Resource ambidexterity through alliance portfolios and firm performance
Bibliographic record
Abstract
Research summary : Partner resources can be an important alternative to internal firm resources for attaining dual and seemingly incompatible strategic objectives. We extend arguments about managing conflicting objectives typically made at the firm level to the level of a firm's alliance portfolio. Specifically, will a balance between revenue enhancement and cost reduction attained collectively through partner resources accessed via a firm's various alliances be similarly beneficial for firm performance? Additionally, how do strategic attributes of alliance portfolio configuration, specifically alliance portfolio size and partner resource scope, condition the balance‐performance relationship? Based on data from the global airline industry, we find support for the balance‐performance relationship, though such balance is less beneficial for firms in the case of access to a broader resource scope per partner . Managerial summary : Increasing revenue and reducing costs simultaneously can potentially enhance firm competitiveness. We highlight that an alliance strategy can be an important alternative to internal resources for attaining such dual strategic objectives, particularly when partner resources accessed through alliances are treated collectively as portfolios. We examine the importance of balancing product‐market extending and efficiency‐improving partner resources in the global airline industry as well as the impact of two alternate strategies for accessing resources through alliances: fewer partners with more resources per partner or more partners with fewer resources per partner. We find that resource balance at the portfolio level helps airlines improve performance. Our results also suggest that managers should be cautious of accessing too many resources through just a few partners . Copyright © 2015 John Wiley & Sons, Ltd.
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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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".