Organizational models for advancing technological innovations: A configurational approach

Antecedents and outcomes of open innovation over the past 20 years: A framework and meta-analysis

Organizational models for advancing technological innovations: A configurational approach

Gina Colarelli O'Connor

kHUB post date: January 2025
Originally published: 30 December 2024 (PDMA JPIM • Vol. 42, Issue 1 • January 2025)
Read time: 60 minutes

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Novel technologies are emerging and evolving at such a rapid pace that it is difficult for companies and society to absorb them. Large mature organizations can be displaced if they fail to learn about, develop, and adopt new technologies, yet they struggle to do so. What is the best approach? Clearly there is no single best answer. This paper examines organizational models that companies have experimented with for leveraging technological discoveries and inventions to create strategic innovations that fuel new growth opportunities. I adopt Kanter's concept of newstreams as the guiding lens, because it addresses the challenges that mature firms face in their attempts to create new platforms of growth that emerging technologies enable, while maintaining the health of the mainstream core business. This notion demands an extension of ambidexterity theory beyond the exploration/exploitation dichotomy, recognizing that creating new streams of growth that ultimately become part of the mainstream organization requires elements of exploitation to enhance reliability and predictability that the mainstream requires. Five organizational approaches for SI that have been observed in practice are described and considered in light of three elements that, together, can be thought of as comprising a technological innovation strategy: (a) type of ambidextrous approach the firm adopts, (b) type of technology (general vs. special purpose), and (c) targeted market (internal vs. external). By combining theory and observation, configurations of ambidexterity type, technology type, and target market are proposed, as well as expected outcomes for each. I offer these as a research agenda whose outcome can provide important guidance to organizational leaders who are attempting to build capabilities for technological innovation that will secure their organizations' future health.

Practitioner Points

  • Firms and organizations should consider integrating artificial intelligence (AI)-driven recommendation systems into their platforms, particularly in sectors susceptible to marketplace discrimination.
  • AI recommendations are especially valuable in public consumption scenarios.
  • Emphasizing the perceived impartiality of AI-based recommendation systems can reassure consumers and encourage adoption as it allows consumers to cope with feelings of embarrassment from discriminatory experiences in the marketplace.

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