IDEAS home Printed from https://ideas.repec.org/a/eee/agiwat/v306y2024ics0378377424004980.html
   My bibliography  Save this article

Social network shapes farmers’ non-point source pollution governance behavior – A case study in the Lijiang River Basin, China

Author

Listed:
  • Qin, Zhanbo
  • Xu, Qinxue
  • Zhang, Changping
  • Zuo, Lanlan
  • Chen, Lingling
  • Fang, Rongjie

Abstract

Agricultural non-point source (ANPS) pollution increasingly threatens China’s aquatic ecosystems. Intercropping grain crops (GC) and cash crops (CC) increases landscape fragmentation, making pollution control harder. As producers of ANPS pollution and beneficiaries of its governance, farmers’ participation is crucial for improving water environments. However, the impact of social networks, closely related to farmers’ economic behavior in rural China, on different cropping types of farmers’ ANPS pollution governance behavior remains unclear. Based on survey data from 305 farmers in a typical village in the Lijiang River Basin, social networks of GC and CC farmers were constructed. By introducing network embedding theory, we examined how social networks influence governance resource allocation and collective action among farmers. Combining social network theory with technology acceptance model (TAM), an extended TAM was proposed to discuss the influence of farmers’ social network structural position (SNSP) on their willingness to participate in governance (WP), considering the role of cognition. Results showed that GC farmers’ social network have small-world characteristics (Small-world quotient=2.153) with a network density of only 0.016, lacking bridging ties and showing low trust among actors. CC farmers’ network had a density of 0.029, a clearer core-periphery structure (Core-periphery index=0.267), key farmers showed stronger bridging capabilities with average betweenness centrality of 4.234 %. CC farmers’ networks had diverse ties and higher trust among actors. CC farmers’ network structure improved information diffusion and is more effective in acquiring resources and collaborative governance. Structural equation modeling showed that SNSP positively affect WP for GC and CC farmers, with path coefficients of 0.245 and 0.294. Mediating analysis showed that GC farmers’ perceived usefulness and CC farmers’ perceived ease of use had the largest mediating effects between SNSP and WP, at 20.9 % and 26.8 %, highlighting cognition’s different roles. Social networks variably impact governance behavior among different farmers, and strategies considering these differences can enhance governance efficiency.

Suggested Citation

  • Qin, Zhanbo & Xu, Qinxue & Zhang, Changping & Zuo, Lanlan & Chen, Lingling & Fang, Rongjie, 2024. "Social network shapes farmers’ non-point source pollution governance behavior – A case study in the Lijiang River Basin, China," Agricultural Water Management, Elsevier, vol. 306(C).
    • Handle: RePEc:eee:agiwat:v:306:y:2024:i:c:s0378377424004980
    DOI: 10.1016/j.agwat.2024.109162
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378377424004980
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.agwat.2024.109162?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Kristen Nelson & Rachel Brummel & Nicholas Jordan & Steven Manson, 2014. "Social networks in complex human and natural systems: the case of rotational grazing, weak ties, and eastern US dairy landscapes," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 31(2), pages 245-259, June.
    2. Ma, Jun & Gao, Huixian & Cheng, Changgao & Fang, Zhou & Zhou, Qin & Zhou, Haiwei, 2023. "What influences the behavior of farmers' participation in agricultural nonpoint source pollution control?—Evidence from a farmer survey in Huai'an, China," Agricultural Water Management, Elsevier, vol. 281(C).
    3. Flett, Ross & Alpass, Fiona & Humphries, Steve & Massey, Claire & Morriss, Stuart & Long, Nigel, 2004. "The technology acceptance model and use of technology in New Zealand dairy farming," Agricultural Systems, Elsevier, vol. 80(2), pages 199-211, May.
    4. Skaalsveen, Kamilla & Ingram, Julie & Urquhart, Julie, 2020. "The role of farmers' social networks in the implementation of no-till farming practices," Agricultural Systems, Elsevier, vol. 181(C).
    5. Peter Moran, 2005. "Structural vs. relational embeddedness: social capital and managerial performance," Strategic Management Journal, Wiley Blackwell, vol. 26(12), pages 1129-1151, December.
    6. Shiyao Zhou & Chen Qing & Shili Guo & Xin Deng & Jiahao Song & Dingde Xu, 2022. "Why “Say One Thing and Do Another” a Study on the Contradiction between Farmers’ Intention and Behavior of Garbage Classification," Agriculture, MDPI, vol. 12(8), pages 1-15, August.
    7. Li, Qinghai & Yu, Yangcheng & Li, Yanru & Sun, Guanglin, 2023. "Heterogeneous Social network shape ability and willingness of rural residents to repay loans in China," Research in International Business and Finance, Elsevier, vol. 65(C).
    8. Fred D. Davis & Richard P. Bagozzi & Paul R. Warshaw, 1989. "User Acceptance of Computer Technology: A Comparison of Two Theoretical Models," Management Science, INFORMS, vol. 35(8), pages 982-1003, August.
    9. Camacho-Villa, Tania Carolina & Zepeda-Villarreal, Ernesto Adair & Díaz-José, Julio & Rendon-Medel, Roberto & Govaerts, Bram, 2023. "The contribution of strong and weak ties to resilience: The case of small-scale maize farming systems in Mexico," Agricultural Systems, Elsevier, vol. 210(C).
    10. Kabbiri, Ronald & Dora, Manoj & Kumar, Vikas & Elepu, Gabriel & Gellynck, Xavier, 2018. "Mobile phone adoption in agri-food sector: Are farmers in Sub-Saharan Africa connected?," Technological Forecasting and Social Change, Elsevier, vol. 131(C), pages 253-261.
    11. Lenore Newman & Ann Dale, 2007. "Homophily and Agency: Creating Effective Sustainable Development Networks," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 9(1), pages 79-90, February.
    12. Xu Wang & Xiaoming Wang & Jingxia Wu & Guochao Zhao, 2017. "Social Network Analysis of Actors in Rural Development: A Case Study of Yanhe Village, Hubei Province, China," Growth and Change, Wiley Blackwell, vol. 48(4), pages 869-882, December.
    13. Schaak, Henning & Mußhoff, Oliver, 2018. "Understanding the adoption of grazing practices in German dairy farming," Agricultural Systems, Elsevier, vol. 165(C), pages 230-239.
    14. Hotte, Ngaio & Kozak, Robert & Wyatt, Stephen, 2019. "How institutions shape trust during collective action: A case study of forest governance on Haida Gwaii," Forest Policy and Economics, Elsevier, vol. 107(C), pages 1-1.
    15. Sarstedt, Marko & Ringle, Christian M. & Smith, Donna & Reams, Russell & Hair, Joseph F., 2014. "Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers," Journal of Family Business Strategy, Elsevier, vol. 5(1), pages 105-115.
    16. Ke He & Junbiao Zhang & Junhui Feng & Ting Hu & Lu Zhang, 2016. "The Impact of Social Capital on farmers' Willingness to Reuse Agricultural Waste for Sustainable Development," Sustainable Development, John Wiley & Sons, Ltd., vol. 24(2), pages 101-108, March.
    17. Shoumin Yue & Ying Xue & Jie Lyu & Kangkang Wang, 2023. "The Effect of Information Acquisition Ability on Farmers’ Agricultural Productive Service Behavior: An Empirical Analysis of Corn Farmers in Northeast China," Agriculture, MDPI, vol. 13(3), pages 1-26, February.
    18. Li, Jing & Zhang, Zelie & Jin, Xianfeng & Chen, Jiaquan & Zhang, Shaojia & He, Zong & Li, Sheng & He, Zhiming & Zhang, Haipeng & Xiao, He, 2018. "Exploring the socioeconomic and ecological consequences of cash crop cultivation for policy implications," Land Use Policy, Elsevier, vol. 76(C), pages 46-57.
    19. Mao, Guoyong & Zhang, Ning, 2017. "Fast approximation of average shortest path length of directed BA networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 243-248.
    20. Komarek, Adam M. & McDonald, Cam K. & Bell, Lindsay W. & Whish, Jeremy P.M. & Robertson, Michael J. & MacLeod, Neil D. & Bellotti, William D., 2012. "Whole-farm effects of livestock intensification in smallholder systems in Gansu, China," Agricultural Systems, Elsevier, vol. 109(C), pages 16-24.
    21. Chung-Hung Tsai, 2014. "Integrating Social Capital Theory, Social Cognitive Theory, and the Technology Acceptance Model to Explore a Behavioral Model of Telehealth Systems," IJERPH, MDPI, vol. 11(5), pages 1-21, May.
    22. repec:plo:pone00:0099502 is not listed on IDEAS
    23. Stephen P. Borgatti, 2006. "Identifying sets of key players in a social network," Computational and Mathematical Organization Theory, Springer, vol. 12(1), pages 21-34, April.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cliff R. Kikawa & Charity Kiconco & Moses Agaba & Dimas Ntirampeba & Amos Ssematimba & Billy M. Kalema, 2022. "Social Media Marketing for Small and Medium Enterprise Performance in Uganda: A Structural Equation Model," Sustainability, MDPI, vol. 14(21), pages 1-20, November.
    2. Jung-Yu Lai & Juite Wang, 2018. "Exploring the impacts of perceived e-collaboration service convenience on new product development in Taiwanese IC design companies," Information Technology and Management, Springer, vol. 19(2), pages 107-120, June.
    3. Faqih, Khaled M.S., 2016. "An empirical analysis of factors predicting the behavioral intention to adopt Internet shopping technology among non-shoppers in a developing country context: Does gender matter?," Journal of Retailing and Consumer Services, Elsevier, vol. 30(C), pages 140-164.
    4. Ruifeng Liu & Jian Wang & Mengling Tian & Yefan Nian & Wei Ren & Hengyun Ma & Fei Liang, 2025. "Farmers’ adoption of green prevention and control technology in China: does information awareness matter?," Palgrave Communications, Palgrave Macmillan, vol. 12(1), pages 1-16, December.
    5. Chidera C. Ugwuanyi & Chukwunonso Oraedu & Chuka U. Ifediora & Ernest E. Izogo & Simplice A. Asongu & Ikechukwu J. Attamah, 2022. "Understanding drivers of self-service technologies (SSTs) satisfaction and marketing bottom lines: Evidence from Nigeria," Working Papers of the African Governance and Development Institute. 22/025, African Governance and Development Institute..
    6. Simarpreet Kaur & Sangeeta Arora, 2023. "Understanding customers’ usage behavior towards online banking services: an integrated risk–benefit framework," Journal of Financial Services Marketing, Palgrave Macmillan, vol. 28(1), pages 74-98, March.
    7. Michels, Marius & Bonke, Vanessa & Wever, Hendrik & Musshoff, Oliver, 2024. "Understanding farmers' intention to buy alternative fuel tractors in German agriculture applying the Unified Theory of Acceptance and Use of Technology," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    8. Kamrath, Carolin & Rajendran, Srinivasulu & Nenguwo, Ngoni & Afari-Sefa, Victor & Broring, Stefanie, 2018. "Adoption behavior of market traders: an analysis based on Technology Acceptance Model and Theory of Planned Behavior," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 21(6), July.
    9. Veronika Hannus & Johannes Sauer, 2021. "Understanding Farmers’ Intention to Use a Sustainability Standard: The Role of Economic Rewards, Knowledge, and Ease of Use," Sustainability, MDPI, vol. 13(19), pages 1-21, September.
    10. Daxini, Amar & Ryan, Mary & O’Donoghue, Cathal & Barnes, Andrew P., 2019. "Understanding farmers’ intentions to follow a nutrient management plan using the theory of planned behaviour," Land Use Policy, Elsevier, vol. 85(C), pages 428-437.
    11. Yuxuan Xu & Jiangbo Chang & Fang Su, 2024. "Multi-Scale Evaluation and Simulation of Livelihood Efficiency in Post-Poverty Mountainous Areas," Land, MDPI, vol. 13(11), pages 1-35, October.
    12. Renata Walczak & Magdalena Kludacz-Alessandri & Liliana Hawrysz, 2022. "Use of Telemedicine Technology among General Practitioners during COVID-19: A Modified Technology Acceptance Model Study in Poland," IJERPH, MDPI, vol. 19(17), pages 1-18, September.
    13. Petr Matous, 2023. "Male and stale? Questioning the role of “opinion leaders” in agricultural programs," Agriculture and Human Values, Springer;The Agriculture, Food, & Human Values Society (AFHVS), vol. 40(3), pages 1205-1220, September.
    14. Maier, Erik, 2016. "Supply and demand on crowdlending platforms: connecting small and medium-sized enterprise borrowers and consumer investors," Journal of Retailing and Consumer Services, Elsevier, vol. 33(C), pages 143-153.
    15. Dana E. Harrison & Haya Ajjan, 2019. "Customer relationship management technology: bridging the gap between marketing education and practice," Journal of Marketing Analytics, Palgrave Macmillan, vol. 7(4), pages 205-219, December.
    16. Kim, Dennie & Funk, Russell & Zaheer, Aks, 2020. "Structure in Context: A Morphological View of Whole Network Performance," SocArXiv x6q7g, Center for Open Science.
    17. Schaak, Henning & Musshoff, Oliver, 2017. "Behavioral Drivers for Grazing Practices in Dairy Farming," 2017 Conference (61st), February 7-10, 2017, Brisbane, Australia 258680, Australian Agricultural and Resource Economics Society.
    18. Nguyen Hong Quan & Nguyen Thi Binh & Bui Thi Ly, 2022. "Impact of smart locker use on customer satisfaction of online shoppers in Vietnam," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-11, December.
    19. Zheng Li & Disheng Zhang & Xiaohuan Yan, 2024. "How Does Information Acquisition Ability Affect Farmers’ Green Production Behaviors: Evidence from Chinese Apple Growers," Agriculture, MDPI, vol. 14(5), pages 1-17, April.
    20. Schikofsky, Jan & Dannewald, Till & Kowald, Matthias, 2020. "Exploring motivational mechanisms behind the intention to adopt mobility as a service (MaaS): Insights from Germany," Transportation Research Part A: Policy and Practice, Elsevier, vol. 131(C), pages 296-312.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:agiwat:v:306:y:2024:i:c:s0378377424004980. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/agwat .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.