Transaction costs, technology, and the scope of human resource outsourcing relationships
Bibliographic record
Abstract
This dissertation develops and tests a theoretical framework designed to provide a better understanding of the way that interfirm relationships are managed. To that end, two streams of literature are brought together: transaction cost economics (TCE) and that related to interfirm relationships. TCE has been widely used to explore the make-or-buy decision for individual services, but until now has been confined to the single service context. On the other hand, research in the area of interfirm relationships has tended to focus on the antecedents of relationship formation (and, to some extent, dissolution), while paying much less attention to the ongoing management of there relationships. This study takes an in depth look at the management and performance of multi-service relationships where respondent firms have one or more services outsourced to the same vendor. In particular, the study looks at two key choices in the management of the relationship: level of outsourcing, and scope of the relationship, as well as their performance implications. In addition to the typical use of asset specificity to explain governance choice, the study looks at the influence of the use of information technology in service provision and interorganizational trust on these two choices. A survey of 80 Canadian firms reveals that there is endogeneity of choice in the two governance decisions. As well, it appears that excessive reliance on information technology for service provision can harm both the performance of an individual service, perhaps even harming the relationship as a whole.
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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".