Human resources are the core resources of an enterprise, and the demand forecasting plays a vital role in the allocation and optimization of human resources. Starting from the basic concepts of human resource forecasting, this paper employs the backpropagation neural network (BPNN) and radial basis function neural network (RBFNN) to analyze human resource needs and determine the key elements of the company’s human resource allocation through predictive models. With historical data as reference, the forecast value of current human resource demand is obtained through the two types of neural networks. Based on the prediction results, the company managers can carry out targeted human resource planning and allocation to improve the efficiency of enterprise operations. In the experiment, the actual human resource data of a certain company are used as the experimental basic samples to train and test the two types of machine learning tools. The experimental results show that the method proposed in this paper can effectively predict the number of personnel required and can support the planning and allocation of human resources.

As an important tool for supervisors to intervene subordinates’ work and influence their performance, supervisor feedback has gradually become a new academic research hotspot. In this study, we build and verify a theoretical model to explore the different effects of supervisor positive and negative feedback on subordinate in-role and extra-role performance, and the moderating role of regulatory focus in these relationships. With data from pairing samples of 403 Chinese employees and their direct supervisors, the results indicate that supervisor positive feedback is positively related to subordinate in-role and extra-role performance. Supervisor negative feedback is positively related to subordinate in-role performance and negatively related to subordinate extra-role performance. Regulatory focus of subordinate can moderate the influence of supervisor positive feedback on subordinate in-role and extra-role performance, but it cannot moderate the influence of supervisor negative feedback on subordinate in-role and extra-role performance. That means when subordinates have promotion focus, the influence of supervisor positive feedback on their in-role performance and extra-role performance was stronger than those with prevention focus. These results further enrich the research on the relationship between supervisor feedback and subordinate performance, especially the different effects of positive and negative feedback from supervisor on subordinate with different regulatory focus. All conclusions from the analyses above not only further verify and develop some previous points on supervisor feedback and subordinate performance, but also derive certain management implications for promoting subordinate in-role and extra-role performance from the perspective of supervisor positive and negative feedback.

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