Bioenergy innovation and energy policy

Using panel data on 13 OECD countries between 1979 and 2008 this paper examines the affect climate and energy policies have had on the rate of biotechnology innovations. The explanatory variables include a vector of important determinants of patenting activity for biotechnologies (e.g. specific and general research and development expenditures, energy consumption, energy prices and total number of registered patents). Fixed effects are employed to capture unobservable country-specific heterogeneity using a negative binomial model. The empirical results indicate that policies are important for stimulating innovations in biotechnologies. The development of feed-in-tariffs (FITs) and the implementation of tradable green certificates have had a positive and statistically significant impact on patent activity. The economic impact of green certificates is found to be larger than that of FITs. In addition, R&D activities have also had a positive and statistically significant effect on innovation.     

Relating business model innovations and innovation cascades: the case of biotechnology

This article conceptualizes innovation as a process, where the scientific and industrial application of technological knowledge nurtures new routines and institutions, in order to relate changing business model innovations to innovation cascades. Innovation in science-based, high-tech sectors is changing its tempo, from the evolutionary pace of incremental novelties punctuated by occasional radical novelties, to innovation cascades. These cascades involve a long series of interlinked radical innovations, which can be traced through various scientific and technological indicators like patents and publications. Innovation cascades are relevant to industry, because they make the future less predictable. They are particularly interesting because these changes also enable the testing an abundance of new business models. Innovation cascades have a major impact on the number and sustainability of business models and on strategy. Business model innovations are visible not only in the existing organizations that undergo change, but also new organizational models appear. The case of biotechnology after the 1980s is used to illustrate our conceptualization.     

Pattern of patent-based environmental technology innovation in China

Technology innovation benign to environmental preservation is one of the key strategies to address sustainable development. Understanding the pattern of environmental technology innovation in a country is necessary for making policies and decisions in environment management. Temporal and spatial distribution of environmental patents was analyzed to identify innovation capability of environmental technologies in China. In terms of features the patents were classified into invention, utility model (performance improvement) and design. The patents belonged to the individuals, enterprises and research institutes in terms of ownership. Through analyzing the pattern of environmental patents by features and ownership, it was found that individual-owned patents and utility model patents accounted for the biggest percentage of all the environmental patents applied by the domestic applicants. Eastern provinces had the majority of environmental patents. The cluster analysis showed that invention patents and enterprise-owned patents were concentrated in the eastern provinces. In general, the innovation capability of environmental technologies in the east is strongest among the regions. Though it had been improved in the last two decades, the percentage of invention patents was still small and enterprises did not play the most important role in innovation. Applications of environmental patents increased gradually but had a declining share of all the patents in the last two decades. The innovation capability of environmental technologies in China is still not strong on a global perspective.     

Collective learning,innovation and growth in a boundedly rational,evolutionary world

We formulate a simple multiagent evolutionary scheme as a model of collective learning, i.e. a situation in which firms experiment, interact, and learn from each other. This scheme is then applied to a stylized endogenous growth economy in which firms have to determine how much to invest in R&D, where innovations are the stochastic product of their R&D activity, spillovers occur, but technological advantages are only relative and temporary and innovations actually diffuse, both at the intra and interfirm levels. The model demonstrates both the existence of a unique long-run growth attractor (in the linear case) and distinct growth phases on the road to that attractor. We also compare the long-run growth patterns for a linear and a logistic innovation function, and produce some evidence for a bifurcation in the latter case.     

Competing incremental and breakthrough innovation in a model of product evolution

This paper develops a growth model in which product cycles arise endogenously from investment in incremental and breakthrough innovations. Incumbent firms invest in incremental technology improvements with the aim of reducing production costs. Market entrants develop breakthrough product designs in order to capture the market from vintage product lines. The competing objectives of the two types of innovation generate product cycles within an environment of creative destruction, as new products displace old and are then manufactured using production technologies that are continuously refined. Investigating the relationship between innovation incentives and the average length of product cycles, we characterized three stable patterns of product evolution: incremental innovation alone, breakthrough innovation alone, and product cycles with both types of innovation. Numerical examples suggest that when the market exhibits stable product cycles, subsidies to either type of innovation raise the rate of economic growth and improve welfare.     

Economics of soft innovation: a review article

This article identifies and articulates the foundations of the theoretical approach of the new book ‘Soft innovation: Economics, product aesthetics and the creative industries’ by Professor Paul Stoneman. This book is likely to open a new research area within the economics of innovation. The source of economic growth and prosperity is technological change and the economics of innovation to date has mainly focused on technological approaches to innovation. However, the development of the technological base of product and process can explain only a part of economic growth as soft innovation represents a relevant additional source of economic development that has received little attention so far. The source of a unified economic approach for soft innovation relies on Lancaster's theory of consumer behaviour coupled with the variety approach, innovation in services and the economics of knowledge. It appears as though industry structures favouring the successive emergence of new variants are characterised by soft innovations.     

Direct and configurational paths of open innovation and organisational agility to business model innovation in SMEs

ABSTRACT

Discussions on opportunities and enablers have remained lacking despite the continued growth of business model innovation (BMI) research. In order to investigate the formation mechanism of BMI in small-medium enterprises (SMEs), we proposed an integrated model, which included factors derived from organisational internal resources and capabilities via the resource-based view (RBV) and dynamic capabilities view (DCV). Structural equation model (SEM) and fuzzy set qualitative comparative analysis (fsQCA) were utilised to test the survey data collected from 245 SMEs in China. SEM results support the hypotheses, except that on the impact of outbound open innovation on market capitalising agility and on BMI. The fsQCA analysis revealed that four configurations of open innovations and organisational agilities can sufficiently explain high levels of BMI, and two configurations of these factors lead to low BMI. The theoretical and practical implications of such findings were also provided.     

Technological innovation and complexity theory

Complexity theory has become influential in recent models in social science. In the context of innovations and new technologies, most applications have focused on technology adoption and technology diffusion, whereas the topic of the innovation process has received less attention. This paper discusses three families of complexity models of technological innovation: fitness landscape models, network models and percolation models. The models are capable of analysing complex interaction structures (between components of technologies, between agents engaged in collective invention) while avoiding ‘over-parameterisation’. The paper ends with discussing the methodological challenges and critiques regarding the application of complexity theory that remain.     

Discoveries, innovations, and business cycles

There is considerable evidence that the density of basic innovations is peaked at definite periods with intervals of about 40–60 years. This has been used as support for the behavior of economic cycles as postulated by Kontradieff and amplified by Schumpeter. Recently some economists have used this model to forecast economic recovery in the middle or late 1980s.This paper points out that the shape of the clusters of innovation or inventions are different and sharper than those of economic depression or economic recovery. The transfer of knowledge from basic inventions to industrial innovations shortens as one moves from the 18th to the 20th century, and some probable explanations for this are offered. The importance of discoveries and limited discoveries to the process of invention and innovation is discussed. Also shown is that discoveries reveal cluster phenomena which are functionally related to the clusters of invention and innovation.     

Promoting innovation and competition with patent policy

Recently the role of institutions on growth, and especially the influence of Intellectual Property Rights, has been integrated into the Schumpeterian Growth Framework. In this contribution, we highlight the possibility using one patent’s characteristic, the patent height, as an instrument for promoting innovation and growth. We introduce this possibility into the Segerstrom (Am Econ Rev 80:1290–1310, 1998)/Li (Am Econ Rev 93:1009–1018, 2003) quality ladders model of growth. The Li (Am Econ Rev 93: 1009–1018, 2003) generalized model overturns Segerstrom (Am Econ Rev 80:1290–1310, 1998) policy implication in terms of the size of innovations having to be taxed or subsidized by relaxing a crucial assumption on the value of the elasticity of substitution between goods. In this paper, we point out the fact that the innovation size requirement has to be considered as a policy instrument, so that it appears extremely important to consider the case when the innovation size has been made endogenous. A patent policy using the novelty requirement as an instrument for innovation policy enables implementation of the social optimum. The consequences of this policy for market structure and economic growth are then discussed. When the level of the patent novelty requirement is initially high, a patent policy that weakens the patent height can reinforce competition and promote innovation.     

Export performance of the Asian miracle economies: The role of innovation and product variety

Traditional export models fall short of explaining the marked increase in exports of the Asian miracle economies in the post‐WWII period. A model showing that exports are driven by innovations, innovative competitiveness, demand and price competitiveness is estimated for China, India, Korea, Japan, Singapore and Taiwan over the period 1953–2010. The results demonstrate that innovation stocks and competitiveness are important determinants behind their success. Furthermore, innovation stocks and innovative competitiveness are shown to be less influential for export growth in China and India and their export booms have been fuelled by process rather than product innovation.     

U. S. energy production activity and innovation

Life-cycle studies provide a comprehensive insight into comparative innovation behavior and innovation constants. In this article a comparison of the life-cycle plots for the production and patent activity is made for US energy production categories. As has been shown previously for material production [TFSC, vol.78, 2011], the two activities may be correlated to such an extent that they may be superimposed to a large degree, for all growth stage except stage IV, simply by an origin-shift. Over ten energy production methods have been studied in this manner for the first time. An origin-shift ratio, OR, (positive or negative lag) describes the amount required to shift the two activity curves in order to superimpose them. The relative drive-force ratio, DR (defined as the ratio of the production and patent growth constants) is noted to scale with the origin-shift. The value of this drive-force ratio determines the amount of production that is influenced by patents. The slope of curve of the drive-force ratio plotted against the origin-shift ratio is noted to be constant across all energy categories in the high growth Stage III. The authors find for the first time that even early stage production displays an origin-shift. Energy materials (i.e., those materials that dominate a particular type of energy production) are also studied in the material category alone, where the total usage of the material is considered. The concept of Green materials is discussed in this context. The life-cycle approach collapses the energy categories/sources and related materials into two groups. The authors discuss these groups in the Schumpeterian framework of constructive and destructive innovation. Group 1, containing coal, natural gas, wind, renewable, fossil fuel, solar and total energies, is composed of energy categories/sources whose patent activity could be inferred as driving their production. On the other hand, energy production from biomass, biofuel, geothermal and nuclear energies is identified in Group 2, in which the patent activity is driven by production (high innovation group). An (OR) of slightly less than one and a (DR) less than one, lead to a placement where with time, a constructive to destructive innovation transition is encountered A very low (OR) and a low (DR) on the other hand leads to a transition from Stage III growth to a no-growth (Stage IV) with time. Innovation enhanced resources and production are also discussed.     

The technology element model,path-dependent growth,and innovation policy

This paper uses a multi-element model of technology-based growth, including characterizations of both private and public components of such elements, to assess expansion paths for high-tech industries. Such a technology element model (TEM) maintains the traditional proprietary (excludable) technology element that directly results in innovations, while adding the ‘technology platform’ – a quasi-public (non-excludable) proof of concept that bridges the gap between an industry's science base and proprietary technology development, and a diverse technical infrastructure that has substantial impacts on industry productivity. These three elements are related to each other and to the production of technical knowledge by a homothetic technology production function. The TEM is then applied to assess the concept of constrained expansion paths. Such path dependence is shown to be a natural evolutionary process in that the evolving character of a technology over time is not necessarily the result of market failures. Finally, the TEM and the concept of path dependence are combined to assess the factors affecting both adaptive and allocative efficiency with respect to the expansion path, thereby better informing innovation policy.     

The nonlinear effects of firm size on innovation: an empirical investigation

ABSTRACT

In conventional studies, large firms tend to emphasize more on process innovation than product innovation. This paper explores factors that could indicate a distinct pattern of firms’ innovation-size relationship: threshold size that implies a positive effect of firm size on the probability of product innovation success; cannibalization effect that creates incentives for large firms to favor product innovations; and financial constraints that have differential effects given different firm sizes. A hypothesis about a non-monotonic relationship between the proportion of product innovation and firm size is tested with nonlinear and dynamic econometric models. For the large firms, empirical evidence shows product innovations result in an overall larger share of new products in total sales, relative to existing products in which process innovations are rooted.     

绿色创新与经济增长动态关系研究——基于VAR模型的实证分析

基于湖北省1993—2018年相关数据,运用VAR模型对绿色创新与经济增长的动态关系进行实证研究,同时将绿色创新分为发明专利授权和实用新型专利授权两个要素。研究发现,经济增长与发明专利授权、实用新型专利授权存在长期协整关系;发明专利授权对经济增长存在“扩散效应”,实用新型专利授权对经济增长先体现“扩散效应”,后体现“挤出效应”,而经济增长对两者均具有“扩散效应”;发明专利授权对经济增长的促进作用明显大于实用新型专利授权对经济增长的促进作用。因此,应积极构建绿色创新与经济增长的长效互动机制;加大绿色创新开发投入,完善绿色创新相关制度;提升绿色创新的投入效率,加速绿色创新成果转化率。     

Sources of technological innovation: Radical and incremental innovation problem-driven to support competitive advantage of firms

A fundamental problem in the field of management of technology is how firms develop radical and incremental innovations that sustain the competitive advantage in markets. Current frameworks provide some explanations but the general sources of major and minor technological breakthroughs are hardly known. The study here confronts this problem by developing a conceptual framework of problem-driven innovation. The inductive study of the pharmaceutical industry (focusing on ground-breaking drugs for lung cancer treatment) seems to show that the co-evolution of consequential problems and their solutions induce the emergence and development of radical innovations. In fact, firms have a strong incentive to find innovative solutions to unsolved problems in order to achieve the prospect of a (temporary) profit monopoly and competitive advantage in markets characterised by technological dynamisms. The theoretical framework of this study can be generalised to explain one of the sources of innovation that supports technological and industrial change in a Schumpeterian world of innovation-based competition.     

Binomial innovation diffusion models with dynamic potential adopter population

Models for describing the time pattern of the diffusion processes for innovations are used by researchers in various disciplines. These models are in general binomial models—binomial in the sense that they focus their attention on two causal variables: 1) that part of the population who have already adopted the innovation, and 2) the rest of the population who are potential adopters. However, these models have a serious limitation in that the potential adopter population is assumed to remain constant over time. This paper presents some modified binomial innovation diffusion models that incorporate dynamic potential adopter populations. Moreover, the developed models are applied to some case studies, and their superiority in forecasting the time pattern of diffusion is also included in this presentation.     

The effect of inflation uncertainty on inflation: Stochastic volatility in mean model within a dynamic framework

This paper investigates the effect of inflation uncertainty innovations on inflation over time by considering the monthly United States data for the time period 1976–2006. In order to investigate the effect of inflation uncertainty innovation on inflation, a Stochastic Volatility in Mean model (SVM) has been employed. SVM models are generally used to capture the innovation to inflation uncertainty, which cannot be achieved in the framework of popular deterministic ARCH type of models. Empirical evidence provided here suggests that innovations in inflation volatility increases inflation persistently. This evidence is robust across various definitions of inflation and different sub-periods.     

The industrial life cycle of wind energy electrical power generation: ARI methodology modeling of life cycle dynamics

This innovation assessment addresses the factors that have influenced the exceptionally lengthy industrial technology life cycle of wind electrical power generation since its inception in the late 19th Century. It then applies the recently developed Accelerated Radical Innovation (ARI) Model to understand the dynamics of this innovation compared to those of other major 18th-20th Century innovations.Despite market pull in the late 19th Century to link small DC electrical generators with hundreds of thousands of existing wind mills used for mechanical water pumping, several factors prevented this from happening. These include the intermittent nature of wind electrical generation requiring low cost battery storage and DC-AC conversion, and the shift in the 1890s from DC to superior AC electrical generation making possible economies of scale for delivering AC electricity long distances over the grid from large hydroelectric and coal fired plants. As a consequence, wind generated electricity remained primarily a technological development until the first energy crisis in the 1970s.Development of an extensive science and technology base for wind turbine dynamics, and deployment since 2000 of commercial scale wind turbines (> 1MW) have elevated wind electrical power generation to commercial practicality, as described in two earlier papers by the authors applying technical cost modeling and experience curve projections of cost of energy (COE) to explore the economic viability of large scale wind electricity generation.. Strongly promoted by wind energy communities of practice in Europe, North America and Asia, normative COE projections suggest that by 2020 wind electrical power will be cost competitive, without tax incentives, with electricity from conventional fossil and nuclear fuel sources.Overcoming technological, business, market, societal, networking and political hurdles to date has required 120years of development to establish wind electricity generation as a breakthrough innovation with the capability to capture 20% of the world electricity market by the mid-to-late 21st Century. Further growth and maturation is expected to continue to 2100, corresponding to a projected ≅ 210year overall industry life cycle at market saturation. This finding has profound implications for innovation theory and practice, since the length of this life cycle exceeds by a factor of ≅ 4 the average life cycle diagnosed for five industrial revolutions and four key 20th Century innovations. The new ARI model provides a holistic approach to understanding the dynamics of the industrial technology life cycle for a wide variety of radical innovations as well as wind electrical power.