IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i22p12141-d682811.html
   My bibliography  Save this article

Research on the Spatio-Temporal Impacts of Environmental Factors on the Fresh Agricultural Product Supply Chain and the Spatial Differentiation Issue—An Empirical Research on 31 Chinese Provinces

Author

Listed:
  • Xuemei Fan

    (School of Management, Jilin University, 5988 Renmin Street, Changchun 130022, China)

  • Ziyue Nan

    (School of Management, Jilin University, 5988 Renmin Street, Changchun 130022, China)

  • Yuanhang Ma

    (School of Management, Jilin University, 5988 Renmin Street, Changchun 130022, China)

  • Yingdan Zhang

    (School of Management, Jilin University, 5988 Renmin Street, Changchun 130022, China)

  • Fei Han

    (School of Management, Jilin University, 5988 Renmin Street, Changchun 130022, China)

Abstract

Environmental factors in time and space play a critical role in advancing the sustainable development of the fresh agricultural product supply chain. This paper, availing the panel data of 31 Chinese provinces from 2008 to 2019, constructs a system of indicators assessing the development of the fresh agricultural product supply chain, and obtains the comprehensive development level in the Entropy Weight Method (EWM). Furthermore, it establishes a comparison between optimal solutions generated by the Instrumental Variables Method (IVM) and the Generalized Method of Moments (GMM) over the endogeneity issue of variables, creates the comparison between the weighted regression methods of Geographically Weighted Regression (GWR) and Multi-scale Geographic Weighted Regression (MGWR), and obtains the relationship among the 14 environmental factors in their spatio-temporal impacts on the development of the fresh agricultural product supply chain. The results indicate that: (1) the environmental influencing factors in this paper have significant endogenous problems and various environmental factors impact on the fresh agricultural product supply chain in different trends and to different degrees. (2) With different bandwidths, the environmental factors could impact the fresh agricultural product supply chain to greatly varied degrees, demonstrating a strong attribute of regional correlation.

Suggested Citation

  • Xuemei Fan & Ziyue Nan & Yuanhang Ma & Yingdan Zhang & Fei Han, 2021. "Research on the Spatio-Temporal Impacts of Environmental Factors on the Fresh Agricultural Product Supply Chain and the Spatial Differentiation Issue—An Empirical Research on 31 Chinese Provinces," IJERPH, MDPI, vol. 18(22), pages 1-26, November.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:22:p:12141-:d:682811
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/22/12141/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/18/22/12141/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Hansen, Christian & Kozbur, Damian, 2014. "Instrumental variables estimation with many weak instruments using regularized JIVE," Journal of Econometrics, Elsevier, vol. 182(2), pages 290-308.
    2. Hlouskova, Jaroslava & Sögner, Leopold, 2020. "GMM estimation of affine term structure models," Econometrics and Statistics, Elsevier, vol. 13(C), pages 2-15.
    3. C. Larochez-Dupraz & M. Huchet-Bourdon, 2016. "Agricultural support and vulnerability of food security to trade in developing countries," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 8(6), pages 1191-1206, December.
    4. Chatelain, Jean-Bernard, 2007. "Improving consistent moment selection procedures for generalized method of moments estimation," Economics Letters, Elsevier, vol. 95(3), pages 380-385, June.
    5. Jianhong He & Yaling Lei & Xiao Fu, 2019. "Do Consumer’s Green Preference and the Reference Price Effect Improve Green Innovation? A Theoretical Model Using the Food Supply Chain as a Case," IJERPH, MDPI, vol. 16(24), pages 1-15, December.
    6. Jingjie Wang & Zhiqiang Zhu & Liliana Mihaela Moga & Jinyou Hu & Xiaoshuan Zhang, 2019. "A Holistic Packaging Efficiency Evaluation Method for Loss Prevention in Fresh Vegetable Cold Chain," Sustainability, MDPI, vol. 11(14), pages 1-18, July.
    7. Baofeng Sun & Mingyang Ma & Yan Li & Lili Zheng, 2020. "Analysis on the stability and evolutionary trend of the symbiosis system in the supply chain of fresh agricultural products," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-20, July.
    8. Fang Qiu & Qifan Hu & Bing Xu, 2020. "Fresh Agricultural Products Supply Chain Coordination and Volume Loss Reduction Based on Strategic Consumer," IJERPH, MDPI, vol. 17(21), pages 1-25, October.
    9. Lejarza, Fernando & Pistikopoulos, Ioannis & Baldea, Michael, 2021. "A scalable real-time solution strategy for supply chain management of fresh produce: A Mexico-to-United States cross border study," International Journal of Production Economics, Elsevier, vol. 240(C).
    10. Xiaoyu Bian & Guanxin Yao & Guohong Shi, 2020. "Social and natural risk factor correlation in China's fresh agricultural product supply," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-13, June.
    11. Nagurney, Anna, 2021. "Supply chain game theory network modeling under labor constraints: Applications to the Covid-19 pandemic," European Journal of Operational Research, Elsevier, vol. 293(3), pages 880-891.
    12. Jinghan Zhang & Wujun Cao & Minyoung Park, 2019. "Reliability Analysis and Optimization of Cold Chain Distribution System for Fresh Agricultural Products," Sustainability, MDPI, vol. 11(13), pages 1-17, July.
    13. Linbo Wang & James M. Robins & Thomas S. Richardson, 2017. "On falsification of the binary instrumental variable model," Biometrika, Biometrika Trust, vol. 104(1), pages 229-236.
    14. Linbo Wang & James M. Robins & Thomas S. Richardson, 2017. "Erratum: On falsification of the binary instrumental variable model," Biometrika, Biometrika Trust, vol. 104(1), pages 1-1.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liukun Wang & Chunjie Qi & Peng Jiang & Si Xiang, 2022. "The Impact of Blockchain Application on the Qualification Rate and Circulation Efficiency of Agricultural Products: A Simulation Analysis with Agent-Based Modelling," IJERPH, MDPI, vol. 19(13), pages 1-17, June.
    2. Jian Li & Xin Yan & Yongwu Li & Xuefan Dong, 2023. "Optimizing the Agricultural Supply Chain through E-Commerce: A Case Study of Tudouec in Inner Mongolia, China," IJERPH, MDPI, vol. 20(5), pages 1-19, February.

    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. Jiaping Xie & Dan Liu & Ling Liang & Qinglin Li, 2022. "Contract choice and advance selling strategy in a supply chain of FAP," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-18, March.
    2. Myoung‐jae Lee, 2021. "Instrument residual estimator for any response variable with endogenous binary treatment," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 83(3), pages 612-635, July.
    3. Alexandre Belloni & Victor Chernozhukov & Denis Chetverikov & Christian Hansen & Kengo Kato, 2018. "High-dimensional econometrics and regularized GMM," CeMMAP working papers CWP35/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Alexandre Belloni & Victor Chernozhukov & Christian Hansen & Damian Kozbur, 2016. "Inference in High-Dimensional Panel Models With an Application to Gun Control," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(4), pages 590-605, October.
    5. Songhong Chen & Jian Ming Luo, 2023. "Understand Delegates Risk Attitudes and Behaviour: The Moderating Effect of Trust in COVID-19 Vaccination," IJERPH, MDPI, vol. 20(5), pages 1-18, February.
    6. Berger, Niklas & Schulze-Schwering, Stefan & Long, Elisa & Spinler, Stefan, 2023. "Risk management of supply chain disruptions: An epidemic modeling approach," European Journal of Operational Research, Elsevier, vol. 304(3), pages 1036-1051.
    7. Matsushita, Yukitoshi & Otsu, Taisuke, 2022. "A jackknife Lagrange multiplier test with many weak instruments," LSE Research Online Documents on Economics 116392, London School of Economics and Political Science, LSE Library.
    8. Rozhkov, Maxim & Ivanov, Dmitry & Blackhurst, Jennifer & Nair, Anand, 2022. "Adapting supply chain operations in anticipation of and during the COVID-19 pandemic," Omega, Elsevier, vol. 110(C).
    9. Emmanuel Selorm Tsyawo, 2023. "Feasible IV regression without excluded instruments," The Econometrics Journal, Royal Economic Society, vol. 26(2), pages 235-256.
    10. Anna Nagurney, 2022. "Supply chain networks, wages, and labor productivity: insights from Lagrange. analysis and computations," Journal of Global Optimization, Springer, vol. 83(3), pages 615-638, July.
    11. Marine Carrasco & Guy Tchuente, 2016. "Efficient Estimation with Many Weak Instruments Using Regularization Techniques," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1609-1637, December.
    12. Chatelain, Jean-Bernard & Ralf, Kirsten, 2021. "Inference on time-invariant variables using panel data: A pretest estimator," Economic Modelling, Elsevier, vol. 97(C), pages 157-166.
    13. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Valid Post-Selection and Post-Regularization Inference: An Elementary, General Approach," Annual Review of Economics, Annual Reviews, vol. 7(1), pages 649-688, August.
    14. Shafiee, Mohammad & Zare-Mehrjerdi, Yahia & Govindan, Kannan & Dastgoshade, Sohaib, 2022. "A causality analysis of risks to perishable product supply chain networks during the COVID-19 outbreak era: An extended DEMATEL method under Pythagorean fuzzy environment," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 163(C).
    15. Maria O. Hanna & Mostafa F. Shaaban & Magdy M. A. Salama, 2022. "A New Cooperative Game—Theoretic Approach for Customer-Owned Energy Storage," Sustainability, MDPI, vol. 14(6), pages 1-14, March.
    16. Qingliang Fan & Yaqian Wu, 2020. "Endogenous Treatment Effect Estimation with some Invalid and Irrelevant Instruments," Papers 2006.14998, arXiv.org.
    17. Victor Chernozhukov & Christian Hansen & Martin Spindler, 2015. "Post-Selection and Post-Regularization Inference in Linear Models with Many Controls and Instruments," American Economic Review, American Economic Association, vol. 105(5), pages 486-490, May.
    18. Gorji, Mohammad-Ali & Shetab-Boushehri, Seyyed-Nader & Akbarzadeh, Meisam, 2022. "Developing public transportation resilience against the epidemic through government tax policies: A game-theoretic approach," Transport Policy, Elsevier, vol. 128(C), pages 229-239.
    19. Anna Nagurney & Pritha Dutta, 2021. "A Multiclass, Multiproduct Covid-19 Convalescent Plasma Donor Equilibrium Model," SN Operations Research Forum, Springer, vol. 2(3), pages 1-30, September.
    20. Achim Ahrens & Christian B. Hansen & Mark E. Schaffer, 2020. "lassopack: Model selection and prediction with regularized regression in Stata," Stata Journal, StataCorp LP, vol. 20(1), pages 176-235, March.

    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:jijerp:v:18:y:2021:i:22:p:12141-:d:682811. 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.