Responding to opportunities provided by General Purpose Technologies : Industry 4.0 in Finland
Companies are currently facing a technological change that has the potential of disrupt- ing entire industries. Recognizing opportunities provided by Industry 4.0 requires com- panies to apply vision and foresight and to adapt their strategies in order to face the changing environment. Acting upon these technological opportunities is managerially demanding, but crucial for maintaining companies’ future competitiveness. This thesis builds on literature on strategic management and General Purpose Technologies (GPTs) and takes a company-level perspective in answering the question of how such techno- logical opportunities are perceived and responded to by decision-makers. In order to explore this issue, the strategic approaches to Industry 4.0 of 16 publicly listed companies in Finland were analyzed. For this purpose, in-depth qualitative interviews with managers from the Industrial and the Basic Material sector were conducted and publicly available material in the form of CEO and CIO Interviews, journalistic articles, as well as company press releases were collected and analysed. The results provide insights into how the characteristics of GPTs influence decision- maker’s perceptions and responses and show that the technologies’ uncertain develop- ment and the generality of purpose result in difficulties in understanding the nature of change and identifying how to turn the potential of the technologies into actual revenue streams. The findings suggest that opportunities provided by GPTs are responded to with new products and services, organizational transformation, new strategies, the adaptation of business models as well as new cooperation with suppliers and customers. Under the high perceived uncertainty and the complexity of required changes, a more experimental, stepwise approach to the implementation of new GPTs is identified as suitable as it allows balancing disruptive effects and for learning and adaptation to occur, as uncertainties are resolved. ...
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Kärnä, Eija (University of Jyväskylä, 2016)
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