Hybrid Evaluation Model Research Articles

The technological assessment of green buildings using artificial neural networks

This study aims to construct a comprehensive evaluation model for efficiently assessing appropriate technologies within green buildings. Initially, an Internet of Things (IoT)-based environmental monitoring system is devised and implemented to collect real-time environmental parameters both inside and outside the building. To evaluate the technical suitability of green buildings, this study employs a multifaceted approach encompassing various criteria, including energy efficiency, environmental impact, economic benefits, user comfort, and sustainability. Specifically, it involves real-time monitoring of environmental parameters, analysis of energy consumption data, and indoor environmental quality indicators derived from user satisfaction surveys. Subsequently, a Multi-Layer Perceptron (MLP) is selected as a conventional artificial neural network (ANN) model, while a Long Short-Term Memory (LSTM) model is chosen as an advanced recurrent neural network model in the realm of deep learning. These models are utilized to process and explore the collected data and assess the technical suitability of green buildings. The dataset comprises physical quantities such as temperature, humidity, and light intensity, as well as economic indicators including energy efficiency and building operating costs. Furthermore, the assessment process considers the building's life cycle assessment and indoor environmental quality factors such as health, comfort, and safety. By incorporating these comprehensive criteria, a holistic evaluation of green building technologies is achieved, ensuring the selected technologies' suitability and effectiveness. The model prediction results demonstrate that the proposed hybrid evaluation model exhibits high accuracy and robust stability in predicting building environmental parameters. For instance, the Root Mean Square Error (RMSE) for temperature prediction is 1.2 °C, the Mean Absolute Error (MAE) is 0.9 °C, and the determination coefficient (R2) reaches 0.95. Similarly, for humidity prediction, the RMSE, MAE, and R2 are 3.5 %, 2.8 %, and 0.88. Compared to the traditional MLP and LSTM models alone, the proposed hybrid model shows significant improvements in predicting building energy consumption, with approximately 15 % and 12 % reductions in RMSE and MAE, respectively, and an increase in R2 values of approximately 7 percentage points. These findings indicate that by amalgamation of the IoT and ANNs, this study successfully establishes a comprehensive model for accurately assessing technologies suitable for green buildings. This approach offers a novel perspective and methodology for the design and evaluation of green buildings.

Hybrid Evaluation Model to assess the overall barriers of public-private partnership contracts

Public-private partnerships are increasingly being used in many countries as a common management technique to enhance the delivery of public services and major public infrastructure projects. Understanding the project characteristics and obstacles to a public-private partnership is key for those involved to improve implementation. This study focuses on barriers that arise from public-private partnership contact in field wastewater treatment plants and offers a methodology for evaluating the overall barrier for public-private partnership projects by analyzing the relationships between the barrier elements. A primary list of barrier factors and their eight latent project characteristics were collected through literature reviews, then using the Delphi technique to filter the barrier insights concerning project characteristics and develop the final list using field interviews. 207 valid questionnaires were obtained. The data was deconvoluted into crisp numbers using fuzzy set theory, and a second-order structural equation model was used to validate the conceptual model. The results of the study indicate that the availability payment capability group has the highest score of all the groups in this study. This study proposed a model that enables the private sector to measure and evaluate aggregate barriers in projects so that it is easier for decision-makers to determine whether they can choose the project or not.

Risk Assessment in Sustainable Production: Utilizing a Hybrid Evaluation Model to Identify the Waste Factors in Steel Plate Manufacturing

In the realm of industrial development, steel has consistently played a pivotal role due to its extensive applications. This research aims to refine the process of steel plate manufacturing, focusing on reducing waste as a critical step towards embracing sustainable development and aligning with the Sustainable Development Goals (SDGs). Our approach integrates a hybrid analytical model grounded in Failure Mode and Effects Analysis (FMEA) to thoroughly investigate the waste-producing elements in steel plate production. The methodology of this study is structured in a three-pronged approach, as follows: Initially, it involves meticulous on-site inspections across various factories to pinpoint potential sources of waste. Subsequently, we employ the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to intricately analyze the interconnectedness and impact of various risk factors. The final phase utilizes the Performance Calculation technique within the Integrated Multiple Multi-Attribute Decision-Making (PCIM-MADM) framework for aggregating and evaluating risk scores. This multifaceted approach aids in establishing the priorities for corrective actions aimed at waste reduction. Our findings present innovative solutions for identifying and mitigating critical waste factors, contributing to a more efficient and sustainable steel manufacturing process. These strategies promise scalability and adaptability for broader industrial applications and provide critical insights into resource optimization. This research directly supports the objectives of SDG 9, which focuses on building resilient infrastructure and promoting sustainable industrialization. Furthermore, it resonates with SDG 12, advocating for sustainable consumption and production patterns. By enhancing the efficiency and cost effectiveness of steel plate production, this study significantly contributes to minimizing waste and elevating the sustainability of industrial practices.

Quantitative flood disaster loss-resilience with the multilevel hybrid evaluation model

The severity of global flood disasters is growing, causing loss of human life and property. Building a high-resilience social system, an important means of sustainable flood control, can address these flood-related issues. Numerous studies have carried out disaster resilience evaluations and explored the correlation between flood disaster loss and intensity, but neglected to analyze the role of resilience construction in disaster loss reduction. This study proposed a research route for linking flood loss and disaster loss to quantify the relationship between the two. Take Guangdong Province, China as a study case, the mixed-effects (ME) model and multilevel hybrid evaluation model (MHEM) were established to assess disaster loss and resilience of cities, respectively. Subsequently, disaster resilience curves were built to quantitatively evaluate disaster resilience and corresponding disaster loss. The results show that (1) the ME model can concurrently build the disaster intensity-loss curves of multiple cities with high fitting accuracy. The MHEM combines multiple methods to determine the evaluation result with the highest consistency, showing high reliability. (2) The central and southern regions of Guangdong Province have low disaster loss and high resilience, while the northern regions have high disaster loss and low resilience. (3) With the improvement of disaster resistance, the reduction in disaster loss gradually decreases. Disaster loss in low-resilience cities exhibits greater randomness than that in high-resilience cities, and increasing their resilience can more significantly reduce their level of loss. This study provides a quantitative basis and available methods for comprehensive responses to natural disasters and adaptation to global climate change.

Evaluating Economy Hotel Website Service Quality: A Hybrid Bounded Rationality Behavioral Decision Support Model

Hotel website service quality evaluation has gained extensive attention. However, previous studies have given little concern about human hesitance and uncertainty in judgments. Moreover, they do not consider hotel managers and customers’ psychological behaviors simultaneously. This study explores criteria for evaluating hotel performance and proposes a hybrid evaluation model for the hesitation and uncertainty in the service quality evaluation of economy hotel websites, and applied to the actual economy hotel websites. The model introduces the probabilistic linguistic term sets to describe customers and managers’ qualitative assessments and use analytical network process to prioritize hotel website features. Then, it develops an integrated TODIM-PROMETHEE II method to rank alternatives considering both hotel managers and customers’ psychological factors. Furthermore, we illustrate the effectiveness of the hybrid evaluation model through a case of economy hotel websites in China. Service competence and customer relationship are the two most important performance features for economy hotel websites. Finally, conclusions and implications are drawn from the results of case study.

A Hybrid Evaluation Model for e-Learning Platforms Based on Extended TOE Framework

E-learning platforms (ELPs) are revolutionizing the higher education system, as they offer tremendous potential to fulfill instructional plans, safeguard students’ learning rights, and improve teaching quality. Higher education institutions (HEIs) have to consider the selection of ELPs from an organizational perspective, which involves multiple stakeholders like university administrators, students, and educators. Therefore, one can take the ELP selection as a complex multi-criteria decision-making (MCDM) problem. This research proposes a new hybrid MCDM approach on the basis of the fuzzy analytic hierarchy process (FAHP) and the evaluation based on distance from the average solution (EDAS) method to select the best ELPs. First, from the organizational perspective, we extend the technology-organization-environment (TOE) framework by adding an auxiliary resource (AR) dimension and define and prioritize 4 criteria and 14 criteria for evaluating and selecting ELPs. Second, the study uses the fuzzy set theory to process the language evaluation of experts, the FAHP method to determine criteria and sub-criteria weights, and EDAS to rank the alternatives. Finally, based on the importance-performance analysis (IPA) method, we identify the most appropriate strategic options for enhancing competitiveness. Three practical cases of China’s ELP evaluation validate the proposed model’s applicability and superiority by comparing to the two other classic evaluation models. In addition, through analysis, we obtain some encouraging results that provide some references for universities to formulate ELP selection policies and offer suggestions for platform producers to further optimize the design.

Research on the construction safety risk assessment of prefabricated subway stations in China

PurposePrefabricated technology is gradually being applied to the construction of subway stations due to its characteristic of mechanization. However, the prefabricated subway station in China is in the initial stage of development, which is prone to construction safety issues. This study aims to evaluate the construction safety risks of prefabricated subway stations in China and formulate corresponding countermeasures to ensure construction safety.Design/methodology/approachA construction safety risk evaluation index system for the prefabricated subway station was established through literature research and the Delphi method. Furthermore, based on the structure entropy weight method, matter-element theory and evidence theory, a hybrid evaluation model is developed to evaluate the construction safety risks of prefabricated subway stations. The basic probability assignment (BPA) function is obtained using the matter-element theory, the index weight is calculated using the structure entropy weight method to modify the BPA function and the risk evaluation level is determined using the evidence theory. Finally, the reliability and applicability of the evaluation model are verified with a case study of a prefabricated subway station project in China.FindingsThe results indicate that the level of construction safety risks in the prefabricated subway station project is relatively low. Man risk, machine risk and method risk are the key factors affecting the overall risk of the project. The evaluation results of the first-level indexes are discussed, and targeted countermeasures are proposed. Therefore, management personnel can deeply understand the construction safety risks of prefabricated subway stations.Originality/valueThis research fills the research gap in the field of construction safety risk assessment of prefabricated subway stations. The methods for construction safety risk assessment are summarized to establish a reliable hybrid evaluation model, laying the foundation for future research. Moreover, the construction safety risk evaluation index system for prefabricated subway stations is proposed, which can be adopted to guide construction safety management.

Critical Factors Affecting the Promotion of Emerging Information Technology in Prefabricated Building Projects: A Hybrid Evaluation Model

Emerging information technology (EIT), characterized by intelligence, digitization, and automation, can facilitate activities such as stakeholder cooperation, information management, and construction management to enhance the overall performance in prefabricated building projects (PBPs). A variety of EITs are currently being used in PBPs, but their development is relatively sluggish and still in the infancy stage. Previous studies have explored the challenges and barriers of EIT in PBPs; however, the correlations between these factors have not been thoroughly examined. Therefore, the goal of this study is to pinpoint the characteristics and connections between EIT-affecting elements. Based on the technology–organization–environment (TOE) framework, this study firstly summarizes 20 influencing factors of EIT adoption and promotion in PBPs mentioned in the previous literature through a literature review. Then, EIT experts were invited to conduct semi-structured interviews to evaluate the relationship and the degree of influence among 20 influencing factors. Finally, the DEMATEL-ISM approach was used to assess the characteristics of each factor and the hierarchy between them. The results demonstrated that the influencing degree of the environmental dimension was more significant and had a greater influence on the whole network of influencing factors. The factors of the organizational dimension have a higher influenced degree and are easily influenced by other factors. Due to the current lack of awareness of EIT, the majority of the technology-related influencing factors have a less significant effect on adopting and promoting EIT. In summary, this study assists in analyzing the characteristics and correlations of the factors that influence EIT adoption and promotion in PBPs and identifies critical influencing factors. It also aids the government and stakeholders in developing a deeper understanding and knowledge of EIT, thereby promoting the development of EIT in PBPs.

Organizational Performance Evaluation of Coal-Fired Power Enterprises Using a Hybrid Model

Carbon peaking and carbon neutrality goals have proposed by many countries, including China. Meanwhile, China has also proposed the construction of a new-type electric power system with new energy as the main body, which will have great impacts on coal-fired power generation enterprises. The transformation of coal-fired power enterprises is imperative, and the evaluation of the organizational performance of coal-fired power enterprises is urgent, which can accurately determine the development status and even can find issues related to the transformation of coal-fired power enterprises. In this paper, a hybrid evaluation model is proposed based on the Variational Auto-Encoder algorithm and fuzzy comprehensive evaluation method improved by a vague set to comprehensively evaluate the organizational performance of coal-fired power enterprises. Eight coal-fired power enterprises in North China are selected for empirical analysis. The results show that the YC coal-fired power enterprise has the best organizational performance, while the NK coal-fired power enterprise has the worst organizational performance. Moreover, sensitivity and comparative analyses are carried out to verify the robustness of the evaluation result using the proposed hybrid method in this paper. This paper focuses on the organizational performance evaluation of coal-fired power enterprises, which can provide a reference for the smooth transformation and sustainable development of coal-fired power enterprises in the context of “Dual-Carbon” goals.

Evaluation of Breakthrough Technological Innovation Capability of Petroleum Equipment Manufacturing Enterprises Based on the CFPR‐TIFNs Model

“Internet + innovation” is a new emerging paradigm for breakthrough technological innovation, which is more complex than traditional scenarios because “Internet +” has completely overturned the acquisition of creativity and knowledge. This article aims to evaluate the breakthrough technological innovation capability (BTIC) of petroleum equipment manufacturing enterprises under the new paradigm of “Internet + innovation.” This article constructs an index system that can reflect the characteristics of “breakthrough” and “Internet +” in five dimensions. Due to the difficulties of conducting quantitative measurements for the novel index system, a hybrid evaluation model based on a consistent fuzzy preference relationship (CFPR) and triangular intuitionistic fuzzy numbers (TIFNs) is put forward for the evaluation of BTIC. The main contribution of this article is to propose an index system and model for the evaluation of BTIC under the “Internet + innovation” paradigm, which is conducive to improving the quality of breakthrough technological innovation activities under more complex scenarios. The CFPR‐TIFNs model can not only effectively calculate the BTIC of petroleum equipment manufacturing enterprises but also deeply analyze the influencing factors for their relatively weak technological innovation capability. This article provides a new methodology to solve problems in a more complex technological innovation system.

Using Improved SPA and ICS-LSSVM for Sustainability Assessment of PV Industry along the Belt and Road

Scientific and timely sustainability evaluation of the photovoltaic industry along the Belt and Road is of great significance. In this paper, a novel hybrid evaluation model is proposed for accurate and real-time assessment that integrates modified set pair analysis with least squares support vector machine that combines improved cuckoo search algorithm. First, the indicator system is set from five principles, namely economy, politics, society, ecological environment and resources. Then, the traditional approach is established through modifying set pair analysis on the basis of variable fuzzy set coupling evaluation theory. A modern intelligent assessment model is designed that integrates improved cuckoo search algorithm and least squares support vector machine where the concept of random weight is introduced in improved cuckoo search algorithm. In the case analysis, the relative errors calculated by the proposed model all fluctuate in the range of [−3%, 3%], indicating that it has the strongest fitting and learning ability. The empirical analysis verifies the scientificity and precision of the method and points out influencing factors. It provides a new idea for rapid and effective assessment of PV industry along the Belt and Road, as well as assistance for the sustainable development of this industry. This paper innovatively proposes the sustainability evaluation index system and evaluation model for the photovoltaic industry in countries along the Belt and Road, thus contributing to the promotion of sustainable development of the photovoltaic industry in countries along the Belt and Road.

Comprehensive Evaluation Model of Bearing Transportation Protection Effect of Bogie Traction Motor under Data Imbalance

Under different transportation protection, the sample data of bogie traction motor bearings of urban rail vehicles are seriously unbalanced, and the fault diagnosis ability and generalization effect are poor, which makes it difficult to evaluate the protection effect of bearings effectively. In this paper, a multimeasure hybrid evaluation model based on compressed sensing is proposed to evaluate the effect of bearing transportation protection under data imbalance. Firstly, bearing vibration signals under different transport protection conditions were compressed and sampled, and the original high‐Witt collection in time domain, frequency domain, and time‐frequency domain was extracted. Then, a multimeasure mixed feature evaluation model of correlation, distance, and signal was constructed, and the optimal multimeasure combination strategy was optimized by using comprehensive sensitivity score evaluation index. Finally, an evaluation model of bearing protection effect based on unified feature index was constructed by using the best feature subset evaluated, and the unified indicator was quantified to characterize the protection effect of different protection states. The experimental results show that the model can effectively evaluate bearings under different transport protection.

Evaluating the Regulatory Environment of Overseas Electric Power Market Based on a Hybrid Evaluation Model

This paper develops a hybrid model for evaluating the regulatory environment of overseas electric power market (OEPM), which is of great theoretical and practical significance for power grid enterprises. Power regulation and investment environment evaluation theories as well as fuzzy Delphi method (FDM) are referenced to identify the final evaluation indicators. Owing to the presence of qualitative indicators in the index system, the analytic hierarchy process (AHP) and improved gray relational analysis (IGRA) approaches are combined to determine the indicator weights so as to ensure the credibility of the weights. Considering the non-compensatory principle among primary indicators, the improved fuzzy comprehensive evaluation method (IFCEM) based on multiplicative synthesis technique is applied to evaluate the alternatives. The empirical results indicate that “Return on Investment” and “Bilateral Relationship” are the main perspectives that greatly affect the regulatory environment of OEPM, and that UK and Greece are the best and worst alternatives in terms of the regulatory environment of OEPM in the analyzed countries. Totally, the proposed hybrid framework expressed great capacity to evaluate and rank the regulatory environment of OEPM and can be also popularized in other fields to support enterprises in making decisions by evaluating the alternatives with ambiguity and uncertainty.

Evaluating the Power Grid Investment Behavior in China: From the Perspective of Government Supervision

Power grid investment behavior (PGIB) is a necessary prerequisite to ensure safe and reliable power supply. The supervision of PGIB is an important measure to reduce electricity price. It helps to release the dividends of the new power system reform and promote the sustainable development of the power industry. However, for a long time, China’s regulation of PGIB was relatively weak, lacking clear supervision awareness and effective supervision methods. On the basis of clarifying the contents of PGIB supervision, this paper establishes an evaluation index system for the compliance of PGIB from the government supervision perspective, involving four dimensions and 14 secondary indicators. Furthermore, a hybrid evaluation model based on the combined decision-making trial and evaluation laboratory method (DEMATEL-ANP), analytical network process method, and vague set is proposed. The results reveal that the control over cost and efficiency of the PGIB in China is not enough. According to the results, this paper puts forward the indicators that close attention should be paid to and the work priorities in China’s supervision of PGIB, which has certain practical value for the implementation of new power system reform and the sustainable development of Chinese power industry.

Evaluating the Effectiveness of New and Old Kinetic Energy Conversion from an Electric Power Economics Perspective: Evidence on the Shandong Province of China

This paper proposes a hybrid model for evaluating the effectiveness of new and old kinetic energy conversion (NOKEC), China’s major strategic move aiming to transform the mode of economic growth and improvie the quality of economic development. Considering the goals of NOKEC and the supporting roles of power industry to NOKEC, this paper constructs an index system for NOKEC effectiveness evaluation from an electric power economics perspective, involving three dimensions and 17 secondary indicators. Furthermore, a hybrid evaluation model based on DEMATEL-ANP and DQ-GRA techniques is developed to accomplish the evaluation of Shandong’s NOKEC effectiveness. The results show that Shandong’s NOKEC effectiveness increased from 2015–2017, indicating that Shandong’s NOKEC policies have achieved remarkable results. According to the evaluation results, this paper puts forward the indicators that should be paid close attention to and the following work priorities in Shandong’s future NOKEC process, which has certain practical value for the promotion of Shandong’s NOKEC. In addition, the evaluation model proposed in this paper considers the interrelationships between indicators and overcomes the shortcomings of traditional GRA, showing good applicability to similar effectiveness evaluation issues. Finally, the limitations and universality of the model are discussed and the improvement direction is put forward.

Examining the sensitivity of spatial scale in cellular automata Markov chain simulation of land use change

ABSTRACTUnderstanding the spatial scale sensitivity of cellular automata is crucial for improving the accuracy of land use change simulation. We propose a framework based on a response surface method to comprehensively explore spatial scale sensitivity of the cellular automata Markov chain (CA-Markov) model, and present a hybrid evaluation model for expressing simulation accuracy that merges the strengths of the Kappa coefficient and of Contagion index. Three Landsat-Thematic Mapper remote sensing images of Wuhan in 1987, 1996, and 2005 were used to extract land use information. The results demonstrate that the spatial scale sensitivity of the CA-Markov model resulting from individual components and their combinations are both worthy of attention. The utility of our proposed hybrid evaluation model and response surface method to investigate the sensitivity has proven to be more accurate than the single Kappa coefficient method and more efficient than traditional methods. The findings also show that the CA-Markov model is more sensitive to neighborhood size than to cell size or neighborhood type considering individual component effects. Particularly, the bilateral and trilateral interactions between neighborhood and cell size result in a more remarkable scale effect than that of a single cell size.

Supplier Selection Study under the Respective of Low-Carbon Supply Chain: A Hybrid Evaluation Model Based on FA-DEA-AHP

With the development of global environment and social economy, it is an indispensable choice for enterprises to achieve sustainable growth through developing low-carbon economy and constructing low-carbon supply chain. Supplier is the source of chain, thus selecting excellent low-carbon supplier is the foundation of establishing efficient low-carbon supply chain. This paper presents a novel hybrid model for supplier selection integrated factor analysis (FA), data envelopment analysis (DEA), with analytic hierarchy process (AHP), namely FA-DEA-AHP. First, an evaluation index system is built, incorporating product level, qualification, cooperation ability, and environmental competitiveness. FA is utilized to extract common factors from the 18 pre-selected indicators. Then, DEA is applied to establish the pairwise comparison matrix and AHP is employed to rank these low-carbon suppliers comprehensively and calculate the validity of the decision-making units. Finally, an experiment study with seven cement suppliers in a large industrial enterprise is carried out in this paper. The results reveal that the proposed technique can not only select effective suppliers, but also realize a comprehensive ranking. This research has enriched the methodology of low-carbon supplier evaluation and selection, as well as owns theoretical value in exploring the coordinated development of low-carbon supply chain to some extent.

Highlighting regional eco-industrial development: Life cycle benefits of an urban industrial symbiosis and implications in China

Industry is double-edge sword to urban sustainability: on the one hand, it provides employment and GDP economic, one the other hand, brings pollutions to cities. The concept of urban industrial symbiosis offers a smart solution for city to coordinate the relationship among industries and between industry and city. While internationally, this idea has been promoted more than two decades, in China, which is ideal laboratory to test such practices, related research is rather few, especially quantitative studies. With this circumstance, this study conducts a case study to test the urban industrial symbiosis promotion in one typical industrial city named Liuzhou, in southern China, of which heavy industries play an important role. A hybrid evaluation model integrating process based life cycle assessment (LCA) and input-output (IO) model is established to assess the environmental benefits in the whole supply chain. Based on local conditions, innovative urban industrial symbiosis is designed and analyzed. Five new waste/energy synergies named waste plastics recycling, scrap tire recycling, coal flying ash recycling, biomass utilization and carbon capture by slag carbonization are selected for scenarios analysis. We particular focus on the carbon mitigations. Compared with business as usual scenario, planned symbiosis enables to reduce CO2 emissions by 29.66, 557.42 and 520.13kt-CO2/year in power purchase, material consumption and waste disposal stage. Results highlight that urban industrial symbiosis is not only able to green the industries, but also utilize industry contribute to urban development. Finally, policy implications and countermeasures to address the barriers of promoting the urban industrial symbiosis are discussed. Our research would be critical for future sustainable urban planning and shed a light on regional eco-industrial development in China.

Assessment of the value of NOM treatment processes based on a matter-element model

Research into natural organic matter (NOM) removal in drinking water treatment processes is mostly independent, distributed, disconnected and unable to meet the needs of technology application; therefore, an assessment of the value of NOM treatment processes is necessary. In this paper, a hybrid evaluation model based on rough set theory and a matter-element model was used to evaluate the value of eight NOM removal processes. The counting process of the weighting factor did not include any subjective information which avoided the artificial factor deviation and made the evaluation more objective. The result indicated that in addition to the MIEX + coagulation + sedimentation + filtration (MCSF) treatment process, the rest of the NOM treatment processes had a certain value; the coagulation + sedimentation + filtration + adsorption (CSFA) and coagulation + sedimentation + filtration + membrane (CSFM) treatment processes had the highest values which meant that these treatment processes could remove the NOM in drinking water effectively. It also illustrated that the coagulation + sedimentation + adsorption + membrane (CSAM) treatment process had high feasibility, which has important significance for guaranteeing the safety of drinking water.

Hybrid e-Book Business Strategy-Evaluation Model Using Fuzzy Multiple Criteria Analysis

Abstract Evaluation of the e-book business strategy model is a critical problem and it plays a significant role in the success of e-book firm development. On the other hand, selecting the most appropriate e-book business strategy model among a pool of alternatives is a multiple criteria decision-making (MCDM) problem. Therefore, this study proposed a hybrid evaluation model based on the decision-making trial and evaluation laboratory (DEMATEL), fuzzy analytic network process (FANP), and the complex proportional assessment (COPRAS) method to help managers with the evaluation of proper business strategy model in a fuzzy environment, where the fuzziness and uncertainties are handled with linguistic terms parameterized by triangular fuzzy numbers (TFNs). The final results show the capability and effectiveness of the hybrid model.