How Smog Awareness Influences Public Acceptance of Congestion Charge Policies
Abstract
:1. Introduction
2. Literature Review
2.1. Prior Studies on Public Acceptance of Congestion Charges
2.2. New Influential Factors: Smog Concerns and Perceived Smog Risks
3. Research Design and Data Source
3.1. Conceptual Model and Variable Specification
3.1.1. Causalities between Smog Awareness and Public Acceptance
3.1.2. Causalities between Behavioral, Policy-Related, and Sociodemographic Factors and Public Acceptance
3.2. Data Source
4. Results
4.1. Descriptive Statistics
4.2. Regression Results
4.2.1. Direct Positive Correlation between Smog Awareness and Public Acceptance
4.2.2. Moderating Influence of Smog Awareness on Perceived Fairness
4.2.3. Positive Relationship between Policy-Related Factors and Public Acceptance
4.2.4. Behavioral Factors and Car Ownership Negatively Influence Public Acceptance
5. Conclusions and Policy Implications
Acknowledgments
Author Contributions
Conflicts of Interest
References
- Xie, Y.; Zhao, B.; Zhang, L.; Luo, R. Spatiotemporal variations of PM2.5 and PM10 concentrations between 31 Chinese cities and their relationships with SO2, NO2, CO and O3. Particuology 2015, 20, 141–149. [Google Scholar] [CrossRef]
- Cheng, S.; Lang, J.; Zhou, Y.; Han, L.; Wang, G.; Chen, D. A new monitoring-simulation-source apportionment approach for investigation the vehicular emission contribution to the PM2.5 pollution in Beijing, China. Atmos. Environ. 2013, 79, 308–316. [Google Scholar] [CrossRef]
- Municipal Environmental Protection Bureau: 70% of PM2.5 Pollution in Shanghai Comes from the Local. Available online: http://www.shanghai.gov.cn/nw2/nw2314/nw2315/nw17239/nw17252/u21aw968232.html (accessed on 8 January 2015).
- 60% of PM2.5 Pollution in Guangzhou Comes from the Industry, Vehicle and Dust. Available online: http://www.gzepb.gov.cn/yhxw/201502/t20150205_78984.htm (accessed on 4 February 2017).
- The Government in Hangzhou Launched the PM2.5 Source Apportionment Results: Vehicle Emission Topped. Available online: http://zjnews.zjol.com.cn/system/2015/06/06/020686281.shtml (accessed on 6 June 2015).
- The PM2.5 Source Apportionment Results of Nanjing Announced that Coal is the Largest pollution Source. Available online: http://jsnews.jschina.com.cn/system/2015/04/30/024548067.shtml (accessed on 30 April 2015).
- Zheng, Z.; Liu, Z.; Liu, C.; Shiwakoti, N. Understanding public response to a congestion charge: A random-effects ordered logit approach. Transp. Res. Part A 2014, 70, 117–134. [Google Scholar] [CrossRef]
- Hensher, D.A.; Li, Z. Referendum voting in road pricing reform: A review of the evidence. Transp. Policy 2013, 25, 186–197. [Google Scholar] [CrossRef]
- Finance Tencent. Why Did 61% of the Public Oppose to the Congestion Fee? Is 20 Yuan too Expensive? Available online: http://finance.qq.com/a/20160603/012060.htm (accessed on 18 August 2017).
- Lieberthal, K.; Oksenberg, M. Policy Making in China: Leaders, Structures and Processes; Princeton University Press: Princeton NJ, USA, 1988. [Google Scholar]
- Li, L. Rights consciousness and rules consciousness in contemporary China. China J. 2010, 64, 47–68. [Google Scholar] [CrossRef]
- Wang, B. New media and communication mechanism of grass roots society—The case study of Jiangmen anti-nuclear movements. Jinan J. Philos. Soc. Sci. 2014, 11, 130–139. [Google Scholar]
- Zhou, B. Media contact, public participation and political efficacy in public emergencies—The case study of the Xiamen PX project. Open Times 2011, 5, 123–140. [Google Scholar]
- Wang, L.; Xu, J.; Qin, P. Will a driving restriction policy reduce car trips?—The case study of Beijing, China. Transp. Res. Part A 2014, 67, 279–290. [Google Scholar] [CrossRef]
- Jakobsson, C.; Fujii, S.; Gärling, T. Determinants of private car users’ acceptability of road pricing. Transp. Policy 2000, 7, 133–158. [Google Scholar] [CrossRef]
- Kim, J.; Schmöcker, J.; Fujii, S.; Noland, R.B. Attitudes toward road pricing and environmental taxation among US and UK students. Transp. Res. Part A 2013, 48, 50–62. [Google Scholar] [CrossRef] [Green Version]
- Schade, J.; Schlag, B. Public acceptability of traffic demand management in Europe. Traffic Eng. Control 2000, 41, 314–318. [Google Scholar]
- Steg, L. Factors influencing the acceptability and effectiveness of transport pricing. In Acceptability of Transport Pricing Strategies; Schade, J., Schlag, B., Eds.; Elsevier: Oxford, UK, 2003. [Google Scholar]
- Gärling, T.; Jakobsson, C.; Loukopoulos, P.; Fujii, S. Acceptability of road pricing. In Pricing in Road Transport: Multidisciplinary Perspectives; Verhoef, E., Bliemer, E., Steg, L., Van Wee, B., Eds.; Edward Elgar: Cheltenham, UK, 2008. [Google Scholar]
- Eliasson, J.; Jonsson, L. The unexpected “yes”: Explanatory factors behind the positive attitudes to congestion charges in Stockholm. Transp. Policy 2011, 18, 636–647. [Google Scholar] [CrossRef]
- Smog Forced the Introduction of Congestion Charge. Available online: http://bj.people.com.cn/n/2015/1214/c82839-27314117.html (accessed on 14 December 2015).
- Li, J.; Hiltunen, E.; He, X.; Zhu, L. A questionnaire case study to investigate public awareness of smog pollution in China’s rural areas. Sustainability 2016, 8, 1111. [Google Scholar]
- Shao, D.; Liu, X. Application of contingent valuation method on evaluating urban management policy: A contingent valuation on potential congestion charge during the peak hour in Hangzhou city. Urban Dev. Stud. 2015, 22, 118–124. [Google Scholar]
- Batel, S.; Devine-Wright, P.; Tangeland, T. Social acceptance of low carbon energy and associated infrastructures: A critical discussion. Energy Policy 2013, 58, 1–5. [Google Scholar] [CrossRef]
- Wüstenhagen, R.; Wolsink, M.; Bürer, M.J. Social acceptance of renewable energy innovation: An introduction to the concept. Energy Policy 2007, 35, 2683–2691. [Google Scholar] [CrossRef]
- Dermont, C.; Ingold, K.; Kammermann, L.; Stadelmann-Steffen, I. Bringing the policy making perspective in: A political science approach to social acceptance. Energy Policy 2017, 108, 359–368. [Google Scholar] [CrossRef]
- Taylor, B.D.; Iseki, H.; Kalauskas, R. Addressing equity issues in political debated over road pricing. In Proceedings of the 89th Annual Meeting of the Transportation Research Board, Washington, DC, USA, 10–14 January 2010. [Google Scholar]
- Fujii, S.; Gärling, T.; Jakobsson, C.; Jou, R.C. A cross-country study of fairness and infringement on freedom as determinants of car owners’ acceptance of road pricing. Transportation 2004, 31, 285–295. [Google Scholar] [CrossRef]
- Fransson, N.; Gärling, T. Environmental concern: Conceptual definitions, measurement methods, and research findings. J. Environ. Psychol. 1999, 19, 369–382. [Google Scholar] [CrossRef]
- Dawes, R.M. Social dilemmas. Ann. Rev. Psychol. 1980, 31, 169–193. [Google Scholar] [CrossRef]
- Bartley, B. Mobility impacts, reactions and opinions: Traffic demand management options in Europe: The MIRO project. Traffic Eng. Control 1995, 36, 596–603. [Google Scholar]
- Schmöcker, J.-D.; Pettersson, P.; Fujii, S. Comparative analysis of proximal and distal determinants for the acceptance of coercive charging policies in the U.K. and Japan. Int. J. Sustain. Transp. 2012, 6, 156–173. [Google Scholar] [CrossRef] [Green Version]
- Harring, N.; Jargers, S.C. Should we trust in values? Explaining public support for pro-environmental taxes. Sustainability 2013, 5, 210–227. [Google Scholar] [CrossRef]
- Hammar, H.; Jagers, S. What is a fair CO2 tax increase? Individual preferences for fair procedures for emission reductions in the transport sector. Ecol. Econ. 2007, 61, 377–387. [Google Scholar] [CrossRef]
- Jagers, S.C.; Hammar, H. Environmental taxation for good and for bad: On individuals’ reluctance to mitigate climate change via CO2-tax vis-à-vis alternative policy instruments. Environ. Politics 2009, 18, 218–237. [Google Scholar] [CrossRef]
- Tyler, T.; Huo, Y.J. Trust in the Law; Russell Sage Foundation: New York, NY, USA, 2002. [Google Scholar]
- Liobikienė, G.; Juknys, R. The role of values, environmental risk perception, awareness of consequences, and willingness to assume responsibility for environmentally-friendly behaviour: The Lithuanian case. J. Clean. Prod. 2016, 112, 3413–3422. [Google Scholar] [CrossRef]
- The 2013–2017 Beijing Clear Air Action Plan. Available online: http://zhengwu.beijing.gov.cn/ghxx/qtgh/t1324558.htm (accessed on 8 August 2017).
- Weigel, R.H. Environmental attitudes and the prediction of behavior. In Environmental Psychology: Directions and Perspectives; Feimer, N.R., Geller, E.S., Eds.; Preager: New York, NY, USA, 1983; pp. 257–287. [Google Scholar]
- Ajzen, I. Attitude structure and behaviour. In Attitude Structure and Function; Pratkanis, A.R., Breckler, S.J., Greenwald, A.G., Eds.; Erlbaum: Hillsdale, NJ, USA, 1989; pp. 241–274. [Google Scholar]
- Sjöberg, L. Global change and human action: Psychological perspectives. Int. Soc. Sci. J. 1989, 121, 414–432. [Google Scholar]
- Takala, M. Environmental awareness and human activity. Int. J. Psychol. 1991, 26, 585–597. [Google Scholar] [CrossRef]
- Warren, C.R.; Lumsden, C.; O’Dowd, S.; Birnie, R.V. ‘Green on green’: Public perceptions of wind power in Scotland and Ireland. J. Environ. Plan. Manag. 2005, 48, 853–875. [Google Scholar] [CrossRef]
- Goodfellow, M.J.; Williams, H.R.; Azapagic, A. Nuclear renaissance, public perception and design criteria: An exploratory review. Energy Policy 2011, 39, 6199–6210. [Google Scholar] [CrossRef]
- Aven, T.; Renn, O. Risk Management and Governance: Concepts, Guildelines and Applications; Springer: Dordrecht, The Netherlands, 2010. [Google Scholar]
- Chen, Y.; Ebenstein, A.; Greenstone, M.; Li, H. Evidence on the impact of sustained exposure to air pollution on life expectancy from China’s Huai River policy. Proc. Natl. Acad. Sci. USA 2013, 110, 12936–12941. [Google Scholar] [CrossRef] [PubMed]
- Zhang, D.; Liu, J.; Li, B. Tackling air pollution in China—What do we learn from the great smog of 1950s in London. Sustainability 2014, 6, 5322–5338. [Google Scholar] [CrossRef]
- Moon, W.; Balasubramanian, S.K. Public attitudes toward agrobiotechnology: The mediating role of risk perceptions on the impact of trust, awareness, and outrage. Rev. Agric. Econ. 2004, 26, 186–208. [Google Scholar] [CrossRef]
- Li, L. Political trust and petitioning in Chinese countryside. Comp. Politics 2012, 40, 209–226. [Google Scholar] [CrossRef]
- Levi, M.; Stoker, L. Political trust and trustworthiness. Ann. Rev. Political Sci. 2000, 3, 475–507. [Google Scholar] [CrossRef]
- Eriksson, L.; Garvill, J.; Nordlund, A.M. Acceptability of single and combined transport policy measures: The importance of environmental and policy specific beliefs. Transp. Res. Part A 2008, 42, 1117–1128. [Google Scholar] [CrossRef]
- Schuitema, G.; Steg, L.; Forward, S. Explaining differences in acceptability before and acceptance after the implementation of a congestion charge in Stockholm. Transp. Res. Part A 2010, 44, 99–109. [Google Scholar] [CrossRef]
- Deutsch, M. Equity, equality, and need: What determines which value will be used as the basis of distributive justice. J. Soc. Issues 1975, 31, 137–149. [Google Scholar] [CrossRef]
- Jagers, S.; Löfgren, Å.; Stripple, J. Attitudes to personal carbon allowances: Political trust, fairness and ideology. Clim. Policy 2010, 10, 410–431. [Google Scholar] [CrossRef]
- Zannakis, M.; Wallin, A.; Johansson, L.-O. Political trust and perceptions of the quality of institutional arrangements—How do they influence the public’s acceptance of environmental rules. Environ. Policy Gov. 2015, 25, 424–438. [Google Scholar] [CrossRef]
- Nunnally, J.C. Psychometric Theory; Tata McGraw-Hill Education: New York, NY, USA, 2010. [Google Scholar]
- Cortina, J.M. What is coefficient alpha? An examination of theory and applications. J. Appl. Psychol. 1993, 78, 98–104. [Google Scholar] [CrossRef]
- End the Plate Auction in Shanghai, and Change to Congestion Charge Policy after 7 Years? Available online: http://business.sohu.com/20150203/n408382391.shtml (accessed on 3 February 2015).
- Data Center of National Environmental Protection Bureau. Available online: http://datacenter.mep.gov.cn (accessed on 14 August 2017).
- Noy, C. Sampling knowledge: The hermeneutics of snowball sampling in qualitative research. Int. J. Soc. Res. Methodol. 2008, 11, 327–344. [Google Scholar] [CrossRef]
- Huang, H. International knowledge and domestic evaluations in a changing society: The case of China. Am. Political Sci. Rev. 2015, 109, 613–634. [Google Scholar] [CrossRef]
- Levin, J.; Fox, J.-M.; Forde, D.-R. Elementary Statistics in Social Research; Pearson Education, Inc.: New York, NY, USA, 2016. [Google Scholar]
- How Much You Know about the Population in Beijing? Available online: http://www.bjstats.gov.cn/rkjd/ (accessed on 14 August 2017).
- The Average Income of Beijing Citizens in 2016. Available online: http://www.cngold.com.cn/newtopic/20160727/2016nbjpjgzsds.html (accessed on 19 August 2016).
- 2014 Shanghai Statistical Yearbook. Available online: http://www.stats-sh.gov.cn/tjnj/tjnj2014.htm (accessed on 10 August 2016).
- The Average Income of Shanghai Citizens in 2016. Available online: http://shebao.yjbys.com/zhengce/561397.html (accessed on 7 March 2017).
- The Ranking of Car Park in 2016. Available online: http://www.sohu.com/a/124633891_565969 (accessed on 18 January 2017).
- Drews, S.; Van den Bergh, J.C. What explains public support for climate policies? A review of empirical and experimental studies. Clim. Policy 2016, 16, 855–876. [Google Scholar] [CrossRef]
- Sun, C.; Yuan, X.; Xu, M. The public perceptions and willingness to pay: From the perspective of the smog crisis in China. J. Clean. Prod. 2016, 112, 1635–1644. [Google Scholar] [CrossRef]
- Wang, Y.; Sun, M.; Yang, X.; Yuan, X. Public awareness and willingness to pay for tackling smog pollution in China: A case study. J. Clean. Prod. 2016, 112, 1627–1634. [Google Scholar] [CrossRef]
- Hardin, G. The tragedy of the commons. Science 1968, 162, 1243–1248. [Google Scholar] [CrossRef] [PubMed]
- Ostrom, E. Governing the Commons: The Evolution of Institutions for Collective Action; Cambridge University Press: Cambridge, UK, 1990. [Google Scholar]
- Toth, F.L. Fair Weather: Equity Concerns in Climate Change; Routledge: Abingdon, UK, 2013; Volume 6. [Google Scholar]
- Tyler, T. Why People Obey the Law, 2nd ed.; Princeton University Press: Princeton, NJ, USA, 2006. [Google Scholar]
- Fung, A. Varieties of participation in complex governance. Public Adm. Rev. 2006, 66, 66–75. [Google Scholar] [CrossRef]
- Fung, A. Putting the public back into governance: The challenges of citizen participation and its future. Public Adm. Rev. 2015, 75, 513–522. [Google Scholar] [CrossRef]
- Kormos, C.; Gifford, R. The validity of self-report measures of proenvironmental behavior: A meta-analytic review. J. Environ. Psychol. 2014, 40, 359–371. [Google Scholar] [CrossRef]
Variable | Cronbach’s α | Number of Items |
---|---|---|
Political Trust | 0.7069 | 4 |
Risk Perception | 0.6956 | 2 |
Background | Frequency | Percentage (%) | Sample from Beijing (%) | Sample from Shanghai (%) | Distribution of Beijing Population (%) | Distribution of Shanghai Population (%) | |
---|---|---|---|---|---|---|---|
Gender | Male | 283 | 49.30 | 56.49 | 42.21 | 50.18 | 51.50 |
Female | 291 | 50.70 | 43.51 | 57.79 | 49.82 | 48.50 | |
Age | <21 | 18 | 3.14 | 3.51 | 2.77 | 3.90 | 4.87 |
21–30 | 359 | 62.54 | 58.95 | 65.74 | 21.70 | 22.55 | |
31–40 | 149 | 25.96 | 28.42 | 23.53 | 18.50 | 17.59 | |
41–50 | 33 | 5.75 | 6.67 | 5.19 | 16.40 | 15.98 | |
>50 | 15 | 2.61 | 2.46 | 2.77 | 22.90 | 30.39 | |
Income | <2000 | 18 | 3.14 | 3.51 | 2.77 | 3.00 | 3.50 |
2000–4000 | 33 | 5.75 | 8.07 | 3.46 | 23.30 | 28.20 | |
4001–7000 | 127 | 22.13 | 25.26 | 19.03 | 27.95 | 27.85 | |
7001–10,000 | 119 | 20.73 | 24.56 | 16.96 | 19.25 | 17.85 | |
10,001–20,000 | 172 | 29.97 | 27.37 | 32.53 | 18.70 | 16.90 | |
>20,000 | 105 | 18.29 | 11.23 | 25.26 | 7.30 | 5.70 | |
Education | Middle school or below | 10 | 1.74 | 3.51 | - | 39.22 | 55.34 |
High school | 34 | 5.92 | 7.02 | 4.84 | 15.36 | 21.84 | |
College | 317 | 55.23 | 48.42 | 61.94 | 38.61 | 20.91 | |
Masters or above | 213 | 37.11 | 41.05 | 33.22 | 4.72 | 1.90 | |
Car | None | 276 | 48.08 | 50.53 | 46.02 | 74.72 | 86.01 |
1 | 240 | 41.81 | 40.00 | 43.60 | 25.28 | 13.99 | |
>1 | 58 | 10.10 | 9.47 | 10.38 |
Variables | Mean | Std. Dev. | Scale | ||
---|---|---|---|---|---|
Dependent variables | Public acceptance | 3.16 | 1.14 | 1–5 | |
Independent variables | Political trust | Willingness | 2.97 | 1.11 | 1–5 |
Various | 2.76 | 1.01 | 1–5 | ||
Capacity | 2.35 | 1.01 | 1–5 | ||
Openness | 2.96 | 1.10 | 1–5 | ||
Perceived fairness | 2.84 | 1.20 | 1–5 | ||
Traffic inconvenience | 2.45 | 1.04 | 1–5 | ||
WTP | 0.65 | 0.48 | 0 or 1 | ||
Risk perception | Healthy | 0.85 | 0.35 | 0 or 1 | |
Severity | 0.56 | 0.50 | 0 or 1 | ||
Control variables | Car | 0.64 | 0.71 | 0–3 | |
Age | 30.45 | 7.71 | 14–69 | ||
Gender | 0.51 | 0.50 | 0 or 1 | ||
Education | 3.27 | 0.65 | 1–4 | ||
Income | 4.27 | 1.37 | 1–7 |
Model 1 | Model 2 | Model 3 | ||||
---|---|---|---|---|---|---|
Coef. | T | Coef. | T | Coef. | T | |
Traffic Inconvenience | −0.20 ** | −2.51 | −0.15 ** | −1.96 | −0.17 ** | −2.08 |
Perceived Fairness | 0.54 **** | 7.47 | 0.49 **** | 6.77 | 0.48 **** | 6.57 |
Political Trust | 0.44 **** | 4.25 | 0.45 **** | 4.19 | 0.43 **** | 3.97 |
WTP | 1.47 **** | 6.23 | 1.62 **** | 6.56 | ||
Risk Perception | 0.52 ** | 2.17 | 0.53 ** | 2.18 | ||
WTP ×Traffic Inconvenience | −0.04 | −0.20 | ||||
WTP × Perceived Fairness | 0.32 * | 1.84 | ||||
WTP × Political Trust | −0.25 | −1.08 | ||||
Risk Perception × Traffic Inconvenience | 0.13 | 0.48 | ||||
Risk Perception × Perceived Fairness | 0.62 *** | 2.86 | ||||
Risk Perception × Political Trust | 0.01 | 0.02 | ||||
Car | −0.51 **** | −4.07 | −0.53 **** | −4.24 | −0.51 **** | −4.03 |
Age Group | ||||||
21–55 | −0.05 | −0.07 | 0.09 | 0.12 | 0.04 | 0.06 |
56–69 | −0.54 | −0.58 | −0.20 | −0.21 | −0.30 | −0.31 |
Gender | −0.09 | −0.56 | −0.13 | −0.86 | −0.14 | −0.89 |
Education | ||||||
2 | −1.30 * | −1.92 | −1.00 | −1.48 | −0.86 | −1.26 |
3 | −1.52 ** | −2.40 | −1.44 ** | −2.29 | −1.34 ** | −2.12 |
4 | −1.24 * | −1.91 | −1.18 * | −1.84 | −1.12 * | −1.72 |
Income | 0.12 * | 1.74 | 0.12 * | 1.83 | 0.12 * | 1.70 |
Area | 0.10 | 0.61 | −0.47 ** | −2.54 | −0.51 *** | −2.73 |
0.0731 | 0.0987 | 0.1058 | ||||
N | 574 | 574 | 574 |
© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Zhou, L.; Dai, Y. How Smog Awareness Influences Public Acceptance of Congestion Charge Policies. Sustainability 2017, 9, 1579. https://doi.org/10.3390/su9091579
Zhou L, Dai Y. How Smog Awareness Influences Public Acceptance of Congestion Charge Policies. Sustainability. 2017; 9(9):1579. https://doi.org/10.3390/su9091579
Chicago/Turabian StyleZhou, Lingyi, and Yixin Dai. 2017. "How Smog Awareness Influences Public Acceptance of Congestion Charge Policies" Sustainability 9, no. 9: 1579. https://doi.org/10.3390/su9091579