Decision Making Trial And Evaluation Laboratory Analysis Research Articles

The Exploring the Relationship between Financial Performance Indicators, ESG, and Stock Price Returns: A Rough Set-based Bipolar Approach

Using a Rough-Set-based approach, this study investigates the connection between financial performance, Environmental, Social, and Governance (ESG) factors, and stock returns. It analyzes data from various companies and industries to examine how ESG metrics interact with financial indicators to influence stock prices. Those findings underscore the importance of considering financial and ESG factors when evaluating a company's performance and market valuation. The Rough-Set-based bipolar model comprises eight decision rules, and the DEMATEL (Decision-Making Trial and Evaluation Laboratory) analysis reveals the influence relationship among the core attributes. Furthermore, the ranking result, based on the bipolar model, is consistent with the market returns, which suggests the validity of this study.

The common drivers of children and young people’s health and wellbeing across 13 local government areas: a systems view

BackgroundSystem dynamics approaches, including group model building (GMB) and causal loop diagrams (CLDs), can be used to document complex public health problems from a community perspective. This paper aims to apply Social Network Analysis (SNA) methods to combine multiple CLDs created by local communities into a summary CLD, to identify common drivers of the health and wellbeing of children and young people.MethodsThirteen community CLDs regarding children and young people health and wellbeing were merged into one diagram involving three steps: (1) combining variable names; (2) CLD merging, where multiple CLDs were combined into one CLD with a set of unique variables and connections; (3) paring, where the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was used to generate a cut-point to reduce the number of variables and connections and to rank the overall importance of each variable in the merged CLD.ResultsCombining variable names resulted in 290 variables across the 13 CLDS. A total of 1,042 causal links were identified in the merged CLD. The DEMATEL analysis of the merged CLD identified 23 common variables with a net importance between 1.0 and 4.5 R + C values and 57 causal links. The variables with the highest net importance were ‘mental health’ and ‘social connection & support’ classified as high net receivers of influence within the system.ConclusionsCombining large CLDs into a simple diagram represents a generalisable model of the drivers of complex health problems.

DEMATEL analysis of corporate and public governance: identifying key factors for good governance

This paper aims to clarify the concepts of corporate governance and public governance, the principles and practices of governance, with an emphasis on the role and responsibility of management and on decision-making transparency. An extensive review of scholarly literature has pinpointed ten factors known to exert an influence on good governance. Following this, expert opinions were leveraged to establish the causal interrelationships among these factors, employing the Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology. The conclusions of the paper show that corporate governance can also be better applied in the field of public affairs, an approach so current under the difficulties and contemporary economic and social changes and under the extraordinary transformational pressure exerted by the new technologies and mentalities that do not bypass the relatively reluctant to change the sector of public administration. The development and diversification of public services, which must ensure a high degree of quality and efficiency under conditions of limiting the financial resources of the administrative-territorial units, obliges the efficiency of the management systems of these institutions, emphasizing their role, responsibility, transparency, and decision-making and credibility in front of the citizens.

Exploring Barriers to Adoption of Halal Certification among Restaurant Owners in Seremban, Malaysia

This preliminary study seeks to gain initial insights into the barriers encountered by restaurant owners in Seremban, Malaysia, regarding the adoption of halal certification. The research, which precedes a more comprehensive DEMATEL (Decision-Making Trial and Evaluation Laboratory) analysis, employs a quantitative approach and data collected through Google Forms from a limited sample of 26 restaurant owners. The findings highlight four primary barriers: cost, lack of awareness, procedural complexities, and insufficient government support. Notably, this study does not aim for exhaustive conclusions but serves as a foundational exploration, offering valuable perspectives for further investigation. The outcomes will be instrumental in advancing our understanding of halal certification adoption among restaurant proprietors in Seremban, ultimately facilitating more in-depth analyses and strategic solutions.

Green hydrogen in India: Prioritization of its potential and viable renewable source

Green hydrogen, a carbon-neutral fuel, has the potential to reduce atmospheric greenhouse gas and plays a vital role in mitigating climate change. Its potential is immense in renewable-rich Asian economies, however, its production is yet to start with key factors such as safety parameters, resources, proper government incentives, and public acceptability affecting its optimal generation. This study employs three multi-criteria decision-making approach like analytic hierarchy process (AHP), decision-making trial and evaluation laboratory (DEMATEL), and Fuzzy-AHP followed by the sensitivity analysis to identify and prioritize the robustness of the five primary potentials (social, political, economic, technical, and environmental). Subsequently, categorized into 22 sub-potentials of green hydrogen and ideal renewable resource for the sustainable development objective of India. The results of the DEMATEL analysis suggest that the social is the key predictor and the last one is Technical. The Fuzzy-TOPSIS method suggests that solar is the best renewable energy resource followed by wind, small hydro, and biomass energy. Hence, the government's intervention and robust policy frameworks are required to increase its production with special emphasis on cost considering solar energy. The finding of this study will guide the governments, energy sector players, producers, environmental advocacy groups, and users to make a strategic decision regarding the choice of the most viable source of renewable energy to achieve the targets of sustainable development Goals (SDGs-7).

Barriers to supply chain performance measurement during disruptions such as the COVID-19 pandemic

PurposeAmid the outbreak of coronavirus disease 2019 (COVID-19), supply chains have faltered. This has influenced operational and financial performance and lead to uncertainty in supply and distribution. Therefore, systems measuring supply chain risk and disruption management performance have gained interest. This study explores barriers to supply chain performance measurement during disruptions such as COVID-19.Design/methodology/approachBased on a survey and literature review, the authors formalise the barriers and rank them using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) fuzzy Višekriterijumsko kompromisno rangiranje (VIKOR) methodology. A total of 14 experts in 11 countries were surveyed. Performance measurement is based on a balanced scorecard.FindingsFifteen barriers are identified. Based on DEMATEL analysis, the cause–effect relationships among the four scorecard aspects are explored. The customer axis is revealed as the cause, while the financial, internal business and learning/development are identified as the effect of the supply chain performance measurement. Fuzzy VIKOR calculations show that uncertainty of investment, disrupted cash flows and the bullwhip effect are the most critical barriers to measure supply chain performance during outbreaks such as the COVID-19 pandemic.Research limitations/implicationsThe study identifies and ranks general barriers; additional research is required to differentiate barriers in specific industrial sectors.Practical implicationsThe findings may help develop proactive, resilient supply chain performance strategies to overcome disruptions.Social implicationsPolicy-makers and decision-makers in industrial and service firms can explore these findings to inform strategies for robust supply chains that can resist disruption in risky environments.Originality/valueThis research addresses a knowledge gap in barriers to measure supply chain performance in post-pandemic areas. It is unclear how far firms will measure supply chain performance in terms of learning from disruption patterns, managing financial and customer demand processes in light of COVID-19. This study contributes by explaining the influences among the barriers and exploring them, offering insights from multiple stakeholders.

Scientometric, fuzzy NGT and DEMATEL analysis for determining sustainable business practices for entrepreneurial firms

PurposeThe purpose of this article is to (1) map the most important topics in the domain of sustainable business practices for entrepreneurial firms in emerging countries, (2) identify important terms in the various dimensions of sustainability in business and (3) identify the important practices and prioritize the practices.Design/methodology/approachThis study has adopted a unique methodology that combines state-of-art scientometric analysis with the fuzzy nominal group technique (NGT) and fuzzy decision-making trial and evaluation laboratory (DEMATEL). Results obtained from the co-occurrence analysis in scientometrics were further mapped through NGT to obtain the list of the most important topics in the domain. The factors affecting sustainable business practices obtained through topic mapping were analyzed through fuzzy DEMATEL to obtain the cause-and-effect relation of variables.FindingsThe scale of firms, leadership, uncertainty, gender, country/location, education and tourism were found to be the factors affecting the sustainable business practices of entrepreneurial firms. The sustainable business practices for entrepreneurial firms were (1) innovation, (2) resilience, (3) policy, (4) business ethics and virtue ethics, (5) business model, (6) upcycling and value creation, (7) collaboration and (8) triple bottom line.Practical implicationsPolicymakers in entrepreneurial firms, as well as other organizations, can implement the identified sustainable business practices to obtain optimum results and smooth functioning of the companies. The research framework obtained can be tested using exploratory methods.Originality/valueVery few researchers have used the technique of scientometric analysis to identify the sustainable business practices of entrepreneurial firms, and to the best of the knowledge of the authors, no earlier researcher has attempted to use the technique of topic mapping, fuzzy NGT and fuzzy DEMATEL in combination.

Blockchain Integrated IoT for Food Supply Chain: A Grey Based Delphi-DEMATEL Approach

The Food Supply Chain (FSC) can be made more efficient, resilient, and transparent by implementing industry 4.0 technologies. In this context, blockchain and the Internet of Things (IoT) become a panacea for several FSC problems. As a result of FSC complexity and their specific needs, the adoption of Blockchain integrated IoT (B-IoT) in FSC is challenging, and further investigation is required. Therefore, this study aims to explore the Critical Success Factors (CSFs) for the adoption B-IoT in FSC. To achieve this objective, a literature review is conducted to identify the CSFs of B-IoT adoption and then a grey Delphi is conducted on finalised CSFs. Ten CSFs finalised that faceplate for the adoption of B-IoT in FSC. Further, these CSFs were analysed through a grey Decision-Making Trial and Evaluation Laboratory (DEMATEL) to determine the importance and causal relationships among them. A grey DEMATEL analysis also categorised these factors into influencing and influenced groups. The findings showed that “top management support”, “knowledge management”, “technology hardware readiness”, “skilled personnel”, and “high investment” were the influencing factors that needed to be addressed for the effective adoption of B-IoT. The FSC partners could benefit from the findings of this study by focusing on high-priority CSFs. The causal relationship among CSFs also helps the managers achieve optimal utilisation of resources. Further, this study encourages the FSC stakeholders to adopt the B-IoT in their supply chain to improve their performance.

Evaluation Cloud Model of Spontaneous Combustion Fire Risk in Coal Mines by Fusing Interval Gray Number and DEMATEL

Coal still occupies a key position in China’s energy consumption structure, and ensuring safe production in coal mines is a key focus for ensuring energy security. Spontaneous combustion fires in coal mines are a serious threat to the sustainability of safe production in coal mines. In order to prevent coal mine fire risk scientifically and effectively and to assess the level of disaster risk effectively and rationally, a study was conducted on the risk of spontaneous combustion fires in underground coal mines. An evaluation cloud model of spontaneous combustion fire risk in coal mines integrating the interval gray number with the Decision-Making Trial and Evaluation Laboratory (DEMATEL) was established. Seventeen representative risk evaluation indicators were selected, and a coal mine spontaneous combustion fire risk evaluation index system was constructed based on four aspects: personnel, machinery, environment, and management. The interval gray number theory was introduced to improve the classical DEMATEL analysis method, which fully expresses the expert empirical knowledge and solves the problem of ambiguity and randomness in the semantic expression of expert evaluation. The relative importance of each indicator was determined by analyzing the influence relationships between risk evaluation indicators through the improved DEMATEL. A cloud model capable of transforming quantitative descriptions and qualitative concepts was used for comprehensive evaluation of risk, and based on the results of DEMATEL analysis, a comprehensive evaluation cloud model of coal mine spontaneous combustion fire risk was formed. Finally, the validity and practicality of the model were verified by using a mine in Shenmu City, Shaanxi Province, China as an example. This study provides a powerful tool to prevent spontaneous combustion fires in coal mines and makes a positive contribution to the sustainable development of coal mine safety management.

Drivers of the Sustainable Development of Agro-industrial Parks: Evidence from Jiangsu Province, China

The agro-industrial park (AIP) is developing rapidly all over the world and their industrial ecological characteristics have extensively promoted the development of the agricultural industry. However, academia and industry still lack a complete evaluation system to guide the sustainable development of AIPs. This study constructs a sustainable development evaluation system of the AIP that includes four parts of economic, social, technical, and sustainable criteria. Then, a multi-criteria decision-making (MCDM) method is employed for quantitative analysis based on a primary survey dataset; that is, the decision-making trial and evaluation laboratory (DEMATEL). In addition, a secondary dataset of 153 national AIPs in China from 2012 to 2014 is taken as a case study. The results of the DEMATEL analysis reveal some interesting findings. First, economic criteria still play an essential role in the sustainable development of AIP, and it is affected by almost all causal factors, which in turn affect most of the influencing factors. Second, there is no significant causal relationship between the criteria criterion and other criteria. Last, the case study reveals that the level of sustainable development of AIP in economically developed areas is significantly higher than the national average. The results of this study can also provide managers and policy planners with support for the sustainable management of AIP.

Analysis of Factors Hindering the Dissemination of Medical Information Standards.

Many medical information standards are not widely used in Japan, and this hinders the promotion of the use of real-world data. However, the complex intertwining of many factors hindering the dissemination of medical information standards makes it difficult to solve this problem. This study analyzed and visualized relationships among factors that inhibit the dissemination of medical information standards. Five medical informatics experts affiliated with universities and hospitals were interviewed about the factors that hinder the dissemination of medical information standards in Japan. The presented factors were analyzed using the interpretive structural modeling (ISM) method and the decision-making trial and evaluation laboratory (DEMATEL) method. We found that “legislation” and “reliability” were important inhibiting factors for the dissemination of medical information standards in Japan. We also found a six-layered structure in which “reliability” was satisfied when “legislation” was in place and “expectations” and “personal information” were resolved. The DEMATEL analysis indicated the relationships and classifications of factors hindering the dissemination of medical information standards. Since the adoption of medical information standards does not directly lead to revenue for medical institutions, it is possible to meet the “expectation” of improving the quality of medical care by ensuring “legislation” and “reliability”, that is, ensuring the dependability of medical treatment. The results of this study visually show the structure of the factors and will help solve the problems that hinder the effective and efficient spread of standards. Solving these problems may support the efficient use of real-world data.

Modelling the factors in the adoption of artificial intelligence in Indian management institutes

PurposeThis study aims to examine which organisational and other factors can facilitate the adoption of artificial intelligence (AI) in Indian management institutes and their interrelationship.Design/methodology/approachTo determine the factors influencing AI adoption, a synthesis-based examination of the literature was used. The interpretative structural modelling (ISM) method is used to determine the most effective factors among the identified ones and the inter-relationship among the factors, while the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is used to analyse the cause-and-effect relationships among the factors in a quantitative manner. The approaches used in the analysis aid in understanding the relationship among the factors affecting AI adoption in management institutes of India.FindingsThis study concludes that leadership support plays the most significant role in the adoption of AI in Indian management institutes. The results from the DEMATEL analysis also confirmed the findings from the ISM and Matrice d’ Impacts croises- multiplication applique and classment (MICMAC) analyses. Remarkably, no linkage factor (unstable one) was reported in the research. Leadership support, technological context, financial consideration, organizational context and human resource readiness are reported as independent factors.Practical implicationsThis study provides a listing of the important factors affecting the adoption of AI in Indian management institutes with their structural relationships. The findings provide a deeper insight about AI adoption. The study's societal implications include the delivery of better outcomes by Indian management institutes.Originality/valueAccording to the authors, this study is a one-of-a-kind effort that involves the synthesis of several validated models and frameworks and uncovers the key elements and their connections in the adoption of AI in Indian management institutes.

Lean in industry 4.0 is accelerating manufacturing excellence – A DEMATEL analysis

PurposeThe purpose of this research paper is to study the digital accelerators in conjunction with lean manufacturing enablers in the technology driven Industry 4.0 (I4.0) and understand their interrelationship dynamics with a goal to accelerate the pace of manufacturing excellence.Design/methodology/approachLiterature review coupled with the focus group approach facilitated to cull the key accelerating enablers to lean in I4.0. Thereafter, application of the multi criteria decision making methodology–DEMATEL (Decision Making Trial and Evaluation Laboratory) was carried out for analysis.FindingsA total of 18 factors from the integration of lean in I4.0 were identified from the focus group approach. The analysis from DEMATEL approach reflected that big data analytics and technology driven talent were the two most important factors in the manufacturing excellence journey. Leadership standard work and continuous improvement culture were the two key cause category factors, while, just in time the critical effect category factor.Practical implicationsAnalysis from DEMATEL approach has provided useful insights to industry leaders with the details of the degree of importance and type of influencing factors. It has given them direction in areas of investment to face the challenges of smart factories of tomorrow for sustainability.Originality/valueApplication of DEMATEL approach for analyzing the dynamics of the 18 factors in the integrated lean systems in I4.0 for manufacturing excellence.

To select suitable supplier for complex equipment military-civilian collaborative design based on fuzzy preference information that from matching perspective

Combine complex equipment collaborative development in military-civilian integration context not only fulfils actual development requirement, but also beneficial to the national economy. Design procedure as first stage of complex equipment military-civilian collaborative development process, select suitable design supplier is significant to whole development process of complex equipment. In order to select suitable design supplier for complex equipment, two aspects done in this paper. One is comprehensive analysis of evaluated influencing factors that affect complex equipment military-civilian collaborative design process, corresponding evaluation indicator constructed and a combination of grey correlation, entropy, DEMATEL (Decision-making Trial and Evaluation Laboratory) and VIKOR analysis theory to obtain grey entropy-DEMATEL-VIKOR, then the combined method is utilized to acquire matching attributes for followed research content. Meanwhile, satisfaction degree for matching side obtained with the help of information aggregation based on power generalized Heronian mean which on the basis of fuzzy preference information. Then, through constructed matching model, suitable design supplier obtained. Finally, a corresponding illustrative example given.

Blockchain implementation for circular supply chain management: Evaluating critical success factors

Blockchain technology implementation in a circular supply chain management (CSCM) context is an emerging topic that involves complex processes and diverse goals. This study aims to develop a framework that describes the main phases of Blockchain-enabled CSCM and evaluates the critical success factors of Blockchain implementation for CSCM. Further, we employed a combined analytical hierarchy process (AHP) and decision-making trial and evaluation laboratory (DEMATEL) method to explore the priorities and relationships of success factors using evaluations from academic and professional experts. The outcome of the AHP analysis shows that the success factors related to technology, such as technical capability, technological maturity, and technological feasibility, play critical roles in CSCM. Furthermore, the DEMATEL analysis suggests that knowledge training and data security should be regarded as essential causal factors influencing other factors. The results provide a possible path for determining critical success factors and facilitating Blockchain-enabled CSCM.

Spatial-temporal energy poverty analysis of China from subnational perspective

Alleviating energy poverty is a significant issue in many countries, for which effective energy poverty measurement is the prerequisite. This paper seeks to make a comprehensive and systematic assessment of the energy poverty performance of 30 provinces in China for 11-year period (2007–2017) by emphasizing their spatial-temporal changes. The paper firstly constructed energy poverty measurement conceptual framework based on overviewing previous studies. Secondly, a technique based on the integrated fuzzy DEMATEL (Decision-Making Trial and Evaluation Laboratory) and Data Envelopment Analysis - Assurance Region (DEA-AR) for performance assessment was proposed. Then, the energy poverty performance was assessed, and clustering analysis was conducted to investigate the spatial-temporal changes of energy poverty in China. Finally, sensitivity analysis was applied for verifying the robustness of the proposed method. It is found that the energy poverty condition in China tends to be similar among most regions, but the gap between the best and worst performers gets wider. In addition, provinces with better economic conditions, have higher performance and are classified into the progressive group for alleviating energy poverty. On the contrary, provinces, whose economy lags, have regressed the most and are also the worst performers in reducing energy poverty. Thus, policies to improve household energy cleanability in high-income provinces and increase energy affordability in low-income regions would help reduce energy poverty in China.

Analysis of the socioeconomic barriers in implementing public health measures to contain COVID-19 transmission in Pakistan: a DELPHI–DEMATEL-based approach

PurposeThe present study aims to identify and evaluate the socioeconomic barriers to effective COVID-19 pandemic transmission control in Pakistan.Design/methodology/approachThe study identifies multiple socio-economic barriers through an extensive literature review. The preliminary analysis unveiled 15 socio-economic barriers. Nine experts were contacted to collect data and finalize the most prominent barriers to COVID-19 transmission control using the DELPHI method. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) method was used to process and interpret the data collected and a cause–effect relationship was established among the barriers.FindingsThe finalized barriers to effective COVID-19 pandemic transmission control were evaluated using DEMATEL which grouped criteria into two grouped criteria – cause and effect. The DEMATEL analysis shows that poor safety culture, lack of strategy and goal setting, lack of resources, late realization and recognition of the pandemic problem and lack of expertise and capacity in disaster and risk management fall into the cause group. These factors are critical as they directly affect the remaining barriers identified in the study.Originality/valueDespite the collective global efforts, the national economies have been struggling to completely control COVID-19 transmission control. Pakistan’s economy has been facing the third wave of the pandemic. It is mandatory to identify the barriers and evaluate them to develop a comprehensive strategy ensuring that there would be no fourth wave. The study identifies and evaluates the barriers to COVID-19 transmission control in Pakistan using the integrated DELPHI-DEMATEL framework. The findings would help the government, experts and strategists to develop a comprehensive disaster and risk management strategy.

An assessment of government measures in combatting COVID-19 using ISM and DEMATEL modelling

PurposeThe purpose of this paper is to evaluate the interplay of various measures used by different governments around the world in combatting COVID-19.Design/methodology/approachThe research uses the interpretative structural modelling (ISM) for assessing the powerful measures amongst the recognized ones, whereas to establish the cause-and-effect relations amongst the variables, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is used. Both approaches utilized in the study aid in the comprehension of the relationship amongst the assessed measures.FindingsAccording to the ISM model, international support measures have the most important role in reducing the risk of COVID-19. There has also been a suggestion of a relationship between economic and risk measures. Surprisingly, no linkage factor (unstable one) was reported in the research. The study indicates social welfare measures, R&D measures, centralized power and decentralized governance measures and universal healthcare measures as independent factors. The DEMATEL analysis reveals that the net causes are social welfare measures, centralized power and decentralized government, universal health coverage measure and R&D measures, while the net effects are economic measures, green recovery measures, risk measures and international support measures.Originality/valueThe study includes a list of numerous government measures deployed throughout the world to mitigate the risk of COVID-19, as well as the structural links amongst the identified government measures. The Matrice d'Impacts croises-multiplication applique and classment analysis can help the policymakers in understanding measures used in combatting COVID-19 based on their driving and dependence power. These insights may assist them in employing these measures for mitigating the risks associated with COVID-19 or any other similar pandemic situation in the future.

An integrated supply chain management system for end-of-life tires in China and its promotion barriers: A stakeholder perspective

End-of-life (EoL) tires have brought severe environmental issues in China while they have a high recovery value. Thus, the Chinese government has worked on establishing a comprehensive system to promote the utilization of EoL tires. However, barriers exist for the implementation of the system, and it is also unclear what all associated barriers are and which works are urgent and crucial. This paper first contributes to introducing an integrated supply chain management (ISCM) system considering the whole life cycle of EoL tires from a different stakeholders’ perspective. Thirteen barriers are identified along three supply chain stages (collection of EoL tires, treatment, and sales & use of “4R” (retreaded/recycled/recovery/reused) products), as well as life-cycle management coordination. Based on evaluations by five experts from two industry associations, two typical tire manufacturers, and one recycling enterprise, we apply the decision-making trial and evaluation laboratory (DEMATEL) method to examine the causal-effect relationships among all barriers. Different from previous findings of critical difficulties (uncertainty of EoL tire supply and lack of treatment technologies), our results from DEMATEL analysis show that it is urgent to develop unified standards for “4R” products in end markets and promote tax incentives policies. In the long term, a coordinating organization is needed to manage all related stakeholders. Developing statistical mechanisms for EoL tires (registration, statistics, and traceability) is both urgent and elementary. Our findings provide managerial implications for the Chinese government to effectively promote the utilization of EoL tires, which can also be diffused to other countries, especially emerging countries.

Modeling the lockdown relaxation protocols of the Philippine government in response to the COVID-19 pandemic: An intuitionistic fuzzy DEMATEL analysis

The COVID-19 pandemic, which started at Wuhan, has shut down world economies, prompting governments to impose drastic lockdown measures of the economy and the society. As these measures are exhausted, non-COVID-19 related issues such as those associated with the mental and physical well-being of people under lockdowns became an emerging concern. As these issues are evident, not to mention the economic downturn, governments are currently looking at designing lockdown relaxation efforts by simultaneously considering both public health and economic restart. Without documented experiences to rely on, governments are resorting to trial-and-error approach in creating a lockdown exit strategy while preventing succeeding waves of cases that may overwhelm healthcare facilities. Thus, this work pioneers the use of the decision-making trial and evaluation laboratory (DEMATEL) method with intuitionistic fuzzy (IF) sets along with the domain of public health and the emerging COVID-19 pandemic. The DEMATEL handles the intertwined causal relationships among guideline protocols for the relaxation strategy. The intuitionistic fuzzy set theory addresses the vagueness and uncertainty of human judgments in the context of the DEMATEL. A case study of the Philippine government response for the lockdown exit is presented to evaluate the applicability of the proposed method. Findings reveal that compliance of minimum public health standards, limited movement of persons, suspension of physical classes, the prohibition of mass gatherings, non-operation of category IV industries, and non-operation of hotels or similar establishments are the most crucial protocols for such strategy. These findings offer practical insights for the government to allocate resources and impose measures to ensure their implementation, as well as for developing mitigation efforts to cushion their socio-economic impacts. Policy insights and avenues for future works are also discussed.