Research and Development Investment Combination Forecasting Model of High-Tech Enterprises Based on Uncertain Information

Abstract

The high demand of the competitive market for innovation has brought the increase of research and development (R&D) investment. High-tech enterprises can reasonably control R&D cost and effectively manage R&D activities by accurately predicting R&D investment. Given the characteristics that high-tech enterprises have high uncertainty and frequently changing information in R&D investment, this paper uses the grey metabolic GM (1, 1) model and the exponential smoothing method in time series to establish a single prediction model of R&D investment in high-tech enterprises. With the analysis of the advantages and disadvantages of each single model, a combined forecast model of R&D investment in high-tech enterprises is thus established. The model was applied to the forecast of R&D investment of a high-tech enterprise in China from 2019 to 2023, and the results verified the higher accuracy and practicability of this model. The establishment of this model can provide effective support for high-tech enterprises in R&D cost management.