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Determinants of adoption of High Speed Data Services in the business market : Evidence for a combined technology acceptance model with task technology fit model

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  • Margherita Pagani

    (EM - EMLyon Business School)

Abstract

This paper presents a Business-Oriented Model of Factors that affect the adoption of wireless High Speed Data Services (HSDS). We reviewed business IT acceptance literature and developed an explorative survey of a sample of twelve companies in Europe and USA. From this, a theoretical model was created and hypotheses were formulated. Data were then collected on a sample of 1545 companies in USA and Europe. Based on these results, we developed a model that combined the key ideas of both TAM and TTF and showed that both were necessary in predicting wireless High Speed Data Service adoption.

Suggested Citation

  • Margherita Pagani, 2006. "Determinants of adoption of High Speed Data Services in the business market : Evidence for a combined technology acceptance model with task technology fit model," Post-Print hal-02313097, HAL.
    • Handle: RePEc:hal:journl:hal-02313097
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    Cited by:

    1. Youngcheoul Kang & Nakbum Choi & Seoyong Kim, 2021. "Searching for New Model of Digital Informatics for Human–Computer Interaction: Testing the Institution-Based Technology Acceptance Model (ITAM)," IJERPH, MDPI, vol. 18(11), pages 1-36, May.
    2. Lütfü Şağbanşua & Osman Şahin & Muhterem Çöl, 2015. "Determinants of Mobile Penetration to Forecast New Broadband Adoption: OECD Case," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 3(2), pages 35-40, December.
    3. John A. Kaliski & Queen E. Booker & Paul L. Schumann, 2012. "An Architecture For Dynamic E-Learning Environments Based On Student Activity And Learning Styles," Business Education and Accreditation, The Institute for Business and Finance Research, vol. 4(2), pages 113-124.
    4. Mazen El-Masri & Karim Al-Yafi & Muhammad Mustafa Kamal, 2023. "A Task-Technology-Identity Fit Model of Smartwatch Utilisation and User Satisfaction: A Hybrid SEM-Neural Network Approach," Information Systems Frontiers, Springer, vol. 25(2), pages 835-852, April.
    5. Wang, Yi-Shun & Li, Hsien-Ta & Li, Ci-Rong & Zhang, Ding-Zhong, 2016. "Factors affecting hotels' adoption of mobile reservation systems: A technology-organization-environment framework," Tourism Management, Elsevier, vol. 53(C), pages 163-172.
    6. Ya-Yueh Shih & Chi-Yuan Chen, 2013. "The study of behavioral intention for mobile commerce: via integrated model of TAM and TTF," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(2), pages 1009-1020, February.
    7. Ting Wang & Chien-Liang Lin & Yu-Sheng Su, 2021. "Continuance Intention of University Students and Online Learning during the COVID-19 Pandemic: A Modified Expectation Confirmation Model Perspective," Sustainability, MDPI, vol. 13(8), pages 1-15, April.

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