{"title":"衡量商业智能和分析系统的成功:文献综述","authors":"Noor Ul Ain , William H. DeLone , Giovanni Vaia","doi":"10.1016/j.technovation.2025.103277","DOIUrl":null,"url":null,"abstract":"<div><div>Technology-based solutions such as business intelligence and analytics (BI&A) systems have become indispensable for organizations due to their ability to support decision-making. Recent developments in big data availability and more powerful analytical tools have increased the potential value of BI&A systems. However, academic and practitioner-oriented research suggests that the potential success of BI&A systems has not yet been fully realized by most organizations. Existing studies have attempted to evaluate the effectiveness and success of BI&A systems by proposing various success measures. However, these studies have generated inconsistent results, limiting the ability to compare and generalize the findings. Therefore, this study takes a step forward by proposing an updated, comprehensive, and consolidated set of success measures for this unique class of information systems. Using a systematic literature review approach, this study examined and synthesized BI&A systems success measures across 173 past studies using the DeLone & McLean IS success framework. Findings revealed success measures such as ease of use, information accuracy, and financial performance that are consistently applied to the measurement of BI&A systems, and importantly, other recommended measures such as system features, presentation format, and decision-making performance that are uniquely important to BI&A systems but infrequently applied. Finally, a comprehensive set of BI&A success measures is proposed for future empirical research studies and practitioner use.</div></div>","PeriodicalId":49444,"journal":{"name":"Technovation","volume":"146 ","pages":"Article 103277"},"PeriodicalIF":11.1000,"publicationDate":"2025-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Measuring the success of business intelligence and analytics systems: A literature review\",\"authors\":\"Noor Ul Ain , William H. DeLone , Giovanni Vaia\",\"doi\":\"10.1016/j.technovation.2025.103277\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Technology-based solutions such as business intelligence and analytics (BI&A) systems have become indispensable for organizations due to their ability to support decision-making. Recent developments in big data availability and more powerful analytical tools have increased the potential value of BI&A systems. However, academic and practitioner-oriented research suggests that the potential success of BI&A systems has not yet been fully realized by most organizations. Existing studies have attempted to evaluate the effectiveness and success of BI&A systems by proposing various success measures. However, these studies have generated inconsistent results, limiting the ability to compare and generalize the findings. Therefore, this study takes a step forward by proposing an updated, comprehensive, and consolidated set of success measures for this unique class of information systems. Using a systematic literature review approach, this study examined and synthesized BI&A systems success measures across 173 past studies using the DeLone & McLean IS success framework. Findings revealed success measures such as ease of use, information accuracy, and financial performance that are consistently applied to the measurement of BI&A systems, and importantly, other recommended measures such as system features, presentation format, and decision-making performance that are uniquely important to BI&A systems but infrequently applied. Finally, a comprehensive set of BI&A success measures is proposed for future empirical research studies and practitioner use.</div></div>\",\"PeriodicalId\":49444,\"journal\":{\"name\":\"Technovation\",\"volume\":\"146 \",\"pages\":\"Article 103277\"},\"PeriodicalIF\":11.1000,\"publicationDate\":\"2025-07-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Technovation\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0166497225001099\",\"RegionNum\":1,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, INDUSTRIAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Technovation","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0166497225001099","RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, INDUSTRIAL","Score":null,"Total":0}
Measuring the success of business intelligence and analytics systems: A literature review
Technology-based solutions such as business intelligence and analytics (BI&A) systems have become indispensable for organizations due to their ability to support decision-making. Recent developments in big data availability and more powerful analytical tools have increased the potential value of BI&A systems. However, academic and practitioner-oriented research suggests that the potential success of BI&A systems has not yet been fully realized by most organizations. Existing studies have attempted to evaluate the effectiveness and success of BI&A systems by proposing various success measures. However, these studies have generated inconsistent results, limiting the ability to compare and generalize the findings. Therefore, this study takes a step forward by proposing an updated, comprehensive, and consolidated set of success measures for this unique class of information systems. Using a systematic literature review approach, this study examined and synthesized BI&A systems success measures across 173 past studies using the DeLone & McLean IS success framework. Findings revealed success measures such as ease of use, information accuracy, and financial performance that are consistently applied to the measurement of BI&A systems, and importantly, other recommended measures such as system features, presentation format, and decision-making performance that are uniquely important to BI&A systems but infrequently applied. Finally, a comprehensive set of BI&A success measures is proposed for future empirical research studies and practitioner use.
期刊介绍:
The interdisciplinary journal Technovation covers various aspects of technological innovation, exploring processes, products, and social impacts. It examines innovation in both process and product realms, including social innovations like regulatory frameworks and non-economic benefits. Topics range from emerging trends and capital for development to managing technology-intensive ventures and innovation in organizations of different sizes. It also discusses organizational structures, investment strategies for science and technology enterprises, and the roles of technological innovators. Additionally, it addresses technology transfer between developing countries and innovation across enterprise, political, and economic systems.