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This study aims to understand how climatic drivers of change will affect rural communities living in the hot semiarid region of Bhokardan Taluka of Jalna district in the Indian state of Maharashtra. In the context of the economic and social change they are experiencing, the concern is to evolve ways that enable them to cope with, adapt to and benefit from these challenges.

The focus of most of the climate change studies is on the short- to long-term trends of weather parameters such as rainfall, temperature and extreme weather events. The impact of climate variability and changing patterns on the local communities, the local economy, livelihoods and social life in specific geographies is less explored.

As the impacts of climatic and nonclimatic drivers of change are cross-sectoral, diverse, multidimensional, interlinked and dynamic, this study has adopted a transdisciplinary “research-in-use” approach involving multidisciplinary teams covering the aspects such as changes in land use and land cover, surface and groundwater status, edaphic conditions, crops and livestock, climate analysis including projected changes, socioeconomic analysis, people’s experience of climate variability and their current coping strategies and resilience (vulnerability) analysis of communities and various livelihood groups.

The study was based on the peoples’ perspective and recommendation based on the local communities ability to cope up with climate change. However, a statistical analysis perspective is missing in the present study.

Based on these findings, a set of implementation-focused recommendations are made that are aimed at conserving and enhancing the resilience of the foundations that uphold and sustain the social and economic well-being of the rural communities in Bhokardan taluka, namely, land, water, agriculture, livestock, food and nutrition security, livelihoods, market access and social capital.

Understanding farmer and consumer behavior is essential to the successful implementation of behavior change interventions. The purpose of this study is to summarize existing research, provide a comprehensive overview of nudge interventions, and identify important trends in behavioral agricultural economics. Research on nudge interventions can help policymakers encourage farmers and consumers to change their behavior in desired direction like switching to organic agriculture or eco-labeled products and promote innovation in sustainable agriculture.

The paper contains a bibliometric analysis of nudge research in general and agricultural economics as well as a literature review of the 53 empirical studies on nudge interventions between 2003 and 2023.

The frequency of nudge research in all research fields and in agricultural economics has increased over the years. This study summarizes nudge interventions that can be used by farmers and consumers on a variety of agricultural economic issues. Information, social norms, and social comparison as nudge interventions are most prominent in the publications, while green nudges have not been researched to a greater extent.

This study provides a comprehensive overview of nudge research in agricultural economics with potential for theoretical and policy implications. It highlights potential nudge interventions among farmers and consumers that can be applied in practices.

This study’s purpose is to analyze the effects of trade interventions and non-tariff impediments between the exporters (the United States and Brazil) and China for soybean trade.

A spatial model is developed and solved using an optimized Monte Carlo simulation (OMCS) and is used to minimize the costs of supplying soybeans to China. The costs included the origin basis; transportation to ports, including trucks, railways and barges; demurrage; and ocean freight. The sum of these charges determines the delivered costs to China from each origin. Most variables are random and correlated. Time-series distributions are based on historical data. Production and exports are highly seasonal and important.

Base-case flows are highly seasonal, are risky and reflect actual trade. Sensitivities illustrate the effects of mitigating the quality differentials and interpreting a term of the Phase One agreement that purchases would be made so long as the prices are competitive. The results are also used to illustrate the influence of diversifying from the United States as a supplier. Finally, the policy implications are discussed.

Removing the quality discounts for US soybeans raises the US market share by 9%. These results also illustrate that diversification of supply sources is important for the importing country. Indeed, if China were to pursue less diversification import costs and/or risks would escalate. Hence, these results suggest that diversification is an appealing element of an import strategy. The results suggest a large distribution of prices and costs, particularly in Brazil. On average, the United States is most likely to be competitive for only a few months of the year, and the results are highly seasonal.

Competition in supplying soybean to China is extremely competitive and the underlying factors impacting spatial competition are risk, correlated and spatially dependent. In addition to these, there are quality differences, and there are trade policies and strategies that affect competition. The empirical model and results illustrate the intensity of competition in this market as well the impacts of these non-tariff barriers and trade strategies in this market.

Important policies have been taken and continue to be under review regarding competition and trade among these countries. These results illustrate the impacts of these policies on market shares and competition.

This problem is important to the world soybean trading sector, and the methodology captures important seasonal and random variables that affect trade flows. The OMCS model is appropriate for this problem and has only been used minimally in the recent literature about commodity trade.

Although technologies such as blockchain (BCT) hold great potential to improve global food supply chains (GFSCs), our understanding of BCT use in GFSCs remains limited. The purpose of this study is to broaden BCT discussions by exploring its benefits and challenges across the entire GFSC.

Qualitative interviews with 23 industry experts were used to identify and comprehend the nuanced issues with BCT application in GFSCs.

The study identifies 21 perceived benefits and challenges with BCT use in GFSCs, including the benefit of broader data incentives beyond BCT use and the challenge of reluctance to assume dominant roles among the GFSC actors.

While prior studies mostly focused on BCT use for traceability and food safety in the GFSC midstream, this study extends the scope to include upstream and midstream actors. It highlights socio-economic benefits for traditionally disadvantaged farmers in the upstream and normative challenges to its adoption in the GFSC midstream and downstream. It also identifies three paradoxes emerging with BCT use in the GFSCs including the paradoxes of food technology, transparency and de-centralization.