System dynamic research on interactive development of rural e-commerce and revitalization
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摘要: 乡村振兴战略的部署实施为农村基础设施建设、农村经济结构创新、农村技术人才培养提供了充分的政策保障,极大地改善了农村电商发展的外部环境与内在要求。与此同时,农村电商的发展又在市场拓展、产业升级、资金融通等方面促进了乡村振兴战略的实施。为了实现二者的高效互动,本文通过构建农村电商与乡村振兴互动发展的系统动力学模型,揭示了农村电商网商数量、农特产品市场、农村电商专业人才规模、资金规模4个子系统之间的因果关系和动态反馈机制,并基于我国2010—2016年农村经济发展的相关统计数据对农村电商和乡村振兴的互动性进行了仿真模拟。对系统动力学模型进行的稳定性和有效性检验表明,模型能够真实地反映农村经济增长过程中农村电商和乡村振兴互动发展的实际系统结构和功能。在此基础上,通过调整农村电商固定资产投资水平参数、农村电商教育投资水平参数、农业财政补贴因子、农村居民消费补贴因子4个政策变量的取值,进一步对农村电商同乡村振兴互动发展的政策进行模拟。模拟结果显示:影响农村电商与乡村振兴互动发展的主要因素是农业财政补贴力度;相关扶持政策在农村电商和乡村振兴互动发展的过程中具有不同的政策效果,呈现出明显的阶段性特征。因此,逐步加大农业财政补贴力度,构建全方位的政策支持体系对于实现农村电商与乡村振兴的互动发展至关重要,同时应根据农村电商发展与乡村振兴战略实施的现状,分阶段、有针对性地重点推进相关政策,以促进农村电商与乡村振兴的互动发展。Abstract: The implementation of rural revitalization strategy has provided sufficient policy guarantee for rural infrastructure construction, rural economic structure innovation and rural technical personnel training; in turn greatly improving the external environment and internal requirements of rural e-commerce development. Also the development of rural e-commerce has promoted the implementation of rural revitalization strategy in terms of market expansion, industrial upgrading and financing. In order to achieve high-efficiency interaction between the two strategies, we constructed a system dynamics model of interactive development between rural e-commerce and rural revitalization to show causal relationship and dynamic feedback mechanism among the four subsystems of number of rural e-commerce operators, agricultural special product market, rural e-commerce professional talents scale and capital scale. Based on statistical data of rural economic development in China for 2010-2016, we simulated the interaction between rural e-commerce and rural revitalization. Stability and validity tests of the system dynamics model showed that the model truly reflected actual system structure and function of rural e-commerce and rural revitalization in rural economic growth. On this basis, the policy of the interactive development between rural e-commerce and rural revitalization was further simulated by adjusting the values of four policy variables of rural e-commerce fixed asset investment parameter, rural e-commerce education investment parameter, agricultural financial subsidy factor and rural resident consumption subsidy factor. The simulation results showed that the main factor influencing interactive development between rural e-commerce and rural revitalization was the intensity of agricultural financial subsidies. Also relevant supporting policies had different effects on the process of interactive development between rural e-commerce and rural revitalization, with obvious stage characteristics. Therefore, gradually increasing the intensity of agricultural financial subsidies and building comprehensive policy support systems were necessary to realize interactive development between rural e-commerce and rural revitalization. Also according to current conditions of rural e-commerce development and rural revitalization strategy implementation, there was need to focus on promoting relevant policies to promote interactive development between rural e-commerce and rural revitalization in a phased and targeted manner.
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图 6 增加政府对农村地区的投资(策略1)下的农村电商市场产值(a)和农村电商专业人才数量(b)
策略1方案1为调整农村电商固定资产投资水平; 策略1方案2为调整农村电商教育投资水平。
Figure 6. Rural e-commerce market output value (a) and number of rural electricity professional talents (b) under increase government investment in rural areas (Strategy 1)
Strategy 1 Plan 1 is to adjust the fixed asset investment level of rural e-commerce; Strategy 1 Plan 2 is to adjust the education investment level of rural e-commerce.
图 7 提高政府对农村补贴政策的支持力度(策略2)下的农村电商市场产值(a)和农村电商专业人才数量(b)
策略2方案1为调整农业财政补贴因子; 策略2方案2为调整农村居民消费补贴因子。
Figure 7. Rural e-commerce market output value (a) and number of rural e-commerce professional talents (b) under increase government support for rural subsidy policy (Strategy 2)
Strategy 2 Plan 1 is to adjust the agricultural financial subsidy factor; Strategy 2 Plan 2 is to adjust the rural resident consumption subsidy factor.
表 1 农村电商与乡村振兴互动发展系统动力学建模主要参数及模型设定
Table 1. Main parameters and model setting of system dynamics modeling of interactive development of rural e-commerce and rural revitalization
类别
Category变量名称Variable name 类型
Type模型方程及参数Model equation and parameter 单位
Unit经济指标
Economic indicator农村电商市场产值
Rural e-commerce market output valueL1) 农村电商产业增加值-农村电商产业减少值
Difference between added value of rural e-commerce industry and decreased value of rural e-commerce industry×108¥ 农业总产值
Agricultural gross output valueL 农业总产值增加值
Added value of agricultural gross output×108¥ 农村电商网商数量
Number of rural e-commerce network operatorsL 农村电商网商增加量-农村电商网商减少量
Difference between increased number of rural e-commerce network operators and decreased number of rural e-commerce network operatorsDmnl 农村电商专业人才量
Number of rural e-commerce professional talentsL 农村电商人才增长量
Increased number of rural e-commerce talentsDmnl 辅助指标
Auxiliary indicator农业总产值增加值
Added value of agricultural gross outputA2) 农业总产值×γ(γ为农业产值增长率, 0 < γ < 1)
Agricultural gross output value × γ (γ is the growth rate of agricultural output value, 0 < γ < 1)×108¥ 农村电商教育投资
Rural e-commerce education investmentA 农业总产值×农村电商教育投资系数
Agricultural gross output value × rural e-commerce education investment coefficientDmnl 农村消费额增长指数
Rural consumption growth indexA 农村消费额增加值/农村消费总额
Added value of rural consumption / total rural consumptionDmnl 农村电商人才增长量
Increased number of rural e-commerce talentsA 农村电商教育投资×教育投资效益系数
Rural e-commerce education investment × education investment benefit coefficientDmnl 农村电商网商增加量
Increased number of rural e-commerce network operatorsA 农村电商网商数量×农村居民人均可支配收入增长速率×β (β为农村居民消费补贴因子, 0 < β < 1)
Number of rural e-commerce network operators × growth rate of per capita disposable income of rural residents × β (β is rural resident consumption subsidy factor, 0 < β < 1)Dmnl 农村电商产业增加值
Added value of rural e-commerce industryA 农村电商固定资产投资+农村电商市场交易额
Rural e-commerce fixed assets investment + Rural e-commerce market transaction volume×108¥ 农村固定资产投资[8]
Rural fixed asset investmentA 农业总产值×农村固定资产投资比例
Agricultural gross output value × rural fixed assets investment ratio×108¥ 常量值
Constant value物流水平影响因子
Logistics level impact factorC3) 0.086 2[4] Dmnl 农村电商教育投资系数
Rural e-commerce education investment coefficientC 0.021 04) Dmnl 农业财政补贴因子
Agricultural financial subsidy factorC 0.2205) Dmnl 农村居民消费补贴因子
Rural resident consumption subsidy factorC 0.0205) Dmnl 农村电商固定资产投资比例
Ratio of investment on rural e-commerce fixed assetsC 0.1204) Dmnl 1)L:水平变量; 2)A:辅助变量; 3)C:常量; 4)采用趋势法计算得出; 5)采用回归分析法计算得出。1) L: level variable; 2) A: auxiliary variable; 3) C: constant; 4) obtained by the trend method; 5) obtained by the regression analysis method. 表 2 农村电商与乡村振兴互动发展的系统动力学模型有效性检验结果
Table 2. Validity test results of system dynamics model of interactive development of rural e-commerce and rural revitalization
年份
Year农业总产值
Agricultural gross output value农村居民人均消费支出
Per capita consumption expenditure of rural residents原始值
Original value (×108 ¥ )仿真值
Simulation value (×108 ¥ )误差率
Error rate (%)原始值
Original value (×108 ¥ )仿真值
Simulation value (×108 ¥ )误差率
Error rate (%)2010 39 362.6 39 362.6 0 4 381.8 4 381.8 0 2011 46 163.1 48 084.2 -4 5 221.1 5 426.3 -4 2012 50 902.3 51 298.4 -1 5 908.0 5 791.9 2 2013 55 329.1 53 988.8 2 7 485.2 6 934.2 7 2014 58 343.5 56 488.3 3 8 382.6 7 837.6 7 2015 60 862.1 59 148.5 3 9 222.6 8 347.4 9 2016 63 670.7 62 453.8 2 10 129.8 9 491.9 6 表 3 农村电商与乡村振兴互动发展的系统动力学模型在不同仿真策略下的系统动态模拟结果
Table 3. System dynamic simulation results of system dynamics model of interactive development of rural e-commerce and rural revitalization under different simulation strategies
年份
Year农村电商市场产值
Rural e-commerce market output value (×108¥ )农村电商专业人才数量
Number of rural e-commerce professional talents (×104)初始值
Initial value策略1 Strategy one 策略2 Strategy two 初始值
Initial value策略1 Strategy one 策略2 Strategy two 方案1
Plan 1方案2
Plan 2方案1
Plan 1方案2
Plan 2方案1
Plan 1方案2
Plan 2方案1
Plan 1方案2
Plan 22010 1 200.00 1 200.00 1 200.00 1 200.00 1 200.00 120.00 120.00 120.00 120.00 120.00 2011 2 139.40 2 141.66 2 140.40 2 143.40 2 143.00 122.81 122.91 123.13 123.81 123.71 2012 3 043.82 3 048.34 3 047.33 3 201.82 3 200.95 125.79 126.00 126.65 126.79 126.31 2013 3 917.00 3 923.79 3 920.52 4 118.00 4 099.63 128.95 129.87 130.30 130.75 130.43 2014 4 762.69 4 771.79 4 768.74 4 889.28 4 877.45 132.35 133.43 134.20 134.28 134.02 2015 5 584.75 5 596.23 5 589.90 5 718.75 5 709.61 136.01 138.64 139.41 137.91 137.33 2016 6 327.22 6 401.20 6 400.17 6 487.23 6 454.59 140.00 142.00 143.00 143.00 142.72 2017 7 174.46 7 391.09 7 249.06 7 344.47 7 327.28 144.39 146.72 152.05 148.39 147.99 2018 7 789.34 7 950.81 7 820.66 7 998.30 7 886.69 149.28 150.38 153.67 150.33 149.99 2019 8 323.17 8 745.92 8 553.82 8 723.23 8 555.94 154.79 156.80 164.01 163.67 157.56 2020 9 096.64 9 523.06 9 162.54 9 996.76 9 346.25 161.11 165.20 172.28 171.42 165.65 策略1方案1为调整农村电商固定资产投资水平, 策略1方案2为调整农村电商教育投资水平; 策略2方案1为调整农业财政补贴因子, 策略2方案2为调整农村居民消费补贴因子。Strategy 1 Plan 1 is to adjust the fixed asset investment level of rural e-commerce; Strategy 1 Plan 2 is to adjust the education investment level of rural e-commerce; Strategy 2 Plan 1 is to adjust the agricultural financial subsidy factor; Strategy 2 Plan 2 is to adjust the rural resident consumption subsidy factor. 表 4 不同政策方案下农村电商市场产值、农村电商专业人才数量和农村居民收入增长率的对比分析
Table 4. Comparative analysis of rural e-commerce market output value, number of rural e-commerce professional talents and growth rate of rural residents income under different policy options
方案Plan 农村电商市场产值
Rural e-commerce market output value (×104¥ )农村电商专业人才数量
Number of rural e-commerce professional talents (×104)农村居民人均可支配收入增长率
Growth rate of per capita disposable income of rural residents (%)初始状态Initial state 7 174.46 144.39 7.900 策略1方案1 Strategy 1 Plan 1 7 391.09 146.72 7.940 策略1方案2 Strategy 1 Plan 2 7 249.06 152.05 7.935 策略2方案1 Strategy 2 Plan 1 7 344.47 148.39 7.958 策略2方案2 Strategy 2 Plan 2 7 327.28 147.99 7.947 策略1方案1为调整农村电商固定资产投资水平, 策略1方案2为调整农村电商教育投资水平; 策略2方案1为调整农业财政补贴因子, 策略2方案2为调整农村居民消费补贴因子。Strategy 1 Plan 1 is to adjust the fixed asset investment level of rural e-commerce; Strategy 1 Plan 2 is to adjust the education investment level of rural e-commerce; Strategy 2 Plan 1 is to adjust the agricultural financial subsidy factor; Strategy 2 Plan 2 is to adjust the rural resident consumption subsidy factor. -
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