Bibliographic record
Abstract
Purpose The purpose of this study is to develop a conceptual framework for defensive strategy by integrating market entry modes and the typology of firms suggested by Day and Nedungandi, and to attempt to propose how local incumbent firms utilize their mental models in order to react against market entry of new competition in global markets. Design/methodology/approach The theoretical perspective adopted in the study is how mental models used by incumbent firms influence their reaction to market entry of new competition in developing defensive strategies to defend their markets. Findings Mental models of incumbent firms, categorized as self‐centered, competitor‐centered, customer‐oriented, and market‐driven firms, impact their reaction and the development of defensive marketing strategies against market entrants using a variety of market entry modes in global markets. Originality/value The paper presents an extensive review of the defensive marketing and mental models literature and shows how the way in which incumbent firms react to market entry of new competition contributes to understanding of incumbent reaction to market entry of new competition in global markets. Research directions for future research and managerial implications are also provided.
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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 | 0.009 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".