Business, Computing, E-Commerce, I.T., Information Systems, Manufacturing, Marketing, Media, Operations Management, Quantitative Methods
I am a part-time senior lecturer and PhD student in E-Commerce. I have a master’s degree in telecommunication engineering and a bachelor’s degree in computing. During the course of my academic career, I have published in a variety of peer-reviewed journals and magazines, both technical and managerial. In the past, I have worked with leading mobile phone equipment suppliers on developing business models in support of multi-radio interface technology. I maintain expertise in a variety of disciplines including, but not limited to, Business, Management, Marketing, Market Intelligence, Computing /IT, and telecommunication engineering. Furthermore, I subscribe to a variety of market intelligence reporting agencies which enables me to quote and refer to facts and figures often inaccessible in a traditional academic environment. Furthermore, I have access to a variety of simulation software and telecommunications/IT laboratories.
A review the theory of disruptive technologies
The theory of disruptive technologies has been widely studied as part of innovation theory. Incorporating research in product and process innovation as well as in techno-economic analysis of technology markets, disruptive technologies have gained a considerable amount of interest in technology organisations.
Generally, a disruptive technology has been perceived as one that introduces superior technological qualities to the mainstream product and thus causes a disruption to the market of the mainstream product. Christensen disagrees with this, according to the theory presented in the book “The Innovator’s Dilemma” (Christensen, 1997). Taking Christensen’s (1997) theory as a starting point, a disruptive technology is one that initially has lower performance and qualities when compared with the original product. However, as the technology develops, it will begin to occupy a place in the market of the mainstream technology and may, indeed, surpass the original product in terms of performance. A disruptive technology change is always classified as one that has had a lower initial performance (Christensen, 1997; Christensen and Raynor, 2003). It also addresses a different market segment compared to the original product and thus competes on a different set of issues and priorities. A critical aspect to note here is that the concept of disruptive technologies is not limited to physical consumer products but can equally apply to a service-based industry.
In this paper we will discuss the basis of the theory of disruptive technologies proposed by Christensen and his colleagues. This will be followed by a review of the criticism of, and proposed extensions to his theory, from an ex post perspective.
1.1 Christensen’s Theory of Disruptive Technology
Christensen’s book, written in 1997, gives an insight into the theory of disruptive technology that can be applied to most technology-related industries. In order to prove the practicality of his proposed theory, Christensen wrote another book titled ‘The Innovator’s Solution’ in 2003. In this book, he gave practical examples of how to make use of the theories put forward in his earlier book. In this section, we describe the fundamentals of Christensen’s theory.
Technological disruptions have occurred throughout history and may come in any form. Disruptive technological changes and disruptive innovations, as Christensen and Raynor (2003) refer to them in ‘The Innovator’s Solution’, drive industries to the next phase of development and can significantly protect organisations from destruction.
Christensen (1997) makes a distinction between a disruptive technology and a sustaining technology. A disruptive technology is one that will eventually take over the mainstream market and become the dominant technology. It is both radically different from the present mainstream technology and has a poorer performance record. Sustaining technologies are those that introduce incremental improvements to the performance of the existing technology. Sustaining technologies address the same market as the original product; they improve the performance of the established product along the dimensions of performance that the mainstream customers have historically valued (Christensen, 1997; Christensen and Raynor, 2003; Christensen and Overdorf, 2000). Sustaining technological changes are usually introduced by the incumbents or leading firms in the existing market and they rarely fail in such ventures, as noted by Christensen and his colleagues (Christensen, 1997, Christensen and Raynor, 2003). New entrants into the fields being addressed by sustaining technologies are very likely to fail as the incumbents would always have the upper hand. On the other hand, the new market for disruptive technologies has growth potential. The substandard technology can be developed by new entrants by sustaining improvements in their own value networks to a level sufficient to satisfy mainstream customers (Christensen, 2004). Although the performance of disruptive technology is inferior, at some point it starts to attract the mainstream consumers. Christensen’s notion of sustaining and disruptive technologies is explained in the following section.
1.1.1 Christensen’s View on the Nature of Disruptive Technologies
Figure 1.1: The Impact of Sustaining and Disruptive Technological Change; Source: Adapted from Christensen (1997); Christensen and Raynor (2003)
Figure 1.1 which shows the impact of sustaining and disruptive technologies, as depicted by Christensen (1997, Christensen and Raynor, 2003), is widely accepted as the most powerful analytical tool provided by Christensen’s theory (Danneel, 2004; Acee, 2001; Walsh, Kirchhoff and Newbert 2002). The technology curves show that after a point in time, the user’s requirement for performance becomes lower than that provided by the original product (Point 1). A disruptive technological innovation results in a new curve being added. As its performance is lower than that offered by the mainstream technology, it cannot be represented by the same curve. Christensen characterises disruptions as being either ‘low end’ or ‘new market’.
‘Low end’ disruptive technology initially targets the requirements of the low end of the market (Point 2) but as the technology improves, it can begin to address the needs of the high end of the market as well and is able to compete with the mainstream technology. This cycle, as envisioned by Christensen (1997), continues and is repeated when a new disruptive technology enters the market. Customers at the low end of the market have lower performance criteria, which are exceeded with the further development of the mainstream technology. The needs of the low end market are not as rigorous as that of the high end market; its requirements can be fulfilled by the early developmental stages of disruptive technology. At the same time, the evolving disruptive technology is improved further by sustaining innovations. At a certain point, it is able to meet the performance requirements of the high end market segment, competing with the mainstream technology in this segment of the market. Because of its lower profit margins, it will eventually out-compete and displace the mainstream technology and take over this segment as the performance of the mainstream technology becomes too high, even for the high end market.
Another technology depicted in Christensen’s analytical tool is that of ‘new market’ disruption. A new market disruptive technological innovation is characterised by a separate graph which extends from the original market. Because new market disruptions address a market that has not existed and are based on performance characteristics that are different from the original technology market, they cannot be represented by the same market graph. The new market disruption addresses the needs of non-consumers or consumers who were not served by the original technology. The challenge in a new market is not to compete with the incumbent but to compete against non-consumption (Christenson and Raynor, 2003). It therefore does not invade the incumbent’s market but pulls customers away from that market into a new one.
1.1.2 Incumbents’ Behaviour
Besides characterising disruptive technologies, Christensen’s theory also studies firms’ behaviour in relation to disruptive change, especially that of the incumbents. Disruptive technologies, in Christensen’s view, are those that show worse product performance in the near-term and bring to a market a very different value proposition from that which had been previously available. It is complex to forecast market requirements for a market that does not exist. The failure of incumbent firms, according to Christensen and his colleagues (Christensen, 1997; Christensen and Raynor, 2003; Christensen and Overdorf, 2000) is not their inability to gear their strategy towards new emerging markets when the impulsion from customers is lacking. The explanation for the incumbents’ behaviour can predominantly be understood in terms of the power of the established customers in the mainstream market (Christensen and Bower, 1996). According to Christensen, the inability of firms to change strategy at the right time and to allocate sufficient resources to the new technology for the emerging market results in the interaction between distinct circumstances in the internal resource allocation process of the firm. This effect is also suggested by resource dependence theory as developed by Pfeffer and Salancik (1978).
In Christensen’s theory, new entrants often cause the fall of incumbents as their business models are the result of a disruptive technological change. On the other hand, the early entry advantage of the entrant firms can be found in their different capabilities to commit strategically to developing emerging markets created by disruptive technologies, and to identify them earlier (Christensen and Rosenbloom, 1995).Hence, due to an early move into the new market, a competitive advantage may be developed by new entrants; small firms that do not have the extra baggage of having to keep satisfying current clients. According to this theory, the strategies that incumbent firms can choose are restricted by the interests of their existing customers and investors, who supply the resources necessary to survive. Therefore, established firms allocate their resources towards sustaining technologies that address the interests of their existing customers rather than towards disruptive technologies for which the customers and markets are highly uncertain and initially structurally unattractive (Christensen and Bower, 1996). In contrast, based upon Christensen’s research, incumbent firms that have the additional load of capitalising on their existing line of products to known customers, find it hard to adapt their cost structures to fit into emerging new markets. After introducing the new disruptive product to the new market segment, gradually the new entrant grows and soon gains a position in the mainstream market occupied by the older incumbents. As the new entrant grows, it becomes even more difficult for incumbents to enter the even smaller emerging market that will some day become a large market. It is therefore difficult for firms to adapt to new markets when they become too big.In summary, the divergent capabilities of incumbent and entrant firms in the adoption of disruptive technologies are based upon different sets of organisational procedures and values embedded in the firm’s mores that are shaped by its business model (Christensen, 1997; Christensen and Overdorf, 2000).
1.2 The Ex Post Perspective – Christensen’s Extensions and Critics
As reviewed in the previous section (1.1), Christensen’s theory of disruptive technologies is rich and multifaceted. However, a significant amount of extensions to his theory and criticism of it has been documented in the academic literature. In this section we, review these ex post extensions to Christensen’s theory.
Table 1.1: Table Summarising the Contribution of Authors
Walsh, Kirchhoff and Newbert (2002), confirm the accuracy of Christensen’s theory by using survey data gathered from 72 manufacturing firms. The results of their studies indicate that disruptive technologies are rarely commercialised by established firms and start-up firms have two distinct benefits in introducing disruptive technologies. These are: shorter times to market and independence in devising marketing strategies. This is much the same as set out by Christensen and his colleagues.
One of Christensen’s earliest critics was Chesbrough (1999, 2003), who challenged Christensen’s claim that the ‘Principles of Disruptive Innovation’ (Christensen, 1997, p.xviii) are supposed to be useful for all types of firms, technologies and industries. Though some of the characteristics of disruptive technologies may be essential, others may be specific to an industry or regional market. Most of Christensen’s work is validated by well-documented and thorough case studies of specific industries ranging from an industry that manufactures hard disc drives to industries involved with aviation. However, the extent to which these case studies may be generalised has not been addressed. Chesbrough (1999,2003), besides noting that Christensen’s stream of research focused on issues of internal validity while neglecting external validity, demonstrated that a majority of Christensen’s case studies were restricted to US companies. The disruption did not occur in Japanese firms in the same industry with the same technological changes. Although this does not deny Christensen’s concepts in principle, it shows that there are further factors that may influence the possibility of disruption.
Another key area of criticism of Christensen’s theory was the resource commitment of disruptive technologies and the incumbent firms’ initial perception of opportunities for these technologies. Gilbert and Bower’s (2002) research suggests that the initial perception of a threat leads to incumbents over committing resources to disruptive technologies rather than starving from a lack of resources, as Christensen suggests in his research. Reinforcing their claim, are the findings of King and Tucci (2002), who, through their study of the history of the worldwide hard disc industry, found that incumbents were more likely to succeed in new market segments, contradicting Christensen’s claims that new entrants prevailed and incumbents failed. Gilbert’s (2000) suggestions, however, still remain the same as Christensen’s that a separate organisation should be established where it is possible to develop the disruptive technology as a prospect.
From an extension perspective, many publications (Ander and Levinthal, 2001; Ander, 2002; Ander and Zemsky, 2005 ) have expressed concerns about how the presence of durable complementary goods, (in)-compatibility, proprietary standards and network externalities can lead to high switching costs and consequently to lock-in situations in which the power of disruption might be reduced. An example of this supposition could be Microsoft and Intel’s dominance in the personal computer industry as explained by West (2003). If performance oversupply indicates an increasing threat of disruption, then this example raises the question of why the personal computer industry has been dominated by Microsoft and Intel for over a decade. Christensen (2002) recently explained the Microsoft and Intel dominance by their degree of integration compared with their less integrated competitors such as WordPerfect. However, completely relying on the personal computer industry makes the theory appear less convincing. This could make forecasting efforts in the other sectors quite difficult as network effects, as suggested by Schoder (2000), often play an important role in the adoption and diffusion of new services. Unlike most industries that Christensen had examined, in a majority of other technology industries, regulation and limited resources play an important role (Mannings and Cosier, 2001).
From another research direction concerning patterns of change, Christensen has ignored other irregular symptoms of change by emphasising only ‘attacks from below’ (Utterback, 1994; Acee, 2001; Utterback and Acee 2002, 2005). Utterback and Acee argue that the real significance of disruptive technologies is not the displacement of current markets and products but the influence they have in driving diversification of markets.
Ander (2002) criticises the prominence given to the attributes of previously marginal products which, according to Christensen (2003), explain the adoption of the disruptive technology in the mainstream market, and argues that more diverse performance dimensions are the key drivers. The case studies presented Christensen’s research as noted by Danneel (2004) often include one or two performance dimensions dominating the customer’s choice. However, in most cases, the number of performance dimensions is much higher. As an example, in the case of the mobile communications industry, key performance dimensions include cost, reliability, data rate, blocking probability, mobility offering, device weight and so forth.
Adner’s (2002) evidence highlights the role of a lower unit price of disruptive technologies and demand side interplay when invading the established market. Adner (2002) suggests that disruptions cannot be identified by just assessing performance-provided and performance-demanded curves as suggested by Christensen. It also requires identification of the price trajectories of the competing technologies. He argued for the need to recognise the structure of price and demand in order to clarify the impact of disruptive technologies as opposed to previously marginal product attributes. He extended Christensen’s concepts by developing a formal modelling approach to characterise the nature of demand and identified the market structures susceptible to disruption. Being very insightful, his approach has attracted mostly positive feedback from most authors (Danneel, 2004; Govindarajan and Kopalle, 2006; Henderson, 2006). As suggested by Danneel (2004), Ander’s approach could potentially be extended to include various interrelated dimensions of performance, as viewed from both market and technological perspectives. Danneel and Lim and Wong (2006) suggest this may even be used heuristically as a qualitative representation of a competitive regime of interest, rather than a quantitative replication of an exactly calculated position.
Although Christensen’s theory has raised a massive amount of criticism and many questions, it has reached a stage of maturity where it can help practitioners in their struggle with emerging technologies and markets. In view of the reviewed literature, there is no comprehensive and easily applicable method to analyse the disruptions caused by new technologies. Recent research (Adner, 2002; Gilbert 2002; Chesbrough, 2003) suggests that more research is needed for a mature understanding of the theoretical foundation of this phenomenon, in order to develop.
Acee, H.J. (2001). Disruptive Technologies: An Extended View. SM Thesis, Management of Technology, Massachusetts Institute of Technology.
Adner R. And Zemskey, P. (2005). Disruptive Technologies and the Emergence of Competition. RAND Journal of Economics. Vol. 36, Issue. 2, pp: 229-251.
Adner, R. (2002). When are Technologies Disruptive? A Demand Based View of the Emergence of Competition. Strategic Management Journal. Vol. 23, Issue. 8. pp: 667-688.
Adner, R. and Levinthal, D. (2001). Demand heterogeneity and technology evolution: implications for product and process innovation. Management Science, 47, pp: 611–628.
Chesbrough, H.W. (1999). The Organizational Impact of Technological Change: A Comparative Theory of National Institutional Factors. Journal of Industrial and Corporate Change, Vol. 8, pp: 447–485.
Chesbrough, H.W. (2003). Environmental Influences Upon Firm Entry into New Sub-Markets: Evidence from the Worldwide Hard Disk Drive Industry. Journal of Research Policy, Vol. 32, pp: 659–678.
Christensen, C.M. (1997). The Innovator’s Dilemma. USA: Harvard Business School Press.
Christensen, C.M. (2004). Seeing What’s Next: Using the Theories of Innovation to Predict Industry. Harvard Business School Press.
Christensen, C.M. and Bower, J.L. (1996). Customer Power: Strategic Investment and the Future of Leading Firms. Strategic Management Journal. Vol. 17, Issue 3. pp: 197-218.
Christensen, C.M. and Overdorf, M. (2000). Meeting the challenge of disruptive change. Harvard Business Review, Vol. 78, pp: 66–76.
Christensen, C.M. and Raynor, M.E. (2003). The Innovator’s Solution: Creating and Sustaining Growth. Harvard Business School Press.
Christensen, C.M., Clayton M., and Rosenbloom, Richard S. (1995). Explaining the Attacker’s Advantage: Technological Paradigms, Organisational Dynamics, and the Value Network. Research Policy 24: 233-257.
Gilbert, C.G. (2002). Beyond Resource Allocation: Towards a Process Model of Response to Disruptive Change. Harvard Business School Working Paper No. 03-018.
Gilbert, C.G. and Bower, J. (2002). Disruptive Change – When Trying Harder is Part of the Problem. Harvard Business Review, Vol. 80, pp: 94–101.
Govindarajan, V., and Kopalle, P.K. (2006). The Usefulness of Measuring Disruptiveness of Innovations Ex Post in Making Ex Ante Predictions. Journal of Production
Henderson, R. (2006). The Innovator’s Dilemma as a Problem of Organisational Competence. Journal of Product Innovation Management. Vol. 23, Issue. 1. pp: 5-11.
King, A.A., and Tucci, C. L. (1999). Can Old Disk Drive Companies Learn New Tricks?. Proceedings of the 6th Annual Product Development Management Conference. Cambridge, U.K.
King, A.A., and Tucci, C. L. (2002). Incumbent Entry into New Market Niches: The Role of Experience and Managerial Choice in the Creation of Dynamic Capabilities. Journal of Management Science. Vol. 42, Issue. 2, pp: 171-186.
Mannings and Cosier, G. (2001) Wireless everything – unwiring the world. BT Technology Journal, Vol. 19, pp: 65–76.
Pfeffer, J. and Salancik G.R. (1978). The External Control of Organizations: A Resource Dependence Perspective. New York, Harper and Row.
Schoder, D. (2000) Forecasting the Success of Telecommunication Services in the Presence of Network Effects. Information Economics and Policy, 12, 181–200.
Utterback, J.M, and Acee, H. J. (2002). Nano Technology: A Disruptive Technology. Internal Paper Series, ESD-WP-2003-01.15, Massachusetts Institute of Technology.
Utterback, J.M, and Acee, H. J. (2005). Disruptive Technologies: An Extended View. International Journal of Innovation Management, Vol. 9, No. 1, pp 1-17.
Utterback, J.M. (1994). Mastering the Dynamics of Innovation. Harvard Business School Press.
Walsh, S.T., Kirchhoff, B.A. and Newbert, S. (2002). Differentiating market strategies for disruptive technologies. IEEE Transactions on Engineering Management. Vol. 49, Issue.4, pp: 341-351.
West, J. (2003). How Open is Open Enough? Melding Proprietary and Open Source Platform Strategies. Research Policy, Vol. 32, Issue. 7, pp: 1259-1285.