Michela Arnaboldi [email protected] Politecnico di Milano
Hans de Bruijn [email protected] TU Delft
Ileana Steccolini [email protected] Essex Business School, University of Essex
Haiko van der Voort [email protected] TU Delft
What is the special issue about?
The objective of this special issue is to catalyse attention on the role of algorithms in performance management. Algorithms condition the way data is interpreted to such an extent that they shape our lives, our organizational choices, our behaviour and our public services, whether directly or indirectly. What is more, this phenomenon is also rapidly changing performance management systems at different levels, although there is no overarching idea that explains how. The algorithms behind the many different devices and technologies (mobile phones, internet of things, etc.) can potentially improve performance measurements; for example, the sensors used to monitor a wide range of processes provide data that can help to improve risk assessment. Algorithms, however, require changes that are not merely to the method of calculation but entail transforming the entire risk management cycle, bringing into clear focus the non-neutrality of data, data analysts and decision makers.
Connected to this is human-machine interaction and the fact that numbers have now entered this relationship, a process that has expanded to auditing and accounting practices, where machine learning and algorithms are substituting human work, with deep implications for this profession.
Beyond altering the performance measurement cycle, the implications of algorithms have raised ethical questions about performance management itself. For example, the internet of things and apps used in delivery services can protect personnel, but at the same time raises serious ethical and privacy concerns. What are the performance management boundaries in this new world?
Specific topics we invite you to provide submissions on:
We welcome qualitative studies from a wide range of theoretical, methodological and empirical approaches which deliver further evidence on the complex duality between algorithm- and human-based actions, and their impact on performance management, risk management, accounting and accountability.
Possible themes include:
- What are the strengths and weaknesses of algorithms compared to human beings in the fields of performance management and accounting? Which types of jobs or institutional settings are best suited to algorithms in preference to human work? And why? (e.g. auditing processes. healthcare. etc.)
- In a hybrid world, mediators are expected to play a critical role, while mediation underpins the entire structure of accounting (Quattrone, 2016): How are algorithms changing the roles of intermediaries in the processing of data within organizations? How are algorithms changing roles and cooperation in inter-organizational relationships? For instance, will government and business be excluded from complex accountability chains when algorithms become ubiquitous, or will intermediaries find other ways to guide this relationship?
- To what extent can reliance on algorithms free us from bias? Or do they reinforce biases and/or create new forms of biases?
- What are the strategies for dealing with the perceived risks of algorithm-based decision-making? Under what conditions will these strategies be effective?
Schedule and deadlines
Submission deadline: 1 March 2021
Arnaboldi, M., Busco, C., & Cuganesan, S. (2017). Accounting, accountability, social media and big data: revolution or hype? Accounting, Auditing & Accountability Journal, 30(4), 762-776.
Greenman, C. (2017). Exploring the impact of artificial intelligence on the accounting profession. Journal of Research in Business, Economics and Management, 8(3), 1451.
Kokina, J., & Davenport, T. H. (2017). The emergence of artificial intelligence: How automation is changing auditing. Journal of Emerging Technologies in Accounting, 14(1), 115-122.
Moll, J., & Yigitbasioglu, O. (2019). The role of internet-related technologies in shaping the work of accountants: New directions for accounting research. The British Accounting Review, 51(6), 100833.