Decision Making Trial And Evaluation Laboratory Research Articles

Analysis of Industry 4.0 technological enablers for sustainable supply chain transparency in a fuzzy environment

AbstractThis study aims to identify various Industry 4.0 technological enablers and analyze their relationships in achieving transparency in sustainable supply chains. Initially, 17 Industry 4.0 technological enablers were selected based on an extensive literature review of sustainable supply chains and evaluated through Systems and Information Processing theories. Using the fuzzy Delphi method, these enablers were then narrowed down to 14 relevant ones. The reliability of these enablers was assessed by measuring their internal consistency using Cronbach's alpha (α) and McDonald's omega (ω). The fuzzy Decision‐Making Trial and Evaluation Laboratory (DEMATEL) method was then used to demonstrate that blockchain, cybersecurity, big data, and artificial intelligence (AI) are the most prominent and influential enablers for enhancing transparency in a sustainable supply chain. Additionally, the cause–effect relationship of other key enablers provides evidence for a feasibility study that links sustainability with transparency across the supply chain. These identified Industry 4.0 technological enablers can assist external stakeholders and policymakers in improving transparency and advancing sustainable supply chain practices.

An integrated group decision support framework utilizing Pythagorean fuzzy DEMATEL–CoCoSo approach for medicine cold chain logistics provider selection

PurposeThe purpose of this study is to establish a synthetic group decision framework based on the Pythagorean fuzzy (PF) set to select the optimal medicine cold chain logistics provider (MCCLP). Fierce market competition makes enterprises must constantly improve every link in the process of enterprise sustainable development. The evaluation of MCCLP in pharmaceutical enterprises is an important link to enhance the comprehensive competitiveness. Because of the fuzziness of expert cognition and the complexity of the decision procedure, PF set can effectively handle the uncertainty and ambiguity in the process of multi-criteria group decision decision-making (MCGDM).Design/methodology/approachThis paper develops an integrated group decision framework through combining the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique and combined compromise solution (CoCoSo) approach to select a satisfactory MCCLP within PF circumstances. First, the PF set is used to process the ambiguity and uncertainty of the cognition ability of experts. Second, a novel PF knowledge measure is propounded to measure the vagueness of the PF set. Third, a comprehensive criterion weight determination technique is developed through aggregating subjective weights attained utilizing the PF DEMATEL approach and objective weight deduced by knowledge measure method. Furthermore, an integrated MCGDM approach based on synthetic weight and CoCoSo method is constructed.FindingsThe outcomes of sensibility analysis and comparison investigation show that the suggested decision framework can help decision experts to choose a satisfactory MCCLP scientifically and reasonably. Accordingly, the propounded comprehensive decision framework can be recommended to enterprises and organizations to assess the MCCLP for their improvement of core competitiveness.Originality/valueMCCLP selection is not only momentous for pharmaceutical enterprises to improve transportation quality and ensure medicine safety but also provides a strong guarantee for enterprises to improve their core competitiveness. Nevertheless, enterprises face certain challenges due to the uncertainty of the assessment environment as well as human cognition in the process of choosing a satisfactory MCCLP. PF set possesses a formidable capability to address the uncertainty and imprecision information in the process of MCGDM. Therefore, pharmaceutical enterprises can implement the proposed method to evaluate the suppliers to further improve the comprehensive profit of enterprises.

Applying Fuzzy Decision-Making Trial and Evaluation Laboratory and Analytic Network Process Approaches to Explore Green Production in the Semiconductor Industry

As environmental awareness grows, society emphasizes green business. Thus, semiconductor companies encompass energy-saving processes and innovative product development. This study employs the fuzzy decision-making trial and evaluation laboratory (DEMATEL) analysis method to assess the impact of four key dimensions, externalities, market orientation, green technology, and corporate social responsibility, on semiconductor companies’ green production decisions. This study uses the DEMATEL-based analytic network process (DANP) approach to rank the criteria order in green production decision-making. The results from the DEMATEL causality diagram highlight externalities as the most critical dimension influencing other dimensions of green production decisions. This study suggests that regulatory pollution punishment and subsidies emerge as the primary drivers for green production decisions. Companies adopt environmentally friendly production practices to prevent regulatory pollution penalties or reduce carbon trading costs. Additionally, the DANP results reveal that corporate image criteria in the corporate social responsibility dimension hold the utmost priority in semiconductor firms’ green production decision-making. This implies that considerations for improving a company’s image should take precedence as semiconductor companies seek shareholder support and governmental subsidies to ensure sustainable operations. Externalities arise as the secondary priority dimension in green production decision-making, aligning with the impact of externalities identified in DEMATEL findings.

An Innovation Management Approach for Electric Vertical Take-Off and Landing

With more companies entering the realm of electric vertical take-off and landing (eVTOL) and governments enacting policies to support the development of low-altitude economies, the commercial potential of eVTOL is being recognized by the public. However, true commercialization is still a long way off. This article analyzes the technologies, product features, potential markets, and government policies related to eVTOL and constructs a four-stage, four-layer Policy–Technology Roadmap (P-TRM) model to guide the R&D process of eVTOL. Then, it is transformed into a system structural model, and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is used to identify several key nodes in the R&D process. Utilizing the Technology Adoption Life Cycle (TALC) theory for interpretation and analysis, the article concludes by proposing strategies in product, technology, and policy support for how eVTOL can successfully cross the chasm. This preliminary analysis of the development path, key nodes, and necessary measures for crossing the chasm provides insights for the R&D and commercialization of eVTOL.

Navigating barriers to reverse logistics adoption in circular economy: An integrated approach for sustainable development

Achievement of sustainability goals is an epic task for developing economies that still strive to fulfil their basic needs. The availability of limited resources in the developing world vis-à-vis the ever-increasing demand poses further challenges to developing economies willing to transition into circular economies. Reverse logistics (RL) can facilitate this transition towards a circular economy (CE) by maximising resource utilisation and minimising waste, contributing to sustainability goals. This paper contributes to emerging literature by analysing the development and comprehensive potential of reverse logistics as a sustainability tool. It explores the significant barriers to the adoption of reverse logistics towards a circular economy, considering long-term sustainability. In the first phase, thirteen barriers have been identified from the past academic literature. Three barriers with a defuzzification number less than the threshold limit are excluded, and the final ten barriers are then prioritised using the decision-making trial and evaluation laboratory (DEMATEL) method. The findings suggest that a lack of strategic plans for returns is crucial for RL adoption towards a circular economy, followed by a lack of visibility for recycling/reuse. Organisations can increase customer satisfaction, promote environmental sustainability, and gain a competitive edge in the market by creating a strategic plan for reverse logistics. Organisations may lower costs and contribute to a more sustainable and ecologically responsible supply chain by improving visibility across the reverse logistics process. The results serve as a framework for decision-making in RL towards sustainable development. Managers and policymakers can formulate more robust and realistic decisions that align with “maximising profits,” “saving the planet,” “social concerns,” and, most importantly, “consumer concerns” in the circular economy ecosystem. Several implications are derived, leading to increased competitiveness and resilient business strategies. The novelty of this work lies in the identification of barriers to reverse logistics adoption towards a circular economy using an integrated fuzzy Delphi-DEMATEL approach, considering long-term sustainability. This approach is studied for the first time in a developing economy context, proposing social, economic, and environmental effects and actions to be taken by organisations for sustainable development.

Psychological resilience factors in intensive care nursing: a hybrid multi-criteria decision-making model

PurposeTo analyze the key factors influencing the psychological resilience of intensive care unit (ICU) nurses during the COVID-19 pandemic and put forward suggestions promoting resilience based on key improvement factors and clinical experience.MethodsData were collected from 35 ICU nurses in a hospital in Zhejiang Province, China, through a questionnaire survey conducted between January and February 2023. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was then used to construct and visualize the relationship structure between the factors. The DEMATEL-based Analytical Network Process (DANP) was applied to determine the influential weights of all factors. Finally, the key improvement factors were identified using importance-performance analysis (IPA).ResultsBased on the cause-effect impact network diagram (CEIND), it was concluded that (C11), (C22), and (C32) are the key factors that promote the improvement of psychological resilience among ICU nurses. Additionally, these factors were the key factors that influence psychological resilience. The confidence levels of these results and the gap were 99.6% and 0.4%, respectively, which exceed the threshold value of 95%, indicating good stability. Finally, for the case hospitals, (C13) was identified as the key improvement factor.ConclusionsHospital administrators should support ICU nurses in enhancing their psychological resilience during major epidemics by: (i) Providing training on comprehensive protective measures and nursing skills; (ii) Effectively managing the human resources of nurses in the hospital to reduce their workload; (iii) Increasing social and organizational support for nurses to alleviate anxiety caused by large-scale public health events and improve their psychological resilience.

Identifying the risk factors of patient safety in internet hospitals: A mixed methods study

ObjectiveThe purpose of this study was to identify key risk factors and their interrelationships for patient safety in internet hospitals from a system perspective, using mixed methods of qualitative and quantitative analysis. MethodsThis study constructed a comprehensive indicator system of patient safety risk factors in internet hospitals by qualitative analysis using the Patient Safety Systems (SEIPS) model as a framework. Risk factors were initially identified through a literature review and subsequently refined using a Delphi survey involving 24 experts related to internet hospitals in China. The identified indicators were quantitatively analyzed to determine key risk factors and their influencing mechanism using the Decision Making Trial and Evaluation Laboratory (DEMATEL) and Interpretive Structural Modeling (ISM) methods. ResultsThe qualitative analysis established a patient safety risk factor indicator system for internet hospitals, comprising 23 elements across six dimensions. Quantitative analysis employing the DEMATEL-ISM approach revealed that risk management has the highest centrality. Among cause factors, task complexity exerts the most significant impact on other factors, while network information security exhibits the highest absolute value among result factors. Risk factors are categorized into three levels: surface, deep, and root factors, with task complexity, legal and regulatory, and guidance policy being the root factors at the foundation of the system. ConclusionsOur study offered a systemic perspective on analyzing risk factors for patient safety in internet hospitals. Policymakers and managers of internet hospitals should take advantage of the interrelationships among these factors to mitigate patient safety risks by effectively controlling key factors. Public Interest SummaryIn the rapidly evolving landscape of internet hospitals, ensuring patient safety is paramount. This study aimed to comprehensively identify and understand key risk factors influencing patient safety within these digital healthcare platforms. Using mixed methods of qualitative and quantitative analysis, the study examined the intricate interplay of factors affecting patient safety. Our methodology involved constructing a risk factors indicator system based on the Patient Safety Systems (SEIPS) model. By employing the integrated Decision-Making Trial and Evaluation Laboratory along with the Interpretive Structural Modeling method, we unveiled the core risk factors and their intricate relationships. Recognizing the interconnectivity of these factors allows us to develop effective risk mitigation strategies that enhance patient safety in internet hospitals. This study encourages stakeholders to leverage the dynamic relationships among these factors to ensure safer online healthcare experiences for patients.

Unlocking AI's potential in the food supply chain: A novel approach to overcoming barriers

This paper delves into the challenges impeding the seamless integration of artificial intelligence (AI) within the food supply chain (FSC) and introduces a novel methodological framework that combines the NK Model with the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique. Through an exhaustive literature analysis and expert discussions, the research identifies and categorizes significant obstacles to AI deployment in the FSC. These hurdles include the imperative for a skilled labor force, financial limits, regulatory complexity and technological limitations. The unique DEMATEL-NK approach highlights the interconnected nature of these barriers, pinpointing the most critical impediments. The study's implications extend to the broader domains of AI adoption in agriculture and the food industry, offering a nuanced perspective for policymakers, industry stakeholders, and researchers. The findings underscore the imperative of overcoming these barriers for the successful implementation of AI technologies in the FSC, promising advancements in efficiency, quality, and sustainability. The innovative methodology not only sheds light on the interconnectedness of these barriers but also provides a systematic approach for prioritizing and implementing solutions. This research offers a fresh viewpoint on barrier relationships, guiding decision-makers in crafting effective strategies and interventions to propel AI integration in the FSC forward.

Review of Cost Control Research in Prefabricated Construction under EPC Mode

Aims: Amidst the accelerating global urbanization and growing demand for sustainable development, prefabricated construction emerges as a pivotal transformational force in the construction industry due to its efficiency and environmental friendliness. This paper comprehensively reviews cost control research in prefabricated construction under the EPC (Engineering, Procurement, Construction) model. Study Design: The study adopts a literature-based approach, incorporating findings from domestic and international scholars, to uncover the critical issues and challenges in cost control within the EPC framework. Additionally, it analyzes the application of technological innovations such as BIM (Building Information Modeling) and DEMATEL (Decision Making Trial and Evaluation Laboratory) in cost control, offering a theoretical foundation and practical guidance for prefabricated construction under EPC. Place and Duration of Study: The research spans various regions globally, examining recent practices and theoretical advancements in cost control for prefabricated construction projects under EPC over the past decade to ensure timeliness and comprehensiveness. Methodology: The methodology encompasses a systematic literature review to construct a theoretical framework, coupled with an analysis of case studies showcasing effective cost control measures. Furthermore, the study explores the utilization of BIM and DEMATEL to enhance cost prediction accuracy, process monitoring, and decision-making support. Results: The findings reveal that the EPC model facilitates more systematic and efficient cost control in prefabricated construction. The application of BIM significantly improves cost forecasting precision and process transparency, enabling timely cost deviation identification and correction. DEMATEL effectively identifies key cost drivers and their interrelationships, informing targeted cost control strategies. Conclusion: This paper underscores the significance of cost control in prefabricated construction under the EPC model and highlights the pivotal role of BIM and DEMATEL in enhancing cost control effectiveness. It concludes by advocating for deeper integration of prefabricated construction with the EPC model to propel the green, intelligent transformation and sustainable development of the construction industry.

Assessment of Factors Influencing the Development of Inland Navigation in Poland

The presented article concerns the development of inland navigation in Poland. The aim is to determine and analyse factors that influence the development of this branch of transportation. To determine the parameters that are subject to further analysis, the author analysed publications on the development of inland waterway transport. Then, three groups of respondents (scientists, shipping administration employees, and inland navigation captains) evaluated seven selected factors (demand, operational parameters, ports, service, waterways improvement, fleet, and crew) and their mutual influence. Responses were analysed using the Decision Making Trial and Evaluation Laboratory (DEMATEL) method. According to the results, the factors influencing inland navigation to the greatest extent are demand, operational parameters, and waterways improvement; at the same time, all these factors were evaluated as influencing the other factors. This means that by modelling these factors, e.g., through political tools, one can achieve the fastest and greatest impact on the development of inland navigation in Poland. The factors assessed as the most important, at the same time being identified as influencing others (not being their effect), are the factors that should be taken into account first, because they can have the fastest and greatest impact on the development of inland navigation in Poland.

DEMATEL and ISM analysis of factors influencing coal spontaneous combustion in longwall gobs

Coal spontaneous combustion in longwall gobs is a major concern in coal mines. In comparison to other hazards, this phenomenon is difficult to detect. Fifteen factors influencing coal spontaneous combustion in longwall gobs were identified from the literature. The logical relationships between these factors were evaluated and quantified by decision-making trial and evaluation laboratory (DEMATEL) and interpretive structural modelling (ISM) methods. A four-level hierarchical structure model was established. The research shows that combining DEMATEL and ISM can reveal the key factors that influence coal spontaneous combustion in longwall gobs and establish the interactions and relationships among these factors. The results can provide the basis for preventing and controlling coal spontaneous combustion in longwall gobs.

An assessment of the prominence and total engagement metrics for ranking interdependent attributes in DEMATEL and WINGS

A weight vector is assigned to the attributes in multiple-attribute decision-making to show their relative importance. The interdependencies among the attributes often influence this weight vector. The decision-making trial and evaluation laboratory (DEMATEL) and weighted influence non-linear gauge system (WINGS) are among those methods that consider these interdependencies. These methods require matrix manipulation with several metrics to evaluate interdependencies. This study investigates the potential irregularities within the metrics employed by these two methods for weighing criteria. It examines these metrics and analyzes their sensitivity to the direction and the level of influence among attributes. We provide several numerical examples and mathematical analyses to evaluate their consistency by comparing the expected outcomes with the outcomes of the metrics. Although the metrics are expected to assign higher importance to the more influencing criteria, the total engagement/prominence metric is not sensitive to the direction and level of influence among attributes. We conclude these metrics are inconsistent and can not be used reliably as a composite indicator. In contrast, we show that the total impact factor reflects both the direction and the level of influence and is a reliable choice for this purpose.

Factors influencing contractors' low-carbon construction behaviors in China: a LDA-DEMATEL-ISM approach.

Contractors' low-carbon construction behaviors (CLCB) are pivotal in advancing decarbonization during the construction phase. However, there exists a notable gap in the comprehensive exploration of the multifaceted factors and mechanisms influencing CLCB. Therefore, this study aims to systematically identify the factors influencing CLCB in China, examine the interrelationships among these factors, and pinpoint the key determinants. Based on topic modeling of Latent Dirichlet Allocation (LDA), influencing factors are identified firstly from the pertinent literature. Subsequently, the causality degree and centrality degree between these factors are assessed by the Decision-Making Trial and Evaluation Laboratory (DEMATEL), followed by the establishment of a hierarchical structure using the Interpretive Structural Modeling (ISM) method, culminating in the identification of pivotal factors. Findings reveal that (1) 21 influential factors influencing CLCB are identified. (2) "Incentive policies for relevant stakeholders" and "Low-carbon regulation and supervision" emerge as key influences. (3) CLCB should be guided by policy and subjective awareness, fortified by market and management support, underpinned by technology, and directly driven by economic considerations. This research furnishes valuable insights for promoting low-carbon development during the construction phase, thereby assisting the construction sector in achieving carbon peak and carbon neutrality.

Prioritizing cybersecurity initiatives in aviation: A dematel-QSFS methodology

The aviation industry's growing dependence on digital technologies necessitates robust cybersecurity measures to counter advanced threats. This study integrates the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method with Quantum Spherical Fuzzy Sets (QSFS) to enable precise and reliable decision-making under uncertainty. Key criteria, identified through expert evaluations, include Threat Detection Systems (TDS), Data Encryption Protocols (DEP), Regulatory Compliance (RC), Incident Response Plans (IRP), User Training (UT), Access Control Mechanisms (ACM), and Network Security Solutions (NSS). Analysis using the proposed method revealed that “Regulatory Compliance” and “Threat Detection Systems” are the most influential factors, emphasizing the need for strict adherence to standards and advanced threat detection capabilities. Additionally, the significance of “User Training” and “Data Encryption Protocols” underscores the importance of comprehensive training programs and strong encryption measures. By incorporating strategic management theories such as the Resource-Based View (RBV), Contingency Theory, and Risk Management Theory, this study presents a strategic framework to assist aviation organizations, policymakers, and researchers in developing effective cybersecurity strategies, ensuring the safety and security of global air travel.

Implementation of Low Carbon Supply Chain Management Practices (LCSCMP) in Indian Manufacturing Industries using ISM-DEMATEL

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.

Study on comprehensive evaluation method of mental workload level

Abstract Mental workload has an important impact on the human performance of ship operators. The purpose of this study is to develop an evaluation method to evaluate the ship operator’s mental workload. First, an evaluation index system was constructed, and the DEMATEL (decision-making trial and evaluation laboratory) method was used to determine the relative weight of each index. Then, the fuzzy evaluation method was used to calculate the mental workload of ship operator based on the evaluation value and relative weight of indexes. The evaluation result of the developed method showed that the ship operators’ mental workload were 3.78 and 2.99 under tasks 1 and 2, and the ship operators’ mental workloads were at the ‘very high’ and ‘high’ levels based on the maximum membership principle. Also, the evaluation result of the developed method was consistent with the evaluation results of subjective mental workload assessment technique. It proves that the developed method can effectively evaluate the ship operator’s mental workload level.

Implementation of Intrahospital Transfer Strategy During COVID-19 and Identify Success Factors Based on DEMATEL Technique.

The COVID-19 pandemic caused a significant strain on world health care systems. The lack of trained and experienced staff was a complicated issue during the pandemic. To overcome insufficient staffing problems, the intrahospital transfer (IHT) strategy was implemented at Milad Hospital in Tehran during COVID-19. We evaluated the effectiveness of the IHT strategy in order to determine whether the strategy should be continued post-COVID. Six supervisors with experience in COVID-19 wards and the IHT strategy were consulted to identify the advantages of continuing the IHT strategy and to evaluate the success and continuation of IHT factors. Then, the decision-making trial and evaluation laboratory (DEMATEL) method was used to establish a network of influence relationships among IHT strategy factors' success. The result showed that all criteria except increasing patient satisfaction (C1) and reducing waste of time (C8) are cause-and-effect criteria that affected other criteria. The research findings have implications for improving the day-to-day experience of staff navigating transfers of patients between wards and paraclinic units. This study also highlights the theoretical value of the cross-disciplinary integration of medical decision issues and multiple-attribute decision-making methodologies.

Applying the extended UTAUT-2 to assess the factors contributing to consumers’ usage intention towards over-the-top video streaming platforms

The current study aims to examine consumers' over-the-top (OTT) video streaming platform usage intention and apply the extended unified theory of acceptance and use of technology version 2 (UTAUT-2) to develop a holistic evaluation model. Specifically, a decision-making trial and evaluation laboratory (DEMATEL) approach was utilised to discover the determinants of OTT video streaming service selection. This study comprehensively analyses data collected from 498 users of an OTT video streaming platform. The research rigorously examines and validates the proposed research questions by utilising multiple attribute causality modelling. The findings demonstrated that the primary factors for platform improvements were performance and effort expectancies, with facilitating conditions, personal innovativeness, hedonic motivations, and social influences significantly impacting consumers’ preferences. The findings provided insights into OTT platform providers to acquire more subscribers while improving respective competitiveness. The study discusses both theoretical and practical implications in depth.

EVALUATING THE SUCCESS FACTORS FOR KNOWLEDGE MANAGEMENT IN THE FINANCIAL SECTOR: AN AHP- DEMATEL APPROACH

The objective of this article is to identify and understand the success factors of knowledge management within the financial sector. In the ever-evolving business environment, effective knowledge management (KM) is imperative to maintain a competitive advantage. Effective KM within financial institutions can build standardized processes, ensure speedy delivery, and foster better customer relationship management. An integrated approach of the Analytical Hierarchy Process (AHP) and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods was used to rank these critical success factors and understand their interrelationships. The findings identify organizational factors (cultural aspects, organizational structure, top management support), technological factors (technological adoption, infrastructure support, collaborative systems), and human resources factors (training & learning, agile workforce, knowledge sharing) as the critical success factors. Technological factors were identified as the most important factors. The article further complements the findings of the AHP by exploring the interrelationships between the identified factors to understand and prioritize possible intervention areas. This research has significant theoretical and practical implications. The findings can help financial institutions implement and manage knowledge management initiatives within the organization. This study also adds to the extant literature and addresses gaps in the research in the context of KM within the financial sector.

Critical success factors for the adoption of AVs in sustainable urban transportation

Before integrating Autonomous Vehicles (AVs) into transportation systems, it's important to evaluate various aspects to facilitate their adoption. Numerous factors are likely to be crucial in this process. This research investigates the critical success factors influencing the adoption of AVs in sustainable urban transportation through a hybrid fuzzy Multiple-Attribute Decision-Making (MADM) approach. The primary aim is to identify key criteria and sub-criteria perceived by transport experts, shedding light on the complex dynamics of AV adoption. Methodologically, a fuzzy Decision Making Trial and Evaluation Laboratory (DEMATEL) is employed to unveil cause-and-effect relationships among the main criteria, determining their respective weights. Subsequently, fuzzy Analytic Network Process (ANP) is applied to calculate the weights of criteria and sub-criteria based on the fuzzy DEMATEL results. The study considers seven major factor dimensions: economic, technical, operational, environmental, safety and risk, social and regulatory, and user acceptance. Key findings underscore user acceptance, financial costs, and environmental impact as the most pivotal criteria, emphasising their significance in the eyes of transportation experts. Contrarily, technological and operational criteria hold the lowest weight in the considered criteria for AV adoption in transportation networks. This research provides valuable insights into critical barriers and opportunities in the adoption of AVs, contributing to the advancement of sustainable urban transportation.