Boards and social media: the institutionalization of corporate social media policy
Bibliographic record
Abstract
Purpose The authors' work examines whether coercive forces in the general regulatory environment lead to similarity in social media policy across industries and if memetic forces of industry-specific values and norms lead to greater similarity of social media policy within industries. Design/methodology/approach Corporate social media policies were analyzed using a convergent parallel mixed method design to assess and identify themes and similarities. Using an institutional theory lens, this paper examines whether coercive forces in the general regulatory environment lead to similarities in social media policies across industries, and if mimetic forces from industry-specific norms lead to greater similarity of social media policies within industries. Findings suggest that industry-specific, institutional field-level mimetic forces have a greater effect on social media policy isomorphism than environmental-level coercive forces. This study represents the first assessment of corporate social media policies across organizations and industries. Findings Findings suggest that industry-specific, institutional field-level mimetic forces have a greater effect on social media policy isomorphism than environmental-level coercive forces. Research limitations/implications Limitations related to sampling were primarily related to policy collection. To deal with these limitations, the sample was planned to allow for the inclusion of both randomly selected North American companies from the Fortune 500 list and another random selection of 35 companies from within a convenience sample of 100 North American firms who had a publicly available social media policy online. Practical implications The authors' research speaks to management, directors and researchers who work with policy, governance or risk management as the authors demonstrate the effect regulatory and normative institutions have on social media policies: stakeholders within and without given industries are forcing firms to develop legitimacy-providing social media policies by penalizing those that do not. The authors' findings demonstrate that firms respond to the 21st Century potential corporate risk of unsanctioned social media communications by developing corporate social media policies with similar themes. By identifying the themes common in corporate social media policies, the authors have identified best practices constituting a risk mitigation tool for boards. Originality/value The authors' approach is innovative in focus and approach. First, using an institutional theory lens, the authors assess the influence of regulatory and memetic forces on social media policies as a formal structure within an institutional field. Second, the authors' approach includes the first major assessment of North American social media policies across a wide array of organizations and industries, adding to understanding about approaches currently used to manage increased social media use in the workplace.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.014 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.019 |
| Scholarly communication | 0.011 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".