Reputation of multinational companies
Bibliographic record
Abstract
Purpose The purpose of this paper is to use stakeholder theory as the theoretical reference framework to study the influence of internationalization (geographic international diversification) and social performance on multinational companies’ (MNCs) reputation. Design/methodology/approach The authors confirm the research hypotheses using a sample of 113 US MNCs in the chemical, energy and industrial machinery sectors during the period 2005-2010. Findings This study contributes to the literature in three ways. First, it incorporates literature on internationalization to study the possible connection between geographic international diversification and social performance in MNCs. Second, it sheds light on the debate between corporate social responsibility (CSR) and the reputation of MNCs in a very diverse transnational context in which MNCs must meet the needs of stakeholders at both local and global levels. Third, it incorporates the mediating role of social performance in the relationship between geographic international diversification and the firm’s reputation. Originality/value Prior studies have hardly analyzed this relationship, which becomes especially relevant for MNCs, since their implementation of advanced CSR practices in the different markets in which they operate will gain them a good reputation, not only in specific local contexts but also globally, benefitting the organization as a whole and enabling it to gain internal consistency (improvement in internal efficiency), transparency and legitimacy.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".