Abstract
Organizations interact with their surroundings and with other organizations, and these interactions are critical for learning and evolution. To overcome the problems that they face during their existence, organizations must certainly adopt survival strategies, both individually and in groups. The aim of this study is to evaluate the effect of a set of prognostic factors (organizational, size, collaboration strategies, etc.) on the survival of organizational networks. Statistical methods for time-to-event data were used to analyze the data. We have used the Kaplan-Meier product-limit method to compute and plot estimates of survival, while hypothesis tests were used to compare survival times across several groups. In our study, we were confronted with one exploratory categorical variable, the strategy of the network, with a large number of levels. We have compared the corresponding survival curves through hypothesis tests, and we conducted a study that established three groups of strategies with the same risk or survival probability. Regression models were used to study the effect of continuous predictors and to test multiple predictors. Since violations of the proportional hazards were found for several predictors, accelerated failure time models were used to study the effect of explanatory variables on network survival.
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Luís Meira-Machado and Paula Lopes were involved in the analysis of the survival data whereas Pedro Campos was mainly involved in the data preparation and brought different expertise to the project in the particular area of application. Gustavo acted as corresponding author and will take primary responsibility for presenting the work and communicating with the journal and the reviewers. He also participating in the last revision and rewriting of the paper.
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Lopes, P., Campos, P., Meira-Machado, L., Soutinho, G. (2023). Survival Analysis of Organizational Network – An Exploratory Study. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2023 Workshops. ICCSA 2023. Lecture Notes in Computer Science, vol 14112. Springer, Cham. https://doi.org/10.1007/978-3-031-37129-5_10
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DOI: https://doi.org/10.1007/978-3-031-37129-5_10
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