expectations regarding quality. Also, the membership degrees of the service quality attributes suggest the ability of each to describe service quality in logistics industry

A step-by-step guide to assist logistics managers in defining efficient re-shelving solutions for retail store deliveries

Purpose City logistics is a challenge in many cities. Literature works focus on the analysis of large or local-scale solutions to increase the efficiency of freight transport. However, store deliveries from the perspective of practitioners, particularly retail stores, are still an issue. In this context, the purpose of this paper is to propose a decision framework to assist logistics managers in defining efficient re-shelving solutions for store deliveries, according to the emplacement characteristics, city administration constraints and social issues. Design/methodology/approach An iterative step-by-step decision framework is developed, which allows taking decisions in a clear and structured way, including the preferences of key stakeholders. Moreover, a “what if” procedure is proposed, aiming to modify some initial conditions of the target store to achieve more efficient solutions. Findings The proposed decision framework is applicable in practice and helps users (mainly logistics managers) to identify solutions for efficient re-shelving in urban settings. Research limitations/implications The decision framework is applied by the logistics manager of two Spanish food retail stores, but it could be used in different logistics sectors and cities/regions, although adapting the decisions taken at each phase. Practical implications Logistics managers have a support tool when addressing re-shelving solutions for store deliveries. Social implications A balance can be found between company interests (minimise costs) and citizens quality of life (less contamination, noise, traffic, etc.). Originality/value This study simultaneously deals with large- and local-scale decisions faced by logistics managers in their day-to-day activity, considering details about the store location, its surroundings and the company it belongs.Peer ReviewedPostprint (author's final draft

Intermodal Terminal Handling Equipment Selection Using a Fuzzy Multi-criteria Decision-making Model

Intermodal transport enables energy, costs and time savings, improves the service quality and supports sustainable development. The basic element of the intermodal transport system is an intermodal terminal, whose efficiency largely depends on the subsystems’ technologies. Accordingly, the topic of this paper is the evaluation and the selection of the appropriate handling equipment within the intermodal terminal. As the decision-making on the handling equipment is influenced by different economic, technical, technological and other criteria, the appropriate multi-criteria decision-making (MCDM) methods have to be applied in order to solve the problem. In this paper, a novel hybrid model which combines the fuzzy step-wise weight assessment ratio analysis (FSWARA) and the fuzzy best-worst method (FBWM) is developed. The defined model is applied for solving the case study of selecting adequate handling equipment for the planned intermodal terminal in Belgrade. The reach stacker is selected as the most adequate handling equipment since it suits best the characteristics of the planned terminal in the given conditions and in relation to the defined criteria. Solving the case study demonstrated the justification for using the MCDM methods to solve these kinds of problems as well as the applicability of the proposed MCDM model

A novel technique for evaluating and selecting logistics service providers based on the logistics resource view

The increasing importance of logistics outsourcing and availability of logistics services providers (LSPs) highlights the significance and complexity of the LSP evaluation and selection process. Most existing LSP evaluation and selection studies use historical performance data and assume independence among decision criteria. This paper proposes an integrated logistics outsourcing approach to evaluate and select LSPs based on their logistics resources and capabilities. This novel approach combines a fuzzy decision making trial, valuation laboratory (FDEMATEL) and fuzzy techniques to order preferences by similarity to ideal solution (FTOPS IS) methods. The new multi-criteria decision making (MCDM) model addresses the impact relationships between decision criteria and ranks LSP alternatives against weighted resources and capabilities. The effectiveness of this approach is demonstrated through a real case study and a two-phase sensitivity analysis confirms its robustness