Generating Generativity

About the Project

Project Summary

Effective innovation is a critical driver of corporate success and growth in the U.S. national economy, and generates useful, novel, and affordable products and services for society. Generative collaborations, group interactions that focus on co-creation, are key to such effective innovation. Organizational researchers have long explored structural characteristics underpinning innovation, yet, there is a need for studying (i) process-based characteristics, i.e., the ways in which groups interact in the course of being generative, and (ii) the role of technology in eliciting group behaviors beneficial to generativity. The recent proliferation of Enterprise Social Media (ESM) promises to create better opportunities for generative collaborations, yet, organizations struggle to establish fully active systems and reap the promised benefits. Leveraging the unparalleled amounts of archival data stored in ESM, this project aims to develop predictive models of the multi-level drivers, processes, and sociotechnical practices of effective ESM-based generative collaborations. Furthermore, following the paradigm of persuasive system design, this project aims to build and evaluate a feedback system, the Cyberinfrastructure for Smart Innovation (CSI). The CSI extracts near real-time data from groups inside the ESM, visualizes their social dynamics and activities, and persuades them to behave in ways beneficial to their generativity. The research will be carried out in three phases: Phase 1: Create a fundamental understanding and predictive models of distinct forms of generative collaborations and their effectiveness through the algorithmic curation and statistical analysis of six years of ESM archival data from the partner organization, Steelcase Inc.; Phase 2: Develop a suite of design guidelines for the proposed CSI using formative and summative user-centered research methods; Phase 3: Evaluate the causal impact of the CSI on generative collaborations, through quasi-experiments within real-world innovation teams at Steelcase and self-reported evaluations with a sample of its client organizations.

Intellectual merit​

ESM represent an essential research context given the innumerable anecdotal claims about the merits of ESM for generativity, but the lack of scientific research validating such claims and explaining when and how these merits occur. The proposed research is thus potentially transformative and will lead to five major intellectual contributions: 1) Improved understanding of the multilevel antecedents of generative collaborations in ESM; 2) Expansion of existing organization science literatures by providing unobtrusive, mixed-method, and sociotechnical insights into processes of generative collaborations; 3) Extension of extant ESM research on the actual impact of these systems; 4) Production of the proposed persuasive feedback system (CSI) intended to foster improved ESM-based generative collaborations; 5) Rigorous empirical testing of the causal effect of the CSI on generativity in real-world groups.

Broader impacts​

ESM spending has been estimated at $100 billion worldwide and currently 80% of companies use some form of ESM. At a time when most organizations are struggling to employ ESM for innovation purposes, there is little scholarly guidance. With growing concerns over enhancing the economic competitiveness of the U.S., understanding the drivers of effective generative collaborations and building systems for eliciting behaviors critical to such effective collaboration is imperative. An integrated education and research program will include a new research seminar where students will work to adapt the CSI for improving the effectiveness of group work in problem-based learning settings thereby creating a second, non-industry testbed for the CSI and enabling the discovery of fundamental theoretical principles that abstract from generative collaboration to learning contexts. The PI will continue to be active in and out of academic circles to present the resulting data, findings, and training materials, through a dedicated website as well as (industry) talks and practitioner-oriented workshops. The PI will also organize academic workshops for sharing the unique mixed-method approach underpinning the proposed project as well as company visits and academe-industry advising seminars with the aim of increasing the representation of women and minorities in STEM fields.


This project is funded by the Cyber-Human Systems program within the Division of Information and Intelligent Systems, Directorate for Computer and Information Science and Engineering: Award number 1749018.