• This study examines the impact of carbon emissions (CO₂) and renewable energy consumption (REC) on firms’ financial performance (ROA and ROE) and market value (Tobin’s Q and EPS). • The study analyzes 3,416 firm-year observations from the NSE CNX500 index (India) over 10 years (2011–2020), using data from Eikon Thomson Reuters and the World Bank. • Both CO₂ and REC show a consistent and significant influence on Tobin’s Q across all tests, indicating a strong link between environmental factors and firm valuation. • The study includes robustness checks by firm size and leverage, revealing that CO₂ and REC significantly affect ROE in low-leverage firms, though not in the full sample. • The findings provide critical insights for investors, fund managers, and policymakers aiming to integrate sustainability into financial decision-making. This study examines the impact of carbon emissions (CO₂) and renewable energy consumption (REC) on financial performance (ROA, ROE) and market value (Tobin’s Q, EPS) using 3,416 firm-year observations from NSE CNX500 firms (2011–2020), sourced from Eikon Thomson Reuters and the World Bank. Results show that CO₂ and REC consistently and significantly influence Tobin’s Q across all models, including by firm size and leverage. REC also significantly affects EPS in the full sample. These findings highlight the strong and persistent relevance of environmental factors for market valuation, offering important insights for investors, fund managers, and policymakers.

• Trust is key in coordination of Thai smallholder-based retailer-driven value chains. • Actors invest in trust building and maintenance not assets for business development. • Trust-based ties stabilize trade but reinforce power asymmetries. • The combination of trust and power asymmetry leads to lock-in, limiting upgrading. • Relational governance calls for new strategies in informal agri-food markets. This article builds on perspectives from relational economic geography to delve deeply into the micro-social processes that underpin market coordination. We examine how trust functions as a central coordinating mechanism in smallholder-based agri-food value chains in Thailand. Drawing on qualitative interviews with actors from the different segments of the value chains for onions and Chinese cabbage, two major crops in Thailand, the study explores how interpersonal relations, inherited networks and socio-cultural norms underpin economic transactions. Instead of viewing trust as a relational supplement to governance structures, the article argues that trust constitutes a primary mode of coordination in hybrid and informal market systems. While trust-based relations enable continuity and stability in volatile agricultural markets, they also reinforce dependency and power asymmetries, particularly for upstream actors. Trust can facilitate upgrading by reducing uncertainty and enabling access to resources, yet the results show that reinforced dependencies and power asymmetries inhibit innovation and investment into business development through lock-in effects. This results in limited opportunities for upgrading and economic development, particularly among smallholders and the smaller traders. The findings challenge conventional typologies of global value chains by highlighting the micro-social foundations of coordination and the double-edged nature of trust in shaping upgrading opportunities. We argue that there is a need to understand these micro-social processes of market coordination and value chain governance in order to address uneven patterns of economic development, particularly among smallholders and traders in agri-food value chains.

Geographical indications (GIs) certify the link between coffee origin and quality, enabling premium pricing and protecting producers. However, the high market value of GI coffees increases their vulnerability to fraud, underscoring the need for reliable and practical authentication methods. Portable near-infrared (NIR) spectroscopy represents a rapid and non-destructive alternative, but its capability to discriminate Brazilian GI coffees requires systematic assessment. This study compared NIR transmittance spectra of aqueous coffee extracts with NIR reflectance spectra of the corresponding ground samples for the authentication of four Brazilian GIs from southeastern Brazil: Cerrado Mineiro, Mogiana Paulista, Mantiqueira de Minas, and Matas de Minas. Distinct spectral signatures were observed in the 900-1650 nm range. Data-driven soft independent modeling of class analogy (DD-SIMCA) was employed, resulting in excellent classification performance. Although both acquisition modes showed satisfactory performance during calibration and validation, reflectance consistently outperformed transmittance in the prediction of a test set, achieving accuracies ranging from 97% to 100%. The superior performance of reflectance-based models was attributed to the preservation of chemically informative features in the solid coffee matrix, including lipids and other compounds poorly extracted into water, whereas aqueous extracts were dominated by water absorption and exhibited greater intraclass variability. Portable NIR spectroscopy, particularly in reflectance mode combined with DD-SIMCA, provides a fast, non-destructive, and highly reliable approach for authenticating Brazilian GI coffees. These findings highlight its potential as a practical tool to protect producers and consumers against fraud and to ensure the integrity of products bearing protected geographical indications. © 2026 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Process-based cost assessment of electrochemical metals recovery from municipal solid waste incineration ash.

The circular economy (CE) has moved to the center of sustainability-driven innovation, with agriculture playing a pivotal role due to its large biomass flows and potential for resource optimization. This study investigates how CE practices relate to sustainable innovation, specifically highlighting value creation for “ergo-iconic” agricultural products—goods that uniquely combine ergonomic functionality (usability, durability, and human-centered design) with culturally embedded, sustainability-oriented identity attributes (place-based branding, heritage value, and symbolic meaning). Employing a qualitative exploratory design in Banten, Indonesia, we conducted semi-structured interviews with ten key informants comprising five agro-industry practitioners, three industry analysts, and two NGO representatives. We complemented this primary data with rigorous document analysis to ensure a holistic understanding of the context. Thematic analysis and triangulation were employed to establish the credibility of the findings. The results indicate that circular business models not only reduce waste but also serve as catalysts for broader innovation processes. Three primary drivers consistently emerged: (1) stakeholder engagement, (2) cross-sector collaboration, and (3) the adoption of environmentally friendly technologies. Building on these insights, we propose the CircAgriResilient Nexus (CAR-Nexus)—a comprehensive framework that conceptualizes circularity as a dynamic nexus connecting four pillars: Circularity, Agri-Innovation, Resilience, and Nexus Governance. CAR-Nexus differs from existing sustainable circular bioeconomy models by explicitly positioning resilience as a core system capability and by integrating a provisional Resilience Index Score (RIS)—a conceptual tool that synthesizes resource efficiency, social progress, and economic robustness to guide balanced assessment of circular transitions. This framework clarifies how circular resource flows, eco-innovation, and inclusive governance jointly enhance market, environmental, and social value within the Industry 4.0 era. The study contributes theoretically by articulating an integrative CE-innovation-resilience nexus tailored specifically to agri-food systems, and practically by outlining actionable levers for firms and policymakers to accelerate circular transitions in developing economies.

Purpose This study examines the valuation of European-listed real estate companies by assessing the value relevance of accounting-based performance metrics – earnings per share (EPS), return on equity (ROE) and dividend per share (DPS) – as complementary or alternative indicators to the traditionally dominant net asset value (NAV). Design/methodology/approach Using a panel dataset of 102 firms from 2005 to 2024, the study applies three regression models – share price, price change and share return – alongside a difference-in-differences (DiD) approach to capture structural shifts during the 2008–09 financial crisis and the 2021–23 COVID-19 and interest rate hike period. Findings The findings reveal that EPS and DPS are the most consistent and significant predictors of share prices, with DPS showing the highest explanatory power, particularly during the COVID-19 and interest rate hike period. ROE is the strongest predictor of share returns, especially in times of economic stress. Sectoral effects are generally weak, indicating that firm-level financial performance outweighs industry classification in explaining market valuation. Research limitations/implications The study is subject to potential biases in sample selection such as firm size, geographic and market classification, language. The sample is representative of large, liquid and internationally oriented firms, the findings may not generalize to smaller, less liquid or emerging market companies. Practical implications For analysts, integrating accounting metrics alongside NAV enhances valuation accuracy and comparability. For generalist investors, understanding which factors consistently influence prices can inform long-term valuation models, portfolio construction and risk assessment. For practitioners, it provides a robust, multi-metric valuation framework that enhances decision-making by integrating familiar financial indicators with traditional asset-based measure. Originality/value The DiD framework is employed to capture how investor responds to financial metrics shift across crisis and COVID-19 and interest rate hike periods (2008–2009 and 2021–2023). Use of three regression models – share price, share price change and share return – isolates the explanatory power of each financial metric under varying market conditions. Sector-level analysis offers insights into performance heterogeneity. For academic research, it fills a gap in European real estate literature by empirically testing the relevance of accounting metrics in stock valuation, an area previously dominated by NAV-based approaches.

Abstract The accelerating consumption of electrical and electronic equipment (EEE) has led to rapid growth in waste electrical and electronic equipment (WEEE), which is currently the fastest-growing waste stream worldwide. E-waste contains valuable resources such as gold, copper, and rare earth elements, but also hazardous substances including lead and cadmium, making its sustainable management a critical environmental and economic challenge. This study applies a PRISMA-guided systematic review of 122 peer-reviewed studies (2014–2024) combined with quantitative analysis of e-waste generation, material recovery potential, life-cycle environmental impacts, and techno-economic feasibility for the Indian context. Globally, e-waste generation reached approximately 62 Mt in 2022, yet less than half was formally recycled, leaving an estimated USD 45 billion in recoverable materials unreclaimed annually. In India, approximately 4.14 Mt of e-waste was generated in 2022, yet only about 1.4% entered formal recycling systems. Population-scaled estimates indicate that Uttar Pradesh, Maharashtra, Bihar, West Bengal, and Madhya Pradesh together account for nearly 45% of India’s total e-waste generation. Material composition analysis indicated a potential recovery of approximately 57,000 tonnes of critical and precious metals, with an estimated market value of USD 4.9 billion. Life-Cycle Assessment (LCA) revealed environmental trade-offs between recycling pathways: pyrometallurgical recovery emitted about 25% more greenhouse gases but required 18% less energy than hydrometallurgical processing. Techno-economic evaluation using Net Present Value (NPV) and Benefit–Cost Ratio (BCR) indicators showed stronger financial feasibility for hydrometallurgical recovery, with an estimated national NPV of USD 1.2 billion and a BCR of 1.45 under baseline assumptions. The findings suggest that hydrometallurgical or hybrid recovery strategies, supported by stronger Extended Producer Responsibility (EPR) enforcement, integration of informal recycling actors, and investment in advanced recycling infrastructure, could significantly enhance resource recovery while reducing environmental impacts, thereby supporting the transition toward a circular economy-based e-waste management system in India. The results represent comparative assessments based on published datasets and secondary sources and therefore highlight general trends and policy implications rather than exact national operational estimates. Graphical Abstract

This study investigates the relationship between environmental, social, and governance (ESG) disclosure, corporate governance mechanisms, and firm value in listed companies. As capital markets increasingly integrate non financial information into valuation processes, ESG disclosure and governance quality have become critical signals for investors. Using panel data from publicly listed firms and employing panel regression techniques, this research examines whether ESG disclosure and corporate governance enhance firm value, measured by Tobin’s Q. The findings provide empirical evidence that ESG disclosure has a positive and significant effect on firm value. Furthermore, corporate governance mechanisms not only directly enhance firm value but also strengthen the valuation effect of ESG disclosure. These results support signaling theory and agency theory, suggesting that transparent ESG reporting and effective governance reduce information asymmetry and agency conflicts, thereby increasing market valuation. The study contributes to the corporate finance and sustainability literature by integrating ESG disclosure and governance perspectives in explaining firm value, with important implications for managers, investors, and policymakers.

Abstract Green lentil ( Lens culinaris Medik.) is typically consumed whole; consequently, the color of the seed coat is an important factor in determining its market value. However, green seed coat color is not stable and tends to deteriorate toward dark brown over time. This reduces the desirability of the lentil seed and results in a lower market value. The purpose of this project was to generate information to assist breeders in developing strategies for improving seed coat color stability in green lentil. The population used in this study (LR‐06) consists of 160 recombinant inbred lentil lines and was grown in three replications, in two locations, during the summers of 2019, 2021, and 2022. Approximately 200 individual seeds from each plot were imaged using a high‐throughput imaging device at different time points, post‐harvest. Commission Internationale de l'Eclairage (CIE) L*a*b* scores were extracted from images using BELT's accompanying software, PhenoSEED. Mixed linear models were used to evaluate the predictability of seed coat color quality following aging based on the initial screenings. The results of this study provide evidence that lentil seed coat color quality following aging is predictable based on these initial screenings. Genotyping was performed using a legume single nucleotide polymorphism chip, and the genotypic data, combined with CIE L*a*b* scores, were used to perform quantitative trait locus analysis. The results of this analysis provide evidence that seed coat color quality is genetic and specific regions of the genome can be targeted during selection.

Indonesia's digital economy has shown rapid growth over the past five years. The e-Conomy SEA 2024 report noted that the gross merchandise value (GMV) of the digital economy increased from US$27 billion in 2018 to US$90 billion in 2024, with projections of reaching US$200–360 billion by 2030. The largest contribution comes from the e-commerce sector, which reached US$65 billion in 2024. Meanwhile, the adoption of digital payments and fintech is increasing rapidly; Bank Indonesia reported that electronic money transactions increased from 47.2 trillion rupiah in 2018 to 594.2 trillion rupiah in 2024. This article is designed to map trends, analyze opportunities, and link digital business developments in Indonesia to government policies, technological developments, consumer behavior, and the startup and MSME ecosystems. The research will employ a systematic literature review approach and secondary data analysis from government reports, scientific journals, and industry surveys. In addition to examining e-commerce and fintech, the study will also examine the edtech subsector—which is projected to have a market value of US$3.23 billion in 2024 with a predicted annual growth of 11.79% through and healthtech, with transaction value projected to increase from US$16 billion in 2023 to US$34 billion in 2027. Challenges such as digital infrastructure inequality, talent shortages, data privacy and cybersecurity regulations, and funding gaps will also be part of the analysis. This research is expected to provide a comprehensive mapping and strategic recommendations for the government, business actors, and researchers to strengthen Indonesia's digital business ecosystem.

Brazil, as one of the world’s leading fruit producers, faces increasing challenges arising from climate change, particularly in avocado cultivation, where excessive solar radiation and high temperatures impair plant metabolism, yield, and fruit quality. This study evaluated the use of a calcium and magnesium hydroxide-based sunscreen in mitigating heat stress in eight-year-old ‘Hass’ avocado trees. The experimental design was a randomized complete block design in a 4 × 8 factorial arrangement, with five replicates. Sunscreen applications were performed at full bloom and at the initial fruit development stage (18 mm). Leaf temperature, fruit drop rate, yield-related traits, fruit classification, and the percentage of fruit lesions were evaluated. Applications of the calcium and magnesium hydroxide-based sunscreen at concentrations of 3.0% and 4.5% (w/v) reduced leaf temperature and improved fruit biometric attributes compared to the control, although the maximum fruit diameter was achieved at the 2.6% concentration. The 4.5% sunscreen concentration reduced leaf temperature and fruit drop in ‘Hass’ avocado trees by 1.5 °C and 24.5%, respectively, compared with the control and decreased the percentage of small and damaged fruits. The application of sunscreen improved fruit weight and the percentage of fruits with higher market value, while the fruit diameter presented higher values at intermediate concentrations.

Do investors value firm inventions that recombine distant knowledge across domain boundaries? Analyzing more than 1.5 million firm patents, we find that, despite its strong association with long-term technological impact beyond the local domain, distant recombination of domain knowledge contributes less to a patent’s market valuation when compared to local recombination, thereby inducing a misalignment between valuation and impact. This valuation disadvantage is especially pronounced when distant recombination occurs in a domain primarily built on local knowledge, draws on knowledge from domains with broad applicability, and spans domains with limited connections. Mechanism tests suggest that the inherent evaluation and appropriation challenges for inventions built on distant recombination plausibly account for these findings. We thus establish domain distinctions in knowledge recombination as a key explanation of why innovations’ private returns may diverge from their technological impact despite the commonly assumed alignment between the two. Funding: The authors acknowledge financial support from Cornell University. Supplemental Material: The online appendices are available at https://doi.org/10.1287/orsc.2023.17475 .

This study looks at the impact of financial ratios on Infosys Limited's share price between 2021 and 2025. It seeks to assess the company's financial performance using important criteria including profitability, liquidity, and leverage and investigate how these ratios relate to changes in stock prices. Regression and correlation analysis are two methods used to examine data that is gathered from financial websites and yearly reports. According to the study, Return on Equity (ROE) considerably raises share prices, underscoring its significance in market value. Earnings Per Share (EPS), on the other hand, exhibits a weak link. Additionally, it mentions how outside variables like investor sentiment and the state of the economy affect share prices, giving analysts and investors important information. KEYWORDS - Financial Ratios, Share Price Movement, Return on Equity (ROE), Earnings Per Share (EPS), Profitability Analysis, Liquidity Ratio,Leverage Ratio,Correlation Analysis, Regression Analysis, Stock Market Behaviour, Infosys Limited

This study aims to analyze the dynamic impact of leverage risk and capital structure on the market capitalization of a sample of Iraqi commercial banks listed on the Iraq Stock Exchange over the period 2004–2024, using annual time-series data. The Autoregressive Distributed Lag (ARDL) model was employed after testing the stationarity of the study variables using the Phillips–Perron test. The results of the bounds test indicate the existence of a long-run equilibrium relationship among the study variables. Furthermore, the ARDL model explains approximately 97% of the variations in market capitalization. The findings reveal that some leverage indicators have a statistically significant negative effect on market capitalization, while the impact of capital structure appears weak and varies in terms of statistical significance. Additionally, the regression results suggest that financing variables explain only a limited proportion of fluctuations in market value despite their statistical significance, reflecting the influence of other market and financial factors on stock pricing. This study provides empirical evidence from the Iraqi banking sector on the dynamic relationship between leverage, capital structure, and market capitalization within an emerging financial environment.

ABSTRACT This study examines the nexus between board gender diversity (BGD), corporate social responsibility (CSR) performance, and financial outcomes in the context of an emerging country, Türkiye. The sample consists of Turkish non‐financial firms listed on Borsa Istanbul for the period 2008–2023. The findings indicate that BGD plays a significant positive role in improving CSR performance. Furthermore, BGD does not moderate the CSR‐accounting performance link but positively moderates the relationship between CSR and market‐based performance. This study extends the literature, testing the associations between BGD, CSR, and financial performance in an institutional context characterized by a soft regulatory framework for BGD. The results provide a business case justification for promoting gender‐diverse boards, as greater female representation enhances CSR performance and strengthens the market valuation of CSR initiatives. Accordingly, policymakers are encouraged to implement measures that foster BGD, given its potential to enhance firms' CSR engagement and support national sustainability goals.

ABSTRACT Noni seed oil (NSO) obtained from the seeds of Morinda citrifolia is emerging as a valuable yet underexploited ingredient in the nutraceutical and functional food sectors. Rich in polyunsaturated fatty acids—particularly linoleic acid—along with phytosterols, tocopherols, and diverse phenolic compounds, NSO exhibits notable therapeutic activities. This review outlines the botanical characteristics and nutritional importance of noni seeds and evaluates conventional and green extraction techniques, emphasizing their impact on oil quality and bioactive retention. This review also discusses physicochemical stability concerns, especially oxidative degradation and sensory limitations. Encapsulation technologies are highlighted as effective approaches to enhance NSO stability, shelf life, dispersibility, and bioavailability, enabling its incorporation into functional foods, beverages, dairy products, and cosmetic formulations. Valorization of noni seeds as a by‐product offers economic and environmental benefits by reducing agro‐industrial waste and creating additional market value. However, large‐scale processing challenges, regulatory gaps, consumer acceptance, and limited clinical evidence remain major barriers to widespread application. Overall, NSO demonstrates strong potential as a multifunctional food ingredient, warranting further clinical validation and technological optimization for large‐scale commercialization.

Defect detection in Arabica coffee beans is a critical aspect of quality control, particularly for export-oriented commodities that require consistent visual standards and uniform quality across production batches. Black and partial-black defects are known to significantly affect market value, quality perception, and sensory characteristics. Meanwhile, manual inspection processes remain vulnerable to evaluator subjectivity and inter-operator inconsistency.This study aims to conduct a comparative analysis between a Modified VGG16 architecture and Slim-CNN for detecting these two defect categories using a deep learning-based Convolutional Neural Network (CNN) approach. The dataset consists of 4,080 high-resolution images of Arabica green coffee beans captured using a 24.2 MP macro camera under controlled lighting conditions to minimize shadows and visual distortion. To preserve the natural characteristics of the defects, minimal data augmentation was applied using cropping and 15-degree rotation techniques. The Modified VGG16 architecture was simplified by reducing the complexity of the fully connected layers, integrating batch normalization, and applying dropout to enhance training stability and computational efficiency. Slim-CNN was employed as a lightweight comparative model with fewer parameters and lower memory requirements, making it suitable for resource-constrained deployment scenarios. Four training schemes were evaluated using variations in learning rate and epoch number to assess configuration impacts on performance. Experimental results show that Modified VGG16 achieved the highest test accuracy of 86.7% at a learning rate of 0.001 with 3 epochs, demonstrating a strong balance between training and validation accuracy. Slim-CNN exhibited shorter training time and lower computational complexity, although with slightly lower classification accuracy compared to Modified VGG16. These findings highlight a trade-off between classification performance and computational efficiency in selecting CNN architectures for coffee bean defect detection. Although the results demonstrate potential for industrial automatic classification systems, further validation using larger datasets and more comprehensive evaluation schemes is required to improve model generalization. This study contributes to the development of a more measurable, adaptive, and efficient deep learning-based coffee quality inspection system to support agro-export industry requirements.

ABSTRACT This paper explores the predictability of monthly US stock returns using adaptive LASSO on firm-specific characteristics from June 1990 to December 2022. By efficiently selecting relevant features, such as lagged returns, mean log-volumes, market values, dividend yields, and R&D expenses, the study develops threshold-based portfolios incorporating transaction costs and no-trade zones. Empirical results show that portfolios based on expected Sharpe ratios outperform benchmarks such as the S&P 500, with the adaptive LASSO portfolio achieving a 337.20% cumulative return and a 76.74% annualised Sharpe ratio. Compared with machine learning methods such as random forests and XGBoost, adaptive LASSO offers superior interpretability and robustness, highlighting its effectiveness for dynamic, cost-aware portfolio management while mitigating overfitting.

ABSTRACT This paper examines how firms’ payout and investment policies respond to exogenous cash windfalls from litigation settlements, focusing on the moderating role of corporate governance. We compare the behaviour of windfall firms – those receiving large litigation settlements – to matched control firms, accounting for cross-sectional heterogeneity in board independence, CEO duality, CEO equity ownership, and blockholder ownership. Our findings indicate that windfall firms with strong governance are more likely to increase shareholder distributions and research and development (R&D) investments. In contrast, firms with weaker governance exhibit signs of the free cash flow problem, allocating windfalls to potentially inefficient capital investments. Market valuation analyses reveal that increases in payouts and R&D by windfall firms enhance future shareholder value, while increases in capital expenditures are penalized by the market. This study provides new evidence on the real effects of legal outcomes on corporate policies, highlighting the role of corporate governance in shaping post-litigation corporate behaviour and ensuring that windfalls are used to enhance shareholder value.

The article substantiates that commercialization of university research results should be treated not merely as a supplementary source of revenue but as an integrated financial mechanism for the accumulation and reproduction of intellectual capital. The purpose of the study is to identify the economic logic, channels, instruments and institutional conditions under which licensing, collaborative research contracts, spin-off creation, intellectual property transactions, consortium-based projects and entrepreneurial practices within academia convert research outputs into financial flows, market value and long-term strengthening of the university’s human, structural and relational capital. The paper synthesizes the approaches proposed by the OECD, WIPO, the European Commission and the current Ukrainian legal framework regulating higher education, science and technology transfer. It is argued that commercialization becomes productive only when the university possesses a coherent intellectual property policy, a transparent benefit-sharing model, professional technology transfer support, proof-of-concept funding, patenting assistance, standard contractual solutions and a stable culture of cooperation with business. It is proven that with proper design, this mechanism provides not only income from licenses or contract research. This will contribute to the renewal of the laboratory base, better retention of research teams, increased motivation of scientists, expansion of partnerships, reputational strengthening of the university’s image and growth of its ability to reproduce knowledge. A matrix of commercialization channels is proposed. The impact of the latter on the components of intellectual capital is determined. The main barriers for Ukraine and priority areas of institutional improvement are outlined.