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Information technology adoption behavior life cycle: Toward a Technology Continuance Theory (TCT)

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  • Liao, Chechen
  • Palvia, Prashant
  • Chen, Jain-Liang

Abstract

For over a decade, researchers have devoted much effort to construct theoretical models, such as the Technology Acceptance Model (TAM) and the Expectation Confirmation Model (ECM) for explaining and predicting user behavior in IS acceptance and continuance. Another model, the Cognitive Model (COG), was proposed for continuance behavior; it combines some of the variables used in both TAM and ECM. This study applied the technique of structured equation modeling with multiple group analysis to compare the TAM, ECM, and COG models. Results indicate that TAM, ECM, and COG have quite different assumptions about the underlying constructs that dictate user behavior and thus have different explanatory powers. The six constructs in the three models were synthesized to propose a new Technology Continuance Theory (TCT). A major contribution of TCT is that it combines two central constructs: attitude and satisfaction into one continuance model, and has applicability for users at different stages of the adoption life cycle, i.e., initial, short-term and long-term users. The TCT represents a substantial improvement over the TAM, ECM and COG models in terms of both breadth of applicability and explanatory power.

Suggested Citation

  • Liao, Chechen & Palvia, Prashant & Chen, Jain-Liang, 2009. "Information technology adoption behavior life cycle: Toward a Technology Continuance Theory (TCT)," International Journal of Information Management, Elsevier, vol. 29(4), pages 309-320.
  • Handle: RePEc:eee:ininma:v:29:y:2009:i:4:p:309-320
    DOI: 10.1016/j.ijinfomgt.2009.03.004
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    Cited by:

    1. Samer Ali Al-shami & Salem Aldahmani & Massila Kamalrudin & Nabil Hasan Al-Kumaim & Abdullah Al Mamun & Mohammed Al-shami & Mustafa Musa Jaber, 2022. "A Model of Motivational and Technological Factors Influencing Massive Open Online Courses’ Continuous Intention to Use," Sustainability, MDPI, vol. 14(15), pages 1-23, July.
    2. Frishammar, Johan & Essén, Anna & Bergström, Frida & Ekman, Tilda, 2023. "Digital health platforms for the elderly? Key adoption and usage barriers and ways to address them," Technological Forecasting and Social Change, Elsevier, vol. 189(C).
    3. Lee, Kyootai & Yan, Aihua & Joshi, Kailash, 2011. "Understanding the dynamics of users’ belief in software application adoption," International Journal of Information Management, Elsevier, vol. 31(2), pages 160-170.
    4. Su-Chen(Cecilia) Lin & Mei-Chen Chuang & Chen-Yuan Huang & Chia-En Liu, 2023. "Nursing Staff’s Behavior Intention to Use Mobile Technology: An Exploratory Study Employing the UTAUT 2 Model," SAGE Open, , vol. 13(4), pages 21582440231, November.
    5. Jin, Xiao-Ling & Zhou, Zhongyun & Lee, Matthew K.O. & Cheung, Christy M.K., 2013. "Why users keep answering questions in online question answering communities: A theoretical and empirical investigation," International Journal of Information Management, Elsevier, vol. 33(1), pages 93-104.
    6. Lara Stocchi & Naser Pourazad & Nina Michaelidou & Arry Tanusondjaja & Paul Harrigan, 2022. "Marketing research on Mobile apps: past, present and future," Journal of the Academy of Marketing Science, Springer, vol. 50(2), pages 195-225, March.
    7. Kaba, Bangaly, 2018. "Modeling information and communication technology use continuance behavior: Are there differences between users on basis of their status?," International Journal of Information Management, Elsevier, vol. 38(1), pages 77-85.
    8. Md. Emam Hossain & Subarna Biswas, 2024. "Technology acceptance model for understanding consumer’s behavioral intention to use artificial intelligence based online shopping platforms in Bangladesh," SN Business & Economics, Springer, vol. 4(12), pages 1-61, December.
    9. Tala Althinayyan & Mohammed Alojail, 2024. "Enhancing User Experience and Sustainability in Open Banking Using PLS-SEM," Sustainability, MDPI, vol. 16(22), pages 1-20, November.
    10. Nurul-Ain Abdul-Halim & Ali Vafaei-Zadeh & Haniruzila Hanifah & Ai Ping Teoh & Khaled Nawaser, 2022. "Understanding the determinants of e-wallet continuance usage intention in Malaysia," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(5), pages 3413-3439, October.
    11. Colomo-Palacios, Ricardo & García-Crespo, Ángel & Soto-Acosta, Pedro & Ruano-Mayoral, Marcos & Jiménez-López, Diego, 2010. "A case analysis of semantic technologies for R&D intermediation information management," International Journal of Information Management, Elsevier, vol. 30(5), pages 465-469.
    12. Deng, Zhaohua & Lu, Yaobin & Wei, Kwok Kee & Zhang, Jinlong, 2010. "Understanding customer satisfaction and loyalty: An empirical study of mobile instant messages in China," International Journal of Information Management, Elsevier, vol. 30(4), pages 289-300.
    13. G, Sowmya & Chakraborty, Debarun & Polisetty, Aruna & Jain, Ravi Kumar, 2024. "Exploring the adoption patterns of matrimonial apps: An analysis of user gratifications," Journal of Retailing and Consumer Services, Elsevier, vol. 78(C).
    14. Yang, Xue & Liu, Na & Teo, Hock Hai, 2017. "How do users cope with trial restrictions? A field experiment on free trial software," International Journal of Information Management, Elsevier, vol. 37(4), pages 339-349.
    15. Heng Xu & Menglu Zhang & Jun Zeng & Huihui Hao & Hao-Chiang Koong Lin & Mengyun Xiao, 2022. "Use of Latent Dirichlet Allocation and Structural Equation Modeling in Determining the Factors for Continuance Intention of Knowledge Payment Platform," Sustainability, MDPI, vol. 14(15), pages 1-25, July.
    16. Wang, Yu-Yin & Wang, Yi-Shun & Lin, Tung-Ching, 2018. "Developing and validating a technology upgrade model," International Journal of Information Management, Elsevier, vol. 38(1), pages 7-26.
    17. Chiou-Hwa Chuang & Yi-Fan Li & Lu-Cheng Kuo & Ming-Chin Yang & Li-Ting Kao, 2021. "Factors Influencing the Use of Health Information Exchange by Physicians—Using the National Health Insurance PharmaCloud System in Taiwan," IJERPH, MDPI, vol. 18(16), pages 1-14, August.
    18. Oludapo, Samson & Carroll, Noel & Helfert, Markus, 2024. "Why do so many digital transformations fail? A bibliometric analysis and future research agenda," Journal of Business Research, Elsevier, vol. 174(C).
    19. David Kocsis & Triparna Vreede & Abdulrahman Alothaim, 2022. "Happy to Continue: Satisfaction, Commitment, and Persistence to Use Technology-Supported Collaborative Work Practices," Group Decision and Negotiation, Springer, vol. 31(6), pages 1235-1262, December.
    20. Abdalwali Lutfi, 2022. "Factors Influencing the Continuance Intention to Use Accounting Information System in Jordanian SMEs from the Perspectives of UTAUT: Top Management Support and Self-Efficacy as Predictor Factors," Economies, MDPI, vol. 10(4), pages 1-17, March.
    21. Ekramifard, Ali & Khademi, Navid & Chaiyasarn, Krisada & Zheng, Zuduo, 2024. "Disability-specific factors in paratransit system continuance: Implications for transportation policy and practice in low-income developing countries," Transport Policy, Elsevier, vol. 153(C), pages 173-189.
    22. Kang, Young Sik & Min, Jinyoung & Kim, Jeoungkun & Lee, Heeseok, 2013. "Roles of alternative and self-oriented perspectives in the context of the continued use of social network sites," International Journal of Information Management, Elsevier, vol. 33(3), pages 496-511.
    23. Adi Alsyouf & Awanis Ku Ishak & Abdalwali Lutfi & Fahad Nasser Alhazmi & Manaf Al-Okaily, 2022. "The Role of Personality and Top Management Support in Continuance Intention to Use Electronic Health Record Systems among Nurses," IJERPH, MDPI, vol. 19(17), pages 1-30, September.

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