Adoption Models

Objectives

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.
-Understanding the IT adoption process.

General characterization

Code

400095

Credits

4.0

Responsible teacher

Tiago André Gonçalves Félix de Oliveira

Hours

Weekly - Available soon

Total - Available soon

Teaching language

Portuguese. If there are Erasmus students, classes will be taught in English

Prerequisites

N/A

Bibliography

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.

Teaching method

Theoretical classes complemented with practical applications. Two team
projects will provide a practical application of the concepts and techniques studied in the course.

Evaluation method

1st Period

Participation in the class (10%), presentation per group of a scientific paper with individual discussion (45%), presentation per group  of a new adoption model (introduction, literature review, and conceptual model) (45%).

 

2nd Period

Presentation per group of a scientific paper with individual discussion (50%), presentation per group  of a new adoption model (introduction, literature review, and conceptual model) (50%).

Subject matter

1.Introduction - Knowledge and the importance of Collaboration in the decision making process
3.Introduction to the Adoption Models and Change Management
4.Adoption innovation drivers
5.Adoption stages (initiation, adoption, use, and value)