{"title":"V-Matrix: A wave theory of value creation for big data","authors":"Guido L. Geerts , Daniel E. O'Leary","doi":"10.1016/j.accinf.2022.100575","DOIUrl":null,"url":null,"abstract":"<div><p>This paper examines the “V-Matrix” and provides a wave theory life cycle model of organizations’ adoption of big data. The V-Matrix is based on the big data five “V’s”: Volume, Velocity, Variety, Veracity, and Value and captures and enumerates the different potential states that an organization can go through as part of its adoption and evolution towards big data. We extend the V-Matrix to a state space approach in order to provide a characterization of the adoption of big data technologies in an organization. We develop and use a wave theory of implementation to accommodate a firm’s movement through the V-Matrix. Accordingly, the V-Matrix provides a life cycle model of organizational use of the different aspects of big data. In addition, the model can help organizations’ plan for decision-making use of big data as they anticipate movement from one state to another, as they add big data capabilities. As part of this analysis, the paper examines some of the issues that occur in the different states, including synergies and other issues associated with co-occurrence of different V’s with each other. Finally, this paper integrates the V-Matrix with other data analytic life cycles and examines some of the implications of those models.</p></div>","PeriodicalId":47170,"journal":{"name":"International Journal of Accounting Information Systems","volume":null,"pages":null},"PeriodicalIF":4.1000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Accounting Information Systems","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1467089522000276","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 6
Abstract
This paper examines the “V-Matrix” and provides a wave theory life cycle model of organizations’ adoption of big data. The V-Matrix is based on the big data five “V’s”: Volume, Velocity, Variety, Veracity, and Value and captures and enumerates the different potential states that an organization can go through as part of its adoption and evolution towards big data. We extend the V-Matrix to a state space approach in order to provide a characterization of the adoption of big data technologies in an organization. We develop and use a wave theory of implementation to accommodate a firm’s movement through the V-Matrix. Accordingly, the V-Matrix provides a life cycle model of organizational use of the different aspects of big data. In addition, the model can help organizations’ plan for decision-making use of big data as they anticipate movement from one state to another, as they add big data capabilities. As part of this analysis, the paper examines some of the issues that occur in the different states, including synergies and other issues associated with co-occurrence of different V’s with each other. Finally, this paper integrates the V-Matrix with other data analytic life cycles and examines some of the implications of those models.
期刊介绍:
The International Journal of Accounting Information Systems will publish thoughtful, well developed articles that examine the rapidly evolving relationship between accounting and information technology. Articles may range from empirical to analytical, from practice-based to the development of new techniques, but must be related to problems facing the integration of accounting and information technology. The journal will address (but will not limit itself to) the following specific issues: control and auditability of information systems; management of information technology; artificial intelligence research in accounting; development issues in accounting and information systems; human factors issues related to information technology; development of theories related to information technology; methodological issues in information technology research; information systems validation; human–computer interaction research in accounting information systems. The journal welcomes and encourages articles from both practitioners and academicians.