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This study was carried out to reveal the key factors affecting farmers’ green prevention and control technology adoption and to deeply analyse the influence of different generations of farmers’ information capacity on green prevention and control technology adoption. Based on the survey data of 509 farmers in Liaoning Province and the probit model and logit model, this paper conducted an empirical analysis of the farmers’ green prevention and control technology adoption, and analysed the differences in farmers’ adoption of green prevention and control technology from the perspective of intergenerational difference. The research results show as follows: First, information capacity has a significant positive impact on farmers’ green prevention and control technology adoption; Second, the influence of information capacity on the green prevention and control technology adoption of different generations of farmers is different. Information consciousness has more significant influences on farmers in the new and middle-generations; information needs have more significant influences on farmers in the new and old generations; information use only has significant influences on farmers in the middle-generation. Therefore, in order to increase the probability of farmers’ green prevention and control technology adoption, it is necessary to not only pay attention to the influence of farmers’ information capacity, but also fully consider the different stages of the life cycle of different generations of farmers and their own endowment differences.
Czasopismo
Rocznik
Tom
Strony
305--317
Opis fizyczny
Bibliogr. 18 poz., rys., tab.
Twórcy
autor
- College of Humanities and Health Management, Jinzhou Medical University, Liaoning Province, 121000, China
autor
- College of Humanities and Health Management, Jinzhou Medical University, Liaoning Province, 121000, China
autor
- Management College, Bohai University, Liaoning Province, Jinzhou city, 121000, China
autor
- Jinzhou Medical University, Liaoning Province, 121000, China
Bibliografia
- [1] Wu C, Tsai S, Liu W, Shao X, Xia Y, Wacławek M. Green environment and sustainable development: methods and applications. Ecol Chem Eng S. 2021;28(4):467-70. DOI: 10.2478/eces-2021-0030.
- [2] Pan Y, Ren Y, Luning PA. Factors influencing Chinese farmers’ proper pesticide application in agricultural products - A review. Food Control. 2021;122:107788. DOI: 10.1016/j.foodcont.2020.107788.
- [3] Li X, Shang J. Analysis of the main body behaviour of non-point source pollution control based on multimodal game model. Ecol Chem Eng S. 2021;28(4):563-79. DOI: 10.1108/CAER-11-2020-0279.
- [4] Wu Q, Zhou J. Need for cognitive closure, information acquisition and adoption of green prevention and control technology. Ecol Chem Eng S. 2021;28(1):129-43. DOI: 10.2478/eces-2021-0011.
- [5] Timprasert S, Datta A, Ranamukhaarachchi S. Factors determining adoption of integrated pest management by vegetable growers in Nakhon Ratchasima Province, Thailand. Crop Protection. 2014;62:32-9. DOI: 10.1016/j.cropro.2014.04.008.
- [6] Pan D, He M, Kong F. Risk attitude, risk perception, and farmers’ pesticide application behavior in China: A moderation and mediation model. J Cleaner Prod. 2020;276(10):124241. DOI: 10.1016/j.jclepro.2020.124241.
- [7] Song Y, Fan T, Tang Y. Quality information acquisition and ordering decisions with risk aversion. International J Prod. Res. 2020;(6):1-17. DOI: 10.1080/00207543.2020.1828640.
- [8] Tian J, Li L. Factors influencing willingness and ability of farmers to adopt new technologies: A case study of Guanzhong Area. Asian Agricultural Res. 2012;4(07):37-44. DOI: 10.22004/ag.econ.139647.
- [9] Gai H, Yan T, Zhang J. A study on farmers' willingness to adopt environmental-friendly technology from stratification angle: Taking straw returning as an example. J China Agricultural Univ. 2018. DOI: 10.11841/j.issn.1007-4333.2018.04.20.
- [10] Magne MA, Cerf M. How information becomes a resource for action in an uncertain and complex world: Sense-making and contingency in the knowing process. Outlook on Agriculture. 2009;38(2):157-65. DOI: 10.5367/000000009788632331.
- [11] Rong L, Chen J, Wen Z. Dynamic regulation on innovation and adoption of green technology with information asymmetry. Naval Res Logistics. 2021;(4). DOI: 10.1002/nav.21990.
- [12] Tang Y, Yang Y, Ge J, Chen J, Xin X. The impact of weather index insurance on agricultural technology adoption evidence from field economic experiment in China. China Agricultural Economic Rev. 2019;11(4):622-41. DOI: 10.1108/CAER-05-2018-0107.
- [13] Zurkowski PG. Information Literacy Is Dead… Long Live Information Literacy. Springer International Publishing. 2013. DOI: 10.1007/978-3-319-03919-0_1.
- [14] Wilson TD. Models in information behaviour research. J Documentation. 1999;55(3):249-70. DOI: 10.1108/EUM0000000007145.
- [15] Brenda D. Sense-making theory and practice: An overview of user interests in knowledge seeking and use. J Knowledge Manage. 1998;2(2):36-46. DOI: 10.1108/13673279810249369.
- [16] Betty R. Multigeneration employees: strategies for effective management. Health Care Manage. 2000;19(1):65-76. DOI: 10.1097/00126450-200019010-00011.
- [17] Friedman LN, Gold AR, Richard C. Dissecting the generation gap: Intergenerational and intrafamilial similarities and differences. Public Opinion Quarterly. 1972;(3):334-46. DOI: 10.1086/268015.
- [18] Hui CM, Wang XR, Jia SH, Fertility rate, inter-generation wealth transfer and housing price in China: A theoretical and empirical study based on the overlapping generation model. Habitat Int. 2016;53:369-78. DOI: 10.1016/j.habitatint.2015.12.010.
Uwagi
W artykule numery ORCID wymienione przy każdym z auotrów przynależą do jednego autora - Shujie Gao.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-58d41a22-c505-42a8-a67f-ae766d63675d