Offering Accounts of Complex IS-Phenomena: Towards a Combination of Mechanistic Predictions and Generative Explanations

Louise Harder Fischer, Christine Abdalla Mikhaeil

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Information Systems (IS) phenomena have become increasingly volatile, complex and fast changing. Capturing their essence is an increasingly daunting task. Data science have emerged in awe to predict future outcomes. Decision-making thus becomes faster while data become bigger. Yet, in the wake of this promising path, many of these predictions lack accuracy due to the unpredictability of complex phenomena. That is why researchers promote the importance of thick qualitative data analysis as a way of seeking explanations of the generativity underlying complex phenomena. This approach is (in comparison) slow, but can answer why events occurred. Thus, we argue that sound accounts of complex IS-phenomena must come from a combinatory approach of fast predictions with slower accounts. Predictions apply laws theorized as causal mechanisms. When these outcomes do not arise, we suggest applying explanatory accounts that apply a different form of causality - generative mechanisms. Generative mechanisms can explain unpredictable outcomes, but can only be inferred through longitudinal qualitative studies. This paper opens up a research agenda for combinatory approaches of fast mechanistic predictions from big data and slower generative explanations from thick data. This combination will help capturing the essence of complex socio-technical phenomena in our capricious digitalized world.
Original languageEnglish
Title of host publicationECIS 2019 Proceedings
Number of pages9
Place of PublicationAtlanta, GA
PublisherAssociation for Information Systems. AIS Electronic Library (AISeL)
Publication date2019
ISBN (Print)9781733632508
Publication statusPublished - 2019
EventThe 27th European Conference on Information Systems (ECIS) 2019: Information Systems for a Sharing Society - Stockholm University, Stockholm, Sweden
Duration: 8 Jun 201914 Jun 2019
Conference number: 27
http://ecis2019.eu/

Conference

ConferenceThe 27th European Conference on Information Systems (ECIS) 2019
Number27
LocationStockholm University
CountrySweden
CityStockholm
Period08/06/201914/06/2019
Internet address
SeriesProceedings of the European Conference on Information Systems
ISSN0000-0034

Keywords

  • Big data
  • Thick data
  • Explanation
  • Predictions
  • Generative mechanisms
  • Causal mechanisms

Cite this

Fischer, L. H., & Abdalla Mikhaeil, C. (2019). Offering Accounts of Complex IS-Phenomena: Towards a Combination of Mechanistic Predictions and Generative Explanations. In ECIS 2019 Proceedings Association for Information Systems. AIS Electronic Library (AISeL). Proceedings of the European Conference on Information Systems http://aisel.aisnet.org/cgi/viewcontent.cgi?article=1070&context=ecis2019_rip