Generativity Theory of Entrepreneurship
Distinct from the popular medical/psychological definition of generativity, which defines the concept as a need to nurture and guide younger people and contribute to the next generation, the generativity theory in relation to entrepreneurship focuses on the development of technology stemming from the foundations set by previous innovations.
According to Zittrain (2006, p. 1980) generativity refers to “technology’s overall capacity to produce unprompted change driven by large, varied, and uncoordinated audiences”. The keyword here being ‘unprompted’. Zittrain suggests that the innovations and outcomes are unintentional and occur without purposeful intent. He also notes that the outcomes of these activities in turn become the basis for future innovation.
Yoo et al. (2010) expands on Zittrain’s definition and illustrates generativity as a layered model where innovation on one layer’s technology can have a cascading effect on other layers. An example of this is a camera using available hardware combined with a recording device within a single unit to expand its functionality and become a video camera.
Jarvenpaa and Standaert (2018) state that generativity theory explains how novel behaviours, developments, and products are a result of pre-established behaviours and concepts. In this definition, the focus is new innovations stemming from the connection of old ones which have opened the doors for these new ideas. Nambisan (2017) uses the example of when Apple updates its operating system (iOS) to implement new capabilities, and how this paves the way for new app developments and new entrepreneurial opportunities. To expand on Nambisan’s example, when Apple introduced Face ID, the technology opened the doors for businesses to adopt this new security technology to their apps and integrate it into their own sign-in pages to enhance their user experience.
The concept of generativity can also be seen influencing the actions, feelings and behaviours of entrepreneurs. For instance, it can be a motivational input (Faraj et al., 2011) and a source of excitement and positive energy (Henfridsson & Yoo, 2014). For example, when wearable technology with biometric sensors, such as FitBit and Apple Watch, was introduced, it generated a huge buzz in the health industry. Entrepreneurs and innovators were looking to be the first ones to capitalize on this new technology for their own ventures. Today, we see countless fitness apps that are built around the health tracking technology. However, it can also create a sense of urgency for entrepreneurial action through the generation of mental health related issues such as increased anxiety (Carlo, Lyytinen, & Boland, 2004).
It is worth noting that the generativity theory is continuously expanding and is relatively new compared to many of the classical theories of entrepreneurship. However, many of those classical theories were conceived before the digital age. While many are still relevant, it seems only right that we should look for new theories appropriate to these new times. So while these newer theories may not be as refined, they are still very important and should not be disregarded. We look to future empirical research to validate some of the theory's main propositions.
Sources:
Carlo, J., Lyytinen, K., & Boland, R. (2004). Systemic risk, information technology artifacts, and high reliability organizations: A case of constructing a radical architecture. International Conference on Information Systems Proceedings (pp. 685–696). AIS.
According to Zittrain (2006, p. 1980) generativity refers to “technology’s overall capacity to produce unprompted change driven by large, varied, and uncoordinated audiences”. The keyword here being ‘unprompted’. Zittrain suggests that the innovations and outcomes are unintentional and occur without purposeful intent. He also notes that the outcomes of these activities in turn become the basis for future innovation.
Yoo et al. (2010) expands on Zittrain’s definition and illustrates generativity as a layered model where innovation on one layer’s technology can have a cascading effect on other layers. An example of this is a camera using available hardware combined with a recording device within a single unit to expand its functionality and become a video camera.
Jarvenpaa and Standaert (2018) state that generativity theory explains how novel behaviours, developments, and products are a result of pre-established behaviours and concepts. In this definition, the focus is new innovations stemming from the connection of old ones which have opened the doors for these new ideas. Nambisan (2017) uses the example of when Apple updates its operating system (iOS) to implement new capabilities, and how this paves the way for new app developments and new entrepreneurial opportunities. To expand on Nambisan’s example, when Apple introduced Face ID, the technology opened the doors for businesses to adopt this new security technology to their apps and integrate it into their own sign-in pages to enhance their user experience.
The concept of generativity can also be seen influencing the actions, feelings and behaviours of entrepreneurs. For instance, it can be a motivational input (Faraj et al., 2011) and a source of excitement and positive energy (Henfridsson & Yoo, 2014). For example, when wearable technology with biometric sensors, such as FitBit and Apple Watch, was introduced, it generated a huge buzz in the health industry. Entrepreneurs and innovators were looking to be the first ones to capitalize on this new technology for their own ventures. Today, we see countless fitness apps that are built around the health tracking technology. However, it can also create a sense of urgency for entrepreneurial action through the generation of mental health related issues such as increased anxiety (Carlo, Lyytinen, & Boland, 2004).
It is worth noting that the generativity theory is continuously expanding and is relatively new compared to many of the classical theories of entrepreneurship. However, many of those classical theories were conceived before the digital age. While many are still relevant, it seems only right that we should look for new theories appropriate to these new times. So while these newer theories may not be as refined, they are still very important and should not be disregarded. We look to future empirical research to validate some of the theory's main propositions.
Carlo, J., Lyytinen, K., & Boland, R. (2004). Systemic risk, information technology artifacts, and high reliability organizations: A case of constructing a radical architecture. International Conference on Information Systems Proceedings (pp. 685–696). AIS.
Nambisan, S. (2017). Digital Entrepreneurship: Toward a Digital Technology Perspective of Entrepreneurship. Entrepreneurship Theory and Practice, 41(6), 1029–1055. https://doi.org/10.1111/etap.12254
Yoo, Y., Henfridsson, O., & Lyytinen, K. (2010). The new organizing logic of digital innovation: An agenda for information systems research. Information Systems Research, 21(4), 724. https://doi.org/10.1287/isre.1100.0322
Jonathan L. Zittrain. (2006). The Generative Internet. Harvard Law Review, 119(7), 1974-2040. Retrieved March 25, 2021, from http://www.jstor.org/stable/4093608
Jarvenpaa, S., Standaert, W., University of Texas at Austin, & Vlerick Business School. (2018). Digital probes as opening possibilities of generativity. Journal of the Association for Information Systems, 19(10), 982-1000. https://doi.org/10.17705/1jais.00516
Yoo, Y., Henfridsson, O., & Lyytinen, K. (2010). The new organizing logic of digital innovation: An agenda for information systems research. Information Systems Research, 21(4), 724. https://doi.org/10.1287/isre.1100.0322
Jonathan L. Zittrain. (2006). The Generative Internet. Harvard Law Review, 119(7), 1974-2040. Retrieved March 25, 2021, from http://www.jstor.org/stable/4093608
Jarvenpaa, S., Standaert, W., University of Texas at Austin, & Vlerick Business School. (2018). Digital probes as opening possibilities of generativity. Journal of the Association for Information Systems, 19(10), 982-1000. https://doi.org/10.17705/1jais.00516
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