Evaluation Laboratory Approach Research Articles

Unveiling the Dynamics of Consumer Attention: A Two-Stage Hybrid MCDM Analysis of Key Factors and Interrelationships in Influencer Marketing

In recent years, influencer marketing has taken over traditional brand advertisements on social media platforms, combining word-of-mouth marketing with celebrity endorsements. However, there has been limited academic research on the key success factors in influencer marketing. This paper used a hybrid MCDM model that integrates the Delphi method and the decision-making trial and evaluation laboratory (DEMATEL) approach. Through a two-stage empirical study, the research aims to explore the crucial success factors in influencer marketing. This study focuses on the Taiwanese market. The target respondents for the survey are consumers in Taiwan who have purchased products or services based on recommendations from key opinion leaders (KOLs) or internet celebrities. This systematic research framework not only pinpoints key factors that capture consumer attention towards influencers, but it also illustrates the inter-relationship of structure and improvement directions among these factors. According to results, the key factors include influencer reputation, credibility, degree of key opinion influence, attractiveness, popularity, consistency between influencers and brands, fan engagement level, and informativeness. Finally, businesses can consider five aspects to be the purpose of collaboration, product type, target audience for the product, characteristics of the influencer’s creative content, and media attributes. By comprehensively considering these aspects, businesses can determine the appropriate format for collaborative content. This decision can then guide how influencers communicate with consumers, effectively conveying brand information to the relevant target audience. The research findings provide fresh and significant insights in the field of influencer marketing studies.

A GIS-Based Flood Risk Assessment Using the Decision-Making Trial and Evaluation Laboratory Approach at a Regional Scale

This paper introduces an integrated methodology that exploits both GIS and the Decision-making Trial and Evaluation Laboratory (DEMATEL) methods for assessing flood risk in the Kosynthos River basin in northeastern Greece. The study aims to address challenges arising from data limitations and provide decision-makers with effective flood risk management strategies. The integration of DEMATEL is crucial, providing a robust framework that considers interdependencies among factors, particularly in regions where conventional numerical modeling faces difficulties. DEMATEL is preferred over other methods due to its proficiency in handling qualitative data and its ability to account for interactions among the studied factors. The proposed method is based on two developed causality diagrams. The first diagram is crucial for assessing flood hazard in the absence of data. The second causality diagram offers a multidimensional analysis, considering interactions among the criteria. Notably, the causality diagram referring to flood vulnerability can adapt to local (or national) conditions, considering the ill-defined nature of vulnerability. Given that the proposed methodology identifies highly hazardous and vulnerable areas, the study not only provides essential insights but also supports decision-makers in formulating effective approaches to mitigate flood impacts on communities and infrastructure. Validation includes sensitivity analysis and comparison with historical flood data. Effective weights derived from sensitivity analysis enhance the precision of the Flood Hazard Index (FHI) and Flood Vulnerability Index (FVI).

Analysis of the Barriers to Smart City Development Using DEMATEL

This study analyzes the barriers to developing smart cities (SCs) using the decision-making trial and evaluation laboratory (DEMATEL) approach. The primary objective is to identify, classify, and assess the main barriers hindering the progress of SCs. Through an extensive literature review, twelve main barriers were identified. The DEMATEL approach models and analyzes the relationships among these barriers based on expert input. The results reveal that technical problems, a lack of infrastructure, and high costs are classified as cause barriers. Security and privacy concerns and the absence of coordinated planning are classified as effect barriers. This study emphasizes the need for established criteria and iterative development requirements. Although the influence of knowledge and skills gaps and a lack of awareness is less significant, these aspects still require attention. The findings suggest that a comprehensive approach focusing on technical solutions, infrastructure development, strategic planning, and cybersecurity measures can effectively overcome barriers. Regular evaluation of barrier dynamics is crucial for implementing adaptive measures. The results provide decision-makers with a valuable model to address the challenges and foster the efforts of SC stakeholders.

Prioritizing sustainable renewable energy systems in Tunisia: An integrated approach using hybrid multi-criteria decision analysis

In recent years, renewable energy technologies (RETs) have become increasingly popular worldwide to achieve energy sufficiency, reduce reliance on conventional fuels, and mitigate their devastating environmental impact. Nonetheless, more appears to have stayed the same in emerging economies, such as Tunisia, as various barriers hampered the implementation of these technologies. Hence, the prime objective of this article is to conduct a thoughtful assessment of four prominent renewable energy options for electricity generation and explore the most potential barriers hindering their development in Tunisia. To do so, a two-stage approach was applied. First, CRiteria Importance Through Inter-Criteria Correlation (CRITIC) and Evaluation based on Distance from Average Solution (EDAS) were used to evaluate the considered alternatives, namely solar PV, concentrated solar power (CSP), onshore wind, and biomass. Then, an integrated step-wise assessment ratio analysis and decision-making trial and evaluation laboratory approach (SWARA-DEMATEL) was developed to identify the most relevant barriers. The related criteria and barriers were determined based on an exhaustive literature review and experts’ feedback. The obtained results indicated that solar PV and wind were the most promising renewable technologies, while biomass was the worst option. To validate the outcome and demonstrate the effect of changing input data on the final results, a sensitivity analysis has been carried out. As for the key obstacles, political instability, high upfront costs, and market access mechanisms were the most influential barriers. Hence, prioritizing different RETs and analyzing the inherent barriers to their utilization would offer insightful guidance to policymakers, enabling them to establish efficient strategies for overcoming these obstacles, and accelerating the deployment of these technologies in the country.

Selection of Industry 4.0 technologies for Lean Six Sigma integration using fuzzy DEMATEL approach

PurposeThis study aims to explore the integration of Industry 4.0 technologies with lean six sigma practices in the manufacturing sector for enhanced process improvement.Design/methodology/approachThis study used a fuzzy decision-making trial and evaluation laboratory approach to identify critical Industry 4.0 technologies that can be harmonized with Lean Six Sigma methodologies for achieving improved processes in manufacturing.FindingsThe research reveals that key technologies such as modeling and simulation, artificial intelligence (AI) and machine learning, big data analytics, automation and industrial robots and smart sensors are paramount for achieving operational excellence when integrated with Lean Six Sigma.Research limitations/implicationsThe study is limited to the identification of pivotal Industry 4.0 technologies for Lean Six Sigma integration in manufacturing. Further studies can explore the implementation challenges and the quantifiable benefits of such integrations.Practical implicationsIntegrating Industry 4.0 technologies with Lean Six Sigma enhances manufacturing efficiency. This approach leverages AI for predictive analysis, uses smart sensors for energy efficiency and adaptable robots for flexible production. It is vital for competitive advantage, significantly improving decision-making, reducing costs and streamlining operations in the manufacturing sector.Social implicationsThe integration of Industry 4.0 technologies with Lean Six Sigma in manufacturing has significant social implications. It promotes job creation in high-tech sectors, necessitating advanced skill development and continuous learning among the workforce. This shift fosters an innovative, knowledge-based economy, potentially reducing the skills gap. Additionally, it enhances workplace safety through automation, reduces hazardous tasks for workers and contributes to environmental sustainability by optimizing resource use and reducing waste in manufacturing processes.Originality/valueThis study offers a novel perspective on synergizing advanced Industry 4.0 technologies with established Lean Six Sigma practices for enhanced process improvement in manufacturing. The findings can guide industries in prioritizing their technological adoptions for continuous improvement.

WHAT HINDERS INTERNET OF THINGS (IOT) ADOPTION IN THE CHINESE CONSTRUCTION INDUSTRY: A MIXED-METHOD

Although the Internet of Things (IoT) has aroused much interest as a potential approach for improving various construction activities, the extent of its adoption remains limited. The multiple barriers that prevent the wider adoption of IoT in the construction industry need detailed investigation. However, limited research has attempted to understand the barriers to IoT adoption. Therefore, this study aims to identify the critical barriers to IoT adoption in the construction industry and explore the prioritization and hierarchical structure of the barriers factors. Data were collected from relevant literature and feedback from Chinese industry experts, sixteen barriers against IoT adoption were identified and categorized based on the TOE framework assessed in the construction industry. An integrated interpretation structure model and decision-making and trial evaluation laboratory (ISM-DEMATEL) approach is adopted to analyze the interdependence between identified constructs and their intensities. In addition, the identified constructs are also clustered into a suitable group using MICMAC analysis. Results show that inadequate infrastructure, lack of governance, and top management support are the fundamental barrier against IoT adoption. By revealing the mutual relationships and interlinking of barriers, this study will help researchers and practitioners in the construction industry to focus on strategic efforts to overcome these obstacles to effective IoT implementation. This research revealed the barriers to IoT implementation in the Chinese construction industry. Also, it provides methodological tool references for exploring the impact factor of other similar innovative technology applied in this industry.

Ethanol production ecosystem in India: Exploring enabling factors of sustainable policy regime

In recent years, policy-makers and researchers have paid close attention to sustainable energy resources. Biofuel has emerged as a viable option among available alternatives in countries with excess agricultural production. India is also ramping up ethanol production. However, there is limited research available on enablers that can help boost production for enhanced blending, thereby assisting in the achievement of energy security and the transition to a low-carbon economy. Furthermore, India can capitalize on its excess agri-production for long-term energy security, increase farmer income, reduce import bills and foreign exchange outflows, encourage local business participation and accelerate its overall economic development while lowering its carbon footprints. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) approach is used in this article to investigate the enablers for implementing a policy regime for increased ethanol production. The findings are important for policy-makers in India to identify areas for policy interventions, and they also lay the groundwork for future similar research on this evolving industry in the global markets.

Moving Towards Industry 5.0 in the Pharmaceutical Manufacturing Sector: Challenges and Solutions for Germany

Emergence of industry 5.0 facilitates real-time synchronisation of production processes, which helps with the production of customized products. Although industry 5.0 can revolutionize the landscape of goods production, still its adoption is in the infancy stage. Hence, the purpose of this article is to examine barriers that impede the adoption of industry 5.0, and to propose solution initiatives (SIs). After an in-depth literature review and interviews with German industry experts in pharmaceutical sector, barriers and SIs are ranked using an integrated Analytical hierarchy process-elimination and choice expressing reality-decision-making trial and evaluation laboratory (AHP-ELECTRE-DEMATEL) approach. “Linking virtual reality and reality” is found to be the most critical deterrent to the adoption of industry 5.0, and falls into a causal group, which signifies their influence on other deterrents. “Measures for better connectivity with patients” is of utmost importance for German firms to ensure secure communication and safeguard patient data. The findings also highlight the problems with the adoption of high-tech innovations due to lack of standardization and fair benchmarking policies on industry 5.0. This article concludes by proposing an industry 5.0 framework. The inhibitors to adopting industry 5.0 were investigated in this article, the results of which will assist practitioners and decision makers to understand the issues with industry 5.0. The results of this article will help potential adopters of this technology to look for the SIs. This will therefore pave the path for effective adoption of industry 5.0 across the pharmaceutical manufacturing sector.

Implementing Additive Manufacturing for Sustainability in Operations: Analysis of Enabling Factors

Additive manufacturing (AM) is heralded as a new manufacturing paradigm with significant environmental, economic, and social sustainability consequences. The purpose of this study is to identify and evaluate the sustainable enablers of AM. The research has identified 19 sustainable enablers of AM belonging to three areas: social, economic, and environmental, through an in-depth literature review. The decision-making trial and evaluation laboratory (DEMATEL) approach has been applied after taking inputs from industry experts to develop causal relationships (cause–effect diagram) and to analyze each enabler's influence. The cause–effect diagram has been developed based on threshold values. Our observations revealed that weight reduction, reduced time to market, mass customization, and personalization are the most critical enablers for sustainability. From visual representation, reduced toxicity of materials, no need for tooling, and ease of accessibility for remote part production have a substantial impact on effect enablers. This study will facilitate AM practitioners to systematically identify and prioritize essential enablers from a sustainability perspective. Practitioners should focus on these cause group enablers because it will help in controlling the effect of group enablers to improve sustainability in operations. Furthermore, insights from the study will enable policymakers to make policies leading to sustainable development. The novelty lies in identifying 19 enablers and incorporating the DEMATEL model to assess the causal relationship.

Enhancing Digital Social Innovation Ecosystems: A Pythagorean Neutrosophic Bonferroni Mean (PNBM) -DEMATEL Analysis of Barriers Factors for Young Entrepreneurs

This study employs a Pythagorean Neutrosophic Bonferroni Mean (PNBM) - Decision Making Trial and Evaluation Laboratory (DEMATEL) approach to analyze barriers faced by young entrepreneurs in Digital Social Innovation (DSI). Pythagorean Neutrosophic Set (PNS) enriches the analysis, accommodating uncertainties in the complex socio-economic context. Limited Access to Funding emerges as the most influential barrier, showcasing its pivotal role in impacting other DSI challenges. Regulatory and Compliance Challenges are identified as interdependent, emphasizing their interconnected nature with broader barriers. Neutrosophic elements elucidate the uncertainties surrounding financial constraints, regulatory frameworks, and mentorship dynamics. The study contributes to a nuanced understanding of DSI challenges and pioneers the application of neutrosophic logic in socio-economic research. It advocates for a more inclusive decision-making methodology, fostering adaptability in addressing the indeterminate nature of barriers faced by young entrepreneurs navigating the digital social innovation landscape. The findings aim to enhance support systems, fostering a conducive environment for DSI initiatives and encouraging future research in neutrosophic decision-making methodologies.

An Analysis of Factors Influencing Green Supply Chain Drivers in the Indian Real Estate Sector Using the ISM-DEMATEL Approach

Abstract In response to compelling environmental and societal imperatives, the real estate sector is increasingly compelled to adopt environmentally sustainable practices, prompting a significant “green” shift. Drawing upon an extensive literature review and insights garnered through expert interviews, this study identifies 15 critical factors influencing the green supply chain in the Indian real estate domain. Employing the Interpretive Structural Modeling–Dynamic Multi-Attribute Decision-Making Trial and Evaluation Laboratory (ISM–DEMATEL) approach, the hierarchical and contextual relationships among these factors are systematically examined. The ISM–DEMATEL analysis unveils that government policies and legislation, developer orientation and commitment, and green financing emerge as the top three pivotal drivers steering the green supply chain in the Indian real estate sector. To further categorize these drivers, a Matrice d’Impacts Croisés Multiplication Appliquée à un Classement (MICMAC) analysis is employed, resulting in the classification of factors into independent, dependent, autonomous, and linkage categories. The research offers practical insights that may prove invaluable to stakeholders within the real estate industry as well as academicians.

Identifying and ranking the critical success factors of fintech adoption: a fuzzy DEMATEL approach

Purpose This study aims to develop cause-and-effect relationships among the critical success factors (CSFs) of fintech adoption and rank these CSFs based on their importance in the model. Design/methodology/approach To achieve the objectives of the study, the Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL) approach was used. The data was collected from 16 experts using a questionnaire. Findings The findings demonstrated the interrelationships among the CSFs. In total, 16 critical factors were recognized as causal factors, and the remaining eight were considered effect factors. The CSFs were ranked based on their importance in fintech adoption. Originality/value This study is novel as it investigates CSFs of fintech adoption using FDEMATEL, and it contributes to understanding the nature of these factors and how they affect fintech adoption. The findings propose a significant basis to deepen fintech adoption and deliver a clue to design a practical framework for fintech adoption.

A hybrid fuzzy decision-making trial and evaluation laboratory and multi-criteria decision-making approach for successful implementation of supply chain collaboration strategies

This study proposes an integrated framework for successfully implementing collaboration strategies in supply chain (SC) management using a fuzzy decision-making trial and evaluation laboratory (DEMATEL) and multi-criteria decision-making (MCDM) approach. The study analyses and measures the successful possibility of SC collaboration implementation in small and medium enterprises (SMEs). The fuzzy DEMATEL is used to evaluate the weight of each criterion, and fuzzy MCDM is used to assess the possible success rates of the collaboration strategies. The result shows that top management support and commitment, SC strategic planning, information sharing, goal congruence, organizational compatibility, and decision synchronization are major factors responsible for SC collaboration success in SMEs. This study helps predict the effectiveness of collaboration strategies and indicates remedial activities in the existing collaborative environment by undertaking corrective actions and measures to increase implementation success.

Identifying ESG investment key indicators and selecting investment trust companies by using a Z-fuzzy-based decision-making model

The rising regulatory and public pressure to align investments with sustainability causes an increasing need to analyze how investment institutions conduct and execute investment strategies related to their environmental, social, and corporate governance (ESG) funds. A thorough literature review shows that multiple criteria decision-making models are rarely used to discuss the relationships and weights of ESG fund indices. Furthermore, no ESG investment strategy evaluation framework has been created to deal with such funds. Therefore, a comprehensive framework is developed in this study to help select appropriate investment trust companies (ITCs). Z-numbers are incorporated into the proposed decision-making model in order to reflect information uncertainty and to assess the confidence of expert evaluations. First, a Z-based decision-making trial and evaluation laboratory approach is used to obtain the relationships and weights of indices to generate a causality diagram that allows decision-makers to quickly recognize the critical influencing factors in their evaluation systems. Then, a Z-based reference ideal method is applied to integrate the performance of the ITCs. The empirical application provides a demonstration of the usefulness of the proposed approach for selecting ITCs, which can aid to formulate appropriate strategies.

Modelling the factors impacting customer engagement for branded content in healthcare

PurposeIn this global digital era, health-care companies are increasing their presence on the internet through branded content that serves as a connecting link between customers and brands. However, there is a limited understanding of branded content’s impact on customers. Thus, this paper aims to empirically analyse customer engagement for branded content in the health-care sector.Design/methodology/approachThe factors impacting customer engagement for branded content were identified and analysed using the Decision-Making Trial and Evaluation Laboratory approach to get their significance and the cause and effect relationship.FindingsIt emerged that co-creation is the most significant factor, having a substantial relationship with all other factors. It is substantiated that health-care companies can increase the intensity of customer engagement by delivering more authentic and relevant content and having an appealing look in a time-bound manner. This will increase the usefulness and entertaining value of the content.Originality/valueThe research findings contribute to the customer engagement dimension in the health-care sector and help the companies construct effective branded content leading towards higher customer engagement.

Optimizing the dam site selection problem considering sustainability indicators and uncertainty: An integrated decision-making approach

Changes of climate, population growth, extended droughts, water scarcity, and sustainability considerations are amongst the concerns that stress more than before the significance of water resources management (WRM). One of the approaches that may assist decision-makers (DMs) in handling water resources is the proper site selection for dam construction. The dam site selection decision is a huge long-term investment and due to multiple decision-making factors, stakeholders or DMs, non-deterministic information in the decision-making process, and ripple effect on many other elements of the economy, meticulous analysis is needed. In this study, dam site selection problem (DSSP) is modeled in the form of binary programming under certainty, uncertainty, and hybrid circumstances. Hence, nadir compromise programming (NCP) model is executed in order to tackle the problem with crisp data. Further, a novel model based on NCP and stochastic programming is suggested to treat the uncertainty. The integration of the proposed models is able to address the problem with crisp and random data. The evaluation criteria are categorized based on sustainability (social, economic, and environmental) and technical indicators for dam site selection. To obtain the criteria weight, an interval group decision-making trial and evaluation laboratory (IGDEMATEL) approach is also applied where experts are able to state their opinions on linguistic terms and interval numbers. A real case study in Iran is then investigated in order to appraise the applicability of the developed methodology. A simulation method is further proposed to assess the obtained results and validate the suggested model's performance. Finally, the IGDEMATEL results are employed to survey the relationships between cause-and-effect criteria. The results obtained from the proposed and simulation models are similar in 83% of the cases, and the remaining difference of 17% is because of the uncertainty governing the problem, as well as the lack of sufficient data for precise decision-making.

Reconfigure and evaluate consumer satisfaction for Open API in advancing FinTech

With the rise of FinTech, Open API (application programming interface) is essential in advancing FinTech applications in the future, but its customer satisfaction is a concern. Therefore, this study uses the technology acceptance model (TAM) to reconfigure and evaluate customer satisfaction of Open API in advancing FinTech by applying extended variables. This study initially applies the decision making trial and evaluation laboratory (DEMATEL) approach with the analytic network process (ANP) technique to reconfigure the modified TAM. Finally, we use Vlse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) analysis to evaluate customer satisfaction for examining the acceptance of Open API.The results of DANP point out ‘perceived privacy’ (0.179), ‘customer use intention’ (0.158) and ‘perceived usefulness’ (0.147) are the three most influential variables for Open API in advancing FinTech. Furthermore, VIKOR analysis indicates online security or cryptocurrency trading (0.536) performs best in which Open API can satisfy customers in advancing FinTech and online banking (0.438) has the most space for improvement. This study also indicates that privacy protection plays a very important role in consumer satisfaction of Open API. The influences of the variables demonstrate that Open API compared to conventional APIs, is more convenient and relatively beneficial in advancing FinTech.

Identifying and exploring the relationship among the critical success factors of sustainability toward consumer behavior

PurposeThe purpose of this study is to find out what is the relationship between sustainability toward consumer behavior. Consumer behavior is the method of choosing, buying and using goods and services with an attachment to needs and wants. Now consumers are aware about sustainability, they make purchase decisions according to environmental safety, benefit to the society and increase economic growth.Design/methodology/approachThis study validates the result through experts in textile industry by using the Decision-Making Trial and Evaluation Laboratory approach. This method has many benefits which provide decision makers and experts to understand the interdependence and influential relation between the criteria by hierarchical approach.FindingsAccording to the results, green culture (F8) and green brand (F3) are the most influential (causal) factors and exert a substantial amount of influence over other factors for achieving organizational performance and sustainability. On the other hand, past experience (F14) and time pressure (F12) are the most influenced (effect) factors that are highly influenced by other factors.Practical implicationsThe study conducted in Pakistan underscores the significance of maintaining a healthy and pristine environment for future generations. Both consumers and organizations play a vital role in this endeavor. It is imperative that they actively promote and support goods and services that advocate for sustainability.Social implicationsMangers should use long-term strategies that meet the high product value to enhance the organization’s reputation, so it will have positive consumer perception. If managers make policies to implement natural resources in their raw material, so this policy avoids conflicts and maintains a balance in our society.Originality/valueThis research delves into the complexities and subtleties associated with the identification and examination of the interconnections between the success factors of sustainability and consumer behavior.

Key factors influencing mass willingness to use CESPs under green concept: ECOCO smart recyclers as a case study

In promoting green life and environmental protection, encouraging mass participation in environmental protection activities and increasing mass willingness to use circular economy service platforms (CESPs) are of high importance. In light of this stance and other several dimensions, including green concept, hedonic value, and user benefits, the multiple attribute decision-making technique was used to develop an evaluation model that assesses the influential factor of one's willingness to use CESPs. By employing the decision-making trial and evaluation laboratory (DEMATEL) approach, the degree of mutual influence between different evaluation dimensions and criteria was first determined to generate an influential network relation map (INRM). Next, the weights of influence of varying evaluation dimensions and criteria were calculated by combining the DEMATEL approach with analytic network process. Finally, an empirical analysis of comprehensive performance of different evaluation dimensions and criteria was carried out based on the modified VIKOR technique. Referring to the INRM, green information emerged as the primary aspect that should be improved and adjusted, followed by green management, hedonic value, user benefits, green appeal, and green participation in order of priority. These outcomes may serve as reference regarding ways to enhance mass willingness to use the ECOCO CESPs and its smart recyclers.

Integrated FAHP-FDEMATEL for determining causal relationships in construction crew productivity modelling

Construction crew productivity is affected by the motivation of the crew performing given activities and by situational/contextual factors forming the dynamic construction environment. The literature lacks a comprehensive analysis of causal relationships between crew motivation and situational/contextual factors for dynamic modelling of crew productivity. The contributions of this paper are (1) identifying a set of criteria for performing expert weight assignment for heterogenous group experts in productivity research, (2) proposing an integrated fuzzy analytic hierarchy process–fuzzy decision-making trial and evaluation laboratory approach that provides a systematic, structured method for determining causal relationship mapping between factors affecting crew productivity, and (3) proposing an approach for identifying cause-and-effect groups among the situational/contextual factors and crew motivation, which can further be used to formulate strategic productivity improvement solutions. The proposed methodology is demonstrated using a case study on an actual industrial construction project in Alberta, Canada.