Optimization Strategy of Digital Economy to Promote the Efficiency of Rural-Urban Integration Based on Big Data Analysis

Figure 1.

Figure 2.

The mediation effect of the factor configuration efficiency is tested

Variable	Model 1	Model 2	Model 3
Digital economic development	0.05792***	0.11043***	0.05206***
Factor configuration efficiency			0.05918***
Control variable	Yes	Yes	Yes
Provincial fixation effect	Yes	Yes	Yes
Year fixed effect	Yes	Yes	Yes
N	350	350	350
R2	0.85261	0.60277	0.86755

The average Malmquist index in Guangdong province in 2017-2023 year

Year	Effch	Techch	Pech	Sech	Tfpch	Tfpch sort
2017-2018	0.9955	2.9426	1.0024	0.9975	2.9319	1
2018-2019	1.0041	0.9426	0.9983	1.0069	0.9446	5
2019-2020	0.8847	1.5478	1.0004	0.8836	1.3708	2
2020-2021	1.0795	0.5428	0.9962	1.083	0.5845	6
2021-2022	1.0561	0.9556	1.0034	1.0528	1.0093	3
2022-2023	0.9996	1.0022	1.0012	1.0011	1.0014	4
Mean	1.0033	1.3223	1.0003	1.0042	1.3071

The average Malmquist index in the Qingyuan city in 2017-2023

Year	Effch	Techch	Pech	Sech	Tfpch	Tfpch sort
2017-2018	1.0098	3.4217	1.0012	1.0115	3.4518	1
2018-2019	1.0006	1.5492	0.9985	1.0005	1.5504	2
2019-2020	0.5457	0.8676	1	0.5446	0.4736	6
2020-2021	1.8353	0.55	0.9989	1.8363	1.0124	3
2021-2022	1.0008	0.9555	0.9972	1.0003	0.9546	4
2022-2023	0.9993	0.7329	0.9975	0.9986	0.7362	5
Mean	1.0653	1.3462	0.9989	1.0653	1.3632

The heterogeneity of urban and rural development of digital economy

Variable	East	Middle	West
Digital economic development	0.12597***	-0.08943***	0.06689***
Control variable	Yes	Yes	Yes
Constant	0.1842	-0.27035	0.50986
Provincial fixation effect	Yes	Yes	Yes
Year fixed effect	Yes	Yes	Yes
N	130	120	100
R2	0.91013	0.80212	0.78006

The results of variable regression

Variable	Model 1	Model 2	Model 3
Digital economic development	0.05792***		0.05206***
Factor configuration efficiency		0.09597***	0.05918***
Urban and rural integration development level	0.03505***	0.03816***	0.03280***
Economic integration	-0.00085	-0.00010	-0.00102
Industry digitization	-0.00628	-0.02207	-0.00709
Digital industrialization	0.04494***	0.06398***	0.04501***
Constant	-0.15904**	-0.20022**	-0.14399*
Provincial fixation effect	Yes	Yes	Yes
Year fixed effect	Yes	Yes	Yes
N	350	350	350
R2	0.85261	0.83024	0.86755

The average Malmquist index in Guangdong province in 2017-2023

City	Effch	Techch	Pech	Sech	Tfpch	Tfpch sort
Guangzhou	0.998	0.7487	0.9981	0.9987	0.7467	20
Zhuhai	1.0039	0.8709	0.9998	1.0071	0.8787	19
Shantou	1.0011	0.9381	0.9994	0.9999	0.9382	18
Foshan	1.0043	0.9764	1.0024	1.0035	0.9789	15
Shaoguan	1.0016	1.0129	0.9998	1.0015	1.0136	14
Heyuan	0.9984	0.9693	0.9993	1.0012	0.9734	17
Meizhou	0.9992	1.023	1.0011	1.0008	1.0256	13
Huizhou	1.0022	0.9754	1.0006	0.9977	0.9736	16
shantou	1.0006	1.3904	1.0011	1.0008	1.3905	5
Dongguan	1.0073	1.4423	1.005	1.0025	1.4524	1
Zhongshan	1.0025	1.4243	1.0007	1.0012	1.4287	4
Jiangmen	1.0055	1.4369	0.9971	1.0037	1.4417	3
Yangjiang	1	1.3829	1	0.9985	1.3849	6
Zhanjiang	1.002	1.2965	0.999	1.0006	1.2955	7
Maoming	1.0022	1.2613	1	0.9993	1.2632	8
Zhaoqing	0.9994	1.1845	0.9998	1.0011	1.1834	10
Qingyuan	1.0012	1.1017	1.0018	1.0001	1.1018	12
Chaozhou	0.9998	1.1555	1.0017	1.0015	1.1537	11
Jieyang	1.0019	1.2303	1.0022	1.0008	1.2321	9
Cloud float	1	1.4404	0.9992	0.9985	1.442	2
Mean	1.0016	1.1631	1.0004	1.0010	1.1649

Urban and rural integration input output index system

Overall index	DEA coordinates	Index dimension	Index name
Urban and rural integrated development level measure system	Input index	Digital economic development	Urban and rural industrial integration
		Factor configuration efficiency	Urban and rural social security coverage
		Urban and rural integration development level	Level of land urbanization
Digital economic development level measure system	Output indicator	Digital infrastructure	Internet penetration
		Industry digitization	Digital financial development
		Digital industrialization	Telecommunications revenue