Author_Institution :
Dept. of Manage. & Inf. Technol., Southern Taiwan Univ. of Sci. & Technol., Tainan, Taiwan
Abstract :
Ambidextrous organizations exploit existing technologies to enable incremental innovation while exploring new opportunities to foster radical innovation. Whether this dual pursuit is effective in furthering performance goals, however, remains inconclusive in the literature. Departing from the ambidexterity literature, which acknowledges in general the performance implication of ambidextrous learning, this study advances our understanding by inquiring into its contextual effect, i.e., to examine its boundary conditions, using environmental dynamism and firm size as moderating factors. Based on a sample of 1740 firm-year observations in manufacturing industries across four industrialized nations (U.S., United Kingdom, Germany, and Japan) during the 1999-2003 period, the empirical evidence shows that environmental dynamism necessitates ambidextrous learning and enhances its consequent performance effect and that large firms also perform better by acting ambidextrously. The configurational model sheds further light on the combined weight of firm and industry effects, giving support to the notion that large firms with ambidextrous learning, in the presence of environmental dynamism, perform better than small ambidextrous firms. As prior studies mostly overlook the context-bound nature of ambidextrous learning, this study not only revisits the performance implication of ambidextrous learning on a global basis but also points out the theoretical sensitivity of organizational learning to different settings.
Keywords :
industrial training; innovation management; knowledge management; manufacturing industries; organisational aspects; ambidextrous learning organizational; configurational model; contextual determinants; environmental dynamism; exploitative learning; industrial effects; industrial firm size; industrialized countries; industrialized nations; manufacturing industries; organizational learning; radical innovation; sensitivity; Context; Dynamic scheduling; Industries; Marketing and sales; Organizations; Patents; Technological innovation; Ambidextrous learning; configurational perspective; exploitative learning; exploratory learning; performance implication;