Bibliographic record
Abstract
Growth in IS outsourcing spurred research in the area that spans many perspectives but contains contradictory findings. Inconsistent findings raise confusion and doubt, leaving managers uncertain about IS sourcing directions and researchers unclear about theoretical perspectives relevant to IS sourcing.We argue that the concept of equifinality accounts for much of this confusion. Equifinality suggests that, in the struggle to match conflicting functional demands with structural options, many equally viable alternatives may exist. For IS sourcing, this means that different sourcing choices can be leveraged producing similar IS capabilities. Thus, embracing equifinality requires that we understand more fully the complexities in the IS function and in the range of sourcing options available. We argue, as well, that the existence of multiple paths raises the importance of implementation and execution issues.Illustrating the complexities of the IS function, we outline several IS function elements, including IT resources, IS activities and IS strategy. An IS-Business Partnering framework is then presented demonstrating the multiplicity of partnering options, situating sourcing as one aspect. We conclude with several company illustrations showing these multiplicities for successful company outcomes.For IS sourcing researchers, equifinality holds important implications. No longer can we afford to view the IS function as a homogeneous entity nor can we limit our scope to a narrow range of sourcing and partnering options. More than one path exists to achieve a particular outcome. Hence, the pursuit in IS sourcing research can no longer be for one good answer but for a few good answers.
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 | 0.048 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.014 |
| Science and technology studies | 0.011 | 0.030 |
| Scholarly communication | 0.039 | 0.041 |
| Open science | 0.004 | 0.021 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".