Fuzzy Logic in Decision Support: Methods, Applications and Future Trends

During the last decades, the art and science of fuzzy logic have witnessed significant developments and have found applications in many active areas, such as pattern recognition, classification, control systems, etc. A lot of research has demonstrated the ability of fuzzy logic in dealing with vague and uncertain linguistic information. For the purpose of representing human perception, fuzzy logic has been employed as an effective tool in intelligent decision making. Due to the emergence of various studies on fuzzy logic-based decision-making methods, it is necessary to make a comprehensive overview of published papers in this field and their applications. This paper covers a wide range of both theoretical and practical applications of fuzzy logic in decision making. It has been grouped into five parts: to explain the role of fuzzy logic in decision making, we first present some basic ideas underlying different types of fuzzy logic and the structure of the fuzzy logic system. Then, we make a review of evaluation methods, prediction methods, decision support algorithms, group decision-making methods based on fuzzy logic. Applications of these methods are further reviewed. Finally, some challenges and future trends are given from different perspectives. This paper illustrates that the combination of fuzzy logic and decision making method has an extensive research prospect. It can help researchers to identify the frontiers of fuzzy logic in the field of decision making

Open innovation: a research framework and case study of Huawei

Open innovation (OI) has received significant attention from practices and theories over the past decades. This paper investigates the role of OI and personalized patterns in firms at home and abroad, and then measures the risks involved. Firstly, this paper reviews the definition of OI, the business model innovation characteristics, and the facing problems in practice. Based on the existing literature, we illustrate the openness and challenges of business OI. By introducing bibliometrics, this paper presents a whole research framework. Based on keywords cooccurrence analysis and clustering analysis, we locate the current research hotspots and potential research opportunities from a comprehensive perspective. According to the analysis results, five clusters are obtained, including resource management and value creation; collective innovation and form sustainability; innovation management, intellectual property management, and crossborder cooperation; knowledge management and knowledge sharing; innovation ecosystem, big data, and policy-level innovation. Taking Huawei as an example, its typical business OI model is studied from the perspectives of organizational, project-related, marketing and consumer-based, and summaries the facing challenges and risks. We illustrate its financial performance, innovation performance, and development prospects. We found that, during the implementation of OI practical activities and theoretical exploration, the risks and opportunities facing small and medium-sized enterprises (SMEs) are multiple dimensional

An Inverse Prospect Theory Based-Approach for Linear Ordinal Ranking Aggregation with Its Application in Site Selection of Electric Vehicle Charging Station

Considering that it is difficult for experts to provide precise preference values for the site selection of electric vehicle charging station in risky environment, this paper develops an approach for linear ordinal ranking aggregation to validly improve the efficiency and accuracy of electric vehicle charging station site selection. At first, the inverse value function of prospect theory is applied to reduce the impact of risk. Then, through combining with the concept of information energy, the experts' weights can be derived. Besides, a consistency constraint is added to the individual ranking-based alternatives' weights deriving model, which can guarantee the consistency degree at an acceptable level. Additionally, a consensus and standard deviation-based model is established to aggregate the alternatives' weights. Finally, a numerical case about the electric vehicle charging station site selection is presented to show the usage of the approach, meanwhile, comparative analysis and sensitivity analysis are also conducted which show the robustness and practicability of the approach

Open innovation: a research framework and case study of Huawei

Open innovation (OI) has received significant attention from practices and theories over the past decades. This paper investigates the role of OI and personalized patterns in firms at home and abroad, and then measures the risks involved. Firstly, this paper reviews the definition of OI, the business model innovation characteristics, and the facing problems in practice. Based on the existing literature, we illustrate the openness and challenges of business OI. By introducing bibliometrics, this paper presents a whole research framework. Based on keywords cooccurrence analysis and clustering analysis, we locate the current research hotspots and potential research opportunities from a comprehensive perspective. According to the analysis results, five clusters are obtained, including resource management and value creation; collective innovation and form sustainability; innovation management, intellectual property management, and crossborder cooperation; knowledge management and knowledge sharing; innovation ecosystem, big data, and policy-level innovation. Taking Huawei as an example, its typical business OI model is studied from the perspectives of organizational, project-related, marketing and consumer-based, and summaries the facing challenges and risks. We illustrate its financial performance, innovation performance, and development prospects. We found that, during the implementation of OI practical activities and theoretical exploration, the risks and opportunities facing small and medium-sized enterprises (SMEs) are multiple dimensional