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This study aims to examine the effects of climate change and agricultural technologies on crop production in Vietnam for the period 1990–2018.

Several econometric techniques – such as the augmented Dickey–Fuller, Phillips–Perron, the autoregressive distributed lag (ARDL) bounds test, variance decomposition method (VDM) and impulse response function (IRF) are used for the empirical analysis.

The results of the ARDL bounds test confirm the significant dynamic relationship among the variables under consideration, with a significance level of 1%. The primary findings indicate that the average annual temperature exerts a negative influence on crop yield, both in the short term and in the long term. The utilization of fertilizer has been found to augment crop productivity, whereas the application of pesticides has demonstrated the potential to raise crop production in the short term. Moreover, both the expansion of cultivated land and the utilization of energy resources have played significant roles in enhancing agricultural output across both in the short term and in the long term. Furthermore, the robustness outcomes also validate the statistical importance of the factors examined in the context of Vietnam.

This study provides persuasive evidence for policymakers to emphasize advancements in intensive agriculture as a means to mitigate the impacts of climate change. In the research, the authors use average annual temperature as a surrogate measure for climate change, while using fertilizer and pesticide usage as surrogate indicators for agricultural technologies. Future research can concentrate on the impact of ICT, climate change (specifically pertaining to maximum temperature, minimum temperature and precipitation), and agricultural technological improvements that have an impact on cereal production.

To the best of the authors’ knowledge, this study is the first to examine how climate change and technology effect crop output in Vietnam from 1990 to 2018. Various econometrics tools, such as ARDL modeling, VDM and IRF, are used for estimation.

Mental budgeting, as a part of mental accounting theory, is expected to impact a household's budgetary management in terms of expenses. The purpose of this paper is to study whether and how mental budgeting can explain differences in farmers' reactions to different incentives of low-toxicity pesticide use.

Based on data from a survey of 393 vegetable farmers in the Sichuan Province, this analysis, using a Likert Scale approach, first explores whether farmers utilize mental budgeting. Secondly, using a Probit model, this paper analyzes how mental budgeting affects farmers' intentions to switch to low-toxicity pesticide use when faced with different incentives.

The results show that the majority of farmers categorize agricultural inputs into different groups and that 26.46% of the investigated farmers utilize mental budgeting for pest control practices. In addition, farmers who utilizing mental budgeting report a higher willingness to switch to low-toxicity pesticides when they're presented with a specific subsidy. Furthermore, if offered a price premium for quality, the willingness to switch to low-toxicity pesticides for farmers utilizing mentally budget is lower compared to other farmers.

This paper examines the existence of mental budgeting among farmers. It provides a better understanding of how farmers categorize agricultural inputs and their mental mechanisms with respect to agricultural expenses. Finally, this paper is the first to study the effects of mental budgeting on farmers' reactions to different incentives aimed at stimulating the adoption of low-toxicity pesticides.

Based on the survey data of 650 kiwi growers from Shaanxi and Sichuan provinces, this paper used multiple endogenous transformation regression models to explore the effect of the joint adoption of green production technology on farmer’s welfare. The purpose of the study is to analyze the influence of green production technology on the yield, household income and socioeconomic characteristics of Kiwi fruit growers.

In the context of the study, multiple endogenous transformation model (MESR) are adopted, but self-actualization tactics were adopted to deal with the instrumental variables. The empirical data has been collected via a combined hierarchical sampling and random sampling, whereas a well-structured Likert scale questionnaire was adopted as well. The empirical data has been processed with the help of STATA 15.1 version.

The study found a positive impact of adopting green production technology. Moreover, the joint adoption of green production technology by kiwi growers has significantly increased the yield, economic values of Kiwi and household income of kiwi farmers. The households with higher asset value, better land quality, weaker credit constraints, more technical training and stronger government promotion and support from local governments are the most likely to adopt pest control technology and soil management technology jointly.

The prime innovation of the paper is to measure the impact of technology combination adoption on farmer’s welfare is evaluated, rather than the impact of single sub technology on farmer’s’ welfare.

The aim of this paper is to assess whether the current European target to increase the areas under organic farming to 25% by 2030 is attainable and whether the simple increase in areas under organic farming may be sufficient to improve the sustainability of European agriculture.

The analysis has been carried out through a simple data processing related to areas under organic farming, for the period 2012–2020 (Eurostat database), in order to highlight the trends of areas under organic farming and to verify whether the annual average change rates may be compatible with the stated target.

The analysis showed that organic farming has a productive weight not corresponding to the amount on the total of the areas under cultivation and a small impact on the total of food consumption. It is a plausible hypothesis, the one that shows the increase in areas under organic farming will engage forms of agriculture and farms that, already, are more sustainable, so the achievement of 25% target will not particularly impact the European potential productive and the less environmental sustainable forms of agriculture.

This paper contributes to the debate, involving scientific community, policy maker and civil society, about the real contribution of organic farming to sustainability, and it will be developed in future research.

This paper investigates constraints to yield enhancing technology adoptions, highlighting credit using data pooled from the first three waves of the Ethiopian socio-economic surveys.

Direct elicitation methodology is used to identify household's non-price credit rationing status. The panel selection model specified to examine causal effects of credit constraint on adoption variables allows us to tackle self-selection into adoptions and potential endogeneity of credit constraint while controlling for unobserved heterogeneity in both the selection and main equations.

Results show that about 54% of sample households face credit rationing, predominantly demand-side risk rationing. There is a negative association between measures of credit constraint status and adoption variables. The effect is stronger when the demand-side credit rationing is accounted for and when within household variation in credit constraint status overtime is considered as opposed to across constrained and unconstrained households.

Expanding physical access to institutional credit alone may not necessarily spur increased uptake of credit and instant investment by farm households. For a majority of them to take advantage of available credit and improved technology, interventions should also aim at minimizing downside risks.

This paper incorporates the role of downside risk in influencing farmer's decisions to uptake credits and subsequently his/her adoption behaviors. The researcher approached the topic by state-of-the-art method which allows obtaining more reliable results and hence more specific contributions to research and practice.

This study aimed to develop the integration of the multiperiod production-distribution model in a closed-loop supply chain involving carbon emission and traceability. The developed model was for agricultural food (agri-food) products, considering the reverse flow of food waste from the disposal center (composting center) to producers.

The results indicate that integrating the production and distribution model considering food waste recycling provides low carbon emissions in lower total costs. The sensitivity analysis also found that there are trade-offs between production and distribution rate and food waste levels on carbon emission and traceability.

This study focuses on the mathematical modeling of a multiperiod production-distribution formulation for a closed-loop supply chain.

The model of the agri-food closed-loop supply chain in this study that considers food recycling and carbon emissions would help stakeholders involved in the agri-food supply chain to reduce food waste and carbon emissions.

The purpose of this paper is to estimate the impact of credit rationing on the amount of capital allocated to inputs used by rice farmers in the Mekong River Delta (MRD).

Based on the literature review, the authors propose nine hypotheses on the determinants of access of rice farmers to credit and four hypotheses on the impact of credit rationing on the amount of capital allocated to inputs used by rice farmers in the MRD. Data were collected from 1,168 farmer households randomly selected out of 10 provinces (city) in the MRD.

Step 1 of propensity score matching (PSM) with probit regression shows that land value, income, education, gender of household head and geographical distance to the nearest credit institution affect the degree of credit rationing facing rice farmers. Step 2 of PSM estimator identifies that the amount of capital allocated to inputs such as fertilizer and hired labour increases when credit rationing decreases while that allocated to seed and pesticide is not influenced by credit rationing because rice farmers use these inputs adamantly regardless of effectiveness.

This paper sheds light on the impact of credit rationing on the amount of capital allocated to inputs used by rice farmers, which is largely different from the main focus of the extant literature just on the determinants of credit rationing facing farmers in general and rice farmers in particular.

Purpose – This study aims to analyze the contribution of revenue and consumption cost of soybean farmers.

Design/Methodology/Approach – Data analysis was done by quantitative descriptive analysis. Data were obtained in the form of numbers then the results of the obtained data were presented in the form of a systematic description. The sample in this study is the entire population of soybean farmers in Muara Batu, Aceh Utara by using census method as much as 50 farmers.

Findings – The results showed that the contribution of soybean farm revenue amounted to 6.94%, non-soybean farming amounted to 48.12%, and out farm activities amounted to 44.94%. This indicates that soybean farming activities are enough to contribute to increase the family revenue. Meanwhile, the average amount of household cost for food is 16,696,800 IDR/Year and for non-food is 8,397,500 IDR/Year. The analysis shows that although the contribution of soybean farming revenue is the lowest than the other farms’ revenue, it is very helpful to the farmers for fulfilling the needs of family consumption cost every year.

Research Limitations/Implications – The object of this research is to study all the farmers who utilize the land for soybean farming in Muara Batu. The research limitations are income contribution and consumption cost of soybean farmers.

Practical Implications – The amount of soybean production produced by farmers is much lower. However, the farmers can still increase their income if the amount of production can be increased by more intensification of soybean farming as tough as the use of superior varieties of soil processing, organic fertilizer on soil, balanced and integrated pest control, and harvesting and post-harvesting to reduce food loses.

Originality/Value – The farmers earned revenue not only from soybeans, but also from non-soybean farm and out farm. Soybean farming activities aim to increase revenues in order to meet the needs of the family that consist of food and non–food consumptions.

During the planting process, agricultural products produce large amounts of greenhouse gas (GHG) emissions. This has placed tremendous pressure on sustainable global development. Many countries and regions in the world have adopted intensive subsistence cultivation methods when planting maize; however, limited studies exist on these methods. The main purpose of this research is to show the impact of climate change on maize yields and carbon footprint (CF) in South Korea over 10 years, find the proper operating method and promote the advanced combination of inputs for the sustainable development of maize farmers.

This study used survey data from the South Korea Rural Development Administration of 2010, 2014 and 2019 to estimate the CF of maize planting under intensive subsistence cultivation. Life-cycle assessment was used to determine the CF. Farmers were grouped according to significant differences in yield and GHG emissions. Linear regression was used to measure the dependence of the main contributors on the CF production and carbon efficiency.

In South Korean maize planting, N in chemical fertiliser was the most significant contributor to the CF and organic fertiliser was the most significant input. The use of chemical and organic fertilisers significantly affects the production of the CF and carbon efficiency. Households in the high-yield and low-GHG emission groups are more sustainable because they generate the least GHG when producing and earning through maize cultivation. Globally, maize production in South Korea has a relatively low CF and maize production produces fewer GHG.

This study provides information for policymakers to determine key operational options for reducing GHG emissions using intensive subsistence cultivation of maize production in South Korea and other countries.

Productivity and production risks affect the use of agricultural production practices and inputs, particularly in developing countries. This paper aims to investigate the effects of adopting drought-tolerant maize varieties (DTMVs) on farm productivity, yield variance and downside risk exposure of maize growing households of Zambia.

The study uses household survey data collected from 11 maize producing districts of Eastern, Southern and Copperbelt provinces of Zambia using a structured questionnaire. The Antle’s flexible moment-based approach was used in specifying, estimating and testing a stochastic production function. The study further applied an endogenous switching regression model to control for both observable and unobservable sources of bias.

The study revealed that DTMV adoption increases maize yield by 15 per cent and reduces the risk of crop failure: reducing yield variance by 38 per cent and exposure to downside risk by 36 per cent.

This study establishes the benefits of DTMV adoption in Zambia with regards to productivity, yield stability and downside risk in the face of climate change. Results from this study underscore the need for more concerted efforts to scale-out DTMVs for both maize productivity enhancement and for risk mitigation against weather shocks.