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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. [ABSTRACT FROM AUTHOR]

Assessing project portfolio risk (PPR) is essential for organizations to grasp the overall risk levels of project portfolios (PPs) and realize PPR mitigation. However, current research is inadequate to effectively assess PPR, which brings challenges to managing PPR. In this context, the purpose of this study is to develop a PPR assessment model via an enhanced backpropagation neural network (BPNN). First, PPR assessment criteria considering project interdependencies are determined. Second, fuzzy logic is used to obtain original data for assessment criteria. Principal component analysis (PCA) is then employed to reduce the dimensionality of assessment criteria and derive the input and output of BPNN. Third, an improved genetic algorithm (IGA) is designed to optimize the initial weights and thresholds of BPNN. On this basis, the PCA-IGA-BPNN assessment model is constructed, followed by training and testing, possessing a test accuracy of 98.6%. Finally, comparison experiments are conducted from both internal and external perspectives. For internal comparison, the proposed model yields less mean absolute percentage error (MAPE), mean square error (MSE), and root mean square error (RMSE) than PCA-GA-BPNN, IGA-BPNN, PCA-BPNN and BPNN and offers the largest convergence speed (γ). As for external comparison, the presented model produces lower MAPE, MSE, and RMSE than Decision Tree (DT), Support Vector Machine (SVM), Random Forest (RF), and K-Nearest Neighbor (KNN) and has the largest coefficient of determination (R 2). Results indicate that the established model performs more satisfactorily in assessing PPR. This research enriches PPR assessment methods and provides managers with a useful tool to evaluate PPR. • A hybrid project portfolio risk assessment model based on an enhanced BPNN is established. • GA is improved by adaptively adjusting the probability of crossover and mutation operations. • PCA and improved GA are integrated with BPNN to enhance its evaluation performance. • The effectiveness and superiority of the proposed model are validated through experiments. [ABSTRACT FROM AUTHOR]

Due to dynamic changes in both internal and external environments, the risk evolution of the project portfolio (PP) becomes extremely complicated, thereby increasing the difficulties of effective risk response. In particular, the real-time influence of risk interactions on the evolution of project portfolio risk (PPR) often goes unnoticed. Meanwhile, risk contagiousness is completely ignored in risk response. To tackle this challenge, this study proposes a PPR evolution and response (PPRER) model by improving the Barrat–Barthelemy–Vespignani (BBV) model and by introducing the evolutionary dynamics method into the PPR response research. The feasibility and applicability of the proposed model are verified through a numerical illustration. Computational results demonstrate that the proposed model can simulate the evolution process of PPRs under the influence of their interactions and give a snapshot of the real-time interactive relationship between PPRs. Based on the obtained results, decision-makers can take effective risk responses by identifying critical strategy intrusion nodes at any time in the evolution process. [ABSTRACT FROM AUTHOR]

This paper considers a prefabricated construction supply chain (PCSC) consisting of a project contractor who shoulders the on-site assembly task and orders prefabs from a prefabricated factory. To mitigate the heavy double handling costs associated with early and late delivery of prefabs, the project contractor requires the right quantity and exact type of prefabs are carried to construction sites according to its assembly schedule. This is known as just-in-time purchasing (JITP). However, JITP may increase the pressure on the prefabricated factory to hold excessive inventory or to compress production time. For these reasons, the prefabricated factory may be reluctant to switch to JITP. To initiate the operation of JITP and establish a win-win outcome, side-payment contracts including a delivery-time dependent subsidy and two constant transfer terms are designed as coordinate schemes. Employing Stackelberg, we explore participants' optimal decisions. The results show that the JITP yields higher profit for PCSC, and the proposed contracts are capable of achieving a win-win coordination. In particular, the constant transfer cost term is relatively equitable to participants, while the constant cost-sharing transfer term outperforms the constant transfer cost term under a high double handling cost. Moreover, the prefabricated factory earns more profit when the double handling cost for early or late delivery is high. Some managerial implications are also obtained and help to strengthen cooperation among participants and promote the sustainable development of the PCSC. • The effect of just-in-time purchasing on double handling costs is investigated by mathematical model. • Information sharing between participants under just-in-time purchasing is considered and quantified. • The different contract combinations are employed to provide participants with various coordination schemes. • Just-in-time purchasing yields higher profits for the prefabricated construction supply chain. • Side-payment contracts can resolve profit conflicts between participants arising from just-in-time purchasing. [ABSTRACT FROM AUTHOR]

This paper considers a prefabricated construction supply chain (PCSC) consisting of a project contractor who shoulders the on-site assembly task and orders prefabs from a prefabricated factory. To mitigate the heavy double handling costs associated with early and late delivery of prefabs, the project contractor requires the right quantity and exact type of prefabs are carried to construction sites according to its assembly schedule. This is known as just-in-time purchasing (JITP). However, JITP may increase the pressure on the prefabricated factory to hold excessive inventory or to compress production time. For these reasons, the prefabricated factory may be reluctant to switch to JITP. To initiate the operation of JITP and establish a win-win outcome, side-payment contracts including a delivery-time dependent subsidy and two constant transfer terms are designed as coordinate schemes. Employing Stackelberg, we explore participants' optimal decisions. The results show that the JITP yields higher profit for PCSC, and the proposed contracts are capable of achieving a win-win coordination. In particular, the constant transfer cost term is relatively equitable to participants, while the constant cost-sharing transfer term outperforms the constant transfer cost term under a high double handling cost. Moreover, the prefabricated factory earns more profit when the double handling cost for early or late delivery is high. Some managerial implications are also obtained and help to strengthen cooperation among participants and promote the sustainable development of the PCSC. • The effect of just-in-time purchasing on double handling costs is investigated by mathematical model. • Information sharing between participants under just-in-time purchasing is considered and quantified. • The different contract combinations are employed to provide participants with various coordination schemes. • Just-in-time purchasing yields higher profits for the prefabricated construction supply chain. • Side-payment contracts can resolve profit conflicts between participants arising from just-in-time purchasing. [ABSTRACT FROM AUTHOR]