IDEAS home Printed from https://ideas.repec.org/a/cog/meanco/v10y2022i3p303-314.html
   My bibliography  Save this article

Community Internet of Things as Mobile Infrastructure: Methodological Challenges and Opportunities

Author

Listed:
  • Chelsea P. Butkowski

    (Annenberg School for Communication, University of Pennsylvania, USA)

  • Ngai Keung Chan

    (School of Journalism and Communication, The Chinese University of Hong Kong, Hong Kong)

  • Lee Humphreys

    (Department of Communication, Cornell University, USA)

Abstract

From smart devices to homes to cities, Internet of Things (IoT) technologies have become embedded within everyday objects on a global scale. We understand IoT technologies as a form of infrastructure that bridges the gaps between offline spaces and online networks as they track, transmit, and construct digital data from and of the physical world. We examine the social construction of IoT network technologies through their technological design and corporate discourses. In this article, we explore the methodological challenges and opportunities of studying IoT as an emerging network technology. We draw on a case study of a low-power wide-area network (LPWAN), a cost-effective radio frequency network that is designed to connect sensors across long distances. Reflecting on our semi-structured interviews with LPWAN users and advocates, participant observation at conferences about LPWAN, as well as a community-based LPWAN project, we examine the intersections of methods and practices as related to space, data, and infrastructures. We identify three key methodological obstacles involved in studying the social construction of networked technologies that straddle physical and digital environments. These include (a) transcending the invisibility and abstraction of network infrastructures, (b) managing practical and conceptual boundaries to sample key cases and participants, and (c) negotiating competing technospatial imaginaries between participants and researchers. Through our reflection, we demonstrate that these challenges also serve as generative methodological opportunities, extending existing tools to study the ways data connects online and offline spaces.

Suggested Citation

  • Chelsea P. Butkowski & Ngai Keung Chan & Lee Humphreys, 2022. "Community Internet of Things as Mobile Infrastructure: Methodological Challenges and Opportunities," Media and Communication, Cogitatio Press, vol. 10(3), pages 303-314.
    • Handle: RePEc:cog:meanco:v:10:y:2022:i:3:p:303-314
    as

    Download full text from publisher

    File URL: https://www.cogitatiopress.com/mediaandcommunication/article/view/5372
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rotolo, Daniele & Hicks, Diana & Martin, Ben R., 2015. "What is an emerging technology?," Research Policy, Elsevier, vol. 44(10), pages 1827-1843.
    2. Laura Forlano & Alison Powell & Gwen Shaffer & Benjamin Lennett, 2011. "From the digital divide to digital excellence: global best practices for municipal and community wireless networks," LSE Research Online Documents on Economics 29461, London School of Economics and Political Science, LSE Library.
    3. Oecd, 2018. "Consumer product safety in the Internet of Things," OECD Digital Economy Papers 267, OECD Publishing.
    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. Zhang, Yi & Huang, Ying & Porter, Alan L. & Zhang, Guangquan & Lu, Jie, 2019. "Discovering and forecasting interactions in big data research: A learning-enhanced bibliometric study," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 795-807.
    2. Laura Borge & Stefanie Bröring, 2020. "What affects technology transfer in emerging knowledge areas? A multi-stakeholder concept mapping study in the bioeconomy," The Journal of Technology Transfer, Springer, vol. 45(2), pages 430-460, April.
    3. Petersen, Alexander M. & Rotolo, Daniele & Leydesdorff, Loet, 2016. "A triple helix model of medical innovation: Supply, demand, and technological capabilities in terms of Medical Subject Headings," Research Policy, Elsevier, vol. 45(3), pages 666-681.
    4. Gao, Qiang & Liang, Zhentao & Wang, Ping & Hou, Jingrui & Chen, Xiuxiu & Liu, Manman, 2021. "Potential index: Revealing the future impact of research topics based on current knowledge networks," Journal of Informetrics, Elsevier, vol. 15(3).
    5. Mark Knell & Simone Vannuccini, 2022. "Tools and concepts for understanding disruptive technological change after Schumpeter," Jena Economics Research Papers 2022-005, Friedrich-Schiller-University Jena.
    6. Andrzej Magruk, 2021. "Analysis of Uncertainties and Levels of Foreknowledge in Relation to Major Features of Emerging Technologies—The Context of Foresight Research for the Fourth Industrial Revolution," Sustainability, MDPI, vol. 13(17), pages 1-16, September.
    7. Stefano Bianchini & Moritz Müller & Pierre Pelletier, 2022. "Artificial intelligence in science: An emerging general method of invention," Post-Print hal-03958025, HAL.
    8. Cécile Godé & François de Corbière & Jessie Pallud, 2020. "Les technologies émergentes en contexte extrême : de l’adaptation à l’anticipation ? (Editorial)," Post-Print hal-02912845, HAL.
    9. Burmaoglu, Serhat & Sartenaer, Olivier & Porter, Alan, 2019. "Conceptual definition of technology emergence: A long journey from philosophy of science to science policy," Technology in Society, Elsevier, vol. 59(C).
    10. Khando Khando & M. Sirajul Islam & Shang Gao, 2022. "The Emerging Technologies of Digital Payments and Associated Challenges: A Systematic Literature Review," Future Internet, MDPI, vol. 15(1), pages 1-21, December.
    11. Zheng Yan & Wenqian Robertson & Yaosheng Lou & Tom W. Robertson & Sung Yong Park, 2021. "Finding leading scholars in mobile phone behavior: a mixed-method analysis of an emerging interdisciplinary field," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(12), pages 9499-9517, December.
    12. Peter Sjögårde & Fereshteh Didegah, 2022. "The association between topic growth and citation impact of research publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(4), pages 1903-1921, April.
    13. Shuo Xu & Liyuan Hao & Xin An & Hongshen Pang & Ting Li, 2020. "Review on emerging research topics with key-route main path analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 607-624, January.
    14. Mendonça, Sandro & Damásio, Bruno & Charlita de Freitas, Luciano & Oliveira, Luís & Cichy, Marcin & Nicita, António, 2022. "The rise of 5G technologies and systems: A quantitative analysis of knowledge production," Telecommunications Policy, Elsevier, vol. 46(4).
    15. Kotowicz, Janusz & Brzęczek, Mateusz, 2019. "Comprehensive multivariable analysis of the possibility of an increase in the electrical efficiency of a modern combined cycle power plant with and without a CO2 capture and compression installations ," Energy, Elsevier, vol. 175(C), pages 1100-1120.
    16. Iizuka, Michiko & Hane, Gerald, 2021. "Transformation towards sustainable development goals: Role of innovation ecosystems for inclusive, disruptive advances in five Asian case studies," MERIT Working Papers 2021-001, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    17. Zamani, Mehdi & Yalcin, Haydar & Naeini, Ali Bonyadi & Zeba, Gordana & Daim, Tugrul U, 2022. "Developing metrics for emerging technologies: identification and assessment," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    18. Ad van den Oord & Arjen van Witteloostuijn, 2018. "A multi-level model of emerging technology: An empirical study of the evolution of biotechnology from 1976 to 2003," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-27, May.
    19. Byoungsam Jin & Youngchul Bae, 2023. "Prospective Research Trend Analysis on Zero-Energy Building (ZEB): An Artificial Intelligence Approach," Sustainability, MDPI, vol. 15(18), pages 1-21, September.
    20. Bonsón, Enrique & Lavorato, Domenica & Lamboglia, Rita & Mancini, Daniela, 2021. "Artificial intelligence activities and ethical approaches in leading listed companies in the European Union," International Journal of Accounting Information Systems, Elsevier, vol. 43(C).

    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:cog:meanco:v:10:y:2022:i:3:p:303-314. 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: António Vieira (email available below). General contact details of provider: https://www.cogitatiopress.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.