Abstract
The study was designed to evaluate the impact of differentiated technological innovation efficiencies of industrial enterprises on the local emissions of environmental pollutants in Anhui province, China, during the period of 2012–2016. The econometric models of DEA and SEM-PLS and Malmquist index are used to explore the potential impacts of differentiated technological innovation efficiencies of industrial enterprises on the local emissions of environmental pollutants in Anhui province. After an initial analysis of SEM-PLS model, the models of DEA and Malmquist index are used to evaluate the differentiated degrees and dynamic development levels of local technological innovation efficiencies of industrial enterprises in different regions of Anhui province. With these analyses, the study presents three main results as follows. There is a positive correlation between the technological innovation efficiencies of industrial enterprises and the technological performance levels of environmental disposal. Meanwhile, there is a large gap among the environmental disposing performances of industrial enterprises in different regions of Anhui province. There is also a large gap between the expected and actual technological performances of industrial enterprises’ environmental disposal, according to the results of SEM-PLS analysis. Furthermore, there are several obvious characteristics of geographical distribution in the impact of differentiated technological innovation efficiencies of industrial enterprises on local environmental pollutant emissions observed from the results of the DEA and Malmquist index models. However, it is not consistent with the overall provincial development trend and regional distribution pattern of industrial economics in Anhui province over the period of 2012–2016. Under the rapid development of social economics and modern technological advance, there is a weak impact of differentiated technological innovation efficiency on the technological performance of industrial environmental disposal in different regions of Anhui province. Meanwhile, the environmental disposal capacity of enterprises’ technological innovation become declining too. Finally, some countermeasures and policy suggestions are put forward based on the investigation and comprehensive analyses of the DEA and SEM-PLS and Malmquist index models.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Anhui Provincial Bureau of Statistics (2013) Anhui Statistical Yearbook 2013. China Statistics Press, Beijing (in Chinese)
Anhui Provincial Bureau of Statistics (2014) Anhui Statistical Yearbook2014. China Statistics Press, Beijing (in Chinese)
Anhui Provincial Bureau of Statistics (2015) Anhui Statistical Yearbook 2015. China Statistics Press, Beijing (in Chinese)
Anhui Provincial Bureau of Statistics (2016) Anhui Statistical Yearbook 2016. China Statistics Press, Beijing (in Chinese)
Anhui Provincial Bureau of Statistics (2017) Anhui Statistical Yearbook2017. China Statistics Press, Beijing (in Chinese)
Bollen KA, Long JS (1993) Testing structural equation models. Sage Publications, Newbury Park https://us.sagepub.com/en-us/nam/testing-structural-equation-models/book3893
Bruneau A, Landry C, Giraudo M, Douville M, Brodeur P, Boily M, Gagnon P, Houde M (2016) Integrated spatial health assessment of yellow perch (Perca flavescens) populations from the St. Lawrence River (QC, Canada), part B: cellular and transcriptomic effects. Environ Sci Pollut Res Int. 23(18):18211–18221. https://doi.org/10.1007/s11356-016-7001-x
Chen TM, Gokhale J, Shofer S, Kuschner WG (2007) Outdoor air pollution: nitrogen dioxide, sulfur dioxide, and carbon monoxide health effects. Am J Med Sci. 333(4):249–256. https://doi.org/10.1097/MAJ.0b013e31803b900f
Choudri BS, Charabi Y, Ahmed M (2018) Health effects associated with wastewater treatment, reuse and disposal. Water Environ Res. 90(10):1759–1776. https://doi.org/10.2175/106143018X15289915807425
Cruz-Martinez L, Smits JE, Fernie K (2015) Stress response, biotransformation effort, and immunotoxicity in captive birds exposed to inhaled benzene, toluene, nitrogen dioxide, and sulfur dioxide. Ecotoxicol Environ Saf. 112:223–230. https://doi.org/10.1016/j.ecoenv.2014.10.016
Feng ZJ (2013) Research on green innovation efficiency of Chinese Industrial Enterprises. China Sci Tech Forum 2:82–88. https://doi.org/10.3969/j.issn.1002-6711.2013.02.015 (in Chinese)
Graafland JJ (2016) Price competition, short-termism and environmental performance. J Clean Prod 116(3):125–134. https://doi.org/10.1016/j.jclepro.2015.12.045
Greenberg N, Carel RS, Derazne E, Tiktinsky A, Tzur D, Portnov BA (2017) Modeling long-term effects attributed to nitrogen dioxide (NO2) and sulfur dioxide (SO2) exposure on asthma morbidity in a nationwide cohort in Israel. J Toxicol Environ Health A. 80(6):326–337. https://doi.org/10.1080/15287394.2017.1313800
Hassan NA, Hashim Z, Hashim JH (2016) Impact of climate change on air quality and public health in urban areas. Asia Pac J Public Health 28(2 Suppl):38S–48S. https://doi.org/10.1177/1010539515592951
Hu XJ, Luo LH (2016) Evaluation of provincial regional innovation efficiency based on static and dynamic perspectives - an empirical analysis based on Jiangsu Province. Sci Tech Manage Res 13:47–52. https://doi.org/10.3969/j.issn.1000-7695.2016.13.009 (in Chinese)
Jiang B, Zhou XM, Li J (2015) Regional differences in input-output efficiency of marine science and technology in China-based on Super Efficiency DEA Window-Malmquist Index. Sci Tech Manag Res 10:49–53. https://doi.org/10.3969/j.issn.1000-7695.2015.10.011 (in Chinese)
Jin W, Zhang H, Liu S, Zhang H (2019) Technological innovation, environmental regulation, and green total factor efficiency of industrial water resources. J Clean Prod 211:61–69. https://doi.org/10.1016/j.jclepro.2018.11.172
Klassen RD, Mclaughin CP (1996) The impact of environmental management on firm performance. Manag Sci 42(8):1199–1214. https://doi.org/10.1287/mnsc.42.8.1199
Li PZ, Jian LR, Liu Y (2019) Research on regional high-tech industry innovation efficiency evaluation based on DEA and Malmquist Index. Ind Tech Econ 1:27–34. https://doi.org/10.3969/j.issn.1004-910X.2019.01.004 (in Chinese)
Liu Y, Zhou Y, Ma J, Bao W, Li J, Zhou T, Cui X, Peng Z, Zhang H, Feng M, Yuan Y, Chen Y, Huang X, Li Y, Duan Y, Shi T, Jin L, Wu L (2017) Inverse association between ambient sulfur dioxide exposure and semen quality in Wuhan, China. Environ Sci Technol. 51(21):12806–12814. https://doi.org/10.1021/acs.est.7b03289
Mousavi SE, Amini H, Heydarpour P, Amini Chermahini F, Godderis L (2019) Air pollution, environmental chemicals, and smoking may trigger vitamin D deficiency: evidence and potential mechanisms. Environ Int. 122:67–90. https://doi.org/10.1016/j.envint.2018.11.052
Noailly J (2012) Improving the energy efficiency of buildings: the impact of environmental policy on technological innovation. Energy Econ 34(3):795–806. https://doi.org/10.1016/j.eneco.2011.07.015
Qian L, Xiao RQ, Chen ZW (2015) Environmental constraints, technology gap and enterprise innovation efficiency - an empirical study based on Chinese inter-provincial industrial enterprises. Stud Sci Sci 33(3):378–389. https://doi.org/10.3969/j.issn.1003-2053.2015.03.008 (in Chinese)
Qu X, Zhao Y, Yu R, Li Y, Falzone C, Smith G, Ikehata K (2016) Health effects associated with wastewater treatment, reuse, and disposal. Water Environ Res. 88(10):1823–1855. https://doi.org/10.2175/106143016X14696400495776
Ramanathan R, Poomkaew B, Nath P (2014) The impact of organizational pressures on the local emissions of environmental pollutants of Firms. Bus Ethics A Eur Rev 23(2):169–182. https://doi.org/10.1111/beer.12042
Tseng FM, Chiu YJ, Chen JS (2009) Measuring business performance in the high-tech manufacturing industry: a case study of Taiwan’s large-sized TFT-LCD panel companies. Omega 37(3):686–697. https://doi.org/10.1016/j.omega.2007.07.004
Wan L, Luo B, Li T, Wang S, Liang L (2016) Effects of technological innovation on eco-efficiency of industrial enterprises in china. Nankai Bus Rev Int 6(3):226–239. https://doi.org/10.1108/NBRI-01-2015-0003
Wang S, Wu P (2015) Reforming the mode of industrial pollution control through interdisciplinary collaboration. Environ Sci Technol 49(13):7522–7523. https://doi.org/10.1021/acs.est.5b02021
Wang J, Wu Q, Liu J, Yang H, Yin M, Chen S, Guo P, Ren J, Luo X, Linghu W, Huang Q (2019) Vehicle emission and atmospheric pollution in China: problems, progress, and prospects. PeerJ 7:e6932. https://doi.org/10.7717/peerj.6932
Wilhelm S, Henneberg A, Köhler HR, Rault M, Richter D, Scheurer M, Suchail S, Triebskorn R (2017) Does wastewater treatment plant upgrading with activated carbon result in an improvement of fish health? Aquat Toxicol. 192:184–197. https://doi.org/10.1016/j.aquatox.2017.09.017
Xiang XD, Lin J (2018) Research on China’s industrial total factor productivity evaluation under environmental regulation based on global network DEA-Malmquist index. Sci Tech Manag Res 6:60–68. https://doi.org/10.3969/j.issn.1000-7695.2018.06.010 (in Chinese)
Xiao RQ, Wang ZJ, Qian L (2014) Research on technology innovation efficiency of Chinese inter-provincial industrial enterprises under environmental constraints. Manage Rev 26(6):56–65. https://doi.org/10.14120/j.cnki.cn11-5057/f.2014.06.040 (in Chinese)
Yan GQ, Sun Q, Chen C, Zhong HS, Ren JX (2008) Research on the measurement index system of innovation level of national high-tech industrial development zone. China Soft Sci 4:141–148. https://doi.org/10.3969/j.issn.1002-9753.2008.04.018 (in Chinese)
Yang W, Xue HJ (2011) Research on regional differences of industrial technology independent innovation ability. China Ind Econ 11:68–76. https://doi.org/10.19581/j.cnki.ciejournal.2010.11.007 (in Chinese)
Yang H, Zhang L (2018) Research on the local emissions of environmental pollutants evaluation of Beijing-Tianjin-Hebei region based on data envelopment (DEA) analysis. Sci Tech Prog Policy 35(14):43–49. https://doi.org/10.6049/kjjbydc.2018010810 (in Chinese)
Yang LS, Wang Q, Chai X (2018) Research on enterprise green sustainable innovation efficiency based on SBM-DEA Model. J Yunnan Univ Financ Econ 5:102–112. https://doi.org/10.16537/j.cnki.jynufe.000316 (in Chinese)
Zhang HC, Li F, Zhang JP (2017) Evaluation of two-stage technology innovation efficiency of resource-based regional industrial enterprises - based on the perspective of green growth. Sci Tech Manag Res 8:69–76. https://doi.org/10.3969/j.issn.1000-7695.2017.08.010 (in Chinese)
Zhou ZY (2016) Improvement of environmental DEA model and its application in urban environmental performance evaluation. Sci Tech Prog Policy 33(4):112–118. https://doi.org/10.6049/kjjbydc.2015100236 (in Chinese)
Zhu Y, Zilong W, Shilei Q, Lingling Z (2019) Effects of environmental regulations on technological innovation efficiency in China’s industrial enterprises: a spatial analysis. Sustainability 11(7):2186. https://doi.org/10.3390/su11072186
Acknowledgment
We are grateful to the anonymous reviewers for their constructive comments and suggestions.
Funding
This study is jointly funded by Anhui Science and Technology Innovation Strategy and Soft Science Research Project (No.201806a02020028), Anhui province Innovation and Development Research Project (No.2018CXF163), and Major Project of Horizontal Cooperation between Fuyang Municipal Government and Fuyang Normal University (No. XDHX201725).
Author information
Authors and Affiliations
Corresponding authors
Additional information
Responsible editor: Philippe Garrigues
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Zhang, K., Jiang, W., Zhang, S. et al. The impact of differentiated technological innovation efficiencies of industrial enterprises on the local emissions of environmental pollutants in Anhui province, China, from 2012 to 2016. Environ Sci Pollut Res 26, 27953–27970 (2019). https://doi.org/10.1007/s11356-019-06032-x
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11356-019-06032-x