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Revalorization, frugal innovation, and circularity: A qualitative exploration of African used automotive parts business

2025· article· en· W4409211156 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTechnovation · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovation and Socioeconomic Development
Canadian institutionsInnovation Cluster (Canada)
Fundersnot available
KeywordsAutomotive industryBusinessMarketingOperations managementProcess managementIndustrial organizationEconomicsEngineering

Abstract

fetched live from OpenAlex

This paper aims to analyze the nexus of revalorization, frugal innovation, and the circular economy in the under-explored African used automotive parts business context. Based on 30 in-depth interviews with key players including dealers, mechanics, and jobbers, our findings illuminate how these players leverage modern electronic communication, video sharing apps, and barter trade in African used automotive part business. We further found local players employing unique practices to renovate, restructure, alter, restore, reuse, extend, and recycle these used parts, emphasizing maximum value extraction from minimal resources. This paper is one of the first academic works to highlight the criticality of local independent actors (non-dealerships) in the automotive aftermarket sector, especially in non-western contexts. It further showcases these local actors’ contributions to circular economy via revalorization, while at the same time creating social value for the bottom of the pyramid (BoP) consumers. Finally, the paper contributes to several literature streams including circular economy beyond formal systems, scalability of frugal and circular practices, and resource-constrained value creation, among others. • Connects revalorization, frugal innovation, and circular economy concepts. • Local practices to renovate, convert, reuse, extend, and recycle, are critical. • Waste reduction and resource optimization for affordable automotive parts. • Ignorance and legislative voids emerged as major challenges.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.196
Threshold uncertainty score0.606

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.043
GPT teacher head0.294
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it