TOPSIS is the abbreviation of “Technique for Order Preference by Similarity to Ideal Solution”. Its weight is often determined by the decision maker. When the decision-maker has a strong subjective awareness of an evaluation criterion, it will lead to biased evaluation results. And it cannot predict the best solution that may be produced after the comparison between different solutions in the future. The main contribution of this research is to make up for the lack of subjective weight with the entropy weight of objective weight. Compare and analyze the difference between the evaluation results of the two models-objective weight (Entropy-TOPSIS) and subjective weight (TOPSIS). And use the GM (1,1) model to effectively predict the future value of each evaluation index item. Provide the predicted future value of each indicator item to two evaluation models for comparison of future operating performance. To break through the limitation of TOPSIS evaluation method that can not predict the future optimal plan. Finally, based on the empirical results, it proposes operational policy recommendations that have more reference value than both TOPSIS wtih only subjective weights (or equal weights), and current operational performance. This article uses TOPSIS, Entropy-TOPSIS and GM (1,1) models to evaluate the future operating performance of listed companies in the Taiwan construction industry. According to the evaluation and analysis of the predicted value of Q4 in 2020 and the current value of Q4 in 2019 based on the two evaluation models, it was found that the current and predicted annual operating performances are in the top 5 construction industries, including Prince Housing & Development Corp. (2511) and Farglory Land Development Co., LTD (5522). In addition, with the TOPSIS method, there are 4 construction industries that have improved in the ranking of operating performance appraisal and 7 construction industries that regressed. However, if the order of evaluation by Entropy-TOPSIS method, there are 4 construction industries with a higher ranking, 6 construction industries with a backward trend, and 1 construction industries with the same ranking. Because the two evaluation models have significant differences in the evaluation ranking results of listed companies in the construction industry, therefore, when using TOPSIS evaluation method to evaluate the performance order of the research objects, the selection of weights must be listed as a prerequisite to improve the applicability of the model evaluation results. In addition, we can know by entropy weight method to evaluate the predicted value of Q4 in 2020 that the facets of the impact on the operating performance of listed companies in Taiwan’s construction industry are total assets (28.46%)> operating profit (24.19%)> paid-in capital (20.50)> operating income (15.95%)> operating cost (5.46%) )> Total Liabilities (5.44%). This is also a recommendation for the order of emphasis on the operational performance aspects of the operating policies of listed companies in Taiwan’s construction industry.
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