Organizing New Product Development Projects in Strategic Alliances
Bibliographic record
Abstract
We utilize research on alliance governance structures and on new product development to study how partners working under an existing alliance governance structure will organize a new product development project. Initially, we consider a contractual alliance doing multiple projects and argue that the critical organization decisions for any project are whether one or both partners should be involved, whether the partners should work with little or considerable interaction, and whether decision-making authority should reside in a project manager or be consensual. Based on the answers to these questions, we identify at least four viable project organization options. We next examine the option that would be selected under conditions involving the alliance's newness, whether a cooperative history exists, and the distribution of skills for the project. Under each condition, we compare the costs and benefits of the options with respect to the underlying transaction costs, potential for learning, and the ability to contribute to developing a social relations network. By allowing variations in time-to-market pressures, the tacit knowledge that a partner can obtain from the project, and the partners' need to work closely together on future projects, we can determine the points at which costs and benefits indicate a switch from one organization option to another. Finally, we indicate how to adjust the theory for it to apply to a contractual alliance doing only one project and to an institutional alliance such as a joint venture.
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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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".