Key problems of interorganizational collaborations: A multi-level and temporal analysis
Bibliographic record
Abstract
Researchers analyze interorganizational problems one at a time, at one level of analysis, and a specific point in time. Yet, interorganizational problems certainly appear in groups of interrelated problems that are nested across multiple levels of analysis and evolve over time. Moreover, analyzing problems independently hinders the ability to assess their relative importance. This study establishes key problems of interorganizational collaboration and highlights their timing. A multiple-case study was realized in the tourism industry. Twenty-eight semi-structured interviews, post-interview surveys, and secondary data allowed us to determine eight key interorganizational problems (interpersonal problems, lack of familiarity, cultural differences, roles and responsibilities problems, toxic work climate, inequity feeling, inappropriate governance, and passivity when problems arise). By using a multi-level and temporal analytical framework, our study contributes to the IOR literature in four ways: confirming problem nesting across levels of analysis, demonstrating greater problem diversity, highlighting relational problem dominance, and demonstrating lifecycle problem evolution.
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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 | 0.019 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.010 | 0.016 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".