Research Article

How Does Technology Import and Export Affect the Innovative Performance of Firms? From the Perspective of Emerging Markets Firms

Table 5

Tobit regressions results for product/process innovation performance (continuous variable).

M1M2M3M4M5M6
Product performanceProduct performanceProduct performanceProcess performanceProcess performanceProcess performance

Control variables
Firm age−1.616−1.596−1.745−1.144−1.239−1.178
(1.875)(1.821)(1.818)(1.249)(1.237)(1.236)
Firm size1.8540.4940.4531.2720.5000.562
(0.780)(0.798)(0.796)(0.517)(0.534)(0.534)
Top managers’ experience3.8313.3553.4953.3342.8652.725
(2.176)(2.125)(2.116)(1.395)(1.388)(1.386)
State ownership−0.206−0.184−0.188−0.264−0.251−0.250
(0.063)(0.062)(0.061)(0.041)(0.041)(0.041)
Foreign ownership−0.005−0.087−0.085−0.010−0.060−0.060
(0.045)(0.045)(0.045)(0.030)(0.031)(0.031)
Diversification19.75116.54316.47111.58310.60810.678
(6.520)(6.359)(6.342)(4.454)(4.435)(4.423)
Formal competition−0.361−1.081−0.9320.9650.5020.404
(1.377)(1.348)(1.346)(0.950)(0.944)(0.942)
Human capital1.9801.5251.5661.0000.8130.768
(0.534)(0.521)(0.520)(0.355)(0.353)(0.353)
Informal competition−0.019−0.250−1.458−0.693−0.782−0.581
(1.099)(1.070)(1.275)(0.741)(0.736)(0.863)

Independent variables
Exporter4.947−4.1165.52011.461
(2.189)(4.864)(1.520)(3.379)
Technology import15.51314.6985.6281.615
(2.119)(4.723)(1.483)(3.338)
ICEPH1: 4.756H2:3.193
(2.280)(1.618)
ICTIH3: 0.376H4: 2.303
(2.264)(1.316)
Constant−19.809−9.787−8.302−1.0465.5406.294
(11.092)(10.921)(10.987)(7.350)(7.366)(7.427)

Var(e.product_perfor)648.564605.959602.132
(40.826)(38.011)(37.761)
Var(e.process_perfor)348.511339.842338.150
(16.773)(16.382)(16.300)
Location effectYesYesYesYesYesYes
Industry effectYesYesYesYesYesYes

Observations118611861186118611861186
Pseudo R20.0570.0660.0670.0420.0450.046
Wald chi square380.088440.608445.307371.974403.556408.387
Log likelihood−3158.1295−3118.8029−3116.4533−4274.8976−4235.7602−4233.3446

Standard errors are in parentheses. , , and .