Sustainable Gastronomy Practices in Evolving Markets: A Circular Economy Framework from Indonesian Culinary Enterprises
Bibliographic record
Abstract
Sustainable gastronomy in hospitality literature is primarily based on studies of large companies in developed economies, but evidence is limited regarding how micro, small, and medium-sized enterprises in evolving markets implement sustainability in the daily operations.Therefore, this study aimed to examine practices, perceptions, barriers, and enabling factors in Indonesian culinary sector and further develop a context-specific framework based on circular economy principles.By using qualitative and exploratory methods, semi-structured interviews were conducted with 24 culinary entrepreneurs across four cities in West Java, as well as with three provincial officials, supplemented by field observations and document reviews from April to August 2025.Data were analyzed thematically through triangulation of interviews, observations, and documents.The results showed that sustainable gastronomy was a multisensory offering combining practical aspects such as local sourcing, waste management, and sustainable packaging with experiential elements including product and recipe innovation, cultural authenticity, and genuine marketing.Six core operational areas evolved, namely local sourcing, waste management, sustainable packaging, product innovation, authentic marketing, and perceived sustainability.Perceived sustainability was a key driver for adopting and implementing sustainability practices.Support systems enhanced activities in this area, while barriers inhibited them.Strengthened practices improved sustainable culinary performance through efficiency gains, reduced waste, and consistent quality, which further increased competitiveness.This study presented a theory-informed and empirically grounded framework for small and medium-sized enterprises in evolving markets, offering practical guidance for policymakers and managers as well as outlining a clear agenda for quantitative validation and longitudinal evaluation in future analysis.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".