Table 5

Result of direct, indirect and interaction effects

EffectRelationshipStd betaStd errort-valuep-valueBCCI 95%VIFf2
LBUB
DirectH1: BDA-AI capabilities → Organisational resilience0.2700.0683.9940.0000.1600.3841.4440.076
 H2: BDA-AI capabilities → Service innovation0.3310.0625.2950.0000.2200.4261.0000.123
 H3: BDA-AI capabilities → Distribution efficiency0.3030.0664.5990.0000.1860.4051.0000.101
 H4: Service innovation → Organisational resilience0.2260.0663.4480.0000.1150.3301.3410.057
 H5: Distribution efficiency → Organisational resilience0.1700.0652.6040.0050.4550.6041.3930.031
 H6: Organisational resilience → Operational performance0.5370.04512.0100.0000.4550.6041.0210.399
IndirectH7a: BDA-AI capabilities → Service innovation → Organisational resilience0.0750.0272.7780.0050.0290.134  
 H7b: BDA-AI capabilities → Distribution efficiency → Organisational resilience0.0520.0242.1430.0320.0110.103  
 H8: BDA-AI risk concerns*BDA-AI → Organisational resilience−0.1090.0502.1940.014−0.182−0.022  
Control variableFirm size → Operational performance0.0120.0610.1980.843−0.1110.132  
 Firm age → Operational performance0.0020.0560.0400.968−0.1110.108  
 Ownership → Operational performance−0.0540.0541.0160.310−0.1590.052  
  R2Q2      
 Service innovation0.1090.095      
 Distribution efficiency0.0920.080      
 Organisational resilience0.3350.199      
 Operational performance0.2910.136      

Note(s): BDA-AI = Big data analytics and artificial intelligence. ***p < 0.001, **p < 0.01, *p < 0.05. Std Beta = Standard beta; Std Error = Standard error; BCCI = Bias-corrected bootstrap confidence interval; LB = Lower bound; UB = Upper bound; VIF = Variance inflation factor; R2 = Coefficients of determination; Q2 = Predictive relevance; Effect size (f2): T = Trivial (<0.02), S = Small (0.02–0.15), M = Medium (0.15–0.35), L = Large (>0.35) (Cohen, 1988)

Source(s): Authors’ own work

or Create an Account

Close subscription notice
Close access options