Hybrid Decision-making Model Research Articles

A Hybrid Multidimensional Performance Measurement Model Using the MSD-MPSI-RAWEC Model for Turkish Banks

Abstract The purpose of the paper is to analyze the multidimensional sustainability performance of deposit banks that operate in the Turkish banking industry. For this aim, the current research presents a novel hybrid decision-making model comprising of MSD, MPSI and RAWEC methodologies. In the developed decision-making model, the MSD and the MPSI objective weighting methods are utilized to assign significance weights to the criteria, while the RAWEC, a relatively new technique, is employed for banks' ranking. In order to check the robustness of the recommended model, various sensitivity and benchmark analyses were conducted. According to the findings of the study, the most important criterion in determining the sustainability performance of deposit banks is the total hours spent on employee training. Moreover, the most successful bank in terms of multidimensional sustainability is Garanti BBVA. Furthermore, sensitivity and comparison analyses prove that the integrated framework in this study is a powerful, reliable and useful decision tool that can be utilized in assessing the sustainability performance of banks. Besides, practical and managerial implications based on the findings of the applied decision-making tool are discussed.

A miscellaneous model for comprehensive attractiveness assessment of chemical plants: Integrating chemical hazards, domino effects and plant traits

The growing threat of intentional attacks on major petrochemical plants underscores the urgent need for robust security risk assessments (SRA). Such assessments are widely acknowledged as crucial for risk mitigation and are currently a focus of active research. This study introduces a methodology for assessing the attractiveness of the petrochemical sector to intentional attacks, considering chemical hazards, domino effects, and plant traits. Within this framework, we have identified 12 risk factors that capture the multifaceted nature of targeting incentives, relating to the enterprise, location, population, and other key features. We have developed a hybrid decision-making model that analyzes the interrelationships among these factors and determines their weights, integrating the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and the Analytic Network Process (ANP). The applicability of this method is demonstrated through a detailed case study. The results indicate that our method can effectively rank the attractiveness of chemical plants within a specific region, serving as a preliminary screening phase in the SRA. The findings of the attractiveness assessment may assist in identifying potential targets among numerous existing plants and support the allocation of security resources and the formulation of defensive measures.

Analysis of market environment for smart grid technology investments via facial action coding system-enhanced hybrid decision-making model

PurposeThis paper aims to market analysis on the base many factors. Market analysis must be done correctly to increase the efficiency of smart grid technologies. On the other hand, it is not very possible for the company to make improvements for too many factors. The main reason for this is that businesses have constraints both financially and in terms of manpower. Therefore, a priority analysis is needed in which the most important factors affecting the effectiveness of the market analysis will be determined.Design/methodology/approachIn this context, a new fuzzy decision-making model is generated. In this hybrid model, there are mainly two different parts. First, the indicators are weighted with quantum spherical fuzzy multi SWARA (M-SWARA) methodology. On the other side, smart grid technology investment projects are examined by quantum spherical fuzzy ELECTRE. Additionally, facial expressions of the experts are also considered in this process.FindingsThe main contribution of the study is that a new methodology with the name of M-SWARA is generated by making improvements to the classical SWARA. The findings indicate that data-driven decisions play the most critical role in the effectiveness of market environment analysis for smart technology investments. To achieve success in this process, large-scale data sets need to be collected and analyzed. In this context, if the technology is strong, this process can be sustained quickly and effectively.Originality/valueIt is also identified that personalized energy schedule with smart meters is the most essential smart grid technology investment alternative. Smart meters provide data on energy consumption in real time.

Assessment of road safety performance based on Entropy-RSR model

This paper develops a hybrid decision-making model, Entropy-RSR, for benchmarking road safety for Southeast Asian countries at the regional level. This model generates ranking and grouping of the countries, which provides policymakers and practitioners with a valuable tool for policymaking and decision-making in road safety management.

A hybrid decomposed fuzzy multi-criteria decision-making model for optimizing parcel lockers location in the last-mile delivery landscape

Parcel lockers are considered an effective solution to address inefficiencies in last mile delivery. However, choosing the appropriate location is crucial to provide optimal service and improve logistic performance. Therefore, this research aims to assess the most suitable locations for parcel lockers in Dublin, the capital of Ireland, using a novel hybrid decision-making model. This study seeks to extend the Combinative Distance based Assessment method and integrate the Analytical Hierarchy Process method to handle parcel locker location evaluation problems through Decomposed Fuzzy Sets. The proposed model is a pioneering application in real-life scenarios, contributing to the existing knowledge in this field. The integrated model we propose offers a suitable approach for selecting parcel locker locations. The outcomes of this study will provide valuable insights for policymakers, aiding them in making strategic decisions regarding the selection of parcel locker locations within Dublin city.

A Flight Base Selection for Flight Academy Using a Rough MACBETH and RAFSI Based Decision-Making Analysis

Airport base selection for pilot training academy is an important issue in the aviation industry because incorrect airport selection can have negative impact on flight operations for the flight academy. The aim of this article is to present a novel hybrid decision-making model based on rough numbers for the evaluation of flight training bases (airports). To select the most suitable alternative among five alternatives, a two-stage model is proposed. In the first stage, the measuring attractiveness by a categorical based evaluation technique approach is used to determine the criteria weights. In the second stage, the rough ranking of alternatives through functional mapping of criterion subintervals into a single interval approach is applied to rank the alternative airport bases. The proposed approach provides a new multicriteria framework for evaluating alternatives for the Turkish Airlines Flight Academy pilot training center in Turkey. The results obtained from the case study showed that the proposed approach could be practical for different multicriteria decision-making problems.

Development and Practical Application of Hybrid Decision-Making Model for Selection of Third-Party Logistics Service Providers

Abstract In this study a problematic of logistics service provider selection is discussed. Traditional decision-making techniques are functionally limited and must be adjusted. Modern approach must be based on contemporary tools and information. The aim of this study is to develop a modern, industry-oriented decision-making model for selection of strategic logistics service providers. Main tasks of this study include: to perform critical analysis and comparison of multiple-criteria decision-making methods; to adapt decision-making framework for specific needs of selection of third-party logistics service providers; to collect and analyze industry data related to procurement projects; to develop modern decision-making model for selection of logistics service providers; to perform practical application of developed decision-making model based on collected industry data. The key novelties of this study are developed methodology for collection of industry data for decision-making process, developed hybrid decision-making model for selection of third-party logistics service provider, as well as application of the model. As the result, there is developed decision-making model for selection of 3PL service providers that includes 6 steps.

Gully erosion mapping susceptibility in a Mediterranean environment: A hybrid decision-making model

Gully erosion is one of the main natural hazards, especially in arid and semi-arid regions, destroying ecosystem service and human well-being. Thus, gully erosion susceptibility maps (GESM) are urgently needed for identifying priority areas on which appropriate measurements should be considered. Here, we proposed four new hybrid Machine learning models, namely weight of evidence -Multilayer Perceptron (MLP- WoE), weight of evidence –K Nearest neighbours (KNN- WoE), weight of evidence - Logistic regression (LR- WoE), and weight of evidence - Random Forest (RF- WoE), for mapping gully erosion exploring the opportunities of GIS tools and Remote sensing techniques in the El Ouaar watershed located in the Souss plain in Morocco. Inputs of the developed models are composed of the dependent (i.e., gully erosion points) and a set of independent variables. In this study, a total of 314 gully erosion points were randomly split into 70% for the training stage (220 gullies) and 30% for the validation stage (94 gullies) sets were identified in the study area. 12 conditioning variables including elevation, slope, plane curvature, rainfall, distance to road, distance to stream, distance to fault, TWI, lithology, NDVI, and LU/LC were used based on their importance for gully erosion susceptibility mapping. We evaluate the performance of the above models based on the following statistical metrics: Accuracy, precision, and Area under curve (AUC) values of receiver operating characteristics (ROC). The results indicate the RF- WoE model showed good accuracy with (AUC = 0.8), followed by KNN-WoE (AUC = 0.796), then MLP-WoE (AUC = 0.729) and LR-WoE (AUC = 0.655), respectively. Gully erosion susceptibility maps provide information and valuable tool for decision-makers and planners to identify areas where urgent and appropriate interventions should be applied.

Sustainability metrics and a hybrid decision-making model for selecting lean manufacturing tools

Sustainability metrics and a hybrid decision-making model for selecting lean manufacturing tools

A Multicriteria-Based Comparison of Electric Vehicles Using q-Rung Orthopair Fuzzy Numbers.

The subject of this research is the evaluation of electric cars and the choice of car that best meets the set research criteria. To this end, the criteria weights were determined using the entropy method with two-step normalization and a full consistency check. In addition, the entropy method was extended further with q-rung orthopair fuzzy (qROF) information and Einstein aggregation for carrying out decision making under uncertainty with imprecise information. Sustainable transportation was selected as the area of application. The current work compared a set of 20 leading EVs in India using the proposed decision-making model. The comparison was designed to cover two aspects: technical attributes and user opinions. For the ranking of the EVs, a recently developed multicriteria decision-making (MCDM) model, the alternative ranking order method with two-step normalization (AROMAN), was used. The present work is a novel hybridization of the entropy method, full consistency method (FUCOM), and AROMAN in an uncertain environment. The results show that the electricity consumption criterion (w = 0.0944) received the greatest weight, while the best ranked alternative was A7. The results also show robustness and stability, as revealed through a comparison with the other MCDM models and a sensitivity analysis. The present work is different from the past studies, as it provides a robust hybrid decision-making model that uses both objective and subjective information.

Evaluating building wayfinding performance in healthcare environment: a novel hybrid decision-making model

The goal of this study is maintained as the process of establishing and validating an evidence-based approach for assessing the quality of hospital’s wayfinding from an environmental standpoint and creating an evaluation tool for the building’s wayfinding performance (WP). To do this, the integrated Multiple-criteria decision-making (MCDM) technique was utilized to examine the independent linkages between users’ movement dynamics based on Factor Analysis and the D-ANP (Decision-making trial and evaluation laboratory (DEMATEL) based Analytical Network Process (ANP)) method. In this regard, experts gave each model’s variable a weight and a significant value. Thus, findings show that experts classified sixteen indicators into three dimensions in the proposed model: physical data (with 50% influence on building wayfinding (BW)), environmental representation data (with 33% influence on BW), and symbolic data of the environment (17% influence on BW). In validating the scheme, the findings met the case criteria, demonstrating tool’s practical feasibility.

A New Hybrid Decision-Making Model for Promoting Sustainable Social Rental Housing

The realization of sustainable social rental housing is regarded as an important policy to solve the housing burden, but social rental housing is often unsustainable. This study assesses the sustainability of social rental housing. However, the decision-making models, such as the classical decision-making hierarchy (AHP) used in the current study, conflict with the resolution of the complex influence of the relationship between evaluation dimensions/criteria. Based on this, we construct a new hybrid multi-attribute decision-making model (MADM) combining the Fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL), Fuzzy DEMATEL-based analytic network process (DANP) and the modified VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method for the sustainability assessment of government-led social rental housing (SRH) using Taiwanese experts as the subject of the investigation. The Fuzzy DEMATEL found that economic sustainability (D1), as the core dimension, affects environmental (D3) and social sustainability (D2). Furthermore, criteria with the “cause” position, including the reasonable development model (C2), the provision of living facilities and services needed (C5), the adoption of environmentally friendly technology and equipment (C10), guaranteed rent and lease (C1), the acquisition of working skill and employment opportunities (C6) and space planning and design (C3), should receive more attention from decision makers because improving these can further enhance the sustainability of the overall scheme. Combined with the DANP weight and modified VIKOR, we also indicate that these criteria should be optimized to make the evaluation more sustainable for a selected social housing case in Taiwan. The research also further proposes management strategy implications.

Evaluating the Performance of various Algorithms for Wind Energy Optimization: A Hybrid Decision-Making model

Wind resource is one of the most promising renewable energy, which has become a suitable replacement for fossil fuels. Optimizing the transferring wind energy from a wind turbine is essential to obtain the maximum power output as other variables are uncontrollable. This paper presents four different optimization algorithms, namely ant lion optimization (ALO), whale optimization algorithm (WOA), particle swarm optimization (PSO), and crow search optimization (CSO), considering a hybrid decision-making model to compare the performances of wind energy optimization. In the first phase, the evolutionary algorithms are defined based on several factors to meet the need for wind energy based on volumetric and time reliability, reversibility, and vulnerability as well as evaluate optimized energy to the subscriber from the Gansu region. In the second phase, the ordinal priority approach (OPA) is coupled with VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method to rank the evolutionary algorithms. Then, the results are compared with the absolute optimal response based on the nonlinear programming method obtained from GAMS software. The results demonstrate that an ALO outperforms other algorithms. The average accuracy of ALO is 92%. CSO is the least accurate with 55% of the absolute optimal response. ALO is found to be faster, more efficient, and achieved economy and reliability as compared to other optimization algorithms for solving the problem under consideration. It is shown that the applied models are robust, effective, and able to save costs.

Review] Exploring an integrated decision-making model to enhance the employee-oriented built environment in urban green buildings: A Review

Integrating building technology systems into urban green buildings is an emerging building movement in developed countries to create a paradigm of a human-oriented built environment inside the workspaces. This paper thrives on aiming at the conversion of green buildings to smart-green facilities initiated to develop an employee-oriented built environment in urban green office buildings using decision-making models. The study identifies the factors affecting employee satisfaction as building-related factors, non-building-related factors, Multiple criteria decision analysis (MCDA) and Structural equation model (SEM) through a comprehensive literature review. Extensive bibliographic research has been driven for 21 years to understand the relationship between decision-making models and employee satisfaction in green office buildings. This paper provides an overall ideology of the impact of green office buildings and the conversion to buildings focusing on employee satisfaction. The study concludes by introducing an integrated MCDA and SEM method to create a lesser complex hybrid decision-making model to create an improved employee-friendly built environment.

An Integrated BWM-TOPSIS-I Approach to Determine the Ranking of Alternatives and Application of Sustainability Analysis of Renewable Energy

The purpose of this paper is to identify the most significant alternatives of renewable energy sustainability using a hybrid decision-making model of multiple criteria. Sustainable energy sources cannot run out and can be used for an indefinite period of time. In addition to meeting our energy needs, sustainable energy does not need to be renewed or replenished, nor does it pose any threat of being wrong or running out. Our energy demands can only be met by renewable energy. The bestworst methodand technique for order preference by similarities to ideal solution-I processes have proposed a hybrid model named the bestworst method—technique for order preference by similarities to ideal solution-I, for this purpose. This study uses comparative analysis and sensitivity analysis to determine the results of the proposed study.

Review] Proposing an integrated decision-making model to enhance the employee-oriented built environment in urban green buildings - A Review

Integrating building technology systems into urban green buildings is an emerging building movement in developed countries to create a paradigm of a human-oriented built environment inside the workspaces. This paper thrives on aiming at the conversion of green buildings to smart-green facilities initiated to develop an employee-oriented built environment in urban office green buildings using decision-making models. The study identifies the factors affecting employee satisfaction as building-related factors, non-building-related factors, Multiple criteria decision analysis (MCDA) and Structural equation model (SEM) through a comprehensive literature review. Extensive bibliographic research has been driven for 21 years to understand the relationship between decision-making models and employee satisfaction in green office buildings. This paper provides an overall ideology of the impact of green office buildings and the conversion to buildings focusing on employee satisfaction. The study concludes by introducing an integrated MCDA and SEM method to create a lesser complex hybrid decision-making model to create an improved employee-friendly built environment.

Review] Proposing an integrated decision-making model to enhance the employee-oriented built environment in urban green buildings: A Review

Integrating building technology systems into urban green buildings is an emerging building movement in developed countries to create a paradigm of a human-oriented built environment inside the workspaces. This paper thrives on aiming at the conversion of green buildings to smart-green facilities initiated to develop an employee-oriented built environment in urban office green buildings using decision-making models. The study identifies the factors affecting employee satisfaction as building-related factors, non-building-related factors, Multiple criteria decision analysis (MCDA) and Structural equation model (SEM) through a comprehensive literature review. Extensive bibliographic research has been driven for 21 years to understand the relationship between decision-making models and employee satisfaction in green office buildings. This paper provides an overall ideology of the impact of green office buildings and the conversion to buildings focusing on employee satisfaction. The study concludes by introducing an integrated MCDA and SEM method to create a lesser complex hybrid decision-making model to create an improved employee-friendly built environment.

Review] Proposing an integrated decision-making model to enhance the employee-oriented built environment in urban green buildings

Integrating building technology systems into urban green buildings is an emerging building movement in developed countries to create a paradigm of a human-oriented built environment inside the workspaces. This paper thrives on aiming at the conversion of green buildings to smart-green facilities initiated to develop an employee-oriented built environment in urban office green buildings using decision-making models. The study identifies the factors affecting employee satisfaction as building-related factors, non-building-related factors, Multiple criteria decision analysis (MCDA) and Structural equation model (SEM) through a comprehensive literature review. Extensive bibliographic research has been driven for 21 years to understand the relationship between decision-making models and employee satisfaction in green office buildings. This paper provides an overall ideology of the impact of green office buildings and the conversion to buildings focusing on employee satisfaction. The study concludes by introducing an integrated MCDA and SEM method to create a lesser complex hybrid decision-making model to create an improved employee-friendly built environment.

Review] Integrated decision-making model to enhance the employee-oriented built environment in urban green buildings

Integrating building technology systems into urban green buildings is an emerging building movement in developed countries to create a paradigm of a human-oriented built environment inside the workspaces. This paper thrives on aiming at the initiation of developing an employee-oriented built environment in urban office green buildings using decision-making models. The study identifies the factors affecting employee satisfaction as building-related factors, non-building-related factors, Multiple criteria decision analysis (MCDA) and Structural equation model (SEM) through a comprehensive literature review. Extensive bibliographic research has been driven for 21 years to understand the relationship between decision-making models and employee satisfaction in green office buildings. This paper provides an overall ideology of the impact of green office buildings and the conversion to buildings focusing on employee satisfaction. The study concludes by introducing an integrated MCDA and SEM method to create a lesser complex hybrid decision-making model to create an improved employee-friendly built environment.

A mixed-integer linear programming model for aggregating multi–criteria decision making methods

Selecting an MCDM method to use in any decision-making problem is always a difficult issue regarding that there is no agreement generally on which method is the most appropriate one. This paper addressed a proposal of a hybrid approach for this problem. Under the assumption that there is no superiority among well-established and accepted MCDM methods, we defined a maximin strategy based on the fact that the lowest correlation between MCDMs and the proposed hybrid approach in terms of alternative rankings should be as high as possible. Even though MCDM methods often rank the alternatives differently, many methods perform similar ranking due to sharing alike mathematical operations. To avoid positive bias towards these methods in an integrated approach, we focused on a prioritizing scheme that supports different rankings. This prioritizing scheme also contributed to hinder the problem of selecting MCDMs with constraining the compound effect of similar rankings. We developed a hybrid decision-making model combining different MCDM methods with prioritizing them by using a binary integer linear programming model. We compared the proposed approach with some well-known prioritizing methods and the results revealed that the proposed approach produced better outcomes in obtaining the desired outputs.