Narrow Results

The location of the spaceport is a significant factor in increasing the success of operations and reducing costs. To choose a suitable site, critical features need to be defined and evaluated. In this context, critical criteria have been collected and prioritized to determine the location of Türkiye’s spaceport. As space technologies are a new subject in Türkiye, expert evaluations include some uncertainty. To overcome this problem, a hybrid methodology based on hesitant fuzzy set theory has been developed by integrating two fuzzy multicriteria decision-making methods. By using hesitant fuzzy Z-DEMATEL, the relationships between the criteria were revealed, and the weights of the criteria were calculated by hesitant fuzzy Z-cognitive mapping method. According to the results, the most important main criteria are technical requirements, infrastructure, and cost and economy, while the most important sub-criteria are technical factors, flight safety/cruise route, and main/supporting infrastructure. To show the validity of the proposed methodology, the spherical fuzzy AHP method was employed for the same case. The comparative analysis has determined the same criteria as significant with the proposed methodology. The research would help policymakers and businesses better understand the critical criteria to spaceport site selection to catch the space race worldwide.

This study investigates the critical success factors (CSFs) of marketing automation (MA) for business-to-business (B2B) IT companies. The research employs a distinctive approach combining qualitative and quantitative methods to study the cause–effect phenomena and ascertain the rank of the CSFs to address the lack of comprehensive research in the existing literature. Utilizing the technology acceptance model (TAM) and DeLone & McLean’s information system success model (D&M ISSM) as a theoretical framework, the study underscores the underexplored domain of MA in the B2B IT sector. Expert interviews and the decision-making trial and evaluation laboratory method (DEMATEL) are employed to understand and rank CSFs comprehensively. Methodological triangulation is applied to the findings of expert interviews and DEMATEL analysis to confirm the CSFs of MA. The study finds that “system integration,” “flexibility and adaptation,” “personalized information,” and “general satisfaction” are the highest-ranked CSFs for adopting MA among B2B IT firms. This study provides valuable insights for managers in B2B IT companies on the CSFs driving MA adoption and effectiveness, enabling them to make informed decisions and optimize their MA strategies.

Causal analysis greatly affects the efficiency of decision-making. Scholars usually adopt structural equation modeling (SEM) to establish a causal model recently. However, statistical data allow researchers to modify the model frequently to arrive at good model fitness, and SEM is often misapplied when the data are merely fitted to an SEM and the theory is then extended from the analytical result based on presumed hypotheses. This paper proposed SEM modified by DEMATEL technique, taking causal model of Web-advertising effects for example. Having revealed that the new model is the one that conforms to actual data and is better than initial model, the results confirm that the DEMATEL technique can be an efficient, complementary, and confident approach for reprioritization of the amended modes in a SEM model. In addition, the most important factor affecting the Web-advertising effects may be found via the modified model, which benefits the manager for making strategic marketing plans.

Real estate brokerage services have developed from individual stores into a chain-store system, and the location of those stores plays a key role in their operation. The purpose of this study is to define and quantify the factors that affect the selection of a site for real estate brokerage services. Mutual relationships between the factors and sub-factors for site selection and their relative weights are also discussed to provide a complete set of decision evaluation models, then how to reduce the gaps to achieve the aspiration level. This research uses a new hybrid Multiple Criteria Decision Making (MCDM) model, combining the Decision Making Trial and Evaluation Laboratory (DEMATEL), DEMATEL-based Analytic Network Process (DANP), and VIšekriterijumsko KOmpromisno Rangiranje (VIKOR) methods to solve these problems. The DEMATEL technique is used to build an influential network relations map, and DANP is expected to obtain the influential weights using the basic concept of Analytic Network Process (ANP), to solve the dependence and feedback problems in the real world. Then, the VIKOR method is used to integrate the performance gaps from criteria to dimensions and overall. As the result shows, there is an interactive and auto-feedback relationship among the four dimensions. Among the 11 evaluation criteria, the income and consumption level is the most important consideration for selection of the site. The number and density of population ranks second in this regard. This study uses VIKOR method for selection of the best site, among three potential sites. Site A is closest to the aspiration level. Site A is better in this regard than the other two sites. The study develops and provides a decision-making system for the site selection in the real estate brokerage services.

Failure mode and effect analysis (FMEA) is one of the risk analysis techniques recommended by international quality certification systems, such as ISO 9000, ISO/TS 16949, CE, and QS9000. Most current FMEA methods use the risk priority number (RPN) value to evaluate the risk of failure. The RPN value is the mathematical product of the three parameters of a failure mode that is rated between 1 and 10 in terms of its severity (S), occurrence (O), and detection (D), respectively. However, the RPN method has been found with three main drawbacks: (1) high duplicate RPN values, (2) failure to consider the ordered weights of S, O, and D, and (3) failure to consider the direct and indirect relationships between the failure modes and causes of failure. Therefore, this paper integrates the technique for order preference by similarity to ideal solution (TOPSIS) and the decision-making trial and evaluation laboratory (DEMATEL) approach to rank the risk of failure. A case of an inlet plate ring that has been drawn from a professional mechanical factory is presented to further illustrate the proposed approach. After comparing the result that was obtained from the proposed method with the conventional RPN and DEMATEL methods, it was found that the proposed method can resolve the abovementioned RPN ranking issues and give a more appropriate risk assessment than other listed approaches to provide valuable information for the decision makers.

Corporations would utilize advanced information technologies for generating corporate social responsibility (CSR) reports and communicating with their stakeholders. However, corporations often could not determine whether their CSR websites are capable of effective communication with the stakeholders. The purpose of this study would be to analyze websites of benchmark companies for establishing an evaluation model to be a reference for CSR website design. Information from expert interviews carried out in this study underwent DEMATEL method for analyzing the mutual relationships between the quality criteria and dimensions of CSR websites. DANP was then used to calculate the weight of each criterion. Finally, we would make use VIKOR method to prioritize the performance CSR website satisfaction. The following provides the recommended improvement priorities according to results of the expert interviews: service quality (C) followed by information quality (B) followed by technical quality (A).

Performance evaluation is one of the most important problems for retail chains and may have effect on tactical and strategic decisions. This paper proposes a grey-based multi-criteria performance evaluation model for retail sector. This model integrates Decision-Making Trial and Evaluation Laboratory (DEMATEL) and modified Grey Relational Analysis (GRA) methods. First, the grey-based DEMATEL method is used for determining the importance of performance indicators to be used in GRA based on the experts’ assessments. Then, the proposed modified GRA method is used for the performance evaluation and ranking of retail stores with respect to the predetermined performance indicators. Finally, the effectiveness and the applicability of the developed approach are illustrated with a case study with the actual data taken from a retail chain in Turkey.

There are several factors that need to be considered in fleet management when it is necessary to resolve disturbances which necessitate aircraft re-assignment due to flight cancellations, making this a multiple-criteria decision-making problem. A change in the type of aircraft assigned can lead to additional alterations as well as directly affecting connecting flights and interconnected schedules serving specific flight segments. Decision-making is crucial and involves the consideration of complex cost effects, with possible disruptive actions evaluated according to the priorities of airline management and the available resources. Airline managers require a practical and flexible tool to help them make appropriate decisions in a rapidly changing and highly competitive environment. Differing from prior studies using mathematical programming, we propose a hybrid model based on the decision-making trial and evaluation laboratory method and the concepts of analytic network process (DANP) to aid in the decision-making process. We also recommend using the VIKOR method to select the most appropriate alternatives, with the corresponding weights obtained using the DANP method. The efficiency and effectiveness of the proposed method is demonstrated by testing it on a real-world flight cancellation case and in consultation with experts. The results show that this hybrid model is an effective resource that airline managers can use to address and resolve aircraft re-assignment irregularities.

ERP system is a software package that integrates and manages all the facets of the business and deeply influences the success of a business endeavor. The increasing competition in the market, rapidly changing demands, and increasing intricacy of business procedures induce enterprises to adopt ERP solutions. Adopting an ERP solution increases synchronization between business activities and reinforces managerial decision-making. However, it also involves a large investment, a significant amount of human resources and time, and risk of failure. Therefore, the selection of an ERP solution is a crucial decision for enterprises. To address this decision-making problem, we propose a four-stage multi-criteria decision-making approach in this paper. Three prevalent MCDM techniques, DEMATEL, IF-ANP, and IF-AHP, are used in different stages of the methodology to achieve better outcomes. The methodology incorporates the intuitionistic fuzzy sets to capture uncertainty and hesitancy involved in decision makers’ judgments. In addition, we develop a novel priority method to derive weights from the intuitionistic fuzzy preference relations. To validate the feasibility of the proposed approach, a case study is carried out on the selection of cloud-based ERP system for SMEs in the Chhattisgarh state of India, which indicates that the proposed four-stage approach effectively handles the ERP selection problem.

Scientific explorations and research in the Antarctic region have specific issues which need to be handled with special measures. Clothing of the scientists is one of the main problems. The clothes are expected to be enduring against compelling conditions and they must have certain features to ensure the safety and comfort of the scientists. Polar clothing is a field that is yet to be studied with different engineering approaches. To generate a better understanding, the polar clothing can be approached as a multiple criteria decision-making problem because many criteria such as layer number, material type, and waterproofness should be considered while evaluating the various alternatives. In this evaluation, expert judgments are used because no strict objective rules determine the conditions of the polar clothing. Also, possible influences among these criteria should be revealed and considered while reaching a decision. In order to deal with the uncertainty and vagueness of the expert judgments, this study proposes a Pythagorean fuzzy version of DEMATEL which is one of the well-known multiple criteria decision-making tools with the aim of evaluating the related selection attributes affecting the decision and searching for the potential influences among them. Since Pythagorean fuzzy sets provide a wider preference domain to the experts, this version was developed as a contribution to the literature. Also, the decision process is kept Pythagorean fuzzy until a conclusion is reached so that there is no early defuzzification problem. The method’s application on overcoat selection for the Antarctic region reveals the relations among attributes, such as “Water Vapor Permeability”, “All-Weather Protection” and “Performing Best in Dry/Wet State”. A sensitivity analysis is conducted to find the changes in influences.

Vietnam, a country in Southeast Asia, is anticipated to experience an increase in energy consumption due to the growth of its manufacturing and industrial sectors, which aims to establish Vietnam as the world’s new production hub. Fossil fuels, which are ecologically unfriendly and quickly running out, are now Vietnam’s primary energy source. Due to the detrimental effects of fossil fuels on the environment, we can apply strategic decision-making in the industrial sector to choose the best alternative for a renewable energy resource (RER). RERs such as solar energy, wind energy, solid waste energy, biomass energy, geothermal energy, biofuel energy, and hydropower energy are important for generating energy and will be crucial for the survival of humanity, the planet, and other living things in the future. The actions of RER-based industrial development must be encouraged since they will make a significant contribution to overcome environmental impact limitations. The 2-tuple linguistic $q$-rung orthopair fuzzy set (2TL$q$-ROFS) is a novel development in fuzzy set theory that presents a decision-making method for selecting the most appropriate alternative. In this paper, we develop a family of the 2TL$q$-ROF Maclaurin symmetric mean aggregation operators such as the 2TL$q$-ROF Maclaurin symmetric mean (2TL$q$-ROFMSM) operator, the 2TL$q$-ROF dual Maclaurin symmetric mean (2TL$q$-ROFDMSM) operator and its weighted forms. We also look into a few of the proposed operators’ properties and special cases. Then based on 2TL$q$-ROFS, a new Decision Making Trial and Evaluation Laboratory (DEMATEL) model is constructed, which can use the decision makers’ preferences to get the optimum objective weights for attributes. Next, we extend the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to 2TL$q$-ROF version which not only covers the uncertainty of human cognition but also gives decision makers a larger space to represent their decisions. Utilizing this model the best RER for Vietnam is selected. The outcomes of the hybrid 2TL$q$-ROF-DEMATEL-TOPSIS method reveal that among the energy resources, hydropower energy ranked highest, followed by biofuel energy.

In globalisation of business, Knowledge Management (KM) plays an important role in Supply Chain (SC) to create, build and maintain competitive advantage through utilisation of knowledge and through collaborative practices. Literature review have suggested the performance of KM adoption in SC may be affected by various influencing factors but it is always difficult for the practitioners to improve all aspects at the same time. The aim of this study is to identify Critical Success Factors (CSFs) of KM adoption in SC. This study presents a favourable method combining fuzzy set theory and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to segment the critical factors for successful KM adoption in SC. The empirical case study analysis of an Indian hydraulic valve manufacturing organisation is conducted to illustrate the use of the proposed framework for identifying the CSFs of KM adoption in SC. According to the results of the empirical study, six CSFs of KM adoption in SC are identified out of 25 influencing factors, these are top management support, communication and collaboration techniques, employee involvement, employee training and education, communication among the SC members and trustworthy teamwork to exchange knowledge within SC which will help to improve effectiveness and efficiency of KM adoption in SC. The decision makers can apply a phased implementation of these CSFs to ensure the effective KM adoption in SC under the constraints of available resources. This proposed method provides a more accurate, effective and systematic decision support tool for identifying CSFs of KM adoption in SC.

Low-carbon supply chain management (LCSCM) strategies are required in the Indian manufacturing industries due to rapidly growing energy usage for financial and environmental reasons. LCSCM technologies face several challenges that limit their adoption. Eleven hurdles were selected from the literature and the recommendations of one business expert and one academic expert. These barriers are defined by several factors, including a lack of information, financial worries, environmental concerns, and governmental limits, among others. In addition, efforts are being made to quantify the most optimal relevant barriers using multi-criteria decision-making (MCDM) techniques such as interpretive structural modeling (ISM) and the decision-making trial and evaluation laboratory (DEMATEL). The MICMAC analysis estimates the sensitivity and priority of barriers based on dependency and driving power. One of these barriers is a needed factor; three are driving elements; four barriers are linked factors; and three are self-sufficient factors. The findings of this study can help academic specialists, industry representatives, and practitioners in their ongoing attempts to adopt “LCSCM techniques” in Indian manufacturing industries. The model is appropriately explained and applies the link between the barriers. The objective of this paper is to evaluate and select the most influential barriers to adopting LCSCM in the Indian manufacturing sector that are interrelated.

Total Quality Management (TQM) implementation in an organization is a complex process that involves certain principles focusing on the constructs crucial to the business of an organization. Some of these principles are found to have a direct relationship with human behavior and thus can be said to be crucial for quality culture in an organization. This study recognizes 12 TQM principles from the literature review and expert consultation that are critical to TQM and a structural model of TQM is built with the help of Interpretive Structural Modeling (ISM). Further, the relative influential strength of the identified TQM principles along with their categorization in cause and effect is carried out using the Decision-Making Trial And Evaluation Laboratory Technique (DEMATEL) approach. In the ISM-DEMATEL-based hybrid approach, Policy Management (PM), Daily Work Management (DWM), Cross-Functional Management (CFM), and Human Resource Management (HRM) have emerged as the “Cause”. Among these, PM tops the rank in relative influential strength with a value of 5.362, followed by DWM, CFM, and HRM with values of 5.173, 5.122, and 4.551. The other TQM principles like Quality Management (QM), Cost Management (CM), Delivery Management (DM), New Product Development (NPD), Supplier Management (SUM), Manufacturing Management (MM), Dealer Management (DEM), and Customer Management (CUM) were emerged as “Effect”. The principles that emerged as “Cause” were found to have a great impact on the principles that emerged as “Effect” and are essential to have successful implementation of TQM in an organization.

The Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are pivotal methods in multi-criteria decision-making, addressing causal relationships among criteria and ranking alternatives, respectively. This paper introduces a novel approach, integrating DEMATEL and TOPSIS under the framework of single-valued neutrosophic set (SVNS) to handle indeterminacy in decision-making. Applied to a knowledge management strategy case, the method utilizes eight criteria and four alternatives derived from the literature. The process involves DEMATEL for expert weight determination and direct-relation matrix creation through linguistic variable influence. Subsequently, TOPSIS is employed to rank alternatives based on distance measures. The combined method identifies the ‘Human Resource Department’ as the most crucial in knowledge management strategy. This integrated approach facilitates organizations in pinpointing vital criteria and alternatives for effective knowledge management. Comparative analyses with existing methods are also presented.

Blockchain is an emerging technology that can transform many sectors in the age of digitization. By adding more transparency to the transitions of information and physical items, blockchain is considered a disruptive innovation that has the power to alter conventional supply chain activities. In these circumstances, blockchain technology must also be implemented in the supply chain. While implementing blockchain technology, supply chain partners face a number of barriers. As a result, the main goal of this research is to explore the prime barriers to the adoption of blockchain technology in the supply chain. In order to achieve these goals, we reviewed the literature and sought the advice of industry experts to identify the 10 main barriers to the adoption of blockchain technology. Further, the DEMATEL approach is used to categorize the finalized barriers into influential and influenced groups. The finding of this study suggests that “influential group” barriers demand more attention from the supply chain partners to minimize these barriers. The top influencing factors are “unwillingness of information sharing”, “lack of trust among SC partners” and “lack of technological advancement” and these barriers demand quick attention from supply chain stakeholders. This study looks into the barriers that stand in the way of effectively implementing blockchain in the supply chain, which will help managers do so.

Because of increasing pressures from government, non-government organizations, and stakeholders, companies are forced to implement climate change mitigation and adaptation initiatives. Suppliers have great impact on a company’s performance and its supply chain’s performance. Managing risks and incurred costs related to climate change at the supplier end becomes a necessary task for companies. Supplier development is one of the most important key strategies for companies to stay competitive in the market. This study pioneers in proposing a Decision-Making Trial and Evaluation Laboratory (DEMATEL) method-based framework to identify influential supplier development strategies related to climate change mitigation and adaptation. The DEMATEL method evaluates supplier development strategies to find the most influential strategy to improve suppliers’ performance and provides a novel approach to arriving at decision-making information in climate change adaptation and mitigation. The applicability of the framework is examined through a real-life case study of an Indian electronic manufacturing company. The results obtained show that top management support, continuous monitoring and feedback, and information sharing supplier development strategies are revealed to be the most influential strategies. The identified interrelationships among supplier development strategies can offer insights for managers to better understand cause–effect relationships in the context of climate change mitigation and adaptation.

Given the characteristics of technology intensity, long cycle, and multiple supporting facilities in the performance of equipment procurement contracts, this paper uses the WBS method to sort out the main tasks of each link in the performance of contracts and constructs the performance risk index system of equipment procurement contracts. Aiming at the interaction of risks during the procurement contract performance, the Dematel-Aism method is used to build the identification model of key risk factors, and the risk confrontation hierarchy chart is obtained, which visually shows the influence path and interaction of different risks factors in the performance process. Finally, the paper puts forward relevant suggestions on risk control.

Compliance with legislation and inclination towards sustainability have been major drivers for electronics manufacturers to implement end-of-life (EOL) and end-of-use (EOU) take back models. Designing of an efficient product recovery network entails key strategic decisions such as locating facilities with suitable capacities and determining an efficient distribution network for the reverse flow. Process of evaluation and selection of suitable location for managing recovery processes must allow the evaluation of opinions of all the stakeholders owing to its major economical, environmental as well as social impact. Multi criteria decision making (MCDM) techniques are therefore required to deal with the numerous conflicting tangible and intangible attributes. The paper aims at developing a MCDM model for an electronics manufacturing company seeking to sustainably manage its recovery processes for EOL and EOU products. It determines the optimal location of a recovery facility center (RFC) and optimal collection routes. For this purpose, the Decision Making Trial and Evaluation Laboratory (DEMATEL) is utilized to determine the interdependencies among the various conflicting criteria considered for evaluation of alternative locations. Analytic Network Process (ANP) is then applied to generate the relative importance of the locations. Locating, capacity and routing decisions are further incorporated by developing a mixed integer linear programming model under fuzzy environment which determines optimum capacity of the RFC to be opened with adoption of best technology and optimal routes of transportation with optimal selection of vehicles. The mathematical model performs trade-off between economical and environmental performance (in terms of carbon emission) of the proposed reverse logistics (RL) network.