Different technological regimes are also supported by distinct institutions governing public research and training and, at the market end, the interactions among producers. Such institutions, together with the corporate actors involved contribute to define distinct sectoral systems of innovation and production: see [26] and [27].
22.4 Innovation, Dominance and the Reasons for Disruption at the Firm Level
The aggregate and sectoral evidence provides precious insights into the broad patterns of creative destruction/disruption. Innovation, industrial change and turbulence are systematic features of industrial dynamics. The timing and the specific features of these processes vary substantially over time and across technologies and industries. Creative destruction and disruptive innovations are more likely to occur – but not exclusively – in Schumpeter Mark I sectors or in the early stages of the life cycle of a new industry. Yet, evidence shows at the same time aspects of remarkable stability, with incremental, path‐dependent innovation and persistence of firms’ traits and performances.
At the level of individual firms the picture remains however much less clear, to say the least.
This observation should not be surprising. It is intuitive and should be almost common sense (although not always recognized in standard economic textbooks and literature) that firms simply differ widely from each other. The empirical evidence cited previously confirm that heterogeneity in firms’ characteristics, behavior and performances is strikingly high. There are obviously good reasons for this observations. Indeed, a large stream of literature in management (more than in economics) has emphasized that firms are to be conceived as bundles of idiosyncratic resources and capabilities, which are built over time, are highly contextual and difficult to change quickly. In this view, the competitive advantages of any one company derive precisely from the specific combination of resources that are uniquely controlled by the firm and even more importantly for the competences and capabilities that have been acquired over time through processes of technological and organizational learning. Such learning processes are typically cumulative and path‐dependent: what a firm is and does now is the outcome of its past history and such history heavily constrains what it will possible to do in the future. Moreover, facing an uncertain future, companies place different bets on the perceived opportunities and threats: diversity is therefore a systematic aspect of economic life, even in extremely narrowly defined business lines [28, 29].
Thus, individual firm would typically react differently to the threats coming from new technologies and innovations. Indeed, coming back to the broad questions raised in Sect. 22.1, it is not clear at all that incumbents are always doomed to fail when confronted with disruptive innovation, nor that new firms are always the winners. Even more difficult it is to identify robust regularities about the strategies which lead to success or failure.
An immense literature – mainly based on case studies – provides however a few important suggestions.
First, disruption in almost by definition hard to predict and it is to a large extent an ex‐post phenomenon. When new technologies appear, uncertainty is the name of the game and firms – both incumbents and new entrants – experiment with different visions and approaches. As mentioned previously, most of them will fail and turn out as dead ends. Prediction is almost impossible, unless perhaps is too late, and often nothing more than an educated guess.
Second, disruption does not always come from new firms, but also from existing organizations diversifying into new business lines and products: IBM from punching cards to mainframe computers is only a prominent example among many others. Similarly, disruption seldom occurs through head‐on, direct confrontation with extant products and industry leaders. Much more often, it happens through the development of initially small and unprofitable market niches at the flanks of the main product. An iconic example is personal computers (PC), which created a new mass market for computers whereas previously expensive mainframe computers were sold only to large organizations. Another example is given by mini‐mills vs. integrated steel mills. Mini‐mills used scrap to make cheap, low quality steel of it and the integrated steel companies were not interested at all in this low margin business. However, slowly but steadily, the quality of the mini‐mills steel improved and gained systematically new market segments.
The attack to dominant positions comes from multiple directions and potential competitors, who encircle and put under siege the current leader, often for prolonged periods of time. In this respect, the popular representation of disruption as a cruel frontal battle could be better understood – if it ever happens – as the final episode of a longer war, in which it is not clear who the enemy is – a heterogeneous and constantly changing army of autonomous tribes – and where the battlefield is actually located and how it looks like.
But when and why dominant positions are severely challenged or even destroyed?
There are entirely rational reasons why an incumbent may decide not to invest in innovation threatening to displace them or to delay such investment (e. g. cannibalization of current products), but the managerial literature does not seem to attribute a fundamental role to them. When clear incentives motivations are absent, the literature remains underdeveloped [30].
A first natural candidate for explanation is that new technologies may turn out to be “competence destroying” [31]: that is to say, they overturn and render obsolete existing competencies, skills and know‐how (e. g. transistors and vacuum tubes, quartz and mechanical watches, etc.). In this respect, the very factors that made a firm dominant – the core capabilities – may become “core rigidities” in a new, different technological environment [32].
In more recent interpretations, however, the main cause of “competence destruction” is not the inability to master the new technology as such, but rather the difficulty established firms encounter in responding to shifts in the market place [33], the challenges that innovation poses to their value and support network [34] and in the larger institutional and social regime [35]: again, the PC was directed to groups of customers (individuals) which had never been the focus of mainframe producers.
It has to be stressed that competence destruction in this wider interpretation does not simply or mainly depends on mistakes in decision making at the most senior levels. Certainly, senior teams are likely to be captured by their largest, most profitable customers, making it difficult to allocate resources to initiatives that serve new customers at (initially) lower margins. But such emphasis might be too simplistic or potentially misleading. Recent studies suggest that organizational competences, in the sense of the embedded organizational routines of established companies, may be much more central to established firm failure in the face of disruptive innovation than is generally acknowledged [36]. Organizational capabilities are almost inherently inertial as they based on and expressed by routines which have been learned and developed over time. They are robust and provide stability to the organization and become deeply embedded cognitive models, shared systems of understanding and of incentives that reinforce, and are in turn reinforced by, the local experience of the firm [37]. Thus, they are path‐dependent and rigid. Exploring a new, possibly disruptive, market thus requires major and difficult changes in patterns of behavior and search that may look unprofitable in the face of deep uncertainty or, even more so, may be not even conceived given the current organizational architecture.
A further important interpretation recently provided by [30], suggests that incumbents failure reflect diseconomies of scope rooted in assets that are necessarily shared across both businesses. Specifically, they show that both Microsoft and IBM were initially very successful in creating free standing business units that could compete with entrants on their own terms, but that as the new businesses grew, the need to share key firm level assets imposed
significant costs on both businesses and created severe organizational conflict. In IBM and Microsoft’s case this conflict eventually led to control over the new business being given to the old and that in both cases effectively crippled the new business.
22.5 Survival and Persistent Leadership
Defeat of the incumbent and victory for the attacker, however, is not the only or even more frequent outcome. In many occasions, dominant firms retreat and diversify into related but different lucrative business. Once again IBM provides an example: it succeeded in entering the new market for personal computers, obtaining a good, but not dominant position. When profit margins fell into that segment, IBM left the PC market and transformed itself into an immensely successful organization selling services and consultancy. In this respect, it remains also to clarify what exactly is destroyed, when disruption occurs: firms, products, business models?
In many other instances, current leaders are able to win, let alone survive. So, what are the capabilities and strategies that allow for maintaining persistent leadership in markets undergoing technological change and potential disruption?
First, it has been long recognized that technological change as such needs not to be destructive for market leaders. In these cases, technological change is defined as “competence enhancing”, meaning that the new technology strengthens rather than weaken the core competences and capabilities of incumbents. The ability of (some) companies to innovate cumulatively and systematically is actually a fundamental source of sustained leadership. But, more than this, in many instances, major – and not simply incremental – innovations, new products and markets have been created by established firms: chemicals, pharmaceuticals, oil, important segments of the “information technology” industry.
Second, incumbents are able to defend their leadership by relying on their big pockets, by imposing their standards, by forging alliances with new firms and maintaining the control of crucial complementary assets, i. e. the upstream and downstream assets necessary to successfully commercialize an invention, like marketing, sales forces, experience and influence with regulatory issues [38]: pharmaceuticals and biotechnology are a textbook example.
More generally, some basic concepts have been proposed as essential strategic and organizational components for sustained leadership in environments characterized by continuous and sometimes disruptive technological change.
Absorptive capacities, i. e. a firm’s “ability to recognize the value of new information, assimilate it, and apply it to commercial ends” is the first on the list [39] and [40]. Absorptive capacities are strongly cumulative, as they are built on previous knowledge and continuous research and development (R&D) investment aiming not only at discovering and developing innovations but, even more importantly to create the competences needed to perceive potential threats and opportunities, to effectively absorb the new relevant knowledge and to put it into use within the organization.
More generally, the notion of dynamic capabilities [38] provides an important framework for devising sustaining strategies. Dynamic capabilities are defined as “the firm’s ability to integrate, build, and reconfigure internal and external competences to address rapidly changing environments.” They are actually composed by a combination of multiple capabilities: “the capacity (1) to sense and shape opportunities and threats, (2) to seize opportunities, and (3) to maintain competitiveness through enhancing, combining, protecting, and, when necessary, reconfiguring the business enterprise’s intangible and tangible assets.” The dynamic capabilities theory provides an important intellectual structure for businesspeople to start thinking systematically about why companies succeed—or fail. It is not a recipe, however: it must be made operational case by case considering the specific attributes of the company, of the technology and of the competitive context.
22.6 Conclusion and Ways Forward
Clearly, much more research – both at the empirical and at the theoretical level – is needed in order to grasp some better understanding of the pace and properties of creative destruction and of disruptive innovation. Better and deeper knowledge of these phenomena must be gained by looking at the same time at different but complementary levels: the broad aggregate properties of the patterns of industrial dynamics, the diversity across sectors, the specificities of individual firms.
Here, only a couple of remarks may be proposed in the view of suggesting avenues of future research. First, almost all of the available research relates to threats to existing products/business models of a company. Much less is known about the behavior and performance of industry leaders when the threat is not directly to their core product(s), but to the business models and products of its customers and suppliers, thereby forcing upstream and downstream incumbents to adapt to those changes. Examples might be the oil industry facing the advent of electric cars or insurance companies having to devise new strategies, products and organizational changes in the light of the diffusion of autonomous driving, robotics or next generation genomics. Analysis of industrial change in interdependent industries is notoriously difficult: it implies the study of complex dynamics and co‐evolutionary processes that may entail a variety of direct and indirect feedbacks as well as unintended consequences. Some work in this direction has been developed but a lot remains to be done [41]. Yet, this is a crucial source of challenges for both incumbents and potential competitors.
A second important area of research concerns the role of regulation and standards in the processes of creative destruction and innovative competition. They clearly play a major role in shaping the evolution of the industries and the fate of the companies involved. The case of the Internet is an excellent example and recent studies show how important and complex are the processes that lead to the development of those rules, standards and laws [42]. Here again, much remains to be understood.
References
1.
K. Marx and F. Engels, The Manifesto of the Communist Party, 1848.
2.
J. A. Schumpeter, The Theory of Economic Development: An Inquriy into Profits, Capital, Credit, Interest and the Business Cycle, Transaction Publishers, 1934.
3.
J. A. Schumpeter, Captialism, Socialism and Democracy, New York: Harper & Row, 1942.
4.
G. Dosi and R. R. Nelson, “Technical change and industrial dynamics as evolutionary processes,” in Handbook of the economics of innovation, Volume 1, Burlington, Academic Press, 2010, pp. 51–128.Crossref
5.
C. Freeman and C. Perez, “Structural crisis of adjustment, business cycles and investment behaviour,” in Technical Change and Economic Theory, London, Frances Pinter, 1988, pp. 38–66.
6.
T. Bresnahan, “General Purpose Technologies,” in Handbook of the Economics of Innovation, Volume 2, Amsterdam, Elsevier, 2010, pp. 761–791.
7.
F. Louçã and S. Mendonça, “Steady change: the 200 largest US manufacturing firms throughout the 20th century,” Industrial and Corporate Change, 11 (4), pp. 817–845.Crossref
8.
J. L. Bower and C. M. Christensen, “Disruptive Technologies: Catching the Wave,” in Harvard Business Review 73, no 1, 1995, pp. 43–53.
9.
E. Danneels, “From the Guest Editor: Dialogue on The Effects of Disruptive Technology on Firms and Industries,” Journal of Product Innovation Management, 23 (1), pp. 2–4.Crossref
10.
e. Danneels, “Disruptive Technology Reconsidered: A Critique and Research Agenda,” Journal of Product Innovation Management. 21 (4), pp. 246–258.Crossref
11.
J. Lepore, “The Disruption Machine. What the gospel of innovation gets wrong,” The New Yorker, Annals of Enterprise, 23 June 2014.
12.
A. A. King and B. Baatartogtokh, “How Useful Is the Theory of Disruptive Innovation?,” MIT Sloan Management
Review, September 2015.
13.
M. Weeks, “Is disruption theory waring new clothes or just naked? Analyzing recent critiques of disruptive innovation theory,” Innovation: Management, Policy & Practice, 17:4, pp. 417–428, 2015.Crossref
14.
G. Dosi, “Statistical regularities in the evolution of industries. A guide thorugh some evidence and challenges for the theory,” in Perspectives on innovation, Cambridge/New York, Cambridge University Press, 2007.
15.
N. Bloom and J. Van Reenen, “Why Do Management Practices Differ across Firms and Countries?,” in Journal of Economic Perspectives 24 (1), 2010, pp. 203–24.Crossref
16.
K. Pavitt, M. Robson and J. Townsend, “The Size Distribution of Innovating Firms in the UK,” The Journal of Industrial Economics, Vol. 35, No. 3, pp. 297–316, 1987.Crossref
17.
G. Dosi, “Technological paradigms and technological trajectories. A suggested interpretation of the determinats and directions of technical change,” in Research Policy, 11 (3), 1982, pp. 147–162.Crossref
18.
K. Pavitt, “Sectoral Patterns of Technical Change: Towards a Taxonomy and a Theory,” Research Policy, 13, pp. 343–373.Crossref
19.
G. Dosi, O. Marsili, L. Orsenigo and R. Salvatore, “Learning, market selection and the evolution of industrial structures,” in Small Business Economics, 7, 1995, pp. 411–436.Crossref
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