The Value of Long-term Relationships when Selling to Informal Retailers - Evidence from India
Bibliographic record
Abstract
Attempts to distribute durable, life-improving goods to customers at the Base of the Pyramid (BoP) – the more than three billion customers who live on less than US$2.50/day – through traditional supply chains or e-commerce have struggled to succeed at scale. One hypothesis for why distributors struggle to scale last-mile distribution is poor relationship management with small informal retailers, who are the primary source of retail purchases for BoP customers. These retailers are often embedded within communities, where local and long-term relationships are particularly important to business transactions. We provide empirical evidence for this hypothesis through an analysis of panel data from a distributor selling to 331 formal retailers and 493 informal retailers in India from April 2016-December 2019. Specifically, we study the role of long-term relationships in selling durable goods to informal retailers, by leveraging a staged natural experiment that allows us to examine the effect of a sales agent reallocation on subsequent orders placed by informal and formal retailers. Using two different quasi-experimental methods, we find that formal retailers experience an average performance decrease of at least 35.7% relative to predicted order value and then recover within three sales cycles of a sales agent reallocation; in contrast, informal retailers experience an average performance decrease of at least 70.4% relative to predicted order value, and do not experience sustained recovery within five sales cycles of a sales agent reallocation. This indicates that business relationships, and disruptions to these relationships, are particularly important when selling to retailers in informal markets.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".