Exploring the dark side of inter-firm coopetition: The harmful effect on customer satisfaction
Bibliographic record
Abstract
Inter-firm coopetition, the simultaneous presence of competition and cooperation between firms, has gained increasing attention in strategic management research. While scholars have focused on its effect on selected firm outcomes, the impact of coopetition on customer satisfaction remains underexplored. Our study addresses this gap and leverages recent advancements in coopetition research by examining how coopetition, and the intensities of competition and cooperation in alliances, affect customer satisfaction. Analyzing a unique dataset of 1893 alliances across 143 U.S. firms from 1994 to 2021, we uncover three key insights: First, the intensity of competition in alliances is negatively related to customer satisfaction. Second, the occurrence of coopetition is negatively related to customer satisfaction. Third, contrary to our hypothesis, the intensity of cooperation in alliances does not have a positive influence on customer satisfaction. Our findings substantially contribute to coopetition research by shedding light on the rarely studied ‘dark side’ of coopetition and emphasizing the importance of considering customer perspectives in coopetition research. Besides, we provide managerial implications and suggest future research avenues.
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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 | 0.003 | 0.000 |
| 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 | 0.001 | 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".