Abstract
AbstractDigitalisation is having profound effects on how enterprises function. Its impact on accounting research is growing as the rise of the internet, mobile technologies and digital economy tools generate depth, breadth and variety of data that far exceed what researchers have had access to in the past. But whilst social scientists interested in organisational issues are starting to question conventional methodological approaches to the study of contexts where digital data forms are drawn upon, little such concern has been voiced in the management accounting literature. This paper seeks to explore the continued applicability of conventional methodological thinking when carrying out investigations within digital data environments to inform management accounting studies. It considers why digitalisation impacts methodological precepts, identifies how descriptive and explanatory modes of questioning which management accountants have conventionally opted for need rethinking, discusses ways in which digital data characteristics alter what can be drawn from empirical studies, and points to the potential offered within digitalised settings for methodological advance. It concludes by highlighting the necessity, where digitalisation exists, to question modes of posing questions and to reconsider the applicability of methodological precepts deployed by management accounting researchers to date.
Publisher
Springer Science and Business Media LLC
Subject
Management of Technology and Innovation,Management Science and Operations Research,Strategy and Management,Management Information Systems,Accounting
Reference98 articles.
1. Agarwal, R., & Nijhawan, S. (2016). Big data and continuous monitoring: A synergy whose time has come? Internal Auditing,31(1), 19–26.
2. Aguinis, H., Cascio, W. F., & Ramani, R. S. (2017). Science’s reproducibility and replicability crisis: International business is not immune. Journal of International Business Studies,48, 653–663.
3. Al-Htaybat, K., & Alberti-Alhtaybat, L. (2017). Big data and corporate reporting: impacts and paradoxes. Accounting, Auditing and Accountability Journal,30(4), 850–873.
4. Alvarez, M. (2016). Computational social science: Discovery and prediction. Cambridge: Cambridge University Press.
5. Appelbaum, D., Kogan, A., & Vasarhelyi, M. (2017a). Big data and analytics in the modern audit engagement: Research needs. Auditing: A Journal of Practice and Theory,36(4), 1–27.
Cited by
57 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献