1. Introduction
Marcos Antonio de Lima Filho, PhD.
1.1 Are Designs Evolving?
The concept of design evolution stands in contrast with the notion of design stasis. Design stasis implies a hypothetical state of absolute perfection and complete knowledge, where no further advancements or improvements are possible. It posits an end to the creative process, suggesting that there would be no more room for innovation since everything is already in its perfect state. Any new information or insights would suggest that the existing knowledge is imperfect or incomplete, which contradicts design stasis.
Clearly, the reality of our human experience directly contradicts the notion of design stasis. There may be some areas in which design seems to be advancing at a very slow pace, which does resemble a state of technological stasis, but this is only a circumstantial approximation. No domain, whether it be a product, service, market, or industry, has ever reached a point of absolute perfection or total knowledge. Imperfection and the unknown are inherent to our existence. Each discovery opens new horizons and presents new challenges, propelling an endless cycle of technological evolution.
Moreover, the changing nature of human preferences lends further weight against the possibility of design stasis. As our needs and preferences evolve, so must the designs that cater to them. Therefore, design can never truly reach a state of absolute perfection, as what is deemed “perfect” is transient, continuously changing as we evolve.
As such, the state of design is one of continual evolution, spurred by our ever-changing needs and the ceaseless pursuit of knowledge. The notion of design stasis exists only in a theoretical vacuum, given the imperfections and uncertainties inherent to our existence. Nevertheless, despite the self-evident truth that designs do evolve, “we don’t know much about the processes by which this evolution takes place” (Carlson, 2000, p. 137).
To advance our knowledge of design evolution, we must appreciate the depth and complexity of evolutionary theory, looking beyond the superficiality of marketing language. This is what happens when marketing departments tout their products as “revolutionary”, suggesting a complete break from what has come before. However, in reality, no product emerges in isolation from its past. New designs are not products of generatio spontanea. They are instead the culmination of previously developed versions and the accumulation of learning over time (Eger & Ehlhardt, 2018). Designs evolve, much like biological species, with each generation building upon and modifying the work of its predecessors. This cumulative and iterative process underlies even the most “revolutionary” designs.
For almost two centuries, the view that technological evolution follows similar rules to biological evolution has captured the interest of scientists, historians, and engineers alike (Solée et al., 2013). The organic analogy has been a constant and recurring theme for architects and designers, who have sought inspiration from biology since the inception of the field in the early nineteenth century:
They have sought not just to imitate the forms of plants and animals, but to find methods in design analogous to the processes of growth and evolution in nature. Biological ideas are prominent in the writings of many modern architects, of whom Le Corbusier and Frank Lloyd Wright are just the most famous. Le Corbusier declared biology to be ‘the great new word in architecture and planning’ (Steadman, 1979/2008).
However, as attractive as the concept might be, developing an evolutionary model has proven elusive. Despite extensive efforts, the biologic analogy has not been able to evolve from a creative and evocative metaphor into a well-structured model of technological evolution (Ziman, 2000). Past studies have also been criticised by their superficial application of biological analogies. In fields like design and architecture, past attempts often resorted to a simplistic “picture-book” approach, in which artistic photos of nature were juxtaposed with human-made structures or products of industrial design (Steadman, 1979/2008).
When considering an evolutionary theory of design, there are serious “disanalogies” to take into account. Unfortunately, these dissimilarities have often dissuaded scholars from fully developing such a theory. Critics have repeatedly highlighted these differences, at times failing to acknowledge the fact that previous research has already identified and discussed the ways in which technological systems diverge from biological systems. For instance, as early as the 1920s, anthropologist Alfred Kroeber discussed the differences between the “family tree” of organic species and the “family tree” of artefacts. Unlike biological descent, which follows a linear pattern of lineage, cultural evolution is characterised by lineages that divide and then reconnect, as ideas or designs for artefacts are brought together into new combinations (Steadman 1979/2008). This ability to recombine is a unique characteristic of cultural evolution, in which new technologies often recombine distant and unrelated lineages: “nuclear submarines, for instance, incorporate aspects of conventional submarines and of nuclear power plants” (Vermaas, 2002).
Another obvious difference lies in the genesis of new entities. Novel artefacts, unlike biological offspring, do not emerge randomly: they are almost always the products of conscious design (Ziman, 2000). Whereas natural things arise out of random natural processes, made things come out of purposeful human activity (Basalla, 1988). Technological evolution is a social process imbued with intent and purpose, from the early beginning (the designer) to the very end (the user). In stark contrast, the Darwinian theory of natural selection proposes a mechanistic process devoid of intentional design. Evolution is not teleological, as it operates without an intending, designing agent (Michl, 1995).
Hence, it is often argued, the analogy with organic evolution is invalid (Ziman, 2002). These differences, however, should not be seen as definitive obstacles to developing an evolutionary theory of design and technological change. Critics often fail to recognise that “not all the familiar features of bio-organic systems are absolutely essential to an evolutionary mechanism of change” (Ziman, 2002). Similarly, it is not necessary for an evolutionary mechanism to encompass a mechanism analogous to sexual recombination, or to have rules barring the recombination of traits from distant lineages and the like (Ziman, 2002). While it is true that the process of technological evolution depends upon the intentionality of a designing agent, this process is also marked by adaptation, variation, and selection — key features shared with Darwinian evolution.
Despite their differences, the evolution of artefacts seems at least partly like that of biological organisms; this partial analogy leads to the interesting idea that the change of both can be articulated in similar ways (Vermaas, 2002). Within the technological domain, there is usually enough diversity and relatively blind variation to sustain an evolutionary process (Ziman, 2000). Thus, the real challenge lies not in striving for perfect analogies between biological and technological evolution, but rather in discerning and comprehending their shared fundamental principles.
The intersections between design and evolutionary theory have already been explored by several scholars (Steadman, 1979/2008; Basalla, 1988; Hybs & Gero, 1992; Michl, 1995; Ziman, 2000; Langrish, 2004; 2014; Yagou, 2005; Whyte, 2007; Ehlhardt, 2016; Eger & Ehlhardt, 2018). But despite decades of discussion, we still know very little about how designs evolve. Though illuminating, these studies have not yet coalesced into a coherent theory on the evolution of technology and design. The field remains marked by divergent perspectives, theoretical frameworks, and interpretations, indicating an enduring lack of consensus.
Efforts have been made to bridge these knowledge gaps, and a notable example is John Ziman’s conferences on the evolution of knowledge. Ziman gathered scholars from diverse fields, such as biology, philosophy, psychology, anthropology, economics, engineering, computer science, and management studies (Steadman, 2008). This collaboration produced two influential works: Technological Innovation as an Evolutionary Process (2000) and The Evolution of Cultural Entities (2002). However, the contributors were unable to reach a consensus on whether an evolutionary perspective would serve as an analogy, a metaphor, or a model. They believed that it was too early to establish standard terminology or concepts, or to anticipate the development of a widely accepted theoretical model (Steadman, 2008). As contributing author stated, “The good news about this book is that technological artefacts do evolve. The bad news is that we don’t know much about the processes by which this evolution takes place” (Carlson, 2000, p. 137).
Instead of sparking research interest, some scholars have interpreted the divergent views presented in Technological Innovation as an Evolutionary Process as a failure. A book reviewer even claimed that “the enterprise was doomed from the start, because the analogy on which it is based is fundamentally flawed” (Cowan, 2003). This critique, like many others, overlooks the potential analogies in the selective process of technologies and instead fixates on their obvious differences. Yet, no one denies such “dissimilarities”, many of which have been explored by cultural anthropologists as early as the 1920s. Moreover, open-ended conclusions are intended to spark intellectual dialogues, not to suppress them. In this sense, these coauthors should have been praised by their intellectual honesty.
1.2 How Do Designs Evolve?
The early 2000s witnessed a burgeoning interest in the study of technological evolution. Unfortunately, since this momentum, our understanding of the mechanisms driving design evolution has seen little progression. There is still considerable debate surrounding the question of whether technological evolution is a Darwinian or Lamarckian process, with some scholars arguing that it is neither, while others arguing that technological evolution follows both principles (Steadman, 2008). Consequently, there is no consensus among scholars on a structured model to explain technological evolution, and the biological analogy is still viewed as a mere creative metaphor.
This thesis may offer some valuable contributions towards an evolutionary theory of design. Historically, the mechanism of natural selection has served as a template to propose a Darwinian theory of technological change. This process is said to be influenced by principles such as diversity, continuity, and novelty (Basalla, 1988), which correspond closely to the biological concepts of variation, inheritance, and mutation. In this respect, this thesis moves this analogy forward by suggesting that design evolution mirrors not only the overarching principles of natural selection (diversity, continuity, and novelty), but also its more specific patterns (disruptive, directional, stabilising, and purifying selection).
Building upon these analogies, I propose categorising innovation into four distinct types. Each type corresponds to a specific pattern of natural selection. These include disruptive innovation, which aligns with disruptive selection and its tendency to upset equilibrium; directional innovation, mirroring directional selection where specific traits become increasingly favoured over time; stabilising innovation, reflecting stabilising selection that maintains the status quo by favouring optimal variations; and purifying innovation, akin to purifying selection that filters out harmful or disadvantageous traits.
Together, these categories form a punctuated model of industrial evolution. The punctuated model aligns with the history of diverse and unrelated industries, in which periods of relative stability are disrupted by periods of rapid change, much like the evolution of species. This punctuated model provides a new perspective for understanding the evolution of design, with potential implications for managing innovation and developing competitive strategies. The following subsections provide a brief overview of these innovation concepts.
Disruptive Innovation
In short, I conceptualise disruptive innovation as the introduction of new qualities, features, or product categories. This new definition aligns disruptive innovation more closely with the pattern of disruptive selection seen in evolutionary theory (Figure 1.2.1). Disruptive selection often leads to an increase in species diversity, eventually creating new species. In an analogous fashion, disruptive innovation can add technological diversity to a market and give rise to novel product categories, changing the landscape of an industry.
This interpretation differs greatly from Clayton Christensen’s definition of disruption. Christensen has shifted away from an evolutionary perspective on industrial evolution and technological change since the mid-1990s (Christensen et al., 2018). This study, in contrast, aims to re-establish the evolutionary foundations within disruptive innovation research.
In natural selection, disruptions increase the genetic diversity of species, allowing new traits and adaptations to emerge. Sometimes, disruptions break the equilibrium to the point of generating new species, as seen in the speciation of Galápagos finches (Figure 1.2.1). Likewise, technological disruptions sometimes accumulate to the point of creating new product categories. For example, the first turbofan airliners (Figure 1.2.1, centre) had an average bypass ratio of 1 to 2. Later in the 1970s, the introduction of newer turbofan architectures divided the market into two categories: low-bypass and high-bypass turbofans.
In the last decades, a new round of advancements in composite materials and the addition of a gearbox have enabled even higher bypass-ratios. These recent disruptions in turbofan architecture have inaugurated a new category: the so-called ultra-high-bypass turbofans (11-13 ratios). These advancements are significant since, in a nutshell, “the higher the bypass ratio, the higher an engine’s efficiency” (ATAG, 2010). Such disruption in engine technology has powered the latest generation of narrow-body and regional airliners: 737 Max, A320neo, A220, E-Jets E2.
The smartphone industry has also experienced a similar effect. In the past, most smartphone designs relied heavily on physical keyboards, such as the famous RIM BlackBerry design. However, these keyboards took up a significant amount of front space, resulting in smaller display sizes. The introduction of the first iPhone in 2007 disrupted this design by pioneering a new form factor (the touchscreen slate), which eliminated the physical keyboard in favour of a virtual one.
Prior to the iPhone, smartphones had an average screen-to-body ratio of 33% (Figure 1.2.1, right). This ratio measures how much of the front surface is occupied by the display. In comparison, the first touchscreen slates had an average of 50% screen-to-body ratio — bezels, front buttons and speakers occupied the remaining 50% area. Since then, smartphone manufacturers have managed to reduce bezel size, eliminate front buttons, and expand the display size. As a result of these successive improvements, the screen-to-body ratio in smartphones launched in 2020 has reached an average of 85%.
Disruptions are distinguishable from incremental innovations. The slate, in particular, represents a fundamental revision of smartphone architecture. In addition to featuring a touchscreen display, this new form factor also incorporates a new set of sensors (ambient light, gyroscope, and proximity). Comparatively, in the natural world, this can be likened to the introduction of new genes or traits within a species, a phenomenon known as disruptive selection.
Directional Innovation
Directional innovation is the second pattern of innovation proposed in this thesis. It can also be understood as incremental innovation. I describe directional innovation as the augmentation of present qualities, characteristics, or product features. The evolution of the horse is a well-studied case of directional selection (Ayala, 2020). Figure 1.2.2 illustrates the gradual evolution in the body mass of horses, juxtaposed with the gradual increase in the dimensions of smartphones and aircraft turbofan engines.
Over the course of 60 million years, larger horse lineages exhibited greater fitness, enabling their survival and expansion. This transition towards larger body size is a response to environmental pressures and the advantages associated with increased size, such as enhanced speed and the ability to access higher vegetation.
Transposing this principle to the evolution of technology, we see a parallel process unfolding in the development of both smartphones and civil aircraft. Market pressures have led to a directional selection favouring incremental improvements in multiple dimensions. Turbofans have become larger, allowing for larger bypass ratios and thus higher efficiency. Smartphones have also grown in size (diagonal), display resolution, computational and graphic power, energy efficiency, to name a few.
Stabilising Innovation
Stabilising innovation is analogous to a type of natural selection in which a species stabilises a given trait around an optimal value. Given that we do not see most species changing drastically over generations, stabilising selection is considered one of the most common mechanisms of natural selection. However, it is surprising that despite being a widespread phenomenon, the concept of stasis has been largely disregarded in both evolutionary theory and innovation studies for several decades.
Over the century that followed the publication of Darwin’s Origin of Species, biologists assumed that evolution proceeded in a stately and relatively linear fashion, leading to a smooth pattern of speciation and extinction (Beinhocker, 2006, p. 173). This changed in 1972, when the palaeontologists Niles Eldredge and Stephen Jay Gould proposed the theory of punctuated equilibrium. Eldredge and Gould argued that species tend to remain unchanged for long periods of time, with little or no discernible evolution occurring.
Evolutionary stasis is widely observed in the fossil record of several species (Mayr, 2001). Stasis is “the most common of all paleontological phenomena” (Gould & Eldredge, 1993). Thus, instead of gradual evolution, the theory of punctuated equilibrium proposes that biological evolution has gone through long periods of relative stasis interspersed with periods of explosive innovation and periods of massive extinction (Beinhocker, 2006).
Despite the fossil evidence, academics used to treat stasis as a non-subject: “As palaeontologists did not discuss stasis, most evolutionary biologists assumed continual change as a norm, and did not even know that stability dominates the fossil record” (Gould & Eldredge, 1993). However, after the groundbreaking work of Gould and Eldredge, researchers in different fields outside of biology started to recognise the patterns of stasis and its significance, adhering to their original dictum that “stasis is data”. Likewise, stasis should also be seen as data in the study of design and innovation.
Indeed, stability is an observable pattern in the evolution of several artefacts. A historical case of technological stabilisation is the traditional craft production of Japanese samurai swords. The functionality and process of manufacture remained virtually unchanged for 700 years (Martin, 2000). Such stasis is an example of evolutionary “lock-in”, where a delicate process becomes resistant to alteration because even small changes in manufacturing can make the finished artefact useless (Lewens, 2002).
Yet, this stabilisation is not confined to traditional arts or craftsmanship, but extends into the domain of modern technology as well. Figure 1.2.3 reveals that the top speed of commercial passenger aircraft has remained constant since the 1950s, with an average speed of 900 km/h. This speed represents an optimal value: while flying faster is feasible, it results in diminishing returns due to increased fuel consumption and other operational costs (ATAG, 2010). Furthermore, the overall architecture of most commercial airliners has experienced minimal changes, as evident in Figure 1.2.4.
These instances of stabilisation highlight the systemic interactions between different innovation patterns. While certain dimensions of aircraft and smartphones have stabilised, they have also been subjected to rounds of disruptive, incremental, and purifying innovations in other aspects.
Purifying Innovation
In nature, adaptation is often accomplished through the loss of formerly useful traits and features (Zeigler, 2014). There are several examples of lost traits and vestigial organs: apes have lost their tails, humans have reduced most of their body hair, cave animals have become blinded, and whales have become legless, among others. The loss of these traits has only increased their adaptation. In essence, evolution is not always about gaining new traits or features, but can also involve the loss or reduction of existing ones.
This evolutionary strategy can enhance our understanding of how designs evolve. In this thesis, I conceptualise Purifying Innovation as a process by which a designed artefact evolves by discontinuing, rejecting, or replacing some of its parts. While disruption often generates greater diversity and complexity, purifying innovation is marked by simplification and optimisation. This approach can enhance user satisfaction by avoiding the addition of excessive features that can make a product overly complex and difficult to use.
The evolution of smartphones and commercial aircraft brings several examples of such purification. Since 2007, smartphones have adopted a number of new sensors and features (the disruption), while losing others (the purification). Figure 1.2.5 shows that smartphones have discontinued capacitive buttons, once commonly featured in the navigation bar of most Android devices. Placed at the bottom of the smartphone, this set of capacitive sensors allowed users to “go back”, go to the home screen, and to visualise recently opened apps. Its adoption rate reached up to 80% in 2011. Then, Google changed Android’s design guidelines in favour of virtualised on-screen buttons. This change has led capacitive buttons to practically disappear from modern smartphones.
This research has also identified several technologies being replaced, discontinued, or rejected in commercial airliners. Section 4.4 reports 14 cases of purifying innovation in this sector -4.4 Purifying Innovation in Aircraft. The emergence of jet propulsion technology inaugurated a new era in aviation (Figure 1.2.6). Within a single decade, jet propulsion (turbojets, turboprops, and turbofans) replaced the previous dominant technology of piston engines in commercial airliners.
This transition represented a significant disruption in engine technology, underscored by the foundational differences between these two systems. Piston engines operate on the principles of intermittent internal combustion, where controlled explosions take place within the engine cylinders. In contrast, jet engines maintain a continuous flow of air and fuel mixture, resulting in a constant combustion reaction. Therefore, the onset of the Jet Age was not the result of gradual enhancements to an existing technology. Instead, it was built over an entirely new platform, disrupting a centuries-old technology in this process.
Purifying innovation and disruptive innovation bear an interesting relationship. In the 1950s, piston engines were reaching their physical limits (Crouch et al., 2020). With many moving parts, these engines were prone to issues such as overheating and frequent failure (Pandley, 2010). These limitations stimulated a quest for improvement, but incremental enhancements proved insufficient to overcome the inherent constraints of this old platform. Such an impasse provides an opportune stage for disruptive innovation. In this case, the limitations of the piston technology catalysed the fast adoption of a fundamentally different solution — jet propulsion.
The Punctuated Evolution of Designs
In conclusion, this dissertation proposes that industrial evolution adheres to a punctuated equilibrium model, where periods of stability and incremental change are punctuated by disruptive innovations and eventual decline. The model also highlights that the early stages of an industry’s evolution are typically marked by uncertainty and extensive experimentation. This can be compared to the emergence of new species, a process heavily dependent on disruptive selection. Like the model put forth by Abernathy and Utterback (1978), this model associates the dynamic nature of nascent industries with disruptive innovation:
Disruptive innovation introduces new qualities, technologies, materials, or features, thus fostering greater technological diversity. It is associated with the entry of new market players and the creation of new market spaces. However, a disruptive technology might fail to gain market acceptance, leading to its extinction (purifying selection).
On the other hand, if consumers respond positively to the disruption, it indicates that other manufacturers should also adopt it. The disruption sets a new direction for the industry, and some competitors are better able to perceive it and modify their designs accordingly.
The directional phase is characterised by growing diffusion and incremental improvements until it reaches a point of stability. In this new stage, design evolution is marked by growing technological stasis and market consolidation. Stabilising innovation hinders significant design changes, thereby strengthening the dominance of established technologies.
Yet, as market preferences shift, an innovation that was once stable may go through a cycle of declining adoption, and may eventually become extinct. The emergence of a new disruptive technology frequently triggers this purification process.
In evolutionary theory, these four patterns of natural selection have been sufficient to explain how species evolve. When it comes to the evolution of technologies, an explanation of how designs evolve would be incomplete without considering one or two of these patterns. This categorisation highlights that the evolution of industries does not fit into a binary dichotomy between disruptive and non-disruptive innovations. Instead, it involves a more complex interplay of different patterns of design evolution.
In summary, I propose that the evolution of industries is characterised by four distinct cycles, each associated with a different pattern of innovation selection (Figure 1.2.7). The theory of punctuated evolution challenged the notion that species evolved through a continuous and linear “progress”. Likewise, the model proposed here comprehends that industrial and technological evolution is a dynamic and iterative process that does not necessarily culminate in decline. Instead, industries can reinvent themselves through cycles of disruption and stabilisation.
The punctuated model and the innovation concepts outlined here hold potential contributions for both theory and practice. The assumption is that each stage of evolution — be it disruptive, directional, stabilising, or purifying — presents unique challenges and opportunities, thus necessitating the right set of innovation strategies from designers and managers. As such, the model incorporates the insights of Abernathy and Utterback (1978), who underscored the importance of aligning product and process development with the industry’s evolution stage.
This study shows how these selection patterns have shaped the evolution of two distinct, vastly different industries, such as consumer electronics and commercial aircraft. However, I am convinced that these patterns represent general processes that are not restricted to the technologies or industries under study.
1.3 Research Purpose
This study adhered to the Classic Grounded Theory methodology, a research strategy that seeks to uncover latent patterns that are abstract of time, place, and people (Glaser, 2016). Hence, this study was not meant to describe the observed shifts in the history of two specific markets, such as smartphones and commercial aviation. Rather, the primary purpose of this study was to explain the processes driving design evolution, not only within the mentioned industries but also potentially across other sectors.
Descriptive studies, while offering detailed insights into specific circumstances, can become outdated and less relevant as the unit of analysis changes over time (Holton & Walsh, 2017). Concepts, on the other hand, can endure and transcend their initial original contexts. A case in point is Darwin’s theory of evolution by natural selection, built on a collection of analogies drawn from the artificial breeding of various species, such as dogs, racehorses, cattle, pigeons, sheep, chickens, and etc. Conceptual abstraction has extended evolution beyond the species Darwin initially studied. As a result, despite its origins in the mid-19th century, this theory retains its relevance even today.
Instead of description, this study aimed to discover abstract patterns of design evolution. It seeks to explain the phenomenon of design evolution, which transcends the confines of particular contexts. The description of the industries examined here has served to ground these concepts in data, thus assuring their internal validity. However, the main goal is to distil principles from specific instances that can be generalised to various markets, industries, places, and times. This thesis is intended for an audience of academics and practitioners, for those interested in theories about technological change and disruptive innovation, for everyone inspired by the intersections of design and entrepreneurship.
1.4 Research Questions
Unlike other research methods, Grounded theory research enables the researcher to delve into a subject matter without a predetermined problem or hypothesis (Glaser, 1992). Rather than preconceiving a research design, the problem and the research questions are expected to emerge naturally from the data. This section details how the research questions emerged during this inductive approach, which began with an exploratory examination of the smartphone industry. This field captivated my interest due to the wide diversity of models and the rapid pace of innovation. Manufacturers were engaged in an intense competition, where product design took on a pivotal strategic role.
This product-based competition was driven by a search for novelties, upon which manufacturers could build some temporary differentiation. In turn, this diversity empowered consumers to select the products that best suited their needs and means. The fittest products were sold, copied, diffused, and maintained in production, while the unfit ones were left on shelves and eventually phased out of production.
As Charles Darwin famously stated, the concept of evolution can be captured by the phrase “descent with modification”. Despite the absence of an inheritance mechanism like a genome, technological novelties also emerge within a context of inherited knowledge and advancements. Clearly, this mode of inheritance is a cultural phenomenon, not a biological one. Without an inheritance mechanism, the market selection process would be pointless, as newly selected variants would not be retained in future generations.
Despite the fundamental differences with biological evolution, the development of smartphones has sustained enough diversity (variation), a continuous stream of novelties (mutation), and a mechanism for accumulating knowledge (inheritance). These elements form the necessary conditions to sustain a selective process, thus implying that “evolution” was a core category for developing a grounded theory about this process.
The core category refers to the main behaviour pattern or process that is central to the field of study. This core category must meet criteria such as centrality, frequency, relevance, grab, and variability (Glaser & Holton, 2005). In the context of this study, the selection of products in the market was directly related to the principles of “natural selection” and “evolution”, highlighting the relevance of Darwinian theory in understanding these phenomena. Indeed, such parallel was not coincidental. Evolution and economics have a long history of reciprocal influence dating back to Darwin’s time (Beinhocker, 2006), which reinforces the idea that markets and biological systems share common evolutionary principles.
In grounded theory studies, the literature review should be conducted after the core category has emerged. This approach helps to avoid forcing the study’s theoretical direction and improves the potential to identify the main concern in the area of study and provide a new way to explain it through a core category (Holton & Walsh, 2017). In this research, the first round of literature review addressed the initial set of research questions:
I. What is the theory of evolution? How does this process occur in nature? What are the main patterns of natural selection?
These initial research questions served to identify, but not to make assumptions about, the phenomenon of interest (Willig, 2013). This first review was conducted to gain insights into the basic mechanisms of evolution, natural selection, and the Darwinian theory as they are understood within the domain of Biology. From this literature, four main patterns of natural selection emerged: disruptive selection (Reviewed in Section 2.4 Disruptive Selection), directional selection (Section 2.5 Directional Selection), stabilising selection (Section 2.6 Stabilising Selection), and negative selection (Section 2.7 Purifying Selection).
Following that, the process of constant comparison resumed. This initial review explained what evolution is (descent with modification), and how it occurs (natural selection). The plausible correspondence between evolutionary theory, design practice, and technology evolution prompted me to ask more specific questions:
II. Is the evolution of designs analogous to the evolution of species? And crucially, does empirical data support this analogy?
The parallels drawn between the evolution of species and the evolution of technologies seem to extend beyond a mere creative metaphor. To explore this further, a comparative analysis was conducted, examining the evolution of smartphones and passenger aircraft. This involved gathering product specifications from the past few decades and compiling them into a database. The comparison showed that these selection patterns were evident in various aspects of product design, which further supported the validity of the biological analogies proposed here. In light of these findings, the following questions emerged:
III. Which principles of evolutionary theory can be extended to the evolution of designs? How can these principles enhance our understanding of design evolution?
The collected data revealed that the evolution of technologies manifested four distinct patterns of natural selection: disruptive, directional, stabilising, and purifying selection. Each of these patterns generated its own subset of questions, such as “What is disruptive selection?”, “Is there evidence to substantiate such analogy?”, “How does this evolutionary process relate to the development of technologies?”, and so on. These findings inspired the development of unique innovation categories, each correlating to a different mechanism of evolutionary selection.
1.5 Thesis Structure
The literature review in this thesis explores the connections between Darwin’s theory of evolution by natural selection with the theories of design and disruptive innovation (2. Literature Review). This chapter consolidates how design evolution has been discussed in academic literature through a semi-systematic review. Following that, it introduces foundational principles of evolutionary thought. The chapter ends with an introduction to disruptive innovation theory, thus providing a foundation for the upcoming discussion on disruption (2.8 Disruptive Innovation).
Grounded theory is a research method that focuses on generating theory from data. Different versions of grounded theory exist, including classical, structured, and constructivist approaches. The methodology chapter explains the rationale for choosing the classical approach of grounded theory over other possible methodologies. This approach incorporates both qualitative and quantitative data, requiring iterative data collection and analysis. The research initially started with an exploratory comparison of product specifications, but it later expanded into a census of commercial aircraft and smartphone specifications. The aim was to establish a historical time series of their technological evolution.
The research findings are divided into two chapters, each presenting the observed incidents associated with their respective industries. Chapter 4 reports on the instances of disruptive, directional, stabilising, and purifying innovations that occurred during the evolution of commercial aviation (4. Results: The Evolution of Commercial Aircraft). Similarly, Chapter 5 presents the instances related to the development of smartphones (5. Results: The Evolution of Smartphones). The significance of these findings is elaborated in subsequent chapters.
Chapters 6 to 10 formalise the concepts proposed in this research and discuss their implications for existing theories of innovation management and design evolution. Notably, the comparison with evolutionary theory led to the emergence of a different notion of disruption, which challenged various assumptions about this phenomenon. Chapter 6 begins with a critique of the dominant paradigm of disruptive innovation (6.2 Issues with Disruption Theory). Unlike earlier innovation scholars who relied on a punctuated model of industrial evolution, Clayton Christensen disconnected disruptive innovation from this evolutionary framework. Unfortunately, this redefinition has resulted in a narrower understanding of the phenomenon. The current theory of disruption fails to explain major industrial shifts, such as the Jet Age, the iPhone, and the emergence of Android smartphones.
The chapter on disruptive innovation also tests the supposed predictive power of Christensen’s model by comparing his theoretical predictions against the stock performance of companies. However, significant anomalies were observed: Regional jet manufacturers did not disrupt the Boeing-Airbus duopoly (6.8 Christensen’s Prediction for Boeing and Airbus). In fact, regional jet sales dwindled right after this prediction, leading Bombardier, one of the supposed disruptors, to exit this industry. Interestingly, regional jets align well with Christensen’s model of disruption, which posits that a new entrant disrupts the market by offering a lower-cost, simpler alternative to existing products. This assumption led Christensen to predict that “the iPhone won’t succeed”, since Apple was doing the exact opposite by positioning the iPhone as a premium device with cutting-edge technology and a higher price point. Since then, Apple’s stock price has surged more than 5.500% -6.9 The Predictive Model of Disruptive Innovation.
Grounded in both data and earlier research on disruption, the chapter 6 concludes by proposing a new definition for disruptive innovations, offering a novel explanation for this phenomenon. The evolutionary analogy highlighted that disruption is just one pattern of selection. Thus, an explanation of technological evolution would be incomplete without comprehending other mechanisms of selection (6.12 How to Design Disruption).
The subsequent chapters discuss the other necessary but often overlooked patterns of innovation selection, namely directional innovation (Chapter 7 - 7. Directional Innovation), stabilising innovation (Chapter 8 - 8. Stabilising Innovation), and purifying innovation (Chapter 9 - 9. Purifying Innovation). These concepts mirror the natural selection processes observed in biology, highlighting the analogy between technological and natural evolution. This comparison is supported by examples from the observed evolution of smartphones and commercial aircraft, as well as from other industries, thereby grounding these concepts with empirical evidence.
The discussion culminates in Chapter 10, where a dynamic model of design evolution is proposed -10. The Dynamics of Design Evolution. It concludes that the evolution of designs can be best understood through a punctuated model of industrial and technological evolution. In nascent industries, new technologies and design concepts emerge, fostering a high rate of product innovation and experimentation. The shift from disruptive to directional/incremental innovation is associated with the emergence of a dominant product design (Abernathy & Clark, 1985), which leads to a more stable phase of industrial evolution. Over time, industries may reach a state of technological stasis, where there is little incentive for substantial improvements. This consolidation may persist for years or even decades, but it leaves established companies vulnerable to disruption by emerging technologies and competitors, eventually resulting in a cycle of decline or extinction. This dynamic is evident in the history of many products and industries, such as compact digital cameras, portable music players, DVD players, fax machines, typewriters, movie rental stores, etc.
The comparison between nature and technology provides valuable insights into the dynamics of design evolution. By understanding the universal principles of selection and recognising the different stages of industrial and technological evolution, companies can make informed decisions about design and innovation management. I expect that this knowledge can help innovators to navigate the cycles of disruption, diffusion, consolidation, and obsolescence, ultimately increasing their chances of success in the marketplace.
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