IDeaSInterpretive Data Science
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IDeaS 2019 · Edmonton

Interpretive Approaches to Data Science in Management Research

Dates
October 25–26, 2019, with informal dinners on October 24
Venue
Alberta School of Business, University of Alberta
Participants
50 faculty and doctoral students from more than 25 institutions
Organizers
Vern Glaser, Tim Hannigan, Dev Jennings, Jennifer Sloan, Chris Steele, Rodrigo Valadao
Sponsors
Society for the Advancement of Management Studies; CCCSR; UBC Sauder W. Maurice Young Centre for Entrepreneurship and Venture Capital Research

Overview

The first IDeaS workshop was a two-day intensive event that gave management doctoral students and faculty working on data science, big data, and artificial intelligence an opportunity to discuss and advance their ongoing research. It grew out of a University of Alberta–UBC collaboration, itself an outgrowth of the Alberta School of Business Data Analytics Group.

The workshop was built to bridge three communities that are normally kept apart: scholars using computational techniques reflexively and theoretically; ethnographers studying the everyday work of data analysts; and researchers examining the societal transformations that follow from data and analytics.

Vern Glaser's opening anchored the event in rendering — the idea, developed in Hannigan et al. (2019), that turning corpora into algorithms and then into theoretical artifacts is an inherently interpretive process. It posed the question the community has returned to ever since: how can we use data science and algorithms to develop new management theory?

Program

Roundtable themes: qualitative studies of deviance and crowds; open strategy; blockchain and distributed trust; topic modeling and field emergence; applied topic modeling; quantitative entrepreneurship and technology battles. Fourteen student submissions came from Oxford, ESADE, Hertie, Leuphana, Ivey, UBC, Washington, Drexel, Oregon, Bologna, Warwick, and Alberta.

Participants

Featured speakers included Joseph Porac, Wendy Espeland, Laura Nelson, Mark Kennedy, and Marc-David Seidel.