RETRACTED: Selecting and balancing market portfolio using artificial intelligence and fuzzy multiobjective decision-making model (Retracted Article)

作     者：Shih, Wen-Lung Wei, Chiu-Chi Lin, Hsien-Hong Chang, Pin-Hsiang 

作者机构：Chung Hua Univ PhD Program Technol Management Hsinchu 300 Taiwan Huaiyin Inst Technol Dept Logist Engn Nanjing Jiangsu Peoples R China Yuan Pei Univ Med Technol Dept Healthcare Management Hsinchu Taiwan 

出 版 物：《CONCURRENT ENGINEERING-RESEARCH AND APPLICATIONS》 (Concurrent Eng Res Appl)

年 卷 期：2022年第30卷第4期

页      面：382-398页

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0802[工学-机械工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Ansoff matrix market segment market portfolio mathematical programming TOPSIS 

摘      要：Most enterprises focus on product portfolio management (PPM) and exclude market portfolio management, and individual markets are selected solely based on financial performance which may not be appropriate because other factors may dictate the outcome of the market selection. This study proposes a market portfolio model that considers market share, market growth, market competition, market risk, and market cost to maximize overall profit. A three-stage approach is proposed to identify potential product markets using an AI algorithm. A set of the most promising market is then determined based on the results of Stage 1 using a fuzzy multi-objective mathematical programming model by concurrently maximizing the total market share and market growth, and minimizing the market competition and market risk. A single-objective mathematical programming model is then used to determine a market portfolio to maximize the total profit using the results for Stage 2. The single-objective model is tested using two sets of threshold constraints. The balance of the market portfolio is discussed and the results are compared. The novelty of the article: (1) the first study involves a product market portfolio, (2) the decision of market selection is scientific (using AI instead of personal judgment), holistic (factors include market share, growth, competition, risk, cost, and profit) and optimized (using mathematical optimization), and (3) the market portfolio maximizes total profit. (4) the proposed method produces a portfolio with a higher profit than the TOPSIS method.