Start Date
10-12-2017 12:00 AM
Description
At the intersection of technology and organizing, processes emerge, evolve and take flight. IS research struggles to keep up with the continual change that characterizes these phenomena. Our thesis is we need better tools and concepts to study “reality in flight”. We introduce the ideas of “strong process theory” to IS research and relate it to existing notions of process models as used in mining, discovery and design. The challenge is to develop methods that are aligned with strong assumptions about continuous change and relational ontology. We report on progress with a new version of ThreadNet, which uses trace data to visualize patterns of action. ThreadNet borrows from more sophisticated process mining tools, but minimizes a priori ontological assumptions to maximize flexibility of interpretation, including contextuality, multiplicity, temporality, relationality and change. Like the processes it helps analyzing, ThreadNet is evolving. Here we describe current functionality and planned extensions.
Recommended Citation
Pentland, Brian; Recker, Jan; and Kim, Inkyu, "Capturing reality in flight? Empirical tools for strong process theory" (2017). ICIS 2017 Proceedings. 4.
https://aisel.aisnet.org/icis2017/ResearchMethods/Presentations/4
Capturing reality in flight? Empirical tools for strong process theory
At the intersection of technology and organizing, processes emerge, evolve and take flight. IS research struggles to keep up with the continual change that characterizes these phenomena. Our thesis is we need better tools and concepts to study “reality in flight”. We introduce the ideas of “strong process theory” to IS research and relate it to existing notions of process models as used in mining, discovery and design. The challenge is to develop methods that are aligned with strong assumptions about continuous change and relational ontology. We report on progress with a new version of ThreadNet, which uses trace data to visualize patterns of action. ThreadNet borrows from more sophisticated process mining tools, but minimizes a priori ontological assumptions to maximize flexibility of interpretation, including contextuality, multiplicity, temporality, relationality and change. Like the processes it helps analyzing, ThreadNet is evolving. Here we describe current functionality and planned extensions.