The evolution clusters of technologies with initial intra-connections and growing inter-connections
Networks of Breakthrough Technologies and their Use in Strategic Games for Competitive Advantage
2016 ||| SCOPE: Network Theory, Game Theory, Breakthrough Technology ||| PROJECT: Master's of Science in Engineering and Management
Summary
Breakthrough technologies sustain competitive advantage and are seen as the engine of
growth. These technologies can be developed by leveraging internal know-how, but more
often they come from an infusion of external technology. The task of screening and selecting
innovative technologies to develop or acquire is challenging and relies on various underlying
assumptions. This research proposes a systematic framework of analysis that combines net-
work theory and game theory concepts to analyze a set of breakthrough technologies and the
companies linked to them, both in the order of O(100) .
In this framework, breakthrough technologies are represented as a network where nodes represent technologies and links represent dimensions of similarities between these technologies. Network-level metrics provide
proxies for estimating the benefit of a node and the cost of a link. The benefitt is derived
based on the position of the node in the network, and the cost of a link is estimated based
on the similarities of technologies it connects. As firms consider a particular target technol-
ogy, the framework offers a way to calculate the payoffs of following a particular path in the
network to attain the target from any one of the technologies already in the firm's portfo-
lio. The model provides a recommendation for the best strategy under specific competitive
scenarios.
Finally, the application of this method is illustrated with various use cases, to
analyze strategic decisions made by companies and to explore some that are ongoing. In
particular, this analysis looks at hypothetical two-player strategic games in the energy sec-
tor, comparing the competitive positions of SolarCity, Siemens and Google to conclude that
all three companies have dominant strategies to invest in this sector. The framework was
also applied to a strategic game where Google competes with Magic Leap, in the bio-fuel
sector and showed a dominant position for Google. The last three scenarios analyzed rep-
resent real-world cases, two in the autonomous vehicle domain involving Apple and Toyota
and Apple and Tesla and one in the robotics domain involving Toyota and Amazon. The
analysis showed the existence of a coordination game in the autonomous vehicle sector where
collaboration was benefecial for all parties. Finally, in the robotics case involving the sell-off
of Boston Dynamics by Google, the analysis showed that Toyota can leverage a first mover's
advantage to create a dominant strategy against Amazon.
Motivation
The interest for this research topic was sparked by recent developments in the Internet of Things sector, a sector poised to transform our personal lives and industrial systems. Against this backdrop and the fact that objects and products are increasingly interconnected, many companies have started expanding their technology portfolios. Some have begun entering completely new technology domains. As this trend continues, competition will increase for breakthrough technologies as both the number of firms pursuing a given technology increases, and the number of alternative technologies a single firm considers increases. This observation led us to wonder how firms select breakthrough technologies to use for creating innovative services and products. The scope of this research focuses on key questions relevant both to companies in the Internet of Things sector as well as to companies outside that sector. In particular, we examine the questions, ”How will companies select ’breakthrough’ technologies to augment their portfolios?” and, ”How will firms position themselves in strategic games against competitors considering the same technology?” Behind the aforementioned high-level questions lie other fundamental questions we explore in this research: ”How do we build the appropriate breakthrough technology landscape?”; ”How do we link breakthrough technologies together?”; ”How do we represent a firm’s position on a technology landscape?”; ”How do we define the technology options a firm has?”; and finally, ”How do we evaluate the payoffs of different strategies in competitive games?” The interconnectedness of technologies and thus the interconnectedness of firms that de- velop, or acquire, them lends itself well to a network representation. Therefore, in this study we have selected network theory as the framework for building the technology landscape and for understanding the links between technologies and firms. Additionally, since competitive forces are strong and strategic moves are important in an increasingly crowded technology space, we selected game theory as the framework for analyzing strategic moves. The result is a model used to uncover underlying links between technologies and firms and allow us to simulate strategic games where multiple firms target the same technology for development or acquisition. The output of the model allows us to understand real-world cases and to predict strategic moves that maximize benefit to a given firm.In chapter 2, we define the meaning of ’breakthrough innovations’ and provide an overview of the literature search focused on where innovative technologies originate and how firms select, evaluate and integrate them into their portfolios. We also make a case for why this particular problematic is a strategic game. In the second part of this chapter we provide definitions of the methods used in the remainder of the research. Starting with network theory, we cover mathematical definitions, and the theory’s use to formalize the representation of complex natural and engineered systems. Then game theory is introduced as a framework suitable for analyzing most business interactions in which multiple participants seek to maximize their benefit in response to other participants’ strategies. Terminology used in Chapter 5 also is introduced. Finally, we provide a short overview of Natural Language Processing, with a particular focus on the use of the IBM-Watson tool in this research. Chapter 3 describes the methodology of this research. In particular, it explains the framework proposed, the data samples applied for developing the framework and the use cases selected to illustrate how the framework would apply in practice. The framework proposed represents breakthrough technologies and the firms linked to them as interconnected network layers. The particular technologies related to a firm are identified through a semantic analysis of descriptions of the technologies. Starting from a firm’s position in the technology network and given a target technology, this framework allows us to evaluate different strategies to acquire the target technology, particularly under competitive conditions. The second part of this chapter addresses the selection of individual breakthrough technologies to build the overall landscape.
Chapter 4 focuses on the definition of several dimensions of technology inter-relatedness. Specifically, we use Natural Language processing to carry out a semantic analysis of the technologies, from which several measures are extracted: (1) concepts; (2) keywords; (3) taxonomy and (4) entities. Technologies and companies are linked together along each dimension if they share at least one element. The strength of the link is represented by the number of elements in common. In this chapter, we compare the four technology networks and two company networks to each other, to select the best dimensions for network representations. Network-level and node-level measures are extracted to help estimate the cost of moving along a given path in the network, and the benefit of a given target technology. Finally, a trade-space of all possible technology pairs is built to help compare the different options. Nodes and edges are assigned benefits and costs respectively, and these are used in the payoff matrices developed in Chapter 5. In Chapter 5, we focus on firms’ strategies related to building breakthrough technology portfolios. Applying the network of technologies proposed in Chapter 4, we analyze where existing firms’ portfolios fall on the network. This is done by highlighting the technology linked to the firms (represented by nodes in the network) and using this technology as a starting point to reach target technologies on the network. The exploration of alternative paths from the source technology to the target technology is based on the cost of the path and the benefit the target technology holds. The combination of these two measures results in the payoff of the chosen strategy. Under competitive conditions the payoff calculation is modified, and can lead to rejection of the previous strategy. The key focus in this section is to analyze the evolution of a firm’s network as it runs through a series of games (corresponding to different paths on the network) with the aim of acquiring more technologies. Finally, Chapter 6 concludes by proposing other areas of research to expand on the topic.