Simplified MCDM Analytical Weighted Model for Ranking Classifiers in Financial Risk Datasets

A validation scheme for intelligent and effective multiple criteria decision-making

The paper illustrates the application of three Multiple-Criteria Decision-Making (MCDM) methods to the problem of the selection of a new hub airport for a hypothetical European Union (EU) airline assumed to operate within the EU liberalised air transport market. The three MCDM methods used are SAW (Simple Additive Weighting), TOPSIS (Technique for Order Preference by Similarity to the Ideal Solution) and AHP (Analytic Hierarchy Process), and they are applied to a preselected set of alternative airports. The attributes (criteria) are defined to express the performance of particular alternatives (airports) relevant for a Decision-Maker (DM), in this case the EU airline in question. In addition to illustrating the three methods, this application of three different MCDM methods is intended to lead to a preliminary judgment about their usefulness as supplementary decision-making tools for eventual practical use. The example in which seven preselected European airports are ranked according to nine performance criteria, indicates that all three methods, if applied to the same problem and using the same method for determining the importance of the different criteria, produce the same results

Many spatial decision-making problems, such as site selection or land use allocation require the decision-maker to consider the impacts of choice-alternatives along multiple dimensions in order to choose the best alternative. The decision-making process, involving policy priorities, trade-offs, and uncertainties, can be aided by Multiple Criteria Decision making (MCDM) methods. This paper presents a framework for integrating geographical information systems (GIS) and MCDM methods. In this framework the MCDM methods are classified and matched with choice heuristics used by the decision-makers in the presence of competing alternatives and multiple evaluation criteria. Two strategies for integrating GIS with MCDM are proposed. The first strategy suggests linking GIS and MCDM techniques using a file exchange mechanism. The second strategy suggests integrating GIS and MCDM functions using a common database. The paper presents the implementation of the first strategy using PC-ARC/INFO, a file exchange module, and four different MCDM computer programs.

An online voting system is an election system that manages the election process. This is a medium for the voters to cast their votes. It is also being used to calculate the votes collected from the voters to choose the representative for their own faculty. A typical voting system is based on a single attempt for each candidate being voted. The voting does not reflect the criteria implies to the characteristic of the candidate that going to be the student leader. To be a student leader, the student should fulfil the requirement such as good academic results, interpersonal skills with society, involving in activities of university and etc. Although the current voting system is able to maximize the participation of the voters, the voters may blindly vote the ballots casually due to they do not know the details of the candidates and the result is low quality and low public’s trust in the selected candidate. In this study, the aim is to develop an interactive online voting system that have ranking feature with MCDM method which allow online voting system to collect high-quality results from the voters. The Multiple Criteria Decision Making (MCDM) method is used in the voting system while choosing the candidate. MCDM can let the voters make decision making or selecting the candidate based on the criteria that suit the position. The study starts with the literature study on implementing MCDM for a voting system. Then, a survey will be made to get the users’ views on the with and without implementation of the MCDM method in an online voting system. The expected result of the study is to investigate the current implementation of MCDM as a tool for decision making, then identify the possibility of adopting MCDM for the online voting system while choosing the representative for faculty students’ society. As a conclusion from the survey from the users’ views, it shown that most of the users thinks that the system with the implementation with MCDM method is less time consuming and able to produce high quality result compare to the current online voting system. Most of the respondents also stated that they are more preferring to use the online voting system with MCDM method in the future.

During the early years of their establishment, information service providers (ISPs) were viewed simply as 'suppliers of information'. Nowadays, however, the commercialization of the Internet coupled with the progressive advancements in information technology (IT) have seen the business paradigm evolve into so-called electronic commerce (EC), with the result of an ever-increasing demand from enterprises for new types of information services (IS) to facilitate and coordinate their daily operations. Now, as the role of the ISP is continually changing, and the content of IS becomes ever broader, an effective means of the assessment of ISPs has become a critical issue in any enterprise's decision on the eventual selection of a competent ISP. Hence, the purpose of this paper is to establish a multiple criteria decision-making (MCDM) framework for assessing and evaluating ISPs. Through a review of the literature of previous works on relevant topics, this paper begins by proposing a hierarchy structure for the problems involved in ISP assessment. Based on the hierarchy structure, both additive (analytic hierarchy process) and non-additive (fuzzy measure and fuzzy integral) MCDM methods are used in this study to show the relative importance of the selection criteria and the dimensions of those criteria. Ten real cases are then employed as illustrative alternatives to demonstrate the synthesis decisions under the application of both MCDM methods, so as to show the applicability of the framework. Finally, we find that there is a distinction between the results of alternative rankings produced by the two MCDM methods, thus the ten alternatives are categorized into four groups.

Comparison of Two MCDM Methodologies in Aircraft Type Selection Problem

Evaluation of clustering algorithms for financial risk analysis using MCDM methods

Information service providers (ISPs) play a pivotal role in facilitating and coordinating enterprises' daily operations by furnishing them with a wide range of information service (IS). Thus, the effective appraisal of ISPs is a critical issue since it critically affects enterprises' decisions on the eventual selection of an appropriate ISP. This study is designed to support those decisions, and it begins by proposing a hierarchy structure for the problems involved in appraising the ISPs. Then, based on the hierarchy structure, both additive (analytic hierarchy process, AHP) and non-additive (fuzzy measure and fuzzy integral) multiple criteria decision-making (MCDM) methods are applied. The results of AHP show that the first three most important dimensions are: performance of information systems, awareness of and response to customer requirements, and performance of networking. Detailed investigation of each criterion indicates that data security and user privacy protection, virus and hacker damage prevention, the maintenance of normal IS operations, rapid resolution of customer problems and stable networking with increasing speed are the more important criteria. For non-additive measurement, the fuzzy measure of various criteria and their combinations within each dimension are obtained for subsequent calculation of the value of fuzzy integral. Finally, ten real cases are employed as illustrative alternatives to demonstrate the synthesis decision under the application of both MCDM methods.

Abstract: A major global problem, water scarcity has a negative impact on ecosystems, socioeconomic activity, and millions of people. Effective water resource management calls for well-informed decision-making processes that consider many factors and their respective importance. The goal of this case study is to use the Multiple Criteria Decision-Making (MCDM) method to address the problem of ranking water scarcity. The study starts out by developing a set of pertinent standards for evaluating water shortage, including water availability, population demand, storage capacity, total population of the household, accessibility of a nearby source, distance to a perennial source, use of rainwater harvesting, number of animals in the household, water obtained from a public supply, and manual water collection methods. Surveys are used to gather information on these criteria, as well as statistical reports, remote sensing, and expert opinions. To ensure comparability across many parameters, the collected data are subsequently analysed and standardized. The regions are then ranked according to the severity of their water scarcity using a suitable MCDM approach. Using the MCDM method, decision-makers can consider their preferences and opinions as well as give various criteria proportionate weights based on their importance. The case study demonstrates how MCDM was used in the study area's battle against water scarcity. Policymakers and stakeholders can utilize the data to identify families that are experiencing the greatest levels of water scarcity and then priorities solutions based on those findings. Furthermore, sensitivity analysis can be performed to assess how well the ranking results hold up under other weightings and criteria. The results of this case study provide a systematic and all-encompassing strategy, which advances water resources management tactics also the results can be further used to prepare a Water Scarcity Zonation Map in ArcGIS or QGIS using RS&GIS method

The product low-carbon design is the key to decrease carbon emissions in manufacturing. The multiple criteria decision-making (MCDM) method has been widely used in solving the design schemes preference choosing problems. However, the existed MCDM method has two primary problems facing the product low-carbon design cases: (i) How to clarify the coupling relationship between low-carbon decision criteria? (ii) How to fuzzily express the low-carbon-orient product design schemes? To solve these problems, we proposed a novel MCDM method for product low-carbon design. It combines the coupling network analysis with the interval hesitant fuzzy set entropy theory into MCDM process. We used a case study of injection molding machine low-carbon design to verify the proposed MCDM method. It turns out that the proposed MCDM method can help us make more rational and equitable decisions among alternative low-carbon schemes.

An Adjusted Decision Support System through Data Mining and Multiple Criteria Decision Making

The influence of the ongoing COVID-19 pandemic that is being felt in all spheres of our lives and has a remarkable effect on global health care delivery occurs amongst the ongoing global health crisis of patients and the required services. From the time of the first detection of infection amongst the public, researchers investigated various applications in the fight against the COVID-19 outbreak and outlined the crucial roles of different research areas in this unprecedented battle. In the context of existing studies in the literature surrounding COVID-19, related to medical treatment decisions, the dimensions of context addressed in previous multidisciplinary studies reveal the lack of appropriate decision mechanisms during the COVID-19 outbreak. Multiple criteria decision making (MCDM) has been applied widely in our daily lives in various ways with numerous successful stories to help analyse complex decisions and provide an accurate decision process. The rise of MCDM in combating COVID-19 from a theoretical perspective view needs further investigation to meet the important characteristic points that match integrating MCDM and COVID-19. To this end, a comprehensive review and an analysis of these multidisciplinary fields, carried out by different MCDM theories concerning COVID19 in complex case studies, are provided. Research directions on exploring the potentials of MCDM and enhancing its capabilities and power through two directions (i.e. development and evaluation) in COVID-19 are thoroughly discussed. In addition, Bibliometrics has been analysed, visualization and interpretation based on the evaluation and development category using R-tool involves; annual scientific production, country scientific production, Wordcloud, factor analysis in bibliographic, and country collaboration map. Furthermore, 8 characteristic points that go through the analysis based on new tables of information are highlighted and discussed to cover several important facts and percentages associated with standardising the evaluation criteria, MCDM theory in ranking alternatives and weighting criteria, operators used with the MCDM methods, normalisation types for the data used, MCDM theory contexts, selected experts ways, validation scheme for effective MCDM theory and the challenges of MCDM theory used in COVID-19 studies. Accordingly, a recommended MCDM theory solution is presented through three distinct phases as a future direction in COVID19 studies. Key phases of this methodology include the Fuzzy Delphi method for unifying criteria and establishing importance level, Fuzzy weighted Zero Inconsistency for weighting to mitigate the shortcomings of the previous weighting techniques and the MCDM approach by the name Fuzzy Decision by Opinion Score method for prioritising alternatives and providing a unique ranking solution. This study will provide MCDM researchers and the wider community an overview of the current status of MCDM evaluation and development methods and motivate researchers in harnessing MCDM potentials in tackling an accurate decision for different fields against COVID-19.

This research presents a short review of Multiple Criteria Decision-Making (MCDM) methods and research in various fields, including marketing and business management. The academic literature shows that MCDM methods in the area of marketing are used by academics to solve problems related to the positioning of products and services, market segmentation, brand management, promotion and advertising strategies, product development and market entry strategies, customer relationship marketing and channel distribution. With regard to business and management domains they are used to prioritize various decision-making aspects, like project assessments, resource allocation, strategic planning, risk management, performance evaluation, supplier and vendor selection, human resource management and strategic investment decisions. We can claim that in both domains, MCDM brings a systematic and transparent approach to decision-making, helping marketing managers to make more informed and objective choices. In summary, the continual refinement of these methods and the integration of cutting-edge technologies hold promise for further enhancing the effectiveness and efficiency of decision-making processes in the dynamic landscape of business and management. Further, the analysis highlights emerging trends and challenges for the future of MCDM research.

Multiple criteria decision making (MCDM) is a process of evaluating alternatives against relevant decision making criteria. Several methods are available to facilitate the evaluation steps. This paper deals with a rural water supply problem in the coastal areas of Bangladesh. Three different MCDM methods – weighted summation, analytical hierarchy process, and novel approach to imprecise assessment and decision environments – were used to evaluate the suitable water supply alternative. The ranking of alternatives obtained from these MCDM techniques produced similar results. Among five water supply alternatives evaluated, rainwater harvesting systems and deep tube wells scored first and second, respectively, for all three evaluation methods. In addition, sensitivity analyses were carried out for the MCDM techniques and these results did not show drastic variations either. This finding implies that while selection of MCDM technique is important, when evaluating similar problems more emphasis should be given to defining the problem comprehensively and thus selecting the relevant criteria and priorities to factor into the decision problem.

Despite the fast emergent of smartphones in day-to-day activity, the sustainable development of mobile financial services (MFS) remains low partially due to online consumer’s trust and perceived risk. This research broadens the trust and the perceived risk at the multi-dimensional for understanding and prioritizing alternatives of MFS decision. A combined methodology; structural equation modeling (SEM) with two multiple criteria decision-making (MCDM) methods such as a technique for order of preference by similarity to ideal solution (TOPSIS) and analytic hierarchy process (AHP) were applied for data analysis. The two steps SEM-TOPSIS techniques were adopted through a two-types survey on datasets consisting of 538 MFS users, and 74 both experienced MFS users and experts in Togo. The SEM is used for causal relationships and assigning weights for the TOPSIS input. TOPSIS was applied for providing MFS alternative classification, in which the results were compared with prior research using the SEM-AHP technique on the given population. The results via SEM revealed particularly strong support for the dispositional trust and perceived privacy risk. Trust has a negative relationship with perceived risk. Except for perceived time risk, all the antecedents of perceived risk and trust validated the proposed relationship. The findings of TOPSIS uncovered that mobile money transfer (MMT) remains the core application used, followed by mobile payment (MP) and mobile banking (MB) and, therefore, consistent with AHP. However, the TOPSIS technique is better suited to the problem of MFS selection for this study field. This research offers a novel and practical modeling and classification concept for researchers, companies’ managers, and experts in the areas of information technology. The implications, limitations, and future research are provided.