Skip to main content
SpringerLink
Log in

Improve Compliance with Limited Resources by a Three-Group Inspection Regime

  • Published:
Environmental Modeling & Assessment Aims and scope Submit manuscript

Abstract

Frequent monitoring and relatively high fines are usually necessary to bring about improvements in environmental quality, but more challenging for many countries with limited human, material, and financial resources is to put them into practice. This paper developed a three-group model of a state-dependent enforcement in a repeated game to improve the policy implementation under limited inspection capacities. A certain number of firms are grouped (group 1, group 2, group 3) for different supervision intensity (e.g., the order of inspection probability corresponding to each group is p 1 < p 2 < p 3) based on their environmental performance. The optimal policy parameters, such as inspection probability of each group and the probability that a firm found in compliance is moved to a better reputation group, were obtained as the basis for regulator’s policy making. Numerical simulations indicated that the three-group inspection regime can significantly increase compliance rate as compared with static enforcement with the same monitoring probability. Among the number of firms in each group under steady state conditions, group 2 had the most, group 1 was the second, and group 3 had the smallest. Analysis and prediction of a three-group reputation example provided a good experiment for the model. The results give a practical reference for the policy makers with inspection capacity constraints to achieve higher compliance rate.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Central People’s Government of the People’s Republic of China (CPGPRC). (2015). Law of the people’s republic of China on the prevention and control of water pollution. Approved by the Standing Committee of the National People’s Congress (NPC) of the People’s Republic of China. Available at: http://zfs.mep.gov.cn/fl/201404/t20140425_271040.htm. Accessed November 2015.

  2. Dresher, M. (1962). A sampling inspection problem in arms control agreements: a game-theoretic analysis. Memorandum RM-2972-ARPA. Santa Monica: The RAND Corporation.

    Google Scholar 

  3. Maschler, M. (1966). A price leadership method for solving the inspector’s non-constant sum game. Naval Research Logistics Quarterly, 13, 11–33. doi:10.1002/nav.3800130103.

    Article  Google Scholar 

  4. Ferguson, T. S., & Melolidakis, C. (1998). On the inspection game. Naval Research Logistics, 45, 327–334. doi:10.1002/(SICI)1520-6750(199804)45:3%3C327::AID-NAV6%3E3.3.CO;2-G.

    Article  Google Scholar 

  5. Andreozzi, L. (2004). Rewarding policemen increases crime. Another surprising result from the inspection game. Public Choice, 121, 69–82. doi:10.1007/s11127-004-6166-x.

    Article  Google Scholar 

  6. Dong, X., Li, C., Li, J., Wang, J., & Huang, W. (2010). A game-theoretic analysis of implementation of cleaner production policies in the Chinese electroplating industry. Resources, Conservation and Recycling, 54, 1442–1448. doi:10.1016/j.resconrec.2010.06.009.

    Article  Google Scholar 

  7. Lin, S. W. (2010). Self-reporting mechanism for risk regulation. Journal of Business Research, 63, 528–534. doi:10.1016/j.jbusres.2009.04.011.

    Article  Google Scholar 

  8. Franckx, L. (2002). The use of ambient inspections in environmental monitoring and enforcement when the inspection agency cannot commit itself to announced inspection probabilities. Journal of Environmental Economics and Management, 43(1), 71–92. doi:10.1006/jeem.2000.1167.

    Article  Google Scholar 

  9. Franckx, L. (2005). Environmental enforcement with endogenous ambient monitoring. Environmental and Resource Economics, 30, 195–220. doi:10.1007/s10640-004-1514-3.

    Article  Google Scholar 

  10. Tapiero, C. S. (2004). Environmental quality control and environmental games. Environmental Modeling and Assessment, 9, 201–206. doi:10.1007/s10666-005-2451-4.

    Article  Google Scholar 

  11. Harrington, W. (1988). Enforcement leverage when penalties are restricted. Journal of Public Economics, 37, 29–53. doi:10.1016/0047-2727(88)90003-5.

    Article  Google Scholar 

  12. Harford, J. D. (1991). Measurement error and state-dependent pollution-control enforcement. Journal of Environmental Economics and Management, 21, 67–81. doi:10.1016/0095-0696(91)90005-4.

    Article  Google Scholar 

  13. Harford, J. D., & Harrington, W. (1991). A reconsideration of enforcement leverage when penalties are restricted. Journal of Public Economics, 45, 391–395. doi:10.1016/0047-2727(91)90034-Y.

    Article  Google Scholar 

  14. Raymond, M. (1999). Enforcement leverage when penalties are restricted: a reconsideration under asymmetric information. Journal of Public Economics, 73, 289–295. doi:10.1016/S0047-2727(98)00106-6.

    Article  Google Scholar 

  15. Friesen, L. (2003). Targeting enforcement to improve compliance with environmental regulations. Journal of Environmental Economics and Management, 46, 72–85. doi:10.1016/S0095-0696(02)00033-5.

    Article  Google Scholar 

  16. Liu L. and Neilson W. (2009). Enforcement Leverage with Fixed Inspection Capacity. Available at: http://web.utk.edu/∼wneilson/Leverage.pdf. Accessed November 2015.

  17. Guangdong Environmental Protection Bureau (GDEPB). (2006). Trial Procedures of Guangdong Provincial Environmental Protection Bureau on Credit Management of Key Sources of Pollution for Environmental Protection. Available at: http://www.gdep.gov.cn/zwxx_1/zfgw/shbtwj/201011/t20101118_115501.html. Accessed November 2015.

  18. Guangdong Environmental Protection Bureau (GDEPB). (2005). An announcement on environmental information of the key industrial pollution sources of Provincial control in Guangdong Province in 2005. Available at: http://www.gdep.gov.cn/gzhd/wlwz/wlwzgzdt/201009/t20100929_96957.html. Accessed November 2015.

  19. Guangdong Environmental Protection Bureau (GDEPB). (2010). Credit enquiries of polluting enterprises. Available at: http://pub.gdepb.gov.cn/pub/dchome.jsp?act=db12. Accessed November 2015.

  20. Leach, A. (2006). Regulation by reputation. Computers & Operations Research, 33, 409–425. doi:10.1016/j.cor.2004.06.013.

    Article  Google Scholar 

Download references

Acknowledgments

This project research was supported by the National Natural Science Foundation of China (Project No. 51408370) and the special funds of Department of Water Administration Supervision of Shenzhen Municipality (Project No. FF25500066). The author is grateful to the Environmental Protection Bureau of Guangdong Province for the opening of the credit management data of key sources of pollution.

Author information

Authors and Affiliations

  1. Department of Environmental Engineering Technology, Shenzhen Institute of Information Technology, Shenzhen, 518172, People’s Republic of China

    Xiaoqing Dong & Xiaofeng He

  2. Environmental Science and Engineering Research Center, Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, 518055, People’s Republic of China

    Chaolin Li, Binbin Ding & Peibing Shao

  3. Department of Environmental Monitoring and Treatment Technology, Shenzhen Polytechnic, Shenzhen, 518055, People’s Republic of China

    Jia Zhu

Authors
  1. Xiaoqing Dong
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chaolin Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Binbin Ding
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xiaofeng He
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Jia Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Peibing Shao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Xiaoqing Dong.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dong, X., Li, C., Ding, B. et al. Improve Compliance with Limited Resources by a Three-Group Inspection Regime. Environ Model Assess 21, 517–529 (2016). https://doi.org/10.1007/s10666-015-9491-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10666-015-9491-1

Keywords

Search

Navigation