Analysis of Causal Relationships Effective Factors on the Green Supplier Selection in Health Centers Using the Intuitionistic Fuzzy Cognitive Map (IFCM) Method

Consider the deep-seated influence of organizational factors on individual safety behavior, by combining the theory of intuitionistic fuzzy sets (IFS) and fuzzy cognitive maps (FCM), this paper proposed a method for individual safety behavior analysis based on intuitionistic fuzzy cognitive maps (IFCM). Firstly, a framework of individual safety behavior analysis under organizational situation was built, and determined the interrelation between organizational factors and individual safety behavior. Secondly, an IFCM model based on intuitionistic fuzzy ordered weighted averaging operator (IFOWA) and FCM was established, and the reasoning steps of IFCM was also proposed. Finally, established the model for individual safety behavior analysis based on IFCM, and the mechanism of organizational factors affecting on individual cognitive behavior, decision-making behavior and execution behavior was analyzed.

Implementation of the Theoretical Concept of Green Procurement and Supplier Selection in Estonian Shipbuilding Industry

The aims of the current study are to determine the criteria to be considered in a green supplier selection (GSS) process, develop an integrated decision-making approach using structural equation modelling (SEM) and fuzzy additive ratio assessment (ARAS) techniques to rank suitable suppliers, and investigate the effectiveness of this approach in collective decision-making. The study’s ultimate objective is to propose a method created from the perspective of fuzzy logic in which criterion weights are determined using SEM to resolve decision-making challenges such as GSS, in which a compromise solution is desired. In the first stage of the study, relevant literature as examined in detail. Eight main criteria and 27 sub-criteria were detected, taking into account classical, green, and social supplier selection (SS) criteria. A questionnaire was administered to 254 participants who were actively involved in SS processes for their companies, and the data were analyzed using SEM. In the second phase, six suppliers were evaluated considering the criteria found to have a positive impact on GSS, and fuzzy ARAS was applied. The results showed that the factors affecting GSS are quality (0.291), social responsibility (0.222), service (0.21), cost (0.149) and green product (0.128). The study presents an effective, objective, and fast method that can be used in decision-making problems such as GSS, that prevents potential loss of information and lack of transparency through an integrated approach, and that can be tested with a generalizable framework. The proposed hybrid method is an efficient and practical approach that can be tested on many decision-making problems, such as SS.

Purpose: Service industry is a massive sector accounting for about two-thirds of GDP of developed economies and is the field of an intensive competition between service companies and their supply chains. As a result, service supply chain management has become a subject of growing interest to researchers and business analysts. Healthcare industry is among the largest service industries with the highest potential for improvement in sustainability performance. The purpose of this study was to identify the concepts influencing the sustainability of hospital supply chain and provide a causal model for sustainable supply chain of hospital service.Design/methodology/approach: In this study, concepts that influence the sustainability of a hospital service supply chain were identified by in-depth interviewing of 18 experts in hospitals of Kerman, Iran. Delphi method was used to reorganize the initial concepts into 15 concepts. Finally, the Intuitionistic Fuzzy Cognitive Map (IFCM) method was used to develop the causal model of sustainable supply chain management for hospital service.Findings: Delphi method was used to reorganize 68 initial concepts into 15 concepts Contains: demand management, resource and capacity management, customer relationship management, supplier relationship management, service management, information management, financial performance management, Attention to the environment, contamination, energy consumption, legal requirements, employees, community and stakeholders, social accountability and business ethics. The results indicate that service delivery management is highly central among other concepts.Originality/value: with focusing on concepts such as service management, and capacity and resources management, The sustainability of the hospital supply chain can be improved.

Brand is one of the most important parts of businesses and many elements are brought together to create a brand. In order for customers to prefer brands, businesses need to consider both customer general and specific expectations, focus on the right points and offer the most appropriate solution to customers because customers consider many factors when making their brand choices. The purpose of this study is to determine which areas the companies operating in the telecommunications sector should focus on according to customer expectations and criteria for brand preference by using the Fuzzy Cognitive Mapping (FCM) method. Customer expectations and criteria are obtained as a result of literature research. After the data are prepared, the most effective criteria are determined with the FCM method. In this study, it is determined that which areas the companies operating in the telecommunications sector should focus on according to customer expectations and criteria. FCM is very useful to decide in complex situations like this. The greatest limitation of this study is determining the customer criteria for brand preference. This study shows that FCM can be very useful to determine the most crucial customer expectations for telecommunications sector. In addition, FCM can be used in other sectors where customer expectations are very important and decisive, to prioritize customer brand preference criteria and to guide businesses.KeywordsBrandBrand preferenceFuzzy cognitive mappingFCMTelecommunication

PurposeThe purpose of this paper is to apply a fuzzy LinPreRa cognitive map to evaluate the interaction and importance of factors affecting the development of strategic alliance partnerships between the outlying island duty-free shops and existing collaboration firms in duty-free shops. Meanwhile, the key factors should be considered in establishing strategic alliance partnerships while analyzing and comparing the perspectives of owners for outlying island duty-free shop and partner vendors of collaborating firms along with differences of influencing key factors on partnership quality.Design/methodology/approachThis study incorporates a fuzzy linguistic preference relation analytical network process (fuzzy LinPreRa ANP) in the fuzzy cognitive map (FCM) method to formulate a fuzzy LinPreRa cognitive map to evaluate the interactions and importance of key factors and the conditions of interactive impacts during the establishment of strategic alliance partnerships. The authors use the outlying island duty-free shops in Taiwan as the empirical subject to illustrate how the fuzzy LinPreRa cognitive map is applied. In-depth, interviews and questionnaire surveys are conducted to collect and evaluate respondents concerning key factors affecting strategic alliance partnerships establishment.FindingsThe following three findings based on the results of empirical analysis: first, the administrative behavioral patterns of managers for strategic alliance partnerships encompass shared values and goal coherence, while the associative statements are located on the first layer of fuzzy LinPreRa cognitive map core associations, which illustrates that businesses attach great importance to conceptual ideas. Second, integrity and reputations of both parties are the governing mechanism of strategic alliance partnerships, influencing mutual reputation. Third, the relationship of strategic alliance partnerships refers to the profit opportunities of both parties and their ability to respond to the market, including future development, regional indicators, marketing capabilities, brand multiplicity and customer retention. However, it can be inferred that such associative factors are located in the outer layer or belong to noncore associations, which means that both parties’ abilities to respond to market reactions are weakened.Practical implicationsThis study provides valuable relationship managerial strategies to maintain long-term partnerships for outlying island duty-free shops and their alliance collaborating firms including strengthened relationships of both parties’ managers to achieve common values and consistent objectives; improved beneficial value of both parties in strategic alliance partnerships; continued close communications to enhance the quality of strategic alliance partnerships; and establishment of personnel training mechanisms and strict formulation of management rules for strategic alliance partnerships.Originality/valueThe main valuable contributions are included the fuzzy LinPreRa cognitive map by combining two different decision methods including FCM and fuzzy LinPreRa ANP is proposed to help decision makers to improve the evaluation quality and calculation efficiency for critical elements’ interaction and importance; the fuzzy LinPreRa cognitive map can clarify considering significant factors when maintaining strategic alliance partnerships and further provide valuable relationship managerial strategies to maintain long-term relationships for duty-free shop owners and their alliance collaborating firms.

Nowadays the Self-Organization (SO) system is becoming to be a hot topic. In this paper, the SO systems Characteristics are studied, and some problems are brought forward related with the SO system research. A Fuzzy Cognitive Map (FCM) method provides a powerful framework for its developing evaluating. In FCM, the concepts such as actions, events, and action motivators are represented as nodes connected in a causal web. The Self-Organization comes from the interactions between the concepts and is encoded in the overall architecture. The nodes are influenced between each other by their weight influence. In this paper, a new method is introduced using FCM to evaluate the SO system.

An intuitionistic fuzzy cognitive map (IFCM) is an extension of a fuzzy cognitive map (FCM) that forms a graph-oriented fuzzy map describing both causal relationships between pairs of concepts and the states of concepts via intuitionistic fuzzy sets (IFSs). In contrast with an FCM, an IFCM provides much more flexibility in system modeling. However, IFCMs may lead to confusing or unreasonable results in system modeling since they do not fully consider the negative influence from conventional operations on IFSs, the activation process of concepts, and the problem of aggregating knowledge with different importance levels. To solve the challenges of IFCMs, we propose a high-order IFCM based on evidential reasoning (ER) (IFCMR) theory in this study. First, we introduce an evidential intuitionistic fuzzy aggregation (EIFA) operator and a multiplication operation on IFSs using an ER theory. Second, we establish the theory of IFCMR based on the EIFA operator and the newly introduced multiplication operation on IFSs. Third, we propose a scheme of aggregating IFCMRs with different importance levels using the EIFA operator, which can also be utilized to aggregate conflict knowledge and to determine objective connections in terms of an evidential cognitive map (ECM). Finally, several numerical and practical examples are employed to test and verify the feasibility and validity of IFCMRs in comparison with both IFCMs and ECMs.

The green supply chain operations try to minimize environmental impact over the product's lifetime including product recycling or use, reduction of harmful substances, resource saving, green design, etc. Supplier selection is the vital issue in green purchasing. This paper aims to develop applicable and efficient methodology for green supplier selection. The proposed methodology includes the combination of Fuzzy Stepwise Weight Assessment Ratio Analysis (SWARA-F) and Fuzzy Measurement Alternatives and Ranking according to the COmpromise Solution (MARCOS-F) methods. Fuzzy extensions of these methods are preferred because of the complexity of the green supplier selection problem and inclusion of both quantitative and qualitative criteria. Also, these criteria may be uncertain and conflict with each other. It is the first time that SWARA-F is combined with MARCOS-F for the green supplier assessment and selection of the best one among them. The effectiveness of the proposed methodology is demonstrated by solving the real selection problem of a company from textile industry. In the problem both classic and green criteria including main and sub-criteria are considered. SWARA-F is used for weighting the evaluation criteria and the rank of each green supplier alternatives is obtained from incomplete information by assessment score calculated from MARCOS-F. The effectiveness of the combination of two methods is verified by sensitivity and comparative analyses. The proposed methodology provides acceptable and satisfactory results in determining the best green supplier namely improving the environmental and cost efficiency evaluation process.

A growing number of companies treat "sustainability" as an important objective in their strategy. Sustainable and green suppliers increase efficiency by reducing costs and waste in industries. Sustainable and green supplier selection is a critically important factor in moving forward along the path of sustainability. A fuzzy R-method is proposed in this paper based on ranking the fuzzy numbers of alternative suppliers and criteria. Triangular fuzzy membership function and different fuzzy scales are presented to demonstrate and validate the proposed method. Fuzzy composite scores are generated, and these scores are converted into crisp forms to evaluate the alternative suppliers. The novelty of the proposed method is that it is simple, can deal with qualitative and quantitative criteria of supplier selection, and requires less computational effort for evaluating and ranking the green and sustainable suppliers in fuzzy group decision-making situations. The weights of the criteria and alternative suppliers are generated using a simple equation and hence there is no need to apply different methods for weights generation and ranking. Furthermore, this method does not require normalization of the data. Two realistic group decision-making problems of green and sustainable supplier selection to test the method. Sensitivity analysis for the proposed method is also conducted to check the consistency of the proposed method to different weights of the criteria. The proposed method is effective, robust, and competitive to the existing multi-criteria decision making (MCDM) methods of sustainable supplier selection.

Proper supplier selection to meet production demand is a major aspect of all manufacturing and process industries. Green supplier selection has been one of the most critical factors for environmental protection on account of increasing consumption levels and for sustainable development as well. This paper aims at developing an applicable methodology for green supplier selection for the process industry. In this study, both economic and environmental criteria are considered and a comprehensive weighted grey incidence decision approach for green supplier evaluation and selection in a process industry is proposed. First, an overall green supplier selection index system for process industries is considered; then a weighted grey incidence decision‐making model with improved grey incidence coefficients and weighted degree of grey incidence is provided. Improved grey incidence coefficients are defined using transformation sequences of the initial data. To eliminate the ill effects from the use of equal weights, the maximum entropy method is used to determine the weights of the improved grey incidence coefficients. An application example is proposed with the data collected for the chemical processing industry, which provides acceptable results in determining the better supplier. In the end appendix, some theory regarding the weights for grey incidence coefficients is proposed. The empirical results indicate that the model is of great practical value for green supplier selection in the process industry.

An extended TODIM multi-criteria group decision making method for green supplier selection in interval type-2 fuzzy environment

Biomass is viewed as one of the critical renewable energies and it widely exists in nature. Developing bioenergy has been promoted as a viable mean of dealing with environment issues that are related to the utilization of fossil fuel. However, due to many obstacles, the biomass and bioenergy technology has not won widespread support in developing countries, like China, with vast land area, particularly in rural area. Furthermore, most existing researches just focused on the description of the influence factors, along with the solution to the technical problems, while many social factors are overlooked. In fact, the process of developing biomass is indeed complicated due to the need for consensus and active participation of the various stakeholders, such as the government, the industry, and the local residents. Therefore, while integrating the intuitionistic fuzzy logic and fuzzy cognitive map, this study constructs an intuitionistic fuzzy cognitive map (IFCM) that is in line with experts’ suggestions and the current literature to investigate how to promote the development of biomass through enhancing public acceptance. We conduct several simulations from the perspective of different stakeholders, according to the IFCM. The analysis results reveal the influence mechanism in the system and illustrate the effect of various factors that are stressed by every stakeholder. The research design also provides a reference for future studies.

Green supplier selection is a key phase in green supply chain management. Green supply chain management is defined as integrating environmental thoughts into supply-chain management, including product design, material sourcing and selection, manufacturing processes, delivery of the final product as well as end-of-life management of the product after its useful life. With worldwide growing awareness of environmental protection, green production is becoming an important issue for every manufacturing company and will determine the sustainability of a company in the long term. A performance evaluation system for green suppliers is felt indeed necessary to determine the suitability of suppliers to cooperate ‘greenly’ with the firm. In this paper, a methodology for the evaluation of suppliers’ environmental performances (green supplier selection) has been reported in order to evaluate and select the best candidate supplier. An interval-valued fuzzy set coupled with VIKOR method has been utilised. A case study h...

The incorporation of environmental criteria into the conventional supplier selection practices is essential for organizations seeking to promote green supply chain management. Challenges associated with green supplier selection have been broadly recognized by procurement and supplier management professionals. The development and implementation of practical decision making tools that seek to address these challenges are rapidly evolving. This article contributes to this knowledge area by comparing the application of intuitionistic multi-criteria supplier selection methods in a fuzzy environment. The intuitionistic fuzzy AHP and TOPSIS methods are thoroughly discussed. The methods are then utilized to complete a green supplier evaluation and selection study for an actual company from the paper mill. For this purpose, 3 alternative green suppliers have been identified. To evaluate the alternatives, 10 criteria in three dimensions including supplier performance, environmental protection and supplier risk have been selected. Since the Multi-Criteria Decision Making (MCDM) methods are often used in problem of supplier selection from past to present. The Intuitionistic Fuzzy Sets (IFS) are used to reflect approval, rejection, and hesitation of decision makers by dealing with real life uncertainty, imprecision, vagueness, and linguistic human decisions. The main purpose of this study is to define the weights of criteria with Intuitionistic Fuzzy AHP. After that, the Intuitionistic Fuzzy TOPSIS and AHP method were used to rank alternatives from best to worst. At the end of the study the results related with alternatives were compared and interpreted.