机构地区:[1]Institute of Geographic Sciences and Natural Resources Research,CAS,Beijing 100101,China [2]College of Resources and Environment,UCAS,Beijing 100049,China [3]Shandong University of Finanee and Economics,Jinan 250014,China [4]Inter national College of Busi ness and Tech no logy,Tianjin Un iversity of Technology,Tianjin 300384,China
出 处:《Journal of Geographical Sciences》2019年第12期1965-1980,共16页地理学报(英文版)
基 金:Strategic Priority Research Program of the Chinese Academy of Sciences,No.XDA19040401;Youth Fund for Humanities and Social Sciences of the Ministry of Education of China,No.16YJCZH040,No.14YJCZH078;National Natural Science Foundation of China,No.41571117,No.41871117;Social Science Foundation of Beijing,No.14CSB010;Shandong Taishan Scholar Youth Expert Support Program
摘 要:As information technology has been applied more broadly and transportation infrastructure has improved,persistent debate has existed as to the question of whether geographic distance influences enterprise financing costs(EFCs).Through mining big data regarding industrial enterprises and commercial bank branches(CBBs)in the Beijing-Tianjin-Hebei region,this paper conducts quantitative analysis of correlation between the EFCs and their distance to CBBs as well as the number of CBBs within a 1–5 km radius,and investigates how geographic factors affect EFCs.The results indicate the following:(1)In overall terms,the shorter the distance to CBBs and the greater the number of CBBs within a 1–5 km radius,the lower the EFCs.(2)Distance to CBBs and number of CBBs within a 1–5 km radius significantly influence state-owned and non-state-owned enterprises,with the effect on non-state-owned enterprises being more pronounced.(3)The EFCs in Beijing and Tianjin are not correlated with distance to CBBs,and negatively correlated to the number of CBBs within a 1–5 km radius;the EFCs in Hebei Province are positively correlated with distance to CBBs,and negatively correlated with the number of CBBs within a 1–5 km radius.(4)Distance to CBBs has a more significant impact on enterprises engaged in heavy industry and labor-intensive industries,while there is not much difference between different industries in terms of how the number of CBBs within a 1–5 km radius affects them.As information technology has been applied more broadly and transportation infrastructure has improved, persistent debate has existed as to the question of whether geographic distance influences enterprise financing costs(EFCs). Through mining big data regarding industrial enterprises and commercial bank branches(CBBs) in the Beijing-Tianjin-Hebei region, this paper conducts quantitative analysis of correlation between the EFCs and their distance to CBBs as well as the number of CBBs within a 1–5 km radius, and investigates how geographic factors affect EFCs. The results indicate the following:(1) In overall terms, the shorter the distance to CBBs and the greater the number of CBBs within a 1–5 km radius, the lower the EFCs.(2) Distance to CBBs and number of CBBs within a 1–5 km radius significantly influence state-owned and non-state-owned enterprises, with the effect on non-state-owned enterprises being more pronounced.(3) The EFCs in Beijing and Tianjin are not correlated with distance to CBBs, and negatively correlated to the number of CBBs within a 1–5 km radius; the EFCs in Hebei Province are positively correlated with distance to CBBs, and negatively correlated with the number of CBBs within a 1–5 km radius.(4) Distance to CBBs has a more significant impact on enterprises engaged in heavy industry and labor-intensive industries, while there is not much difference between different industries in terms of how the number of CBBs within a 1–5 km radius affects them.
关 键 词:FINANCIAL GEOGRAPHY enterprise FINANCING GEOGRAPHIC distance BEIJING-TIANJIN-HEBEI
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