Hybrid Multiple Attribute Decision Making Research Articles

Assessing the Sustainability of Urban Community Renewal Projects in Southern China Based on a Hybrid MADM Approach

Urban renewal is extensively practiced around the world and has attracted substantial attention among scholars and the public. To ensure that urban renewal is directed toward sustainable development goals, sustainability assessments for urban renewal projects have become critical topics. Simultaneously, the ex ante evaluation research of urban renewal projects has not received enough academic attention, and most results have not fully considered the localization of criteria and the internal correlation between criteria/dimensions. Therefore, this paper proposes an ex ante decision model for the sustainability assessment of urban renewal projects based on a hybrid multiple-attribute decision-making (MADM) approach, which includes 3 dimensions and 16 criteria. It uses a case in Guangzhou to assess the sustainable potential of the project and explore relevant improvement strategies. Empirical results from the Decision Testing and Evaluation Laboratory (DEMATEL) indicate that the economic (D1) and environment (D2) dimensions both impact the social and cultural (D3) dimensions, with the environment (D2) dimension being impacted by the economic (D1) dimension. The criteria occupying the “cause” position include reducing construction costs and materials expenses (C5), increasing greening configuration and open space (C6), reducing resource consumption and waste (C8), improving existing land-use efficiency (C2), promoting the biodiversity of space (C9), and strengthening the safety of pedestrians and residents (C15), where increasing greening configurations and open space (C6) and reducing resource consumption and waste (C5) are considered the key criteria based on the results of DEMATEL and the DEMATEL-Analytic Network Process (DANP). The modified VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method revealed that the economic (D1) dimension has poor performance, and its improvement needs to be prioritized. Further improvement strategies are proposed based on the influence network relationship graph (INRM). In conclusion, our results show that urban community renewal projects in Guangzhou are steadily progressing toward a sustainable vision.

Development potential of Chinese smart cities and its spatio‐temporal pattern: A new hybrid MADM method using combination weight

AbstractTaking advantage of information communication technology, a smart city is a city that has its critical urban infrastructure upgraded to optimise resources allocation and maintenance activities. It serves as a new technology‐based solution to mitigate urban diseases and to improve urban development in China. However, unbalanced and uncoordinated smart city development potential (SCDP) would impede the future construction of the smart city. Consequently, this study aims to measure SCDP and further examine the equality of its spatial distribution in China. In this regard, a brand‐new hybrid multiple attribute decision‐making (MADM) model is proposed to evaluate SCDP. Subsequently, a series of spatial analyses are introduced to uncover the spatial differentiation of SCDP. The results suggest that (a) overall SCDP in China has a continuous upward tendency, and the SCDP compositions of six subsystems contribute variously; (b) over time high‐SCDP cities agglomerated in the east, whereas most of the low‐SCDP cities clustered in the west. This feature indicates that SCDP in China is unevenly distributed; (c) high‐SCDP cities preferred to cooperate in coordinated efforts rather than develop independently. This study makes new contributions to smart city development research in terms of methodology and empirical evidence.

Application of Hybrid Multiple Attribute Decision-Making Model to Explore the Design Strategies of Children's Facilities in Neighborhood Open Spaces Based on Sensory Integration Theory.

In recent years, the prevalence of sensory integration disorders in children in urban areas has increased. Most existing sensory integration treatments are located in hospital-based sensory integration units; however, medical resources are extremely limited, making it difficult to guarantee the appropriate treatment time and intervention results for many children. The concept of sensory integration therapy must be disseminated widely and correctly to meet these children's needs. Although most urban communities have a high number of children's spaces, these spaces require improvement. This study proposes the incorporation of the concept of sensory integration therapy into neighborhood open spaces for children to positively impact children's sensory development. The purpose of this study is to determine the effective facility factors of an occupational therapy room, translate them into a community facility design, clarify the categories and relative importance of each design attribute, and explore the design strategies of the children's facilities in neighborhood open spaces based on the sensory integration theory. This study investigates the importance of the sensory integration treatment level. The facilities in neighborhood open spaces for children can be considered systemic structures consisting of five partitioned units with different levels of importance among the synergistic components within each unit. These structures will enable children to experience sensory stimulation during daily outdoor play and will serve as preventive and therapeutic tools.

Sustainable Sports Tourism Performance Assessment Using Grey-Based Hybrid Model

The development of sports tourism is gaining momentum around the world, with many tourism industries combining sports events and programs to attract more domestic and overseas customers to promote economic and culture. Sustainability awareness has been gaining attention from many international organizations, resulting in the rise of sports tourism that incorporates sustainability. Therefore, the development of a valid and applicable sustainable sports tourism (SST) assessment model is an important task. In this study, a hybrid Multiple Attribute Decision-Making (MADM) model is proposed to measure the development performance of SST. The aims of this study include developing a SST assessment framework, identifying the mutual influential relationships among attributes, generating attribute influence weights, and calculating the performance of the evaluated items. The proposed model is divided into three stages. First, a cause-and-effect diagram is generated using the Grey Decision-Making Trial and Evaluation Laboratory (GDEMATEL) to describe the interactions and feedback among the attributes. Then, the GDEMATEL-based Analytic Network Process (GDANP) is applied to generate the influence weights of the attributes and their rankings. Finally, the expanded Probability-based Grey Relational Analysis (expanded PGRA) was applied to calculate the performance of the evaluated items and to determine the gap between evaluated items and the aspiration level. This study improves the original PGRA technique by introducing the concept of aspiration level into the PGRA calculation process, thereby replacing the traditional concept of “relative satisfaction” with “aspiration level”. In addition, the expanded PGRA can assess a single rated item without being limited to at least two items. We used the Sun Moon Lake Scenic Area in Taiwan as a model demonstration. The results show that the top three attributes that need to be strengthened are disease prevention and treatment, local social welfare and protection, and sports diversity. In the Sun Moon Lake, intersection control should be set up to ensure the health status of visitors and local residents. In addition to epidemic prevention, more measures and behaviors should be developed to deal with tourism diseases. We suggested that subsidies be provided to local residents to rebuild the fences around their homes to avoid disturbances caused by the influx of tourists. Moreover, the local government can create more sports events with special characteristics that can attract tourists to come again and again.

A Hybrid MADM Model for Newly Graduated Nurse's Competence Evaluation and Improvement.

Nursing departments in hospitals must evaluate the practical competency of newly graduated nurses and assist them to increase their competence. Competency assessments often consider multiple qualitative attributes and use expert knowledge as the basis for decision-making. This study proposes a hybrid multiple attribute decision-making (MADM) model that determines practical competency of the newly graduated nurse as an evaluation framework. A causal influence-network diagram (CIND) and influential weights are obtained from nursing experts' clinical experience using the decision-making trial and evaluation laboratory (DEMATEL)-based analytical network process analysis (DANP). The MOORA-AS method is then used to evaluate the ability expectation ratio-gap for newly graduated nurses in practice. The CIND is used to allow each newly graduated nurse to reduce the performance ratio-gaps between the current level and the aspirational level from a systematic perspective. The empirical data applies to a third-class and a first-class hospital in China. The results show that the proposed hybrid MADM model has reliable results and allows nursing department decision-makers/managers to easily evaluate and systematically improve competencies for newly graduated nurses.

Turnaround project risk assessment using hybrid fuzzy SWARA and EDAS method: case of upstream oil process industries in Iran

PurposeThe purpose of this paper is to propose a new framework for assessing the risks of turnaround projects in upstream oil process plants.Design/methodology/approachThis study represents a new hybrid framework for turnaround project risk assessment. First, according to experts’ opinions, the project risks were identified using interviews and brainstorming. The most important risks selected by experts and a hybrid multiple-attribute decision-making (MADM) method used to assess and prioritize them. The proposed MADM method uses fuzzy step-wise weight assessment ratio analysis (SWARA) and fuzzy evaluation based on distance from average solution (EDAS) methods based on trapezoidal fuzzy numbers.FindingsIn this research, 28 usual risks of turnaround projects are identified and 10 risks are then selected as the most important ones. The findings show, that among the risks of upstream oil industry turnaround projects from the perspective of experts, the risk of timely financing by the employer, with an appraisal score of 0.83, has the highest rank among the risks and the risk of machine and equipment failure during operation, with an appraisal score of 0.04, has the lowest rank.Research limitations/implicationsThe risk analysis based on inputs collected from the experts in the Iranian upstream oil industry, and so the generalization of the results is limited to the context of developing countries, especially oil producer ones. However, the proposed risk analysis methodology and key insights developed can be useful for researchers and practitioners in any other process industry everywhere.Originality/valueA novel framework for risk assessment is introduced for turnaround projects in the oil industry using MADM methods. There is no literature on using MADM methods for turnaround project risk analysis in the oil and gas industries. Furthermore, this paper presents a hybrid fuzzy method based on SWARA and EDAS.

Evaluating Critical Factors Influencing the Reliability of Emergency Logistics Systems Using Multiple-Attribute Decision Making

The infectious disease COVID-19 has swept across the world in 2020, and it continues to cause massive losses of life and severe economic problems in all countries. Providing emergency supplies such as protective medical equipment and materials required to secure people’s livelihood is thus currently prioritized by governments. Establishing a reliable emergency logistics system is critical in this regard. This paper used the Delphi method to design a formal decision structure to assess emergency logistics system reliability (ELSR) by obtaining a consensus from a panel of experts. Assessing ELSR is a typical multiple-attribute decision making (MADM) problem, and the related MADM methods are usually on the basis of symmetry principles. A hybrid MADM model, called the Decision Making Trial and Evaluation Laboratory (DEMATEL)-based Analytical Network Process (D-ANP), was developed to identify the critical factors influencing ELSR. An analysis of empirical evidence showed that the emergency logistics command and coordination system and the emergency material supply system play important roles in ELSR, while the emergency logistics transportation and distribution system and the emergency information system are not so important. This conclusion is different from previous research about traditional disaster emergency logistics. Moreover, the cause–effect relationships among the key factors indicated that the system of command and coordination for emergency logistics and the supply system for emergency materials should be improved. Accordingly, effective suggestions for emergency logistics services for epidemic prevention are provided in this paper. The main contributions of this paper are (1) establishing a comprehensive and systematic evaluating index of ELSR for epidemic prevention; (2) employing a kind of structured, namely D-ANP, to identify the critical factors with non-commensurable and conflicting (competing) characteristics; and (3) comparing the differences of reliable criteria between the emergency logistics of epidemic prevention and the traditional disaster emergency logistics.

A phase change material selection using the interval-valued target-based BWM-CoCoMULTIMOORA approach: A case-study on interior building applications

The move towards sustainable development and energy efficient solutions in the built environment has led to develop innovative solutions, particularly in the area of indoor environmental comfort in buildings. Phase change materials (PCMs) are a potential approach to target building energy use reduction. PCMs are smart materials that have been commercialized and used in buildings for effective regulation of surface and indoor air temperature fluctuations and peak energy reductions. Appropriate PCM selection is the critical step in PCM system design that determines the full effectiveness and applicability of PCM integrated building applications. Optimal selection of PCMs can be effectively executed with the support of multiple attribute decision making (MADM) approaches. Although, the traditional MADM methods have usually focused on beneficial and non-beneficial attributes, in real-world and practical problems, decision-makers tend to determine the rank of an optimal alternative based on the target values of their attributes. In response to the knowledge gap of an existing practical and functional PCM selection solution, this study proposed a hybrid and novel target-based MADM approach that combines the best-worst method (BWM) with COmbined COmpromise SOlution (CoCoSo) and multi-objective optimization of ratio analysis plus the full multiplicative form (MULTIMOORA) with an interval-valued structure called the IV-T-BWM-CoCoMULTIMOORA approach. A case study is examined to select the optimal PCM for interior building surface applications based on a case-specific construction project in Toronto, Canada. Two separate scenarios are considered, one based on thermophysical specifications and one based on managerial preferences. The connection between both technical and managerial criteria was demonstrated to clearly affect the decision-making process to take into account both thermophysical properties of PCM alternatives in the context of risk factors and design considerations. Nevertheless, the influence of the technical parameters was shown to be dominant in the final selection of the best case scenario.

A Hybrid Decision-Making Method for the Selection of a Phase Change Material for Thermal Energy Storage

Abstract Phase change materials (PCMs) are considered to be promising contenders for thermal energy storage (TES) due to their high latent heat and nearly constant temperature during the intake/release of heat. The present study focuses on providing the most suitable PCM for low-temperature (40–80 °C) heat storage applications. However, the selection of the most suitable one from the wide range of PCMs for an application needs a thorough insight of their thermophysical properties, thermal stability, compatibility, and melting and solidification behavior. Among the PCMs available for low-temperature heat storage applications, organic PCMs stand as an attractive option. Based on melting point temperature, latent heat, cost, and ease of availability, five widely used organic PCMs, viz., lauric acid (LA), myristic acid (MA), stearic acid (SA), paraffin wax (PW), and palmitic acid (PA), are selected. Initially, thermophysical properties are measured and tabulated. Subsequently, thermal stability experiments up to 1500 melting/freezing cycles, compatibility studies with container materials (aluminum and stainless steel (SS)), and melting and solidification experiments giving total melting and solidification times are performed. Further, a hybrid multiple attribute decision-making (MADM) method is employed to select the best PCM based on the obtained experimental results. During the selection process at first, the subjective weights of the attributes are measured according to the analytical hierarchy process (AHP). Later, the PCMs are ranked based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). The hybrid MADM results show that among the selected PCMs, paraffin wax is the optimal PCM for low-temperature heat storage applications.

NEIGHBORHOOD SELECTION FOR A NEWCOMER VIA A NOVEL BWM-BASED REVISED MAIRCA INTEGRATED MODEL: A CASE FROM THE COQUIMBO-LA SERENA CONURBATION, CHILE

Nowadays, cities are developing differently according to their needs, limitations and certain strategic plans. Moreover, conurbation areas will be more common in so many countries like Chile when there are two or more cities developing one next to another, leaning on each other. In this atmosphere, typical residents live in a region or a neighborhood based on certain criteria, so they know how and where they are going to live. From another point of view, a newcomer is usually faced with a city full of contrasts which make things completely and surprisingly complicated. In order to illustrate this, a real case was selected based on the research field, qualitative and quantitative (real) data. The Coquimbo-La Serena conurbation and it’s regions as “Comuna (in Chile)” is a really suitable case to show the complexity of the study. In order to face the challenge, a new hybrid Multiple-Attribute Decision-Making (MADM) method is introduced based on the Best-Worst Method (BWM) and Multi-Attributive Ideal-Real Comparative Analysis (MAIRCA). The five best different neighborhoods as Comunas of the conurbation were analyzed based on the two main scenarios: having a private car or using only public transportation. To obtain more reliable results, a sensitivity analysis was made so as to determine the behavior of the proposed model against weight changes. Besides, the final results were compared with the other MADM methods, for example: Multi-Attributive Border Approximation Area Comparison (MABAC), VIsekriterijumsko KOmpromisno Rangiranje (VIKOR) and COmbinative Distance-based ASsessment (CODAS).

Prospective MADM and Sensitivity Analysis of the Experts Based on Causal Layered Analysis (CLA)

“Multiple Attribute Decision Making (MADM)” is an expert based field which is working based on real data and experts’ opinions. So many studies have been doing based on MADM methods which they usually use qualitative data based on experts’ ideas. Decisions based on the experts’ opinion shall be carefully designed to cope the real problems uncertainty. This uncertainty will be even more intricate if combining the problem with the ambiguity of the future study. Prospective MADM is a future based type of MADM field which is concentrating on decision making and policy making about the future. Prospective MADM (PMADM) can have both explorative and descriptive paradigms in the studies but it will more useful to be applied for strategic planning. In this regard, experts’ role would be even more challenging because one/some possible future/futures will be partially designed based on their opinions. Future and prediction always complicates the decision environment, especially methodologies founded on experts’ judgement. Considering experts’ preferences, attitude, and background, they may be a major source of inaccurate results. Causal Layered Analysis (CLA) is well-known “Futures Studies” method which is qualitative and usually is supporting other methods such as “Backcasting” and “Scenario Planning”. CLA has a deep point of view to the subjects to support a future with all those changes which are necessary for the main goal/goals. In this study, this idea will be proposed that CLA can be added to PMADM outline to decrease the risk of unsuitable decisions for the future and for this aim a case study about energy and CO2 consumption in policy making level proposed and a hybrid MADM method based on BWM-CoCoSo applied in the PMADM outline for the procedure.

Integrating interval-valued multi-granular 2-tuple linguistic BWM-CODAS approach with target-based attributes: Site selection for a construction project

The site selection procedure for mega-structure projects can be an effective tool that could considerably improve the amount of income generation potential. Evidently, selecting the optimal location to establish a shopping center in a metropolitan area of Tehran, Iran is challenging due to the complexity of several conflicting evaluation criteria as well as multiple alternatives. Moreover, the site selection process of a mega-structure project can be viewed as a multiple attribute decision making (MADM) problem. Additionally, in such complex environments decision-makers and policy-makers usually might utilize linguistic terms to evaluate different alternatives with respect to multiple evaluation criteria according to their experience, qualifications, and preferences. Moreover, in real-world decision-making assessment problems, decision-makers tend to assign specific target-values for the selection attributes to obtain their optimal choices. In response, this study solves a site selection problem using a hybrid multi-granular interval-valued 2-tuple linguistic variables and target-valued criteria with the Best-Worst Method (BWM) and COmbinative Distance-based ASsessment (CODAS). Using the suggested hybrid MADM approach can results in an optimal and comprehensive site selection process without information loss. Finally, the outcomes of the current study show that the proposed target-based method is an optimal technique for such decision-making problems.

A PRE-PLANNING FOR HOTEL LOCATING ACCORDING TO THE SUSTAINABILITY PERSPECTIVE BASED ON BWM-WASPAS APPROACH

Finding an appropriate location from any kind of perspectives is a really vital issue for businesses. Searching for the best location to meet a business perspective which can be also a sustainable one would be really challenging and it needs pre-planning. Locating for business issues in tourism industry for instance hotel locating is one of the major complicated topics in this area. Locating can come along with pre-planning and kind of feasibility studies which can cover all necessities of current and future needs of an issue. Locating with sustainability point of view is one the newest approach in different studies which this research is also working on that based on a hybrid Multiple Attribute Decision Making (MADM) model. MADM methods are really suitable ways in making complicated decisions in different areas. A hybrid MADM model based on BWM-WASPAS is applied for locating problem in finding the best location for the hotel locating challenge. To meet the aim of this research, a case study for evaluating probable locations of a five star hotel examined for the Shahrekord city, Iran. As locations were prioritized based on sustainability perspective, business goals can also be seen as a pre-planning project.

A Hybrid Multiple-Attribute Decision-Making Model with Modified PROMETHEE for Identifying Optimal Performance-Improvement Strategies for Sustainable Development of a Better Life

Governments worldwide are cognizant of the deficiencies of measuring quality of life according to gross domestic product; consequently, they have created indicators of citizen well-being that can be applied in governmental policy. To improve citizens’ lives, governments should create an environment with maximal quality of life, ideal material living conditions, and sustainable well-being and determine the true needs of citizens. This paper proposes a hybrid multiple-attribute decision-making model with a modified PROMETHEE method that can identify practical performance-improvement strategies for the sustainable development of a better life by accounting for the complex dependencies among the indicators. In the proposed model, an influential network relation map is first obtained using the DEMATEL method to delineate the interrelationships among the indicators. Second, to address the feedback and dependence concerns associated with interrelationships among criteria, the influence weights are identified through the DANP method. Finally, the degree of preference is determined through the modified PROMETHEE method and combined with the influence weights to calculate flow indicators, which facilitate attaining the aspiration level. The aspiration level is set and an aspiration alternative is identified as an improvement benchmark to facilitate continual melioration and sustainable development of a better life. This model uses the OECD well-being indicators consisting of 11 dimensions and 24 criteria to measure material living conditions (namely housing, income, jobs) and quality of life (namely civic engagement, community, education, environment, health, life satisfaction, safety, and work–life balance). An empirical case study was performed to illustrate the feasibility and effectiveness of the proposed model by using questionnaire data of six cities in Taiwan. Our results prove that the proposed model (aspired-worst as benchmark) outperforms the traditional model (max–min as benchmark) and that it can obtain more realistic net flows and an improvement benchmark to conduct ranking, selection, and continual improvement for facilitating sustainable development of a better life.

Renewable Energy Technology Selection Problem Using Integrated H-SWARA-MULTIMOORA Approach

Due to the adaptation of recent pollution mitigation and justification policies there has been a growing trend for electricity generation from various renewable resources. The selection of the optimal renewable energy technology could be measured as a complex problem due to the complication of forthcoming circumstances in any country. Consequently, the proposed similar complex assessment problem can be tackled with the support of Multiple Attribute Decision Making (MADM) methods. The current research study investigates a technology selection problem by proposing a hybrid MADM approach based on the Step-Wise Weight Assessment Ratio Analysis (SWARA) approach with a hierarchical arrangement combined with the Multi-Objective Optimization on the basis of Ratio Analysis plus the full MULTIplicative form (MULTIMOORA). Ultimately, a conceptual case study regarding the selection of the optimal renewable energy technology based on a conceptual development project in Iran has been examined by the proposed combinative MADM methodology.

Schemes for enhancing Taiwanese cruise PAK relationships using the hybrid MADM model

Because of the emerging cruise travel market, major Taiwanese travel agencies have promptly formed PAK to distribute cruise sales nationwide. However, few studies have discussed this issue or proposed empirical schemes to help enhance relations inter-alliances. The purpose of this study is to address this problem within the theoretical framework of trust-commitment theory. The method of hybrid MADM (multiple attribute decision-making) is used to manage multi-variant problem and produce optimal enhancing models. The result shows that Trust and Commitment mediate the relation, as found in previous studies, but unveils that Antecedents can also directly influence Relational outcomes, such as from Opportunistic behavior to Propensity to leave. Notably, Trust and Commitment play the leading roles to reach the aspired relation. The findings are integrated into a useful scheme index for decision-makers to enforce the on-going relational exchange to reach the common goal of PAK.

IMPROVING CHINA’S REGIONAL FINANCIAL CENTER MODERNIZATION DEVELOPMENT USING A NEW HYBRID MADM MODEL

The regional financial center is the propeller of regional economic development. Regional financial center modernization, however, has been the predominant propulsion of economic sustainability. Decisions related to regional financial center modernization development are in­herent problems of multiple attribute decision-making (MADM), and strategically important to the government. The purpose of this paper is to set up a regional financial center improvement model for modernization development, as based on a hybrid MADM model, which addresses the main causal-effect factors and amended priorities in order to strengthen ongoing planning. This paper adopts a new hybrid MADM model combined with the DEMATEL technique to construct an influential network relationship map (INRM) and determined the influential weights of DANP. Then, a modified VIKOR method using influential weights is applied to measure and integrate the performance gaps from each criterion into dimensions, as well as the overall criterion for evaluating and improving the modernization development of the regional financial center, as based on INRM. Finally an empirical case study using data from the Guangzhou regional financial center is carried out as an example to demonstrate the suitability of the proposed hybrid MADM model for solving real-world problems. The results show the priorities for improvement, as based on the degree of the effect and impact of the dimensions, as follows: first is making “government policy”, second is enforcing “financial infrastructure and safety”, next is formulating “financial institutions and human resources”, and finally “financial service”.

New Hybrid Multiple Attribute Decision-Making Model for Improving Competence Sets: Enhancing a Company’s Core Competitiveness

A company’s core competitiveness depends on the strategic allocation of its human resources in alignment with employee capabilities. Competency models can identify the range of capabilities at a company’s disposal, and this information can be used to develop internal or external education training policies for sustainable development. Such models can ensure the importation of a strategic orientation reflecting the growth of its employee competence set and enhancing human resource sustainably. This approach ensures that the most appropriate people are assigned to the most appropriate positions. In this study, we proposed a new hybrid multiple attributed decision-making model by using the Decision-making trial and Evaluation Laboratory Technique (DEMATEL) to construct an influential network relation map (INRM) and determined the influential weights by using the basic concept of the analytic network process (called DEMATEL-based ANP, DANP); the influential weights were then adopted with a modified Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. A simple forecasting technique as an iteration function was also proposed. The proposed model was effective. We expect that the proposed model can facilitate making timely revisions, reflecting the growth of employee competence sets, reducing the performance gap toward the aspiration level, and ensuring the sustainability of a company.

Target market selection based on market segment evaluation: a multiple attribute decision making approach

Target market selection is one of the most important marketing decisions for many companies. Besides, many other decisions of an organisation such as market mix, procurement and distribution channels are affected by this decision. An appropriate target market selection is performed upon market segment evaluation results and considering many factors such as segment size, number of competitors, risk and profitability. Moreover, multiple-attribute decision making (MADM) tools are used as a natural approach for evaluating alternatives with respect to conflict criterion, and target market selection can be considered as an MADM problem. To this end, a novel hybrid MADM method including AHP and TOPSIS is proposed to elicit a suitable target market. More precisely, AHP is derived to calculate each criterion's weight and TOPSIS is applied to rank target market alternatives from the best to the worst ones. Additionally, a case study is presented to validate the developed framework.

Exploring mobile banking services for user behavior in intention adoption: using new hybrid MADM model

Mobile banking services are one of the most promising recent technological innovations. In this study, we developed a conceptual model to explore mobile banking services for user behavior in the financial banking industry in intention adoption. The aim of this study is to explore the effect of user behavior and guidance on the mobile banking services intention adoption structure model among customers based on decomposed theory of planned behavior and trust-related behaviors based on the knowledge of experts. In this study, we use a new hybrid model, the multiple attribute decision making (MADM) model, which combines decision making trial and evaluation laboratory (DEMATEL) for building an influential network relationship map (INRM), DANP (DEMATEL-based ANP) for determining the influential weights of criteria, and the VIKOR method using the influential weights to evaluate and integrate the criteria in the gaps and reduce the gaps to satisfy the users’ behavior needs based on INRM. An empirical case of Taiwan’s financial banking industry is used as an example to demonstrate the application of the proposed hybrid MADM model and its efficiency. In the results, we find that the proposed user behavior framework can offer a deeper understanding of the variables/criteria that influence the interrelationship for the intention adoption of mobile banking services by DEMATEL technique. We can also combine the influential weights of DANP with weighting gaps using the VIKOR method to evaluate how to reduce these gaps and provide the best improvement strategies to satisfy the mobile banking services for users’ behavior needs.