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Purpose: The purpose of this paper is to propose a subcontractor selection model to fully consider the impact of construction enterprise demands on subcontractor selection. The objectives are to understand the translating process of specific enterprise demands to the evaluating criteria and the weight calculation process. Design/methodology/approach: A three-stage model of subcontractor selection was designed based on quality function deployment (QFD), analytic hierarchy process (AHP) and improved grey correlation analysis (IGCA). In the proposed model, specific enterprise demands are translated by the QFD method, and the weights of the criteria are determined by the IGCA. The AHP is used to quantify the exporters' experience and construct the judgment matrix, which is used as inputting of the grey correlation analysis. Findings: The proposed model provides a feasible process for subcontractor selection by fully considering the actual requirements of the project. By combining the company requirements and project requirement to put forward the requirements of the target subcontractor, the selection process ensures that the selected subcontractor and the project have a higher "fit" Originality/value: Few researches on construction subcontractor selection have taken into account the "voice" of the company's stakeholders. Therefore, this paper designs a three-stage construction subcontractor selection model by introducing QFD to achieve the transmission of "voice" in the subcontractor selection process, so as to take full consideration of the project objectives and the needs of the company's stakeholders. Meanwhile, in order to decrease the subjective of weight calculation, this paper designs an AHP-IGCA allocation method to determine the weight of relevant indicators. By integrating the proposed weight calculation method and QFD method, the subcontractor selection results become more reasonable and objective. [ABSTRACT FROM AUTHOR]

Project schedule management is an important aspect of project management. Earned value management (EVM) and its extension methods are widely adopted in project schedule management in various previous studies, however, most of these studies adopted schedule performance indicators based on definiteness condition and historical data, which ignored the impact of uncertainty and dynamics. So the decision risk in schedule management has been increased dramatically. Therefore, this paper proposed an active construction dynamic schedule management model based on fuzzy earned value management (F-EVM) and BP neural network (BP-NN). Firstly, the fuzzy theory was introduced into EVM to evaluate the schedule performance when the project finish schedule cannot be deterministic expression. Then, the main resource planning was functioned as input variables to predict the schedule in advance through BP-NN. Finally, the future action plans was adjusted based on the results to achieve active control of the project schedule. The case results indicated that the introduction of F-EVM effectively reduced influence of subjective estimation on uncertainty in the data measurement process. And the proposed dynamic schedule management model gave a 32.06% better mean absolute percentage error (MAPE) than the existing methods for estimated project duration. Hence, the proposed model provided a more accurate estimation of the project duration and considered the uncertainty and dynamics of the construction project, thereby achieving more effective management of project schedule. [ABSTRACT FROM AUTHOR]