Analysis of the Success Factors of Shenzhen as a Location
Keywords:
Shenzhen, Location Success Factors, PEST Analysis, Economic Development, Technological InnovationAbstract
This paper takes Shenzhen, a city that has achieved rapid development from a small fishing village to an international metropolis, as the research object, aiming to explore the core factors driving its economic development and location success. First, the paper sorts out the theoretical basis of location success factors, including their definition, effective operation process, and core objectives. It then adopts the PEST analysis model to systematically elaborate on the influence of economic, political, social, and technological factors on urban development, with a focus on the decisive role of economic factors. On this basis, the paper conducts an in-depth empirical analysis of Shenzhen, exploring its performance as an economic-oriented city in terms of employment, corporate agglomeration, GDP, and technological innovation. It further dissects Shenzhen's key location success factors from six economic dimensions: investment and capital accumulation, industrial structure optimization, employment and labor market construction, consumer demand growth, opening-up to foreign trade, and technological innovation and application. Finally, the paper summarizes the comprehensive driving role of multi-dimensional factors in Shenzhen's development, points out the research limitations caused by time constraints on data and literature, and proposes future research directions related to opportunities and challenges in Shenzhen's sustainable development.References
1. J. Cui, Z. Shen, C. Mai, C. Lin, and S. Wang, "Spatial distribution and location determinants of high-tech firms in Shenzhen, a Chinese national innovative city," Land, vol. 13, no. 9, p. 1355, 2024. doi: 10.3390/land13091355
2. Huang and S. Rohayah Sheikh Dawood, "Geography of knowledge interactions and innovation in Shenzhen," Cogent Business & Management, vol. 11, no. 1, p. 2327469, 2024. doi: 10.1080/23311975.2024.2327469
3. F. Amjady, "Short-term hourly load forecasting using time-series modeling with peak load estimation capability," IEEE Transactions on Power Systems, vol. 16, no. 3, pp. 498-505, 2002. doi: 10.1109/59.932287
4. C. Liu, T. Li, T. Zhuang, Y. Zheng, H. Wu, and J. Tang, "Determining the spatial distribution characteristics of urban regeneration projects in China on the city scale: The case of Shenzhen," Land, vol. 11, no. 8, p. 1210, 2022. doi: 10.3390/land11081210
5. Y. Chen, L. Lai, L. Tao, and Y. Lin, "Spatial variation of industrial land conversion and its influential factors in urban redevelopment in China: case study of Shenzhen, China," Journal of Urban Planning and Development, vol. 150, no. 2, p. 05024005, 2024. doi: 10.1061/jupddm.upeng-4636
6. W. Taylor and R. Buizza, "Neural network load forecasting with weather ensemble predictions," IEEE Transactions on Power Systems, vol. 17, no. 3, pp. 626-632, 2002.
7. S. Hippert, C. E. Pedreira, and R. C. Souza, "Neural networks for short-term load forecasting: A review and evaluation," IEEE Transactions on Power Systems, vol. 16, no. 1, pp. 44-55, 2002.
8. H. Hahn, S. Meyer-Nieberg, and S. Pickl, "Electric load forecasting methods: Tools for decision making," European Journal of Operational Research, vol. 199, no. 3, pp. 902-907, 2009. doi: 10.1016/j.ejor.2009.01.062
9. W. Hong, "Short term electric load forecasting," North Carolina State University, 2010.
10. S. Fan and R. J. Hyndman, "Short-term load forecasting based on a semi-parametric additive model," IEEE Transactions on Power Systems, vol. 27, no. 1, pp. 134-141, 2011. doi: 10.1109/tpwrs.2011.2162082
11. J. Chen and M. W. Chang, "Load forecasting using support vector machines: A study on EUNITE competition 2001," IEEE Transactions on Power Systems, vol. 19, no. 4, pp. 1821-1830, 2004.
12. M. Al-Hamadi and S. A. Soliman, "Short-term electric load forecasting based on Kalman filtering algorithm with moving window weather and load model," Electric Power Systems Research, vol. 68, no. 1, pp. 47-59, 2004.

