Service provider portfolio selection for project management using a BP neural network

Libiao Bai (), Kanyin Zheng (), Zhiguo Wang () and Jiale Liu ()
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Libiao Bai: Chang’an University
Kanyin Zheng: Chang’an University
Zhiguo Wang: Chang’an University
Jiale Liu: Chang’an University

Annals of Operations Research, 2022, vol. 308, issue 1, No 3, 62 pages

Abstract: Abstract Service provider portfolio selection (SPPS) can be a major challenge for organizations to achieve project success. Hence, organizations need to decide on which service provider portfolio (SPP) is appropriate for project management (PM). However, there has been limited research on how to select a SPP in PM. To address this research gap, we establish a novel model for SPPS based on a BP neural network integrated with entropy-AHP from the perspective of the comprehensive economic benefit. This model employs a BP neural network due to its robustness and memory and nonlinear mapping abilities. Furthermore, we implement the proposed model for a construction project to verify the effectiveness. Our results indicate that the model performs well with a prediction accuracy of 97%. Moreover, the model is confirmed to be robust as it still achieves high prediction accuracy when the input data are disturbed randomly.

Keywords: Service provider portfolio selection; Project management; Comprehensive economic benefit; BP neural network (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s10479-020-03878-0

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