As an LSE Fellow and Postdoctoral Research Fellow in Digital Economy at INDEX, I hold a PhD in Information Systems from the Department of Management at the London School of Economics and Political Science. My research focuses on the essential elements of big data value chain, from the development of data infrastructures, through the practices of data production, analysis and use, to the monetisation of big data through various business models. Specifically, I focus on understanding how organisations derive value from data and how analytics support organisational decision-making and management, and I investigate the development of data infrastructures and ecosystems. In my research, I combine qualitative and quantitative approaches to research, blending the case study methodology with computational methods in social sciences. My research programme is geared towards information systems and management journals. I am committed to multidisciplinary teaching and keen to explore constructive alignment in information systems, as well as the use of online and technology-based approaches to effective learning. I serve as a reviewer for top journals and conferences in the field, and regularly organise and volunteer at workshops and events. Both my research and teaching benefit from past industry experience as an entrepreneur in e-learning, IT and communication.
Stelmaszak, M., & Aaltonen, A. (2018). Toward a Bidirectional View of Causality in Big Data Analytics: The Case of Learning Analytics. Academy of Management Global Proceedings, Vol. Surrey, No. 2018.
Aaltonen, A. & Stelmaszak, M. Big Data, Analytics and the Rise of Con-figuration Work.
Stelmaszak, M. & Aaltonen, A. Working in the Analytical Cage: The Decline of Transformative Agency in the Age of Analytical Organizing.
Stelmaszak, M. Evaluative Drift in Knowledge Work: Evaluating Knowledge Workers’ Performance with Analytics.
Stelmaszak, M. Data as Objects of Tensions: Co-creating Valuable Data in Infrastructuring Work.
Stelmaszak, M. Data is in the Eye of the Beholder. Understanding the Characteristics and Value of Data through Bourdieu’s Notion of Capital.
Stelmaszak, M. Getting emotional about analytics: revisiting attitudes, IT cues and emotions at work.
Work in progress
Aaltonen, A., Stelmaszak, M. & Lopez, D. Customizing Learning Journeys with Learning Analytics: A Reactivity Theory Approach.
Stelmaszak, M., Parry, G. & Maull, R. Data Supply Chain. Governance Mechanisms in the Supply of Big Data.
Stelmaszak, M. & Aaltonen, A. Acceleration with data: are faster decisions always better? A study of Stack Exchange.
Stelmaszak, M. & Aaltonen, A. (2019). Big Data, Analytics and the Rise of Con-figuration Work. 8th Changing Nature of Work (CNoW) Workshop: Working Smarter with ICT, 15 December 2019, Munich, Germany.
Stelmaszak, M. (2019). Between a Data Ecosystem and a Data Infrastructure. The Design, Development and Implementation of a Learning Analytics Platform in the UK. 6th Innovation in Information Infrastructures (III) Workshop, Surrey Business School, University of Surrey.
Stelmaszak, M. & Aaltonen, A. (2019). Working in the Analytical Cage: Big Data Analytics and Organisational Change. European Group for Organizational Studies (EGOS) Colloquium 2019, 3-6 July 2019, Edinburgh, UK.
Stelmaszak, M. & Aaltonen, A. (2018). Toward a Bidirectional View of Causality in Big Data Analytics: The Case of Learning Analytics. Academy of Management Specialized Conference Big Data and Managing in a Digital Economy, 18-20 April 2018, Surrey, UK.
Stelmaszak, M. & Aaltonen, A. (2018). Closing the Loop of Big Data Analytics: the Case of Learning Analytics. European Conference on Information Systems (ECIS) 2018, 23-28 June 2019, Portsmouth, UK.