Managing business model innovation to create value for all stakeholders
Managers and designers of innovative business models that are enabled by emerging technologies need to build legitimacy with ecosystem participants. Yet increasing legitimacy within the ecosystem raises competitors’ incentives to imitate the business model innovators, thereby adversely affecting the innovators’ ability to appropriate value.

The authors refer to this trade-off as the appropriation dilemma. The authors draw on institutional and resource-based perspectives to develop propositions about mitigating the appropriation dilemma and provide illustrations with a range of cases.

This theory development contributes to the technology management and business model innovation literatures by delineating how business model innovators can create value for all stakeholders and at the same time appropriate value through strategic business model design, a task that is particularly salient in the context of emerging technologies. The authors also strengthen the theoretical foundations of business model innovation research by grounding propositions about the strategic design of business models in resource-based theory and institutional theory.

Yuliya Snihur, Christoph Zott and Raphael (Raffi) Amit. 2021. Managing the Value Appropriation Dilemma in Business Model Innovation.

Profiting from enabling technologies across different domains
How to profit from innovation has been an important question for both innovation scholars and practitioners over the years. It is certainly a relevant question for all types of technological innovation, including emerging ones.

David J. Teece’s profiting from innovation (PFI) framework [Teece DJ (1986) Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy. Res. Policy 15(6):285–305.] sets forth a theory of the relevant contingencies. However, Teece’s framework focuses on technologies with applications in specific domains. The authors focus on the question of how to profit from enabling technologies: technologies that are applicable across multiple domains.

The authors argue that capturing value in such circumstances is fundamentally different from profiting from less-enabling technologies and raises new issues with respect to the relevant business models and public policies. This paper’s contribution is threefold. It formally revises and extends the original PFI framework to include the case of enabling technologies, it provides empirical evidence to support the distinction between profiting from enabling and profiting from narrower “discrete” technologies, and it generates perspectives on the appropriate business models for these technologies and discusses related public policy implications, in light of the fact that the share of the benefits the innovator can capture is likely to be even smaller for enabling than for discrete technologies.

Alfonso Gambardella, Sohvi Heaton, Elena Novelli and David J. Teece. 2021. Profiting from Enabling Technologies?

Technology’s value creation: Emerging, enabling, embedding
Technology has been conceptualised in many ways, ranging from scientific and engineering knowledge to business enterprise “production functions” to physical artifacts that fulfill a particular purpose. These different conceptualisations underscore technology as a multifaceted construct that encompasses production know-how, problem solving, and functionality.

Although new technologies present significant opportunities for value creation, the realisation of those opportunities varies across firms, industries, and technologies over time. An understanding of the sources of this variation can help firms with their strategic decision making and offer guidance to policy makers on how they can facilitate technological progress to help spur economic growth. It requires recognising the important distinction between invention and innovation that goes back to Schumpeter (1934). Whereas inventions represent scientific discoveries that encompass new knowledge within a technological domain, innovation represents the subsequent commercialisation of those inventions so as to create value—and, hopefully, capture some of it as well.

Therefore, situating the technology in its commercialisation context and identifying the features that can have a significant impact on its value creation are pivotal to understanding how firms and policy makers can contribute to technological progress and generate superior performance.

Read this Open Access article online for free.

Rahul Kapoor and David J. Teece. 2021. Three Faces of Technology’s Value Creation: Emerging, Enabling, Embedding.

Enabling technologies and the role of private firms
Investments in enabling technologies—including the fifth-generation technology standard for broadband cellular networks (5G), artificial intelligence (AI), and light detection and ranging (LIDAR) technology—are important strategic decisions for firms.

This paper asks how inventions that private firms developed with (versus without) public-sector partners differ in their enabling technology trajectory. Using a novel method of machine learning matching, the authors compare patented technologies generated from more than 30,000 public–private relationships with comparable technologies invented by private firms alone during a 21-year period.

To measure the enabling potential of a technology, the authors introduce a new enabling technology index. The findings show that private-firm relationships with the public sector—in particular cooperative agreements and grants with mission agencies (National Aeronautics and Space Administration and Department of Defense)—are likely starting points for enabling technology trajectories. The authors thus put a spotlight on organisational arrangements that combine the breadth of exploration (agreements, grants) with deep exploitation in a particular domain (mission agency). A key contribution is a better understanding of the types of private-firm efforts that are associated with enabling technologies.

The authors also challenge the common assumption that enabling technologies have their origins only in public-sector projects and show how private firms are involved. This paper’s significant contribution is to show how private firms can change evolution of ecosystems through technology development.

Jason M. Rathje and Riitta Katila. 2021. Enabling Technologies and the Role of Private Firms: A Machine Learning Matching Analysis.

Choosing technology in start-ups
A central premise of research in the strategic management of innovation is that start-ups are able to leverage emerging technological trajectories as a source of competitive advantage. But, if the potential for a technology is given by the fundamental character of a given technological trajectory, then why does entrepreneurial strategy matter? Or, put another way, if the evolution of technology is largely shaped by the strategic choices entrepreneurs make, then why do technological trajectories exhibit systematic patterns such as the technology S-curve?

Taking a choice-based perspective, this paper illuminates the choices confronting a start-up choosing their technology by resolving the paradox of the technology S-curve through a reformulation of the foundations of the technology S-curve. Specifically, the authors reconceptualise the technology S-curve not as a technological given but as an envelope of potential outcomes reflecting differing strategic choices by the entrepreneur in exploration versus exploitation.

Taking this lens, the authors are able to clarify the role of technological uncertainty on start-up strategy, the impact of constraints on technological evolution, and how technology choice is shaped by the possibility of imitation. The findings suggest that staged exploration may stall innovation as a result of the replacement effect, increasing the strategic importance of commitment.

Joshua S. Gans, Michael Kearney, Erin L. Scott and Scott Stern. 2021. Choosing Technology: An Entrepreneurial Strategy Approach.

Using increasing abstraction to accelerate adoption of complex technologies
Many new technologies are complex and embody high levels of technical sophistication, and applying them should require significant knowledge and experience. Yet, the rapid adoption and incorporation of these technologies into other innovations seems inconsistent with the expertise needed to make them work.

In this paper, the authors propose increasing levels of abstraction as a strategy for speeding the adoption of new technologies. Higher-level abstractions package complexity in ways that makes them easier to understand and recombine, and they decrease the resources needed by firms to deploy sophisticated technical know-how. Increasing the level of abstraction is a way to push forward the innovative frontier by making such difficult-to-use technologies readily accessible to other innovators.

Although this framing has been used in engineering and software development to describe modular encapsulation and cumulative innovation, the authors propose its use in the management literature to describe more broadly the uptake of new technologies and their facile recombination. This framing casts a different light on cumulative innovation and exposes new managerial questions to explore.

Willy C. Shih. 2021. Increasing the Level of Abstraction as a Strategy for Accelerating the Adoption of Complex Technologies.

Managing uncertainty surrounding emerging technologies
Emerging technologies, while offering enormous potential for economic growth, carry a high degree of uncertainty regarding whether and when that potential may be realised. How can firms evaluate the uncertainty surrounding an emerging technology?

To address this question, the authors offer a structured approach that unbundles the uncertainty surrounding emerging technologies, incorporating both supply- and demand-side factors. These include the focal technology itself, the potential market applications, the users adopting the technology, the ecosystem of activities that support the technology’s value creation, and the business model with which the technology is being commercialised. The authors further consider that the uncertainty surrounding each of these sources may not be resolved in a vacuum, but, rather, that it may interact with other sources of uncertainty in a pooled, sequential, or reciprocal way.

Such a structured approach of evaluating uncertainty can help firms and managers in terms of the cognitive processes and the managerial practices and provide micro-foundations for dynamic managerial capabilities. The authors illustrate the applicability of the framework for two emerging technologies—gene therapy and autonomous vehicles—and how the framework can be integrated with prominent managerial practices for managing uncertainty.

Rahul Kapoor and Thomas Klueter. 2021. Unbundling and Managing Uncertainty Surrounding Emerging Technologies.