Evolutionary Phases in Emerging Quantum Technologies: General Theoretical and Managerial Implications for Driving Technological Evolution

Abstract

The goal of this study is to analyze evolutionary phases of emerging technologies to improve technological forecasting and management of promising innovations. Methodology applies S-shaped models with patent data to analyze the evolutionary phases in quantum technologies. Findings reveal that the evolutionary cycle of recent quantum technologies, based on patent data, is reducing compared to older technologies originated before 1980: from about 66 to 45 years. In addition, recent quantum technologies have a growth phase of about 22 years and maturity phase of 11 years, a shorter period than technologies originated before the 1980s (having a growth phase of 40 years and a maturity phase of about 13 years). The measure of entropy in the growth phase is lower (0.64) than maturity phase (0.74): a lower diversification of technological topics and technological trajectories. Results here suggest that the evolution of emerging technologies, such as quantum technology, has a high complexity and uncertainty for rapid changes in scientific and innovation ecosystem. Results support a technological management based on an ambidexterity strategy: a) Exploitation strategy in early phase of a technology's life cycle, which is characterized by concentrated topics (lower entropy index), directed to targeted investments in specific technologies; b) structure and dynamics in the maturity phase of technology's life cycle, having diversified themes (higher entropy index), suggests a strategy of exploration for detecting the most promising technological directions for future quantum innovations among new and expanding domains for achieving and sustaining competitive advantage of firms in a world of innovation-based competition.

The General Theory of Scientific Variability for Technological Evolution

“…The specificity and nature of the research fields and technologies affect the variability and related evolutionary pathways. High variability within the complex system of research fields that are more oriented to support general purpose technologies (diving different technologies), such as Quantum Sensing, seems to induce a high rate of growth in scientific and technological evolution [29,30,83].…”

“…Variability in a research field having scientific and technological information may not be independent of the variation in other scientific and technological systems [114]. This mutual influence is a challenge to the study of scientific variability because the determinants of variability in a single research field can have the main consequences for variation and evolution in other scientific disciplines and related technologies [29,30]. Some scholars suggest the concept of "nested ecosystems" [115] that can be also applied per analogy in our context: the changes in a research field and related technology has interdependencies with other research fields and technologies in a larger science and technology ecosystem [116,117].…”

“…In order to position our theory in a manner that displays similarities and differences with existing approaches, a critical review of accepted frameworks in the evolution of science and technology is presented here. Quantitative works on emergence and evolution of disciplines are scarce, and this aspect is in part due to the difficulty in detecting and measuring basic sources of scientific change [7,[29][30][31][32]. Many theories of scientific development have been inspired by the notion of paradigm shifts associated with anomalies and contradictory results in science [33].…”

“…The predictions of the proposed theory of scientific variability for technological evolution will be verified empirically in some main quantum technologies by measuring the variation in scientific and technological information with the entropy index, a measure of changes in a group of individual data points [14]. Quantum science and technology are path-breaking systems having a high potential growth with manifold applications, such as in quantum machine learning [77][78][79], drug discovery processes [80], cryptographic tasks [81], information processing of big data [29,30,82], etc. [83][84][85][86].…”

Converging Artificial Intelligence and Quantum Technologies: Accelerated Growth Effects in Technological Evolution

“…One of the fundamental problems in science is how a scientific field and related technology evolve and sustain radical scientific and technological change [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19]. The evolution of new research fields and path-breaking technologies, such as ICTs, nanotechnology, quantum computing, etc., can generate a convergence of fields and technologies that supports disruptive innovations with unparalleled effects in science and society [20][21][22][23][24][25][26][27][28][29].…”