Understanding household vehicle ownership dynamics in the post-COVID-19 era is critical for designing equitable, resilient, and sustainable transportation policies. This study employs an interpretable machine learning framework to model household vehicle ownership using data from the 2022 National Household Travel Survey (NHTS)—the first nationally representative U.S. dataset collected after the onset of the pandemic. A binary classification task distinguishes between single- and multi-vehicle households, applying an ensemble of algorithms, including Random Forest, XGBoost, Support Vector Machines (SVM), and Naïve Bayes. The Random Forest model achieved the highest predictive accuracy (86.9%). To address the interpretability limitations of conventional machine learning approaches, SHapley Additive exPlanations (SHAP) were applied to extract global feature importance and directionality. Results indicate that the number of drivers, household income, and vehicle age are the most influential predictors of multi-vehicle ownership, while contextual factors such as housing tenure, urbanicity, and household lifecycle stage also exert substantial influence highlighting the spatial and demographic heterogeneity in ownership behavior. Policy implications include the design of equity-sensitive strategies such as targeted mobility subsidies, vehicle scrappage incentives, and rural transit innovations. By integrating explainable artificial intelligence into national-scale transportation modeling, this research bridges the gap between predictive accuracy and interpretability, contributing to adaptive mobility strategies aligned with the United Nations Sustainable Development Goals (SDGs), particularly SDG 11 (Sustainable Cities), SDG 10 (Reduced Inequalities), and SDG 13 (Climate Action).

This study aims to identify and analyze the farm risk management strategies of rubber farmers in Southern Thailand. The study also provides efforts to examine the factors influencing risk management strategies in rubber farming in Thailand. The data were collected from a cross-sectional household survey conducted in Songkhla and Phatthalung Provinces of Thailand. A standardized and structured questionnaire was used to gather data from a total of 400 respondents. A number of statistcal tools such as descriptive statistics and multiple regression model were employed to analyze the data. The findings revealed that the rubber farmers adopted 8 (eight) main strategies to manage the risks in rubber farming, namely i) diversification in production, ii) market management, iii) labor and contract management, iv) decreasing production costs, v) production planning, vi) increasing non-farm employment, vii) debt management and viii) using high frequency tapping systems. The study also identified a number of factors including age, gender, level of education and farming experience of the farmers, number of household members, non-farm labor, off-farm labor, hired-labor, household income, debt, landholding size, participation in replanting scheme with RAOT, and membership in farmer institution that affect significantly (with the confidence level > 90%) the risk management strategies of the rubber farmers. Finally, the study recommends that the government should support and promote the research and development on risk management strategies in agriculture sector so that the farmers and farmer institutions can achieve more knowledge and efficiency to cope up successfully various risks in rubber farming in Thailand.

Agroforestry and sustainable farming have been predominant and widespread practices among smallholder farmers in Thailand. The research was conducted in three distinct regions of Thailand, such as the Northeast, East, and South regions. These regions featured diverse agricultural practices, encompassing integrated rubber-based farming, agroforestry plantations, and monoculture. The research aims to bridge the empirical evidence gap by comparing the benefits of agroforestry against monoculture farming, employing a thorough methodology that integrates purposive sampling, structured interviews, and both qualitative and quantitative analyses, revealing substantial disparities in social health averages. Findings showed that monoculture farms scored 4.02, while integrated rubber and agroforestry farms achieved 4.48, highlighting enhanced well-being. Examining various health dimensions, the findings advocate for a paradigm shift towards sustainable farming, emphasizing the holistic well-being of farmers. Results revealed the average opinion on well-being happiness for integrated rubber farms and rubber agroforestry farms emerged prominently higher at 4.43, signifying a categorization of "Very much well-being happiness." In contrast, the average opinion for rubber monocultured farms was 3.22, indicating a classification of "Moderate well-being happiness." The study serves as a crucial and key contribution, guiding informed decision-making for policymakers, researchers, and practitioners, steering agriculture towards an equitable and environmentally conscious future.

The Thailand Research Fund (TRF) paid for a total of 12 research projects on Thai fruits and fruit products. The studies looked at and measured the social return on investment (SROI). The fruits studied included functional fruits like mango, pomelo, papaya, and banana. We collected the data through structured questionnaires and in-depth interviews with the key informants of the 12 research projects. We employed the SROI analysis tool to analyze the data. The value of the net benefit of the research projects in terms of output and outcome was estimated to be 125,389,794 THB (Thai Baht), while the Thailand Research Fund (TRF)’s research funding for these projects amounted to 11,883,370 THB. Therefore, the SROI of the projects is estimated to be 10.55. This value implies that the TRF was able to achieve an SROI of 10.55 THB for each 1.0 THB investment in the research projects. The findings suggest that TRF’s investment in the research projects on Thai functional fruits and fruit products was successful and effective as well as worth value. The study findings might be beneficial for TRF, research grant associations, and educational institutions to formulate appropriate policies for further research support.

This study investigates various environmental aspects of different rubber farming systems (i.e. conventional monoculture, integrated rubber-based farming, and agroforestry plantations) across three regions, namely Northeast, East and South in Thailand. These regions are enriched with diverse soil types, weather conditions and a diverse spectrum of agricultural practices. The study conducted a cross-sectional survey in the above-mentioned regions to collect primary data from the selected respondents. A purposive sampling technique was employed to select the samples. A total of 30 representative rubber farmers were interviewed using a structured and standardized questionnaire. In addition, the study employed qualitative methods to assess the environmental aspects of different rubber farming systems. Based on socio-economic and production criteria, the study identified five types of rubber farms, ranging from single-crop para-rubber to highly diversified operations. The analyses revealed that integrated rubber farms and rubber agroforestry farms demonstrated overall better performance compared to rubber monoculture farms, particularly in areas having higher organic matter content, DRC of rubber fresh latex, water holding capacity (WHC), and soil moisture. The study also found that ecosystem service ratings varied widely, with monoculture farms scoring low (1.98) and integrated systems scoring high (4.60). In addition, the study assessed the farmers’ desire/concern toward biodiversity of different rubber farming systems. The farmers expressed significant concern for biodiversity (average score is 4.23 indicating a consensus at the "very much" level). These findings highlight the environmental advantages of integrated rubber farming and agroforestry, emphasizing the need for sustainable, diverse approaches to rubber production in Thailand.

1. The global expansion of the internet has significantly transformed communication, economic structures, as well as trade over the last two decades (Li & Liu, 2021; Mukhopadhyay et al., 2023). E-c...