Follow Suit: Imitative governance, resource inclination, and regional innovation efficiency
DOI:
https://doi.org/10.58567/rea02010002Abstract
Influenced by traditional notions of solidarity, when a province’s planning can be highly aligned with that of the central government, the province is perceived to be more collective and thus able to receive financial or resource favors from the central government. This consistency, as is often the case, reflected in doing the same thing as the central government. This situation may lead governors to ignore local economic performance and thus reduce regional innovation efficiency, as in the case of China’s Great Leap Forward. Likewise, it is possible to get better resources (energy or capital) by demonstrating managerial submissiveness, thus improving the regional innovation efficiency. Therefore, to verify the relationship between imitative governance and regional innovation efficiency, we collected relevant data from 31 major provincial administrative units in China, calculated the degree of imitative governance between provincial government work reports and central government work reports through text similarity, as well as utilized the SBM-DEA model to evaluate regional innovation efficiency. Meanwhile, we provide a new explanation of the phenomenon from the perspective of resource inclination. Finally, the empirical results show that imitative governance promotes local innovation efficiency and is moderated by resource inclination.
References
Ataay, A. (2020). CEO outsiderness and firm performance in an emerging economy: The moderating role of managerial discretion. J. Manag. Organ. 26(5), 798-814. https://doi.org/10.1017/jmo.2018.36
Barney, J.B., Ketchen, D.J., Wright, M. (2011). The Future of Resource-Based Theory: Revitalization or Decline? J. Manag. 37(5), 1299-1315. https://doi.org/10.1177/0149206310391805
Bel, R., Smirnov, V., Wait, A. (2018). Managing change: Communication, managerial style and change in organizations. Econ. Model. 69, 1-12. https://doi.org/10.1016/j.econmod.2017.09.001
Chang, Y.T., Zhang, N., Danao, D., Zhang, N. (2013). Environmental efficiency analysis of transportation system in China: A non-radial DEA approach. Energy Policy 58, 277-283. https://doi.org/10.1016/j.enpol.2013.03.011
Charnes, A., Cooper, W.W., Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research 2(6), 429-444. https://doi.org/https://doi.org/10.1016/0377-2217(78)90138-8
Chen, F., Ding, J., Li, M., & Wang, B. (2021). From self‐entertainment to being appreciated: how does social media transfer talent to business?. Accounting & Finance, 61(5), 6113-6146. https://doi.org/10.1111/acfi.12859
Chen, K.H., Kou, M.T., Fu, X.L. (2018). Evaluation of multi-period regional R&D efficiency: An application of dynamic DEA to China's regional R&D systems. Omega-Int. J. Manage. Sci. 74, 103-114. https://doi.org/10.1016/j.omega.2017.01.010
Chen, T.J., Chen, H.M., Ku, Y.H. (2012). Resource dependency and parent-subsidiary capability transfers. J. World Bus. 47(2), 259-266. https://doi.org/10.1016/j.jwb.2011.04.013
Cohen, L., Malloy, C., Nguyen, Q. (2020). Lazy Prices. J. Financ. 75(3), 1371-1415. https://doi.org/10.1111/jofi.12885
Cong, D., Liang, L.L., Jing, S.X., Han, Y.M., Geng, Z.Q., Chu, C. (2021). Energy supply efficiency evaluation of integrated energy systems using novel SBM-DEA integrating Monte Carlo. Energy 231, 10. https://doi.org/10.1016/j.energy.2021.120834
Deng, G.Y., Li, L., Song, Y.N. (2016). Provincial water use efficiency measurement and factor analysis in China: Based on SBM-DEA model. Ecol. Indic. 69, 12-18. https://doi.org/10.1016/j.ecolind.2016.03.052
Ding, J., Liu, B., & Shao, X. (2022). Spatial effects of industrial synergistic agglomeration and regional green development efficiency: Evidence from China. Energy Economics, 112, 106156. https://doi.org/10.1016/j.eneco.2022.106156
Du, K.R., Cheng, Y.Y., Yao, X. (2021). Environmental regulation, green technology innovation, and industrial structure upgrading: The road to the green transformation of Chinese cities. Energy Econ. 98, 10. https://doi.org/10.1016/j.eneco.2021.105247
Giachetti, C., Li Pira, S. (2022). Catching up with the market leader: Does it pay to rapidly imitate its innovations? Res. Policy 51(5), 14. https://doi.org/10.1016/j.respol.2022.104505
Gore, L.L.P. (2019). The Communist Party-Dominated Governance Model of China: Legitimacy, Accountability, and Meritocracy. Polity 51(1), 161-194. https://doi.org/10.1086/700615
Hu, J. (2023). Synergistic effect of pollution reduction and carbon emission mitigation in the digital economy. Journal of Environmental Management, 337, 117755. https://doi.org/10.1016/j.jenvman.2023.117755
Hu, J., Zhang, H., & Irfan, M. (2023). How does digital infrastructure construction affect low-carbon development? A multidimensional interpretation of evidence from China. Journal of Cleaner Production, 396, 136467. https://doi.org/10.1016/j.jclepro.2023.136467
Ji, Y.H., Lei, Y.L., Li, L., Zhang, A., Wu, S.M., Li, Q. (2021). Evaluation of the implementation effects and the influencing factors of resource tax in China. Resour. Policy 72, 9. https://doi.org/10.1016/j.resourpol.2021.102126
Kim, D.H., Wu, Y.C., Lin, S.C. (2018). Heterogeneity in the effects of government size and governance on economic growth. Econ. Model. 68, 205-216. https://doi.org/10.1016/j.econmod.2017.07.014
Kozlenkova, I.V., Samaha, S.A., Palmatier, R.W. (2014). Resource-based theory in marketing. J. Acad. Mark. Sci. 42(1), 1-21. https://doi.org/10.1007/s11747-013-0336-7
Li, Z., Li, Y.B., Shao, S.S. (2019). Analysis of Influencing Factors and Trend Forecast of Carbon Emission from Energy Consumption in China Based on Expanded STIRPAT Model. Energies 12(16), 14. https://doi.org/10.3390/en12163054
Lin, X.Y., Zhu, X.P., Han, Y.M., Geng, Z.Q., Liu, L. (2020). Economy and carbon dioxide emissions effects of energy structures in the world: Evidence based on SBM-DEA model. Sci. Total Environ. 729, 9. https://doi.org/10.1016/j.scitotenv.2020.138947
Liu, B., Ju, T., Bai, M., Yu, C.F. (2021). Imitative innovation and financial distress risk: The moderating role of executive foreign experience. Int. Rev. Econ. Financ. 71, 526-548. https://doi.org/10.1016/j.iref.2020.09.021
Maiti, M., Krakovich, V., Shams, S.M.R., Vukovic, D.B. (2020). Resource-based model for small innovative enterprises. Manag. Decis. 58(8), 1525-1541. https://doi.org/10.1108/md-06-2019-0725
Marquis, C., Qiao, K.Y. (2020). Waking from Mao's Dream: Communist Ideological Imprinting and the Internationalization of Entrepreneurial Ventures in China. Adm. Sci. Q. 65(3), 795-830. https://doi.org/10.1177/0001839218792837
Mol, M.J., Kotabe, M. (2011). Overcoming Inertia: Drivers of the Outsourcing Process. Long Range Plan. 44(3), 160-178. https://doi.org/10.1016/j.lrp.2010.12.002
Ouyang, X.L., Li, Q., Du, K.R. (2020). How does environmental regulation promote technological innovations in the industrial sector? Evidence from Chinese provincial panel data. Energy Policy 139, 10. https://doi.org/10.1016/j.enpol.2020.111310
Ployhart, R.E. (2021). Resources for What? Understanding Performance in the Resource-Based View and Strategic Human Capital Resource Literatures. J. Manag. 47(7), 1771-1786. https://doi.org/10.1177/01492063211003137
Shen, W.T., Yang, C., Huang, B.Y. (2022). Impact of Managerial Discretion "Stranglehold" on Enterprises Investment Efficiency: Based on Heterogeneous Stochastic Frontier Model. Emerg. Mark. Financ. Trade 58(13), 3711-3725. https://doi.org/10.1080/1540496x.2022.2068410
Shi, J.M., Katehakis, M.N., Melamed, B. (2013). Martingale methods for pricing inventory penalties under continuous replenishment and compound renewal demands. Ann. Oper. Res. 208(1), 593-612. https://doi.org/10.1007/s10479-012-1130-5
Shih, V., Adolph, C., Liu, M.X. (2012). Getting Ahead in the Communist Party: Explaining the Advancement of Central Committee Members in China. Am. Polit. Sci. Rev. 106(1), 166-187. https://doi.org/10.1017/s0003055411000566
Shuai, S., Fan, Z. (2020). Modeling the role of environmental regulations in regional green economy efficiency of China: Empirical evidence from super efficiency DEA-Tobit model. J. Environ. Manage. 261, 8. https://doi.org/10.1016/j.jenvman.2020.110227
Wang, D.P., Du, K.R., Zhang, N. (2022). Measuring technical efficiency and total factor productivity change with undesirable outputs in Stata. Stata J. 22(1), 103-124. https://doi.org/10.1177/1536867x221083886
Wang, J.X., Lin, J.T., Feng, K.S., Liu, P., Du, M.X., Ni, R.J., Chen, L.L., Kong, H., Weng, H.J., Liu, M.Y., Baiocchi, G., Zhao, Y., Mi, Z.F., Cao, J., Hubacek, K. (2019). Environmental taxation and regional inequality in China. Sci. Bull. 64(22), 1691-1699. https://doi.org/10.1016/j.scib.2019.09.017
Wang, L. (2023). Political cycle and effective corporate tax rate: evidence from China. Applied Economics, 1-14. https://doi.org/10.1080/00036846.2023.2174937
Wu, J.D., Li, N., Shi, P.J. (2014). Benchmark wealth capital stock estimations across China's 344 prefectures: 1978 to 2012. China Econ. Rev. 31, 288-302. https://doi.org/10.1016/j.chieco.2014.10.008
Zhang, J., Du, Z.L., Fu, L.Q., Han, Y.M., Zheng, W., Yu, F.H., Chen, H.M., Feng, L., Li, Y.Q., Ping, W.Y. (2021). Novel anaerobic digestion and carbon dioxide emissions efficiency analysis of food waste treatment based on SBM-DEA model. J. Clean Prod. 328, 11. https://doi.org/10.1016/j.jclepro.2021.129591
Zor, S. (2023). Conservation or revolution? The sustainable transition of textile and apparel firms under the environmental regulation: Evidence from China. Journal of Cleaner Production, 382, 135339. https://doi.org/10.1016/j.jclepro.2022.135339
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