**3. Innovation**

Several authors (among others, [2]) hypothesized that innovation is among the key determinants of adaptive resilience. However, there is no one single definition of innovation. It has been investigated by a wide array of disciplines, with economic approaches alone adopting different theoretical perspectives.

In the neoclassical models, before the 1960s, innovation and technological change were treated as "manna from heaven" and approached as being largely exogenous to the economy. Technological change was purely the result of a scientific discovery that was not driven by any economic incentive. In the neoclassical approach, knowledge, or a particular advance in knowledge, can be applied widely among firms. All the companies have equal abilities in transforming such knowledge into production capability since it is codified, context-independent, and characterized by negligible transmission cost.

Joseph Schumpeter, instead, by placing innovation at the heart of his theory of economic development, has greatly influenced the economics of innovation literature. Schumpeter, indeed, argued that "economic development consists primarily in employing existing resources differently, in doing new things with them" ([25], p. 68). In this study, he also proposed a list of five main types of innovations:


#### *Resilience and Innovation: A Conceptual Approach DOI: http://dx.doi.org/10.5772/intechopen.113842*

Whereas product innovation is linked to the development of a brand-new product or improved product or services, process innovation involves, instead, changes in the production method. It concerns discovering a novel way of achieving an output, which was traditionally done differently.

As Antonelli [26] argues, Schumpeterian innovation is a fundamental component of a dynamic process that cannot be analyzed with any equilibrium approach.

Schumpeter's theories about innovations can be classified under two labels: Schumpeter Mark I and Schumpeter Mark II. The Schumpeter Mark I conceptualization of innovation proposed in The Theory of Economic Development [25] is based on a creative destruction model in which individuals (the entrepreneurs), or uncoordinated groups, prompt radical innovations that disrupt the existent equilibrium. Radical innovations occur when new products, services, processes, or strategies are introduced to a market, replacing existing technologies and methods. On the contrary, in Schumpeter Mark II theory—firstly formalized in the book "Capitalism, Socialism and Democracy" [27] —the innovative process is based on highly coordinated approaches of incremental accumulation undertaken within very large firms [7]. Incremental innovations consist of a series of small improvements made to a company's existing products or processes. This leads us to argue that in this context, innovation assumes a recombinatory nature. This is arguably due to the fact that, according to Weitzman [28], new knowledge does not fall like "manna from heaven," but it is the results of a process that combine already existing pieces of knowledge in a new way.

Schumpeter's works highly influence evolutionary economics literature. In this theoretical framework, since the seminal contribution of Nelson and Winter [6], the traditional starting point to explain the innovative process is the firm, which competes on the basis of its routines (knowledge) and core competences that are endogenously built up over time. Evolutionary economics scholars argue that routines are the most appropriate unit of analysis through which to explain the decision-making process under bounded rationality. As highlighted by Herbert Simon [29] in his Nobel Memorial Lecture, decision-making in organizations typically involves heuristics because the conditions for rational models rarely hold in a heterogeneous and uncertain world. The classical model for rationality, instead, foresees the perfect knowledge for all the agents among all the relevant alternatives. Therefore, in this theoretical framework, market is always in equilibrium.

This idea is sharply at odds with the argument of Schumpeter that economic growth has to be understood as a process involving disequilibrium. Economic evolution is the process by which existing structures of knowledge, such as markets, firms, technologies, institutions, and industries, endogenously change through a selective process of "creative destruction" [27]. Following this line of inquiry, Winter [30] defines routine as "a pattern of behavior that is followed repeatedly but is subject to change if conditions change" ([30], p. 263). Routines (and the supporting skill packages) are a key repository of knowledge in the firm ([31], p. 152) in the sense that they *"represent successful solutions to particular problems"* ([32], pp. 191–192). In this context, an organization's innovative process is driven by a learning behavioral mechanism where the search for new problems and new problem-solving procedures enhances the creation of new routines that break away from the past pattern of behavior. Thus, in the evolutionary models, economic dynamics show only temporary convergence toward equilibrium to be "upset" by endogenously determined innovative firm behavior [6]. The disequilibrium tendency caused by deviant firms becomes the fundamental driving force underlying economic development.

In this scenario, evolutionary economists view the search for supranormal profits by innovation, called Schumpeterian competition, as the primary dynamic in the economy (moving away from equilibrium), while the erosion of profits due to price competition is only considered a secondary dynamic (converging to equilibrium). In the evolutionary economics theoretical framework, market competition acts indeed on the variety of routines (old and new) as a selective device by determining which firms survive and prosper and which ones decline. Thus, in a dynamic economy, the selected routines become dominant over time, enabling the firms endowed with fitter routines to grow and to gain a competitive advantage against their rivals. The diffusion and imitation of innovative routines, however, is not a straightforward process. This is arguably because the set of competencies and the knowledge that make up organizations' routines are both historically and locally determined (among others, Teece and Pisano [33]). Routines present, indeed, both a cumulative and tacit nature. It is well recognized by the literature (among others, Nelson and Winter [6]) that routines change in a path-dependent manner and are shaped by history. The set of competencies may adapt incrementally in response to feedback, and firms do so based on the knowledge they have built up in the past.

Moreover, routines are credited with being able to store tacit knowledge, which is hard to codify and transmit across different geographical contexts. According to Glaeser et al. [34], this is because "intellectual breakthroughs must cross hallways and streets more easily than oceans and continents" (p. 1226). Firms located in the same circumscribed geographical and technological area may, indeed, benefit from tacit knowledge spillovers only transmittable through repeated interactions. Thus, from this evolutionary process of firm dynamics based on competition, innovation, and selection, an emergent spatial pattern of economic activity arises.

In this context, evolutionary economic geography is increasingly gaining attention. It, indeed, deals with "the processes by which the economic landscape the spatial organization of economic production, distribution and consumption is transformed over time" ([35], p. 539). This field of study, by applying the core concepts and methodologies from evolutionary economics in the context of economic geography, recognizes the importance of place-specific elements and processes. In particular, it investigates how the spatial distribution of routines evolves. Boschma and Frenken [36] argue that we can classify the application of the evolutionary economic geography scholars into three main levels of analysis: firm, industry and network, and spatial systems. The applications that employ firms as units of analysis mainly focus on the firms' locational choices. Sectors instead are mainly analyzed through models of stochastic growth, on spin-offs and agglomeration economies. Networks, on the contrary, are considered the vehicles for knowledge diffusion, and one of the main topics investigated at this level of analysis is whether knowledge diffusion and innovation is more a matter of being in the right network or in the right place, or in both. Finally, spatial systems are obtained by aggregating the meso-level actors to the related macro level. The localities in spatial systems, be it cities, travel-to-work areas, provinces, or regions, are characterized by a dynamic interplay among sectors, networks, and the real place. According to the literature [37], the process of structural change is determined by the sectorial logic underlying the evolution of spatial systems.

In light of the aforementioned framework, to sum up, we can argue that innovation is a complex knowledge-driven process based on the development and the commercial exploitation of a new idea for a product or process that contributes to wealth creation and profitability [7]. In this context, new knowledge is endogenously generated, shared, and recombined through continuous dynamics of interactive

learning among co-localized agents. Accordingly, innovation is a cumulative process with evolutionary trajectories [6] and geographically grounded roots. This is arguably because economies are based on and driven by knowledge, and knowledge is never static, but it is constantly being created [38]. Thus, economies are always evolving through the process of adaptation and transformation rendering capitalism restless.
