Decision Making Trial And Evaluation Laboratory Model Research Articles

Research on the influence factors of sustainable development of plateau characteristic agriculture based on DEMATEL and AISM combined model.

Under the background of the continuous progress of China's agricultural reform, the development of characteristic agriculture is an important field of agricultural development in the country and even the world. Yunnan has unique advantages in geography, location, climate, and human resources, and has unique conditions for the development of agriculture with plateau characteristic. However, the sustainable development of agriculture with plateau characteristic is affected and restricted by many factors. How to promote the sustainable development of agriculture with plateau characteristic is an important research topic, and it is also the main purpose of this study. Therefore, through literature analysis and investigation, this study studies the advantages and disadvantages, development status, main problems, countermeasures and suggestions, macro development direction, and theoretical research methods of characteristic agriculture in the Yunnan plateau. This paper analyzes the advantages and disadvantages of the Decision-making Trial and Evaluation Laboratory (DEMATEL) and the Adversarial Interpretation Structure Modeling Method (AISM) and proposes to combine the two models to make up for each other and improve the accuracy of model analysis. On this basis, a set of identification and evaluation systems of factors affecting the sustainable development of agriculture with plateau characteristic is established, which can comprehensively and accurately identify and evaluate various influencing factors, and provide a scientific basis for the sustainable development of agriculture with plateau characteristic. Finally, combined with the relevant statistical data of Yunnan Province from 2009 to 2020 and many results calculated by the model, the factors affecting the sustainable development of agriculture with plateau characteristic were comprehensively analyzed. The results show that transportation, environment, and insurance support factors are the root factors that affect the sustainable development of agriculture with plateau characteristic, while the regional economy, scientific and technological support, and the development of agricultural enterprises are of high importance. Financial support, the level of agricultural mechanization, the quality of labor, and other factors can not be ignored. Finally, according to the results of the analysis, the corresponding policy recommendations are put forward to provide a reference for the sustainable development of plateau characteristic agriculture in Yunnan Province.

Prioritizing competencies for soldier's mental resilience: an application of integrative fuzzy-trapezoidal decision-making trial and evaluation laboratory in updating training program.

The development of resilience is of the utmost importance in military training due to the demanding and high-stress nature of combat situations. Although there have been numerous studies on resilience competencies in the military, there is a research gap when it comes to identifying the most essential competencies that should be prioritized in training programs, particularly within compressed timeframes. With the current geopolitical landscape and ongoing military conflicts in Europe, it is necessary to expedite training of soldiers, including resilience training, without compromising the effectiveness of the program. This study aims to address this research gap by using a reductionist approach to resilience training and identifying the critical competencies that senior soldiers need to be trained to coach younger soldiers to maintain psychological strength during deployment. By filling this research gap, the study will contribute to the development of more efficient and targeted resilience training programs that optimize the ability of soldiers to adapt and excel in challenging military environments. To address the issue, this study assessed the competencies comprising the master resilience training (MRT) program, widely recognized as one of the most effective military resilience training programs. Two groups of military experts, totaling 16 individuals, were involved in the evaluation process, representing two military contexts. The first group consisted of Ukrainian military experts whose experiences primarily focused on defending their own country's territory. The second group comprised Lithuanian military experts who had greater expertise in conducting military missions abroad. The assessment of resilience competencies was carried out using a deep analysis approach through the application of effective multi-criteria decision making (MCDM). Specifically, the decision-making trial and evaluation laboratory (DEMATEL) method was used, which is a significant multicriteria technique used to determine relationships among criteria and assign weight coefficients. In this study, the DEMATEL model was extended using trapezoidal fuzzy numbers (TrFN-DEMATEL) to accommodate decision-making under uncertainty conditions. The research findings highlight the critical importance of three core resilience competencies: self-regulation, mental agility and strength of character. The importance of each competency varies depending on the specific military context. When defending one's own country's territory, strength of character emerges as the key factor in enhancing soldiers' mental resilience. Conversely, during military operations abroad, self-regulation is the primary factor that promotes psychological resilience. Furthermore, the results show that these three primary competencies form a 'cause group' that influences other competencies through a cause-and-effect dependency. Based on the findings, the theoretical conclusion is drawn that the importance of resilience competencies is contextually differentiated. Furthermore, each resilience competency is associated with a set of causes or effects. These are valuable insights for improving resilience competency training programs.

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.

A DEMATEL-based approach of multi-criteria evaluation for urban fire and emergency facilities

With the increasing complexity of rapidly growing urban environments and the interactions of humans and socioeconomic and political systems, the global urgency for applying sustainable risk management planning strategies, comprehensively for urban fire risk reduction activities, becomes increasingly evident in most fire-prone megacities worldwide such as Istanbul. The current research aims to examine the complex interrelationships and levels of influence among the criteria previously determined for optimally selecting new urban infrastructure for fire and emergency services in Istanbul as part of the fire risk mitigation planning efforts applying the multi-criteria decision analysis method of the Decision-Making Trial and Evaluation Laboratory (DEMATEL). Useful insights were generated from the study by constructing an intelligible structural model visually in the form of a digraph involving analysis of causal relationships among criteria and their directional influences, as well as corresponding degrees of strength. The findings reveal that high population density is the most critical criterion followed by the density of hazardous materials criterion in effectively planning new urban facilities for fire and emergency services, thus significantly influencing and impacting all the other criteria, while the distance-to-earthquake risk criterion does not influence any other criteria and consequently is not essential in the planning procedure. The DEMATEL model results were validated in terms of levels of criteria significance using previous studies and shown to be in high correlation. In this regard, these contextual relationships established would contribute toward an integrated fire risk mitigation planning policy formulation in urban environments through the engagement of all decision-makers across various backgrounds and disciplines such as urban and city planners, engineers, emergency and risk managers and administrators, socioeconomic and environmental experts, fire service industry practitioners, and local community leaders.

A corporate risk assessment and reporting model in emerging economies

PurposeThe growing business complexity has caused many risks (e.g. operational, financial, reputational, cybersecurity, regulatory and compliance) that threaten companies' sustainability and have received attention from regulators, investors, and businesses. The authors present a model for assessing and reporting corporate risk by examining the indicators underlying corporate risk reporting.Design/methodology/approachA thorough review of the literature and semi-structured interviews with experts were conducted and the fuzzy Delphi technique was used to obtain consensus and screening of risks. The relationships between these risk indicators were recognized, weighted and prioritized by employing a hybrid Decision Making Trial and Evaluation Laboratory Model (DEMATEL) method integrated with Analytic Network Process (ANP) (DEMATEL-ANP [DANP]) approach. Finally, using the Iranian setting of corporate risk reporting, a model was developed to calculate the risk-reporting scores.FindingsThe results indicate that risk disclosure quality is more important than risk disclosures' textual properties and quantity. According to the experts, reporting the key risks that the company faces, management's approach to dealing with these risks and quantifying their impact are more important than the other indicators. The results also show that risk reporting in Iran lacks quantitative and specific information, and most risk disclosures are sticky.Research limitations/implicationsThe data have been prepared and analyzed according to the unique Iranian reporting environment, which should be considered when interpreting the results.Practical implicationsThe results of this research can be used by the regulators of the Stock Exchange Organizations (SEO) to evaluate corporate risk reports and rank companies. Results are also relevant to investors and policymakers to identify companies with poor risk disclosure and to take necessary measures to improve their reporting practices.Social implicationsThis paper contributes to the social and governance literature by presenting the importance of risk reporting in corporate disclosures.Originality/valueThe unique Iranian setting of corporate risk reporting furthers the understanding of risk reporting and thus provides education, policy, practice and research implications for other emerging economies like Iran. Many prior studies focus mainly on the quality of risk disclosure, and other aspects of corporate risk disclosure presented in the study have remained largely overlooked. The corporate risk reporting attributes identified in the study are relevant to the rise of non-financial risks, the textual and qualitative nature of risk reporting and textual risk disclosures.

Green port management practices for sustainable port operations: a multi method study of Asian ports

ABSTRACT Ports pose a substantial portion of marine emissions, causing significant health and environmental risks. Providing profitable services in compliance with environmental regulations has become a significant challenge for port authorities. The idea of green port management practices (GPMP) has recently grown as an innovative method for balancing port economic growth with ecological issues. The study systematically reviewed the literature regarding the green port management model and identified an integrated set of drivers of GPMP for sustainable port operations. Besides, an empirical multiple case study methodology was adopted where twelve major Asian ports from developing and developed countries were investigated through a performance-based scoring measurement method based on their GPMP drivers’ implementation status. Finally, the study employed a quantitative fuzzy decision-making trial and evaluation laboratory model (DEMATEL) to examine the interdependent cause-and-effect connections among the different green port drivers. The study reveals that Singapore is rated highest in green port implementation practices while the Port of Male (Maldives) was classified lowest among 12 Asian ports. Besides, Pollution Control Measures are the most significant driver having the highest influence on all drivers. Automation and digitalization have the most significant causal influence on all the drivers of GPMP, followed by environmental incentives and penalty pricing.

Adaptability evaluation of conceptual design for smart product-service system: An integrated rough DEMATEL and Bayesian network model

Smart product service system (PSS) design evaluation plays a crucial role in the early design stage of Smart PSS development. It aims at considering the user's value proposition for Smart PSS in the dimensions of intelligence, sustainability, and society, while also ranking Smart PSS to support delivery risk management under uncertainty. However, related Smart PSS evaluation models advocate the use of multi-criteria decision models for obtaining the intrinsic value of PSS by ignoring the influence of the causality of criteria on Smart PSS design, which results in an unstable evaluation process. Additionally, the adaptiveness of Smart PSS has not been thoroughly explored, and determining the adoption intentions of Smart PSS can be challenging. To fill these gaps, a Smart PSS evaluation model that integrates a rough decision-making trial and evaluation laboratory (DEMATEL) and a Bayesian network (BN) is proposed to support probabilistic reasoning for Smart PSS adaptiveness and reduce the risk of Smart PSS development. First, a set of 17 evaluation criteria is identified, and their causal relationships and weights of the criteria were identified using a rough DEMATEL under uncertainty. Second, a BN-based reasoning model for Smart PSS criteria is developed to evaluate the adaptability of smart PSS by constructing a conditional probability calculation model based on criterion weights. Finally, a multifunctional smart cooking center (MFSCC) case study is presented to demonstrate the applicability of the proposed approach. The belief propagation analysis results revealed the key criteria affecting the MFSCC service system development and provided design strategies to improve the adaptiveness of the Smart PSS.

Selection of suitable biomass conservation process techniques: a versatile approach to normal wiggly interval-valued hesitant fuzzy set using multi-criteria decision making

A country that relies on developing industrialization and GDP requires a lot of energy. Biomass is emerging as one of the possible renewable energy resources that may be used to generate energy. Through the proper channels, such as chemical, biochemical, and thermochemical processes, it can be turned into electricity. In the context of India, the potential sources of biomass can be broken down into agricultural waste, tanning waste, sewage, vegetable waste, food, meat waste, and liquor waste. Each form of biomass energy so extracted has advantages and downsides, so determining which one is best is crucial to reaping the most benefits. The selection of biomass conversion methods is especially significant since it requires a careful study of multiple factors, which can be aided by fuzzy multi-criteria decision-making (MCDM) models. This paper proposes the normal wiggly interval-valued hesitant fuzzy-based decision-making trial and evaluation laboratory model (DEMATEL) and the Preference Ranking Organization METHod for Enrichment of Evaluations II (PROMETHEE) for assessing the problem of determining a workable biomass production technique. The proposed framework is used to assess the production processes under consideration based on parameters such as fuel cost, technical cost, environmental safety, and CO_2 emission levels. Bioethanol has been developed as a viable industrial option due to its low carbon footprint and environmental viability. Furthermore, the superiority of the suggested model is demonstrated by comparing the results to other current methodologies. According to comparative study, the suggested framework might be developed to handle complex scenarios with many variables.

Analyzing the Challenges to Circular Economy in Indian Fashion Industry

The fashion industry, during production and post-consumption, has major adverse environmental impacts. With the recent circular economy (CE) practices initiative, discarded fashion materials are reused to recover value from the waste. However, the CE practices initiative have not been well-received by society. The role of CE practices is very crucial in fashion industry as it helps in lowering the environmental burden caused by the discarded fashion materials, which in turn help to achieve the sustainable development goals (SDG). This study aims to collect and evaluate the challenges restricting the preference for CE practices initiative in Indian fashion industry. Based on literature review and inputs from the fashion industry experts, the study identified twenty-one challenges, in seven categories (Industrial management, Labour, Material, Regulations, Knowledge, Collaboration, and Infrastructure). An integrated multi-criteria decision-making (MCDM) approach comprising fuzzy Decision-Making Trial and Evaluation Laboratory Model (DEMATEL), Analytical Network Process (ANP), and Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) is used to evaluate the challenges. The outcome of the study identifies costly raw materials, absence of certifications, problem in collection and separation, weak technical know-how, and absence of shared vision as the top five challenges to CE practices in Indian fashion industry. Further, the revelation of the causal interrelationship among the challenges helps the industrial management in taking appropriate steps to avert the challenges.

Sustainable competitiveness practices of SMEs: a strategic framework using integrated DEMATEL-NK model

PurposeIt is critical for small and medium-scale enterprises (SMEs) to review and monitor sustainability performance indicators across three dimensions: economic, environmental and social to attain long-term competitiveness. SMEs lack a holistic perspective on sustainability; they are frequently hindered from contemplating environmentally favorable investments beyond what is legally needed. The purpose of this paper is to present a joint Decision-making trial and Evaluation Laboratory (DEMATEL) and NK methodology for developing a process model for introducing and implementing sustainable competitiveness practices for SMEs.Design/methodology/approachThis study addresses the issue by adopting a sustainable competitiveness practices framework and applying a novel method that integrates DEMATEL and NK model for evaluating and developing the implementation path model for Indian manufacturing SMEs.FindingsThis paper also demonstrates that not only the relational practice itself but also the order in which the relational practices are implemented can be related to performance. According to the authors' preliminary findings, organizations in this study should first implement a social dimension, which includes sustainable leadership, knowledge sharing, etc., then an economic dimension like quality, sustainable innovations, etc., and finally environmental dimensions like green marketing, solid waste reduction, etc., with their management for competitiveness.Research limitations/implicationsThese findings offer some preliminary information as well as advice for managers and policymakers looking to integrate sustainable efforts.Practical implicationsThis study asserts that not only the interdependent practice but also the sequence of implementation is important and can relate to the performance. The path result shows that the organization develops first sustainable design and product development (economic), sustainable leadership (social) and solid waste reduction (environmental) practices.Originality/valueThere is no such study that develops a process model for introducing and implementing sustainable competitiveness of SMEs which assesses and analyzes the interdependencies across relational behaviors, to the best of authors’ knowledge. The novelty of this work lies in integrating DEMATEL-NK model approach.

Evaluation on service quality in institutional pensions based on a novel hierarchical DEMATEL method for PLTSs

In recent years, to address the continued aging of China’s population, the Chinese government has focused on the issue of pensions through a series of pension policies. The traditional system of institutional pensions is facing serious challenges, with a variety of novel pension modes placing them under enormous pressure. Furthermore, the development of institutional pensions has been restricted by many factors, such as long construction cycles and high fees, meaning that this traditional system no longer meets the pension needs of the elderly. Improving the service quality of institutional pensions is inevitable for future progress. Thus, identifying the key factors that influence the service quality of institutional pensions, and understanding the relationships between these factors, is hugely significant. Furthermore, traditional decision-making trial and evaluation laboratory (DEMATEL) method can not solve this problem because the number of factors is too large. To address these issues, we establish an evaluation system for Chinese pension institutions, and propose a hierarchical DEMATEL model based on probabilistic linguistic term sets (PLTSs), which can help decision makers to find the key factors influencing service quality in institutional pensions and deal with the evaluation problem with a large number of criteria. The proposed hierarchical DEMATEL model based on PLTSs fully reflects experts’ preferences and evaluation information, and is able to identify the directions in which China’s pension institutions should improve their quality of service. In addition, we use the best-worst method (BWM) to calculate the importance values of each subsystem, which makes the cause-effect relationship between subsystems more reasonable than the traditional DEMATEL method. Finally, we apply our method to evaluate nursing homes in Zhenjiang, Jiangsu province and propose some managerial implications.

Predicting and managing megaproject gray rhino risks with IF-ANP and DEMATEL based on panel data

The use of the combination of color and animal as a metaphor for the risk is a common and vivid practice, such as white elephant risk, white rabbit risk, golden monkey risk, grey rhino risk, black swan risk, and so on. Black swan risk and grey rhino risk are a set of relative concepts. The black swan is used as a metaphor for rare, unpredictable risks. The grey rhino is used as a metaphor for common but often overlooked risks. Statistics show that most megaproject failures are caused by common gray rhino risks rather than rare black swan risks. Existing studies disregard the interactions among risks, which results in managers being unable to effectively avoid the recurrence of common risks. Therefore, this study applies a decision-making trial and evaluation laboratory model (DEMATEL) research method to rank risks by the strength of the interactions among the risks. It can provide a new perspective for decision-makers when they develop a defense plan for megaproject risks. Also, a megaproject is a kind of complex nonlinear system. This results in serious subjectivity when experts directly assign quantitative values to the relations among risks. To reduce the effect of the nonlinearity, this work created an interference fuzzy analytical network process (IF-ANP). In our experiments, this method effectively reduced the fluctuation of the evaluation values of each expert and improved research accuracy. Empirical research was done to assess common risks in the Chengdu–Chongqing Middle Line High-speed Railway megaproject (CMLHRm) by panel data that was collected from 1.12.2020 to 6.30.2022. The result of the case study shows that there are obvious interactions among risks and these interactions are dynamic. Through the combination method proposed in this work, experts can make effective risk response suggestions in time at different stages of the megaproject.

An Evaluation of the Coordinated Development of Coastal Zone Systems: A Case Study of China’s Yellow Sea Coast

The coastal zone is an area of transition between land and sea, containing rich resources, and it is an important spatial unit where humans engage in production and livelihood. However, in the process of benefiting from the coastal zone, people have neglected the coordinated development of the ecological environment, the economy, and society. To investigate the coordinated development mechanisms of coastal zone systems influenced by human activities, the DEMATEL (Decision making trial and evaluation laboratory) model was applied to identify the key factors influencing a complex coastal zone system. The results were used to construct an indicator system to evaluate the developmental stages of three coastal zone subsystems (ecological environment (EE), society (SOC), and economy (ECO)). The developmental levels of these subsystems over the past ten years were evaluated in five cities along the Yellow Sea coast of China, and the degrees of coupling and coordination among the subsystems were calculated using the coupling coordination degree model. The results showed that during the past decade, the developmental levels of the EE, SOC, and ECO subsystems increased in all five coastal regions, except for Yancheng, where there was a small decrease in the EE level; the coupling degrees of all five regions were high, and the interactions between the EE, SOC, and ECO were very close; the coordination degree was relatively poor. The mean values of Qingdao and Nantong were at an ‘Intermediate coordination level’, and the other three cities were at the ‘Primary coordination’ or ‘Barely coordination level’. Three types of interactions between the subsystems emerged: (1) three subsystems have benign interactions and collaboration with each other; (2) the EE, SOC, and ECO compete with each other and have fluctuating upward development; (3) there is a focus on development in the SOC and ECO, and there is a neglect of environmental protection. Based on the development trends of the subsystems and the coupling and coordination laws, some suggestions were proposed.

How to choose the right influencer for a marketing strategy

This paper attempts to build a new model for deciding which social media influencers (SMIs) are suitable for the marketing strategies of businesses. How to choose social media influencers is an unanswered question in the literature, and this study attempts to fill this gap. The study employs a Multiple-Criteria Decision-Making (MCDM) method, the fuzzy decision-making trial and evaluation laboratory model (DEMATEL), to determine the relevance of criteria constructed. It observed SMIs on Instagram and reviewed insights from the literature. Five criteria are proposed for selecting the correct influencers: 1) positioning; 2) target; 3) budget; 4) past campaigns; and 5) the number of followers. Businesses were asked to evaluate these criteria according to their experience with using SMIs. The results suggest that the most important criterion is ‘target’, whereas ‘past campaigns’ is the least influential.

A decision support model for estimating participation-oriented designs of crowdsourcing platforms based on quality function deployment

The designs presented in crowdsourcing platforms for supporting, facilitating, and regulating solvers’ behaviors have significantly effect on solvers’ decision to participate. To estimate those important designs, referred to as participation-oriented designs in this study, a decision support model is developed based on quality function deployment (QFD). This model connects participation-oriented designs to solvers’ motives through the matched incentives, ensuring the estimated designs could activate solvers’ motives most. Specifically, the relations among these three aspects are represented by two house of quality (HoQ) models in which one links solver motives and incentives and the other connects the incentives and participation-oriented designs. Moreover, a combination of the fuzzy Delphi method (FDM), fuzzy Best-Worst method (BWM), and fuzzy Decision Making Trial and Evaluation Laboratory Model (DEMATEL) is developed to handle information in these two HoQ models. Therein, the FDM is employed to screen and map solver motives, incentives, and participation-oriented designs. The fuzzy BWM is used to determine the relationship weights between solver motives and incentives and incentives and participation-oriented designs respectively. The fuzzy DEMATEL is employed to describe and calculate the inner dependencies of incentives and participation-oriented designs respectively. A case of the crowdsourcing platforms for graphic design contests is presented to demonstrate the effectiveness and practicability of the proposed model.

Prioritizing Scheduling Parameters in the Automotive Industry Using Fuzzy TOPSIS-DEMATEL Model

The Automotive industry is one of the biggest emerging sectors in terms of revenue. Every automotive industry has an indispensable need for optimum manufacturing scheduling systems for generating good revenues and profits. This need can be pulled off by identifying and prioritizing the scheduling parameters. Multi-criteria decision making (MCDM) is one of the best techniques of operation research in selecting the best parameters or factors among the various alternatives. This study includes the identification and prioritization of the various important scheduling parameters (SPs) in the Indian automotive industry. The twelve scheduling parameters have been identified in this study and these parameters are prioritized by the fuzzy- Technique for order preference by similarity to ideal solution (TOPSIS) and Decision Making Trial and Evaluation Laboratory Model (DEMATEL). The expert’s views are gathered from the five automobile industries. Makespan, energy consumption, due date, and travel time are the crucial parameters obtained using Fuzzy TOPSIS. The least important parameters obtained using Fuzzy TOPSIS are work in process, flow time, and release date. The most influential parameters identified using the DEMATEL method are completion time and processing time. This study is valuable for every industry and research organization in the field of the automobile industry.

Fuzzy Concept Evaluation Based on Prospect Theory and Heterogeneous Evaluation Information

Abstract Concept evaluation is the core stage of new product development and has a significant impact on the downstream process of product development. Because of the uncertainty and ambiguity of early design information, the concept evaluation process not only relies on the semantic terms of decision makers (DMs) but also includes uncertain criteria values (such as crisp numbers and interval numbers). In addition, DMs will have psychological preference errors when evaluating concepts owing to the risks taken in the evaluation. To address these drawbacks, a fuzzy concept evaluation approach based on prospect theory and heterogeneous evaluation information is proposed. Initially, based on the definition of intuitionistic fuzzy numbers (IFNs), a numerical model is developed to unify the representation of crisp numbers, interval numbers, and fuzzy numbers, and a normalized decision matrix is constructed. Second, a weight distribution method of DMs is proposed, which introduces hesitation and similarity, and the weighted intuitionistic fuzzy evaluation information is transformed into interval IFNs. Third, the weight of the evaluation criteria is determined using the decision-making trial and evaluation laboratory model (DEMATEL), and an evaluation information correction model based on the prospect theory is established to select the optimal concepts. Finally, the feasibility of the proposed approach is demonstrated using a bar-peeling machine, and a comparison and sensitivity analysis is conducted to verify the robustness of the decision results.

A hybrid multiple-criteria decision portfolio with the resource constraints model of a smart healthcare management system for public medical centers

A Smart Healthcare Management System (SHMS) is an intelligent technology integration practice for public medical centers. During the implementation of the SHMS, information on strategy and decision-making problems play an important role in smart hospital development, which directly affects the effective workflow of the hospital operation and the service quality of patient care. Existing literature has explored the main factors for evaluation the SHMS, but a qualitative and quantitative analysis is rarely mentioned. To address the research gap, this study proposes a hybrid exploratory three-phased Multi-criteria Decision-making (MCDM) model that combines the Decision-Making Trial and Evaluation Laboratory Model (DEMATEL) approach, the Analytic Network Process (ANP), and Zero-One Goal Programming (ZOGP) for evaluating SHMS portfolios in a resource-limited environment. The results indicate that the Financial Subsidy Policy is the most important determinant for SHMS development, while the Medical Data Informational System (MDIS) and Medical Device and Drug Management System (MDMS) are the optimal SHMS portfolios that satisfy the goal of strategy weights and limited resources. The proposed hybrid decision model can improve the reliability of SHMS portfolios.

Key barriers to the commercial use of the Northern Sea Route: View from China with a fuzzy DEMATEL approach

The unprecedented reduction in the Arctic sea ice may lead to shipping shortcuts through the Arctic region. Among these, the Northern Sea Route (NSR) linking Europe and Asia has received wide attention because of its potential to save time and energy compared with the conventional southerly transit. However, limited by various factors, the NSR has not witnessed sustained commercial operation, that is, no shipping companies have started regular services there. By reviewing existing literature, we classify 10 factors that have influenced NSR development into four categories: natural conditions, commercial costs, service support, and political considerations. We evaluate the interdependent relationships among these factors through a fuzzy decision-making trial and evaluation laboratory model (DEMATEL), an effective approach in identifying the cause–effect chain in an uncertain and complex decision-making environment. The most critical elements restricting Arctic NSR development include extreme climate, political considerations, and sea ice condition based on expert inputs. This study discusses relations among these factors as well as their policy implications, which could contribute to the decision making of shipping companies and policy focus of the government.

Improving bicycle sharing operations: A multi-criteria decision-making approach

Bicycle sharing is quickly becoming popular because it is environmentally friendly and offers convenience to customers. Determining how to improve the service level and customer satisfaction are the keys to a successful bicycle sharing business in today’s fiercely competitive market and are also the keys to achieving a sustainable operation. In this paper, following a hierarchical structure, five main factors related to the bicycle sharing operations are identified: (1) convenience and flexibility, (2) operation service, (3) economic cost, (4) design and layout and (5) management specification. Eighteen sub factors are then derived. To determine the significant factors affecting bicycle sharing operations, the Multi-Criteria Decision-Making (MCDM) approach based on Interval Type-2 Fuzzy Sets (IT2FSs), Decision Making Trial and Evaluation Laboratory Model (DEMATEL) and the Analytic Network Process (ANP) are proposed. First, IT2FSs and fuzzy DEMATEL are integrated to analyze the complex relationships among the various factors. DEMATEL is then integrated with ANP to rank the importance of these factors. Results are compared with those of other state-of-the-art MCDM methods. It is concluded that convenience and flexibility, rationality of the layout, and economic cost are the three most important factors impacting the bicycle sharing business model. Based on the findings, theoretical guidance for the development of bicycle sharing operations is provided.