Analysis of labor resources wastage in China’s real estate brokerage: from the perspective of opportunity costs
Abstract
Real estate brokerage has experienced the rapid growth over the past two decades in China, with a significant increase of employees. In particular, in the megacities like Beijing, the growth of employees exceeds the growth of real estate transaction volume. This may lead to the wastage of labor resources. In this regard, the optimal employee size (OES) in China’s real estate brokerage is proposed from the perspective of opportunity costs, which include both under-size and over-size costs. In the proposed OES models, a real estate brokerage firm makes the optimal decisions of number of employees by minimizing expected opportunity costs. In addition, an iterative algorithm is employed to obtain the optimal employee size in different scenarios. The result reveals that high profit gained from the business does attract more employees than what is needed. By addressing various scenarios based on the game model, it is found that asymmetric competition, the increase of market participants, and demand fluctuations also contribute to the labor resources wastage in real estate brokerage industry. The theoretical analysis results are verified by taking Beijing as the case study. Finally, suggestions for reducing labor resources wastage in real estate brokerage of China are provided.
Keyword : real estate brokerage, labor resource, opportunity cost, optimal employee size
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Allen, M. T., Benefield, J. D., & Rutherford, R. C. (2021). Co-listing strategies: Better transaction outcomes? The Journal of Real Estate Finance and Economics. https://doi.org/10.1007/s11146-021-09858-w
Barwick, P. J., & Pathak, P. A. (2015). The costs of free entry: An empirical study of real estate agents in Greater Boston. The RAND Journal of Economics, 46(1), 103–145. https://doi.org/10.1111/1756-2171.12082
Barwick, P. J., & Wong, M. (2019). Competition in the real estate brokerage industry: A critical review. Brookings Economic Studies.
Beijing Municipal Commission of Housing and Urban-Rural Development. (2019, May 9). Million real estate brokers survival report 2021. https://wos.anjukestatic.com
Benefield, J. D., Sirmans, C. S., & Sirmans, G. S. (2019). Observable agent effort and limits to innovation in residential real estate. Journal of Real Estate Research, 41(1), 1–36. https://doi.org/10.1080/10835547.2019.12091517
Benjamin, J. D., Chinloy, P., Jud, G. D., & Winkler, D. T. (2007). Do some people work harder than others? Evidence from real estate brokerage. The Journal of Real Estate Finance and Economics, 35(1), 95–110. https://doi.org/10.1007/s11146-007-9031-0
China Real Estate Managers Union & Beike Research Institute. (2021, June 3). Real estate broker employment report 2020. http://admin.fangchan.com
Chiu, B. W., & Lai, J. H. (2017). Project delay: Key electrical construction factors in Hong Kong. Journal of Civil Engineering and Management, 23(7), 847–857. https://doi.org/10.3846/13923730.2017.1319410
Datta, D. K., Guthrie, J. P., & Wright, P. M. (2005). Human resource management and labor productivity: Does industry matter? Academy of Management Journal, 48(1), 135–145. https://doi.org/10.5465/amj.2005.15993158
DeVany, A., & Frey, N. G. (1981). Stochastic equilibrium and capacity utilization. The American Economic Review, 71(2), 53–57.
Fedulova, I., Voronkova, O. Y., Zhuravlev, P., Gerasimova, E., Glyzina, M., & Alekhina, N. A. (2019). Labor productivity and its role in the sustainable development of economy: On the example of a region. Entrepreneurship and Sustainability Issues, 7(2), 1059–1073. http://doi.org/10.9770/jesi.2019.7.2(19)
Fuchs-Schündeln, N., & Izem, R. (2012). Explaining the low labor productivity in East Germany – A spatial analysis. Journal of Comparative Economics, 40(1), 1–21. https://doi.org/10.1016/j.jce.2011.09.001
Gilbukh, S., & Goldsmith-Pinkham, P. (2021). Heterogeneous real estate agents and the housing cycle (Working paper). City University of New York.
Glaeser, E., Huang, W., Ma, Y., & Shleifer, A. (2017). A real estate boom with Chinese characteristics. Journal of Economic Perspectives, 31(1), 93–116. https://doi.org/10.1257/jep.31.1.93
Glower, M., & Hendershott, P. (1988). The determinants of REALTOR income. Journal of Real Estate Research, 3(2), 53–68. https://doi.org/10.1080/10835547.1988.12090555
Guo, K. (2017). Demand and regulation mechanism of China’s real estate market: an analytical framework for dealing with the relationship between government and market. Management World, 2, 97–108. https://doi.org/10.19744/j.cnki.11-1235/f.2017.02.009
Han, L., & Hong, S. H. (2011). Testing cost inefficiency under free entry in the real estate brokerage industry. Journal of Business & Economic Statistics, 29(4), 564–578. https://doi.org/10.1198/jbes.2011.08314
He, Z., Dong, J., & Yu, L. (2018). An agent-based model for investigating the impact of distorted supply–demand information on China’s resale housing market. Journal of Computational Science, 25, 1–15. https://doi.org/10.1016/j.jocs.2018.01.002
Hopp, W. J., & Xu, X. (2008). A static approximation for dynamic demand substitution with applications in a competitive market. Operations Research, 56(3), 630–645. https://doi.org/10.1287/opre.1080.0541
Hsieh, C. T., & Moretti, E. (2003). Can free entry be inefficient? Fixed commissions and social waste in the real estate industry. Journal of Political Economy, 111(5), 1076–1122. https://doi.org/10.1086/376953
Huang, D., Zhou, H., & Zhao, Q. H. (2011). A competitive multiple-product newsboy problem with partial product substitution. Omega, 39(3), 302–312. https://doi.org/10.1016/j.omega.2010.07.008
Jiang, X., & Song, C. (2011). Research on the formation path for the information sharing system in the real estate brokerage industry. Journal of Engineering Management, 4, 449–453.
Lozano-Torró, A., García-Segura, T., Montalbán-Domingo, L., & Pellicer, E. (2020). Competitive advantages and barriers in international construction: An origin-host market approach. Journal of Civil Engineering and Management, 26(5), 475–489. https://doi.org/10.3846/jcem.2020.12180
Meng, X., Zhang, Y., & Li, T. (2018). Optimal macro-prudential policies for effective regulation of real estate market and the transition from virtual to real Economy. China Industrial Economics, 6, 81–97. https://doi.org/10.19581/j.cnki.ciejournal.2018.06.006
Miceli, T. J., Pancak, K. A., & Sirmans, C. F. (2007). Is the compensation model for real estate brokers obsolete? The Journal of Real Estate Finance and Economics, 35(1), 7–22. https://doi.org/10.1007/s11146-007-9026-x
Nazarko, J., & Chodakowska, E. (2017). Labour efficiency in construction industry in Europe based on frontier methods: Data envelopment analysis and stochastic frontier analysis. Journal of Civil Engineering and Management, 23(6), 787–795. https://doi.org/10.3846/13923730.2017.1321577
Netessine, S., & Rudi, N. (2003). Centralized and competitive inventory models with demand substitution. Operations Research, 51(2), 329–335. https://doi.org/10.1287/opre.51.2.329.12788
Osmond, I. C., Adesiyan, O. S., Olusola, A. M., & Daniel, D. O. (2015). Towards an effective real estate agency education: A stride to efficiency in Nigeria. Procedia – Social and Behavioral Sciences, 191, 2687–2692. https://doi.org/10.1016/j.sbspro.2015.04.360
Rajaram, K., & Tang, C. S. (2001). The impact of product substitution on retail merchandising. European Journal of Operational Research, 135(3), 582–601. https://doi.org/10.1016/S0377-2217(01)00021-2
Saiz, A. (2020). Bricks, mortar, and proptech: The economics of IT in brokerage, space utilization and commercial real estate finance. Journal of Property Investment & Finance, 38(4), 327–347. https://doi.org/10.1108/JPIF-10-2019-0139
Viriato, J. C. (2019). AI and machine learning in real estate investment. The Journal of Portfolio Management, 45(7), 43–54. https://doi.org/10.3905/jpm.2019.45.7.043
Wang, H., & Wang, K. (2012). What is unique about Chinese real estate markets? Journal of Real Estate Research, 34(3), 275–290. https://doi.org/10.1080/10835547.2012.12091335
Wang, J., & Xu, Q. (2017). The influence of floating population on real estate prices: An empirical study of Beijing. In Proceedings of the 2nd International Conference on Education, E-learning and Management Technology (pp. 112–118). DEStech Publications, Inc. https://doi.org/10.12783/dtssehs/eemt2017/14418
Yang, L., Li, L., & Wu, T. (2017). Expected impact and real estate market volatility anomaly in China. China Economic Quarterly, 16(1), 321–348. https://doi.org/10.13821/j.cnki.ceq.2016.04.13
Yang, G. L., Fukuyama, H., & Chen, K. (2019). Investigating the regional sustainable performance of the Chinese real estate industry: A slack-based DEA approach. Omega, 84, 141–159. https://doi.org/10.1016/j.omega.2018.04.009
Yap, J. B. H., Lam, C. G. Y., Skitmore, M., & Talebian, N. (2022). Barriers to the adoption of new safety technologies in construction: A developing country context. Journal of Civil Engineering and Management, 28(2), 120–133. https://doi.org/10.3846/jcem.2022.16014
Yavas, A. (2001). Impossibility of a competitive equilibrium in the real estate brokerage industry. Journal of Real Estate Research, 21(3), 187–200. https://doi.org/10.1080/10835547.2001.12091051
Yinger, J. (1981). A search model of real estate broker behavior. The American Economic Review, 71(4), 591–605.
Zhang, Y., & Zhang, H. (2014). An experimental comparison of commission patterns in the resale housing market in China. Journal of Comparative Asian Development, 13(3), 436–463. https://doi.org/10.1080/15339114.2014.934021
Zhang, Z., & Zhang, H. (2021). Policy suggestions on standardizing the development of real estate brokerage industry in China. China Real Estate, 16, 26–29. https://doi.org/10.13562/j.china.real.estate.2021.16.007
Zhang, R. Q., Zhang, L. K., Zhou, W. H., Saigal, R., & Wang, H. W. (2014). The multi-item newsvendor model with cross-selling and the solution when demand is jointly normally distributed. European Journal of Operational Research, 236(1), 147–159. https://doi.org/10.1016/j.ejor.2014.01.006
Zhang, C., Jia, S., & Yang, R. (2016). Housing affordability and housing vacancy in China: The role of income inequality. Journal of Housing Economics, 33, 4–14. https://doi.org/10.1016/j.jhe.2016.05.005
Zhang, X., Lin, Z., Zhang, Y., Zheng, Y., & Zhang, J. (2021). Online property brokerage platform and prices of second-hand houses: Evidence from Lianjia’s entry. Electronic Commerce Research and Applications, 50, 101104. https://doi.org/10.1016/j.elerap.2021.101104
Zhao, Y., & Zhao, X. (2016). How a competing environment influences newsvendor ordering decisions. International Journal of Production Research, 54(1), 204–214. https://doi.org/10.1080/00207543.2015.1034330
Zhou, J., & Hui, E. C. M. (2022). Housing prices, migration, and self-selection of migrants in China. Habitat International, 119, 102479. https://doi.org/10.1016/j.habitatint.2021.102479
Zumpano, L. V., Elder, H. W., & Crellin, G. E. (1993). The market for residential real estate brokerage services: Costs of production and economies of scale. The Journal of Real Estate Finance and Economics, 6(3), 237–250. https://doi.org/10.1007/BF01096960
Zumpano, L. V., Johnson, K. H., & Anderson, R. I. (2003). Internet use and real estate brokerage market intermediation. Journal of Housing Economics, 12(2), 134–150. https://doi.org/10.1016/S1051-1377(03)00018-4