Comparative Theories of the Evolution of Technology

C Comparative Theories of the Evolution of Technology Mario Coccia CNR – National Research Council of Italy, Torino, Italy Yale University, New Haven, CT, USA Synonyms Nature of technology; Technological advances; Technological change; Technological evolution; Technological progress Definition Evolution of technology is a stepwise advancement of a complex system of artifact, driven by interactions with sub-systems and other technological systems, considering technical choices, technical requirements, and science advances, which generate new and/or improved products or processes for use or consumption to satisfy increasing needs of people and/or to solve complex problems in society. Introduction The evolution of technology plays an important role for the economic and social change of societies and the competitive advantage of firms and nations (Arthur 2009; Basalla 1988; Bryan et al. 2007; Coccia 2018a, b, 2019a, b, c; Hosler 1994). In order to explain main theories of the evolution of technology, it is important to clarify the concept of evolution and of technology. Firstly, evolution is a stepwise and comprehensive development of a complex system in nature and/or in society (cf. Coccia 2019e). Secondly, technology is a complex system of artifact that is composed of more than one entity or sub-system and a relationship that holds between each entity and at least one other entity in the system (Coccia 2018a, 2019a). Technology is selected and adapted in society to satisfy needs, achieve goals, and/or solve problems of people, institutions, and nations (Coccia 2005b, 2006, 2012, 2015b, 2017b, 2019a; Coccia and Wang, 2015). Another important concept is the interaction between technologies: an interrelationship of information/resources/energy and of other physical/chemical phenomena in interrelated complex systems of artifacts for reciprocal adaptations in markets and society (Coccia 2019a). In this context, the coevolution of technologies is the © Springer Nature Switzerland AG 2019 A. Farazmand (ed.), Global Encyclopedia of Public Administration, Public Policy, and Governance, https://doi.org/10.1007/978-3-319-31816-5_3841-1 2 Comparative Theories of the Evolution of Technology THEORIES BASED ON COMPETITION THEORIES OF THE EVOLUTION OF TECHNOLOGY NEWTHEORIESBASED ON A MULTI-MODE INTERACTION BETWEEN TECHNOLOGIES  The viewpoint of technological substitution and competition between technologies   Model of Fisher and Pry Predator-prey approach  The approach by Utterback and other scholars  Theory of the technological parasitism and virus-technologies Comparative Theories of the Evolution of Technology, Fig. 1 Theories of the evolution of technology evolution of reciprocal adaptations in a complex system, supporting the reciprocal enhancement of technologies’ growth rate and innovations (Coccia 2019a). Moreover, any technology is not independent from the behavior of other technologies (Coccia 2018a, b). Sahal (1981), analyzing the patterns of technological innovation, argues that “evolution. . .pertains to the very structure and function of the object (p. 64) . . .. involves a process of equilibrium governed by the internal dynamics of the object system (p. 69).” (cf. Coccia 2005b, 2006, 2012, 2014b, 2016) Kauffman and Macready (1995, p. 26, original emphasis) state that “Technological evolution, like biological evolution, can be considered a search across a space of possibilities on complex, multipeaked ‘fitness,’ ‘efficiency,’ or ‘cost’ landscapes.” Kauffman and Macready (1995, p. 27 and p. 42) also point out that evolution, biological or technological, is actually a story of coevolution. In particular, the evolution of technology paves the way for other technologies in a process that Kauffman has called “expanding the adjacent possible.” Tria et al. (2014) suggest a model, based on a generalization of Polya’s urn, that predicts statistical laws for the rate at which novelties happen (e.g., Heaps’ law describes the number of distinct words in a document as a function of the document length, so-called type-token relation), as well as signatures of the process by which one novelty sets the stage for another (i.e., technological evolution). In this research field, Iacopini et al. (2018) describe the occurrence of novelties as a (noncausal) network exploration process (an edge-reinforcing random walk) showing the appearance of Heaps’s law, whereas the model by Mazzolini et al. (2018, p. 8) shows that the causal relationships between individual components encoded in the network affect the trend of Heaps’s law and thus the probability of finding new components in a dependency cone added to a realization (cf. Vespignani 2009). In general, technological evolution can be explained in economics and management with two different approaches (Fig. 1): • Traditional theories are based on processes of competitive substitution of a new technology for the old one and a competition between predator and prey technologies in markets. • New theories based on a multimode interaction between technologies (Coccia 2018a, 2019a; Pistorius and Utterback 1997; Sandén and Hillman 2011; Utterback et al. 2019). A main theoretical framework in this new research stream is the theory of technological parasitism by Coccia (2019a). Comparative Theories of the Evolution of Technology Theories of the Evolution of Technologies Based on Competition Between New and Established Technologies The Viewpoint of Technological Substitution and Competition Between Technologies The adoption and diffusion of a new technology is associated with the nature of some comparable older technology in use. When comparable technologies do exist, each technology tends to affect the behavior of the other. In fact, the evolution of technology does not take place in isolation, but it is a process of actual substitution of new technology for the old one. In this context, an established technology can improve when confronted with the prospect of being substituted by a new technology. Pistorius and Utterback (1997) argue that emerging technologies often substitute for more mature technologies. In general, the interaction between technologies is typically referred to as competition between new and old technology. As a matter of fact, Pistorius and Utterback (1997, p. 72) claim: “Pure competition, where an emerging technology has a negative influence on the growth of a mature technology, and the mature technology has a negative influence on the growth of the emerging technology.” Overall, then, a competition is often embodied in substitutes, and Porter (1980) considers substitutes as one of the forces in his model of industrial competition for competitive advantage of firms and nations (cf. Calabrese et al., 2005; Coccia 2005a, 2015b, 2017b, 2018c, 2018d, 2019d; Coccia and Wang 2015). Model of Fisher and Pry Fisher and Pry (1971, p. 75) argue that technological evolution consists of substituting a new technology for the old one, such as the substitution of coal for wood, hydrocarbons for coal, etc. Fisher and Pry (1971) modeled the evolution of a new product or process becoming a substitute for a prior one and they plotted the substitution data in the form of f/(1 f) as a function of time on semilog paper, fitting a straight line through the resulting points – where f is the market share of the emerging product or process in question versus time (cf. Utterback et al. 2019, p. 2). Fisher and 3 Pry (1971, p. 88) state that “The speed with which a substitution takes place is not a simple measure of the pace of technical advance . . .. It is, rather a measure of the unbalance in these factors between the competitive elements of the substitution.” Predator-Prey Approach Farrell (1993a, b) used a model based on Lotka-Volterra equations to examine pure competition between various technologies, such as nylon versus rayon tire cords, telephone versus telegraph usage, etc. In this context, the interaction between technologies can generate a predator-prey relation, where one technology enhances the growth rate of the other, but the second inhibits the growth rate of the first (Pistorius and Utterback 1997, p. 74). In fact, a predator-prey relationship can exist between an emerging technology and a mature technology, where emerging technology enters a niche market. In this case, emerging technology can benefit from the presence of mature technology. At the same time, emerging technology may reduce the market share of mature technology. Overall, then, a predator-prey interaction has an emerging technology in the role of predator and the mature technology as prey. However, it is also possible to visualize a situation where a mature technology is predator and emerging technology is prey (Pistorius and Utterback 1997, p. 78). Utterback et al. (2019) show this type of predator-prey relation in a specific period between plywood and oriented strand board (OSB) technology (OSB is a composite of oriented and layered strands, peeled from widely available smaller trees). New Theories of the Evolution of Technologies based on Multimode Interactions The Viewpoint by Utterback and Other Scholars Utterback et al. (2019) suggest to abandon the idea that technology and innovation originate only in pure competition between new and established artifacts. These scholars argue that the growth of one technology will often stimulate the growth of other technologies, calling this 4 Comparative Theories of the Evolution of Technology Evolution of a Complex Benefit to Technologies Tj from interaction with Ti System of Technology S(Ti, Tj) Strong Strong + + Parasitism/ Commen- Strong Predation salism Mutualism + Parasitism/ Commensal Predation ism 0 Amensalism Symbiosis Strong Neutral Mutualism Mutualism Commen- Strong salism Commensalism Parasitism – Competition – Parasitism Amensalism 0 Strong Predation /predation + + + Benefit to Technologies Ti from interaction with Tj Comparative Theories of the Evolution of Technology, Fig. 2 Types of relationships between technologies and evolutionary pathways in a complex system. (Note: The notions of positive, negative, and neutral benefit to technologies Ti and Tj in a complex system S from mutual interaction are represented with the following symbols of logic: +, , 0 (zero); ++ is a strong positive benefit to technologies Ti and Tj in S from long-run mutual symbiotic interaction, i.e., coevolution of Ti and Tj in S, 8i = 1, . . ., n; 8j = 1, . . ., m. Thick solid arrows indicate the probable evolutionary route of interactive technologies in a complex system S: the possibility for parasitic-virus technologies to become commensals, mutualists, and symbiotic; thin arrows show other possible evolutionary pathways of technologies Ti and Tj during the interaction in a complex system S of artifact.) interaction as symbiotic competition (Utterback et al. 2019). As a matter of fact, there are many cases where technologies interact in a relationship that is not of competition in the strict sense of the word. In this context, Pistorius and Utterback (1997, p. 72ff) suggest different interactions among technologies in analogy with biology. Sandén and Hillman (2011, p. 407) also propose six technological interactions, using a similarity with the interaction of species, i.e., neutralism, commensalism, amensalism, symbiosis, competition, and parasitism-predation into one category. Coccia (2018a) suggests a matrix to show how these different relationships between technologies evolve over time (Fig. 2). Pistorius and Utterback (1997, p. 67) argue that a multimode interaction between technologies provides a much richer theoretical framework for technology analysis. Theory of Technological Parasitism and Virus Technologies Technological parasitism by Coccia (2018a, 2019a) is a new theory to explain the evolution of technology in society considering the interaction between technologies that generates the coevolution of a host-parasite complex system of artifacts. The theoretical background of this theory is based on a “Generalized Darwinism” (Hodgson and Knudsen 2006) for framing a broad analogy between technologies and evolutionary ecology of parasites that provides a logical structure of scientific inquiry (cf. Coccia 2018a, 2019a). Basalla (1988) suggested that the evolution of technology can Comparative Theories of the Evolution of Technology profitably be seen as analogous to biological evolution. Technological evolution, alongside biological evolution, displays radiations, stasis, extinctions, and novelty (Solé et al. 2013). The crux of the theory of technological parasitism is rooted in the evolutionary ecology of parasites, and since the concept of parasite is uncommon in economics of technology, it is useful to clarify it. In the evolutionary ecology, parasites (from Greek para = near; sitos = food) are any life form finding their ecological niche in another living system (host). Parasites have a range of traits that evolve to locate in available hosts, to survive and disperse among hosts, and to reproduce and persist. Coccia (2018a, 2019a) argues that technologies can have a behavior similar to parasites because technologies cannot survive and develop as independent systems per se, but they can function and evolve in societies if they are associated with other host or master technologies, such as audio headphones, wireless speakers, software apps, etc. that function if and only if they are associated with host or master electronic devices, such as smartphone, radio receiver, television, etc. In particular, a parasitic technology P in a host or master technology H is a technology that during its life cycle is able to interact and adapt into the complex system of H, generating coevolutionary processes to satisfy human needs and desires and/or solve problems in society. Parasitic technologies are often subsystems embedded within and primarily functional in the ecological system of host or master technologies. A technology can be a parasite of different hosts or master technologies, as well as a technology can be a host or master of different parasitic technologies (e.g., mobile devices are host of software applications, headphones, Bluetooth technology, and other parasitic technologies, cf. Coccia 2018a). In general, many technologies do not function as independent systems, but de facto they depend, as parasites, on other technologies (hosts or masters) to form a complex system of parts that interact in a nonsimple way. This behavior of technologies can be generalized with the theorem of not independence of any technology (Coccia 2018b): the long-run behavior and evolution of any technological innovation Ti is not independent from the behavior and 5 evolution of the other technological innovations Tj (8i = 1, . . ., n and j = 1, . . ., m). In particular, parasitic technologies can be considered specifically as virus technologies because they have the characteristics of obliged parasites, as they depend on a host or master for most of their technological functions and developmental processes. Some virus technologies are able to function only to a specific host (e.g., diesel fuel as virus technology can be used only in compression-ignition engines as host technologies), while others are able to function on many host technologies (e.g., electrical energy as virus technology can be used for many appliances of different scale). Moreover, parasitic-virus technologies can be defined and classified on the basis of the technological host in which they adapt, and their evolution in the form of different generations is due to interaction with hosts. Moreover, a technology can be seen as a parasite or host, depending on the scale of analysis. Smartphone is host of many parasitic technologies, e.g. Bluetooth technology, but it can be also seen as a parasite of satellite technology for some functions, communication and transmission of information. This theory of technological parasitism proposes a model to analyze the interaction between a host or master technology (H system) and a parasitic-virus technology (P sub-system). The logarithmic form of the model (Coccia 2019a) is a simple linear relationship: log P ¼ log a þ B log H þ ut – P = evolutionary advances of parasitic-virus technology, e.g., fuel consumption efficiency in horsepower hours indicates the technological advances of engine for farm tractor – log a = constant – H = evolutionary advances of host or master technology, e.g., total mechanical efficiency of farm tractor – ut = error term B is the evolutionary coefficient of growth that measures the evolution of technology P (parasite) in relation to H (host or master technology). 6 In particular, the value of B measures the relative growth of P in relation to the growth of H, and it suggests different patterns of technological evolution: • B<1 (underdevelopment of host-parasite technological system) • B=1 (isometric growth of host-parasite technological system) • B>1 (development of host-parasite technological system) This theory of technological parasitism and virus technologies suggests critical theoretical and empirical predictions in the evolution of technology (Coccia 2018a, 2019a): 1. The long-run behavior and evolution of any technology depend on behavior and evolution of interrelated technologies; in particular, the long-run behavior and evolution of any technology are driven by interactions with other technologies within and between complex systems of technology (Coccia 2019a, b, c). 2. The long-run evolution of an established technology is also due to interaction with new parasitic-virus technologies. 3. Technological host or master with many parasitic-virus technologies generates a rapid stepwise evolution of technological hostparasite system. Technological systems with fewer parasitic-virus technologies and a low level of interaction with other technologies improve slowly. 4. Interaction within and between technological host-parasite systems generates coevolution of interrelated systems. May (1981, p. 95) suggests the concept of “orgy of mutual benefaction” that may be also appropriate for explaining the interaction within technological domains. In fact, in this context, the property of mutual benefaction by Coccia (2018a) argues that the interaction between technologies reduces negative effects and favors positive effects directed to Comparative Theories of the Evolution of Technology an evolution of reciprocal adaptations of technologies in complex systems of technology over time and space (cf., vertically transmitted parasites by Cullen, 1998). The idea of a technological parasitism associated with technological host-parasites coevolution is adequate in some cases but less in others because of the diversity of technologies in different complex systems and socioeconomic environments (cf. Coccia 2018a; Pistorius and Utterback 1997; Sandén and Hillman 2011). Nevertheless, the analogy here keeps its validity in explaining several phenomena of the coevolution of technology in markets and society. Overall, then, the theory of technological parasitism and virus technologies contributes to our understanding of how a technology works, how it is organized, and how it develops. This new theory suggests some general properties and predictions that are a reasonable starting point for understanding the universal features of the coevolution of technologies that leads to technological and economic change in society. However, this theoretical framework, of course, cannot predict any given paths and characteristics of the evolution of technologies with precision. We know, de facto, that other things are often not equal in the domain of technology over time and space. Conclusion The evolution of technology is associated with the idea of human progress. The prime factor of the evolution of technology is a progressive satisfaction of human wants, such as the improvement of health, the growth of wealth, the creation of new knowledge, the solution of complex problems, etc. In general, determinants of technological evolution seem to be human wants and human control of nature through science advances and newtechnology (cf. Coccia 2010, 2018a). Moreover, the evolution of technologies is faster in appropriate social structures with strong democracy, good economic governance, widespread Comparative Theories of the Evolution of Technology higher education system, skilled human capital, moderate growth rates of population, purposeful socioeconomic systems with high economic potential (e.g., superpower), etc. (Coccia 2010, 2014a, 2015a, 2018a, 2019b). These elements support the evolution of technology and advancement of science for the acquisition of better and more complex forms of life in society. To conclude, evolution of technology is a result of human activity and of human nature in order to take advantage of important opportunities, to cope with and/or adapt to environmental threats and/or changing contexts. Overall, then, evolution of technology is mainly linked to the question of what human beings truly need and how they seek to satisfy needs, to solve socioeconomic issues, and to adapt to new social, political, and economic conditions. However, a comprehensive explanation of the evolution of technology is a difficult topic for manifold complex and interrelated factors, such that Wright (1997, p. 1562) properly claims that “In the world of technological change, bounded rationality is the rule.” Cross-References ▶ Comparative World Systems Theory ▶ Revolutions and Evolutions ▶ Role Superpowers in Conflict Development and Resolutions ▶ Theories of Development References Arthur BW (2009) The nature of technology. What it is and how it evolves. 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