{"title":"建立了公司数字化水平绩效评价的模糊管理控制模型","authors":"Gergő Thalmeiner , Sándor Gáspár , Zoltán Zéman","doi":"10.1016/j.joitmc.2025.100633","DOIUrl":null,"url":null,"abstract":"<div><div>Measuring digital transformation is inherently complex and multidimensional, with objective evaluation hindered by subjective factors. Existing maturity models and composite indices typically capture readiness and technology adoption but fail to address the subjective nature of digitalization performance. This study develops a novel performance evaluation management control model that explicitly incorporates subjectivity into the assessment process. We design a KPI set that measures firm-level digitalization performance while integrating multiple subjective benchmarks. To manage uncertainty, the model applies triangular fuzzy membership functions, enabling the definition of flexible thresholds and the aggregation of indicators into a composite Digitalization Index. The proposed approach differs from existing frameworks by focusing not on readiness, but on strategic results and operational outcomes, while systematically addressing subjectivity. The model’s applicability is demonstrated through a case study of a Hungarian SME in the food industry. The results show that fuzzy logic provides a dynamic and adaptive evaluation framework that generates management-relevant insights. By handling the inherent subjectivity of digitalization processes, the model offers a robust tool for supporting both strategic and operational decision making.</div></div>","PeriodicalId":16678,"journal":{"name":"Journal of Open Innovation: Technology, Market, and Complexity","volume":"11 4","pages":"Article 100633"},"PeriodicalIF":0.0000,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Developing a fuzzy management control model for the performance evaluation of the company digitalization level\",\"authors\":\"Gergő Thalmeiner , Sándor Gáspár , Zoltán Zéman\",\"doi\":\"10.1016/j.joitmc.2025.100633\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Measuring digital transformation is inherently complex and multidimensional, with objective evaluation hindered by subjective factors. Existing maturity models and composite indices typically capture readiness and technology adoption but fail to address the subjective nature of digitalization performance. This study develops a novel performance evaluation management control model that explicitly incorporates subjectivity into the assessment process. We design a KPI set that measures firm-level digitalization performance while integrating multiple subjective benchmarks. To manage uncertainty, the model applies triangular fuzzy membership functions, enabling the definition of flexible thresholds and the aggregation of indicators into a composite Digitalization Index. The proposed approach differs from existing frameworks by focusing not on readiness, but on strategic results and operational outcomes, while systematically addressing subjectivity. The model’s applicability is demonstrated through a case study of a Hungarian SME in the food industry. The results show that fuzzy logic provides a dynamic and adaptive evaluation framework that generates management-relevant insights. By handling the inherent subjectivity of digitalization processes, the model offers a robust tool for supporting both strategic and operational decision making.</div></div>\",\"PeriodicalId\":16678,\"journal\":{\"name\":\"Journal of Open Innovation: Technology, Market, and Complexity\",\"volume\":\"11 4\",\"pages\":\"Article 100633\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Open Innovation: Technology, Market, and Complexity\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2199853125001684\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Economics, Econometrics and Finance\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Open Innovation: Technology, Market, and Complexity","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2199853125001684","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Economics, Econometrics and Finance","Score":null,"Total":0}
Developing a fuzzy management control model for the performance evaluation of the company digitalization level
Measuring digital transformation is inherently complex and multidimensional, with objective evaluation hindered by subjective factors. Existing maturity models and composite indices typically capture readiness and technology adoption but fail to address the subjective nature of digitalization performance. This study develops a novel performance evaluation management control model that explicitly incorporates subjectivity into the assessment process. We design a KPI set that measures firm-level digitalization performance while integrating multiple subjective benchmarks. To manage uncertainty, the model applies triangular fuzzy membership functions, enabling the definition of flexible thresholds and the aggregation of indicators into a composite Digitalization Index. The proposed approach differs from existing frameworks by focusing not on readiness, but on strategic results and operational outcomes, while systematically addressing subjectivity. The model’s applicability is demonstrated through a case study of a Hungarian SME in the food industry. The results show that fuzzy logic provides a dynamic and adaptive evaluation framework that generates management-relevant insights. By handling the inherent subjectivity of digitalization processes, the model offers a robust tool for supporting both strategic and operational decision making.