China's indigenous innovation approach: the emergence of Chinese innovation theory?

Theory-driven and theory-based studies on innovation in China are relatively scarce. Most innovation studies about Chinese business are based on Chinese policy and government programmes and their results. This special issue of Technology Analysis and Strategic Management explores China's indigenous innovation strategy and suggests a research agenda that focuses on Chinese innovation theory building that incorporates China's efforts to move towards an innovation-based economy. Currently, China is developing its indigenous innovation capabilities (The Chinese term is 自主创新, pronounced zizhu chuangxin). We suggest that innovation studies of Chinese business could focus on these indigenous innovation ambitions. In addition to this, it could adopt, and be embedded in a Chinese theory of innovation instead of a traditional Western-centric theory of innovation. Our proposition is that to better understand Chinese indigenous innovation, a new paradigm of Chinese innovation should be developed. We therefore present a research agenda that can be a starting point for the development of such a theory, and present seven papers in this special issue that give content to this idea. Obviously no theory will have a monopoly on exploring Chinese innovation phenomena, but it is interesting to add a Chinese-centric view into the Western-centric scholarly view. We hope that will be one of the contributions of this special issue on innovation in China.     

Study on the modes of metropolitan innovation system

Building regional innovation system has become the important means to upgrade competence of both country and region. Based on comparatively analysis of the metropolitan innovation systems of major innovation centers in the world, this paper concludes four modes of metropolitan innovation system, which are comprehensive knowledge innovation, venture entrepreneurship, learning and overtaking, and Science Park as a carder. According to the four modes and tri-spiral theory of RIS, this paper designs the mode of Shanghai innovation system of overtaking by learning, emphasizing composite innovation player combined firm, university and government, and the strategic aim to build regional and even international innovation center through knowledge innovation, systemic innovation, organizational innovation, cultural innovation and effective control.     

Exploring the impact of open innovation on national systems of innovation — A theoretical analysis

This paper investigates the impact of open innovation on national systems of innovation. The open innovation concept has become widely established among scholars and practitioners. However, an overview of its impact on national innovation systems is still lacking. Given that the innovating firm is at the core of national innovation systems, a better understanding of shifting innovation strategies at the firm level is of fundamental importance to the actions of policy-makers within the national innovation systems framework. Based on the main analytical approaches of national innovation systems and the current state of open innovation research, we argue that open innovation practices have at least three critical effects on national systems of innovation: (a) they reinforce its importance; (b) they improve its effectiveness; and (c) they diversify its networks.     

Changing the rules? Institutional innovation and the diffusion of microgeneration

The paper addresses the question of how institutional change relates to the diffusion of microgeneration energy technologies in the UK, posed in a research project comprising interviews with thirty-one respondents connected with the field of microgeneration in the UK. It analyses the nature of institutional rules in the prevailing regime of electricity generation and in microgeneration niches. It examines how such rules might facilitate systems innovation, or contribute to the maintenance of the prevailing system or partial change. The conclusions of the paper inform and deepen understanding of how conformity to or innovation in institutional rules may hamper or potentially contribute to diffusion of environmentally sustainable microgeneration of energy.     

Does innovation help the good or the poor performing firms?

Using firm-level innovation data we find surprising results on the benefits of innovation. Only manufacturing firms with below average productivity growth are likely to benefits significantly from successful innovation, while faster growing firms do not gain additional benefits from innovating.     

Intermediary–user collaboration during the innovation implementation process

The innovation process is characterised by obstacles faced both by innovation suppliers during development and by users during implementation. Although the literature has underscored the importance of collaboration, how this process occurs during implementation remains understudied. In this study, a cross-case analysis of implementation processes showed that intermediary–user collaborations are characterised by different ways of matching users’ demands with intermediaries’ services, different formal and informal governance mechanisms, and different implementation outcomes. We propose that these characteristics are due to the specificities of implementation and to the particularities of the intermediary–user relationship. Additionally, there are particularities to intermediary–user collaborations that both facilitate implementation and create risks for its outcomes. We suggest that the link between the implementation outcome and the collaboration process affects user satisfaction, further investments in the technology, and learning. We conclude by drawing implications of the particularities of intermediary–user collaboration and implementation for theory, managers, and further research.     

Does the analysis of innovation barriers perceived by high growth firms provide information on innovation policy priorities?

High growth firms and reducing innovation barriers figure high in the European innovation policy debate. Do high growth firms face specific innovation barriers which are relevant for innovation policy? In this paper we study the robustness of the perception of innovation barriers when alternative definitions of high growth firms are used. Using data from two waves of the European Innovation survey (CIS 4 and CIS 2006) we show not only that different definitions of high growth firms lead to quite different results across country groups, but also that the results are quite different for the CIS 4 and CIS 2006 samples. We argue that in the light of the available empirical evidence this non-robustness should not come as a surprise and that this negative result makes it difficult to specifically target high growth firms with public policies. Fostering the emergence of high growth innovative firms in Europe may not be feasible with targeted funding policies only but needs a systemic approach.     

Assessing measurement errors in the CDM research–innovation–productivity relationships

ABSTRACT

The Crépon-Duguet-Mairesse 1998 article, known as CDM, initiated a structural econometric framework to analyze the relationships among research, innovation and productivity, which has been estimated most generally on the basis of cross-sectional innovation survey-type data. Some econometric implementations of the CDM approach have suggested that such data give useful but imprecise measures of the innovation output (share of innovative sales), and to a lesser degree of the innovation input (R&D). These ‘measurement errors’ may result in attenuation biases of the estimated R&D and innovation impact elasticities in the two basic CDM ‘roots’ relations of R&D to innovation and innovation to productivity, as well as in the extended production function à la Griliches linking directly R&D to productivity. Using a panel of three waves of the French Community Innovation Survey (CIS), we assess these biases and the magnitude of the underlying measurement errors, assuming mainly that they are ‘white noise’ errors. We do so by comparing two pairs of usual panel estimators (Total and Between) in both the cross-sectional and time dimensions of the data (Levels and Differences). We find large measurement errors on innovation output in the innovation–productivity equation, resulting in large attenuation biases in the related elasticity parameter. We also find smaller but sizeable measurement errors on R&D, with significant attenuation biases in the corresponding elasticity estimates, in the R&D–innovation equation and the extended production function. Simulations suggest that the measurement errors on innovation and R&D are unaffected by similar measurement errors on the capital variable.     

How does cooperative innovation affect innovation performance? Evidence from Chinese firms

This paper explores the impact of different cooperation networks upon their cooperative innovation effect (CIE) and innovation performance, and examined the relationship between the CIE and the innovation performance of firms. Some interesting findings appear. First, the findings indicate that there are significant and positive relationships between the seven cooperation networks and the CIE of firms, of which the internal cooperation network has the most significant and positive impact on their CIE. Second, the findings also reveal that there are significant and positive relationships between the six cooperation networks, except firm–government cooperation (FGC) and the innovation performance of firms. Third, contrary to some studies from developed countries, the results reveal that FGC does not demonstrate any significant impact on the innovation performance of firms. These results enrich and supplement the current understanding of the relationships between cooperation networks and innovation performance.     

Reverse causality in the R&D–patents relationship: an interpretation of the innovation persistence

Starting from the failure of the R&D–patents traditional relationship, when time-series and/or within-industry dimensions are included in the empirical analysis, the present work tries to contribute to the empirical literature from two directions. First, it performs a Granger causality test based on the theoretical presumption of a reverse patents→R&D link as an explanation for the failure of the traditional relationship. Second, assuming the reverse patents–R&D causality, we test and interpret the lag structure of such a relationship which shows the effective patent life that firms can expect within the two Schumpeterian patterns of innovations they belong to. In the light of the effective patent life, we offer a further explanation of innovation persistence which overturns the findings of the existing literature on persistence.     

Are experts better than potential users in predicting the uptake of an innovation? Extending the use of the Juster Scale

Are experts or potential users better at predicting the success of a new product? To explore this question we used an eleven-point probability scale, the Juster Scale, to ask various groups of people about their probability of taking up a new product and also their assessment of its chance of its success in the marketplace. Although this type of scale generally performs better than intention scales it tends to over-predict when used in a repertoire market and we examine its performance for a boundary condition of such a market. We also explored the use of the scale as a projective research tool which is a novel application. In this study the product was a new type of charity lottery. The study was undertaken in the month prior to the lottery closing and we subsequently knew the actual outcome. The Juster Scale generally performed poorly as a predictor in this context. The predictions from the experts were no more accurate than those of the general public but none had direct knowledge of an equivalent lottery. This exploratory study concluded that the actual behaviour of a sample of relevant consumers, where the product is available, is better for forecasting than asking for estimates of their potential behaviour, that is, behaviour predicts behaviour better than probabilities of behaviour.     

Determinants of persistence in innovation: evidence from the case study of the ‘Eye Microsurgery’ Complex

This study aims at determining the major factors supporting innovative persistence based on an in-depth analysis of the internal organizational processes of the state-owned medical institution, ‘Eye Microsurgery’ Complex in Moscow. I propose a systemic approach to the study of innovation activities, which incorporates aspects of evolutionary economics, institutional analysis and dynamic capabilities theory. The study explicitly incorporates the changing external environment as a factor shaping innovation dynamics. The findings suggest that at the earliest stage of the firm's development, the interaction between the nature of the technology and the nature of the demand, the presence of prolific innovators and a certain organizational structure that supports learning, effective knowledge production and accumulation are determinant of persistence in innovation. In later periods, the availability of resources (material, financial, specialized human capital), external collaborations, specific production techniques, well-organized technological diffusion, and motivational factors are the elements providing the basis for innovative persistence. Leadership plays a crucial role in supporting innovation and organizational transformation.     

With whom do you trade? Defensive innovation and the skill‐bias

Abstract We examine whether increased trade with countries with ineffective protection of intellectual property has contributed to the skill‐deepening of the 1980s. We construct an index of effective protection of intellectual property at the country level, combining data on protection of patents and rule of law. Next, we construct an industry‐specific version of this index, using as weights each country's trade share in the total trade of the industry. We find a decline in this trade‐weighted index, owing to a rise in trade with countries with low effective protection of intellectual property, which explains 29% of the rise in within‐industry skill‐intensity.     

Is small really beautiful? A review of the concept of niches in innovation

This article reviews the concept of innovation niches through three categories: strategic niche management (SNM), specialised markets and niches formed as a technology declines. In the literature, innovation niches generate interest from both innovation and marketing perspectives. This review focuses predominately on the former from which the niche types have been adopted and analysed. Mostly, contributions since 1980 have been included, representing the period of academic interest in innovative small firms, while both temporal and locational filters were applied to the study. It is noted that SNM has been proposed as a means to protect potentially useful innovations from full market competition, while specialist niches supply technologies to few customers in more stable environments. Incumbent technologies at the stage of decline may also retreat to niches where they can still remain competitive. Finally, it is suggested that further research on innovation niches would extend our understanding of technology dynamics.     

BIG data – BIG gains? Understanding the link between big data analytics and innovation

ABSTRACT

This paper analyzes the relationship between firms' use of big data analytics and their innovative performance in terms of product innovations. Since big data technologies provide new data information practices, they create novel decision-making possibilities, which are widely believed to support firms' innovation process. Applying German firm-level data within a knowledge production function framework we find suggestive evidence that big data analytics is a relevant determinant for the likelihood of a firm becoming a product innovator as well as for the market success of product innovations. These results hold for the manufacturing as well as for the service sector but are contingent on firms' investment in IT-specific skills. Overall, the results support the view that big data analytics have the potential to enable innovation.     

China top brand strategy and innovation

The Chinese economy appears the double-restraint characteristic at present stage including mainly resources restraint and market restraint. With the policy of reform and opening up, and especially after accelerating the two fundamental changes put forward by central government, the transformation of the economic growth mode achieved positive progress in China. There was still no brand from China mainland belonging to the 100 top world valuable brands according to Business Weekly of America in 2006. By 2007, a total of 1957 China top brand, 10 world famous China top brand are awarded in china to form a powerful enterprise group. But how to assess a brand is still troublesome. This paper shows the evolution of the policy and discusses the dilemma expecting the advice from the domestic and abroad.     

Innovation as a nonlinear process,the scientometric perspective,and the specification of an ‘innovation opportunities explorer’

The process of innovation follows nonlinear patterns across the domains of science, technology, and the economy. Novel bibliometric mapping techniques can be used to investigate and represent distinctive, but complementary perspectives on the innovation process (e.g. ‘demand’ and ‘supply’) as well as the interactions among these perspectives using animations. In a map, the different perspectives can be represented as ‘continents’ of data related to varying extents over time. For example, the different branches of Medical Subject Headings (MeSH) in the Medline database provide sources of such perspectives (e.g. ‘Diseases’ vs ‘Drugs and Chemicals’). The multiple-perspective approach enables us to reconstruct facets of the dynamics of innovation, in terms of selection mechanisms shaping localisable trajectories and/or resulting in more globalised regimes. By expanding the data with patents and scholarly publications, we demonstrate the use of this multi-perspective approach in the case of RNA Interference (RNAi). The possibility to develop an ‘Innovation Opportunities Explorer’ is specified.     

On SD-oriented mechanism of technological innovation

If one enterprise just takes technological innovation as the way for economic profit but not the combinationalprofit of economy, society and ecology, it will never survive in this fierce competition market. Based on the relationshipbetween technological innovation and sustainable development, this paper brings forward that technological innovationmust take the sustainable1 development of society as the fundamental goal. Technological innovation should be the realimpulse for the development of society, economy and ecology. On the basis of the analysis on previous technologicalinnovation impetus mechanism, combined with the influential factors, this paper puts forward SD-oriented mechanism oftechnological innovation.     

A new approach to estimation of the R&D–innovation–productivity relationship

ABSTRACT

We apply a generalized structural equation model approach to the estimation of the relationship between R&D, innovation and productivity that focuses on the potentially crucial heterogeneity across sectors. The model accounts for selectivity and handles the endogeneity of this relationship in a recursive framework which allows for feedback effects from productivity to future R&D investment. Our approach enables the estimation of the different equations as one system, allowing the coefficients to differ across sectors, and also permits us to take cross-equation correlation of the errors into account. Employing a panel of Swedish manufacturing and service firms observed in three consecutive Community Innovation Surveys in the period 2008–2012, our full-information maximum likelihood estimates show that many key channels of influence among the model's components vary meaningfully in their statistical significance and magnitude across six different sectors based on the OECD classification on technological and knowledge intensity. These results cast doubt on earlier research which does not allow for sectoral heterogeneity.