Structuration of Community Knowledge and Community Engagement: Social Media, IoT, and Big Data
Organizing vision theory concerns how a collectively created idea, or an organizing vision, about an IT innovation contributes to diffusion of an IT innovation across a community of members. Despite community knowledge being the foundation of organizing visions, our understanding of the nature of community knowledge and its role in community members’ engagement with IT innovations is limited. Employing a grounded theory approach, we took an initial step to unpack the mutual influence process (i.e., structuration) between community knowledge and community engagement with IT. We investigated the structuration process in the context of three technologies–Social Media, Internet of Things, and Big Data–using a sample of 210 trade journal articles from an 11-year period and 2,559 press releases from a 16-year period. We identified three knowledge facets–namely, vendor- related knowledge, adopter-related knowledge, and knowledge diversity–and uncovered three types of engagement by community member: vendor engagement, adopter engagement, and decentralized engagement. We found that the knowledge facets have differential impacts on community engagement with IT innovations and these impacts vary temporally. We also found that the community engagement has varying effects on community knowledge. This structural processes suggest more complex relationships than described in prior research.
Wang, D. D., Miranda, S., & Kim, I. (2017). Structuration of Community Knowledge and Community Engagement: Social Media, IoT, and Big Data. Academy of Management Annual Meeting Proceedings, 2017(1) Academy of Management (AOM).
The definitive version is available at https://doi.org/10.5465/AMBPP.2017.14914abstract
Business and Information Technology
International Standard Serial Number (ISSN)
Article - Journal
© 2017 Academy of Management (AOM), All rights reserved.
30 Nov 2017