Investigating the Driving Factors of Public Participation in Public-Private Partnership (PPP) Projects—A Case Study of China
Abstract
:1. Introduction
2. Literature Review
2.1. Existing Research on Public Participation in PPP Projects
2.2. Theory of Planned Behavior
3. Theoretical Model Development
3.1. Attitude towards Behavior
3.2. Subjective Norm
3.3. Perceived Behavior Control
3.4. Perceived Benefit
3.5. Perceived Risk
4. Methodology
4.1. Survey Instrument
4.2. Measurement Items
4.3. Data Collection
4.4. Data Analysis
5. Results
5.1. Measurement Model
5.2. Structural Model
6. Discussions
6.1. In-Depth Analysis of SEM Results
6.2. Public Preferences of Participation Approaches
7. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
Constructs | Code | Measurement Items |
---|---|---|
Attitude towards behavior (AB) | AB1 | I think public participation can reduce the government’s decision-making mistakes in PPP projects |
AB2 | I think public participation can improve the public understanding of PPP projects and help the projects go smoothly | |
AB3 | I think public participation can effectively monitor the behavior of the government and enterprises in PPP projects | |
AB4 | I think public participation helps the public opinions on PPP projects to be referenced or adopted by the government, thus guaranteeing the public rights | |
AB5 | I think public participation helps PPP projects to build and operate according to local conditions | |
Subjective norm (SN) | SN1 | My family approves of my participation in PPP projects |
SN2 | My neighbors or friends encourage me to participate in PPP projects | |
SN3 | Residents’ community committee encourages me to participate in PPP projects | |
SN4 | The government encourages me to participate in PPP projects | |
SN5 | News media supports me to participate in PPP project | |
Perceived behavioral control (PBC) | PBC1 | I have enough time to participate in PPP projects |
PBC2 | I have enough energy to participate in PPP projects | |
PBC3 | I have enough cognitive ability to participate in PPP projects | |
PBC4 | I have sufficient ways to participate in PPP projects | |
PBC5 | I can obtain relevant information to participate in PPP projects | |
Perceived benefit (PB) | PB1 | PPP projects have a positive impact on local housing prices will affect whether I participate in PPP projects or not |
PB2 | PPP projects have a positive impact on local employment will affect whether I participate in PPP projects or not | |
PB3 | PPP projects have a positive impact on local transportation will affect whether I participate in PPP projects or not | |
PB4 | PPP projects have a positive impact on local tourism will affect whether I participate in PPP projects or not | |
PB5 | PPP projects have a positive impact on local education will affect whether I participate in PPP projects or not | |
Perceived risk (PR) | PR1 | PPP projects have the potential risk of environmental pollution will affect whether I participate in PPP projects or not |
PR2 | PPP projects have the potential risk of physical health will affect whether I participate in PPP projects or not | |
PR3 | PPP projects have the potential risk of mental health will affect whether I participate in PPP projects or not | |
PR4 | PPP projects have the potential risk of damaging local culture will affect whether I participate in PPP projects or not | |
PR5 | PPP projects have the potential risk of charging the public unreasonably will affect whether I participate in PPP projects or not | |
Behavioral intention (BI) | BI1 | I am willing to participate in the decision-making of PPP projects |
BI2 | I am willing to participate in the supervision of PPP projects | |
BI3 | I hope to be involved in the early stages of PPP projects | |
BI4 | I will recommend people around me to pay attention to information about PPP projects |
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Characteristic | Distribution of Answers |
---|---|
Gender | Male: 48.4%; Female: 51.6% |
Age | <20: 3.6%; 20–29: 76%; 30–39: 12.7%; 40–49: 5.4%; ≥50: 2.3% |
Education level | PhD: 6.8%; Master: 31.7%; Bachelor: 52.5%; College or below: 5.4% |
Workplace | Government department: 6.8%; Public institution: 12.2%; State-owned enterprise: 5.4%; Private enterprise: 21.7%; Others: 45.3% |
Constructs | Items | Item Loadings | Cronbach’s α |
---|---|---|---|
AB | AB1 | 0.66 *** | 0.857 |
AB2 | 0.72 *** | ||
AB3 | 0.79 *** | ||
AB4 | 0.70 *** | ||
AB5 | 0.83 *** | ||
SN | SN1 | 0.75 *** | 0.879 |
SN2 | 0.87 *** | ||
SN3 | 0.89 *** | ||
SN4 | 0.68 *** | ||
SN5 | 0.66 *** | ||
PBC | PBC1 | 0.86 *** | 0.827 |
PBC2 | 0.88 *** | ||
PBC3 | 0.63 *** | ||
PBC4 | 0.63 *** | ||
PBC5 | 0.43 *** | ||
PR | PR1 | 0.90 *** | 0.932 |
PR2 | 0.91 *** | ||
PR3 | 0.87 *** | ||
PR4 | 0.81 *** | ||
PR5 | 0.79 *** | ||
PB | PB1 | 0.58 *** | 0.834 |
PB2 | 0.80 *** | ||
PB3 | 0.84 *** | ||
PB4 | 0.55 *** | ||
PB5 | 0.77 *** | ||
BI | BI1 | 0.82 *** | 0.855 |
BI2 | 0.79 *** | ||
BI3 | 0.74 *** | ||
BI4 | 0.75 *** |
Goodness-of-Fit Measure | Level of Acceptance Fit | Fit Statistics | |
---|---|---|---|
Absolute fit | CMIN/DF | 1~2 good | 1.788 |
GFI | >0.80 acceptable; >0.90 good | 0.844 | |
AGFI | >0.80 acceptable; >0.90 good | 0.808 | |
RMSEA | <0.10 acceptable; <0.08 good | 0.060 | |
Incremental fit | IFL | >0.90 | 0.930 |
CFI | >0.90 | 0.929 | |
Simple fit | PNFI | >0.50 | 0.746 |
PGFI | >0.50 | 0.686 |
Goodness-of-Fit Measure | Level of Acceptance Fit | Fit Statistics | |
---|---|---|---|
Absolute fit | CMIN/DF | 1~2 good | 2.020 |
GFI | >0.8 acceptable; >0.9 good | 0.827 | |
AGFI | >0.8 acceptable; >0.9 good | 0.790 | |
RMSEA | <0.1 acceptable; <0.08 good | 0.068 | |
Incremental fit | IFL | >0.9 good | 0.908 |
CFI | >0.9 good | 0.907 | |
Simple fit | PNFI | >0.5 good | 0.738 |
PGFI | >0.5 good | 0.804 |
Estimate | S.E. | C.R. | p | |||
---|---|---|---|---|---|---|
BI | <--- | AB | 0.334 | 0.094 | 3.532 | *** |
BI | <--- | SN | 0.262 | 0.078 | 3.361 | *** |
BI | <--- | PBC | 0.119 | 0.062 | 1.931 | 0.053 |
BI | <--- | PR | 0.151 | 0.051 | 2.961 | 0.003 |
BI | <--- | PB | 0.176 | 0.116 | 1.523 | 0.128 |
AB1 | <--- | AB | 1.000 | |||
AB2 | <--- | AB | 1.030 | 0.113 | 9.130 | *** |
AB3 | <--- | AB | 1.226 | 0.126 | 9.698 | *** |
AB4 | <--- | AB | 0.976 | 0.112 | 8.742 | *** |
AB5 | <--- | AB | 1.264 | 0.126 | 10.036 | *** |
SN1 | <--- | SN | 1.000 | |||
SN2 | <--- | SN | 1.208 | 0.090 | 13.496 | *** |
SN3 | <--- | SN | 1.165 | 0.088 | 13.245 | *** |
SN4 | <--- | SN | 1.007 | 0.103 | 9.803 | *** |
SN5 | <--- | SN | 0.898 | 0.095 | 9.504 | *** |
PBC1 | <--- | PBC | 1.000 | |||
PBC2 | <--- | PBC | 1.091 | 0.070 | 15.571 | *** |
PBC3 | <--- | PBC | 0.824 | 0.085 | 9.699 | *** |
PBC4 | <--- | PBC | 0.750 | 0.081 | 9.302 | *** |
PR1 | <--- | PR | 1.000 | |||
PR2 | <--- | PR | 1.125 | 0.054 | 20.922 | *** |
PR3 | <--- | PR | 1.040 | 0.056 | 18.545 | *** |
PR4 | <--- | PR | 1.038 | 0.063 | 16.389 | *** |
PR5 | <--- | PR | 0.978 | 0.062 | 15.761 | *** |
PB1 | <--- | PB | 1.000 | |||
PB2 | <--- | PB | 1.265 | 0.146 | 8.683 | *** |
PB3 | <--- | PB | 1.361 | 0.154 | 8.849 | *** |
PB4 | <--- | PB | 0.876 | 0.126 | 6.966 | *** |
PB5 | <--- | PB | 1.263 | 0.148 | 8.525 | *** |
BI1 | <--- | BI | 1.000 | |||
BI2 | <--- | BI | 0.985 | 0.080 | 12.325 | *** |
BI3 | <--- | BI | 1.048 | 0.093 | 11.223 | *** |
BI4 | <--- | BI | 0.988 | 0.086 | 11.449 | *** |
Goodness-of-Fit Measure | Level of Acceptance fit | Fit Statistics | |
---|---|---|---|
Absolute fit | CMIN/DF | 1~2 good | 1.739 |
GFI | >0.8 acceptable; >0.9 good | 0.872 | |
AGFI | >0.8 acceptable; >0.9 good | 0.837 | |
RMSEA | <0.1 acceptable; <0.08 good | 0.058 | |
Incremental fit | IFL | >0.9 good | 0.948 |
CFI | >0.9 good | 0.939 | |
Simple fit | PNFI | >0.5 good | 0.760 |
PGFI | >0.5 good | 0.813 |
Estimate | S.E. | C.R. | p | |||
---|---|---|---|---|---|---|
BI | <--- | AB | 0.393 | 0.082 | 4.772 | *** |
BI | <--- | SN | 0.262 | 0.078 | 3.378 | *** |
BI | <--- | PBC | 0.124 | 0.063 | 1.978 | 0.048 |
BI | <--- | PR | 0.182 | 0.049 | 3.701 | *** |
AB1 | <--- | AB | 1.000 | |||
AB2 | <--- | AB | 1.010 | 0.110 | 9.203 | *** |
AB3 | <--- | AB | 1.214 | 0.123 | 9.840 | *** |
AB4 | <--- | AB | 0.965 | 0.109 | 8.844 | *** |
AB5 | <--- | AB | 1.228 | 0.122 | 10.090 | *** |
SN1 | <--- | SN | 1.000 | |||
SN2 | <--- | SN | 1.230 | 0.087 | 14.134 | *** |
SN3 | <--- | SN | 1.114 | 0.084 | 13.315 | *** |
SN4 | <--- | SN | 0.872 | 0.100 | 8.764 | *** |
SN5 | <--- | SN | 0.825 | 0.091 | 9.029 | *** |
PBC1 | <--- | PBC | 1.000 | |||
PBC2 | <--- | PBC | 1.092 | 0.070 | 15.578 | *** |
PBC3 | <--- | PBC | 0.824 | 0.085 | 9.706 | *** |
PBC4 | <--- | PBC | 0.749 | 0.081 | 9.285 | *** |
PR1 | <--- | PR | 1.000 | |||
PR2 | <--- | PR | 1.084 | 0.055 | 19.660 | *** |
PR3 | <--- | PR | 0.989 | 0.058 | 16.958 | *** |
PR4 | <--- | PR | 1.050 | 0.063 | 16.630 | *** |
PR5 | <--- | PR | 0.986 | 0.062 | 15.926 | *** |
BI1 | <--- | BI | 1.000 | |||
BI2 | <--- | BI | 0.983 | 0.080 | 12.318 | *** |
BI3 | <--- | BI | 1.045 | 0.093 | 11.221 | *** |
BI4 | <--- | BI | 0.985 | 0.086 | 11.440 | *** |
BI | <--- | AB | 0.393 | 0.082 | 4.772 | *** |
BI | <--- | SN | 0.262 | 0.078 | 3.378 | *** |
BI | <--- | PBC | 0.124 | 0.063 | 1.978 | 0.048 |
BI | <--- | PR | 0.182 | 0.049 | 3.701 | *** |
AB1 | <--- | AB | 1.000 | |||
AB2 | <--- | AB | 1.010 | 0.110 | 9.203 | *** |
Approach | Average Value | Standard Deviation | Average Standard Error |
---|---|---|---|
Internet platforms, such as Weibo or WeChat | 3.93 | 0.876 | 0.059 |
Information disclosure or consultation provided by the government | 3.70 | 0.900 | 0.061 |
Discussion with experts or NGOs | 3.44 | 0.978 | 0.066 |
Newspapers, magazines, television news or other traditional media | 3.40 | 0.966 | 0.065 |
Public lectures on PPP Projects | 3.27 | 0.927 | 0.062 |
Community residents’ committees | 3.26 | 0.983 | 0.066 |
Writing letters, telephone calls or site visits | 3.06 | 1.021 | 0.069 |
Assemblies or parades | 2.73 | 1.132 | 0.076 |
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Luo, Z.; Li, J.; Wu, Z.; Li, S.; Bi, G. Investigating the Driving Factors of Public Participation in Public-Private Partnership (PPP) Projects—A Case Study of China. Int. J. Environ. Res. Public Health 2022, 19, 5192. https://doi.org/10.3390/ijerph19095192
Luo Z, Li J, Wu Z, Li S, Bi G. Investigating the Driving Factors of Public Participation in Public-Private Partnership (PPP) Projects—A Case Study of China. International Journal of Environmental Research and Public Health. 2022; 19(9):5192. https://doi.org/10.3390/ijerph19095192
Chicago/Turabian StyleLuo, Ziqian, Junjie Li, Zezhou Wu, Shenghan Li, and Guoqiang Bi. 2022. "Investigating the Driving Factors of Public Participation in Public-Private Partnership (PPP) Projects—A Case Study of China" International Journal of Environmental Research and Public Health 19, no. 9: 5192. https://doi.org/10.3390/ijerph19095192