Table A11.

Configurations for improving university performance – China

Models for high UPERCUCCModels for low UPERCUCC
Model1a: UPE = f(RES*PRO*PEO)Model1b: ∼UPE = f(RES*PRO*PEO)
1. ∼RES*PRO*PEO0.3200.3200.8341. RES*∼PRO0.4120.0830.775
    2. ∼PRO*PEO0.4300.1020.774
Solution coverage: 0.320
Solution consistency: 0.834
Solution coverage: 0.514
Solution consistency: 0.751
Model2a: UPE = f(NVE*INN*SEL*PRT)Model2b: ∼ UPE = f(NVE*INN*SEL*PRT)
1. ∼NVE*∼INN*∼SEL*PRT0.3190.0950.8931. ∼NVE*∼INN*∼SEL*∼PRT0.6500.6500.904
2. NVE*INN*SEL*PRT0.5470.3230.933    
Solution coverage: 0.642
Solution consistency: 0.899
Solution coverage: 0.650
Solution consistency: 0.904
Model3a: UPE = f(RES*PRO*PEO*NVE*INN*SEL*PRT)Model3b: ∼ UPE = f(RES*PRO*PEO*NVE*INN*SEL*PRT)
1. ∼RES*PEO*NVE*INN*SEL*PRT0.3150.0380.9691. ∼PRO*∼PEO*∼NVE*∼INN*∼SEL*∼PRT0.5710.5710.914
2. PRO*PEO*NVE*INN*SEL*PRT0.4180.1570.919    
Solution coverage: 0.569
Solution consistency: 0.891
Solution coverage: 0.571
Solution consistency: 0.914

Note(s):

RC = raw coverage; UC = unique coverage; C = consistency; RES = resource; PRO = process; PEO = people; NVE = new venture behaviour; INN = innovativeness; SEL = self-renewal; PRT = proactiveness; UPE = university performance. RC >0.2 are reported

Source(s): Authors’ own creation/work

or Create an Account

Close subscription notice
Close access options