Intellectual structure of research in business ethics
Bibliographic record
Abstract
Purpose The study aims to map the intellectual structure of business ethics studies by analyzing 17,246 citations of 225 papers published inBusiness Ethics Quarterly(BEQ) in the year between 2005 and 2014. Specifically, the purpose of the study is to describe the current state ofBEQ, identify the most influential journals and works, identify the key themes of business ethics studies during 2005-2014 and, at the same time, report the changes in themes by making a comparison between two time periods – 2005-2009 and 2010-2014. Design/methodology/approach First, the study presents the information of the authors, institutions and countries that contribute toBEQwith a statistical analysis. Second, the study identifies the most cited journals and works inBEQduring 2005-2014 with a citation analysis. Third, the study identifies the key research themes in business ethics studies with a co-citation analysis. With the help of factor and social network analysis (NA), the study groups the research themes and maps their links. Findings First, the statistical results show that many well-known researchers from famous US institutions publishing inBEQ. Second, the citation analysis results show that quite a few journals become mature gradually in business ethics domain. Besides, most of the influential works are normative and theoretical. Third, the co-citation results indicate that “stakeholder management” and “corporate social responsibility” (CSR) are two main themes in business ethics studies in the past decade. Specifically, “stakeholder management” attracts the most research interests in both two sub-time periods. In addition, compared with the pure studies on CSR during 2005-2009, increasing researchers are keen on the theme of “political CSR under globalization” in the second five years. Meanwhile, other focus like “society, state and business ethics” earns a certain degree of attention in the time window 2005-2009. And “accountability in MNCs” and “political philosophy” are the new concerns in the year between 2010 and 2014. Originality/value The study confirmsBEQ’s leadership role in business ethics domain. And, it further proves that business ethics has evolved as an independent discipline. It also helps the researchers to have a concise knowledge of the main contents and key points of business ethics research. Methodologically, co-citation analysis combined with factor and NA provides clear results and visualized figures which can be understood easily by the researchers and practitioners.
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 | 0.023 | 0.116 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.057 | 0.056 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".