Creación de un Framework que nos Ayude a Seleccionar el Equipo Adecuado para Proyectos Remotos
Resumo
El objetivo principal de este trabajo es crear un Framework que ayude a especificar las características de un proyecto remoto y ayude en la selección de los equipos de trabajo más apropiados teniendo en cuenta las características de los miembros del equipo. Este Framework, además, será capaz de predecir cuáles serán los principales desafíos que va a experimentar el equipo de trabajo en función de las características del proyecto.
Palavras-chave:
Trabajo remoto, GSD, Motivación, Estrés, Rendimiento
Referências
Akbar, M. A., Khan, A. A., Khan, A. W., & Mahmood, S. (2020). Requirement change management challenges in GSD: An analytical hierarchy process approach. Journal of Software: Evolution and Process, 32(7), e2246.
Ebert, C., Vizcaíno, A., García, F. O., & Albanchez, J. S. (2023). Measure and Improve Software Productivity. IEEE Software, 41(1), 35-44.
Fink, G. (2016). Stress, definitions, mechanisms, and effects outlined: Lessons from anxiety. In Stress: Concepts, cognition, emotion, and behavior (pp. 3-11). Academic Press.
Manjavacas, A., Vizcaíno, A., Ruiz, F., & Piattini, M. (2020). Global software development governance: Challenges and solutions. Journal of Software: Evolution and Process, 32(10), e2266.
Moe, N. B. & Šmite, D. (2007), Understanding Lacking Trust in Global Software Teams: A Multi-case Study, in Product-Focused Software Process Improvement, Berlin, Heidelberg, pp. 20–34.
Noll, J., Razzak, M. A., & Beecham, S. (2017, June). Motivation and autonomy in global software development: an empirical study. In Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering (pp. 394-399).
Roldán, J. L., & Sánchez-Franco, M. J. (2012). Variance-based structural equation modeling: Guidelines for using partial least squares in information systems research. In Research methodologies, innovations and philosophies in software systems engineering and information systems (pp. 193-221). IGI global.
Russo, D., Hanel, P. H., Altnickel, S., & van Berkel, N. (2021). Predictors of well-being and productivity among software professionals during the COVID-19 pandemic–a longitudinal study. Empirical Software Engineering, 26(4), 62.
Šmite, D., Moe, N. B., Klotins, E., &Gonzalez-Huerta, J. (2023a). From forced working-from-home to voluntary working-from-anywhere: two revolutions in telework. Journal of Systems and Software, 195, 111509.
Šmite, D., Moe, N. B., Hildrum, J., & Gonzalez-Huerta, J. (2023b). Work-from-home is here to stay: Call for flexibility in post-pandemic work policies.. Journal of Systems and Software, 195, 111552.
Suárez, J., & Vizcaíno, A. (2023). Stress, motivation, and performance in global software engineering. Journal of Software: Evolution and Process, e2600.
Ebert, C., Vizcaíno, A., García, F. O., & Albanchez, J. S. (2023). Measure and Improve Software Productivity. IEEE Software, 41(1), 35-44.
Fink, G. (2016). Stress, definitions, mechanisms, and effects outlined: Lessons from anxiety. In Stress: Concepts, cognition, emotion, and behavior (pp. 3-11). Academic Press.
Manjavacas, A., Vizcaíno, A., Ruiz, F., & Piattini, M. (2020). Global software development governance: Challenges and solutions. Journal of Software: Evolution and Process, 32(10), e2266.
Moe, N. B. & Šmite, D. (2007), Understanding Lacking Trust in Global Software Teams: A Multi-case Study, in Product-Focused Software Process Improvement, Berlin, Heidelberg, pp. 20–34.
Noll, J., Razzak, M. A., & Beecham, S. (2017, June). Motivation and autonomy in global software development: an empirical study. In Proceedings of the 21st International Conference on Evaluation and Assessment in Software Engineering (pp. 394-399).
Roldán, J. L., & Sánchez-Franco, M. J. (2012). Variance-based structural equation modeling: Guidelines for using partial least squares in information systems research. In Research methodologies, innovations and philosophies in software systems engineering and information systems (pp. 193-221). IGI global.
Russo, D., Hanel, P. H., Altnickel, S., & van Berkel, N. (2021). Predictors of well-being and productivity among software professionals during the COVID-19 pandemic–a longitudinal study. Empirical Software Engineering, 26(4), 62.
Šmite, D., Moe, N. B., Klotins, E., &Gonzalez-Huerta, J. (2023a). From forced working-from-home to voluntary working-from-anywhere: two revolutions in telework. Journal of Systems and Software, 195, 111509.
Šmite, D., Moe, N. B., Hildrum, J., & Gonzalez-Huerta, J. (2023b). Work-from-home is here to stay: Call for flexibility in post-pandemic work policies.. Journal of Systems and Software, 195, 111552.
Suárez, J., & Vizcaíno, A. (2023). Stress, motivation, and performance in global software engineering. Journal of Software: Evolution and Process, e2600.
Publicado
06/05/2024
Como Citar
ALBANCHEZ, Julio Suárez.
Creación de un Framework que nos Ayude a Seleccionar el Equipo Adecuado para Proyectos Remotos. In: CONGRESSO IBERO-AMERICANO EM ENGENHARIA DE SOFTWARE (CIBSE), 27. , 2024, Curitiba/PR.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 335-339.
DOI: https://doi.org/10.5753/cibse.2024.28458.
