Microlevel Analysis of Institutional Intermediation in a Rudimentary Market-Based Economy: Entrepreneurship in Kathmandu’s Indrachok Market
Bibliographic record
Abstract
Institutional theory research on institutional intermediation typically focuses on how institutional intermediaries address voids in market-based institutions that inhibit entrepreneurship. In doing so, the research rarely studies what types of institutional intermediaries entrepreneurs prefer to use. We address this gap with a microinstitutional inquiry of how entrepreneurs in a rudimentary market-based economy differ in the relevance they place on different types of institutional intermediaries. Using a sample from the Indrachok market in Kathmandu, Nepal, and using a three-stage qualitative and quantitative abductive investigation of a cascading set of increasingly refined research questions, we identify two key preferences for institutional intermediaries. First, we find a key institutional intermediation tripod consisting of three locally focused institutional intermediaries: family, suppliers, and peer entrepreneurs. The tripod is supplemented by institutional intermediaries with more moderate preference in this context: four other locally focused institutional intermediaries (local politicians, police, religious figures, and political gangs) and three broad-based institutional intermediaries (government, microlenders, and nongovernmental organizations). Second, the importance of suppliers and peers as institutional intermediaries reflects entrepreneurs’ registration status (registered versus unregistered) and microgeographic location (dispersed versus clustered businesses). The research reconceptualizes institutional intermediation in rudimentary market-based economies from the entrepreneurs’ perspective, identifying mechanisms that shape entrepreneurs’ preferences and providing proposition for future testing. Funding: This research was partially supported by the National Natural Science Foundation of China [Grant 71620107001]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/orsc.2021.1531 .
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".