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Table 2 Path coefficient between the latent variables and observed variables

From: Impact of dynamic capacities on the performance of food and beverage enterprises in Lagos, Nigeria

Path relation Standardized estimate Standard error T statistics P
Sales growth > Product innovation .850 .023 36.565 .000
Sales growth > Strategic decision-making .114 .038 2.953 .003
Sales growth > Technological capability .052 .023 2.217 .027
Sales growth > Strategic flexibility − .041 .022 -1.750 .081
Sales growth > Competitive intensity − .097 .049 -1.882 .060
Sales growth > Technological turbulence − .094 .054 -1.754 .080
Enterprise survival > Product innovation .002 .011 .208 .836
Enterprise survival > Strategic decision-making .079 .017 4.525 .000
Enterprise survival > Technological capability − .007 .011 − .696 .487
Enterprise survival > Strategic flexibility .032 .010 3.096 .002
Enterprise survival > Competitive intensity .585 .022 25.215 .000
Enterprise survival >Technological turbulence .347 .025 14.308 .000
Enterprise efficiency > Product innovation .030 .049 .741 .459
Enterprise efficiency> Strategic decision-making .121 .082 1.789 .074
Enterprise efficiency > Technological capability .263 .050 6.413 .000
Enterprise efficiency > Strategic flexibility .142 .048 3.494 .001
Enterprise efficiency > Competitive intensity .213 .105 2.363 .018
Enterprise efficiency > Technological turbulence − .142 .116 − .1.516 .130
Competitive advantage > Product innovation − .035 .023 − .1.583 .114
Competitive advantage > Strategic decision-making − .029 .038 − .809 .419
Competitive advantage > Technological capability − .026 .023 − .1.178 .239
Competitive advantage > Strategic flexibility .870 .022 39.893 .000
Competitive advantage > Competitive intensity .048 .048 .993 .321
Competitive advantage > Technological turbulence − .030 .053 − .603 .547
  1. Source: Lisrel 8.70 output (2020)