Journal of Economics and Management Sciences

China's Economic Growth from a Comprehensive Analysis Perspective: A Synergistic Application of GRA, PCA, and GRU Models

2025-01-06T15:28:22+08:00

In the context of globalization and economic integration, accurately predicting China's quarterly GDP growth rate is crucial for macroeconomic decision-making. This paper proposes a comprehensive forecasting framework that combines Grey Relational Analysis (GRA), Principal Component Analysis (PCA), and a Gated Recurrent Unit (GRU)-based neural network model to improve prediction accuracy. The study first identifies economic indicators highly correlated with GDP growth through GRA. It then extracts key variability from multidimensional data using PCA, constructing a "China Macroeconomic Vitality Index." Simultaneously, a GRU model, combined with error correction and Bayesian optimization techniques, significantly enhances prediction accuracy. The results demonstrate that the optimized GRU model exhibits significant reductions in evaluation metrics such as SMAPE, MAE, and MSE, indicating good forecasting performance. Additionally, SHAP value analysis reveals the specific impact of each economic indicator on GDP growth, providing a basis for macroeconomic decisions.

Analysis of the Influencing Factors of Digital Transformation on Enterprise Innovation and Development

2025-01-15T13:44:16+08:00

Based on the data of Chinese listed companies from 2007 to 2022, this article deeply analyzes the catalytic effect of digital transformation on enterprise innovation and development. Research has found that digital transformation significantly promotes the improvement of enterprise innovation capabilities, and exhibits heterogeneity among different types of enterprises. After sufficient robustness testing, this conclusion still holds true; When financing constraints are high, the promotion effect of digital transformation on enterprise innovation is stronger, that is, digital transformation can effectively alleviate the financing constraints of enterprises and empower enterprise innovation; The level of human capital can positively regulate the promoting effect of digital transformation on the high-quality development of enterprises. This study not only enriches the theoretical framework of the relationship between digital transformation and enterprise innovation development, but also provides useful references and inspirations for enterprises to implement digital transformation and enhance innovation capabilities.

Research on the Efficiency of Human-Machine Collaborative Delivery Management for Takeout Riders Under Algorithmic Control

2025-01-17T21:35:23+08:00

In the current digital economy era, the takeout industry is expanding, which makes human-machine collaborative delivery management between takeout riders and intelligent algorithms increasingly important. Based on this, this paper takes takeout riders as Decision Making Units to study the management efficiency of the delivery algorithm from the perspective of input and output. Firstly, a comprehensive evaluation index system for input and output is constructed. Secondly, the entropy method is used to obtain the weights of the delivery input indicators at all levels and the comprehensive input index. Then, the output-oriented DEA-BCC model is established by combining the comprehensive input index and several delivery output indicators. Finally, the efficiency of the delivery algorithm in managing takeout riders is evaluated using the results calculated from the DEA-BCC model. Additionally, this paper also proposes suggestions for personalized human-machine collaborative delivery management in terms of quantity, quality and safety based on the slack variables of the output indicators.