Research On Comprehensive Evaluation And Prediction Of Enterprise Performance Dynamics Based On Hierarchical Incentives

Since the start of the large-scale spread of the new coronavirus,the global economy has been hit and disrupted like never before,and the survival of micro,small and medium-sized enterprises has faced major challenges,and their employees have also been stressed physically and mentally.In order to cope with the challenges posed by the economic downturn,companies need to motivate employees and improve their competitiveness to tide over this crisis.In order to stimulate the potential of employees and promote the better development of enterprises,this paper proposes a dynamic comprehensive evaluation method based on hierarchical incentive for the evaluation of enterprise employee performance,and a dynamic combination prediction model is proposed to predict the performance of enterprise employees,so as to adjust the enterprise development plan in time.Firstly,aiming at the problem that there are many decision-makers and difficult to standardize and unify decisionmaking opinions in the process of dynamic evaluation,a dynamic evaluation method that effectively assembles group opinions is proposed,which is based on the evaluation method with hierarchical incentive characteristics,further discusses the division method of hierarchy,and integrates the idea of multi-stage interactive group evaluation into it,so as to obtain a better,more detailed and satisfactory hierarchical division method for the vast majority of decision makers.Then,a process of gathering evaluation information that can avoid the influence of decision-makers’ preferences is discussed,so as to make the evaluation results more fair and reasonable.Secondly,aiming at the problem that a single forecasting model in time series forecasting has prediction defects and cannot change according to the period and data changes,this paper dynamically combines the autoregressive integrated moving average model(ARIMA)and the quadratic exponential smoothing method,and proposes a dynamic combined forecasting model based on ARIMA model and quadratic exponential smoothing method.The model first obtains the dynamic weights according to the prediction errors of the ARIMA model and the quadratic exponential smoothing method,and then constructs a dynamic combination prediction model.Then,according to the constructed model,a set of time series is predicted and analyzed,and the results show that the model prediction results have a high fit degree,which proves the effectiveness and applicability of the model.Finally,the time series is simulated and predicted,hoping that the prediction results can help the economic development of enterprises.The method proposed in this paper takes MJ enterprises as the research object,comprehensively evaluates employee performance,and gives "rewards and punishments" according to the evaluation results to achieve the role of improving employee enthusiasm,and then predicts employee performance so that enterprises can dynamically adjust strategic planning.This paper not only provides evaluation and prediction methods for MJ enterprise performance appraisal and forecasting,but also provides a new evaluation and prediction method for employee appraisal of similar small and medium-sized enterprises,so that it can promote the improvement of employee work quality and the growth of enterprise efficiency with a new idea,which has certain practical significance and promotion value.