| Literature DB >> 34950081 |
Jun Li1, Wanrong Li2, Yongchuan Shi3.
Abstract
Business gang refers to the enterprise cluster formed by geographical relationship, which has always been the focus of research on entrepreneurship and regional economic development. The research of new institutional economics shows that culture, as an informal system, will change the social psychology, thinking mode and behavior of economic individuals, and provide a good environment for the growth of start-ups, thus affecting economic activities and economic development. Taking the five modern business gangs in China as the research subject, this paper uses the comparative method to analyze the regional cultural differences of the five modern business gangs, as well as the differences of the entrepreneurs' psychological characteristics and startup behaviors. Through the analysis of the economic data of the provinces where the modern business gangs are located, this paper summarizes the differences of economic development in different regions. It is concluded that regional culture has a significant impact on the development of modern business gangs and regional economy. It is necessary to give full play to the advantages of regional culture and promote the high-quality development of modern business gangs and regional economy.Entities:
Keywords: modern business gangs; new institutional economics; psychological characteristics; regional cultural differences; regional economies; startup behaviors
Year: 2021 PMID: 34950081 PMCID: PMC8688531 DOI: 10.3389/fpsyg.2021.732377
Source DB: PubMed Journal: Front Psychol ISSN: 1664-1078
FIGURE 1Hypothetical model for the impact of regional cultural differences on modern business gangs.
General information of the provinces where the five modern business gangs are located (By the end of 2019).
| Shandong | Jiangsu | Zhejiang | Fujian | Guangdong | |
| Area | The total land area of Shandong is 15,712,600 square kilometers. | The total area of Jiangsu is 107,200 square kilometers. | The total area of Zhejiang is 105,500 square meters. | The total land area of Fujian is 121,400 square kilometers. | The total area of Guangdong is 179,700 square kilometers. |
| Permanent resident population | 10,702,100 million people | 80,700,000 million people | 58,500,000 million people | 39,730,000 million people | 115,210,000 million people |
| Education situation | There were 34 graduate schools with 115,000 students, 146 colleges and universities with 2,184,000 students, 391 secondary vocational schools (excluding technical schools) with 730,000 students, and 181 technical schools with 355,000 students. | There were 215,000 graduate students, 142 colleges and universities with 1,874,000 students, and 622,000 students in secondary vocational schools (excluding technical schools). | There were 109 colleges and universities (including independent colleges), and 245 secondary vocational schools (excluding technical schools) with 542,000 students. | There were 58,700 graduate students, 89 colleges and universities with 861,200 students, and 334,800 students in secondary vocational schools (excluding technical schools). | There were 147 colleges and universities in Guangdong. The number of students in graduate education is 154700, and the number of ordinary college students is 240200. |
| Natural resources | Shandong has abundant mineral resources, taking an important place in China. | Jiangsu is rich in non-ferrous metals, building materials, gypsum-salts, and special non-metallic minerals. | Zhejiang has a wide variety of minerals with alumite reserves ranking first in the world (60%), fluorite reserves second in China. | As one of the important mineralization areas in the Pacific Rim mineralization zone, Fujian is rich in mineral resources. | Guangdong is rich in water resources and has a wide variety of plants and animals. Guangdong is home to rare and non-ferrous metals. |
China Statistical Yearbook.
GDP in the five provinces (2010–2019).
| Year | Gross domestic product (100 million yuan) | ||||
| Shandong | Jiangsu | Zhejiang | Fujian | Guangdong | |
| 2019 | 71067.53 | 99631.52 | 62351.74 | 42395.00 | 107671.07 |
| 2018 | 76469.67 | 92595.40 | 56197.15 | 35804.04 | 97277.77 |
| 2017 | 72634.15 | 85869.76 | 51768.26 | 32182.09 | 89705.23 |
| 2016 | 68024.49 | 77388.28 | 47251.36 | 28810.58 | 80854.91 |
| 2015 | 63002.33 | 70116.38 | 42886.49 | 25979.82 | 72812.55 |
| 2014 | 59426.59 | 65088.32 | 40173.03 | 24055.76 | 67809.85 |
| 2013 | 55230.32 | 59753.37 | 37756.58 | 21868.49 | 62472.79 |
| 2012 | 50013.24 | 54058.22 | 34665.33 | 19701.78 | 57067.92 |
| 2011 | 45361.85 | 49110.27 | 32318.85 | 17560.18 | 53210.28 |
| 2010 | 39169.92 | 41425.48 | 27722.31 | 14737.12 | 46013.06 |
China Statistical Yearbook.
FIGURE 2Trends of GDP in the five provinces (2010−2019).
FIGURE 3Proportion of legal entity by industry in the five provinces.
FIGURE 4GDP by industry in the five provinces.
Added value by industry in the five provinces in 2015–2019.
| Year | Industry | Value added | |||||||||
| Shandong | Jiangsu | Zhejiang | Fujian | Guangdong | |||||||
|
| |||||||||||
| Value added(100 million) | % | Value added(100 million) | % | Value added(100 million) | % | Value added(100 million) | % | Value added(100 million) | % | ||
| 2015 | Primary industry | 4979.08 | 7.90% | 3986.05 | 5.68% | 1832.91 | 4.27% | 2118.1 | 8.15% | 3345.54 | 4.59% |
| Secondary industry | 29485.9 | 46.80% | 32044.45 | 45.70% | 19711.67 | 45.96% | 13064.82 | 50.29% | 32613.54 | 44.79% | |
| Tertiary industry | 28537.35 | 45.30% | 34085.88 | 48.61% | 21341.91 | 49.76% | 10796.9 | 41.56% | 36853.47 | 50.61% | |
| Total | 63002.33 | 70116.38 | 42886.49 | 25979.82 | 72812.55 | ||||||
| 2016 | Primary industry | 4929.13 | 7.25% | 4077.18 | 5.27% | 1965.18 | 4.16% | 2363.22 | 8.20% | 3694.37 | 4.57% |
| Secondary industry | 31343.67 | 46.08% | 34619.5 | 44.73% | 21194.61 | 44.86% | 14093.47 | 48.92% | 35109.56 | 43.42% | |
| Tertiary industry | 31751.69 | 46.68% | 38691.6 | 50.00% | 24091.57 | 50.99% | 12353.89 | 42.88% | 42050.88 | 52.01% | |
| Total | 68024.49 | 77388.28 | 47251.36 | 28810.58 | 80854.91 | ||||||
| 2017 | Primary industry | 4832.71 | 6.65% | 4045.16 | 4.71% | 1933.92 | 3.74% | 2215.13 | 6.88% | 3611.44 | 4.03% |
| Secondary industry | 32942.84 | 45.35% | 38654.87 | 45.02% | 22232.08 | 42.95% | 15354.29 | 47.71% | 38008.06 | 42.37% | |
| Tertiary industry | 34858.6 | 47.99% | 43169.73 | 50.27% | 27602.26 | 53.32% | 14612.67 | 45.41% | 48085.73 | 53.60% | |
| Total | 72634.15 | 85869.76 | 51768.26 | 32182.09 | 89705.23 | ||||||
| 2018 | Primary industry | 4950.52 | 6.47% | 4141.72 | 4.47% | 1967.01 | 3.50% | 2379.82 | 6.65% | 3831.44 | 3.94% |
| Secondary industry | 33641.72 | 43.99% | 41248.52 | 44.55% | 23505.88 | 41.83% | 17232.36 | 48.13% | 40695.15 | 41.83% | |
| Tertiary industry | 37877.43 | 49.53% | 47205.16 | 50.98% | 30724.26 | 54.67% | 16191.86 | 45.22% | 52751.18 | 54.23% | |
| Total | 76469.67 | 92595.4 | 56197.15 | 35804.04 | 97277.77 | ||||||
| 2019 | Primary industry | 5116.44 | 7.20% | 4296.28 | 4.31% | 2097.38 | 3.36% | 2596.23 | 6.12% | 4351.26 | 4.04% |
| Secondary industry | 28310.92 | 39.84% | 44270.51 | 44.43% | 26566.6 | 42.61% | 20581.74 | 48.55% | 43546.43 | 40.44% | |
| Tertiary industry | 37640.17 | 52.96% | 51064.73 | 51.25% | 33687.76 | 54.03% | 19217.03 | 45.33% | 59773.38 | 55.51% | |
| Total | 71067.53 | 99631.52 | 62351.74 | 42395 | 107671.07 | ||||||
China Statistical Yearbook.
Results of the one-way ANOVA for industrial added value.
| Sum of squares | df | Mean square | F | Sig. | |
| Between groups | 11118754208.169 | 4 | 2779688552.042 | 4.584 | 0.002 |
| Within groups | 57611137793.470 | 95 | 606433029.405 | ||
| Total | 68729892001.640 | 99 |
Comparison of differences in industrial added value in the five provinces.
| Groups | N | Subsets (alpha = 0.05) | |
| 1 | 2 | ||
| Added value in Fujian | 20 | 16517.1530 | |
| Added value in Zhejiang | 20 | 26045.5000 | 26045.5000 |
| Added value in Shandong | 20 | 35119.8170 | |
| Added value in Jiangsu | 20 | 42560.1340 | |
| Added value in Guangdong | 20 | 44832.1480 | |
| Significance | 0.224 | 0.082 | |