Partnership or self‐reliance: prescriptions for small and medium‐sized enterprises
Bibliographic record
Abstract
Purpose The past decade has witnessed the growing importance of partnerships by small and medium‐sized enterprises (SMEs). Yet, despite the popularity and presumed strategic importance of partnerships, partnerships by SMEs often fail and many SMEs turn to self‐reliance operation modes. This study explores industry and firm factors which affect SMEs's choices between partnerships and self‐reliance operation modes. Identification of these factors has important managerial implications for SMEs in their fights to overcome resource and competence limitations. Design/methodology/approach The authors collected data from 68 sample firms and ran regression models to test the propositions. Findings SMEs in technology industries should form partnerships. SMEs that are seeking foreign markets should form partnerships to pool their resources and manage diversities, whereas SMEs that focus on their home markets should use self‐reliance operation modes. International expansion requires substantial resources, including country‐specific knowledge. SMEs may not have sufficient resources to overcome market entry barriers and may have to seek resources from external sources. Partnerships are not appropriate for SMEs that focus on market niches. Age places severe constraints on whether an SME should form a partnership or remain self‐reliant. Young SMEs may rely on partnerships to outsource while established SMEs may be uninterested in partnerships. Finally, SMEs that enjoy first mover advantages should not rely too much on partnerships for external resources. In contrast, SMEs that do not enjoy first mover advantages can take partnerships as an important source of external resources. Originality/value The findings of this study make important contributions to the existing strategy literature. The study identifies contextual impacts that affect SMEs' choices between partnerships and self‐reliance modes and thus explain why partnerships work for some SMEs but not others. The findings of the study also provide managers with practical guidance as to how to make strategic decisions on partnerships
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 | 0.012 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.039 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".