Fficient r = 0.418, p 0.01), as well as the correlation coefficient among capability reconfiguration and enterprise sustainable innovation was considerable and optimistic (correlation coefficient r = 0.535, p 0.01). The correlation coefficient between IT governance and enterprise sustainable innovation was also substantial and good (correlation coefficient r = 0.350, p 0.01). Hence, the correlation coefficients amongst the variables have been all less than 0.70.Processes 2021, 9,ten ofThese evaluation outcomes offered preliminary assistance for the study hypotheses proposed in this study.Table 4. Descriptive statistics and correlation analysis results (n = 269). Variable 1. Enterprise age 2. Enterprise scale three. Supply-side 9-PAHSA-d9 Protocol search four. Demand-side search five. Cross-regional search six. Capability reconfiguration 7. IT governance eight. Sustainable innovation Imply SD 1 — 0.365 0.130 0.112 0.167 0.022 0.153 0.175 2.870 1.138 — 0.031 0.022 0.098 0.062 0.746 0.572 0.560 0.487 0.290 0.492 3.810 0.698 0.732 0.529 0.461 0.247 0.464 3.880 0.851 0.708 0.413 0.267 0.418 3.800 0.967 0.749 0.423 0.535 three.780 1.059 0.781 0.350 three.950 1.028 0.778 three.952 0.983 2 3 4 5 6 7-0.109 -0.3.060 0.Note: Diagonal within the table refers to root square of AVE; p 0.05 and p 0.01 (bilateral test).four.two. Hypotheses Testing The theoretical model and relevant hypotheses are verified, and also the test results are displayed in Table five.Table 5. Model hierarchical regression final results. Variable Handle variables Enterprise age Enterprise scale Independent variables Supply-side search Demand-side search Cross-regional search Mediator variable Capability reconfiguration Moderator variable IT governance (ITG) Interactions ITGsupply-side search ITGdemand-side search ITGcross-regional search R2 Adjusted R2 Capability Reconfiguration Model1 0.24 0.07 Model 2 0.22 0.05 0.24 0.19 0.12 Model three 0.20 0.03 0.18 0.16 0.10 Model four 0.19 0.02 0.21 0.20 0.16 Enterprise Sustainable Innovation Model 5 0.24 0.09 Model six 0.23 0.06 0.38 0.33 0.15 0.41 0.14 0.15 0.09 0.08 0.16 0.47 0.45 Model 7 0.19 0.04 Model 8 0.16 0.03 0.13 0.12 0.09 0.23 0.06 0.0.35 0.0.43 0.0.25 0.0.28 0.0.33 0.0.38 0.Note: p 0.05, p 0.01, and p 0.001.4.2.1. Principal Effect Test Taking enterprise sustainable innovation because the dependent variable, this study verified the regression outcomes with the manage and independent variables around the dependent variable to get Models 5 and 6, respectively, as presented in Table five. It may be observed from Model 5 that the control variables (enterprise age and enterprise scale) have no considerable influence on enterprise sustainable innovation. Further, it may be observed from Model six that supply-side search ( = 0.38, p 0.001), demand-side search ( = 0.33, p 0.01), and cross-regionalProcesses 2021, 9,11 ofsearch ( = 0.15, p 0.01) all exhibited a optimistic and substantial influence on enterprise sustainable innovation. Hence, Hypotheses 1a, 1b, and 1c had been verified. four.2.2. Mediating Effect Test Primarily based on the mediating effect analysis actions proposed by Baron [66], this study tests the mediating CAY10502 Protocol impact of capability reconfiguration in between boundary-spanning search and enterprise sustainable innovation. The investigation results are presented in Table 5. In line with the analysis data of Model 7, capability reconfiguration exhibited a constructive effect on enterprise sustainable innovation ( = 0.41, p 0.01). Comparing Model 8 with Model six, it was identified that the direct impact of supply-side search on en.