1. Jing Hua China Agricultural University Justus Wesseler Wageningen University Yubin Wang China Agricultural University the 20 th ICABR Conference Ravello

2. Potential benefits Potential risks GM technology Perceptions Regulations premise Farmers’ decision-making behaviors Asymmetric Information Uncertainty

3. 1 What’s the farmers’ attitudes towards GM technology? 2 3 Is there any relation among farmers’ perceptions, information and willingness to adopt? Is there spatial dependence of farmers’ willingness to adopt the GM crops? 4 What determines affecting farmers’ willingness to adopt?

4. Spatial Durbin Model Interaction mechanism among perceptions, information and willingness to adopt Farmers’ perceptions and willingness toward GM Crops The different information resources’ influence to the farmers’ willingness to adopt Test the spatial dependence of farmers’ willingness to adopt the GM crops Multiattribute Model Mediation Model Value function

5. is the GM Crops’ sales price is the crops’ yield is the cost function is the GM Crops’ sales price is the crops’ yield is the cost function of adopting GM technology is the potential benefit to the environment since adopting new technology >0 choose traditional technology adopt GM technology

6. Trust of regulatory agencies Awareness of GMOs Information Householder’s characteristics Risk Perceptions ( health, environment,ethics) Benefit Perceptions ( production, nutrition, taste, shelf life, pesticide use) Attitude to GMOs Willingnes s to adopt A B C D Determinants of farmers’ willingness to adopt GMOs. Test of Mediating effect

7. Gansu Wuhan Hebei Beijing The distribution of surveyed samples (east, central, west; 302 random farmers) farmers’ knowledge to biotechnology; farmers’ perceptions towards GM crops; differences in farmers’ willingness to adopt GM crops according to their socio- demographic and household characteristics; farmers’ trust of legislations, government and other propaganda subjects. Main structure of the questionnaire:

8. Variables Proporti on VariablesProportion gendermale67.2% per capita annual household income below ￥ 3000 15.2% female32.8% ￥ 3001- ￥ 5000 17.5% ageaverage47.7 ￥ 5001- ￥ 8000 20.2% acreageaverage6.7 ￥ 8001- ￥ 10000 18.9% family size average4 ￥ 10001- ￥ 15000 14.6% educatio n primary school15.8% Above ￥ 15001 13.6% junior high school 51.7% non-farm income proportion 0-20%20.9% high school27.5%21%-40%11.3% college5.0%41%-60%18.9% 61%-80%19.2% 81%-100%29.7% Table 1 Characteristics of respondents (N=302)

9. the degree of familiarity towards GM crops knowledge; the number of known GM crops, the benefits and potential risks of GM crops the perceptions of biotechnology knowledge Farmers’ perceptions scores towards GM crops Farmers’ willingness to grow towards GM crops Factor analysis The average score was 4.57 the lowest score was 1.04 the highest score was 7.63 Willingness to growNever grow Do not want to growAs the case More willing to grow Greatly willing to try Proportion13.7%23.3%23.0%29.0%11.0%

10. Model 1Model 2Model 3Model 4Model 5Model 6 VariablesAttitude Risk Perceptions Householder’s characteristics age-0.013(***)-0.017(***)-0.0190.0340(***) 0.004 0.0890.011 gender0.0580.090-0.013-0.691(***) 0.0860.0870.0090.225 incomeo0.070(***)0.054(***)0.020-0.263(***) 0.0220.023 0.063 education0.105(***)0.095(***)0.0790.147(*) 0.0460.048 0.109 Risk perceptions-0.129(***)-0.116(***) 0.0130.014 Benefit perceptions0.063(***)0.049(***) 0.0150.016 Trust to regulatory agency0.166(***)0.147(***)0.095(***)-0.261(***) 0.0190.0230.0220.060 Awareness of GMOs0.146(***)0.045(***)0.027(**)0.146(***) 0.1410.016 0.041 Information0.205(***)0.191(***)0.107(***) 0.184 （ ** ） 0.038 0.0340.092 Note:“***” significant at 1% level,“**”significant at 5%, “*”significant at 10%. Determinants of farmers’ attitudes to GM plant age, income and education were mediated by risk perceptions trust of regulatory agencies, awareness of GM products and the information of obtaining GMO indirectly influenced farmers’ attitudes to adopt the new technology, and some direct impact on farmers’ behavior, namely paths A and B occur simultaneously

11. Variables Estimated value Standard value WaldSignificance Willingness to grow (great willing to try as control group) Never grow 1.6401.6101.0370.308 Don’t want to grow now 3.2901.6164.1450.042 It depends 4.5351.6267.7800.005 More willing to grow 6.5691.64715.9140.000 Independent variables Age 0.0090.0110.6390.424 Education -0.1010.0533.5370.060 Non-farm proportion 0.0140.0750.0340.854 Household members 0.1810.0834.8070.028 Farm size 0.0370.0129.1500.002 Benefit expectations 0.6020.17511.8590.001 Environmental attitude 0.3110.1177.1030.008 Attitude to GM crops 0.2600.1085.7740.016 Trust of regulatory agencies 0.6650.15717.9660.000 Awareness of GM crops -0.0130.1090.0140.904 Frequency of getting information from media -0.3420.1793.6480.056 Frequency of discussions with neighbors 0.3140.1197.0090.008 Information obtained from government 0.5910.4082.0970.148 Information obtained from academia 0.4630.6690.4800.489 Information obtained from retailers -0.0710.2530.0790.778 Information obtained from training -0.4120.3691.2450.265 Information obtained from neighborhoods and friends 0.0550.5250.0110.017 Empirical result of farmers’ willingness to adopt GM crops

12. VariablesTotal effectDirect effectIndirect effect Householder characteristics Age0.00590.0071-0.0012 Education0.06280.05040.0124 Non-farm income proportion0.04080.0488-0.0080 Household characteristics Household members 0.10570.08490.0208 Farm size0.01650.0198-0.0033 Risk and preference Benefit expectation0.37070.4438-0.0730 Environmental attitude0.15870.1899-0.0313 Attitude to GM crops0.13440.1608-0.0265 Information characteristics Biotechnology training0.24460.19640.0482 Frequency of obtaining information from media-0.2096-0.25090.0413 Frequency of discussion with neighborhoods0.62380.23580.0388 Other variables Trust of regulatory agencies0.29800.3566-0.0587 Awareness of GM crops0.03610.0432-0.0071 Effect analysis of Spatial Durbin Model the exchange of information between farmers adjacent to each other will affect their willingness to adopt the new technology, confirming the hypothesis of this paper, the neighboring farmer information exchange will be presented spatial dependence, farmers will exhibit similar decision-making behaviors.

13. 1 The farmers’ perceptions increased slightly than 2010; 2 3 The neighborhoods’ information communication had a positive effect on the farmers’ choice behavior while the other information sources such as academia, the government and biotech companies didn’t show significant effects; 4 40% households had a strong willingness to grow while 13.7% chose never to grow and farmers locate in close proximity exhibit similar behaviors. Age, income and education were mediated by risk perceptions trust of regulatory agencies, awareness of GM products and the information of obtaining GMO indirectly influenced farmers’ attitudes to adopt the new technology;

14. Thank you