Adoption Models
Objetivos
At the end of the course students should be able to:
- Critically discuss the key notions and concepts related to Adoption Models.
- Initiate scientific research related to Adoption Models.
- IT Adoption encompasses all activities aimed at helping an organization successfully accept and adopt new technologies and new ways to serve its customers.
Caracterização geral
Código
400095
Créditos
4.0
Professor responsável
Tiago André Gonçalves Félix de Oliveira
Horas
Semanais - A disponibilizar brevemente
Totais - A disponibilizar brevemente
Idioma de ensino
Português. No caso de existirem alunos de Erasmus, as aulas serão leccionadas em Inglês
Pré-requisitos
N/A
Bibliografia
Aparicio A., Oliveira T., Bacao F., & Painho M. (2018) Gamification: A key determinants of massive open
online course (MOOC) success. Information & Management .
Baptista, G. & Oliveira, T. (2017). Why so serious? Gamification impact in the acceptance of mobile banking
services. Internet Research , 27(1), 118-139.
Cameron, E., & Green, M. (2015). Making sense of change management: a complete guide to the models,
tools and techniques of organizational change . Kogan Page Publishers.
Chipeva, P., Cruz-Jesus, F. Oliveira T. & Irani Zahir (2018) Digital divide at individual level: Evidence for
Eastern and Western European countries. Government Information Quarterly.
Corte-Real, N., Oliveira, T. & Ruivo P. (2017). Assessing Business Value of Big Data Analytics in European
Firms. Journal of Business Research , 70, 379-390.
Gonçalves, G., Oliveira, T., and Cruz-Jesus, F. (2018) Understanding individual-digital divide: Evidence of an
African Country. Computers in Human Behavior.
Martins, C, Oliveira, T. & Popovi?, A. (2014) Understanding the Internet banking adoption: An unified theory
of acceptance and use of technology and perceived risk application, International Journal of Information
Management , 34(1), 1-13.
Naranjo M., Oliveira T., & Casteleyn S. (2018) Citizens? intention to use and recommend e-participation:
Drawing upon UTAUT and citizen empowerment. Information Technology & People.
Nascimento, B., Oliveira, T., & Tam, C. (2018). Wearable technology: What explains continuance intention in
smartwatches?. Journal of Retailing and Consumer Services , 43, 157-169.
Puklavec B., Popovic A. & Oliveira T. (2018). Justifying Business Intelligence Systems Adoption in SMEs:
Impact of Systems Use on Firm Performance. Industrial Management & Data Systems.
Puklavec, B., Oliveira, T., & Popovi?, A. (2018). Understanding the determinants of business intelligence
system adoption stages: an empirical study of SMEs. Industrial Management & Data Systems , 118(1), 1-28.
Oliveira, T., Thomas, M., Baptista, G. and Campos, F., (2016) Mobile payment: Understanding the
determinants of customer adoption and intention to recommend the technology. Computers in Human
Behavior , 61, pp.404-414.
Oliveira, T., Thomas M. & Espadanal, M. (2014) Assessing the determinants of cloud computing adoption: An
analysis of the manufacturing and services sectors, Information & Management , 51, 497-510.
Oliveira, T. & Dhillon, G. (2015). From Adoption to Routinization of B2B e-Commerce: Understanding
Patterns across Europe, Journal of Global Information Management , 23(1), 24-43.
Oliveira, T., Faria, M., Thomas, M. A., & Popovi?, A. (2014). Extending the understanding of mobile banking
adoption: When UTAUT meets TTF and ITM, International Journal of Information Management , 34(5),
689-703.
Oliveira, T. & M. F. Martins (2010) "Understanding e-business adoption across industries in European
countries," Industrial Management & Data System (110) 9, pp. 1337-1354.
Rogers, E. M. (2010). Diffusion of innovations. Simon and Schuster.
Ruivo, P., Oliveira, T., & Neto, M. (2015). Using resource-based view theory to assess the value of ERP
commercial-packages in SMEs. Computers in Industry , 73, 105-116.
Tam, C. and Oliveira, T., 2016. Understanding the impact of m-banking on individual performance: DeLone &
McLean and TTF perspective. Computers in Human Behavior , 61, pp.233-244.
Tam, C., & Oliveira, T. (2017). Understanding mobile banking individual performance: The DeLone & McLean
model and the moderating effects of individual culture. Internet Research , 27(3), 538-562.
Tam C. & Oliveira T. (2018). Does culture influence m-banking use and individual performance? Information
& Management . In press.
Tam, C., Santos, D. & Oliveira, T., (2018). Exploring the influential factors of continuance intention to use
mobile Apps: Extending the expectation confirmation model. Information Systems Frontiers , pp.1-15.
Thomas, M., Costa, D. & Oliveira, T. (2016). Assessing the role of IT-enabled Process Virtualization on
Green IT adoption. Information Systems Frontiers , 18 (4) 693-710.
Tomás, S., Thomas, M., & Oliveira, T. (2017). Evaluating the impact of virtualization characteristics on SaaS
adoption. Enterprise Information Systems , 1-20.
Zhu, K., K. Kraemer, and S. Xu (2003) "Electronic business adoption by European firms: a cross-country
assessment of the facilitators and inhibitors," European Journal of Information Systems (12) 4, pp. 251-268.
Zhu, K. and K. L. Kraemer (2005) "Post-adoption variations in usage and value of e-business by
organizations: Cross-country evidence from the retail industry," Information Systems Research (16) 1, pp.
61-84.
Zhu, K., Kraemer, K. L., & Xu, S. (2006). The process of innovation assimilation by firms in different
countries: a technology diffusion perspective on e-business. Management Science , 52(10), 1557-1576.
Método de ensino
Theoretical classes complemented with practical applications. Two team
projects will provide a practical application of the concepts and techniques studied in the course.
Método de avaliação
1st Period
Master students: Participation in the class (10%), one presentation per group of a scientific paper (40%), write the introduction, literature review, and conceptual model of a scientific paper per group (50%).
2nd Period
Master students: One presentation per group of a scientific paper (45%), write the introduction, and literature review, and conceptual model of a scientific paper per group (55%).
Conteúdo
1. Introduction to the Adoption Models
2. Adoption models at individual level
3. Adoption models at firm level
4. Adoption stages (initiation, adoption, use, and value)
5. Development of new conceptual model
Cursos
Cursos onde a unidade curricular é leccionada: