VlseKriterijumska Optimizacija I Kompromisno Resenje Research Articles

An integrated group decision-making method under q-rung orthopair fuzzy 2-tuple linguistic context with partial weight information.

Considering the advantages of q-rung orthopair fuzzy 2-tuple linguistic set (q-RFLS), which includes both linguistic and numeric data to describe evaluations, this article aims to design a new decision-making methodology by integrating Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and qualitative flexible (QUALIFLEX) methods based on the revised aggregation operators to solve multiple criteria group decision making (MCGDM). To accomplish this, we first revise the extant operational laws of q-RFLSs to make up for their shortcomings. Based on novel operational laws, we develop q-rung orthopair fuzzy 2-tuple linguistic (q-RFL) weighted averaging and geometric operators and provide the corresponding results. Next, we develop a maximization deviation model to determine the criterion weights in the decision-making procedure, which accounts for partial weight unknown information. Then, the VIKOR and QUALIFLEX methodologies are combined, which can assess the concordance index of each ranking combination using group utility and individual maximum regret value of alternative and acquire the ranking result based on each permutation's general concordance index values. Consequently, a case study is conducted to select the best bike-sharing recycling supplier utilizing the suggested VIKOR-QUALIFLEX MCGDM method, demonstrating the method's applicability and availability. Finally, through sensitivity and comparative analysis, the validity and superiority of the proposed method are demonstrated.

Challenges in adopting blockchain technology in supply chain management: a too far fetched idea?

PurposeRecent technological advancements, often linked to Industry 4.0, require organizations to be more agile and innovative. Blockchain technology (BT) holds immense potential in driving organizations to achieve efficiency and transparency in supply chains. However, there exist some insurmountable challenges associated with the adoption of BT in organizational supply chains (SC). This paper attempts to categorically identify and systematize the most influential challenges in the implementation of BT in SC.Design/methodology/approachThis study resorts to an extensive literature review and consultations with experts in the field of supply chain management (SCM), information technology and academia to identify, categorize and prioritize the major challenges using VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and Combined Compromise Solution method (CoCoSo).FindingsThe top three classes of challenges revealed in this study are privacy challenges (PC), infrastructure challenges (IC) and transparency challenges (TC). Maintaining a balance between data openness and secrecy and rectification of incorrect/erroneous input are the top two challenges in the PC category, integration of BT with sustainable practices and ensuring legitimacy are the top two challenges in the IC category, and proper and correct information sharing in organizations was the top most challenge in the TC category.Originality/valueFuture scholars and industry professionals will be guided by the importance of the challenges identified in this study to develop an economical and logical approach for integrating BT to increase the efficiency and outcome of supply chains across several industrial sectors.

Long-term safety evaluation of soft rock tunnel structure based on knowledge decision-making and data-driven models

Tunnel structure are often subjected to continuous deformation caused by the creep effect of soft rock, leading to posing significant long-term operational risks. This paper focuses on ensuring the safe operation of a typical soft rock tunnel in the complex and dangerous mountainous area of western China. On the basis of studying the structural mechanic characteristics of the tunnel under the influence of soft rock creep, the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) model based on Analytic Hierarchy Process (AHP) and Entropy Weight Method (EWM) to determine subjective and objective weights, and game theory (GT) to obtain comprehensive weights was established. Additionally, the differential evolution-grey wolf optimization (DE-GWO) improved extreme learning machine (ELM) model was also constructed. By comparing the safety evaluation results of the two models on typical monitoring sections of soft rock tunnel structure, it is demonstrated that the proposed knowledge-based decision-making and data-driven models effectively and accurately evaluated the long-term safety of typical monitoring sections. Ulteriorly, to address the issue of structure safety evaluation caused by the inability to comprehensively monitor the entire tunnel (missing monitoring data), the DE-GWO improved ELM model was further adopted, and the structure safety status of the entire tunnel was precisely deduced.

Double-layer multi-criteria group decision-making approach using neutralized possibility degree-based decision matrix with fuzzy information

Multi-criteria group decision-making (MCGDM) problems are fundamentally characterized by uncertainty and ambiguity. The quantification of such data is vital for determining the most optimal course of action. In this paper, a double-layer possibility degree-based interval-valued q-rung orthopair fuzzy sets (IVq-ROFSs) Vlsekriterijumska Optimizacija i Kompromisno Resenje (VIKOR) approach is presented. First, the possibility degrees of IVq-ROFSs are calculated and processed to establish a new neutralized decision matrix. Second, the components of the new decision matrix are taken into account for obtaining a new pair of positive and negative ideal solutions. The utility and regret measures in the VIKOR approach are ultimately determined by combining criteria weights and cumulative possibility degrees to rank the alternatives. The results of the study show that the proposed approach contributes to acquiring accurate alternative rankings in situations where traditional approaches have had difficulty generating ranks. Also, by eliminating the early normalization stage, which has a direct impact on the final ranking, the proposed approach concludes a unique ranking for each decision-making problem. Several comparative and sensitivity analysis are also conducted to exhibit robustness and applicability of the proposed approach in real world.

Modelling of Flood Hazard Early Warning Group Decision Support System

Early warning of flood hazards needs to be carried out comprehensively to avoid a higher risk of disaster. Every decision on early warning of a flood hazard is carried out in part by one party, namely the government or water resource managers. This research aims to provide a collaborative decision-making model for early warning of flood hazards through a Group Decision Support System Model (GDSS), especially in Indonesia. The novelty of this research is that the GDSS model involves more than one decision-maker and multi-criteria decision-making for early warning of flood hazards in the downstream Kali Sadar River, Mojokerto Regency, East Java Province, Indonesia. The GDSS model was developed using a hybrid method, namely the Analytical Network Process (ANP) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). There was more than one decision result; voting was carried out using the BORDA method to produce the decision. The test results of GDSS were obtained using a Spearman rank correlation coefficient of 0.8425 and matrix confusion, an accuracy value of 86.7%, a precision value of 86.7%, a recall value of 86.7%, and an f-measure of 86.7%. Based on the test results, good results were obtained from the GDSS model. Doi: 10.28991/CEJ-2024-010-02-018 Full Text: PDF

Design concept evaluation based on cloud rough model and modified AHP-VIKOR: An application to lithography tool manufacturing process

Design concept evaluation is a wide domain of research as the production process of new product development is mainly based on the evaluations of experts. As different types of uncertainties like vagueness, randomness, and diversity essentially exist in the evaluation information, the manipulation models that deal with just one type of uncertainty are not appropriate for ranking the design alternatives. The integration of multiple approaches into a single mathematical model to create an effective framework is more useful for uncertain information manipulation. This paper presents an innovative group decision-making approach to evaluate design concepts by integrating cloud rough numbers, analytic hierarchy process (AHP) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method to introduce a novel cloud rough AHP-VIKOR model. The concept of cloud rough numbers is utilized by fusing the merits of the cloud model theory and rough approximations in addressing randomness in experts’ judgments and intrapersonal uncertainty for handling consensus inconsistency. Some new modified algebraic operations are introduced to remove the errors in already existing operations of cloud rough numbers. The cloud rough AHP technique is introduced to compute weights of design criteria by computing the cloud rough numbers of linguistic values and their reciprocals. Based on cloud rough values of positive and negative ideals, the individual regret, group utility values and evaluation indices are determined. Using the distance of evaluation indices from minimized cloud rough value, the design alternatives are ranked using different formulae. The significance of the proposed approach is illustrated with a real-world application in lithography tool manufacturing process. The out-performance and reliability of the proposed model is studied by a sensitivity analysis of different parameters in the method, and a comparison analysis with existing approaches.

A novel B&B recommendation method based on improved intuitionistic fuzzy sets

PurposeThis paper aims to propose a bed and breakfast (B&B) recommendation method that takes into account review timeliness and user preferences to help consumers choose the most satisfactory B&B.Design/methodology/approachThis paper proposes a B&B ranking method based on improved intuitionistic fuzzy sets. First, text mining and cluster analysis are combined to identify the concerns of consumers and construct an attribute set. Second, an attribute-level-based text sentiment analysis is established. The authors propose an improved intuitionistic fuzzy set, which is more in line with the actual situation of sentiment analysis of online reviews. Next, subjective-objective combinatorial assignments are applied, considering the consumers’ preferences. Finally, the vlsekriterijumska optimizacija i kompromisno resenje (VIKOR) algorithm, based on the improved score function, is advised to evaluate B&Bs.FindingsA case study is presented to illustrate the use of the proposed method. Comparative analysis with other multi-attribute decision-making (MADM) methods proves the effectiveness and superiority of the VIKOR algorithm based on the improved intuitionistic fuzzy sets proposed in this paper.Originality/valueProposing a B&B recommendation method that takes into account review timeliness and user customization is the innovation of this paper. In this approach, the authors propose improved intuitionistic fuzzy sets. Compared with the traditional intuitionistic fuzzy set, the improved intuitionistic fuzzy set increases the abstention membership, which is more in line with the actual situation of attribute-level sentiment analysis of online reviews.

Application of Multi-Criteria Decision Making Methods for Menu Selection

Nutritional information on menus can assist customers in making healthier eating choices. One technique being utilized to tackle the rise of overweight and obesity is the use of nutritional information on menus. Menu engineering strategies can be used to improve sales of generally healthier and higher margin items. For today's food and beverage companies, menu engineering has become essential. Companies must continually evaluate their menus in order to keep up with changing customer demands and the conditions of the competitive market. Menu engineering's core involves comparing the effectiveness of each menu. At this point, correct decision-making under numerous factors is thought to be a very challenging procedure. To evaluate alternatives according to many features, several Multi-Criteria Decision-Making (MCDM) approaches have been created. The main novelty of this paper is that four MCDM methods, including Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), Fuzzy TOPSIS, VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), and Fuzzy VIKOR, are employed to evaluate menu options. Comparative analysis of MCDM methods is another contribution of this study. The process of evaluating and selecting healthier menu alternatives can become challenging and time-consuming. This study pointed out how crucial it is to conduct comparative analysis using various MCDA methods and to carefully determine the right ones when addressing the issue of selecting the best menu, taking into account the values of the criterion in fuzzy numbers.

A holistic multi-tiered decision framework for evaluating rainwater harvesting potential in arid regions: A case study of the southeastern basin of Djibouti

Rainwater harvesting (RWH) stands as a strategy to mitigate the widespread challenge of water scarcity in arid and semi-arid regions worldwide. The practice of capturing and storing stormwater via different RWH technologies during wet periods can serve as a means of replenishing stressed local aquifers. However, identifying optimal locations conducive to the successful implementation of RWH initiatives accounts for a multi-tiered and intricate challenge. Furthermore, contemporary methodologies utilized to assess the potential of RWH often adhere to conventional paradigms, exhibiting a dearth of sophisticated mathematical foundations. Hence, this study proposes a hybrid approach that integrates the fuzzy analytic hierarchy process (AHP) and the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) algorithms to delineate suitable RWH sites. The proposed framework was subsequently applied in the southeastern basin of Djibouti, a nation facing acute water stress. The assessment of RWH potential in this research is predicated upon twelve decision criteria, organized into three principal dimensions: physical, environmental, and socio-economic aspects. The results highlighted the vitality of environmental (47.67%) and physical (37.98%) dimensions, whereas the socio-economic (14.35%) cluster was deemed less significant according to the established decision framework. Furthermore, the resultant suitability map portrays that a substantial area of the basin, approximately 872.5 km2 (equivalent to 64.25%), exhibits moderate to very high suitability for the implementation of diverse RWH structures, including check dams, percolation tanks, and infiltration ponds. The reliability of the analysis is verified through sensitivity analysis, underscoring the robustness of the decision model. This contributes to the empowerment of decision-makers and the research community, facilitating the creation of accurate RWH potential maps, and thereby advancing effective water resource management strategies for water stressed regions.

Failure mode and effect analysis using VIKOR method based on interval-valued linguistic Z-numbers

Failure mode and effect analysis (FMEA) is an effective quality management tool used to improve product quality and reliability. However, with the application of FMEA, its shortcomings are exposed regarding risk assessment, weight determination, and failure mode risk prioritization. This paper proposes a new FMEA model using VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method based on the Interval-valued linguistic Z-numbers (IVLZNs). Specifically, IVLZNs and the Interval-valued linguistic Z-numbers weighted arithmetic averaging (IVLZNWAA) operator are used to evaluate and aggregate risk information of failure modes; the maximum deviation method is used to determine the weight of risk factors; the IVLZNs-VIKOR method is used to determine the risk priority of failure modes. Then, a numerical example is given to verify the effectiveness of the proposed model. Finally, a comparative analysis is made to demonstrate the feasibility and rationality of the proposed method.

A software trustworthiness evaluation methodology for cloud services with picture fuzzy information

VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) is one of the most commonly used decision-making technique. This work provides a software trustworthiness evaluation method based on VIKOR technique in a group decision-making (GDM) environment. Entropy is an important measure that refers to the amount of disorder in a decision support system. To quantify the decision quality of decision maker (DM), a new method for determining DM weights is proposed according to the entropy value of decision matrix, which is provided by that DM. A new normalization-projection measure is developed in order to test the closeness between two evaluation matrices in software trustworthiness evaluation process. The group regret measure in VIKOR-based GDM method is based on two negative reference matrices in this model. A new ranking method with classification is also developed in this work. Aiming at the complex and changeable environment, these new measures and methods are expected to enrich VIKOR techniques and to play a constructive role in group decision support systems. The feasibility and practicability of developed method are verified by some experiments. This study finds that the different methods (models) may have different results in situations where the same decision data are provided by DMs; and this study also finds that the different parameters may have different results in situation where the decision model is same. The practical implications of developed GDM method can apply not only to software trustworthiness evaluation, but also to many other product quality evaluations.

Towards Efficient Energy Solutions: MCDA-Driven Selection of Hybrid Renewable Energy Systems

In these days of growing awareness on Renewable Energy Sources and their benefits, there is a major issue that needs to be considered, which is selection of suitable Hybrid Renewable Energy System (HRES) among the vast multitude of choices. In this paper, multiple Multi Criteria Decision Analysis (MCDA) techniques are proposed to select the best among a choice of six HRES Systems using different criteria including but not limited to net present cost (NPC), operating cost, renewability fraction, CO2 & NOx emissions etc. The criteria weights are obtained using Analytical Hierarchy Process (AHP) based on the preference order of the criteria. The decision matrix is obtained from the statistical data of the different HRES and using different MCDA techniques such as Multi-Objective Optimization on the Basis of Ratio Analysis (MOORA), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), rankings are given to the HRES systems based on their closeness to the ideal solution. These rankings are helpful in the selection of suitable HRES configuration for normal household purposes. Since cost aspects are given greater preference, the obtained rankings lean more towards economically affordable solutions without compromising on the number of units generated.

Conceptual design decision-making considering multigranularity heterogeneous evaluation semantics with uncertain beliefs

Conceptual design decision-making, as an important stage of new product development, is used to select the most appropriate design by decision-makers (DMs) carrying out semantic judgments of conceptual schemes (CSs). However, evaluation semantics involve uncertainties such as subjectivity, randomness, and heterogeneity, and how to capture and handle these uncertainties is one of the challenging topics. Previous studies have focused on the introduction of heterogeneous semantics with different expressions for CS ranking while neglecting the negative impact of multigranularity semantics as well as fuzzy cognition on CS decision results. Furthermore, the randomness embedded in the evaluation semantics has not yet been addressed in heterogeneous semantics integration. To fill these gaps, a conceptual design decision-making approach considering multigranularity heterogeneous evaluation semantics with uncertain beliefs is proposed. First, multigranularity semantics with uncertain beliefs are assigned by DMs, and an initial decision matrix for CSs with a mixed distribution of crisp values, interval values, and monotonic values is constructed. Second, two transformation rules for the normal cloud model and the exponential cloud model are constructed to transform the multigranularity heterogeneous semantics into cloud models, and the cloud model decision matrix is built. Third, by generating random numbers based on the distribution of cloud models to construct the dominance matrix, the Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) model is used to select the optimal CS. A case study of a tree climbing and trimming (TCT) machine is used to validate the effectiveness of the proposed model, and the sensitivity analysis and comparison results confirm the practicality of the concept selection process considering the multigranularity heterogeneous evaluation semantics.

Evaluation of the Sustainable Forest Management Performance in Forestry Enterprises Based on a Hybrid Multi-Criteria Decision-Making Model: A Case Study in China

Sustainable Forest Management (SFM) can fully use forest resources and improve the economic, environmental, and social sustainability of forest areas. Forestry enterprises play a crucial role in the implementation of SFM. However, the previous literature on SFM pays little attention to the subject of forestry enterprises. This paper aims to extend research on SFM from a macro perspective to the micro level of forestry enterprises. Taking the Triple Bottom Line (TBL) as a theoretical framework and the Montreal Process Criteria and Indicators (MP C&Is) as a basis, this paper constructs an indicator system to evaluate the performance of SFM of forestry enterprises from economic, social, and environmental aspects. Then, we apply the hybrid Multi-Criteria Decision-Making (MCDM) methods, i.e., the Best–Worst Method (BWM) and the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, to construct the methodological system for SFM performance evaluation of forestry enterprises. Through a questionnaire survey of 68 academics and researchers, we determine the weights of the SFM indicators and select a representative forestry enterprise as a case study. The effectiveness of this SFM performance evaluation model is then demonstrated through its application to the case study of forestry enterprises in China. Through the application of the model, this paper evaluates the enterprise’s SFM performance over the five-year period 2017–2021 and proposes appropriate policy recommendations and improvements. It is found that environmental factors are the primary factors of SFM in forestry enterprises. Forestry enterprises should not only pay attention to economic benefits but also to the use of forest resources and the protection of forest ecosystems to better achieve SFM.

A compromise decision-support technique with an augmented scoring function within circular intuitionistic fuzzy settings

The VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method provides a valuable means of evaluating options based on assessment criteria, intending to generate the finest compromise options through multiple-criteria optimization. However, decision-making often involves uncertainty, where decision-makers may lack complete information or struggle to predict outcomes accurately. Circular intuitionistic fuzzy (C-IF) sets offer a versatile way to represent uncertainty and indecision, adding circularity to intuitionistic fuzzy sets' membership and non-membership. C-IF sets bring sophistication by incorporating circular functions to address complicated ambiguity, alongside assigning membership and non-membership components. This research aims to create a C-IF VIKOR decision-support method to handle multiple-criteria compromise solutions with C-IF uncertainties. The study focuses on enhancing the augmented scoring function and Chebyshev distance metric in C-IF surroundings. The augmented scoring function exhibits unique characteristics, including a direct relationship between membership and function value, an inverse correlation with nonmembership, and reflection of information reliability. The enhanced C-IF Chebyshev distance measure combines radial and membership/nonmembership distances, considering their special features. The proposed C-IF VIKOR technique utilizes these concepts to identify superior and inferior options and determine the finest compromise solution using an identification mechanism and VIKOR indices. The method is demonstrated in the context of healthcare waste disposal and will undergo sensitivity analyses and comparative studies to showcase its advantages, adaptability, and robustness.

TODIM-VIKOR method for quality evaluation of tourism rural landscape planning and design with 2-tuple linguistic neutrosophic numbers

With the continuous deepening of the construction of urban-rural economic integration in China, rural construction activities supported by rural revitalization strategies have changed the development thinking of rural economy. While implementing the goal of rural ecological economy, optimizing the rural living environment has become one of the important contents of rural revitalization, including the planning and design of rural landscapes. Rural landscape planning and design need to comprehensively consider the adaptability of landscape and rural ecological environment, emphasize the impact of rural spatial structure differences on landscape planning and design, and achieve scientific and humanized landscape planning and design, thereby creating a more warm, natural, and comfortable rural living space. The quality evaluation of tourism rural landscape planning and design is a multiple attribute group decision making (MAGDM) problems. Recently, the TODIM (an acronym in Portuguese of interactive and multicriteria decision making) and VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) method has been inaugurated to cope with MAGDM issues. The 2-tuple linguistic neutrosophic sets (2TLNSs) are inaugurated as a effective tool for characterizing uncertain information during the quality evaluation of tourism rural landscape planning and design. In this paper, the 2-tuple linguistic neutrosophic TODIM-VIKOR (2TLN-TODIM-VIKOR) method is inaugurated to solve the MAGDM under 2TLNSs. In the end, a numerical case study for quality evaluation of tourism rural landscape planning and design is inaugurated to confirm the proposed method.

An improvement to the interval type-2 fuzzy VIKOR method

Vlsekriterijumska optimizacija i kompromisno resenje (VIKOR) method is one of the most popular multiple criteria decision making (MCDM) techniques in which, the optimal alternative is determined based on an agreement between maximum group utility and minimum individual regret. Despite VIKOR presents important advantages regarding other techniques for decision situations, it may result in a situation where an alternative with high measures for most criteria and low value for one criterion is not chosen as the optimal alternative. Thus, VIKOR may lead to unreasonable and inconsistent results and cannot present true situation of alternatives in indices’ list. The goal of this paper is to present an improved extended version of interval type-2 fuzzy VIKOR (IT2FVIKOR) method for relieving the drawbacks of usual IT2FVIKOR. The proposed indices present more continuous and logical values than prior one such that better ranking results obtain for the MCDM problems. In order to demonstrate effectuality of the suggested method, a case study and an illustrative example are performed. Eventually, the extracted ranking upshots are analyzed with the others.

Comparative analysis of fuzzy multi-criteria decision making methods for selecting sustainable battery suppliers of battery swapping station

ABSTRACT Sustainable battery supplier (SBS) selection of battery-swapping station belongs to a complex multi-criteria decision-making (MCDM) problem due to the fact that included multiple and often conflicting criteria. To this end, this study presents a comparative analysis of selecting SBS using four fuzzy MCDM methods, and a case is executed to compare the ranking results obtained by the proposed four MCDM methods. From the weighting results of criteria, it is observed that economic criteria is the first priority in all evaluation criteria, followed by the technical, social, and environmental criteria in descending order. In terms of the priorities and recommendations of multiple SBSs for the battery swapping station, the comparative analysis demonstrates that the rankings of all alternatives obtained by all approaches are in high agreement, except that determined by fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) slightly varies from the other three approaches, and none of these MCDM methods are deemed to be absolutely “perfect”. If possible, we recommend that more than one method should be applied to the same problem to provide a more comprehensive decision basis. If not possible, it is suggested to use the fuzzy VIKOR since it shows more superior potential in sustainable supplier decision analysis.

Sustainable supplier selection based on VIKOR with single-valued neutrosophic sets.

Considering economic, environmental, and social issues, the sustainability of the supply chain has drawn considerable attention due to societal and environmental changes within the supply chain network. The strategic study of the entire supply chain process and maximizing an organization's competitive advantage depend heavily on supplier selection based on sustainable indicators. Selecting sustainable suppliers for the supply chain is challenging since it is a multi-criteria decision-making (MCDM) problem with significant uncertainty in the decision-making process. This study uses the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) technique and single-valued neutrosophic sets (SVNS) to deal with the challenge of choosing a sustainable supplier with insufficient information. This method reduces the influence of personal experience and preference on the final evaluation results and the problem of excessive individual regret caused by factor correlation and improves the consistency of evaluation results. Finally, the method's success and adaptability are demonstrated by sensitivity analysis and additional comparison analysis, and the benefits and drawbacks of the suggested framework are examined. Compared to other approaches, it can assist decision-makers in communicating fuzzy and uncertain information, offering a perspective and approach for MCDM in the face of such situations, and helping them select suppliers of high caliber and who practice sustainable business practices.

Reconfigure and evaluate consumer satisfaction for Open API in advancing FinTech

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