关键词: 权重组合, 共享经济企业, 绩效评价, 模糊综合评价法

Abstract: This study focuses on the field of performance evaluation of sharing economy enterprises, and aims to provide an effective performance evaluation method for sharing economy enterprises by constructing a scientific and reasonable performance evaluation system. With the vigorous development of the sharing economy in China, the number of sharing economy enterprises has surged, covering clothing, food, housing, transportation, health, knowledge education and life services and other fields. However, some sharing economy enterprises are facing the risk of poor performance or even bankruptcy in the rapid development, so it is particularly important to scientifically evaluate their performance.
In this study, we refer to Osterwalder’s business model theory and combine the research results of LIU Yanan(2017) on the performance of sharing economy enterprises to preliminarily screen out multiple indicators that affect the performance of sharing economy enterprises. Through interviews and questionnaire surveys with senior leaders, this study further refines the indicators into two categories: product factors and enterprise quality credit factors, and determines specific indicators including product life cycle, environmental protection degree, user rating, financing ability, cost management ability, technological innovation, number of awards, executive breach of trust record and contract performance ability.
In terms of determining the weight of the indicators, this study innovates the existing methods. In view of the shortcomings of the traditional single weight determination method, this study proposes a new method that combines subjective weight determination methods (such as the expert investigation method, analytic hierarchy process, and decision laboratory method) with objective weight determination methods (such as the entropy weight method and correlation function method). By calculating the similarity of the weight ranking results under each method, the optimal combination of subjective and objective weights is determined by using the angle cosine method, so as to improve the accuracy and reliability of weight determination.
In order to verify the feasibility of the proposed method, this study takes the “LD Technology” shared power bank enterprise in the big data credit network as an example, and conducts an empirical analysis. By collecting the index data of the enterprise and combining the fuzzy comprehensive evaluation model, the performance level of the enterprise is comprehensively evaluated. The evaluation results show that the performance level of “LD Technology” is good, but there is still some room for improvement, especially in terms of financing ability, user rating and performance ability.
The contributions of this study are: First, to construct a set of performance evaluation system that adapts to the characteristics of sharing economy enterprises. Second, an improved index weight determination method is proposed, which has improved the accuracy and scientificity of performance evaluation. Third, the feasibility and effectiveness of the proposed method are verified through an empirical analysis, which provides new ideas and methods for the performance evaluation of sharing economy enterprises.
However, there are some limitations in this study, such that the construction of the indicator system may not be comprehensive, and the selection of weight determination methods may be limited by the sample data and research conditions. Future research can further refine the indicators, optimize the weighting method, and expand the scope of an empirical analysis to improve the scientificity and applicability of the research. At the same time, with the continuous development of the sharing economy, the performance evaluation methods and systems also need to be constantly updated and improved to adapt to the new market environment and enterprise needs.

Key words: weight combinations, sharing economy enterprises, performance evaluation, fuzzy comprehensive evaluation method