IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i4p1557-d1337913.html
   My bibliography  Save this article

Sustainable Regional Straw Utilization: Collaborative Approaches and Network Optimization

Author

Listed:
  • Jing Tao

    (School of Business, Xinyang Normal University, Xinyang 464000, China)

  • Wuliyasu Bai

    (School of Economic and Management, China University of Geosciences, Wuhan 430074, China)

  • Rongsheng Peng

    (School of Business, Xinyang Normal University, Xinyang 464000, China)

  • Ziying Wu

    (School of Business, Xinyang Normal University, Xinyang 464000, China)

Abstract

The SDGS repeatedly emphasizes the importance of reducing greenhouse gas emissions such as carbon dioxide. The strategic utilization of straw resources to curtail open-air burning not only epitomizes optimal resource deployment but also constitutes a significant stride in environmental preservation and sustainable development. Globally, the imperative of this challenge is increasingly recognized, prompting nations to enhance straw resource utilization technologies, devise regional management strategies, and extend requisite policy support. Regional straw utilization encapsulates a comprehensive concept involving an array of stakeholders including governments, farmers, corporations, brokers, and rural cooperatives, with each one of these uniquely contributing to a multifaceted network that is influenced by their respective resource utilization intentions. This heterogeneity, coupled with the diverse roles of these stakeholders, renders the identification of the pivotal participants and their specific functions within the intricate network. To navigate this complexity, this study employed text analysis and social network analysis, uncovering 30 robust associative rules within this domain. Our findings elucidate that the stakeholder network in regional straw resource utilization exhibits characteristics akin to the NW small-world network model. The key network entities identified include farmers, corporations, governments, and rural cooperatives. Furthermore, the study systematically categorizes the principal entities and elucidates the dynamics of this multi-stakeholder network. This research delineates four developmental models that are pertinent to regional straw resource utilization, which is a framework that is instrumental in pinpointing the accountable parties and optimizing the overarching benefits derived from these resources. The significance of this research lies not only in showcasing the potential of straw resources for environmental conservation but also in underscoring the importance of collaborative strategies and network optimization in order to achieve sustainable development goals.

Suggested Citation

  • Jing Tao & Wuliyasu Bai & Rongsheng Peng & Ziying Wu, 2024. "Sustainable Regional Straw Utilization: Collaborative Approaches and Network Optimization," Sustainability, MDPI, vol. 16(4), pages 1-23, February.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:4:p:1557-:d:1337913
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/4/1557/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/4/1557/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Matthias Honegger & Axel Michaelowa & Joyashree Roy, 2021. "Potential implications of carbon dioxide removal for the sustainable development goals," Climate Policy, Taylor & Francis Journals, vol. 21(5), pages 678-698, May.
    2. M. E. J. Newman & D. J. Watts, 1999. "Renormalization Group Analysis of the Small-World Network Model," Working Papers 99-04-029, Santa Fe Institute.
    3. Comellas, Francesc & Sampels, Michael, 2002. "Deterministic small-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 309(1), pages 231-235.
    4. Fu, Lipeng & Wang, Xueqing & Zhao, Heng & Li, Mengnan, 2022. "Interactions among safety risks in metro deep foundation pit projects: An association rule mining-based modeling framework," Reliability Engineering and System Safety, Elsevier, vol. 221(C).
    5. Can, Umit & Alatas, Bilal, 2019. "A new direction in social network analysis: Online social network analysis problems and applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    6. Wu, Juanjuan & Zhang, Jian & Yi, Weiming & Cai, Hongzhen & Su, Zhanpeng & Li, Yang, 2021. "Economic analysis of different straw supply modes in China," Energy, Elsevier, vol. 237(C).
    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. Lu, Zhe-Ming & Guo, Shi-Ze, 2012. "A small-world network derived from the deterministic uniform recursive tree," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 87-92.
    2. Chen, Lei & Yue, Dong & Dou, Chunxia, 2019. "Optimization on vulnerability analysis and redundancy protection in interdependent networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1216-1226.
    3. Marcus Berliant & Axel H. Watanabe, 2018. "A scale‐free transportation network explains the city‐size distribution," Quantitative Economics, Econometric Society, vol. 9(3), pages 1419-1451, November.
    4. An, Sufang & Gao, Xiangyun & An, Haizhong & Liu, Siyao & Sun, Qingru & Jia, Nanfei, 2020. "Dynamic volatility spillovers among bulk mineral commodities: A network method," Resources Policy, Elsevier, vol. 66(C).
    5. Khalilzadeh, Jalayer, 2022. "It is a small world, or is it? A look into two decades of tourism system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    6. Xiangyun Gao & Haizhong An & Weiqiong Zhong, 2013. "Features of the Correlation Structure of Price Indices," PLOS ONE, Public Library of Science, vol. 8(4), pages 1-9, April.
    7. Chung-Yuan Huang & Chuen-Tsai Sun & Hsun-Cheng Lin, 2005. "Influence of Local Information on Social Simulations in Small-World Network Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(4), pages 1-8.
    8. Gao, Xiangyun & An, Haizhong & Fang, Wei & Li, Huajiao & Sun, Xiaoqi, 2014. "The transmission of fluctuant patterns of the forex burden based on international crude oil prices," Energy, Elsevier, vol. 73(C), pages 380-386.
    9. Wang, Wenhao & Wang, Yanhui & Wang, Guangxing & Li, Man & Jia, Limin, 2023. "Identification of the critical accident causative factors in the urban rail transit system by complex network theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 610(C).
    10. Yuan Yuan & Xintong Sun & Ning Liu, 2022. "Measuring structural characteristics and evolutionary patterns of an industrial carbon footprint network: A social network analysis approach," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(S2), pages 159-180, November.
    11. Ru Fang, Yan & Zhang, Silu & Zhou, Ziqiao & Shi, Wenjun & Hui Xie, Guang, 2022. "Sustainable development in China: Valuation of bioenergy potential and CO2 reduction from crop straw," Applied Energy, Elsevier, vol. 322(C).
    12. Yu, Haitao & Guo, Xinmeng & Wang, Jiang & Deng, Bin & Wei, Xile, 2015. "Vibrational resonance in adaptive small-world neuronal networks with spike-timing-dependent plasticity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 170-179.
    13. Huang, Chung-Yuan & Chin, Wei-Chien-Benny & Fu, Yu-Hsiang & Tsai, Yu-Shiuan, 2019. "Beyond bond links in complex networks:Local bridges, global bridges and silk links," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 536(C).
    14. Mark Newman, 1999. "Small Worlds: The Structure of Social Networks," Working Papers 99-12-080, Santa Fe Institute.
    15. An, Haizhong & Gao, Xiangyun & Fang, Wei & Ding, Yinghui & Zhong, Weiqiong, 2014. "Research on patterns in the fluctuation of the co-movement between crude oil futures and spot prices: A complex network approach," Applied Energy, Elsevier, vol. 136(C), pages 1067-1075.
    16. Lan, He & Ma, Xiaoxue & Qiao, Weiliang & Ma, Laihao, 2022. "On the causation of seafarers’ unsafe acts using grounded theory and association rule," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    17. Yu, Haitao & Guo, Xinmeng & Wang, Jiang & Deng, Bin & Wei, Xile, 2015. "Spike coherence and synchronization on Newman–Watts small-world neuronal networks modulated by spike-timing-dependent plasticity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 307-317.
    18. Kim, Minjung & Kim, Beom Jun, 2022. "Defense strategies against cascading failures in networks: “Too-big-to-fail” and “too-small-to-fail”," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    19. Shi, Wen & Zhou, Qing & Zhou, Yanju, 2023. "An efficient elementary effect-based method for sensitivity analysis in identifying main and two-factor interaction effects," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    20. Samaniego, Joseluis & Lorenzo, Santiago & Rondón Toro, Estefani & Krieger Merico, Luiz F. & Herrera Jiménez, Juan & Rouse, Paul & Harrison, Nicholas, 2023. "Nature-based solutions and carbon dioxide removal," Documentos de Proyectos 48691, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).

    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:gam:jsusta:v:16:y:2024:i:4:p:1557-:d:1337913. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.