The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
Not All Events Are Attended Equally: Toward a Middle-Range Theory of Industry Attention to External Events
Abstract
This paper builds on prior theory and research on attention and identity to examine whether and how industries publicly attend to external events. Events are critical triggers of institutional transformation and industry evolution. However, they must first become the focus of public attention to have this effect. We draw on a paired case comparison of media coverage of eight nonroutine events affecting the natural environment and the U.S. chemical industry. We employ both deductive and inductive analysis to develop a model and hypotheses to explain two research questions. First, what determines the initial public attention to an event? Second, when and why do certain events attain high and sustained levels of industry attention? A key inference is that whether an event receives industry-level attention depends on either outsiders holding the industry accountable for the event, or insiders' internal concerns with the industry image. We further infer that an event can be transformed into a critical issue for an industry, warranting sustained attention, if there is contestation with outsiders over the accountability for the event and its enactment, and internal contradictions and challenges to the industry's identity.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The Discovery of Grounded Theory; Strategies for Qualitative Research
Glaser, B. G., Strauss, A. L., & Strutzel, E. (1968) · Nursing Research · doi:10.1097/00006199-196807000-00014 · Cited by 39,449
Building Theories from Case Study Research
Eisenhardt, K. M. (1989) · The Academy of Management Review · doi:10.2307/258557 · Cited by 17,455
Designing Social Inquiry: Scientific Inference in Qualitative Research
King, G., Keohane, R. O., & Verba, S. (1994) · Princeton University Press · doi:10.1515/9781400821211 · Cited by 7,225
The Uses of Comparative History in Macrosocial Inquiry
Skocpol, T., & Somers, M. (1980) · Comparative Studies in Society and History · doi:10.1017/s0010417500009282 · Cited by 1,074 · cited 4×
“This research uses historical comparisons primarily for the purpose of making causal inferences about macro-level structures and processes (Skocpol and Somers, 1980: 181).”
BackgroundMethodInfluential
Cited by
Institutional Complexity and Organizational Responses
Greenwood, R., Raynard, M., Kodeih, F., Micelotta, E. R., & Lounsbury, M. (2011) · Academy of Management Annals · doi:10.5465/19416520.2011.590299 · Cited by 3,519
Barnett, M. L. (2007) · Academy of Management Review · doi:10.5465/amr.2007.25275520 · Cited by 2,060
Sensemaking in organizations: Taking stock and moving forward
Maitlis, S., & Christianson, M. (2014) · Academy of Management Annals · doi:10.5465/19416520.2014.873177 · Cited by 1,764
The Liability of Good Reputation: A Study of Product Recalls in the U.S. Automobile Industry
Rhee, M., & Haunschild, P. R. (2006) · Organization Science · doi:10.1287/orsc.1050.0175 · Cited by 743
An inconvenient truth: How organizations translate climate change into business as usual
Wright, C., & Nyberg, D. (2017) · Academy of Management Journal · doi:10.5465/amj.2015.0718 · Cited by 722
How Media Coverage of Corporate Social Irresponsibility Increases Financial Risk
Kölbel, J. F., Busch, T., & Jancso, L. M. (2017) · Strategic Management Journal · doi:10.1002/smj.2647 · Cited by 682
Exceptional boards: Environmental experience and positive deviance from institutional norms
Walls, J. L., & Hoffman, A. J. (2013) · Journal of Organizational Behavior · doi:10.1002/job.1813 · Cited by 221
Self-citationOn the forgetting of corporate irresponsibility
Mena, S., Rintamäki, J., Fleming, P., & Spicer, A. (2016) · Academy of Management Review · doi:10.5465/amr.2014.0208 · Cited by 209
Masters of Disasters? An Empirical Analysis of How Societies Benefit from Corporate Disaster Aid
Ballesteros, L., Useem, M., & Wry, T. (2017) · Academy of Management Journal · doi:10.5465/amj.2015.0765 · Cited by 179
(2011) · Social Problems · doi:10.1525/sp.2011.58.4.491 · Cited by 129
Product Categories as Judgment Devices: The Moral Awakening of the Investment Industry
Arjaliès, D.-L., & Durand, R. (2019) · Organization Science · doi:10.1287/orsc.2018.1267 · Cited by 75
Metadata
- Authors
- Hoffman, A. J., & Ocasio, W.
- Venue
- Organization Science
- Published
- 2001-08
- Volume
- 12
- Issue
- 4
- Pages
- 414-434
- ISSN
- 1047-7039 (ISSN-L)
- 1526-5455
- OpenAlex
- W2114605393
- Cited by
- 683
- References
- 4
- FWCI
- 14.93
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
