Summary of the talk:
The discourse on the structure of technology and modularity typically focuses on the macro-level: Technology structures are modular if they limit the degree to which changes propagate throughout a complex system, constituted by how interdependencies among all parts pattern into a nested design structure with shared parts at the top transmitting functionalities via central parts down to the bottom. In this talk, I shift the focus to micro-level structures of interdependencies that reflect the local decisions of designers with limited rationality. Today many complex technical systems are the result of parallel and iterative design efforts of a large number of actors. There is no central architect. Each designer engages in a purposive “local” and situated search for a technical solution for a design problem and makes choices related to the most fundamental micro-structures of interdependence: finite set of five distinct types of directed interdependencies between three parts. I refer to these building blocks of modularity as design motifs, a term first introduced in biology.
I introduce a design motif theory that builds upon the concept of design motifs to understand technology structures and sources of macro-level modularity. This theory assumes that value-seeking designers weigh costs and benefits when creating motifs. One of our recent studies explores this design motif theory of technology structure using 20,000 different design structures of Nova, a cloud computing OSS product in Open Stack. The design of complex technologies implies not only direct but also indirect coordination and collaboration among dispersed actors. Thus, at the end of my talk – if time allows – I will present new research seeking to uncover the endogenous micro-level mechanisms of interactions among actors that cause the emergence of efficient core-periphery coordination structures as a complex technology structure evolves. Specifically, I focus on artifact-based coordination following principles of stigmergy, often used to describe coordination among social insects. In a recent study, my collaborator and I specify and empirically examine an Exponential Random Graph Model (p*) to study the significance of three relational mechanisms - preferential attachment, knowledge similarity, and triadic closure. I invite the audience to discuss and brainstorm how this stream of research can be used to study technology evolution, scaling, and coordination to shape future research on the structure of technology.
Papers related to this talk and relevant literature of potential interest:
- Brunswicker, Sabine, and Satyam Mukherjee. (in print). The Microstructure of Modularity in
Design: A Design Motif View. Industrial Corporate Change.
- Brunswicker, Sabine, and Satyam Mukherjee (2021). Evolution of Coordination Structures in
OSS Software: An Exponential Random Graph Model. Academy of Management Best Paper
Proceedings (2021):15832. doi: 10.5465/AMBPP.2021.267.
- Brunswicker, Sabine, and Mukherjee, Satyam (under review, 2nd round). Emergence of Artifact-
Mediated Collaboration Structures in Open Source Software (OSS) Evolution. MIS Quarterly.
- Baldwin C, Clark KB (2000) The Power of Modularity (MIT Press, Cambridge, MA).
- Baldwin C, von Hippel E (2011) Modeling a Paradigm Shift: From Producer Innovation to User
and Open Collaborative Innovation. Organization Science 22(6):1399–1417.
- Milo R, Shen-Orr S, Itzkovitz S, Kashtan N, Chklovskii D, Alon U (2002) Network Motifs: Simple
Building Blocks of Complex Networks. Science 298(5594):824–827.
- Puranam P (2018) The microstructure of organizations (Oxford University Press).
About the speaker:Dr. Sabine Brunswicker is a Full Professor of Digital Innovation at Purdue University and a Visiting Professor at Northwestern’s Kellogg School of Management. At Purdue, Dr. Brunswicker is the Founder and Director of a university-wide Research Center for Open Digital Innovation (RCODI). In her interdisciplinary research on digital innovation, she is particularly focused on the role of digital technologies as a means to leverage distributed machine and human intelligence when solving complex problems. Examples of digital innovation she and her team study are: Open source software (OSS) communities, OSS supply chains, crowdsourcing for innovation, data science hackathons/challenges, smart energy communities, conversational AI for legal services, human-swarm intelligence in unmanned aviation (UAVs). Her research relies on methods of computational social science, such as agent-based modeling, and advanced network analysis, and increasingly also on large online field experiments to advance theories and models of complex technological and social systems. Her work has been funded by NSF, NIH, DARPA, the European Commission (EC), and industry and philanthropic donors. As part of her research or broader engagement efforts, she collaborates with industry (e.g. Red Hat, Accenture) policymakers.
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