|
|
|
| The Driving Path for Low-carbon Transformation of Resource-dependent Cities under the TOE Framework:An fsQCA Research Based on 108 Resource-dependent Cities in China |
| Sun Xiumei,Yan Su |
| (Business school, Shandong University of Technology, Zibo 255000, China) |
|
|
|
|
Abstract As a basic element of human life and social development, energy is an important hub in the modern energy supply system and an important guarantee for social stability and development. At present, the world is facing the severe problem of resource shortage. It is urgent to deal with the relationship between resource utilization and environmental protection to ensure the sustainable development of economy, but the development of resource-dependent cities lags far behind, and the environment deteriorates seriously. #br#This study deconstructs the TOE theory framework into seven antecedents at three levels as follows: technical level, organizational level and environmental level, and takes 108 resource-dependent cities in China from 2015 to 2020 as the research object. The driving path of low-carbon transformation of resource-dependent cities is studied from the perspective of configuration by applying qualitative comparative analysis of fuzzy sets.#br#The study reaches four conclusions. (1) The promotion condition of low-carbon transition of resource-dependent cities is not any single factor, and it requires the synergy of technology, organization and environment. (2) Government support and environmental regulation play important roles in promoting the low-carbon transition of resource-dependent cities. (3) Better low-carbon transition effect can be produced by six key configuration paths which refer to the organization-environment co-driving, policy-driven resource transformation, government-led, technology-organization interaction, technology-environment interaction and environment-oriented organization assistance. (4) The resource-dependent cities should improve the efficiency of resource allocation. In the transition stage, not all the multi-input will necessarily bring multi-output. From the configuration path of high-level low-carbon transformation of resource-dependent cities, it is found that there are potential substitutional relationships among technology, organization and environment. This paper not only enriches the theory of factor substitution, but also summarizes the differential driving path of low-carbon transformation of resource-dependent cities from the multi-dimensional interactive perspective. It further provides policy suggestions and useful references for the low-carbon transition of resource-dependent cities at different stages of development. The following implications are proposed. (1) The local governments of resource-dependent cities should focus on the driven effects of both the internal and external synergy, and make full use of regional favorable conditions. (2) It is essential to break through the barrier between technology and management, strengthen the integration of green technology innovation and government support. (3) The policy of “fragmentation” should be integrated and coordinated. (4) Rational allocation of resources shall be achieved by stages. To sum up, the three levels and seven antecedents of TOE framework all play indispensable roles in the low-carbon transition of resource-dependent cities, and they are always in the process of interaction through mutual promotion, internal and external synergy and other internal relations to promote the transformation of resource-dependent cities in accordance with their own actual conditions.#br#The theoretical significance of this study lies in three aspects. Firstly, instead of focusing on the impact of a single factor like previous studies, this study breaks the limitation of the single factor and constructs the TOE research framework for the low-carbon transition of resource-dependent cities, and emphatically analyzes the interaction of different influencing factors and the driving role of the combination of factors; given the characteristics of low-carbon transition of resource-dependent cities, this paper selects the important variables affecting low-carbon transition from three aspects of technology, organization and environment, which enriches the research of TOE framework in the field of low-carbon transition. Secondly, it provides a new perspective for the study on low-carbon transition of resource-dependent cities, and by applying the fsQCA method, it integrates the elements of technology, organization and environment systematically, and realizes the linkage and matching among the multi-level elements. Finally, it verifies the cause-and-effect relationship among the conditional factors of low-carbon transition in resource-dependent cities and the substitution relationship among the multi-level factors in different configurations, and provides an optional low-carbon transition path for resource-dependent cities with different conditions.#br#
|
|
Received: 22 July 2022
|
|
|
|
|
|
[1] 李慧, 涂家豪. 多层级视角下能源低碳转型因素组态研究——基于我国30个省域的模糊集定性比较分析 [J]. 技术经济, 2020, 39(8): 152-160.
[2] MUHAMMAD B, KHAN M K, KHAN M I, et al. Impact of foreign direct investment, natural resources, renewable energy consumption, and economic growth on environmental degradation: evidence from BRICS, developing, developed and global countries [J]. Environ Sci Pollut Res, 2021, 28(17): 21789-21798.
[3] 董晓林, 张晔. 自然资源依赖、政府干预与数字普惠金融发展——基于中国273个地市级面板数据的实证分析 [J]. 农业技术经济, 2021, 40(1): 117-128.
[4] PRADHAN B K, GHOSH J. A computable general equilibrium (CGE) assessment of technological progress and carbon pricing in India's green energy transition via furthering its renewable capacity [J]. Energy Econ, 2022, 106(10).
[5] 文淑惠, 陈灿. 考虑环境因素的财政支持资源型城市转型效率研究 [J]. 地域研究与开发, 2019, 38(6): 52-57.
[6] BAI Y P, DENG X Z, JIANG S J, et al. Exploring the relationship between urbanization and urban eco-efficiency: Evidence from prefecture-level cities in China [J]. J Clean Prod, 2018, 195:1487-1496.
[7] 张逸昕, 张杰. 创新驱动、政府规制与资源型城市转型效率研究——基于Super-SBM模型的实证分析 [J]. 河南师范大学学报(哲学社会科学版), 2020, 47(2): 37-44.
[8] 庞明川, 宁赋宪. 经济转型视域下的地方政府投资与资源错配——环境规制的门槛效应及国企依赖度的调节效应 [J]. 西部论坛, 2021, 31(6): 1-17.
[9] 曾胜, 张明龙. 绿色投资、碳排放强度与经济高质量发展——采用空间计量模型的非线性关系检验 [J]. 西部论坛, 2021, 31(5): 69-84.
[10] 张司飞, 王琦. 资源型产业集聚、要素扭曲配置与技术创新 [J]. 工业技术经济, 2020, 39(6): 29-37.
[11] 庄贵阳, 潘家华, 朱守先. 低碳经济的内涵及综合评价指标体系构建 [J]. 经济学动态, 2011, 52(1): 132-136.
[12] 陈诗一. 中国各地区低碳经济转型进程评估 [J]. 经济研究, 2012, 47(8): 32-44.
[13] ZHANG W H, ZHANG J H, LI R. Assessment about development level of low-carbon economy in resource-based city[C].The 2nd International Conference on Renewable Energy and Environmental Technology (REET),2014.
[14] 王学军, 侯睿, 王玲. 基于TOPSIS法的资源型城市低碳转型评价体系研究——以焦作市为例 [J]. 生态经济, 2015, 31(11): 42-46.
[15] CHAPMAN A, SHIGETOMI Y, OHNO H, et al. Evaluating the global impact of low-carbon energy transitions on social equity [J]. Environ Innov Soc Trans, 2021, 40:332-347.
[16] 邵帅, 范美婷, 杨莉莉. 经济结构调整、绿色技术进步与中国低碳转型发展——基于总体技术前沿和空间溢出效应视角的经验考察 [J]. 管理世界, 2022, 38(2): 46-69.
[17] 徐胜, 司登奎. 结构转型、能源效率对低碳经济的异质性影响——基于省际数据的面板协整分析 [J]. 软科学, 2014, 28(7): 6-10,39.
[18] 吴巧生, 李慧. 长江中游城市群能源效率评价研究 [J]. 中国人口·资源与环境, 2016, 26(12): 140-146.
[19] 李梦雅, 严太华. 基于DEA模型和信息熵的我国资源型城市产业转型效率评价——以全国40个地市级资源型城市为例 [J]. 科技管理研究, 2018, 38(3): 86-93.
[20] WANG K Y, WU M, SUN Y, et al. Resource abundance, industrial structure, and regional carbon emissions efficiency in China [J]. Resour Policy, 2019, 60:203-314.
[21] ZHANG H L, SHEN L, ZHONG S, et al. Economic structure tansformation and low-carbon development in energy-rich Cities: the case of the contiguous area of shanxi and shaanxi provinces, and iInner mongolia autonomous region of China [J]. Sustainability, 2020, 12(5): 14.
[22] 张复明. 资源的优势陷阱和资源型经济转型的途径 [J]. 中国人口·资源与环境, 2002, 12(4): 10-15.
[23] 杨明华, 周娜. 资源型区域经济可持续发展的途径:特色产业集群的升级与转型 [J]. 科技进步与对策, 2009, 26(17): 37-40.
[24] WU J H, HUANG X H, GAO Y. The Study on the low-carbon transformation and sustainable development of the resource-based cities[C].The Proceedings of the 2nd International Conference on Energy and Environmental Protection (ICEEP 2013),2013.
[25] FRAGKOS P, VAN SOEST H L, SCHAEFFER R, et al. Energy system transitions and low-carbon pathways in Australia, Brazil, Canada, China, EU-28, India, Indonesia, Japan, Republic of Korea, Russia and the United States [J]. Energy, 2021, 216:13.
[26] 黎江平, 姚怡帆, 叶中华. TOE框架下的省级政务大数据发展水平影响因素与发展路径——基于fsQCA实证研究 [J]. 情报杂志, 2022, 41(1): 200-207.
[27] 张诗卉, 李明煜, 王灿,等. 中国省级碳排放趋势及差异化达峰路径 [J]. 中国人口·资源与环境, 2021, 31(9): 45-54.
[28] LIU Y J, DONG F. How technological innovation impacts urban green economy efficiency in emerging economies: a case study of 278 Chinese cities [J]. Resour Conserv Recycl, 2021, 169:105534.
[29] AHMAD M, ISIK C, JABEEN G, et al. Heterogeneous links among urban concentration, non-renewable energy use intensity, economic development, and environmental emissions across regional development levels [J]. Sci Total Environ, 2021, 765:144527.
[30] 范丹, 刘婷婷. 低碳城市试点政策对全要素能源效率的影响机制和异质性研究 [J]. 产业经济评论, 2022, 10(2): 93-111.
[31] MOHSIN M, HANIF I, TAGHIZADEH-HESARY F, et al. Nexus between energy efficiency and electricity reforms: a DEA-based way forward for clean power development [J]. Energy Policy, 2021, 149:112052.
[32] DU K R, LI J L. Towards a green world: How do green technology innovations affect total-factor carbon productivity [J]. Energy Policy, 2019, 131:240-250.
[33] 古惠冬, 杨维光, 陈文捷. 绿色技术创新对城市碳减排的效应研究 [J]. 学术探索, 2022,30(3): 120-132.
[34] DONEGAN M, LESTER T W, LOWE N. Striking a Balance:a national assessment of economic development incentives [J]. Urban Aff Rev, 2021, 57(3): 794-819.
[35] YANG X L, HE L Y, XIA Y F, et al. Effect of government subsidies on renewable energy investments:the threshold effect [J]. Energy Policy, 2019, 132:156-166.
[36] 吴建祖, 范会玲. 基于组态视角的企业绿色创新驱动模式研究 [J]. 研究与发展管理, 2021, 33(4): 41-53.
[37] MUHAMAD G M, HESHMATI A, KHAYYAT N T. How to reduce the degree of dependency on natural resources [J]. Resour Policy, 2021, 72:102047.
[38] HU H, RAN W J, WEI Y C, et al. Do energy resource curse and heterogeneous curse exist in provinces? evidence from China [J]. Energies, 2020, 13(17): 25.
[39] 董利红, 严太华. 资源依赖度对中国区域经济增长影响研究 [J]. 重庆大学学报(社会科学版), 2021, 27(5): 1-12.
[40] 张艳, 张雨, 孙哲远. 资源依赖、政府治理能力对资源型城市绿色经济转型的影响 [J]. 南京财经大学学报, 2022,40(2):76-85.
[41] DU K R, CHENG Y Y, YAO X. Environmental regulation, green technology innovation, and industrial structure upgrading:the road to the green transformation of Chinese cities [J]. Energy Econ, 2021, 98(10).
[42] 高红贵, 许莹莹, 朱于珂. 命令控制型环境规制对碳市场价格的影响——来自中央环保督察的准自然实验 [J]. 中国地质大学学报(社会科学版), 2022, 22(3): 54-66.
[43] FENG Y C, WU H Y. How does industrial structure transformation affect carbon emissions in China: the moderating effect of financial development [J]. Environ Sci Pollut Res, 2022, 29(9): 13466-13477.
[44] 赵玉焕, 钱之凌, 徐鑫. 碳达峰和碳中和背景下中国产业结构升级对碳排放的影响研究 [J]. 经济问题探索, 2022, 43(3): 87-105.
[45] MTAR K, BELAZREG W. On the nexus of innovation, trade openness, financial development and economic growth in European countries: new perspective from a GMM panel VAR approach [J]. International Journal of Finance & Economics, 2023, 28(1): 766-791.
[46] 陈国福, 唐炎钊. 经济高质量发展的内外双循环驱动因素和政府竞争的影响机制 [J]. 经济问题探索, 2022, 43(1): 1-14.
[47] FISS P C. Building better causal theories: a fuzzy set approach to typologies in organization research [J]. Acad Manage J, 2011, 54(2): 393-420.
[48] FURNARI S, CRILLY D, MISANGYI V F, et al. Capturing causal complexity: heuristics for configurational theorizing [J]. Academy of Management Review, 2021, 46(4): 778-799.
[49] STOKKE O S. Qualitative comparative analysis, shaming, and international regime effectiveness [J]. Journal of Business Research, 2007, 60(5): 501-511.
[50] 宫晓辰, 孙涛. 节能减排政策工具降低碳强度影响机制研究——基于30省(市、自治区)数据的模糊集定性比较分析 [J]. 城市问题, 2021, 40(7): 23-32.
[51] 王飞航, 本连昌. 创新生态系统视角下区域创新绩效提升路径研究 [J]. 中国科技论坛, 2021, 38(3): 154-163.
[52] 李江龙, 徐斌. “诅咒”还是“福音”:资源丰裕程度如何影响中国绿色经济增长[J]. 经济研究, 2018, 53(9): 151-167.
[53] 李婉红, 李娜. 自然资源禀赋、市场化配置与产业结构转型——来自116个资源型城市的经验证据 [J]. 现代经济探讨, 2021, 40(8): 52-63.
[54] 李玥萤, 黄丽君. 财政环保支出对碳减排的空间溢出效应分析 [J]. 统计与决策, 2022, 38(15): 154-158.
[55] 段忠贤, 吴鹏. 科技资源配置效率影响因素组态与路径研究——基于中国内地30个省市的QCA分析 [J]. 科技进步与对策, 2021, 38(22): 11-18.
[56] VERWEIJ S. Set-theoretic methods for the social sciences: a guide to qualitative comparative analysis [J].International Journal of Social Research Methodology,2013, 16(2):165-169.
[57] 张明, 杜运周. 组织与管理研究中QCA方法的应用:定位、策略和方向 [J]. 管理学报, 2019, 16(9): 1312-1323.
|
|
|
|
