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This study develops a research model to explain the acceptance of social banking. In order to find the antecedents of social banking intention, a meta-combination has been used. The results of a systematic review of the last decade of social commerce acceptance studies and the use of fuzzy Delphi and fuzzy DEMATEL methods led to the development of the model. The obtained model was investigated by the partial least squares method in the statistical community of banking customers. Then, by analyzing intermediate variables, the final results were obtained. Based on the obtained model, three types of effects were investigated: direct effects with the presence of the mediating factor or factors, direct effects by removing the mediating factor or factors, and indirect effect by considering the mediating factor or factors. The results show that except for privacy considerations, other factors including trust, attitude, social support, social commerce constructs, word of mouth, social influence, customer social responsibility and perceived usefulness have a direct and indirect effect on social banking intention. The privacy consideration factor has only indirect effect on social banking intention through the full mediation of the trust factor. Except for the effect of factors on the intention of social banking, based on the model obtained from meta-combination, the effect of factors on each other was also investigated and some were confirmed. This research introduces a socio-technical innovation by combining the application of social banking with a social commerce platform and presents a comprehensive model of the willingness to accept this innovation. [ABSTRACT FROM AUTHOR]

Sustainable supply chain management (SSCM) is a tactical concern for managers seeking a longterm result. Different managers are attempting to apply SSCM in order to get a competitive advantage. One of the critical processes is the identification of strategy implementation hurdles, which has been a research focus. As a result, this paper identifies these obstacles and analyzes their interrelationships. A list of obstacles was initially established by a survey of the literature and expert judgment in the form of the fuzzy Delphi approach. Next, an investigation was designed to collect expert opinions on the interrelationships between these obstacles. The fuzzy DEMATEL (FDEMATEL) approach was employed for examining the causal linkages and interdependencies of these obstacles. Subsequently, the interpretative structural modeling (ISM) technique was utilized to create a classified structure and to identify the driving and dependent connections. A fuzzy MICMAC analysis was applied for categorizing the obstacles based on driving and dependent power. The results reveal that barriers, "cost of implementation sustainability (B1)", "lack of financial resources (B2)", "institutional complexity (B3)", "complexity in measuring and monitoring sustainability practices (B4)", "lack of effective regulations (B5)", "lack of a proper evaluation system for suppliers (B6)", "lack of sustainability knowledge (B7)", and "strategic and structural restraints (B8)", are the influence-forwarding obstacles. These obstacles influence "inadequate government support (B9)", "high investments for sustainability and less return-oninvestments (B10)", "old equipment and machinery (B11)", and "lack of management commitment (B12)", which are the greatest influences on SSCM practices. Identifying the important obstacles and their interdependences can help policymakers in the manufacturing sector minimize or overcome them, boosting the possibilities of effectively incorporating sustainable principles into these projects. [ABSTRACT FROM AUTHOR]

Sustainable humanitarian relief logistics (SHRL) is gaining attention due to increased disasters, unpredictable demand, large volumes, high delivery stakes, and limited resources, evaluated through adaptable performance drivers. This study presents a novel hybrid framework for SHRL, combining the Fuzzy Delphi Method (FDM) and Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL). Initially, FDM is utilized to reach a consensus among experts concerning key performance indicators (KPIs) for humanitarian logistics and supply chains. By incorporating the inherent uncertainty and vagueness in expert judgments, FDM refines the list of key performance indicators that reflect the real-life conditions and constraints in disaster operations. Finally, the fuzzy DEMATEL approach was used to analyze the interrelationships among factors, identifying cause-and-effect behavior and ranking them, forming a robust theoretical framework. Based on the acquired results, the KPIs attached to the Quality (P1) aspect of the proposed framework have gained significant importance and are the main cause in a cause-and-effect relationship which impacts and is helpful to improve the performance of humanitarian organizations in all phases of disaster management. The KPIs prompt delivery (D1), and delivery accuracy (D2) are more significant, while capacity building and training (D19) and delivery compliance (D15) are least significant in SHRL scenarios. This research is expected to support humanitarian organizations in enhancing their capabilities, thereby improving the effectiveness and efficiency of aid delivery in disaster-stricken areas. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to propose an approach for identifying and prioritizing ecosystem indicators for effective ecosystem management. Specifically, fuzzy Delphi and fuzzy DEMATEL approaches are used to define ecosystem management goals and indicators, rank the importance of quality attributes in ecosystem management, and rank the effectiveness of each indicator in each pillar of ecosystem management. The ultimate goal is to provide a tool to decision-makers that can help in allocating resources more effectively and efficiently toward achieving sustainability. Design/methodology/approach: The proposed approach involves a three-phase framework. Phase 1 involves identifying and determining the indicators affecting ecosystem management. This has been performed by studying theoretical articles, reviewing systematic literature, and searching previous studies to identify different indicators for each pillar of ecosystem management. A list of indicators and factors affecting each of the pillars of ecosystem management has been determined accordingly, and an initial categorization has been created using library studies. Phase 2 involves using a fuzzy Delphi method to rank the most important indicators in each pillar of ecosystem management. Experts have been asked to indicate their proposed indicators in a questionnaire based on fuzzy variables, and the degree of proportionality of the proposed factors. Phase 3 involves using a fuzzy DEMATEL approach to rank the effectiveness of each indicator in each pillar of ecosystem management. This approach handles imprecise or subjective data and can be replicated for different cities. Overall, this methodology aims to provide a comprehensive approach for identifying and prioritizing ecosystem indicators that can be used by decision-makers in environmental management and policy-making. Findings: Findings imply that the integrated approach of the Fuzzy Delphi Method and the Fuzzy DEMATEL can be used to identify and rank the importance of quality attributes in ecosystem management, and to rank the effectiveness of each indicator in each pillar of the ecosystem management. A total of 36 indicators were identified across four pillars of ecosystem management, i.e., economic, social, environmental and institutional. The results indicated that the most important indicators for each pillar were science and technology and innovation for the economic pillar; air quality, waste treatment and energy efficiency for the environmental pillar; poverty, health, and safety and security for the social pillar; and transparent sharing of information and political stability for institutional pillar. It was also found that there was a strong interrelationship between different pillars of ecosystem management. For example, the institutional pillar had serious effects on most of the other identified EM pillars. In addition, the economic pillar was the second most influential factor. Moreover, the institutional pillar profoundly influenced the environmental pillar. Finally, the economic pillar highly affected the environmental pillar, which doubled the complexity of ecosystem management. Research limitations/implications: Several limitations and implications have been addressed for future research. The number of participating experts was limited, which could affect the results and limit the possibility of their summarization. Expert bias may have influenced the results of the study. Such limitations imply that further research with a larger and more diverse group of experts is necessary to validate and expand upon such findings. This study was limited in scope to a particular ecosystem or region and the identified indicators as a result may not apply and be generalizable to other ecosystems or regions. Based on the cause-and-effect relationships between the studied elements, a hypothesis can be expanded and validated using a larger sample. Future studies could replicate this methodology in different contexts to test its applicability and effectiveness. Practical implications: Decision-makers in environmental management and policy-making can use the methodology presented in this study to identify and prioritize ecosystem indicators. By using an integration of the Fuzzy Delphi Method and the Fuzzy DEMATEL, decision-makers can identify the most important indicators for each pillar of ecosystem management and evaluate their effectiveness. This information can be used to allocate resources more effectively and efficiently toward achieving sustainability. Decision-makers could use this methodology to evaluate different ecosystem management practices and policies, and develop new policies or modify existing ones to better address the needs of different stakeholders. Overall, this study provides a useful tool for decision-makers in environmental management and policy-making by providing a comprehensive approach to identifying and prioritising ecosystem indicators. Social implications: This study highlights the importance of considering social factors in ecosystem management. The study identifies several social indicators, such as poverty and material deprivation, education level, public awareness and training, gender equality, and social participation. By prioritizing such indicators in ecosystem management, decision-makers can ensure that the needs and perspectives of different stakeholders are taken into account. This can help to promote social equity and cohesion, which are important for achieving sustainable development. Furthermore, by involving a wide range of stakeholders in the decision-making process, including local communities and marginalized groups, decision-makers can ensure that ecosystem management policies are more inclusive and responsive to the needs of all members of society. Overall, this study highlighted the importance of considering social factors in ecosystem management and provides a useful framework for identifying and prioritizing social indicators. Originality/value: The main contribution of this study is the application of the integrated approaches of the Fuzzy Delphi Method and the Fuzzy DEMATEL to identify and rank the importance of quality attributes in ecosystem management. This methodology is innovative because it allows decision-makers to handle imprecise or subjective data, which is often encountered in ecosystem management. The study provides a three-phase framework for identifying and prioritizing ecosystem indicators, which can be replicated for different cities. Findings indicated that science and technology, air quality, poverty, and transparent sharing of information were identified as the most important quality indicators in their respective pillars of ecosystem management alternatives. This implies that decision-makers and policymakers should consider allocating more resources toward improving such areas. Overall, this study provided a useful tool for decision-makers in environmental management and policy-making by providing a comprehensive approach to identifying and prioritizing ecosystem indicators. [ABSTRACT FROM AUTHOR]

In today's competitive world, Six Sigma can serve as a corporate strategy to improve quality and reduce costs. Six Sigma is a comprehensive and flexible system for achieving, maintaining and maximizing organizational success, through an improved performance of processes. However, this tool can only be successful in organizations which are already prepared for Six Sigma implementation. This study investigated the readiness of an Iranian company, Tabarestan Steel Co., in terms of Six Sigma projects. In doing so, the study proposed a model designed for assessing the readiness of Six Sigma in organizations. To this end, primarily Six Sigma readiness indicators were identified through Fuzzy Delphi, by recourse to the experts’ opinions. Next the interrelationships between the indicators were examined through the Fuzzy DEMATEL method. The internal links between the indicators were determined after the examination, and the degree of importance and the weights of the indicators were decided. Ultimately, three highly important dimensions were discovered that had a significant function in Six Sigma implementation (leadership and perspective, corporate strategy, and focus on the customer).

Today, due to the importance and expansion of the use of information technology, many organizations are witnessing problems and inconsistencies regarding the non-fulfillment of business needs due to the high volume of investment in information technology. One of the reasons for this discrepancy is the lack of alignment between the IT strategy and the business strategy, and therefore the lack of effective implementation of information technology governance. Therefore, the most important goal of this research is to provide a model for identifying and ranking the factors affecting IT governance. For this purpose, combined approach of fuzzy DEMATEL and fuzzy ANP has been used. In this study, the data of 20 experts in the field of information technology is collected through a questionnaire. Therefore, the research method is descriptive survey based on the nature and data collection and in terms of purpose, it is a practical development. In order to achieve the goals and answer the research questions, this research has been done in three main phases. In the first stage, by reviewing the literature and evaluating the results of studies, a context for the comprehensive identification and extraction of factors and sub-factors affecting IT governance and their classification is provided. Following, for the screening the identified variables, fuzzy Delphi technique has been used and with the opinion of experts, the classification of 21 key sub-factors among the 7 main factors have been confirmed. In the second step, internal relationships between the main factors are calculated using fuzzy DEMATEL method and the location of the network is plotted. Finally combined DEMATEL and fuzzy ANP and fuzzy ANP method has been used to weigh the factors and rank them. One of the most important results of the current research is to identify the causes and prioritize the effective factors in implementing information technology governance in organizations. These priorities indicate that, among other factors, the position of information technology in organizational structure in the weight of networks analysis has the first priority. Also, by DEMATEL method the IT strategy factor with the highest output vector has been identified as the most influential factor and the support and skills of senior IT managers with the highest total output and input vector have been identified as the most interactive factor. [ABSTRACT FROM AUTHOR]

Blockchain and Internet of Things (IoT) technologies have considerable potential to achieve sustainability in logistics and supply chain management. However, the integration of blockchain-IoT has not been explored extensively in past research. This research provides a complete analysis of the enablers for using blockchain-IoT to manage logistics and supply chains. It aims to explore and prioritise various enablers for its adoption. The Diffusion of Innovation and the Technology-Organisation-Environment theories are used in this research to examine blockchain-IoT adoption enablers. The enablers identification is confirmed using the Fuzzy-Delphi technique and then analysed using the fuzzy - Decision-Making Trial and Evaluation Laboratory tool to determine the strength of cause-effect hierarchical framework. The sensitivity analysis is also carried out to address the robustness of the results obtained. In order to measure the extent of a firm's readiness to adopt blockchain-IoT, a framework based on Graph Theory Matrix Method is proposed. It is illustrated with the help of a real life case. The results revealed that 'sustainability focus', 'emphasis on emerging technology by organisation', and 'technology maturity' are the top three enablers for blockchain-IoT adoption. Findings of study may motivate managers to include blockchain-IoT into their strategic planning processes based on their categorization of enablers into cause and effect categories. The research findings may also be used to the creation of efficient Blockchain-IoT deployment methods. • Nineteen enablers to Blockchain-IoT adoption in supply chains are identified. • Fuzzy-DEMATEL method is used to rank enabling factors of BIoT adoption. • A self-assessment framework to evaluate readiness for BIoT adoption is proposed. • Sustainability focus, emphasis on emerging technology and technology maturity are major enablers. [ABSTRACT FROM AUTHOR]

Nowadays, tourism industry is considered as the main part of the global economy. tourism industry is among the most important industries capable of stimulating economic growth. Understanding what drives satisfaction for a tourist is one of the most relevant areas of research for the tourism industry. Tourists’ satisfaction is a strong indicator of their intention to visit and recommend destinations to others. This is one of the cheapest and most effective forms of marketing and development. Yazd province is important in tourism. In this research, fuzzy DEMATEL is used to investigate and modeling the relationship among effective factors in Domestic tourists’ satisfaction in Yazd province. To achieve this purpose, factors were identified after a comprehensive review of literature and fuzzy Delphi. Then to explain and evaluate the relationship among the factors, the fuzzy DEMATEL approach was used. According to the results, factors affecting the satisfaction of Yazd domestic tourists are cost levels and their fairness; public transportation performance; provided services; quality of facilities and services; tour operators’ knowledge; cleanness of places; quality of attractions; parking services; urban architecture beauty and quality; cultural values; hospitality of host community; tourism advertisement at province level; quality of tourist guide books, brochures and maps; destination facilities and infrastructure; variety of customs, traditions and cultures; variety of accommodation and entertainment services; region’s health; uniqueness of attractions; variety of tour services, souvenirs, handicrafts, food and beverage; and secondary attractions. Finally, some recommendations were offered for enhancing tourists’ satisfaction based on findings.

A programmable logic controller (PLC) is a real-time system operated in severe conditions such as high/low temperatures or tough environments with excessive electrical noise. In particular, a PLC is designed to connect and control multiple mechatronic devices such as facility sensors and actuators and thus the issue of selecting/assessing PLC suppliers is critically important to achieve automatic process control and facility monitoring. In reality, various MCDM (multi-criteria decision making) composed of MADM (multi-attribute) and MODM (multi-objective) based schemes are frequently adopted to tackle the problem of supplier selection. Nevertheless, most of them have the following demerits: (1) the causal dependences between main criteria (or associate attributes) are rarely considered (2) a large number of pairwise comparisons are usually required to conduct the evaluation process. Consequently, a novel framework combining fuzzy DEMATEL, fuzzy AHP, with fuzzy Delphi is proposed to overcome the aforementioned shortcomings. Without requiring tedious pairwise comparisons, the importance weights of main criteria (associated attributes) and the performance scores of PLC vendors are systematically fused into the whole evaluation process. Furthermore, an industrial example is demonstrated to assist PLC practitioners in assessing the top three suppliers, such as SIEMENS (31 %), Allen-Bradley (22 %) and Mitsubishi (13 %). [ABSTRACT FROM AUTHOR]

This study contributes by developing a set of household waste separation (HWS) attributes to address waste mishandling and to enhance waste separation intentions in households. In Mongolia, a lack of waste separation at the household level needs to be addressed to improve municipal solid waste management systems. However, prior studies have not established attributes in a hierarchical structure, nor do they understand their cause-effect interrelationships. First, the fuzzy Delphi method (FDM) was used to screen out the unnecessary attributes in qualitative information. The fuzzy decision-making trial and evaluation laboratory (FDEMATEL) was then applied to understand the hierarchical structure of the attributes and their cause-effect interrelationships. The study identifies a valid set of attributes consisting of five aspects and 17 criteria under uncertainties. A hierarchical framework consisting of environmental attitudes, social norms, perceived behavioral control, perceived convenience, and persuasive communication is provided. The findings reveal that persuasive communication and environmental attitudes are causal group aspects. Furthermore, persuasive communication has a strong causal impact and higher importance in improving HWS intentions, and it leads to perceived convenience and behavioral control. For policymakers, credibility of information, knowledge and information, awareness of consequences, willingness to sort, and perceived policy effectiveness are the key causal criteria for enhancing HWS intentions. Theoretical and practical policy implications are discussed. [ABSTRACT FROM AUTHOR]