Hybrid Multiple Criteria Decision Making Methods Research Articles

The selection of renewable energy technologies using a hybrid subjective and objective multiple criteria decision making method

The use of renewable energy technologies is a key factor for sustainable development but their selection from several alternatives is a difficult task that relies on the careful assessment of relevant criteria. While Multiple Criteria Decision Making (MCDM) methods have been used successfully in various renewable energy technology selection problems, the decision process becomes more challenging when preferential judgements are made on the basis of non-homogenous and imprecise input data, and when there is uncertainty due to disparities among decision makers. This paper presents a hybrid MCDM method capable of overcoming these problems by taking into account quantitative and qualitative data under a probabilistic environment in the context of group decision making. In this method, qualitative data is fuzzified and used along with quantitative data to develop a hybrid model. A coefficient factor allows decision makers to vary the weight of each quantitative model so that the resultant criteria weights and overall alternatives’ scores consider both subjective considerations and objective information. An example is presented to showcase the usability of the method developed for ranking and evaluating renewable energy technologies in the mining industry. In addition, the impact of different coefficient factors on the final results was assessed by means of sensitivity analysis. The results indicate that the method developed is able to minimise the loss of valuable objective information, caused by the subjective bias of qualitative weights during the evaluations, by adjusting the coefficient factors of the hybrid model during the calculations.

Identifying Key Financial, Environmental, Social, Governance (ESG), Bond, and COVID-19 Factors Affecting Global Shipping Companies—A Hybrid Multiple-Criteria Decision-Making Method

The international shipping industry is the largest transportation system in the world. However, shipping stock prices were highly volatile during the 2020–2021 COVID-19 pandemic. The purpose of this study is to identify the causal relationships of the four dimensions (financial performance, bond financing, environmental, social, governance, and COVID-19) and 20 criteria affecting the sustainability of global shipping companies. The research scope includes a sample of nine listed international shipping companies accounting for 49% of the global market share with data collected from 2010 to 2020. Survey responses from 15 investment experts were also obtained. We applied a hybrid multiple criteria decision-making (MCDM) method integrating the Decision-Making Trial and Evaluation Laboratory (DEMATEL), analytic network process, and modified VlseKriterijumska Optimizacija I Kompromisno techniques to be the DANP-mV model to identify the causal relationships among the dimensions and criteria, providing ways of narrowing the performance gaps of shipping companies. The results indicate that financial performance is the main cause affecting COVID-19 and ESG practices. The ESG practices influence bond financing. The largest performance gaps across shipping companies include earnings per share (EPS), yield to maturity, corporate social responsibility (CSR), and timely delivery. The findings of this study suggest that shipping companies may focus on gross profit margin to improve EPS, term to maturity to enhance yield to maturity, social distancing policy to meet timely delivery, and the board size to enhance corporate social responsibility (CSR). The outcome of this study aids shipping companies in prioritizing their resources and investors in selecting shipping company stocks in response to COVID-19.

Evaluation of the Consumer Interaction Capability of the Virtual Brand Community of Chinese Mobile Internet Enterprises Based on the Hybrid MCDM Method

E-commerce has grown considerably with increasing access to the Internet. As a means of e-commerce, the virtual brand community (VBC) has become one of the important channels for brand enterprises to promote products, enhance brand awareness and compete with enterprises in the digital economy. The most important task of any website is the provision of tailored information and services to satisfy client needs. This research aimed to evaluate the status of websites and services provided by Chinese mobile internet enterprises. Based on the Fogg behaviour model, initial criteria and sub-criteria were constructed, and a new hybrid multiple criteria decision-making (MCDM) model was used in this study that combines the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique and the analytic network process (ANP) method to determine the interaction between factors and to determine the weight of each factor. Finally, the PROMETHEE method was utilised to rank and develop the consumer interaction capability of the VBC of Chinese mobile internet enterprises. Once these perceptions were captured, among the three criteria determined for the evaluation of the VBC of different mobile internet enterprises, affective involvement was the most important criterion, followed by motivation and environment triggers. Moreover, the VBCs of three communication enterprises were evaluated and ranked to validate the proposed model.

A New Hybrid MCDM Model for Personnel Selection Based on a Novel Grey PIPRECIA and Grey OCRA Methods

People represent one of the most significant resources of an organization, and therefore, personnel selection is one of the problems that organizations have increasingly been facing. The criteria that influence the final decision are usually opposing, so the application of multiple-criteria decision-making methods (MCDM) represents a suitable way for the facilitation of the given process. Additionally, the decision environment is characterized by the vagueness and uncertainty and, because of that, it is very hard to express the criteria over the exact crisp numbers. To acknowledge the unpredictability and obscurity of the available information important for the selection of the optimal candidate, a hybrid grey MCDM model for personnel selection is proposed in this paper. As an extension of the PIPRECIA method, the novel Grey Pivot Pairwise Relative Criteria Importance Assessment—the PIPRECIA-G method—is proposed and used for the determination of criteria importance. The PIPRECIA-G method preserved the good features of the PIPRECIA, but its superiority is reflected in its ability to deal with input data that are vague and grey. For the final ranking of the considered alternative candidates, the OCRA-G method is used. Basing the decision process and candidate selection on the two grey extended MCDM methods contributes to the increase of the reliability and confidence in the performed selection.

Evaluating the Investment Projects of Spinal Medical Device Firms Using the Real Option and DANP-mV Based MCDM Methods.

In an era of global aging, spinal and other joint degeneration issues have become a major problem for many elders. Bone-related operations have become the largest percentage of surgeries, accounting for 40% of the top 10 operations in the United States. Further, these spine-related operations are now ranked second among all bone-related operations. Due to this enormous and daily increasing market demand, more and more firms have started to pay closer attention to related medical devices and products. The global venture capitalists (VCs) have also started to follow the mega trend and will continue to invest heavily in this industry. Although most VCs recognize that investing in firms that produce innovative spinal products or devices is a must, very few practical managers or research scholars have defined the appropriate evaluation methods for these firms to use. The traditional net present value (NPV) method, which does not consider operation flexibility and changes in strategy, is far from the reality. The real option method can reveal the vagueness and flexibilities of the values being embedded in the investment projects at spinal medical device firms. However, the real option method is strictly quantitative. Usually, the evaluation aspects contain qualitative factors or local criteria which are hard to quantify in monetary terms. Thus, the adoption of multiple criteria decision making (MCDM) methods that can manipulate both quantitative and qualitative factors will be very helpful in evaluating and selecting investment cases like the spinal medical device firms, where both quantitative and qualitative factors should be considered. An analytical framework that consists of hybrid MCDM methods and the real option method will thus be very useful to evaluate the newly established firms producing spinal medical devices. Therefore, the authors propose a real option valuation as well as the Decision-Making Trial and Evaluation Laboratory (DEMATEL) based analytic network process (DANP) and the modified VIšekriterijumsko KOmpromisno Rangiranje (VIKOR) method (DANP-mV) based MCDM framework for evaluating the investment projects offered by these firms of spinal medical devices. An empirical study based on three newly established spinal medical device companies specializing in vertebral compression fracture (VCF) surgical devices was used to demonstrate the feasibility of the proposed analytical framework. Sensitivity analysis is performed to determine the influence of modeling parameters on ranking results of alternatives. This analytical framework can thus serve as a tool for VCs to use to determine the value of a potential candidate for investment. The proposed method can also serve as an effective and efficient tool for investment projects in other fields.

Equipment selection in mineral processing - A sensitivity analysis approach for a fuzzy multiple criteria decision making model

Selecting the most suitable mineral processing equipment among feasible alternatives with respect to multiple conflicting criteria is considered a Multiple Criteria Decision Making (MCDM) problem. For example, a type of crusher that might allow a very high throughput is less likely to be used in a mobile plant, so trade-offs between these type of criteria need to be clearly defined in the decision making process. One of the most frequently used MCDM methods is the Analytical Hierarchy Process (AHP) method, which relies on judgements from decision makers that allow for comparisons to be made between alternatives (e.g. the type of equipment) or criteria (e.g. the characteristics of the equipment that are of interest). However, AHP is not able to capture the uncertainty associated with the various decision makers’ judgements and the lack of precise information. An integrated constrained fuzzy stochastic analytic hierarchy process (IC-FSAHP) is a new hybrid MCDM method that can be used to overcome the aforementioned limitations of AHP. In order to understand the robustness of AHP based methods, a sensitivity analysis of the decision making results is required. However, sensitivity analyses are not often carried out for fuzzy AHP methods, arguably because of the complexity of some of the procedures involved, the computation time required and the limited resources available to do so. The main objective of this paper is therefore to propose a new sensitivity analysis approach by applying an additional fuzzification factor and disagreement level of decision makers in order to model uncertainty. For this purpose, a case study for the selection of primary crushers was considered. Five types of primary crushers were evaluated with respect to six criteria to showcase the applicability of the proposed approach to assess IC-FSAHP. The results obtained showcase that the proposed sensitivity analysis approach is capable of providing extensive and useful “what-if” information on the decision making results.

Improving Financial Service Innovation Strategies for Enhancing China’s Banking Industry Competitive Advantage during the Fintech Revolution: A Hybrid MCDM Model

The recent emergence and rapid growth of new financial services by financial technology (Fintech) companies have driven banking institutions towards operational innovation in order to gain sustainable competitive advantage. This study aims to conduct an in-depth investigation of the banking sector in response to the challenges brought by Fintech startups. Based on the service innovation theory, we propose a novel hybrid multiple criteria decision-making method (MCDM) to evaluate service innovation strategies for improving the sustainability of China’s banking industry during the Fintech revolution. A six-dimensional model comprising 20 sub-criteria is constructed and both the decision making trial and evaluation laboratory (DEMATEL) technique and DEMATEL-based analytic network process (DANP) are used to explore interrelationships among the indices and their related weights. Finally, the modified VIšekriterijumsko KOmpromisno Rangiranje (VIKOR) method is employed to evaluate performance gaps in the four major types of commercial banks in China—state-owned, joint-stock, city commercial banks, and other credit cooperatives—in the field of service innovation. The improvement priorities, ranked from highest to lowest, are new business partners, new service concepts, organizational innovation, technological innovation, new customer interactions, and new revenue models. These results will provide strategies for the sustainable development of China’s banking industry and the implementation of changes in response to the impact of the Fintech revolution.

Using a Novel Grey DANP Model to Identify Interactions between Manufacturing and Logistics Industries in China

As a crucial part of producer services, the logistics industry is highly dependent on the manufacturing industry. In general, the interactive development of the logistics and manufacturing industries is essential. Due to the existence of a certain degree of interdependence between any two factors, interaction between the two industries has produced a basis for measurement; identifying the key factors affecting the interaction between the manufacturing and logistics industries is a kind of decision problem in the field of multiple criteria decision making (MCDM). A hybrid MCDM method, DEMATEL-based ANP (DANP) is appropriate to solve this problem. However, DANP uses a direct influence matrix, which involves pairwise comparisons that may be more or less influenced by the respondents. Therefore, we propose a decision model, Grey DANP, which can automatically generate the direct influence matrix. Statistical data for the logistics and manufacturing industries in the China Statistical Yearbook (2006–2015) were used to identify the key factors for interaction between these two industries. The results showed that the key logistics criteria for interaction development are the total number of employees in the transport business, the volume of goods, and the total length of routes. The key manufacturing criteria for interaction development are the gross domestic product and the value added. Therefore, stakeholders should increase the number of employees in the transport industry and freight volumes. Also, the investment in infrastructure should be increased.

Evaluation and Selection of Materials for Particulate Matter MEMS Sensors by Using Hybrid MCDM Methods

Air pollution poses serious problems as global industrialization continues to thrive. Since air pollution has grave impacts on human health, industry experts are starting to fathom how to integrate particulate matter (PM) sensors into portable devices; however, traditional micro-electro-mechanical systems (MEMS) gas sensors are too large. To overcome this challenge, experts from industry and academia have recently begun to investigate replacing the traditional etching techniques used on MEMS with semiconductor-based manufacturing processes and materials, such as gallium nitride (GaN), gallium arsenide (GaAs), and silicon. However, studies showing how to systematically evaluate and select suitable materials are rare in the literature. Therefore, this study aims to propose an analytic framework based on multiple criteria decision making (MCDM) to evaluate and select the most suitable materials for fabricating PM sensors. An empirical study based on recent research was conducted to demonstrate the feasibility of our analytic framework. The results provide an invaluable future reference for research institutes and providers.

A novel hybrid MCDM model combining the SAW, TOPSIS and GRA methods based on experimental design

Multiple criteria decision-making (MCDM) is a difficult task because the existing alternatives are frequently in conflict with each other. This study presents a hybrid MCDM method combining simple additive weighting (SAW), techniques for order preference by similarity to an ideal solution (TOPSIS) and grey relational analysis (GRA) techniques. A feature of this method is that it employs an experimental design technique to assign attribute weights and then combines different MCDM evaluation methods to construct the hybrid decision-making model. This model can guide a decision maker in making a reasonable judgment without requiring professional skills or extensive experience. The ranking results agreed upon by multiple MCDM methods are more trustworthy than those generated by a single MCDM method. The proposed method is illustrated in a practical application scenario involving an IC packaging company. Four additional numerical examples are provided to demonstrate the applicability of the proposed method. In all of the cases, the results obtained using the proposed method were highly similar to those derived by previous studies, thus proving the validity and capability of this method to solve real-life MCDM problems.

A Novel Hybrid MCDM Procedure for Achieving Aspired Earned Value Project Performance

A better-performing project gains more subsequent businesses. Many organizations worldwide apply an earned value management (EVM) system to monitor and control their projects’ performance. However, a successful EVM application requires handling multiple interinfluenced criteria with feedback effects for decision-making and continuous improvements throughout the application life cycle. The conventional decision approaches assume that preferences between criteria are independent and put their focuses on decision-making. This study employs a hybrid multiple criteria decision-making (HMCDM) method to devise a novel procedure to fulfil the deficiencies. The proposed procedure enables us to evaluate interinfluence effects and gap indices among criteria/dimensions/alternatives and then systemize the evaluation results in a context of influential network relation map (INRM). The INRM provides managers with visual information to find a route in making application decisions, while identifying critical gaps for continuous improvements. A numerical example is presented to illustrate the applicability of the proposed procedure. The results show that, by employing the HMCDM method, the proposed procedure can provide organizations with a foundation to ensure that the aspired EVM application outcomes are achieved at different levels within an organization.

HYBRID MULTIPLE CRITERIA DECISION MAKING METHODS: A REVIEW OF APPLICATIONS IN ENGINEERING

To support evaluation and selection processes in engineering, formal decision making methods can be used. A great number of works applying diverse multiple criteria decision making (MCDM) techniques for engineering problems have been published recently. A new approach of hybrid MCDM methods has been developing rapidly during the past few years. The current paper aims at filling the gap and to summarize publications related to applications of hybrid MCDM for engineering. The study is limited solely on papers referred in Thomson Reuters Web of Science Core Collection academic database. It aims to review how the papers have been distributed by period of publishing and by country, which multiple criteria decision making methods have been used the most frequently in developing hybrid approaches and in what domains the methods have been applied. For a more detailed analysis of applications, journal articles from engineering research area were grouped by research domains and further by analyzed issues. Findings of the current review paper confirm that hybrid MCDM approaches, due to their abilities in integrating different techniques, can assist in handling miscellaneous information taking into account stakeholders’ preferences when making decisions in engineering.

Strategic project portfolio selection for national research institutes

As global competition intensifies, many national research institutes (NRIs) are investing substantial resources in research and development (R&D) to gain competitive advantage and develop the national economy. However, R&D investment involves a high degree of market and technological uncertainty. The literature on project portfolio selection focuses on either quantitative economic benefits or complex criteria to assess project(s). By emphasizing the features of NRIs, the present study proposes a decision model for evaluating a project portfolio at the early initiation stage. This decision model rests on a strategy for differentiating products and services. The decision model provides a solution to a market need to maximize benefits through differentiation. A systematic hybrid multiple-criteria decision-making (MCDM) method comprising a modified Delphi method (MDM), a decision-making trial and evaluation laboratory (DEMATEL) method, and an analytic network process (ANP) offers a systematic approach to the project portfolio-selection problem. The present empirical study on the selection of alternative R&D projects in NRIs investigates the flexible electronics industry, using the hybrid MCDM method to test the decision model's effectiveness. The present study also discusses cognitive differences between NRIs and for-profit organization in terms of their R&D portfolio selection.

Decision making on business issues with foresight perspective; an application of new hybrid MCDM model in shopping mall locating

Shopping malls are one of the glories of metropolises with their attractive shops and a wide variety people who are walking in order to purchase goods. Location of a shopping mall is one of the critical criteria, because it can influence the success of the project. In addition, selecting an appropriate location to establish a new shopping mall is a sophisticated, time consuming and risky decision. Commonly multi-factors should be considered in the decision making model. Thus, a comprehensive model should be considered for similar studies. Moreover, the foresight perspective can be necessary for the future competitiveness of the project. Decision makers need powerful tools for the process of the decision making, for this aim two Multiple Criteria Decision Making (MCDM) methods are applied in our model. Stepwise Weight Assessment Ratio Analysis (SWARA) is applied to decision making in order to prioritize and calculating the relative importance of the criteria. Then, Weighted Aggregated Sum Product Assessment (WASPAS) methodology is used to evaluate potential alternatives. Tehran is considered as a real example of this research and potential places for this mean considered in research. This brand-new hybrid MCDM method is presented in this research as a powerful framework is decision making. This framework can be useful as an appropriate framework for solving locating issues in other companies.

Developing a new hybrid MCDM method for selection of the optimal alternative of mechanical longitudinal ventilation of tunnel pollutants during automobile accidents

Abstract Breathable air inside the tunnel is an undeniable necessity and beside natural ventilation, the tunnel should be reliably organized, to automatically provide healthy air under different conditions. Among methods of tunnel ventilation, longitudinal and transverse modes are the most common mechanical methods. This research is focused on selection of the optimal method for mechanical longitudinal ventilation of tunnel pollutants from four presented models. In terms of this research, the authors used SWARA (Step-wise Weight Assessment Ratio Analysis) as one of the most versatile MCDM (Multiple-Criteria Decision-Making) methods for managerial decision making in complex situations with multiple and varied measures. Fourteen experts of different fields were involved. The research model was established based on expert ideas and the following criteria: smoke control (C 1), safety level (C 2), design complexity (C 3), investment costs (C4), increasing concentration of pollutants until portal (C5), smoke la...

Next Generation Passive Optical Networking Technology Predictions by Using Hybrid MCDM Methods

The evolution of broadband telecommunication technologies has enabled applications over networks, which, in turn, has enabled the emergence of novel network services and applications such as VoIP and video on demand in triggering demand for higher network bandwidth. Passive Optical Networking (PON) is suitable for eliminating bandwidth insufficiency, so national governments and communities are observing the emergence of Fiber-To-The-Home (FTTH) technologies. Ethernet-based Passive Optical Networks (EPON) and Gigabit-based PON (GPON) are two candidates for next-generation PON in bandwidth efficiency. To predict which is more suitable nationally, we define a foresight framework based on hybrid Multiple Criteria Decision Making (MCDM) methods for selecting the most suitable PON. The development of next-generation PON, including Ethernet PON (EPON) and Gigabit PON (GPON), is introduced and compared. Experts from industry and academia were invited to predict the most suitable next-generation PON for Japan and emerging economies such as Taiwan. Results showed that EPON is most suitable for Japan and GPON most suitable for Taiwan. Results for the technological foresight can serve as the basis for national telecommunication policy and business product definition.

Using Hybrid MCDM Methods to Assess Fuel Cell Technology for the Next Generation of Hybrid Power Automobiles

With their huge consumption of petroleum and creation of a large number of pollutants, traditional vehicles have become one of the major creators of pollution in the world. To save energy and reduce carbon dioxide emissions, in recent years national governments have aggressively planned and promoted energy-saving vehicles that use green energy. Thus, hybrid electric vehicles have already become the frontrunners for future vehicles while fuel cells are considered the most suitable energy storage devices for future hybrid electric vehicles. However, various competing fuel cell technologies do exist. Furthermore, very few scholars have tried to investigate how the development of future fuel cells for hybrid electric vehicles can be assessed so that the results can serve as a foundation for the next generation of hybrid electric vehicle developments. Thus, how to assess various fuel cells is one the most critical issues in the designing of hybrid electric vehicles. This research intends to adopt a framework based on Hybrid Multiple-Criteria Decision Making (MCDM) for the assessment of the development in fuel cells for future hybrid electric vehicles. The analytic framework can be used for selecting the most suitable fuel cell technology for future hybrid electric vehicles. The results of the analysis can also be used for designing the next generation of hybrid electric vehicles.

Combined DEMATEL technique with hybrid MCDM methods for creating the aspired intelligent global manufacturing & logistics systems

The concept of globalization has been prosperous in the past decades while manufacturing as well as logistics have already become one of the most significant issues in the globalization era. However, while modern globalized firms are leveraging both global manufacturing resources as well as logistics systems for pursuing higher quality, lower cost as well as product differentiation, how to evaluate, selecting an appropriate global manufacturing strategy by considering issues from both aspects of global manufacturing as well as logistics has become one of the most critical and difficult issues. Moreover, how the chosen intertwined global manufacturing as well as logistics system is to be optimized so that the aspired level of the global manufacturing system can be achieved have few been addressed. Thus, this research aims to resolve the above mentioned global manufacturing and logistics strategy selection as well as system reconfiguration issue. A Decision Making Trial and Evaluation Laboratory (DEMATEL) technique based novel multiple criteria decision making (MCDM) method with Analytic Network Process (ANP), Grey Relational Analysis (GRA) as well as VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) will be proposed for selecting and re-configuring the aspired global manufacturing and logistics system. An empirical study based on the global manufacturing and logistics system design of a semiconductor company will be provided for verifying the effectiveness of this proposed methodology.