Article(id=1241116646513889664, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1241116641321350143, articleNumber=null, orderNo=null, doi=null, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1723651200000, receivedDateStr=2024-08-15, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773834867361, onlineDateStr=2026-03-18, pubDate=1742400000000, pubDateStr=2025-03-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773834867361, onlineIssueDateStr=2026-03-18, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773834867361, creator=13701087609, updateTime=1773834867361, updator=13701087609, issue=Issue{id=1241116641321350143, tenantId=1146029695717560320, journalId=1234093305789726721, year='2025', volume='45', issue='3', pageStart='1185', pageEnd='1776', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773834866123, creator=13701087609, updateTime=1773881366030, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241311676130193619, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1241116641321350143, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241311676130193620, tenantId=1146029695717560320, journalId=1234093305789726721, issueId=1241116641321350143, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1713, endPage=1730, ext={EN=ArticleExt(id=1241116647264670124, articleId=1241116646513889664, tenantId=1146029695717560320, journalId=1234093305789726721, language=EN, title=Research on the impact mechanism of industrial digitalization on green total factor productivity: The threshold effect of environmental regulation, columnId=1234106417825772207, journalTitle=China Environmental Science, columnName=Environmental Impact Assessment and Management, runingTitle=null, highlight=null, articleAbstract=

This study analyzes provincial panel data from China covering the period from 2014 to 2022 to measure the level of industrial digitalization across three sectors: agriculture, industry, and services. Additionally, it accounts for the input of data factors and various undesired outputs while evaluating green total factor productivity, thereby exploring the interaction effects and mechanisms between the two. The research findings are demonstrated as follows: Significant disparities exist in the levels of industrial digitalization among provinces, demonstrating a spatial pattern of “East >Central >West.”Moreover, green total factor productivity shows a consistent upward trend, indicating a progressive improvement in regional multi-level differentiation. Robustness tests reveal that industrial digitalization across Chinese provinces significantly enhances green total factor productivity, with impact effects characterized by the order of agriculture < industry < services. Regarding transmission pathways, the development of industrial digitalization in each province predominantly boosts green total factor productivity by reducing the mismatch between capital and labor and facilitating industrial structure upgrades; In provinces characterized by high public environmental awareness and lower industrialization levels, the effect of industrial digitalization on enhancing green total factor productivity is comparatively pronounced; The impact of industrial digitalization on green total factor productivity exhibits a single threshold characteristic, contingent upon the intensity of various forms of environmental regulation, with threshold values of 0.4582 for command-and-control regulation and 0.0096 for market-based regulation. Consequently, the government should formulate differentiated regional industrial policies and marketing strategies to more effectively promote the development of industrial digitalization and bolster green total factor productivity, thereby achieving sustainable green development.

, correspAuthors=He-ping HUANG, Guo-min LI, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, authorCompany=null, fund=null, authors=null, authorsList=He-ping HUANG, Gui-ming ZHOU, Guo-min LI), CN=ArticleExt(id=1241116655355483016, articleId=1241116646513889664, tenantId=1146029695717560320, journalId=1234093305789726721, language=CN, title=产业数字化对绿色全要素生产率的影响机制研究——兼议环境规制的门槛效应, columnId=1234106419604157142, journalTitle=中国环境科学, columnName=环境影响评价与管理, runingTitle=null, highlight=null, articleAbstract=

基于2014~2022年中国省域面板数据从农业、工业和服务业三个维度衡量产业数字化水平，同时测度考虑了数据要素投入和多种非期望产出的绿色全要素生产率，进而探究两者间的影响效应与作用机制.研究发现：各省域产业数字化水平差异显著并呈现出“东部>中部>西部”的空间布局.绿色全要素生产率也表现出逐渐提高的趋势，区域多级分化现象逐步改善;经过一系列稳健性检验后发现，中国省域产业数字化显著促进了绿色全要素生产率的提升，且影响效应呈现出农业<工业<服务业的特征;在传导路径上，各省域产业数字化的发展主要通过降低资本与劳动力错配度和促进产业结构升级提升绿色全要素生产率;公众环境关注度高和工业化程度较低的省域，产业数字化发展的绿色全要素生产率提升效应相对较高;产业数字化对绿色全要素生产率的影响随不同类型环境规制强度的变化呈现出单一门槛特征，命令控制型环境规制强度和市场激励性环境规制强度的门槛值分别为0.4582和0.0096.因此，政府应制定差异化的区域产业政策与市场策略，以更加有效的方式促进产业数字化发展进而提升绿色全要素生产率，实现绿色可持续发展.

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黄和平(1969-)，男，江西吉水人，教授，博士，主要从事生态系统管理与评价、环境规划与管理等研究.发表论文100余篇.hphuang@163.com

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黄和平(1969-)，男，江西吉水人，教授，博士，主要从事生态系统管理与评价、环境规划与管理等研究.发表论文100余篇.hphuang@163.com

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Economic Modelling，2020，86:306-316., articleTitle=Stock market response to environmental policies: Evidence from heavily polluting firms in China, refAbstract=null)], funds=[Fund(id=1241116665627333440, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, awardId=2023BJY090, language=CN, fundingSource=国家社会科学基金项目(2023BJY090), fundOrder=null, country=null), Fund(id=1241116665727996748, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, awardId=23BJL077, language=CN, fundingSource=国家社会科学基金项目(23BJL077), fundOrder=null, country=null), Fund(id=1241116667271500634, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, awardId=42201294, language=CN, fundingSource=国家自然科学基金项目(42201294), fundOrder=null, country=null), Fund(id=1241116667388941160, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, awardId=20241125194930833, language=CN, fundingSource=江西财经大学第十九届学生科研课题(20241125194930833), fundOrder=null, country=null)], companyList=[AuthorCompany(id=1241116655720387504, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, xref=null, ext=[AuthorCompanyExt(id=1241116655728776116, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, companyId=1241116655720387504, language=EN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=School of Economics, Jiangxi University of Finance and Economics, Nanchang 330013, China), AuthorCompanyExt(id=1241116655737164723, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, companyId=1241116655720387504, language=CN, country=null, province=null, city=null, postcode=null, companyName=null, departmentName=null, remark=江西财经大学经济学院，江西 南昌 330013)])], figs=[ArticleFig(id=1241116659830804759, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=EN, label=Fig.1, caption=Evolution of green total factor productivity distribution in China, figureFileSmall=E1Q5+JA36S+EdwVxJzWo8g==, figureFileBig=9HlRdA3cA2r+uAv6fEDDsA==, tableContent=null), ArticleFig(id=1241116659939856676, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=CN, label=图1, caption=中国绿色全要素生产率分布演变, figureFileSmall=E1Q5+JA36S+EdwVxJzWo8g==, figureFileBig=9HlRdA3cA2r+uAv6fEDDsA==, tableContent=null), ArticleFig(id=1241116660199903557, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=EN, label=Fig.2, caption=Evolution of spatial pattern of green total factor productivity in China Review, figureFileSmall=PT27DXnuh6k8tmfxA+KfLw==, figureFileBig=poT2y4aC0Qawo4+ymBvzoQ==, tableContent=null), ArticleFig(id=1241116660296372565, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=CN, label=图2, caption=中国绿色全要素生产率的空间格局演化情况

审图号：GS(2024)0650号，下同

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Green total factor productivity evaluation index system

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一级指标	二级指标	指标含义
投入	资本要素	资本存量(永续盘存法估算得出)
	劳动力要素	年末城镇从业人数
	能源要素	全社会用电量
	水资源要素	全社会用水总量
	数据要素	信息传输、计算机服务和软件业固定资产投资
		移动电话基站数
		电子及通信设备制造业的R&D支出
产出	期望产出	地区生产总值
	非期望产出	二氧化碳排放量
		工业二氧化硫排放量
		工业烟(粉)尘排放量
		工业废水排放量

), ArticleFig(id=1241116660862603686, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=CN, label=表1, caption=

绿色全要素生产率评价指标体系

, figureFileSmall=null, figureFileBig=null, tableContent=

一级指标	二级指标	指标含义
投入	资本要素	资本存量(永续盘存法估算得出)
	劳动力要素	年末城镇从业人数
	能源要素	全社会用电量
	水资源要素	全社会用水总量
	数据要素	信息传输、计算机服务和软件业固定资产投资
		移动电话基站数
		电子及通信设备制造业的R&D支出
产出	期望产出	地区生产总值
	非期望产出	二氧化碳排放量
		工业二氧化硫排放量
		工业烟(粉)尘排放量
		工业废水排放量

), ArticleFig(id=1241116660971655602, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=EN, label=Table 2, caption=

Industrial digitalization evaluation index system

, figureFileSmall=null, figureFileBig=null, tableContent=

一级指标	二级指标	三级指标	指标权重
产业数字化	农业数字化	农业生产电气化[(kW·h)/元]	0.039
		农业机械作业服务机构数(个)	0.048
		环境与农业气象观测站数量(个)	0.017
		农业科技专利数量(个)	0.036
		农村宽带接入用户数(万户)	0.030
		农村普惠金融指数(%)	0.018
		农村数字化基地数量(个)	0.111
	工业数字化	软件产品收入(亿元)	0.079
		信息技术服务收入(亿元)	0.082
		嵌入式系统软件产品收入(亿元)	0.118
		工业机器人安装密度(台/万人)	0.058
		规模以上工业企业新产品销售收入与工业企业主营业务收入之比(%)	0.018
		国内专利申请授权量与规模以上工业企业R&D人员全时当量之比(%)	0.029
		计算机、通讯与其他电子设备制造业营业收入(亿元)	0.074
	服务业数字化	快递量(亿件)	0.077
		电子商务交易额(亿元)	0.053
		每百家企业拥有网站数(个)	0.011
		有电子商务交易活动的企业数比重(%)	0.021
		政企宽带接入用户数(万户)	0.030
		移动电话年末用户(万户)	0.022
		移动电话普及率(%)	0.031

), ArticleFig(id=1241116661139427782, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=CN, label=表2, caption=

产业数字化评价指标体系

, figureFileSmall=null, figureFileBig=null, tableContent=

一级指标	二级指标	三级指标	指标权重
产业数字化	农业数字化	农业生产电气化[(kW·h)/元]	0.039
		农业机械作业服务机构数(个)	0.048
		环境与农业气象观测站数量(个)	0.017
		农业科技专利数量(个)	0.036
		农村宽带接入用户数(万户)	0.030
		农村普惠金融指数(%)	0.018
		农村数字化基地数量(个)	0.111
	工业数字化	软件产品收入(亿元)	0.079
		信息技术服务收入(亿元)	0.082
		嵌入式系统软件产品收入(亿元)	0.118
		工业机器人安装密度(台/万人)	0.058
		规模以上工业企业新产品销售收入与工业企业主营业务收入之比(%)	0.018
		国内专利申请授权量与规模以上工业企业R&D人员全时当量之比(%)	0.029
		计算机、通讯与其他电子设备制造业营业收入(亿元)	0.074
	服务业数字化	快递量(亿件)	0.077
		电子商务交易额(亿元)	0.053
		每百家企业拥有网站数(个)	0.011
		有电子商务交易活动的企业数比重(%)	0.021
		政企宽带接入用户数(万户)	0.030
		移动电话年末用户(万户)	0.022
		移动电话普及率(%)	0.031

), ArticleFig(id=1241116661361725911, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=EN, label=Table 3, caption=

Descriptive statistical results of variables

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变量类型	变量含义	变量符号	样本数	平均值	标准差	最小值	最大值
被解释变量	绿色全要素生产率	GTFP	270	0.8799	0.1310	0.5040	1.3100
解释变量	产业数字化	IDL	270	0.1751	0.1535	0.0273	0.6926
	农业数字化	AGRICULTURE	270	0.1609	0.1342	0.0097	0.5345
	工业数字化	INDUST	270	0.1550	0.1942	0.0079	0.8937
	服务业数字化	SERVICE	270	0.2384	0.1700	0.0581	0.8763
机制变量	资本错配度	CAPITAL	270	1.6927	0.5291	0.4487	2.7486
	劳动力错配度	LABOR	270	1.1361	0.3607	0.3963	1.9873
	产业结构升级	TS	270	241.0512	11.8088	223.9000	283.2000
门槛变量	命令控制型环境规制强度	ER1	270	0.2577	0.2226	0.0112	1.0886
	市场激励型环境规制强度	ER2	270	0.0272	0.0206	0.0043	0.0949
控制变量	科技创新投入水平	TII	270	0.1831	0.0325	0.1167	0.2562
	人力资本水平	PCAP	270	0.0219	0.0055	0.0106	0.0413
	经济发展水平	PGDP	270	6.6315	3.1128	2.6437	17.9907
	社会就业水平	EMP	270	0.5358	0.0453	0.4544	0.7224
	政府干预程度	GOVERN	270	0.2517	0.1015	0.1188	0.6269

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变量的描述性统计结果

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变量类型	变量含义	变量符号	样本数	平均值	标准差	最小值	最大值
被解释变量	绿色全要素生产率	GTFP	270	0.8799	0.1310	0.5040	1.3100
解释变量	产业数字化	IDL	270	0.1751	0.1535	0.0273	0.6926
	农业数字化	AGRICULTURE	270	0.1609	0.1342	0.0097	0.5345
	工业数字化	INDUST	270	0.1550	0.1942	0.0079	0.8937
	服务业数字化	SERVICE	270	0.2384	0.1700	0.0581	0.8763
机制变量	资本错配度	CAPITAL	270	1.6927	0.5291	0.4487	2.7486
	劳动力错配度	LABOR	270	1.1361	0.3607	0.3963	1.9873
	产业结构升级	TS	270	241.0512	11.8088	223.9000	283.2000
门槛变量	命令控制型环境规制强度	ER1	270	0.2577	0.2226	0.0112	1.0886
	市场激励型环境规制强度	ER2	270	0.0272	0.0206	0.0043	0.0949
控制变量	科技创新投入水平	TII	270	0.1831	0.0325	0.1167	0.2562
	人力资本水平	PCAP	270	0.0219	0.0055	0.0106	0.0413
	经济发展水平	PGDP	270	6.6315	3.1128	2.6437	17.9907
	社会就业水平	EMP	270	0.5358	0.0453	0.4544	0.7224
	政府干预程度	GOVERN	270	0.2517	0.1015	0.1188	0.6269

), ArticleFig(id=1241116662947172847, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=EN, label=Table 4, caption=

Baseline regression results

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变量名称	变量符号	(1)	(2)	(3)	(4)
产业数字化	IDL	0.4233*** (0.1128)
农业数字化	AGRICULTURE		0.4678*** (0.1193)
工业数字化	INDUST			0.4878*** (0.0309)
服务业数字化	SERVICE				0.5910*** (0.0318)
科技创新投入水平	TII	1.2417*** (0.3530)	1.1720*** (0.3375)	1.1558*** (0.1982)	1.2614*** (0.2056)
社会就业水平	EMP	0.4140** (0.1829)	0.4525** (0.1929)	0.3920*** (0.1319)	0.5465*** (0.1458)
人力资本水平	PCAP	4.8455** (2.2553)	4.8443** (2.2770)	6.5051*** (1.2447)	6.6020*** (1.1479)
经济发展水平	PGDP	0.0069 (0.0064)	0.0066 (0.0074)	-0.0117* (0.0059)	-0.0125* (0.0063)
政府干预程度	GOVERN	0.3306 (0.2674)	0.3703 (0.2926)	-0.4199** (0.1717)	-0.3367* (0.1689)
常数项	constant	0.1082 (0.1515)	0.0919 (0.1620)	0.4153*** (0.1018)	0.2285** (0.1003)
省份固定效应	province effect	控制	控制	控制	控制
年份固定效应	year effect	控制	控制	控制	控制
R2	R2	0.535	0.520	0.824	0.846
样本数	observations	270	270	270	270

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基准回归结果

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变量名称	变量符号	(1)	(2)	(3)	(4)
产业数字化	IDL	0.4233*** (0.1128)
农业数字化	AGRICULTURE		0.4678*** (0.1193)
工业数字化	INDUST			0.4878*** (0.0309)
服务业数字化	SERVICE				0.5910*** (0.0318)
科技创新投入水平	TII	1.2417*** (0.3530)	1.1720*** (0.3375)	1.1558*** (0.1982)	1.2614*** (0.2056)
社会就业水平	EMP	0.4140** (0.1829)	0.4525** (0.1929)	0.3920*** (0.1319)	0.5465*** (0.1458)
人力资本水平	PCAP	4.8455** (2.2553)	4.8443** (2.2770)	6.5051*** (1.2447)	6.6020*** (1.1479)
经济发展水平	PGDP	0.0069 (0.0064)	0.0066 (0.0074)	-0.0117* (0.0059)	-0.0125* (0.0063)
政府干预程度	GOVERN	0.3306 (0.2674)	0.3703 (0.2926)	-0.4199** (0.1717)	-0.3367* (0.1689)
常数项	constant	0.1082 (0.1515)	0.0919 (0.1620)	0.4153*** (0.1018)	0.2285** (0.1003)
省份固定效应	province effect	控制	控制	控制	控制
年份固定效应	year effect	控制	控制	控制	控制
R2	R2	0.535	0.520	0.824	0.846
样本数	observations	270	270	270	270

), ArticleFig(id=1241116663228191253, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=EN, label=Table 5, caption=

Robustness test results

, figureFileSmall=null, figureFileBig=null, tableContent=

变量名称	变量符号	(1)	(2)	(3)
		滞后一期	双侧缩尾回归	剔除直辖市
产业数字化	IDL	1.0762*** (0.0706)	0.3021*** (0.0855)	0.4682*** (0.1157)
科技创新投入水平	TII	1.1012*** (0.3126)	0.9861*** (0.3405)	1.4054*** (0.3747)
社会就业水平	EMP	0.2359 (0.1573)	0.4115 (0.2809)	0.4690** (0.1795)
人力资本水平	PCAP	8.5290*** (1.4062)	4.2735* (2.4184)	3.2402 (2.5279)
经济发展水平	PGDP	-0.0047 (0.0028)	0.0092 (0.0080)	0.0202** (0.0092)
政府干预程度	GOVERN	0.5135*** (0.1038)	0.2528 (0.2836)	0.3167 (0.2706)
绿色全要素生产率滞后一期	GTFPit-1	0.0217 (0.0593)
常数项	constant	0.0810 (0.1128)	0.2016 (0.2278)	0.0159 (0.1596)
省份固定效应	province effect	控制	控制	控制
年份固定效应	year effect	控制	控制	控制
R2	R2		0.480	0.582
样本数	observations	240	270	234

), ArticleFig(id=1241116663395963435, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=CN, label=表5, caption=

稳健性检验结果

, figureFileSmall=null, figureFileBig=null, tableContent=

变量名称	变量符号	(1)	(2)	(3)
		滞后一期	双侧缩尾回归	剔除直辖市
产业数字化	IDL	1.0762*** (0.0706)	0.3021*** (0.0855)	0.4682*** (0.1157)
科技创新投入水平	TII	1.1012*** (0.3126)	0.9861*** (0.3405)	1.4054*** (0.3747)
社会就业水平	EMP	0.2359 (0.1573)	0.4115 (0.2809)	0.4690** (0.1795)
人力资本水平	PCAP	8.5290*** (1.4062)	4.2735* (2.4184)	3.2402 (2.5279)
经济发展水平	PGDP	-0.0047 (0.0028)	0.0092 (0.0080)	0.0202** (0.0092)
政府干预程度	GOVERN	0.5135*** (0.1038)	0.2528 (0.2836)	0.3167 (0.2706)
绿色全要素生产率滞后一期	GTFPit-1	0.0217 (0.0593)
常数项	constant	0.0810 (0.1128)	0.2016 (0.2278)	0.0159 (0.1596)
省份固定效应	province effect	控制	控制	控制
年份固定效应	year effect	控制	控制	控制
R2	R2		0.480	0.582
样本数	observations	240	270	234

), ArticleFig(id=1241116663584707137, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=EN, label=Table 6, caption=

Endogeneity test results

, figureFileSmall=null, figureFileBig=null, tableContent=

变量	(1) IV=1984年的邮局历史数据×对应年份互联网用户数	(2) IV=1984年的邮电业务总量×对应年份互联网用户数
产业数字化	0.4658*** (0.0713)	0.4397*** (0.0704)
常数项	0.0522 (0.1513)	0.0723 (0.1529)
控制变量	是	是
省份固定效应	是	是
年份固定效应	是	是
IV识别不足检验	29.544***	29.273***
弱IV检验	367.351 [16.38]	1007.713 [16.38]
R2	0.632	0.633
样本量	270	270

), ArticleFig(id=1241116663706341965, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=CN, label=表6, caption=

内生性检验结果

, figureFileSmall=null, figureFileBig=null, tableContent=

变量	(1) IV=1984年的邮局历史数据×对应年份互联网用户数	(2) IV=1984年的邮电业务总量×对应年份互联网用户数
产业数字化	0.4658*** (0.0713)	0.4397*** (0.0704)
常数项	0.0522 (0.1513)	0.0723 (0.1529)
控制变量	是	是
省份固定效应	是	是
年份固定效应	是	是
IV识别不足检验	29.544***	29.273***
弱IV检验	367.351 [16.38]	1007.713 [16.38]
R2	0.632	0.633
样本量	270	270

), ArticleFig(id=1241116663827976795, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=EN, label=Table 7, caption=

Mechanism test results

, figureFileSmall=null, figureFileBig=null, tableContent=

变量名称	变量符号	(1)	(2)	(3)
		资本错配度	劳动力错配度	产业结构升级
产业数字化	IDL	-2.6878*** (0.2222)	-1.5911*** (0.1934)	56.6168*** (8.0926)
科技创新投入水平	TII	1.0076 (0.7838)	-0.8856 (0.5471)	23.4595* (12.8535)
社会就业水平	EMP	-0.7617 (0.4660)	0.4252 (0.3235)	-17.2703** (7.2301)
人力资本水平	PCAP	3.4788 (5.5313)	5.1285* (2.6540)	17.3519 (107.8536)
经济发展水平	PGDP	0.0129 (0.0372)	0.0174 (0.0239)	-0.3068 (0.9774)
政府干预程度	GOVERN	0.6617 (0.9035)	0.6806* (0.3370)	-9.7459 (23.0832)
常数项	constant	2.0739*** (0.4452)	1.0116*** (0.2526)	232.8595*** (10.1910)
省份固定效应	province effect	是	是	是
年份固定效应	year effect	是	是	是
R2	R2	0.676	0.646	0.675
样本数	observations	270	270	270

), ArticleFig(id=1241116663974777458, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=CN, label=表7, caption=

机制检验结果

, figureFileSmall=null, figureFileBig=null, tableContent=

变量名称	变量符号	(1)	(2)	(3)
		资本错配度	劳动力错配度	产业结构升级
产业数字化	IDL	-2.6878*** (0.2222)	-1.5911*** (0.1934)	56.6168*** (8.0926)
科技创新投入水平	TII	1.0076 (0.7838)	-0.8856 (0.5471)	23.4595* (12.8535)
社会就业水平	EMP	-0.7617 (0.4660)	0.4252 (0.3235)	-17.2703** (7.2301)
人力资本水平	PCAP	3.4788 (5.5313)	5.1285* (2.6540)	17.3519 (107.8536)
经济发展水平	PGDP	0.0129 (0.0372)	0.0174 (0.0239)	-0.3068 (0.9774)
政府干预程度	GOVERN	0.6617 (0.9035)	0.6806* (0.3370)	-9.7459 (23.0832)
常数项	constant	2.0739*** (0.4452)	1.0116*** (0.2526)	232.8595*** (10.1910)
省份固定效应	province effect	是	是	是
年份固定效应	year effect	是	是	是
R2	R2	0.676	0.646	0.675
样本数	observations	270	270	270

), ArticleFig(id=1241116664113189503, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=EN, label=Table 8, caption=

Threshold effect test results

, figureFileSmall=null, figureFileBig=null, tableContent=

门槛变量	门槛个数	F统计量	P值	门槛值
命令控制型环境规制强度(ER1)	单一门槛	14.28	0.0167	0.4582
市场激励型环境规制强度(ER2)	单一门槛	9.94	0.0600	0.0096

), ArticleFig(id=1241116664230630032, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=CN, label=表8, caption=

门槛效应检验结果

, figureFileSmall=null, figureFileBig=null, tableContent=

门槛变量	门槛个数	F统计量	P值	门槛值
命令控制型环境规制强度(ER1)	单一门槛	14.28	0.0167	0.4582
市场激励型环境规制强度(ER2)	单一门槛	9.94	0.0600	0.0096

), ArticleFig(id=1241116664377430694, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=EN, label=Table 9, caption=

Threshold regression results of industrial digitalization affecting green total factor productivity

, figureFileSmall=null, figureFileBig=null, tableContent=

变量名称	变量符号	门槛变量
		命令控制型环境规制强度ER1	市场激励型环境规制强度ER2
命令控制型环境规制强度小于等于门槛值0.4582	IDL×I(ER1≤γ1)	0.3623*** (0.0577)
命令控制型环境规制强度大于门槛值0.4582	IDL×I(ER1>γ1)	0.7771*** (0.1127)
市场激励型环境规制强度小于等于门槛值0.0096	IDL×I(ER2≤γ2)		0.2478*** (0.0826)
市场激励型环境规制强度大于门槛值0.0096	IDL×I(ER2>γ2)		0.5137*** (0.0620)
科技创新投入水平	TII	1.4002*** (0.3211)	1.3706*** (0.3246)
社会就业水平	EMP	0.2781 (0.2026)	0.2712 (0.2045)
人力资本水平	PCAP	5.9401*** (2.0439)	5.8162*** (2.0616)
经济发展水平	PGDP	0.0139** (0.0069)	0.0156** (0.0071)
政府干预程度	GOVERN	0.3372 (0.3402)	0.4306 (0.3422)
绿色全要素生产率滞后一期	GTFPit-1	-0.0928* (0.0559)	-0.0840 (0.0563)
常数项	constant	0.1796 (0.1774)	0.1376 (0.1787)
门槛值	γ1 ( γ2)	0.4582	0.0096
样本数	observations	240	240
R2	R2	0.425	0.415

), ArticleFig(id=1241116664511648440, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=CN, label=表9, caption=

产业数字化影响绿色全要素生产率的门槛回归结果

, figureFileSmall=null, figureFileBig=null, tableContent=

变量名称	变量符号	门槛变量
		命令控制型环境规制强度ER1	市场激励型环境规制强度ER2
命令控制型环境规制强度小于等于门槛值0.4582	IDL×I(ER1≤γ1)	0.3623*** (0.0577)
命令控制型环境规制强度大于门槛值0.4582	IDL×I(ER1>γ1)	0.7771*** (0.1127)
市场激励型环境规制强度小于等于门槛值0.0096	IDL×I(ER2≤γ2)		0.2478*** (0.0826)
市场激励型环境规制强度大于门槛值0.0096	IDL×I(ER2>γ2)		0.5137*** (0.0620)
科技创新投入水平	TII	1.4002*** (0.3211)	1.3706*** (0.3246)
社会就业水平	EMP	0.2781 (0.2026)	0.2712 (0.2045)
人力资本水平	PCAP	5.9401*** (2.0439)	5.8162*** (2.0616)
经济发展水平	PGDP	0.0139** (0.0069)	0.0156** (0.0071)
政府干预程度	GOVERN	0.3372 (0.3402)	0.4306 (0.3422)
绿色全要素生产率滞后一期	GTFPit-1	-0.0928* (0.0559)	-0.0840 (0.0563)
常数项	constant	0.1796 (0.1774)	0.1376 (0.1787)
门槛值	γ1 ( γ2)	0.4582	0.0096
样本数	observations	240	240
R2	R2	0.425	0.415

), ArticleFig(id=1241116664738140883, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=EN, label=Table 10, caption=

Heterogeneity test results of different regions

, figureFileSmall=null, figureFileBig=null, tableContent=

变量名称	变量符号	(1)	(2)	(3)
		东部	中部	西部
产业数字化	IDL	0.2247* (0.1214)	0.7826*** (0.1474)	0.8055*** (0.0781)
科技创新投入水平	TII	1.7230** (0.6238)	0.8275 (0.4567)	1.2251** (0.5280)
社会就业水平	EMP	0.2970 (0.8099)	0.0983 (0.2844)	0.5688* (0.2711)
人力资本水平	PCAP	6.9630*** (1.7193)	11.2630*** (2.7247)	1.8259 (3.4414)
经济发展水平	PGDP	0.0142* (0.0068)	0.0406 (0.0400)	-0.0379 (0.0245)
政府干预程度	GOVERN	1.1959** (0.4199)	1.0357 (0.8548)	-0.5778 (0.4881)
常数项	constant	-0.1587 (0.4495)	-0.0389 (0.3950)	0.5340* (0.2596)
省份固定效应	province effect	控制	控制	控制
年份固定效应	year effect	控制	控制	控制
R2	R2	0.541	0.747	0.716
样本数	observations	99	72	99

), ArticleFig(id=1241116664889135844, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=CN, label=表10, caption=

分区域检验结果

, figureFileSmall=null, figureFileBig=null, tableContent=

变量名称	变量符号	(1)	(2)	(3)
		东部	中部	西部
产业数字化	IDL	0.2247* (0.1214)	0.7826*** (0.1474)	0.8055*** (0.0781)
科技创新投入水平	TII	1.7230** (0.6238)	0.8275 (0.4567)	1.2251** (0.5280)
社会就业水平	EMP	0.2970 (0.8099)	0.0983 (0.2844)	0.5688* (0.2711)
人力资本水平	PCAP	6.9630*** (1.7193)	11.2630*** (2.7247)	1.8259 (3.4414)
经济发展水平	PGDP	0.0142* (0.0068)	0.0406 (0.0400)	-0.0379 (0.0245)
政府干预程度	GOVERN	1.1959** (0.4199)	1.0357 (0.8548)	-0.5778 (0.4881)
常数项	constant	-0.1587 (0.4495)	-0.0389 (0.3950)	0.5340* (0.2596)
省份固定效应	province effect	控制	控制	控制
年份固定效应	year effect	控制	控制	控制
R2	R2	0.541	0.747	0.716
样本数	observations	99	72	99

), ArticleFig(id=1241116665048519416, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=EN, label=Table 11, caption=

Heterogeneity test results of industrialization degree

, figureFileSmall=null, figureFileBig=null, tableContent=

变量名称	变量符号	(1)	(2)
		高工业化程度	低工业化程度
产业数字化	IDL	0.2758** (0.1218)	0.6719*** (0.1048)
科技创新投入水平	TII	0.9828** (0.3624)	0.8507* (0.4793)
社会就业水平	EMP	0.2427 (0.2312)	0.2995 (0.3683)
人力资本水平	PCAP	6.6219*** (1.8846)	6.3324* (3.4015)
经济发展水平	PGDP	0.0296** (0.0128)	-0.0068 (0.0060)
政府干预程度	GOVERN	1.1267* (0.6262)	-0.3180 (0.3639)
常数项	constant	-0.0349 (0.1874)	0.3830 (0.2872)
省份固定效应	province effect	控制	控制
年份固定效应	year effect	控制	控制
R2	R2	0.545	0.682
样本数	observations	143	127

), ArticleFig(id=1241116665212097289, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=CN, label=表11, caption=

工业化程度异质性检验结果

, figureFileSmall=null, figureFileBig=null, tableContent=

变量名称	变量符号	(1)	(2)
		高工业化程度	低工业化程度
产业数字化	IDL	0.2758** (0.1218)	0.6719*** (0.1048)
科技创新投入水平	TII	0.9828** (0.3624)	0.8507* (0.4793)
社会就业水平	EMP	0.2427 (0.2312)	0.2995 (0.3683)
人力资本水平	PCAP	6.6219*** (1.8846)	6.3324* (3.4015)
经济发展水平	PGDP	0.0296** (0.0128)	-0.0068 (0.0060)
政府干预程度	GOVERN	1.1267* (0.6262)	-0.3180 (0.3639)
常数项	constant	-0.0349 (0.1874)	0.3830 (0.2872)
省份固定效应	province effect	控制	控制
年份固定效应	year effect	控制	控制
R2	R2	0.545	0.682
样本数	observations	143	127

), ArticleFig(id=1241116665358897948, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=EN, label=Table 12, caption=

Heterogeneity test results of public environmental concern

, figureFileSmall=null, figureFileBig=null, tableContent=

变量名称	变量符号	(1)公众环境关注度	(2)公众环境关注度
		高	低
		产业数字化	IDL	0.5239*** (0.1478)	0.3211** (0.1308)
科技创新投入水平	TII	1.4747*** (0.5119)	1.1502*** (0.3836)
社会就业水平	EMP	0.4441* (0.2417)	0.4839 (0.3559)
人力资本水平	PCAP	-2.4279 (5.6009)	4.5463 (3.0174)
经济发展水平	PGDP	0.0176 (0.0186)	-0.0013 (0.0078)
政府干预程度	GOVERN	1.7639** (0.7768)	0.1012 (0.4528)
常数项	constant	-0.2090 (0.2756)	0.1971 (0.2411)
省份固定效应	province effect	控制	控制
年份固定效应	year effect	控制	控制
R2	R2	0.660	0.479
样本数	observations	96	174

), ArticleFig(id=1241116665467949869, tenantId=1146029695717560320, journalId=1234093305789726721, articleId=1241116646513889664, language=CN, label=表12, caption=

公众环境关注度异质性检验结果

, figureFileSmall=null, figureFileBig=null, tableContent=

变量名称	变量符号	(1)公众环境关注度	(2)公众环境关注度
		高	低
		产业数字化	IDL	0.5239*** (0.1478)	0.3211** (0.1308)
科技创新投入水平	TII	1.4747*** (0.5119)	1.1502*** (0.3836)
社会就业水平	EMP	0.4441* (0.2417)	0.4839 (0.3559)
人力资本水平	PCAP	-2.4279 (5.6009)	4.5463 (3.0174)
经济发展水平	PGDP	0.0176 (0.0186)	-0.0013 (0.0078)
政府干预程度	GOVERN	1.7639** (0.7768)	0.1012 (0.4528)
常数项	constant	-0.2090 (0.2756)	0.1971 (0.2411)
省份固定效应	province effect	控制	控制
年份固定效应	year effect	控制	控制
R2	R2	0.660	0.479
样本数	observations	96	174

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