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More Income, Less Pollution? How Income Expectation Affects Pesticide Application

Author

Listed:
  • Xiaoshan Su

    (School of Management, Zhengzhou University, Zhengzhou 450001, China)

  • Jingyi Shi

    (School of Management, Zhengzhou University, Zhengzhou 450001, China)

  • Tianxi Wang

    (Business School, University of Edinburgh, 29 Buccleuch Place, Edinburgh EH8 9JS, UK)

  • Qinghui Shen

    (School of Management, Zhengzhou University, Zhengzhou 450001, China)

  • Wentao Niu

    (School of Management, Zhengzhou University, Zhengzhou 450001, China)

  • Zhenzhen Xu

    (School of Architecture and Built Environment, Deakin University, Geelong 3219, Australia)

Abstract

Farmers are still the foundation of China’s current “small, scattered, and weak” agricultural production pattern. As such, increasing guidance for reduction response behavior is central to reducing agricultural pesticide use. Following this pesticide reduction logic, four of the most widely promoted pesticide reduction technologies, including light trapping, biopesticide application, healthy crop growth, and insect-proof net technologies, were selected, and a theoretical analysis framework of farmers’ willingness to adopt these technologies was constructed based on the theories of value perception and planned behavior. An ordered logistic regression model is used to explore key factors behind current pesticide reduction technology perceptions, technology response willingness, and behavioral decisions of farmers in China, with survey data from 516 farmers in Henan Province. The results show that among the four pesticide reduction technologies, healthy crop growth technology is the most-appealing one for farmers, followed by insect-proof net technology and biopesticide application technology. The least-appealing one for farmers is the light trapping technology. Farmers’ perceived degree of income improvement from technology adoption is the main determinant of their willingness, which is positively significant at a 1% confidence level in all four models. In addition, farmers’ willingness to respond to technologies is also significantly influenced by farmers’ perception of technical operational ability, perception of risk from adopting technology, government-related subsidies, government technical training guidance, trust in government promotion of technology, and perception of the government’s role in improving the external environment for adopting technology.

Suggested Citation

  • Xiaoshan Su & Jingyi Shi & Tianxi Wang & Qinghui Shen & Wentao Niu & Zhenzhen Xu, 2022. "More Income, Less Pollution? How Income Expectation Affects Pesticide Application," IJERPH, MDPI, vol. 19(9), pages 1-23, April.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:9:p:5136-:d:800438
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    References listed on IDEAS

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    1. Roba Argaw Tessema & Károly Nagy & Balázs Ádám, 2021. "Pesticide Use, Perceived Health Risks and Management in Ethiopia and in Hungary: A Comparative Analysis," IJERPH, MDPI, vol. 18(19), pages 1-14, October.
    2. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    3. Gary C. Moore & Izak Benbasat, 1991. "Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation," Information Systems Research, INFORMS, vol. 2(3), pages 192-222, September.
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    Cited by:

    1. Yi Liu & Hanyue Wang & Chongxu Liu & Mengding Li & Dingde Xu, 2024. "The Impact of Outsourcing Service Adoption on Pesticide Application Reduction from the Perspective of the Principal–Agent Theory: An Empirical Study from Rural China," Land, MDPI, vol. 13(12), pages 1-15, November.
    2. Siyu Gong & Bo Wang & Zhigang Yu, 2022. "Whether the Use of the Internet Can Assist Farmers in Selecting Biopesticides or Not: A Study Based on Evidence from the Largest Rice-Producing Province in China," Sustainability, MDPI, vol. 14(24), pages 1-17, December.
    3. Yayan Xie & Yang Su & Feng Li, 2022. "The Evolutionary Game Analysis of Low Carbon Production Behaviour of Farmers, Government and Consumers in Food Safety Source Governance," IJERPH, MDPI, vol. 19(19), pages 1-16, September.
    4. Xiuling Ding & Apurbo Sarkar & Lipeng Li & Hua Li & Qian Lu, 2022. "Effects of Market Incentives and Livelihood Dependence on Farmers’ Multi-Stage Pesticide Application Behavior—A Case Study of Four Provinces in China," IJERPH, MDPI, vol. 19(15), pages 1-19, August.

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