Adoption Models and Change Management
Código
400043
Unidade Orgânica
NOVA Information Management School
Créditos
7.5
Professor responsável
Tiago André Gonçalves Félix de Oliveira
Língua de ensino
Português. No caso de existirem alunos de Erasmus, as aulas serão leccionadas em Inglês
Objectivos
No final do curso os alunos deverão ser capazes de:
- Discutir criticamente as principais noções e conceitos relacionados com Modelos de Adoção e Gestão de Mudança;
- Iniciar investigação científica em modelos de adoção e Gestão de mudança.
Pré-requisitos
N/A
Conteúdo
1.Introdução - O conhecimento e a importância da colaboração no processo de tomada de decisão;
2.Introdução à inovação Adoção e Gestão da Mudança
3.Determinantes de inovação e adoção
4.Estádios de adoção (iniciação, adoção, uso e valor)
5.Por que gerir a mudança? (ROI de gestão de mudanças, mudar conceitos; características da alteração)
6.Avaliação (avaliação atributos organizacional; desafios e riscos)
7.Criação de uma estratégia de gestão da mudança (preparação da equipe de gestão da mudança; plano de comunicação; patrocinador roteiro)
8.Gestão do alinhamento de mudança com resultados de negócios (imunidade a mudar, a mudança de reforço)
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.
Kotter, J. P. (1996). Leading change. Harvard Business Press.
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
Aulas teóricas, complementadas por aplicações práticas, casos de estudo e simulações. Quatro trabalhos de grupo permitirá uma aplicação prática dos conceitos e técnicas estudadas na disciplina.
Método de avaliação
1st Period
Master students: Participation in the class (5%), one presentation per group of a scientific paper (15%), write the introduction, literature review, and conceptual model of a scientific paper per group (25%), change management simulation per group (15%), and exam (40%).
Ph.D. students: Presentation of a scientific paper as individual work (15%), scientific paper (8000 words maximum) as individual work (75%), participation and discussion (10%).
2nd Period
Master students: One presentation per group of a scientific paper (20%), write the introduction, literature review, and conceptual model of a scientific paper per group (30%), and exam (50%).
Ph.D. students: Scientific paper (8000 words maximum) as individual work (100%).
Scientific paper presentation – We provide a set of scientific papers and each group of students chooses one paper to analyze and make a presentation (12 minutes + 12 discussion). The aim of this work is to develop research skills to prepare students to start research. Each group should submit their presentation in Moodle until 11:59pm of 16th of October.
Write the introduction, literature review, and conceptual model of a scientific paper –The introduction, literature review, and conceptual model of a scientific paper per group (4000 words maximum includes references), each group should submit their presentation in Moodle until 11:59 pm of 4th of November.
Change management simulation – participation is mandatory at least at 2 of the 3 lab sessions held on the 21st, 28th of November and 5th of December
Exam – The pass mark for the exam is 8.