Table 5 Computed indicator weights.
Endogenous latent variable (η) | Exogenous latent variable (ξ) | Standardized loading coefficient | Item weight | Observed variables | Standardized loading coefficient | Item weight |
|---|---|---|---|---|---|---|
Urban spatial innovation potential (η) | Innovation driving forces (\({\xi }_{1}\)) | 1.04 | 0.349 | Gazelle enterprise density (X1) | 0.82 | 0.208 |
High-tech enterprise density (X2) | 0.77 | 0.196 | ||||
College and research institute density (X3) | 0.61 | 0.155 | ||||
Scientific research institution density (X4) | 0.73 | 0.185 | ||||
Population with a college education or higher distribution (X5) | 0.60 | 0.152 | ||||
Straight-line distance from the center of Shanghai (X6) | 0.41 | 0.104 | ||||
Innovation resource support (\({\xi }_{2}\)) | 1.03 | 0.346 | Co-working space density (X7) | 0.89 | 0.175 | |
Incubator density (X8) | 0.83 | 0.163 | ||||
Startup park density (X9) | 1.01 | 0.199 | ||||
Venture capital institution density (X10) | 0.72 | 0.142 | ||||
Bank density (X11) | 0.82 | 0.161 | ||||
Provincial-level and above Enterprise R&D center density (X12) | 0.81 | 0.160 | ||||
Innovation environment quality (\({\xi }_{3}\)) | 0.91 | 0.305 | Distance to parks and green spaces (X13) | 0.42 | 0.069 | |
Distance to subway stations (X14) | 0.85 | 0.140 | ||||
Distance to bus stations (X15) | 0.40 | 0.066 | ||||
Dining facility density (X16) | 0.86 | 0.141 | ||||
Sports facility density (X17) | 1.01 | 0.166 | ||||
Primary and secondary school density (X18) | 0.92 | 0.151 | ||||
Hospital facility density (X19) | 0.93 | 0.153 | ||||
Nighttime light intensity (X20) | 0.69 | 0.114 |
