EVALUATION OF LOGISTIC FLOWS IN GREEN SUPPLY CHAINS BASED ON THE COMBINED DEMATEL-ANP METHOD

Supply chains and transport corridors have a significant impact on the socio-economic and environmental situation in the regions where the elements of the logistics infrastructure are located. The achievement of the goals of the concept of sustainable development in these regions is ensured, among other things, as a result of the formation of green supply chain management (GSCM), that is, as a result of changes in existing approaches to supply chain management. Analysis of the practice of supply chain management showed a wide variety of parameters and indicators of logistics flows used in decision-making at different stages of managing these flows. The authors propose a universal system of the logistic flows parameters and indicators for the GSCM, corresponding to the principles of the concept of sustainable development. A methodology for ranking indicators of logistics flows based on a combined DEMATEL-ANP method has been developed. The results of a case study on the evaluation of logistics flows for the GSCM are presented. The ranks of logistics flow indicators obtained in the study are proposed to be used in GSCM to adjust of the logistics flows actual parameters to achieve the goals of the concept of sustainable development.

MEASURING EFFICIENCY CHANGE IN TIME APPLYING MALMQUIST PRODUCTIVITY INDEX: A CASE OF DISTRIBUTION CENTRES IN SERBIA

In the last decade, more and more attention has been paid to the efficiency of logistics systems not only in the literature but also in practice. The reason is the huge savings that can be achieved. In a very dynamic market with environmental changes distribution centers have to realize their activities and processes in an efficient way. Distribution centers connect producers with other participants in the supply chain, including end-users. The main objective of this paper is to develop a DEA model for measuring distribution centers’ efficiency change in time. The paper investigates the impact of input and output variables selection on the resulting efficiency in the context of measuring the change in efficiency over time. The selection of variables on the one hand is a basic step in applying the DEA method. On the other hand, the number of basic and derived indicators that are monitored in real systems is increasing, while the percentage of those used in the decision-making process is decreasing (less than 20%). The developed model was tested on the example of a retail chain operating in Serbia. The main factors changing the efficiency have been identified, as well as the corresponding corrective actions. For measuring efficiency change in time Malmquist productivity index is used. The developed approach could help managers in the decision-making process and also represents a good basis for further research.

COMBINING THE SUITABILITY-FEASIBILITY-ACCEPTABILITY (SFA) STRATEGY WITH THE MCDM APPROACH

Suitability-Feasibility-Acceptability (SFA) is a fundamental tool for the development and selection of strategy. Any type of decision-making problem can be resolved by Multiple Criteria Decision Making (MCDM) methods. In this research, we explore the complexity of determining the proper goal market for the Chilean fish market. This study proposed a combined approach of SFA with MCDM methods in a real case study. The proposed structure helps to assign the best market for Chilean export fish to West Asia. Three countries (Saudi Arabia, the United Arab Emirates, and Oman) are selected as a target market in this region, and then related criteria are obtained from various sources. In order to develop a new market for the Chilean fishery industry, five major criteria, including the potential of a target market, region's economic attractiveness, consumption of the seafood, location, cost of transportation, and country risks, were selected based on the SFA framework. Calculating the criteria weights is performed by the Best-Worst (BWM) method, and ordering the alternatives is operated by Measurement Alternatives and Ranking according to compromise Solution (MARCOS) methods. The results showed that Oman is the best destination (importer) for the Chilean fish market (Salmon fish as the case).

D NUMBERS – FUCOM – FUZZY RAFSI MODEL FOR SELECTING THE GROUP OF CONSTRUCTION MACHINES FOR ENABLING MOBILITY

The paper presents a hybrid model for decision-making support based on D numbers, the FUCOM method and fuzzified RAFSI method, used for solving the selection of the group of construction machines for enabling mobility. By applying D numbers, the input parameters for the calculation of the weight coefficients of the criteria were provided. The calculation of the weight coefficients of the criteria was performed using the FUCOM method. The best alternative was selected using the fuzzified method, which was conditioned by the specificity of the issue so that in this case, the selection of the best alternative was made using the fuzzified RAFSI method.

AN INTEGRATED DECISION-MAKING MODEL FOR EFFICIENCY ANALYSIS OF THE FORKLIFTS IN WAREHOUSING SYSTEMS

In the logistics world, special attention should be given to warehousing systems, cost rationalization, and improvement of all the factors that affect efficiency and contribute to smooth functioning of logistics subsystems. In real time industrial practice, the issue of evaluating and selecting the most appropriate forklift involves a complex decision-making problem that should be formulated through an efficient analytical model. The forklifts efficiency plays a very important role in the company. The forklifts are being used on a daily basis and no logistical processes could be done without them. Therefore, it has been decided to determine their efficiency, which will contribute to the optimization of the process in this logistics subsystem. This study puts forward an integrated forklift selection model using Data Envelopment Analysis (DEA), Full Consistency Method (FUCOM) and Measurement Alternatives and Ranking According to the Compromise Solution (MARCOS) methods. Five input parameters (regular servicing costs, fuel costs, exceptional servicing costs, total number of all minor accidents and damage caused by forklifts) and one output parameter (number of operating hours) were first identified to assess efficiency of eight forklifts in a warehousing system of the Natron-Hayat company using the DEA model. This step allows sorting of efficient forklifts which are subsequently evaluated and ranked using FUCOM and MARCOS methods. A sensitivity analysis is also performed in order to check reliability and accuracy of the results. The findings of this research clearly show that the proposed decision-making model can significantly contribute to all spheres of business applications.

A NEW LOGARITHM METHODOLOGY OF ADDITIVE WEIGHTS (LMAW) FOR MULTI-CRITERIA DECISION-MAKING: APPLICATION IN LOGISTICS

Logistics management has been playing a significant role in ensuring competitive growth of industries and nations. This study proposes a new Multi-Criteria Decision-making (MCDM) framework for evaluating operational efficiency of logistics service provider (LSP). We present a case study of comparative analysis of six leading LSPs in India using our proposed framework. We consider three operational metrics such as annual overhead expense (OE), annual fuel consumption (FC) and cost of delay (CoD, two qualitative indicators such as innovativeness (IN) which basically indicates process innovation and average customer rating (CR)and one outcome variable such as turnover (TO) as the criteria for comparative analysis. The result shows that the final ranking is a combined effect of all criteria. However, it is evident that IN largely influences the ranking. We carry out a comparative analysis of the results obtained from our proposed method with that derived by using existing established frameworks. We find that our method provides consistent results; it is more stable and does not suffer from rank reversal problem.

GREEN SUPPLIER SELECTION BASED ON THE INFORMATION SYSTEM PERFORMANCE EVALUATION USING THE INTEGRATED BEST-WORST METHOD

Information Systems (IS) have become crucial for all the organizations to survive in contemporary technology-oriented environment. Consequently, the number of companies and organizations which have invested widely in their IS infrastructures to present better services and to produce higher value products is increasing. On the other hand, nowadays, because of the increase of governmental rules and serious requirements of more people in the case of environmental protection, it seems necessary for all the enterprises to follow these regulations if they want to survive in the global markets. However, what is at issue here is not just the companies’ agreement with the environmental laws; in addition, they should apply some strategies to decrease the negative environmental impacts of their products in some countries. Thus, the aforementioned arguments are the reasons for the compulsory use of the green supplier selection (GSS) in all firms. Considering the mentioned contents, the purpose of this study is representation of the relation between ISs and GSS as two vital components of firms in a novel way which has not been done before. Actually, it shows the ISs' performance or effectiveness to select the green suppliers taking into account the different levels of importance of GSS measures (including eight criteria and 31 sub-criteria), using a multi-criteria decision-making method called Best Worst Method (BWM) to identify the weights (importance) of GSS measures and compute the GSS performance of 10 ISs in a company using the data gathered in a survey from ISs' experts.

STUDY TOWARDS THE TIME-BASED MCDA RANKING ANALYSIS – A SUPPLIER SELECTION CASE STUDY

Decision-making processes increasingly use models based on various methods to ensure professional analysis and evaluation of the considered alternatives. However, the abundance of these methods makes it difficult to choose the proper method to solve a given problem. Also, it is worth noting whether different results can be obtained using different methods within a single decision problem. In this paper, we used three selected Multi-Criteria Decision Analysis (MCDA) methods called COMET, TOPSIS, and SPOTIS in order to examine how the obtained rankings vary. The selection of material suppliers was taken into consideration. The equal weights, entropy and standard deviation methods were used to determine the weights for criteria. Final preferences values were then compared with the WS similarity coefficient and weighted Spearman correlation coefficient to check the similarity of the received rankings. It was noticed that in the given problem, all of the methods provide highly correlated results, and the obtained positional rankings are not significantly different. However, practical conclusions indicate the need to look for improved solutions in the correct and accurate assessment of suppliers in a given period.

A NEW INTEGRATED GREY MCDM MODEL: CASE OF WAREHOUSE LOCATION SELECTION

Warehouses link suppliers and customers throughout the entire supply chain. The location of the warehouse has a significant impact on the logistics process. Even though all other warehouse activities are successful, if the product dispatched from the warehouse fails to meet the customer needs in time, the company may face with the risk of losing customers. This affects the performance of the whole supply chain therefore the choice of warehouse location is an important decision problem. This problem is a multi-criteria decision-making (MCDM) problem since it involves many criteria and alternatives in the selection process. This study proposes an integrated grey MCDM model including grey preference selection index (GPSI) and grey proximity indexed value (GPIV) to determine the most appropriate warehouse location for a supermarket. This study aims to make three contributions to the literature. PSI and PIV methods combined with grey theory will be introduced for the first time in the literature. In addition, GPSI and GPIV methods will be combined and used to select the best warehouse location. In this study, the performances of five warehouse location alternatives were assessed with twelve criteria. Location 4 is found as the best alternative in GPIV. The GPIV results were compared with other grey MCDM methods, and it was found that GPIV method is reliable. It has been determined from the sensitivity analysis that the change in criteria weights causes a change in the ranking of the locations therefore GPIV method was found to be sensitive to the change in criteria weights.

REGIONAL AIRCRAFT SELECTION WITH FUZZY PIPRECIA AND FUZZY MARCOS: A CASE STUDY OF THE TURKISH AIRLINE INDUSTRY

Aircraft selection is an important issue in achieving long-term goals in the airline industry. For this issue in which multiple conflicting criteria are involved, the extant literature points to the use of multi-criteria decision-making (MCDM) methods. In this respect, this study aims to propose a systematic and comprehensive framework with a focus on the regional aircraft selection perspective. To achieve this, an integrated fuzzy Pivot Pairwise Relative Criteria Importance Assessment (F-PIPRECIA) and fuzzy Measurement Alternatives and Ranking according to the Compromise Solution (F-MARCOS) approach was employed. In this study, in which six regional aircraft alternatives were evaluated according to 14 criteria, data were collected from five decision experts. As a result, it was found that the most pivotal criterion is C33 (Operational Cost), and the least important criterion is C12 (NOx). In addition, CRJ1000 was identified as the most promising regional aircraft alternative. The results of the application were further validated by applying a three-stage sensitivity analysis. The proposed structure is anticipated to assist airline managers in aircraft selection decisions under uncertainty by offering a robust and systematic tool.