Purpose: This research was carried out with the objective of identifying the gaps that exist for the development of tourism enterprises in Chachapoyas-Amazonas, Peru. Method: We worked with a quantitative approach and a non-experimental design. The population was integrated by 241 micro and small companies, better known as Mypes. These are characterized by offering services such as accommodation, food, and travel agencies. Results and conclusion: The survey was applied to a sample of 52 Mypes. As a main result, it was found that 44.2% of the internal factors represent a high level of difficulty. As a result, it is concluded that the gaps for these ventures in the province are wide, which prevents their successful development. Research implications: This study revealed that administrative management represents a 40.4% average level of difficulty. This is interpreted as the problem in the organization and acquisition of roles in a company or venture. Originality/value: Latin America also contributes to the Gross Domestic Product with 90% of entrepreneurial activity. Regarding the countries with the highest entrepreneurship record, the United States tops the list of the 10 registered as leaders.

Smallholder coffee producers in the Amazonas Region, Peru, face increasing climate variability, yet evidence on their sensitivity and adaptive capacity remains limited. This study quantifies both dimensions for organised producers (associations and cooperatives) using a large cross-sectional survey (N = 5473). Composite indices were constructed via polychoric principal component analysis (PCA): items were harmonised to a common direction, standardised (z-scores), and rescaled to 0–1. Average Sensitivity and Adaptive Capacity were intermediate (0.49 and 0.47), indicating moderate overall vulnerability. Group comparisons reveal statistically significant heterogeneity across producer characteristics and territories. Cooperative members exhibit higher Adaptive Capacity than association members (0.50 vs. 0.43), consistent with stronger organisational services and networks; differences in Sensitivity are modest and vary across dimensions. Additional variation is observed by gender, farming experience, and province (Bagua, Luya, Rodríguez de Mendoza, Utcubamba). Post hoc tests (Tukey) indicate where pairwise differences concentrate. The findings prioritise organisational strengthening, targeted financial and technical support, and territorially tailored interventions to enhance resilience. These results inform regional adaptation policies and cooperative-strengthening programmes to improve the climate robustness of smallholder coffee systems in the Amazonas region, Peru.

This paper examines the role of agricultural credit in shaping farm performance and technology-related outcomes in Peru, using nationally representative microdata from the Encuesta Nacional Agropecuaria (ENA). In a context characterized by credit rationing and institutional constraints, access to finance may influence agricultural income, productivity, and the adoption of improved practices through multiple direct and indirect channels. To address the non-random allocation of credit, the analysis employs a quasi-experimental framework that combines propensity score trimming, block-based common support restrictions, entropy balancing, and doubly robust treatment-effect estimators (IPWRA and AIPW). Descriptive evidence documents substantial heterogeneity in credit sources, loan uses, and rejection reasons, highlighting structural barriers related to collateral, land tenure, and risk. Regression results on the balanced sample indicate positive and statistically significant associations between credit access and both real agricultural income and land productivity. However, estimated treatment effects are sensitive to the estimation strategy: while IPWRA estimates suggest economically meaningful gains among credit recipients, AIPW estimates are smaller and not always statistically distinguishable from zero. Exploratory results further suggest that credit access is positively associated with technology adoption and managerial capacity, consistent with, but not identifying, a potential association between credit approval and technological practices. Overall, the findings are consistent with a growing body of evidence showing that the impacts of agricultural credit are modest, heterogeneous, and context dependent. From a sustainability perspective, the results underscore the importance of complementary interventions—such as land tenure security, risk management instruments, and tailored financial services—in enhancing the effectiveness of rural credit programs in agricultural systems characterized by imperfect markets and high production risk.

This study aims to provide an empirical, decision-oriented comparison of four widely used sustainability assessment frameworks applied to agri-food systems (LCA, MESMIS, SAFA, and RISE). Using a Scopus-based search (2000–2025), we compiled a purposively balanced corpus of 89 empirical applications and coded each study with a standard rubric spanning normative, systemic, and procedural dimensions. Dimension indices were constructed using polychoric PCA (first component) and rescaled to 0–1, and a global index was computed as the mean of the three dimensions. Within the constructed corpus, MESMIS shows the highest mean global index (0.54), followed by LCA (0.46), SAFA (0.45), and RISE (0.32). LCA leads the normative dimension (0.56), while MESMIS leads the systemic (0.64) and procedural (0.53) dimensions; SAFA presents a balanced profile and explicitly incorporates governance considerations. Findings are interpreted as descriptive patterns within the constructed corpus rather than population-level estimates of inherent method superiority. We conclude that framework choice should be driven by evaluation purpose and information conditions and that hybrid approaches can combine complementary strengths across methods.

National dairy sustainability monitoring requires indicators that are scientifically defensible, policy-relevant, and feasible to construct from recurrent agricultural surveys. The aim of this study was to construct, interpret, and evaluate a national, survey-weighted, frame-aware, MESMIS-informed monitoring profile for Peruvian dairy cattle producers using ENA 2021–2024 microdata. The Peruvian National Agricultural Survey (Encuesta Nacional Agropecuaria, ENA) was explicitly treated as a source of proxy-based sustainability monitoring rather than as a complete farm sustainability assessment. Using survey design variables and harmonized items on livestock, markets, producer capacity, and resource management, the analysis constructed survey-weighted formative profiles for nationally monitored dairy cattle producer units. The analytical sample comprised 42,331 agricultural producer units selected based on complete interview status, reported livestock activity, and harmonized evidence of dairy cattle activity. Because ENA documentation indicates a sampling-frame transition in 2023, the 2021–2022 and 2023–2024 rounds were treated as separate sampling-frame regimes. Indicators were scaled to 0–1 formative profiles, with explicit checks for missingness, indicator availability, exclusion of derivative outputs, exclusion of producer age, minimum-availability thresholds, and sampling-regime-specific scaling. The median indicator availability was 12 of 14 economic and productive indicators, five of five social access and capacity indicators, and eight of eight environmental and resource-management indicators. Survey-weighted descriptive estimates and adjusted within-regime contrasts showed that the strongest signal was a lower social access and capacity profile in 2022 than in 2021, mainly associated with lower agricultural information use, livestock training, and technical assistance. Within the 2023–2024 sampling-frame regime, the main adjusted profiles were statistically stable. The results show that ENA can support a reproducible national monitoring baseline, provided that the resulting profiles are interpreted as proxy-based formative summaries constrained by survey coverage rather than as direct environmental performance scores, causal trends, or complete sustainability measures.