Risk preferences and the low-carbon agricultural technology adoption:Evidence from rice production in China

Climate change which is mainly caused by carbon emissions is a global problem affecting the economic development and well-being of human society.Low-carbon agriculture is of particular significance in slowing down global warming and reaching the goal of“carbon peak and carbon neutrality”.Therefore,taking straw incorporation as an example,this paper aims to investigate the impact of risk preferences on farmers’low-carbon agricultural technology(LCAT)adoption.Based on a two-phase micro-survey data of 1038 rice farmers in Jiangsu,Jiangxi,and Hunan provinces,this paper uses experimental economics methods to measure farmers’risk aversion and loss aversion to obtain the real risk preferences information of the farmers.We also explore the data to examine the actual LCAT adoption behavior of farmers.The results revealed that both risk aversion and loss aversion significantly inhibit farmers’LCAT adoption:more risk-averse or more loss-averse farmers are less likely to adopt LCAT.It is further found that crop insurance,farm scale and governmental regulations can alleviate the negative impact of risk aversion and loss aversion on farmers’LCAT adoption.Therefore,we propose that local governments need to promote low-carbon agricultural development by propagating the benefits of LCAT,extending crop insurance,promoting appropriate scale operations,and strengthening governmental regulations to promote farmers’LCAT adoption.

Farmers’risk preference and fertilizer use

This study examines the role of farmers’risk attitudes toward fertilizer use in cotton production in China.Contradicting previous studies,this paper theoretically shows that the relationship between farmers’risk aversion and fertilizer use is not always monotonic.Field survey data were collected to test this relationship using the Cobb–Douglas production function.Results suggest that when the elasticity of fertilizer use and the probability of achieving the desired effects from fertilizer use are high,risk-averse farmers apply more fertilizer than risk-taking farmers.Conversely,when the elasticity of fertilizer use and the probability of achieving the desired effects are low,risk-taking farmers apply more fertilizer than risk-neutral or risk-averse farmers.

Econometric Analysis of Risk Preference Patterns among Smallholder Organic Producers in South Africa

The article assesses the determinants of farmers＇ decisions to participate in organic farming, eliciting farmers risk preferences and empirically analysing farmer＇s sources of risk and risk management strategies. The ordered probit results indicate that older farmers, who are less risk averse and reside in the sub-ward Ogagwini, Ezigani and Hwayi were more likely to be certified organic. Similarly, the propensity to adopt organic farming is positively correlated to household size, livestock ownership, asset base and tenure security. At higher pay-offs, farmers were intermediate to moderately risk-averse, with little variation according to personal characteristics. In general, price, production and financial risks were perceived as important sources of risk. Seven principal components, explaining 66.13% of the variation were extracted. Socio-economic factors having a significant effect on the various sources of risk were age, gender, education, location, information access and risk taking ability. The dimensions of risk strategies were named as diversification, precautionary savings and social networks. Results provide practical insights for policy changes relevant in motivating the adoption of organic practices, increasing smallholder farmers＇ capacity to manage risk and driving growth in the organic food market.

Linear-contract Mechanisms Based on the Risk Preference of an Agent in a Supply Chain

With respect to different risk preference of an agent in a supply chain, linear-contract models are designed according to the principal-agent theory. The study shows that the risk preference of an agent directly correlates with the incentive compensation coefficient of principal, order quantity of principal and production capability level of the agent. The principal should offer an appropriate incentive contract according to the risk preference of the agent, or choose an agent holding a different risk preference to establish the supply chain.

Farmers' Risk Preferences and Agricultural Weather Index Insurance Uptake in Rural China

The purpose of this study is to investigate the effect of farmers' risk preferences on their decisions to purchase the agricultural weather index insurance based on the evidence from a household survey and field experiments conducted in Yongqiao District,Suzhou City of Anhui Province in China.Our empirical results show that farmers' risk aversion significantly increases the probability of their decision to buy weather index-based crop insurance.Other factors that significantly influence weather index insurance participation decisions include farmers' subjective beliefs on the probability of crop losses,farming experience,education level,farm size,and their household income.The empirical results of this study can provide helpful insights for policymakers and local insurers to further improve farmers' participation in weather indexbased crop insurance.

Group Decision Making With Consistency of Intuitionistic Fuzzy Preference Relations Under Uncertainty

Intuitionistic fuzzy preference relation(IFPR) is a suitable technique to express fuzzy preference information by decision makers(DMs). This paper aims to provide a group decision making method where DMs use the IFPRs to indicate their preferences with uncertain weights. To begin with, a model to derive weight vectors of alternatives from IFPRs based on multiplicative consistency is presented. Specifically, for any IFPR,by minimizing its absolute deviation from the corresponding consistent IFPR, the weight vectors are generated. Secondly,a method to determine relative weights of DMs depending on preference information is developed. After that we prioritize alternatives based on the obtained weights considering the risk preference of DMs. Finally, this approach is applied to the problem of technical risks assessment of armored equipment to illustrate the applicability and superiority of the proposed method.

Optimizing continuous cover management of boreal forest when timber prices and tree growth are stochastic

Background： Decisions on forest management are made under risk and uncertainty because the stand development cannot be predicted exactly and future timber prices are unknown. Deterministic calculations may lead to biased advice on optimal forest management. The study optimized continuous cover management of boreal forest in a situation where tree growth, regeneration, and timber prices include uncertainty. Methods： Both anticipatory and adaptive optimization approaches were used. The adaptive approach optimized the reservation price function instead of fixed cutting years. The future prices of different timber assortments were described by cross-correlated auto-regressive models. The high variation around ingrowth model was simulated using a model that describes the cross- and autocorrelations of the regeneration results of different species and years. Tree growth was predicted with individual tree models, the predictions of which were adjusted on the basis of a climate-induced growth trend, which was stochastic. Residuals of the deterministic diameter growth model were also simulated. They consisted of random tree factors and cross- and autocorrelated temporal terms. Results： Of the analyzed factors, timber price caused most uncertainty in the calculation of the net present value of a certain management schedule. Ingrowth and climate trend were less significant sources of risk and uncertainty than tree growth. Stochastic anticipatory optimization led to more diverse post-cutting stand structures than obtained in deterministic optimization. Cutting interval was shorter when risk and uncertainty were included in the analyses. Conclusions： Adaptive optimization and management led to 6%-14% higher net present values than obtained in management that was based on anticipatory optimization. Increasing risk aversion of the forest landowner led to earlier cuttings in a mature stand. The effect of risk attitude on optimization results was small.

Diverging effects of subjective prospect values of uncertain time and money

Studies from behavioral economics show that the subjective prospect value of money has diminishing sensitivity to losses/gains,represented by an S-shape,and this has been applied in representing the subjective prospect value of time in many transportation studies such as travel behavior modeling and network equilibrium.In this study,we demonstrate that the prospect value of time has an increasing sensitivity to losses/gains and can be represented by anϨ-shape,which contrasts that of money.We further explain the rationality of this surprising finding based on psychological and behavioral theories and discuss extensive practical implications.The correlations between sensitivities to gains and losses in terms of magnitude are revealed as well to shed light on potential underlying correlated behavioral principles.Substantial loss-aversion features are observed in the empirical analysis,supporting endowment effects.Implications of the findings on decision-making and other areas that utilize time as a key indicator have been discussed.The findings may revolutionize many research areas that utilize time as a key indicator such as transportation engineering.

Decision-making under uncertainty for buildings exposed to environmental hazards

Buildings are exposed to risks from environmental hazards such as earthquakes,windstorms and floods.Sub-stantial uncertainties from various sources are inevitably involved in the risk estimation and decision-making for activities such as design and disaster risk mitigation for buildings.Decision makers seek to achieve economic efficiency while ensure building safety by managing the extreme tail risk that is typically a concern when facing low-probability,high-consequence events.Thus,risk preferences and tolerances play an important role in the decision process,which often vary among different decision makers.The conventionally used minimum expected life-cycle cost criterion(MELC)fails to adequately cope with large uncertainty and risk preferences.To this end,this paper presents the application of a set of decision models beyond the MELC to support decision-making under uncertainty for buildings exposed to environmental hazards.The objective is to provide risk-informed de-cision support for decision-makers with a wide range of risk appetites while taking into account uncertainties involved in the life-cycle cost.The features,strengths and weaknesses of these decision models are discussed from a practical point of view.The application and selection of the decision models are demonstrated by two practical decision problems:(i)seismic design of a high-rise commercial building,and(ii)wind hazard mitigation for a low-rise residential building.These examples illustrate how the decisions for choosing seismic design levels and wind mitigation measures vary when different decision models and model settings are applied.