The dissolution of strategic manufacturer–industrial supplier relationships: are insights from the investment model valid and predictive?
Bibliographic record
Abstract
Purpose The purpose of this study is to assess the validity and predictability of insights from the investment model (IM) in the context of strategic manufacturer–industrial supplier relationships. IM is a theoretical model in social psychology pertaining to interpersonal relationship discontinuity. This formal empirical test of IM in a different context supports vertical theory borrowing and minimizes the risk of committing atomistic fallacy. Design/methodology/approach Data collected from 256 sourcing professionals participating in a scenario-based role-playing experiment were analyzed via structural equation modeling. The authors also performed bootstrapping to assess indirect effects. Findings The IM is generally applicable to the context of interfirm relationship dissolution. Relative to the original context of interpersonal relationship dissolution, three nuances are detected: investment size as an antecedent has lowered prominence in influencing commitment; satisfaction level, quality of alternatives and investment size have non-orthogonal effects on commitment; and satisfaction level influences relationship continuity through and beyond commitment. Research limitations/implications The empirical findings broaden boundary conditions for IM insights. Beyond interpersonal relationship dissolution, the IM appears to also describe, explain and predict interfirm relationship dissolution. Practical implications Keeping the manufacturer satisfied is critical. Moreover, suppliers should be cautious when entering joint product development agreements. Originality/value This study appears to be among the first to formally validate the applicability of IM insights as they pertain to the dissolution of strategic manufacturer–industrial supplier relationships.
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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 | 0.006 | 0.042 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".