IDEAS home Printed from https://ideas.repec.org/p/osf/socarx/4nge5.html
   My bibliography  Save this paper

How unified is the Australian agricultural sector when talking to policy makers about digitalization?

Author

Listed:
  • Terhorst, Andrew
  • Garrard, Robert

Abstract

Technological advances are transforming agriculture in many parts of the world. Despite the importance of agriculture to its economy, Australia lags behind other advanced economies in the adoption of digital agricultural technology. The country risks losing its comparative advantage due to a weak policy around digital agriculture. This study combines network analysis and natural language processing to assess 654 public submissions to six government inquiries addressing agricultural innovation, the digital economy, and rural broadband communication networks, held between 2016 and 2018. The analysis shows there is no consistent narrative driving policy development around digital agriculture. A fragmented policy landscape is a concern because it means that current and emerging policies may not address key issues, resulting in sub-optimal outcomes for Australian agriculture.

Suggested Citation

  • Terhorst, Andrew & Garrard, Robert, 2022. "How unified is the Australian agricultural sector when talking to policy makers about digitalization?," SocArXiv 4nge5, Center for Open Science.
    • Handle: RePEc:osf:socarx:4nge5
    DOI: 10.31219/osf.io/4nge5
    as

    Download full text from publisher

    File URL: https://osf.io/download/6272628062f51d10ab22bdea/
    Download Restriction: no
    File URL: https://libkey.io/10.31219/osf.io/4nge5?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
    ---><---

    References listed on IDEAS

    as
    1. Brezina, Tadej, 2010. "The impacts of technology on growth: Studies of agriculture and steel," Technology in Society, Elsevier, vol. 32(4), pages 312-323.
    2. Chen, Yongmin, 2020. "Improving market performance in the digital economy," China Economic Review, Elsevier, vol. 62(C).
    3. Grün, Bettina & Hornik, Kurt, 2011. "topicmodels: An R Package for Fitting Topic Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i13).
    4. Hailin Liu & Ling Xu & Mengning Yang & Meng Yan & Xiaohong Zhang, 2015. "Predicting Component Failures Using Latent Dirichlet Allocation," Mathematical Problems in Engineering, Hindawi, vol. 2015, pages 1-15, July.
    5. Dele Raheem & Maxim Shishaev & Vladimir Dikovitsky, 2019. "Food System Digitalization as a Means to Promote Food and Nutrition Security in the Barents Region," Agriculture, MDPI, vol. 9(8), pages 1-19, August.
    6. Watanabe, Chihiro & Naveed, Nasir & Neittaanmäki, Pekka, 2018. "Digital solutions transform the forest-based bioeconomy into a digital platform industry - A suggestion for a disruptive business model in the digital economy," Technology in Society, Elsevier, vol. 54(C), pages 168-188.
    7. Garrard, Robert & Fielke, Simon, 2020. "Blockchain for trustworthy provenances: A case study in the Australian aquaculture industry," Technology in Society, Elsevier, vol. 62(C).
    8. Burroughs, Benjamin & Burroughs, W. Jeffrey, 2020. "Digital logistics: Enchantment in distribution channels," Technology in Society, Elsevier, vol. 62(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. Xiangzhen Peng & Xin Zhang & Xiaoyi Wang & Haisheng Li & Jiping Xu & Zhiyao Zhao, 2022. "Multi-Chain Collaboration-Based Information Management and Control for the Rice Supply Chain," Agriculture, MDPI, vol. 12(5), pages 1-26, May.
    2. Fang, Mingyue & Nie, Huihua & Shen, Xinyi, 2023. "Can enterprise digitization improve ESG performance?," Economic Modelling, Elsevier, vol. 118(C).
    3. Sandra Wankmüller, 2023. "A comparison of approaches for imbalanced classification problems in the context of retrieving relevant documents for an analysis," Journal of Computational Social Science, Springer, vol. 6(1), pages 91-163, April.
    4. Zhenxiang Cao & Liqing Peng, 2023. "The Impact of Digital Economics on Environmental Quality: A System Dynamics Approach," SAGE Open, , vol. 13(4), pages 21582440231, December.
    5. Arsenyan, Jbid & Mirowska, Agata & Piepenbrink, Anke, 2023. "Close encounters with the virtual kind: Defining a human-virtual agent coexistence framework," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    6. Holopainen, Jani & Mattila, Osmo & Pöyry, Essi & Parvinen, Petri, 2020. "Applying design science research methodology in the development of virtual reality forest management services," Forest Policy and Economics, Elsevier, vol. 116(C).
    7. Wei-Liang Zhang & Li-Ying Song & Muhammad Ilyas, 2023. "Can the digital economy promote fiscal effort?: Empirical evidence from Chinese cities," Economic Change and Restructuring, Springer, vol. 56(5), pages 3501-3525, October.
    8. Kun Wang & Bing Chen & Yuhong Li, 2024. "Technological, process or managerial innovation? How does digital transformation affect green innovation in industrial enterprises?," Economic Change and Restructuring, Springer, vol. 57(1), pages 1-32, February.
    9. Hong Joo Lee & Hoyeon Oh, 2020. "A Study on the Deduction and Diffusion of Promising Artificial Intelligence Technology for Sustainable Industrial Development," Sustainability, MDPI, vol. 12(14), pages 1-15, July.
    10. Coskun-Setirek, Abide & Tanrikulu, Zuhal, 2021. "Digital innovations-driven business model regeneration: A process model," Technology in Society, Elsevier, vol. 64(C).
    11. Ge Zhang & Yuxiang Gao & Gaoyong Li, 2023. "Research on Digital Transformation and Green Technology Innovation—Evidence from China’s Listed Manufacturing Enterprises," Sustainability, MDPI, vol. 15(8), pages 1-23, April.
    12. Maksym Polyakov & Morteza Chalak & Md. Sayed Iftekhar & Ram Pandit & Sorada Tapsuwan & Fan Zhang & Chunbo Ma, 2018. "Authorship, Collaboration, Topics, and Research Gaps in Environmental and Resource Economics 1991–2015," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 71(1), pages 217-239, September.
    13. Stefano Sbalchiero & Maciej Eder, 2020. "Topic modeling, long texts and the best number of topics. Some Problems and solutions," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(4), pages 1095-1108, August.
    14. Md Nazrul Islam & Md Mofazzal Hossain & Md Shafayet Shahed Ornob, 2024. "Business research on Industry 4.0: a systematic review using topic modelling approach," Future Business Journal, Springer, vol. 10(1), pages 1-15, December.
    15. Martin Baumgaertner & Johannes Zahner, 2021. "Whatever it takes to understand a central banker - Embedding their words using neural networks," MAGKS Papers on Economics 202130, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    16. Daoud, Adel & Kohl, Sebastian, 2016. "How much do sociologists write about economic topics? Using big data to test some conventional views in economic sociology, 1890 to 2014," MPIfG Discussion Paper 16/7, Max Planck Institute for the Study of Societies.
    17. Cardinale, Roberto & Cardinale, Ivano & Zupic, Ivan, 2024. "The EU's vulnerability to gas price and supply shocks: The role of mismatches between policy beliefs and changing international gas markets," Energy Economics, Elsevier, vol. 131(C).
    18. Shr-Wei Kao & Pin Luarn, 2020. "Topic Modeling Analysis of Social Enterprises: Twitter Evidence," Sustainability, MDPI, vol. 12(8), pages 1-20, April.
    19. Wang, Weilong & Wang, Jianlong & Wu, Haitao, 2024. "The impact of energy-consuming rights trading on green total factor productivity in the context of digital economy: Evidence from listed firms in China," Energy Economics, Elsevier, vol. 131(C).
    20. Al-Adwan, Ahmad Samed & Al-Debei, Mutaz M. & Dwivedi, Yogesh K., 2022. "E-commerce in high uncertainty avoidance cultures: The driving forces of repurchase and word-of-mouth intentions," Technology in Society, Elsevier, vol. 71(C).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:osf:socarx:4nge5. 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: OSF (email available below). General contact details of provider: https://arabixiv.org .

    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.