Project performance prediction model linking agility and flexibility demands to project type

Abstract

The main purpose of this work is the development of a performance prediction model of projects, considering the influence of the leadership style and organizational factors on the agility and flexibility of the organization. The motivation of this work is the absence in the literature of a model to establish the relationship among leadership and agility factors, by means of the integration of prediction and sensitivity analysis capacities. The originality of this work lies on the presentation of a general model integrating both capacities, dedicated to the analysis of different kind of projects. The first part of the study deals with a literature review regarding the components of leadership, organizational structure, agility, flexibility and organizational factors and the intrinsic relationship among them. This information is the basis of the framework of this study that serves for the construction of the model. Artificial intelligence (AI) techniques and statistical tools are used for modeling purposes. From the model application, it is possible to identify under which conditions of leadership style and organizational factors there are the highest chances of high project performances. The main results are the characterization of agility and flexibility demands for each type of project, the understanding of how leadership affects agility and flexibility, and the impacts on the project performance.

Self‐organizing maps and Bayesian networks in organizational modelling: A case study in innovation projects management

“…Analysis of different scenarios considering the average values of the BN variables (De Oliveira et al, 2021) [Colour figure can be viewed at wileyonlinelibrary.com]…”

“…In this study, validity also concerns to the role‐played in the team during the period examined, and the degree of perception of the project performance. Major changes on these profiles can affect the results (De Oliveira et al, 2021).…”

“…In this study, validity also concerns to the role-played in the team during the period examined, and the degree of perception of the project performance. Major changes on these profiles can affect the results (De Oliveira et al, 2021). The use of causal models (BN) provides more traceable and reproducible predictions, showing explanatory and predictive capability, thus enabling not only to predict the probability of a certain human behaviour, but also to explain why these behaviours happen (Groth & Mosleh, 2012).…”

“…To the extent that the overlap of activities will be high (purple line), the agility required for maintenance of high project performance is maintained by the increase in the contribution of continuous improvement, compensating for the reduction of the values of people's flexibility, continuous delivery, team communication and maturity. The continuous improvement contributes to agility via learning, the review of the processes (improvements) and the implementation of best practices, leading to the organization growth (De Oliveira et al, 2021). was that these representations resulted in three groupings (clusters), from the three different levels of the variable project performance: H, High; M, Mid (Moderate); and L, Low.…”

“…According to Preiser (2019), theories of complexity inspire new ways of doing science and presenting tangible implications for the way how practical solutions are implemented. Although the understanding of an observed phenomenon is fundamental to any scientific effort, managing such phenomenon has great importance too (De Oliveira et al, 2021). This management implies in a model construction.…”