Role of strategic alliance and innovation on organizational sustainability
Bibliographic record
Abstract
Purpose The purpose of this paper is to examine the role of strategic alliance (SA) and innovation on organizational sustainability using data from North American organizations listed in the Dunn-Bradstreet database. While organizational economic sustainability could be achieved in several ways, this research investigates the relationship of engagement in SA, product life cycle (PLC) and innovation with organizational sustainability from the perspective of the strategy-based balanced scorecard (BSC) that incorporates the mix of financial as well as environmental and social concerns in an environment. Design/methodology/approach This paper reports the results of an empirical study investigating the above relationships in Canadian and American organizations listed in the Dunn & Bradstreet database. The authors analyze the responses to the survey consisting of the questions about firm’s internal process, external environment, strategy, BSC perception and corporate performance of the companies who indicated that they use the BSC. Findings Consistent with the authors’ predictions, results show that there are positive and significant relationships between PLC and SA, between innovation and sustainability, and between innovation and SA (though positive but not significant), thus providing support for the hypotheses. Though the methodology the authors applied is acceptable in management accounting research, the authors recognize that there are limitations of this study and further studies are necessary before the results can be generalized. Originality/value This paper contributes to the literature by providing empirical evidence encompassing the areas of SA, innovation and performance leading toward sustainability.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.000 | 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".