Standard setters have increased their commitments to ensuring more standardized and high-quality information as the need to address climate change evolves. In this regard, businesses are crucial, and their contribution to SDGs is highly essential. As such, large corporations are mandated to publish sustainability reports. While some small and medium-scale enterprises (SMEs) engage in sustainability initiatives or environmental, social, and governance (ESG), they do not always disclose them. Consequently, this study addresses this gap by identifying and structuring the barriers to sustainability reporting among Indian SMEs. A systematic literature review identified 14 barriers spanning organisational, regulatory, financial, informational, and stakeholder-related dimensions. These barriers were then structured using Interpretive Structural Modelling (ISM) and MICMAC analysis following the judgements of a panel of nine experts (seven SME managers and two academics). The resulting structure represents the collective judgement of this panel and is not statistically generalisable. The results indicate that lack of regulation, limited awareness, and financial constraints function as high-driving barriers underpinning the reporting hierarchy, while difficulties in materiality assessment and reporting cost are comparatively more dependent outcomes. These findings offer Indian policymakers, SME support agencies, and industry bodies a prioritised, expert-informed basis for designing interventions that can help SMEs move toward sustainability reporting and, in turn, indirectly support the visibility and accountability of SDG-relevant practices.
Despite substantial growth in social media marketing (SMM) research, evidence of whether eco-brand digital visibility translates into financial performance remains absent from the literature. Most existing studies measure consumer attitudes and purchase intentions rather than observed market outcomes, leaving the green gap, the divergence between sustainability intentions and actual behavior, untested at the firm financial level. This study addresses that gap through an exploratory multiple-case analysis of four publicly listed, sustainability-positioned consumer brands (Allbirds, Beyond Meat, Oatly, and The Honest Company) observed monthly from January 2021 to December 2024, combining 48 months of Wikipedia pageview data as a digital public attention proxy with audited annual financial statements. Four analytical layers are applied: non-parametric trend analysis, correlational analysis, fuzzy-set Qualitative Comparative Analysis, and Fuzzy Cognitive Map scenario simulation. Within this four-firm sample, the evidence supports H1, does not support H2, and yields inconclusive or preliminary results for H3 and H4; H5 is illustrated by simulation rather than tested. Aggregate eco-brand digital attention declined by 38.6
Spatial differences can shape both technical efficiency and the implementation of Good Agricultural Practices (GAP) in rice farming. This study compares technical efficiency and GAP implementation across urban, peri-urban, and rural rice farming systems and examines whether the relationship between GAP implementation and benchmark-level technical efficiency differs across these settings. Data from rice farmers in Kebumen and Pekalongan Regencies were analyzed using Stochastic Frontier Analysis (SFA), Kruskal–Wallis and Mann–Whitney tests, and binary logistic regression with spatial interaction terms. Urban farming systems recorded higher technical efficiency than rural systems and marginally higher efficiency than peri-urban systems, providing partial evidence of spatial differences in technical efficiency. GAP implementation also varied significantly across farming systems, with the highest level found in urban areas. Higher GAP implementation was positively associated with the likelihood of achieving benchmark-level technical efficiency, although the strength of this relationship differed across farming systems. Education was positively associated with benchmark-level technical efficiency in urban areas, while participation in agricultural extension and training was positively associated with benchmark-level technical efficiency in the pooled model and in urban farming systems. These findings highlight the importance of considering differences across farming systems when developing strategies to strengthen GAP implementation and improve technical efficiency in rice farming.
This study examines whether improvements in peacefulness generate measurable economic and sustainability dividends and identifies the institutional and fiscal conditions under which those dividends are strengthened or weakened. Using an annual country panel for 2008–2024 with maximum coverage of 163 economies, subject to variable availability, peacefulness is measured as the inverted and standardised Global Peace Index. The empirical model combines two-way fixed effects, instrumental-variable two-stage least squares, dynamic system GMM, panel threshold and smooth-transition regressions, and local projections, thereby addressing unobserved heterogeneity, reverse causality, persistence, nonlinear moderation, and dynamic adjustment within a common framework. A one-standard-deviation improvement in peacefulness is associated with higher FDI inflows, larger tourism receipts, and better SDG and environmental performance; the endogeneity-robust estimates preserve the positive sign while yielding more conservative magnitudes. The dynamic results show that tourism responds relatively quickly and FDI effects persist for several years. Most importantly, the estimated peace dividend weakens sharply when military expenditure exceeds approximately 3.5
Post-harvest rice residue burning in India has important implications for air quality and soil nutrient retention, yet its spatial and temporal dynamics remain difficult to quantify because widely used burned-area products are relatively coarse for fragmented agricultural fields. This study provides a high-resolution, temporally resolved assessment of rice residue burning across India during the 2025 Kharif season. Sentinel-2 imagery was used to delineate rice-growing areas through spectral matching and to map the first detection of burned residue at 10-day intervals using an empirically selected threshold-separability rule. Image-interpreted Sentinel-2 reference points were used to assess spectral separability, while MODIS MCD64A1 was used for an inter-product comparison rather than as independent ground-truth validation. The analysis detected 8.33 million hectares of burned rice residue, with the five highest-burning states accounting for 72.1
