Evidence map›Paper›PMID 42794025›Full record

ArticleFoods (Basel, Switzerland)2026

How Domestic Demand Drives Coffee Export-Basket Upgrading: Pathways to Agri-Food System Transformation.

Ying Hu, Yongle Xie

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Ying HuSchool of Economics, Yunnan University, Kunming 650504, China.ORCID 0009-0002-6877-9359
Yongle XieSchool of Economics, Yunnan University, Kunming 650504, China.

Funding

Major Project of the National Social Science Fund of China 25&ZD190National Natural Science Foundation of China 72563035Yunnan Fundamental Research Projects 202601AS070040
6 · The paper itself

Abstract

The coffee industry in developing countries has long been locked into the lower end of the global value chain, and external governance mechanisms such as fair trade have struggled to fundamentally reverse this situation. This study adopts a mixed-methods research design, using the coffee industry in Yunnan, China, as a case study to reveal the micro-level mechanisms by which domestic demand drives industrial upgrading. Building on these case-derived mechanisms, it then uses panel data from 96 major coffee-producing and coffee-consuming economies from 2012 to 2024 to examine their macro-level implications, including national-level relationships, nonlinear patterns, and cross-country heterogeneity. The study shows that both factors generally drive export upgrading and exhibit a "promotion-inhibition-re-promotion" pattern characterized by a dual-threshold nonlinearity. The case study reveals that the inhibition phase stems from a mismatch between market expansion and demand structure upgrading, where homogeneous capacity growth temporarily offsets the effects of quality upgrading. Heterogeneity manifests in three distinct patterns: producing countries exhibit only a significant domestic market absorption effect; traditional consuming countries are primarily characterized by path dependence; and emerging consuming countries achieve dual-driven growth in both scale and quality. By bridging macroeconomic effects and microeconomic logic, this study clarifies the conditions under which domestic demand drives product-end upgrading along the value chain, providing a reference for different economies to formulate differentiated upgrading strategies.

Indexed as

agri-food systemscoffee export-basket upgradingdemand maturitydomestic market absorptionresource orchestration

Identifiers

PMID42794025
PMCPMC13605605

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.