Mechanisms of Resident Satisfaction Enhancement Through Waterfront Sports Buildings: A Synergistic Perspective of Blue Space and Built Environment—Empirical Evidence from Nine Chinese Cases
Abstract
1. Introduction
2. Literature Review and Research Hypothesis
2.1. Social Functions of the Four Dimensions of Waterfront Sports Complexes
2.1.1. Social Connections in Waterfront Sports Buildings
2.1.2. Accessibility of Waterfront Sports Buildings
2.1.3. Safety of Waterfront Sports Buildings
2.1.4. Multifunctionality of Waterfront Sports Buildings
2.2. The Mediating Role of Place Attachment
3. Research Design
3.1. Recipients and Questionnaire Distribution
3.2. Measurement of Variables
4. Result
4.1. Common Methodological Biases
4.2. Exploratory Factor Analysis
4.3. Validation Factor Analysis
4.4. Structural Equation Modeling Analysis
4.5. Intermediary Testing
5. Discussion
5.1. Direct Effects
5.2. Mediating Effects
5.3. Comparison of Studies
5.4. Policy Recommendations
6. Conclusions
7. Shortcomings and Prospects
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Variant | Categorization | Frequency (N) | Percentage (%) |
---|---|---|---|
Gender | Male | 423 | 58.67 |
Female | 298 | 41.33 | |
Marital status | Unmarried | 233 | 32.32 |
Married | 488 | 67.68 | |
Educational background | Secondary school and below | 559 | 77.53 |
Junior college or above | 162 | 22.47 | |
Annual income | 50 K yuan and below | 445 | 61.72 |
50–90 K yuan | 200 | 27.74 | |
90 K yuan and above | 76 | 10.54 | |
Domicile | Municipalities | 319 | 44.24 |
Suburbia | 239 | 33.15 | |
Countryside | 163 | 22.61 |
Research Variable | A Test Example of the Question Item | Reference Scale |
---|---|---|
Social interaction in waterfront sports architecture (SIWS) | At the waterfront sports facility, I can naturally interact and engage with friends or companions. | Glaeser and Scheinkman [69] Heimberg et al. [70] Wang et al. [71] |
Accessibility to waterfront sports architecture (AWS) | The architectural planning of Waterfront Sports ensures convenient access to all sports zones. | Páez and Morency [72] Lättman et al. [73] |
Safety of waterfront sports architecture (SWS) | I feel reassured by the slip-resistant design of waterfront sports buildings | Manca and Fornara [74] Zhang et al. [75] |
Multifunctionality of waterfront sports architecture (MWS) | This waterfront sports facility can be quickly reconfigured for different events. | Petrick. [76] Lee et al. [77] Finkel & Dashper [78] |
Place attachment (PA) | This waterfront sports building makes me feel like I belong here. | Brown and Raymond [79] Raymond et al. [80] |
Resident life satisfaction (RLS) | In general, the existence of this waterfront sports stadium has made my life better! | Jiang et al. [81] Wolk and Telleen [82] Diener et al. [83] |
Test | Value |
---|---|
KMO value | 0.929 |
Approximate chi-square | 10,375.728 |
Degrees of freedom | 300 |
Significance | 0.000 |
Component | Initial Eigenvalues | Extraction Sums of Squared Loadings | Rotation Sums of Squared Loadings | Component | Initial Eigenvalues |
---|---|---|---|---|---|
8.890 | 35.559 | 35.559 | 3.704 | 14.815 | 14.815 |
2.416 | 9.664 | 45.223 | 2.863 | 11.451 | 26.266 |
2.350 | 9.400 | 54.623 | 2.844 | 11.378 | 37.644 |
1.837 | 7.347 | 61.970 | 2.793 | 11.171 | 48.815 |
1.079 | 4.315 | 66.285 | 2.701 | 10.803 | 59.619 |
1.032 | 4.130 | 70.415 | 2.699 | 10.796 | 70.415 |
0.638 | 2.552 | 72.967 | |||
0.589 | 2.356 | 75.323 | |||
0.578 | 2.311 | 77.634 | |||
0.529 | 2.116 | 79.749 | |||
0.495 | 1.979 | 81.729 | |||
0.478 | 1.912 | 83.641 | |||
0.441 | 1.762 | 85.404 | |||
0.430 | 1.721 | 87.125 | |||
0.417 | 1.670 | 88.794 | |||
0.400 | 1.598 | 90.393 | |||
0.383 | 1.532 | 91.924 | |||
0.337 | 1.350 | 93.274 | |||
0.323 | 1.291 | 94.565 | |||
0.284 | 1.137 | 95.702 | |||
0.260 | 1.041 | 96.743 | |||
0.233 | 0.933 | 97.677 | |||
0.210 | 0.841 | 98.518 | |||
0.200 | 0.802 | 99.319 | |||
0.170 | 0.681 | 100.000 |
Rotated Component Matrix a | ||||||
---|---|---|---|---|---|---|
Ingredient | ||||||
1 | 2 | 3 | 4 | 5 | 6 | |
SIWS1 | 0.110 | 0.006 | −0.039 | 0.119 | 0.089 | 0.741 |
SIWS2 | 0.221 | 0.015 | −0.003 | 0.205 | 0.004 | 0.751 |
SIWS3 | 0.178 | 0.057 | 0.026 | 0.057 | 0.069 | 0.742 |
SIWS4 | 0.078 | 0.076 | 0.020 | 0.140 | 0.133 | 0.802 |
AWS1 | 0.182 | 0.012 | 0.038 | 0.107 | 0.773 | 0.109 |
AWS2 | 0.075 | 0.046 | 0.061 | 0.112 | 0.755 | 0.036 |
AWS3 | 0.233 | 0.003 | 0.057 | 0.065 | 0.757 | 0.069 |
AWS4 | 0.111 | 0.028 | 0.046 | 0.152 | 0.766 | 0.089 |
SWS1 | 0.202 | 0.023 | 0.767 | 0.109 | 0.115 | −0.002 |
SWS2 | 0.136 | 0.055 | 0.805 | 0.114 | 0.045 | 0.039 |
SWS3 | 0.234 | 0.013 | 0.777 | 0.145 | 0.006 | 0.000 |
SWS4 | 0.061 | 0.049 | 0.783 | 0.132 | 0.044 | −0.033 |
MWS1 | 0.087 | 0.799 | 0.070 | 0.118 | 0.037 | 0.096 |
MWS2 | 0.154 | 0.812 | 0.060 | 0.093 | 0.022 | 0.042 |
MWS3 | 0.145 | 0.750 | −0.059 | 0.193 | 0.016 | −0.025 |
MWS4 | 0.176 | 0.813 | 0.072 | 0.087 | 0.019 | 0.042 |
PA1 | 0.281 | 0.191 | 0.201 | 0.743 | 0.196 | 0.206 |
PA2 | 0.285 | 0.194 | 0.166 | 0.787 | 0.131 | 0.209 |
PA3 | 0.326 | 0.206 | 0.199 | 0.715 | 0.187 | 0.184 |
PA4 | 0.290 | 0.160 | 0.211 | 0.726 | 0.175 | 0.186 |
RLS1 | 0.764 | 0.175 | 0.218 | 0.240 | 0.205 | 0.206 |
RLS2 | 0.791 | 0.198 | 0.200 | 0.231 | 0.226 | 0.190 |
RLS3 | 0.781 | 0.188 | 0.193 | 0.270 | 0.208 | 0.175 |
RLS4 | 0.756 | 0.190 | 0.192 | 0.268 | 0.180 | 0.170 |
RLS5 | 0.747 | 0.195 | 0.221 | 0.258 | 0.183 | 0.240 |
Extraction method: principal component analysis.Rotation method: Kaiser normalized maximum variance method. |
Variant | Variant | Entry | CR | AVE |
---|---|---|---|---|
AWS | AWS1 | 0.758 | 0.801 | 0.552 |
AWS2 | 0.677 | |||
AWS3 | 0.742 | |||
AWS4 | 0.694 | |||
MWS | MWS1 | 0.755 | 0.835 | 0.56 |
MWS2 | 0.713 | |||
MWS3 | 0.742 | |||
MWS4 | 0.74 | |||
PA | PA1 | 0.813 | 0.908 | 0.711 |
PA2 | 0.836 | |||
PA3 | 0.84 | |||
PA4 | 0.823 | |||
PLS | RLS1 | 0.869 | 0.943 | 0.768 |
RLS2 | 0.876 | |||
RLS3 | 0.885 | |||
RLS4 | 0.865 | |||
RLS5 | 0.89 | |||
SIWS | SIWS1 | 0.72 | 0.804 | 0.515 |
SIWS2 | 0.726 | |||
SIWS3 | 0.708 | |||
SIWS4 | 0.754 | |||
SWS | SWS1 | 0.59 | 0.83 | 0.552 |
SWS2 | 0.731 | |||
SWS3 | 0.787 | |||
SWS4 | 0.679 |
Dimension | SIWS | AWS | SWS | MWS | PA | RLS |
---|---|---|---|---|---|---|
SIWS | 0.718 | |||||
AWS | 0.305 | 0.709 | ||||
SWS | 0.099 | 0.226 | 0.743 | |||
MWS | 0.190 | 0.141 | 0.179 | 0.748 | ||
PA | 0.521 | 0.472 | 0.489 | 0.472 | 0.843 | |
RLS | 0.510 | 0.526 | 0.513 | 0.470 | 0.756 | 0.876 |
Fitness Index | Reasonable Range | in the End | Assessment Results |
---|---|---|---|
GFI | >0.8 | 0.961 | favorable |
AGFI | >0.8 | 0.951 | favorable |
RMR | <0.08 | 0.020 | favorable |
RMSEA | <0.08 | 0.025 | favorable |
NFI | >0.8 | 0.964 | favorable |
IFI | >0.8 | 0.988 | favorable |
CFI | >0.8 | 0.988 | favorable |
TLI | >0.8 | 0.987 | favorable |
Trails | Non-Standardized Coefficient | Standard Error | z-Value | p-Value | Significant Judgment | Standardized Coefficient β |
---|---|---|---|---|---|---|
PA ← SIWS | 0.568 | 0.062 | 9.173 | 0.001 | *** | 0.354 |
PA ← AWS | 0.39 | 0.059 | 6.667 | 0.001 | *** | 0.243 |
PA ← SWS | 0.552 | 0.059 | 9.338 | 0.001 | *** | 0.344 |
PA ← MWS | 0.497 | 0.057 | 8.725 | 0.001 | *** | 0.309 |
RLS ← SIWS | 0.378 | 0.066 | 5.775 | 0.001 | *** | 0.21 |
RLS ← AWS | 0.404 | 0.061 | 6.611 | 0.001 | *** | 0.225 |
RLS ← SWS | 0.445 | 0.064 | 6.972 | 0.001 | *** | 0.247 |
RLS ← MWS | 0.362 | 0.06 | 6.039 | 0.001 | *** | 0.201 |
RLS ← PA | 0.364 | 0.057 | 6.43 | 0.001 | *** | 0.324 |
Effect Type | Path | Effect Value | Std. Error | 95% CI | p-Value |
---|---|---|---|---|---|
Direct | SIWS → PLS | 0.210 | 0.029 | [0.152, 0.267] | <0.001 |
AWS → PLS | 0.197 | 0.026 | [0.146, 0.248] | <0.001 | |
SWS → PLS | 0.227 | 0.028 | [0.173, 0.281] | <0.001 | |
MWS → PLS | 0.188 | 0.027 | [0.135, 0.242] | <0.001 | |
Indirect | SIWS → PA → PLS | 0.133 | 0.014 | [0.093, 0.148] | <0.001 |
AWS → PA → PLS | 0.091 | 0.013 | [0.065, 0.119] | <0.001 | |
SWS → PA → PLS | 0.126 | 0.015 | [0.091, 0.150] | <0.001 | |
MWS → PA → PLS | 0.116 | 0.013 | [0.084, 0.136] | <0.001 | |
Total | SIWS → PLS | 0.342 | 0.029 | [0.284, 0.400] | <0.001 |
AWS → PLS | 0.287 | 0.027 | [0.234, 0.340] | <0.001 | |
SWS → PLS | 0.353 | 0.027 | [0.299, 0.407] | <0.001 | |
MWS → PLS | 0.304 | 0.027 | [0.250, 0.357] | <0.001 |
Mediation Path | Indirect Effect | Boot SE | 95% Boot CI | Significance |
---|---|---|---|---|
SIWS → PA → PLS | 0.133 | 0.014 | [0.093, 0.148] | Yes (p < 0.001) |
AWS → PA → PLS | 0.091 | 0.013 | [0.065, 0.119] | Yes (p < 0.001) |
SWS → PA → PLS | 0.126 | 0.015 | [0.091, 0.150] | Yes (p < 0.001) |
MWS → PA → PLS | 0.116 | 0.013 | [0.084, 0.136] | Yes (p < 0.001) |
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Zhang, Z.; Liu, W.; Zhang, J.; Du, L.; Pan, J. Mechanisms of Resident Satisfaction Enhancement Through Waterfront Sports Buildings: A Synergistic Perspective of Blue Space and Built Environment—Empirical Evidence from Nine Chinese Cases. Buildings 2025, 15, 2233. https://doi.org/10.3390/buildings15132233
Zhang Z, Liu W, Zhang J, Du L, Pan J. Mechanisms of Resident Satisfaction Enhancement Through Waterfront Sports Buildings: A Synergistic Perspective of Blue Space and Built Environment—Empirical Evidence from Nine Chinese Cases. Buildings. 2025; 15(13):2233. https://doi.org/10.3390/buildings15132233
Chicago/Turabian StyleZhang, Zhihao, Wenyue Liu, Jia Zhang, Linkang Du, and Jianhua Pan. 2025. "Mechanisms of Resident Satisfaction Enhancement Through Waterfront Sports Buildings: A Synergistic Perspective of Blue Space and Built Environment—Empirical Evidence from Nine Chinese Cases" Buildings 15, no. 13: 2233. https://doi.org/10.3390/buildings15132233
APA StyleZhang, Z., Liu, W., Zhang, J., Du, L., & Pan, J. (2025). Mechanisms of Resident Satisfaction Enhancement Through Waterfront Sports Buildings: A Synergistic Perspective of Blue Space and Built Environment—Empirical Evidence from Nine Chinese Cases. Buildings, 15(13), 2233. https://doi.org/10.3390/buildings15132233