Forecasting emerging technologies with the aid of science and technology databases

Short term forecasting was applied to 20 emerging technologies under the “Machine and Materials” category based on the Vision 2023 foresight study previously conducted for Turkey. This scientometric approach uses the most suitable keywords linked to the technology in question and determines the number of publications and patents in those fields for a given year. Database analysis of publications and patents in the previous 11 years indicates that while the majority of the top 20 technologies identified by the experts are indeed emerging (i.e. the number of research and/or patenting in these technologies is increasing), some of them have not actually attracted too much interest in the science and technology (S&T) community. Forecasts based on S-curves indicate steady growth in some of the selected technologies. There is a high correlation between the number of scientific publications and patents in most of the technologies investigated. The method is proposed as a simple and efficient tool to link national foresight efforts to international S&T activities and to obtain quantitative information for prioritized technologies that could be used for technology management and decision making for research funding and technology investment.     

Forecasting emerging technologies: Use of bibliometrics and patent analysis

It is rather difficult to forecast emerging technologies as there is no historical data available. In such cases, the use of bibliometrics and patent analysis have provided useful data. This paper presents the forecasts for three emerging technology areas by integrating the use of bibliometrics and patent analysis into well-known technology forecasting tools such as scenario planning, growth curves and analogies. System dynamics is also used to be able to model the dynamic ecosystem of the technologies and their diffusion. Technologies being forecasted are fuel cell, food safety and optical storage technologies. Results from these three applications help us to validate the proposed methods as appropriate tools to forecast emerging technologies.     

The dynamic effects of general purpose technologies on Schumpeterian growth

General purpose technologies (GPTs) are drastic innovations characterized by pervasiveness in use and innovational complementarities. The dynamic effects of a GPT are analyzed within a quality-ladders model of scale-invariant Schumpeterian growth. The diffusion path of a GPT across a continuum of industries is governed by S-curve dynamics. The model generates a unique, saddle-path long-run equilibrium. Along the transition path, the measure of industries that adopt the new GPT increases, consumption per capita falls, and the interest rate rises. The growth rate of the stock market depends negatively on the rate of GPT diffusion and the magnitude of the GPT-ridden R&D productivity gains; and positively on the rate of population growth. It also follows a U-shaped path during the diffusion process of the new GPT. Finally, the model generates transitional growth cycles of per capita GNP.JEL Classification: E3, O3, O4I would like to thank Elias Dinopoulos for encouragement, and for constructive comments and suggestions. I would also like to thank David Figlio, Douglas Waldo, Steven Slutsky and participants in the 9th Biennial Congress of the International Schumpeter Society for useful discussions and suggestions. Any remaining errors are my own responsibility.     

Tailoring CTA for emerging technologies

Technology assessment (TA) has developed into a method that puts a strong emphasis on facilitating interfaces between supply of science and technology and the demand for useful applications. Recently, we also see that TA becomes an integral part of science and technology programs, for instance in nanotechnology. The basic aim of the latter is to articulate the needs, wishes, and constraints, for example from professional users, already in the emerging stage of technological development. TA methods come in many different forms, although they are often different versions of a limited set of ‘basic approaches’ adapted to specific conditions with the overall aim to improve societal embedding. The thrust of this paper lies in the development and results of a variant of constructive TA (CTA), addressing technological development in an early phase in order to bypass the Collingridge dilemma by developing and testing scenarios including options for the further development of emerging technologies.How to support a broad selection of relevant actors effectively with CTA in such a way that they are enabled to play their role in innovation processes of emerging technologies? This is the main research question taken up in this paper. To take on this challenge we develop, apply, and evaluate an intervention we named the 3-step constructive technology assessment (CTA) approach. We will apply the approach to a nanotechnology related topic, Lab-on-a-chip technology. By assessing the effects and evaluating the proposed approach, we also want to contribute to the development of new methodological insights relevant for the TA community.     

The hunt for S-shaped growth paths in technological innovation: a patent study*

Since the works by the business cycle theorists in the 1930s, no attempts have been made to study empirically the long term evolution paths of individual technologies starting with long time series. This is an empirical exploration and confirmation of the now almost assumed image or metaphor of the way technology develops; that it follows an S-shaped growth path which is commonly associated with a similar shaped diffusion function of entrepreneurial activity. The paper also confirms the diversity of technology dynamics and explores how technological cycle takeoffs appear to be clustered within certain historical epochs. The results have implications for our understanding of the evolution paths of individual technologies, and of the evolution of technological systems and waves of innovation. By use of computational statistics, logistic growth functions are fitted to US patent stocks, 1920–1990, at a detailed level of aggregation, including chemical, electrical/electronic, mechanical, transport and non-industrial technologies. Some practical considerations when developing an empirically testable model of innovation cycles are addressed in the paper as well.     

A theory of classification and evolution of technologies within a Generalised Darwinism

This paper here proposes a theory of classification and evolution of technology based on taxonomic characteristic of interaction between technologies that is an under-studied field of research in economics of technical change and management of technology. The proposed classification of technologies, in a broad analogy with evolutionary ecology of parasites, within a theoretical framework of Generalised Darwinism, is: (1) parasitic technologies, (2) commensal technologies, (3) mutualistic technologies, (4) symbiotic technologies. This theory here suggests the property of mutual benefaction from interaction between different technologies and the theorem of not independence of any technology to explain and predict characteristics and evolutionary pathways of technologies over time. Overall, then, this study may be useful for bringing a new perspective in economics of innovation to categorise and analyse the interaction between technologies that can be a ground work for development of more sophisticated concepts to explain and predict the evolution of technology and generalise aspects of technological change in human society.     

Knowledge spillovers and R&D subsidies to new,emerging technologies

Is knowledge spillover a rationale for supporting R&D on new, emerging technologies more than R&D on other technologies? In this paper, I analyze whether innovation externalities caused only by knowledge spillovers differ between technologies of different maturity. I show that R&D should not be subsidized equally across industries when the knowledge stocks differ. This is because knowledge spillovers depend on the size of the knowledge stock and the elasticity of scale in R&D production. R&D in the emerging technology should be subsidized more when the elasticity is smaller than one. However, R&D in the mature technology should be subsidized more when the elasticity is larger than one.     

Uncovered Interest Parity at Long Horizons: Evidence on Emerging Economies*

This paper estimates uncovered interest parity (UIP) at long horizons using bilateral US dollar rates vis‐à‐vis mature economy and emerging market currencies. The paper finds support in favor of UIP for dollar rates vis‐à‐vis major mature economy currencies, but far less against emerging market currencies. There are also signs that political risk and the exchange risk premium help explain the empirical failure of UIP for these latter currencies. This suggests that whether UIP holds depends more on the currency than on the horizon.     

The Galor–Weil model revisited: A quantitative exercise

The long-run growth model of Galor and Weil [Galor, O., Weil, D., 2000. Population, technology, and growth: From Malthusian stagnation to the demographic transition and beyond. American Economic Review 90, 806–829] is examined quantitatively. We first give parametric forms to some functions which were only given on general form in the original article. We then choose numerical parameter values in line with calibrations of related long-run growth models, and with data. Finally, we simulate the model. We find, inter alia, that the time paths for population, and other variables, display oscillatory behavior: they move in endogenous cycles. As the economy transits from Malthusian stagnation to modern growth these oscillations die out. This is consistent with population growth rates fluctuating considerably in historical data, but having stabilized in modern economies. We also show that these cycles are not an artifact of the two-period life setting: allowing adults to live on after the second period of life with some probability does not make the oscillations go away. Rather, the cycles are driven by fertility being proportional to per capita income minus the parental subsistence requirement. When population is large, and per capita incomes close to subsistence, fertility is therefore sensitive to changes in population levels.     

Bridging the gap between foresight and market research: Integrating methods to assess the economic potential of nanotechnology

This paper discusses how to bridge the gap between foresight research oriented to the long-term, and traditional market research oriented to the medium to short term, when applied to an early stage of a technology's life cycle. It proposes using an integrating approach, i.e. a combination of methods and both foresight and traditional market research. A mix of complementary methods for the acquisition and analysis of data is presented in a case study. This helps to overcome the deficits of some qualitative foresight methods and quantitative methods often used in traditional market research and allows us to examine research results from the different methods applied both on their own and as a group. In the absence of a single fully-fledged and accepted economic approach, this paper argues that combined market research and foresight modules are the best possible approach for analyzing the economic potential of emerging technologies like nanotechnology. In the future, similar applications of such market foresight modules may be useful, for example, as elements of foresight. They will also be useful in studies of emerging technologies (e.g. converging technologies, cognitive science and Web 2.0) where traditional market research does not produce a realistic market assessment.     

Integral stabilization policy and flexible exchange rates

Summary Under a floating exchange rate system, exchange rates influence economic activity through their effect on the trade balance. Nevertheless, exchange rate movementsper se do not prevent integral fiscal and monetary policies from achieving a target for domestic economic activity²⁴. At the same time, since the exchange rate continuously moves to preserve asset market equilibrium, the (potential) balance of payments may not be equilibrated when the authorities have attained their internal target. In that event, the continued movement in exchange rates may produce cycles in economic activity which in turn lead to exchange rate oscillations. Finally, the reader is warned that the introduction of inside and outside lags into the system may produce additional oscillatory behavior or even explosiveness, as Phillips demonstrated for the closed economy. However, these new possibilities would arise independently of the floating exchange rate system and could not be attributed to it.     

Cooperation,stability and social welfare under majority rule

We resolve collective irrationality in the stability set, a solution concept for voting games proposed by Rubinstein (J Econ Theory 23:150–159, 1980) to resolve the well-known paradox of voting in the core. A lack of cooperation within winning coalitions prevents their members from eliminating an alternative globally less preferred to another one when they observe the rational behavior defining the stability set. Allowing for the possibility of accompanying a coalitional vote with a binding solidarity agreement is a natural response to this cooperation failure. This leads to a new standard of behavior and a new solution concept called stability set with binding solidarity agreement or S _c -stability set. It is shown that the S _c -stability set and a newly defined version of the Mas-Colell bargaining set for simple games are not comparable with respect to set inclusion. The S _c -stability set includes the core, is included in the stability set and contains only Pareto-optimal alternatives. When individual preferences are complete linear orders, the S _c -stability set is always non-empty.      

Context matters: How existing sectors and competing technologies affect the prospects of the Swiss Bio-SNG innovation system

Emerging technological fields are affected by developments in their broader context. This article proposes a differentiation of context structures as a crucial step in the analysis of technological innovation systems. A thorough context analysis, so the argument, is essential for understanding the pace and direction of technology development and the prospects of an emerging technological innovation system. Empirical insights are provided for Bio-SNG, a technology in an early stage of development. The article discusses the conditions under which actors from different sectors (forestry, wood industry, and energy supply) may play a role in the emerging field. It is shown that Bio-SNG is likely to become a victim of the recent boom in wood-to-energy technologies that has favored investments in more mature but technologically inferior alternatives. The case provides lessons for policy making as it highlights how effective support schemes might foster a lock-in into technologies that are readily available.     

Hypercongestion in production correspondences: an empirical exploration

This empirical contribution reviews the rather limited existing literature measuring congestion in production. It first compares current ways to measure congestion using nonparametric specifications of technologies. In particular, it focuses on the magnitude and incidence of the congestion detected in empirical studies using traditional radial efficiency measures. Thereafter, it shows the limitations of this radial measurement and how alternative measurement schemes may reveal higher amounts of congestion. Then, the new, more general methodology of measuring S-congestion is presented. In particular, we first present a numerical example to illustrate the way the S-disposable technologies allow to capture more extreme forms of congestion by setting empirically determined upper bounds to the wasting of inputs. Then, an empirical illustration is presented based on an existing sample of data. A final section concludes.     

Estimating endogenous switching regression model with a flexible parametric distribution function: application to Korean housing demand

This study introduces Johnson's S_U -normal distribution which can accommodate the flexibility of true error distribution to obtain consistent estimates in an endogenous switching regression model. Simulation results indicate that the S_U -normal model outperforms the normal model for the consistency of estimators when the error distribution is nonnormal. Korean housing demand model estimated by the S_U -normal model also outperforms the normal model in terms of parameter estimates and graphical predictions.     

Discovering quiescent meanings in technologies: exploring the design management practices that support the development of Technology Epiphanies

In contemporary business and academia, design has been increasingly viewed as an important strategic asset such that several scholars and executives have recently investigated the links among design, innovation and competitive advantage. Indeed, recent and emerging literature streams are exploring the potential contribution design can provide in valorising and differently adopting new or existing technologies [Dell’Era, Marchesi, and Verganti 2010. “Mastering Technologies in Design-Driven Innovation – How Two Italian Companies Made Design a Central Part of their Innovation Process.” Research Technology Management 53 (2): 12–23 Buganza et al. 2015. “Unveiling the Potentialities Provided by New Technologies: A Process to Pursue Technology Epiphanies in the Smartphone App Industry.” Creativity and Innovation Management 24 (3): 391–414]. This paper aims to investigate the design managerial practices able to support Technology Epiphanies, which are defined as the discovery of quiescent meanings in new or existing technologies [Verganti 2009. Design-Driven Innovation. Changing the Rules of Competition by Radically Innovating What Things Mean. Boston: Harvard Business Press]. The paper relies on four in-depth case studies developed by both primary and secondary sources: Nintendo, Kartell, Technogym and KUKA Robotics. The paper identifies three design management practices that can guide managers in the development of Technology Epiphanies: interpreting technology as an enabling platform, building double-sided network and accessing new knowledge domains.     

Strategic experimentation and disruptive technological change

This paper studies the diffusion of a new technology that is brought to market while its potential is still uncertain. We consider a dynamic game in which an incumbent and a startup firm improve both a new and a rival old technology while learning about the relative potential of both technologies. The main findings are that (i) risk considerations make incumbents with higher market shares more likely to adopt the new technology and (ii) changes in market power are often preceded by a subpar performance of the new technology. We also show that introducing a better new technology or confronting a worse old technology may hurt the startup firm as its new technology is then adopted earlier by incumbents.     

PREDICTING STOCK RETURNS AND VOLATILITY WITH INVESTOR SENTIMENT INDICES: A RECONSIDERATION USING A NONPARAMETRIC CAUSALITY‐IN‐QUANTILES TEST

Evidence of monthly stock returns predictability based on popular investor sentiment indices, namely S^BW and S^PLS as introduced by Baker and Wurgler (2006, 2007) and Huang et al. (2015) respectively are mixed. While, linear predictive models show that only S^PLS can predict excess stock returns, nonparametric models (which accounts for misspecification of the linear frameworks due to nonlinearity and regime changes) finds no evidence of predictability based on either of these two indices for not only stock returns, but also its volatility. However, in this paper, we show that when we use a more general nonparametric causality‐in‐quantiles model of Balcilar et al., (forthcoming), in fact, both S^BW and S^PLS can predict stock returns and its volatility, with S^PLS being a relatively stronger predictor of excess returns during bear and bull regimes, and S^BW being a relatively powerful predictor of volatility of excess stock returns, barring the median of the conditional distribution.     

Science studies: a guide for strategic management

The paper describes and discusses the current state of science studies research and its linkages to other fields, such as applied policy and management. It is argued that science studies is differentiated into science and technology studies, and science and technology policy research; and that these are twin interdisciplinary area of research in which a whole range of social scientists, as well as historians and philosophers are involved. The high degree of interdisciplinarity makes the field peculiarly difficult to categorize simply. Nevertheless, it is suufficiently mature and focused to be an established academic field in its own right; it possesses its own journal structure, specialized institutions, national and international professional associations, and teaching programmes. Research in science studies is potentially applicable-especially in the longer term-for policy-makers in the public and private sectors, as well as for public interest groups. However, the need to bridge a perched gap between acadmic studies and the needs of policy-makers is highlighted. Finally, a listing of emerging issues in the field is provided.     

Emerging patterns of complex technological innovation

Technological innovation is increasingly concerned with complex products and processes. The trend toward greater complexity is suggested by the fact that in 1970 complex technologies comprised 43% of the 30 most valuable world goods exports, but by 1996 complex technologies represented 84% of those goods. These technologies are innovated by self-organizing networks. Networks are those linked organizations that create, acquire, and integrate the diverse knowledge and skills required to innovate complex technologies. Accessing tacit knowledge (i.e., experienced-based, unwritten know-how) and integrating it with codified knowledge is a particular strength of many networks. Self-organization refers to the capacity networks have for reordering themselves into more complex structures (e.g., replacing individual managers with management teams), and for using more complex processes (e.g., evolving strategies) without centralized, detailed managerial guidance. Case studies of the innovation pathways traced by six complex technologies indicate that innovations can be grouped into three quite distinct patterns. Transformation: the launching of a new trajectory by a new coevolving network and technology. Normal: the coevolution of an established network and technology along an established trajectory. Transition: the coevolutionary movement to a new trajectory by an established network and technology. Policy makers and managers face the greatest challenge during those periods of movement from one innovation trajectory to another. These are periods of turbulence; they are the embodiment of Schumpeter's “gales of creative destruction.” This paper investigates how, in six case studies, core capabilities, complementary assets, organizational learning, path dependencies, and the selection environment varied among the innovation patterns. The paper builds on work reported in a recent book by the authors entitled: The Complexity Challenge: Technological Innovation for the 21st Century, Pinter, London, 1999.