The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Which Problems to Solve? Online Knowledge Sharing and Attention Allocation in Organizations
Open accessAbstract
Why do individuals allocate attention to specific problems in organizations? Viewing online knowledge sharing as a matching process between knowledge providers and problems, we examine attention allocation in the context of an online community within which knowledge providers respond to problems posted by other organization members. We argue that knowledge providers are more likely to allocate attention to solving problems that more closely match their expertise, but that decisions to allocate attention are also influenced by problem characteristics such as length, breadth, and novelty, as well as by problem crowding. Analyzing 1,251 realized matches and 12,510 nonrealized matches among knowledge providers and problems posted over a 32-month period on an online discussion forum within a global engineering firm, we find evidence to support our claim that attention allocation is driven by the features of a particular provider–problem match, thereby shifting the discourse from knowledge provider–seeker relationships to knowledge provider–problem matches. The implications for theories of knowledge sharing, matching processes, and managerial attention are discussed.
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Citations
Cites
Situated Learning: Legitimate Peripheral Participation
Lave, J., & Wenger, E. (1991) · Cambridge University Press eBooks · doi:10.1017/cbo9780511815355 · Cited by 35,324
Toward a knowledge-based theory of the firm
Grant, R. M. (1996) · Strategic Management Journal · doi:10.1002/smj.4250171110 · Cited by 16,157
Cognitive Load During Problem Solving: Effects on Learning
Sweller, J. (1988) · Cognitive Science · doi:10.1016/0364-0213(88)90023-7 · Cited by 11,048
Exploring internal stickiness: Impediments to the transfer of best practice within the firm
Szulanski, G. (1996) · Strategic Management Journal · doi:10.1002/smj.4250171105 · Cited by 7,839
The Search-Transfer Problem: The Role of Weak Ties in Sharing Knowledge across Organization Subunits
Hansen, M. T. (1999) · Administrative Science Quarterly · doi:10.2307/2667032 · Cited by 5,809 · cited 2×
“…extensive literature on interpersonal knowledge sharing in organizations emphasizes the role of personal connections in facilitating exchanges between individuals, usually through social network ties (e.g., Hansen, 1999; Levin & Cross, 2004; Reagans & McEvily, 2003; Tortoriello & Krackhardt, 2010).”
BackgroundLogistic Regression in Rare Events Data
King, G., & Zeng, L. (2001) · Political Analysis · doi:10.1093/oxfordjournals.pan.a004868 · Cited by 4,316 · cited 2×
“To correct this bias, we used weighted exogenous sampling maximum-likelihood estimation (WESMLE), an approach that weights the contribution of each dyad to the likelihood function and is better than alternative approaches for large samples (King & Zeng, 2001).”
MethodWhat Firms Do? Coordination, Identity, and Learning
Kogut, B., & Zander, U. (1996) · Organization Science · doi:10.1287/orsc.7.5.502 · Cited by 3,078
Cognitive Load Theory and the Format of Instruction
Chandler, P., & Sweller, J. (1991) · Cognition and Instruction · doi:10.1207/s1532690xci0804_2 · Cited by 2,894
What attributes guide the deployment of visual attention and how do they do it?
Wolfe, J. M., & Horowitz, T. S. (2004) · Nature Reviews Neuroscience · doi:10.1038/nrn1411 · Cited by 1,766 · cited 1×
“Longer problems take upmore space on the screen, dominating a provider’s field of vision and crowding out other stimuli (see Parkhurst, Law, & Niebur, 2002; Wolfe & Horowitz, 2004).”
BackgroundLakhani, K. R., & Wolf, R. G. (2003) · doi:10.2139/ssrn.443040 · Cited by 1,531
Technology Transfer by Multinational Firms: The Resource Cost of Transferring Technological Know-How
Teece, D. J. (1977) · The Economic Journal · doi:10.2307/2232084 · Cited by 1,464
Eggers, J. P., & Kaplan, S. (2009) · Organization Science · doi:10.1287/orsc.1080.0401 · Cited by 774 · cited 1×
“It has long been recognized that problems compete for the attention of members (e.g., Cyert & March, 1963; Simon, 1947), with wide-ranging implications for decision making in organizations (e.g., Eggers & Kaplan, 2009; Joseph & Ocasio, 2012; Sullivan, 2010).”
Background
Cited by
Schwarzmüller, T., Brosi, P., Duman, D., & Welpe, I. M. (2018) · management revu · doi:10.5771/0935-9915-2018-2-114 · Cited by 409
Wang, B., Liu, Y., & Parker, S. K. (2020) · Academy of Management Annals · doi:10.5465/annals.2018.0127 · Cited by 377
Green at the Top: How CEOs’ Environmental Experience Shapes ESG Performance in Chinese Firms
Lai, Z., Lian, Y., Zhao, F., & Zheng, Y. (2025) · International Review of Economics & Finance · doi:10.1016/j.iref.2025.104451 · Cited by 17
Metadata
- Authors
- Haas, M. R., Criscuolo, P., & George, G.
- Venue
- Academy of Management Journal
- Publisher
- Academy of Management
- Published
- 2015-06
- Volume
- 58
- Issue
- 3
- Pages
- 680-711
- ISSN
- 0001-4273 (ISSN-L)
- 1948-0989
- OpenAlex
- W2041167252
- Cited by
- 284
- References
- 12
- FWCI
- 41.38
- Type
- journal article
- Language
- en
- Open access
- green
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