系统管理学报2026，Vol.35Issue(2)：573-586,14.DOI:10.3969/j.issn2097-4558.2026.02.019
基于价值网络与SCIS大数据补全方法的现代服务企业竞争力评价
Competitiveness Evaluation of Modern Service Enterprises Based on Value Networks and SCIS Big Data Imputation Method
摘要
Abstract
In response to the cross-border integration,digitalization,and intelligentization characterizing the modern service sector,this paper introduces value network theory and develops a competitiveness evaluation framework for modern service enterprises across three dimensions:"value creation,value delivery,and value acquisition."Large-scale data imputation is performed using machine learning combined with the SCIS method,enabling the identification and positioning of modern service enterprises,and resulting in an analysis dataset covering 580 000 enterprises,including 791 listed companies.For indicator weighting,a combined approach of the CRITIC method and entropy method is employed.The evaluation results indicate that although competitiveness in industries and their sub-sectors has improved in vertical comparisons,overall levels remain relatively low,and multidimensional imbalances exist across industries,within industries,and among indicators.The framework developed in this paper is applicable to the analysis of modern service enterprise competitiveness in China,offering valuable theoretical and practical guidance for relevant enterprises and policymakers.关键词
现代服务业/企业竞争力/价值网络/数据补全/评价指标体系Key words
modern service sector/competitiveness of enterprises/value network/data imputation/evaluation indicator system分类
管理科学引用本文复制引用
雷李楠,张琼文,沈思祎,苗晓晔,吴晓波..基于价值网络与SCIS大数据补全方法的现代服务企业竞争力评价[J].系统管理学报,2026,35(2):573-586,14.基金项目
国家重点研发计划项目(2022YFF0902900) （2022YFF0902900）
国家自然科学基金资助项目(72372147) （72372147）
