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“Technology Readiness and Acceptance Model” as a Predictor for the Use Intention of Data Standards in Smart Cities

Author

Listed:
  • Raf Buyle

    (Internet Technology and Data Science Lab, Ghent University, Belgium)

  • Mathias Van Compernolle

    (Research Group for Media, Innovation, and Communication Technologies, Ghent University, Belgium)

  • Eveline Vlassenroot

    (Research Group for Media, Innovation, and Communication Technologies, Ghent University, Belgium)

  • Ziggy Vanlishout

    (Informatie Vlaanderen, Flemish Government, Belgium)

  • Peter Mechant

    (Internet Technology and Data Science Lab, Ghent University, Belgium)

  • Erik Mannens

    (Research Group for Media, Innovation, and Communication Technologies, Ghent University, Belgium)

Abstract

Taking the region of Flanders in Belgium as a case study, this article reflects on how smart cities initiated a grassroots initiative on data interoperability. We observe that cities are struggling due to the fragmentation of data and services across different governmental levels. This may cause frustrations in the everyday life of citizens as they expect a coherent user experience. Our research question considers the relationship between individual characteristics of decision makers and their intention to use data standards. We identified criteria for implementing data standards in the public sector by analysing the factors that affect the adoption of data governance, based on the Technology Readiness and Acceptance Model (TRAM), by conducting an online survey (n = 205). Results indicate that respondents who score high on innovativeness have a higher intention to use data standards. However, we conclude that personality characteristics as described in the TRAM-model are not significant predictors of the perceived usefulness and perceived ease of use of data standards. Therefore, we suggest exploring the effects of network governance and organisational impediments to speed-up the adoption of open standards and raise interoperability in complex ecosystems.

Suggested Citation

  • Raf Buyle & Mathias Van Compernolle & Eveline Vlassenroot & Ziggy Vanlishout & Peter Mechant & Erik Mannens, 2018. "“Technology Readiness and Acceptance Model” as a Predictor for the Use Intention of Data Standards in Smart Cities," Media and Communication, Cogitatio Press, vol. 6(4), pages 127-139.
    • Handle: RePEc:cog:meanco:v:6:y:2018:i:4:p:127-139
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    References listed on IDEAS

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    1. Viswanath Venkatesh, 2000. "Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model," Information Systems Research, INFORMS, vol. 11(4), pages 342-365, December.
    2. Viswanath Venkatesh & Hillol Bala, 2012. "Adoption and Impacts of Interorganizational Business Process Standards: Role of Partnering Synergy," Information Systems Research, INFORMS, vol. 23(4), pages 1131-1157, December.
    3. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    4. Joan Costa-Font & Elias Mossialos & Caroline Rudisill, 2009. "Optimism and the perceptions of new risks," Journal of Risk Research, Taylor & Francis Journals, vol. 12(1), pages 27-41, January.
    5. Stango Victor, 2004. "The Economics of Standards Wars," Review of Network Economics, De Gruyter, vol. 3(1), pages 1-19, March.
    6. Gabriela Viale Pereira & Maria Alexandra Cunha & Thomas J. Lampoltshammer & Peter Parycek & Maurício Gregianin Testa, 2017. "Increasing collaboration and participation in smart city governance: a cross-case analysis of smart city initiatives," Information Technology for Development, Taylor & Francis Journals, vol. 23(3), pages 526-553, July.
    7. Jari Kolehmainen & Joe Irvine & Linda Stewart & Zoltan Karacsonyi & Tünde Szabó & Juha Alarinta & Anders Norberg, 2016. "Quadruple Helix, Innovation and the Knowledge-Based Development: Lessons from Remote, Rural and Less-Favoured Regions," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 7(1), pages 23-42, March.
    8. James C. Brancheau & James C. Wetherbe, 1990. "The Adoption of Spreadsheet Software: Testing Innovation Diffusion Theory in the Context of End-User Computing," Information Systems Research, INFORMS, vol. 1(2), pages 115-143, June.
    9. Patrick Biernacki & Dan Waldorf, 1981. "Snowball Sampling: Problems and Techniques of Chain Referral Sampling," Sociological Methods & Research, , vol. 10(2), pages 141-163, November.
    10. Erik Brynjolfsson & Brian Kahin (ed.), 2002. "Understanding the Digital Economy: Data, Tools, and Research," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262523302, December.
    11. Mukherjee, Ashesh & Hoyer, Wayne D, 2001. "The Effect of Novel Attributes on Product Evaluation," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 28(3), pages 462-472, December.
    12. Rosseel, Yves, 2012. "lavaan: An R Package for Structural Equation Modeling," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 48(i02).
    13. Rao, Akshay R & Monroe, Kent B, 1988. "The Moderating Effect of Prior Knowledge on Cue Utilization in Product Evaluations," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 15(2), pages 253-264, September.
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    Cited by:

    1. Jadrić, Mario & Mijač, Tea & Ćukušić, Maja, 2020. "Identifying Costs and Benefits of Smart City Applications from End-users' Perspective," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2020), Virtual Conference, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Virtual Conference, 10-12 September 2020, pages 398-409, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
    2. Jinkyung Jenny Kim & Heesup Han, 2022. "Hotel Service Innovation with Smart Technologies: Exploring Consumers’ Readiness and Behaviors," Sustainability, MDPI, vol. 14(10), pages 1-15, May.
    3. Marimuthu, Malliga & D'Souza, Clare & Shukla, Yupal, 2022. "Integrating community value into the adoption framework: A systematic review of conceptual research on participatory smart city applications," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    4. Arfan Shahzad & Nurhana Zahrullail & Ahsan Akbar & Hana Mohelska & Arsalan Hussain, 2022. "COVID-19’s Impact on Fintech Adoption: Behavioral Intention to Use the Financial Portal," JRFM, MDPI, vol. 15(10), pages 1-18, September.
    5. .Ibrahim Halil Efend.iou{g}lu & Gokhan Akel & Bekir Deu{g}.irmenc.i & Dilek Aydou{g}du & Kamile Elmasou{g}lu & Hande Begum Bum.in Doyduk & Arzu c{S}eker & Hatice Bahc{c}e, 2023. "The Mediating Effect of Blockchain Technology on the Cryptocurrency Purchase Intention," Papers 2310.05970, arXiv.org.
    6. Peter Mechant & Nils Walravens, 2018. "E-Government and Smart Cities: Theoretical Reflections and Case Studies," Media and Communication, Cogitatio Press, vol. 6(4), pages 119-122.
    7. Pillai, Rajasshrie & Sivathanu, Brijesh & Dwivedi, Yogesh K., 2020. "Shopping intention at AI-powered automated retail stores (AIPARS)," Journal of Retailing and Consumer Services, Elsevier, vol. 57(C).

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