Influential Network Relation Map Research Articles

ASSESSING THE DIFFUSION OF FINTECH INNOVATION IN FINANCIAL INDUSTRY: USING THE ROUGH MCDM MODEL

We develop a conceptual structure to explore how financial technology (FinTech) innovation is being implemented to deal with vague, inconsistent and ambiguous knowledge in actual world. The structure of this study is built upon the technology, organization, environment (TOE) context, which one uses the concept of multi-criteria estimation to measure the significance of FinTech innovation. We develop an integrated MCDM (multiple criteria decision-making) model through rough set theory help administrators obtain a strategic influence relation map for enhancing performance approaching towards the aspiration value. This model involves three steps: primary, we apply this rough number to define group views which reflect upon experts’ real experiences; second, we use the rough DEMATEL-based ANP-(RDANP) to acquire the rough influential weights and rough influential network relationship map (RINRM) based on this TOE structure and its corresponding attributes; finally, we utilize the rough modified VIKOR with the influence to analyze the gap between the performance value and the aspirated level. The empirical case was originated from financial industry in Taiwan. According to the weighting results the expected benefits, technology integration, and competitive pressure were the most important criteria. Our results also illustrate how FinTech innovation can be used for promoting financial services.

Evaluating the Interrelationships of Industrial 5.0 Development Factors Using an Integration Approach of Fermatean Fuzzy Logic

The maturation of the Industry 4.0 concept has brought numerous benefits to human society. However, it is not without its challenges, including neglect of worker welfare, vulnerability of global supply chains, and environmental degradation. To enhance the adaptability of the Industry 4.0 concept, Industry 5.0 has been developed. As of now, the practical implementation of Industry 5.0 has not yet been fully realized. This paper presents a novel conceptual framwork to analyze and evaluate the complex interrelationships of development factors in Industrial 5.0. Through extensive literature review and prolonged interviews with experts, three critical dimensions and their 18 key factors for the development of Industry 5.0 have been identified. Herein, a combination of Fermatean Fuzzy sets (FFs) and Decision-Making Trial and Evaluation Laboratory (DEMATEL) has been employed to discern the interrelationships among these factors, and an Influential Network Relationship Map (INRM) has been constructed to aid decision-makers in formulating improvement strategies. The results indicate that “Sustainable Development” is the most influential dimension, with factors “Renewable Energy,” “Data-Driven Analysis Technologies,” and “Distributed Control” emerging as the most significant factors within their respective dimensions.

Exploring consumer purchase intention in cross-boundary retail alliances with gamified OMO virtual-physical fusion services

The emergence of digitalisation and COVID-19 have induced notable lifestyle changes. For example, contactless online-offline engagement remains popular even after the reopening of physical venues. This demand has led organisations to advance their technologies via gamification and improve customer experiences and involvement. Hence, this study examined how retail store cross-boundary alliances and gamified marketing methods impact the implementation of online-merge-offline (OMO) virtual-physical fusion services from customers' viewpoints. An evaluation model was developed by integrating Chou's eight-core Octalysis framework for gamification and decision-making approaches. Furthermore, an online survey performed in Taiwan generated 550 valid responses. The empirical data were subsequently analysed with DEMATEL to determine the interconnections among evaluation indicators and construct an influential network relation map (INRM). The indicators' influence weights were ascertained via DANP. Unpredictability (Unp) was ranked first, followed by avoidance (Avo), epic meaning (Epi), scarcity (Sca), empowerment (Emp), social influence (Soc), ownership (Own), and accomplishment (Acc). Both Acc and Unp were the most and least significant factors, respectively. Optimal gamified marketing approaches positively influenced customers' repurchase intentions, shopping experiences, and retail loyalty. Overall, retail stores seeking to apply cross-boundary alliances and gamified marketing methods can benefit from the empirical outcomes to incorporate efficient OMO virtual-physical fusion services.

Exploring the Mutual Influence Relationships of International Airport Resilience Factors from the Perspective of Aviation Safety: Using Fermatean Fuzzy DEMATEL Approach

International airports are responding to the threat of climate change and various man-made hazards by proposing impact protection measures. Airport managers and risk controllers should develop a comprehensive risk assessment model to measure the mutual influence relationships of resilience factors. In this paper, the problem of treating resilience factors as independent ones in previous studies is overcome. In this study, we not only develop a framework for assessing resilience factors in international airports based on an aviation safety perspective, but also develop the Fermatean fuzzy decision-making trial and evaluation laboratory (FF-DEMATEL) to identify the mutual influence relationships of resilience factors. Fermatean fuzzy sets are incorporated in DEMATEL to reflect information incompleteness and uncertainty. The critical resilience factors of international airports were identified through real-case analysis. In terms of importance, the results show that rescue capability is a core capability that is important for airport resilience. In addition, “security management system (SeMS) integrity”, “education and training of ground staff on airport safety awareness”, “first aid mechanism for the injured”, and “adequate maintenance equipment for rapid restoration tasks” are identified as key factors that are given more weights. On the other hand, in terms of influence strength, the detection capability has the highest total influence and significantly influenced the other resilience capabilities. Finally, the influential network relation map (INRM) is utilized to assist decisionmakers in swiftly comprehending the impact of factors and formulating viable strategies to enhance airport resilience. This enables airport managers and risk controllers to make informed decisions and allocate resources efficiently.

Consumers' switching intention towards E-commerce platforms’ store-to-store pickup services: The application of the extended PPM model

The knowledge of the preference of innovative service consumers is crucial for e-commerce platforms to boost profit, gain a competitive advantage, and achieve remarkable growth. In this research, the consumer's viewpoint was applied. Furthermore, the extended Push-Pull-Mooring (PPM) model was integrated into the multi-attribute decision-making (MADM) approach to investigate the elements impacting the consumers' attempt of shifting to the store-to-store pickup service developed by e-commerce platforms. Besides, the development of the Decision-Making Trial and Evaluation Laboratory (DEMATEL) was for the investigation into the reciprocal effects of evaluation dimensions and factors and the development of an influential network relation map (NRM). The DEMATEL-based Analytic Network Process (DANP) was used to calculate the influential weights of these dimensions and factors. It could be seen from the NRM that the first dimension that required improvement and adjustment ought to begin with a push and subsequently a pull, mooring, switching intentions, and inertia. The influential weights from the DANP highlighted inertia as the most impactful dimension, with mooring coming in second. Meanwhile, push held the lowest significance. The next discussion focuses on the theoretical, managerial and practical implications.

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.

Analyzing Interrelationships and Prioritizing Performance Indicators in Global Product Development: Application in the Chinese Renewable Energy Sector

Today’s global business landscape and intense market competition have heightened the significance of global product development (GPD) practices, making it necessary for organizations to evaluate GPD projects for sustained success. Existing research has primarily focused on independent and tangible performance metrics, neglecting their interdependencies and intangible nature in real-world scenarios. To address this gap, this study seeks to enhance the understanding of GPD performance by establishing a more sophisticated assessment approach. A hybrid decision-making trial and evaluation laboratory (DEMATEL) and analytical network process (ANP) method, known as DANP, was employed to determine the importance of evaluation metrics and their relationships. This research stands out by integrating financial, quality, time, environmental, and capability dimensions, along with their respective indicators, and presenting their interrelationships and priority weights for evaluating GPD projects. The proposed framework was validated through an in-depth case investigation conducted with a Chinese sustainable energy solutions company, involving extensive discussions with decision-makers. The results indicate that technological, innovation, and environmental indicators are the most critical metrics. The influential network relation map (INRM) derived from these findings offers practical recommendations to enhance GPD project performance, catering to policymakers and researchers in both managerial and theoretical contexts.

Exploring the critical factors influencing the outlying island talent recruitment and selection evaluation model: Empirical evidence from Penghu, Taiwan

The declining birth rate, population ageing and the outbound migration of young people in recent years have created obstacles for local companies in recruiting skilled personnel. Similar factors have also affected recruitment in the outlying island of Penghu, Taiwan. Multiple-attribute decision-making (MADM) techniques for evaluation model development were incorporated in the present research to investigate the key determinants of talent recruitment by the coffee house operators in the outlying island of Penghu. The decision-making trial and evaluation laboratory (DEMATEL) approach was first implemented to (i) examine the extent of mutual impact between evaluation predictors and (ii) develop an influential network relation map (NRM) for indicator and sub-indicator assessments. Subsequently, the DEMATEL-based analytic network process (DANP) technique was utilised to compute the weights of every indicator and sub-indicator. Additionally, the modified VlseKriterijumska Optimizcija I Kaompromisno Resenje or VIKOR (in Serbian) approach evaluated every indicator and sub-indicator performance gap for empirical data analysis with suggested conclusions and recommendations. The results showed that the first dimension that should be improved is past experience, followed by personality traits and professional competence, according to the causal diagram of the NRM. The weights acquired through the DANP indicated that professional competence was the most influential dimension, followed by personality traits, whereas past experience was the least influential. Past experience revealed that the highest gap value is the most important for development if coffee house operators want to attain the appropriate levels. Finally, the theoretical, managerial, and practical implications were discussed. Notably, the research outcomes could optimise talent recruitment, establish appropriate talent recruitment methods for coffee house operators, and enhance the human resource quality in the outlying island of Penghu.

The Construction of Critical Factors for Successfully Introducing Chatbots into Mental Health Services in the Army: Using a Hybrid MCDM Approach

Previous research has shown that although military personnel are at high risk of developing mental disorders because of the excessive stress caused by their work, they also display low levels of intention to seek assistance because of the military culture. This, in turn, creates exorbitant costs for their respective countries. With the rapid development of artificial intelligence (AI)-related digital technologies, chatbots have been successfully applied to mental health services. Although the introduction of chatbots into the military to assist with mental health services is not common, it may become a future trend. This study aims to construct the critical factors for introducing chatbots into mental health services in the military, the relationships between the effects, and a weighting system, to ensure that the introduction of chatbots complies with sustainable practices. This includes four stages. In the initial stage, in accordance with the AI-readiness framework, in combination with the findings of previous research and specialist recommendations, preliminary indicators and items were developed. In the second stage, Fuzzy Delphi was used to confirm each dimension and indicator. In the third stage, using DEMATEL, an influential-network-relation map (INRM) of dimensions and indicators was created. In the fourth stage, using DANP, the relationships between the effects of the indicators and the weighting system were established. The findings of this study indicated that: (1) the key to success includes four dimensions and twenty-one indicators; (2) there is an interdependent relationship between the four dimensions and twenty-one indicators, and they influence each other; and (3) the four dimensions are technologies, goals, boundaries, and activities, in order of importance. Finally, specific suggestions are put forward to provide references for future practical applications and research, drawing on the results of this research.

Analysis of Mutual Influence Relationships of Purchase Intention Factors of Electric Bicycles: Application of DEMATEL Taking into Account Information Uncertainty and Expert Confidence

As the negative environmental impacts of transportation systems become more severe, governments and environmental groups are seeking more sustainable transportation options, such as replacing fuel-powered vehicles with electric vehicles and expanding public transportation systems to reduce the number of people driving on their own, in order to reduce the environmental impacts of transportation systems. At present, the rapid expansion of public transportation systems is not an easy task and requires a long period of time to plan for expansion and construction, so people are increasingly looking to find means of transportation that meet sustainable conditions as solutions. In this context, electric bicycles are one of the solutions that people can choose, with benefits such as energy saving, carbon reduction, effective air pollution reduction, and simple and labor-saving riding. However, in Taiwan, despite the many benefits of electric bicycles, their popularity is not high. Therefore, this study focuses on the factors that affect the purchase of electric bicycles in Taiwan. The Influential Network Relation Map (INRM) generated by the Z-based Decision-making Trial and Evaluation Laboratory (Z-DEMATEL) technique is used to describe the influence relationships among the factors and to establish the key evaluation criteria of electric bicycle purchase intention. The results indicate that vehicle price, safety, motor performance, battery life, and battery durability are the most important factors in purchasing electric bicycles. Furthermore, the power of motor is considered as the factor that most significantly affects other criteria, while safety and price are most likely to be affected by other criteria. This study has contributed to academia and industry, for the dependency weights of these factors are set to provide a scientific and systematic way to show how consumers think in the decision-making process and to provide more reliable information and management implications for the electric bicycle industry.

EXPLORING HOTEL APPRAISAL DETERMINANTS AMID SALES TREND DURING COVID-19 PANDEMIC: USING A DANP-MV MODEL

In the current hotel sales trend due to COVID-19 pandemic, few empirical studies have discussed hotel appraisal determinants and prioritization in terms of operational efficiency. This paper presents an innovative approach for appraisal practice efficiency based on hotel appraisal approach and the multiple criteria decision making (MCDM). The DANPmV model is used to identify the determinants related to actual hotel appraisal practices, including the techniques of the decision-making trial and evaluation laboratory (DEMATEL), DEMATEL-based ANP (DANP), and modified VIKOR. The result of influential network relationship map (INRM) and the gaps of determinants to the aspiration level may contribute to improving hotel appraisal efficacy. In practice, the “discounted cash flow” becomes the most influential determinant (dimension) and the “market survey” is the most manageable one. More findings together with an action plan are presented and useful in the real world. Therefore, this innovative approach could help hotel appraisers and related parties, such as hospitality managers, investors, lenders, and decision makers, better manage the evaluation determinants of hotel appraisal efficacy.

Which food delivery platforms are winning the restaurant food delivery wars? Analysis from a consumer perspective

AbstractThe emergence of the COVID‐19 pandemic dramatically lowered the foodservice industry's income overnight. Conversely, the practical measure of remaining at home to deal with the pandemic's impact has boosted the online food delivery business. In this study, a consumer perspective was adopted and an adapted version of the extended unified theory of acceptance and use of technology (UTAUT2) was used alongside multi‐attribute decision‐making methods (DEMATEL, DANP and modified VIKOR) to construct a model for evaluating and selecting a food delivery platform (FDP). The results of the INRM (influential network relation map) revealed that the first dimension to be improved upon and adjusted should be security, followed by effort expectancy, performance expectancy, social influence, facilitating conditions, hedonic motivation and habit. The DANP influential weights suggested that habits were the most important dimension, followed by hedonic motivation, while performance expectancy was the least important. According to the results of the gap analysis, the first dimension that required improvement was performance expectancy, followed by effort expectancy, facilitating conditions, security, social influence, habits and hedonic motivation. It is expected that the findings of this study can serve as a reference for consumers selecting FDPs to better satisfy their dining needs. The novel model is discussed in terms of theoretical, practical and managerial implications.

An Evaluation of the Advertising Media Function Using DEA and DEMATEL

Since a large amount of food industry advertising budget is spent on advertising media, it is necessary to ensure the appropriateness of the media program to choose the media more effectively. One of the factors in evaluating advertising media is efficiency. Considering the various indices affecting the efficiency of advertising media, this study uses the DEMATEL technique to investigate the relationship between these indices and the DEA to evaluate and rank the efficiency of them. The DEA (Data Envelopment Analysis) is a mathematical technique that calculates the efficiency of multiple decision-making units based on multiple inputs and outputs. The DEMATEL (Decision Making Trial and Evaluation Laboratory) technique is used to construct an influential network relation map to indicate the relationship among criteria. The results indicate that newspapers, magazines, radio, internet, and social networking sites, outdoor advertising, and television are the most efficient advertising media in the food industry, respectively.

USING THE SUSTAINABILITY-BALANCED SCORECARD FOR ASSESSING SUSTAINABILITY ISSUES OF THE GREEN ENERGY COMPANIES

Assessing the sustainability issues of the green energy companies is a multiple criterion decision that includes both quantitative and qualitative elements. The sustainability-balanced scorecard (SBSC) for sustainability evaluation is more difficult than an internal evaluation and it requires more serious investigation in the green energy companies. This paper objectives to mix this sustainability evaluation and use fuzzy information with the SBSC. The study presents a fuzzy DEMATEL (decision-making trial and evaluation laboratory) method to develop an assessment model that integrates triangular fuzzy numbers, and DEMATEL to develop a fuzzy assessment, which prioritizes the relative influence of SBSC for green energy companies’ elements. First, this paper conducts a literature review on SBSC regarding sustainability issues to generate 15 elements with five aspects, which are used to measure the sustainability assessment. Next, fuzzy DEMATEL is employed to manage the uncertain linguistic terms, then to set up an influential network relationship map (INRM). This suggested model provides a structure for the related green energy companies to select the evaluation method and could arrange the sustainability approach according to future competitive pressure. The result shows that environmental aspect is the most direct effect and social aspect is the most important effect aspect to the other aspects.

Exploring the Key Factors of Shared Decision-Making Through an Influential Network Relation Map: The Orthopedic Nurse's Perspective.

BackgroundFew studies have used quantitative methods to explore the key factors affecting shared decision-making (SDM) in nursing decision-making from the perspective of orthopedic nurses.PurposeTo understand the intercorrelations among shared decision-making questionnaire–nurse (SDM-Q-NUR) factors and identify key factors for clinical nursing care decisions in orthopedics.MethodsIn May 2021, this study investigated the interdependence of the SDM-Q-NUR scale and developed an influential network-relation map (INRM) from the clinical experience of 13 trained orthopedic nurses using the Decision-making Trial and Evaluation Laboratory method.ResultsThe INRM results showed that the nine criteria corresponded to three stages: preparation, discussion, and decision. “I helped my patient or patient's family understand all the information” (C5) and “I wanted to know from my patient or patient's family how they want to be involved in making the nursing care decision” (C2) are the main key factors for the beginning of nursing decision. In the discussion and decision stages, the corresponding key factors are “I made it clear to my patient or patient's family that a nursing care decision needs to be made” (C1) and “I asked my patient or patient's family which nursing care option they prefer” (C6). The result's statistical significance confidence and gap error were 98.106% and 1.894%, respectively.ConclusionsWhen making nursing decisions with patients, orthopedic nurses need to have detailed information about how patients are involved in SDM and all relevant information. Nurses should also inform patients and their families regarding the purpose of the discussion, namely, to help one understand the content, advantages, and disadvantages of the nursing care options, and finally, make a decision.

An evaluation model for the development of more humane correctional institutions: Evidence from Penghu Prison

Over time, correctional institutions have actively implemented innovations in prison administration. Most correctional institutions constitute conservative and closed societies. Generally, people do not have sufficient knowledge or understanding of penal correction. Therefore, it is difficult but necessary to break the stereotyped impression people hold about correctional institutions, actively integrate them into society, and encourage people to assume a more humane attitude towards correctional institutions. We conducted an inductive analysis of Penghu Prison administered by the Agency of Corrections, Ministry of Justice, Taiwan. After creating evaluation indices for the development of more humane correctional institutions, we conducted a survey to classify the evaluation indices into criteria under the four major evaluation dimensions. Using DEMATEL, we determined the causal relationship among different evaluation indicators and generated an influential network relation map about the evaluation criteria. Using DANP, we subsequently calculated weightings for the influence of each criterion. Finally, using the modified VIKOR, we conducted a gap analysis. The results of this study can be used to build a more positive and human reputation for correctional institutions and enable their sustainable creation.

Exploring the Key Factors for Preventing Public Health Crises Under Incomplete Information

The spread of COVID-19 has triggered one of the largest pandemics in modern human history. Humanity is still in the incomplete information period for this infectious disease, and how to effectively deal with such a major public crisis is a crucial problem. Although there are divergences in human natural semantics, the incomplete information increases it. Therefore, this study integrates the neutrosophic set and the Decision-Making Trial and Evaluation Laboratory (DEMATEL) methods to explore the key factors which would prevent expansion of the epidemic in the face of incomplete knowledge. The neutrosophic set technique is an effective tool for the representation of the ambiguity of natural human semantic expression, for the analysis of incomplete, uncertain, and inconsistent information. DEMATEL is used to explore the causes and effects between factors and to generate an influential network relationship map. The results of analysis can help the government and relevant organizations to understand the cause and effect relationship between the factors and set appropriate prevention strategies. The results of this study show that the incorporation of neutrosophic set theory leads to a more meaningful evaluation under incomplete information. “Detect” is a key factor affecting the entire system. The results of this study contribute to the advancement and development of scientifically based decision-making by helping governments and relevant organizations to understand the causal relationships between factors, to set appropriate prevention strategies.

Using DANP-mV Model to Improve the Paid Training Measures for Travel Agents amid the COVID-19 Pandemic

Due to the COVID-19 pandemic bringing travel to a standstill, an initiative of paid training for travel agencies was launched by the government. The purpose of this research is to improve the effectiveness of this measure, which is fundamental to the next tourism crisis management. Based on the related theories of tourism crisis management, organizational learning, and behavior adaption, the DANP-mV model developed an evaluation system for examining the training measure. The result of an influential network relationship map (INRM) shows that using influential effects, the “policy object” dimension and its criterion “subsidiary” should be the first improvement priority. To effectively achieve the aspiration level, the gap values point out “training courses” dimension and its criterion “excellent services” are first to improve. An action plan is produced containing all the findings and made available for easy indexing. It may contribute to the current measure improvements. Therefore, this innovative approach could help decision makers with tourism crisis policy making and help the sector with evolving learning readiness to remain sustainable.

Environmental Design Strategies to Decrease the Risk of Nosocomial Infection in Medical Buildings Using a Hybrid MCDM Model.

The prevention and control of nosocomial infection (NI) are becoming increasingly difficult, and its mechanism is becoming increasingly complex. A globally aging population means that an increasing proportion of patients have a susceptible constitution, and the frequent occurrence of severe infectious diseases has also led to an increase in the cost of prevention and control of NI. Medical buildings' spatial environment design for the prevention of NI has been a hot subject of considerable research, but few previous studies have summarized the design criteria for a medical building environment to control the risk of NI. Thus, there is no suitable evaluation framework to determine whether the spatial environment of a medical building is capable of inhibiting the spread of NI. In the context of the global spread of COVID-19, it is necessary to evaluate the performance of the existing medical building environment in terms of inhibiting the spread of NI and to verify current environmental improvement strategies for the efficient and rational use of resources. This study determines the key design elements for the spatial environment of medical buildings, constructs an evaluation framework using exploratory factor analysis, verifies the complex dominant influence relationship, and prioritizes criteria in the evaluation framework using the decision-making trial and evaluation laboratory- (DEMATEL-) based analytical network process (ANP) (DANP). Using representative real cases, this study uses the technique for order preference by similarity to ideal solution (TOPSIS) to evaluate and analyze the performance with the aspiration level of reducing the NI risk. A continuous and systematic transformation design strategy for these real cases is proposed. The main contributions of this study include the following: (1) it creates a systematic framework that allows hospital decision-makers to evaluate the spatial environment of medical buildings; (2) it provides a reference for making design decisions to improve the current situation using the results of a performance evaluation; (3) it draws an influential network relation map (INRM) and the training of influence weights (IWs) for criteria. The sources of practical problems can be identified by the proposed evaluation framework, and the corresponding strategy can be proposed to avoid the waste of resources for the prevention of epidemics.

A Hybrid, Data-Driven Causality Exploration Method for Exploring the Key Factors Affecting Mobile Payment Usage Intention

Several methodologies for academically exploring causality have been addressed in recent years. The decision-making trial and evaluation laboratory (DEMATEL), one of the multiple criteria decision-making (MCDM) techniques, relies on expert judgements to construct an influential network relation map (INRM), revealing the mutual causes and effects of the criteria and dimensions for presentation of the results in a visual manner. The interactional impacts may be evaluated without considering the presumed hypotheses. The DEMATEL has been successfully utilized to assist in complex decision-making problems in various contexts. However, there is controversy about the reliance upon expert judgements, which could be subjective. Thus, this study seeks to overcome this dispute by developing a data-driven, concept-based novel hybrid model which the authors call SEM-DEMATEL. The model first constructs the direct effects between indicators based on structural equation modeling (SEM) and then utilizes DEMATEL to confirm the interdependence among the variables and identify their causes and effects. Finally, an empirical study exploring the key factors affecting mobile payment usage intention is further conducted to demonstrate the feasibility, validity, and reliability of the novel SEM-DEMATEL research approach. The results identify that the perceived value is the key influencing indicator of m-payment usage intention, and the objectivity and efficiency of the research results are compared.