Effect of strategic purchasing on supplier development and performance: a structural model
Bibliographic record
Abstract
Purpose This purpose of this paper is to introduce strategic purchasing (SP) and supplier development (SD) as constructs that could have the potential to contribute to the success of relationship marketing efforts. Based on the relational view of the firm, the authors propose that SP is an antecedent of SD practices and can create value for the buying firm in terms of better purchasing performance. Design/methodology/approach Hypotheses derived from the key features of SP and SD practices are tested using structural equation modeling through field research on a sample of 306 manufacturing companies in Spain. Findings Findings from this study indicate that there is significant evidence to support the hypothesized model in which SP exerts a direct influence on SD practices and purchasing performance, as well as an indirect impact on purchasing performance mediated through SD. Research limitations/implications Further research is necessary to increase our understanding of a buyer's strategic purchasing and supplier development practices and more specifically how suppliers could develop a supporting environment to facilitate the strategic alignment of these two concepts. The limitations of the survey are also discussed. Practical implications The findings from this study provide supplying firms with an understanding of how buying firms use SD to deploy their SP initiatives in order to achieve improvements in purchasing performance. Originality/value While there is some literature analyzing SP and the implications for buyer‐supplier relationships, the relationship between SP and SD practices and their effect on purchasing performance has not been yet analyzed.
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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".