{"title":"分析对决策的价值:管理者和分析师的角色","authors":"Sakshi Srivastava, Gaurav Dixit","doi":"10.1080/08874417.2023.2255557","DOIUrl":null,"url":null,"abstract":"ABSTRACTDespite the hype and investments, the successful use of analytics demands human-intensive efforts to exploit its full potential. The mixed outcomes of analytics initiatives indicate the need to dive deep into how analytical activities and processes contribute to business value creation. Building on the knowledge-based and dynamic capability views and following the analytics process perspective, we examine managers’ and analysts’ roles in creating value for data-driven decision-making. We conducted Q-sorting, exploratory factor analysis, and partial least squares analysis using data from 159 firms with low to medium-level analytics. As part of our research, we conceptualize and develop two novel multi-dimensional constructs: 1) managerial analytics competency and 2) technical analytics competency and then empirically investigate their impact on decision-making efficiency and effectiveness. Our results reveal the crucial role of managerial analytics competency in driving the technical analytics competency for improved decision-making. Furthermore, our research offers significant contributions to theory and practice.KEYWORDS: Data-driven decision-makinganalyticscompetencyknowledge-based viewconstruct development Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThe work was supported by the Sponsored Research & Industrial Consultancy office, Indian Institute of Technology Roorkee [MSD/FIG/100703].","PeriodicalId":54855,"journal":{"name":"Journal of Computer Information Systems","volume":"205 1","pages":"0"},"PeriodicalIF":2.5000,"publicationDate":"2023-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Value of Analytics for Decision-Making: Role of Managers and Analysts\",\"authors\":\"Sakshi Srivastava, Gaurav Dixit\",\"doi\":\"10.1080/08874417.2023.2255557\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACTDespite the hype and investments, the successful use of analytics demands human-intensive efforts to exploit its full potential. The mixed outcomes of analytics initiatives indicate the need to dive deep into how analytical activities and processes contribute to business value creation. Building on the knowledge-based and dynamic capability views and following the analytics process perspective, we examine managers’ and analysts’ roles in creating value for data-driven decision-making. We conducted Q-sorting, exploratory factor analysis, and partial least squares analysis using data from 159 firms with low to medium-level analytics. As part of our research, we conceptualize and develop two novel multi-dimensional constructs: 1) managerial analytics competency and 2) technical analytics competency and then empirically investigate their impact on decision-making efficiency and effectiveness. Our results reveal the crucial role of managerial analytics competency in driving the technical analytics competency for improved decision-making. Furthermore, our research offers significant contributions to theory and practice.KEYWORDS: Data-driven decision-makinganalyticscompetencyknowledge-based viewconstruct development Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThe work was supported by the Sponsored Research & Industrial Consultancy office, Indian Institute of Technology Roorkee [MSD/FIG/100703].\",\"PeriodicalId\":54855,\"journal\":{\"name\":\"Journal of Computer Information Systems\",\"volume\":\"205 1\",\"pages\":\"0\"},\"PeriodicalIF\":2.5000,\"publicationDate\":\"2023-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Computer Information Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/08874417.2023.2255557\",\"RegionNum\":4,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Computer Information Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/08874417.2023.2255557","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Value of Analytics for Decision-Making: Role of Managers and Analysts
ABSTRACTDespite the hype and investments, the successful use of analytics demands human-intensive efforts to exploit its full potential. The mixed outcomes of analytics initiatives indicate the need to dive deep into how analytical activities and processes contribute to business value creation. Building on the knowledge-based and dynamic capability views and following the analytics process perspective, we examine managers’ and analysts’ roles in creating value for data-driven decision-making. We conducted Q-sorting, exploratory factor analysis, and partial least squares analysis using data from 159 firms with low to medium-level analytics. As part of our research, we conceptualize and develop two novel multi-dimensional constructs: 1) managerial analytics competency and 2) technical analytics competency and then empirically investigate their impact on decision-making efficiency and effectiveness. Our results reveal the crucial role of managerial analytics competency in driving the technical analytics competency for improved decision-making. Furthermore, our research offers significant contributions to theory and practice.KEYWORDS: Data-driven decision-makinganalyticscompetencyknowledge-based viewconstruct development Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThe work was supported by the Sponsored Research & Industrial Consultancy office, Indian Institute of Technology Roorkee [MSD/FIG/100703].
期刊介绍:
The Journal of Computer Information Systems (JCIS) aims to publish manuscripts that explore information systems and technology research and thus develop computer information systems globally.
We encourage manuscripts that cover the following topic areas:
-Analytics, Business Intelligence, Decision Support Systems in Computer Information Systems
- Mobile Technology, Mobile Applications
- Human-Computer Interaction
- Information and/or Technology Management, Organizational Behavior & Culture
- Data Management, Data Mining, Database Design and Development
- E-Commerce Technology and Issues in computer information systems
- Computer systems enterprise architecture, enterprise resource planning
- Ethical and Legal Issues of IT
- Health Informatics
- Information Assurance and Security--Cyber Security, Cyber Forensics
- IT Project Management
- Knowledge Management in computer information systems
- Networks and/or Telecommunications
- Systems Analysis, Design, and/or Implementation
- Web Programming and Development
- Curriculum Issues, Instructional Issues, Capstone Courses, Specialized Curriculum Accreditation
- E-Learning Technologies, Analytics, Future