Complex Innovation Systems Research Articles

Evaluation of Breakthrough Technological Innovation Capability of Petroleum Equipment Manufacturing Enterprises Based on the CFPR‐TIFNs Model

“Internet + innovation” is a new emerging paradigm for breakthrough technological innovation, which is more complex than traditional scenarios because “Internet +” has completely overturned the acquisition of creativity and knowledge. This article aims to evaluate the breakthrough technological innovation capability (BTIC) of petroleum equipment manufacturing enterprises under the new paradigm of “Internet + innovation.” This article constructs an index system that can reflect the characteristics of “breakthrough” and “Internet +” in five dimensions. Due to the difficulties of conducting quantitative measurements for the novel index system, a hybrid evaluation model based on a consistent fuzzy preference relationship (CFPR) and triangular intuitionistic fuzzy numbers (TIFNs) is put forward for the evaluation of BTIC. The main contribution of this article is to propose an index system and model for the evaluation of BTIC under the “Internet + innovation” paradigm, which is conducive to improving the quality of breakthrough technological innovation activities under more complex scenarios. The CFPR‐TIFNs model can not only effectively calculate the BTIC of petroleum equipment manufacturing enterprises but also deeply analyze the influencing factors for their relatively weak technological innovation capability. This article provides a new methodology to solve problems in a more complex technological innovation system.

A Framework to Assess the Citation Performance of Complex Innovation Systems.

Scientometric indicators are useful to evaluate the relevance of scientific research, to prepare rankings, and to evaluate and inform research policies. That is why the choice of appropriate indicators is a matter of primary concern. This article aims to introduce a framework to decide the appropriate type of indicator for assessing the citation-based performance of complex innovation systems. The framework is two-fold: First, it brings the methodology to decide when the use of standard average based indicators is granted, and when scale-invariant indicators are mandatory. Second, it provides the procedures to build scale-invariant indicators to assess the relative impact of complex innovation systems. The framework is validated empirically through the evaluation of the relative impact of the Chilean science system in 2017. The result suggests that the Chilean science system has characteristics of a complex innovation system such as the distribution of citations fits to a power law with an exponential cutoff and a power-law correlation between the size of the system and its impact . Furthermore, the framework shows to be efficient to compare fields of vastly different sizes.

Cooperation, scale-invariance and complex innovation systems: a generalization

The focus of this paper is the question “Can scale-invariant properties of collaborative research activities of a complex innovation system be quantified, modeled and used to inform decision makers about the effect that cooperation has on the impact of published peer-reviewed research?” Over the past few decades cooperative research activities have been extensively studied. Presently, encouragement and support for collaborative research and training is a cornerstone of many innovation policies and programs. Concurrently, the study of complex systems has produced tools and techniques that can be applied to the study of innovation systems. They have been shown to be complex systems with scale-invariant properties that can be measured and modeled providing novel insights to decision makers. An important factor contributing to the emergence of scale-invariant properties is the inseparable tension between competitive and cooperative activities among actors within a complex system. Peer-reviewed papers index in the 1990–2010 Web of Science and citations to these papers are used as a partial measure of size and impact, respectively. Documents are classified into 14 natural, health and applied sciences fields. Numbers of authors and country information from each paper are used to classify documents into various types of cooperation. Scale-invariant correlations between impact and sizes where prepared to provide measures and models used to explore the effects of cooperation types. It is shown that collaborative research tends to have greater impact and for a longer period of time that non-collaborative research. Cooperation in the more applied fields show higher growth of impact when compared to the growth of their sizes than cooperation in fields closer to the basic or ‘blue sky’ end of the R&D spectrum. Cooperation in a complex innovation system can have significant effects on the relative growth of impact with respect to growth of size and it enhances the sustainability of the Matthew Effect over time. Cooperative activities appear to sustain self-organization in a complex innovation system.

Participatory potato (solanum tuberosum l.) variety development in Ethiopia. A review

Participatory potato variety development includes the identification of the main components, participants and stakeholders, their roles, types of interactions and constraints identified in the system. Some research result indicate that, there is a less complex potato innovation system was observed at the plot site of Ethiopia and a more complex and dynamic system was observed in the case of Peru. Many Achievements were gained by participatory potato variety development in different part of Ethiopia. In southern Ethiopia, Umbulowach, Hawassa Zuria Wereda of Sidama Zone; Marachere variety was preferred by farmers for its excellent response in yield and other traits. In Tigray region of Atsbi woreda, from seven varieties three best performing varieties: Jalene, Gera, and Gudene were selected for their disease resistance and other quality traits. In North-western Ethiopia, With aid of CASCAPE project in South Achefer, Burie and Jabitehenan Districts, Belete variety was selected for its superior yield, disease and insect tolerance; In West shewa, at Jeldu, Dendi, Wolmera and Degem district, both Farmers Field School (FFS) and Farmers research Group (FRG) were established and a chances were given Farmers to select potato clones suitable to their conditions based on late blight disease resistance and yield. As a result, farmer’s ranked as 1st, a potato clone CIP–392650.516 which is the highest yielder and late blight resistant among the tested clones); in Jimma area kersa (serbo), Seka Chekorsa and Dedo Districts, Farmers select Abalolarge 1 st, abateneh 2 nd and Gudane 3 rd as three high yielder variety and in Jimma and Illuababora zone area, variety “Guasa” was selected due to its earliness, high yield advantage and market demand.

An Integrated Participatory Systems Modelling Approach: Application to Construction Innovation

This paper presents a novel five-stage integrated participatory systems modelling (IPSM) approach that can be used for a range of systems dynamics (SD) applications. The IPSM approach was formulated considering the advantages and disadvantages of existing SD modelling approaches, as well as balancing the competing goals of SD model development efficiency and robustness. A key feature of the IPSM approach is that stakeholders are central to each of the five stages of the modelling process from problem scoping, to scenario analysis and strategy implementation recommendations. Each stage of the IPSM approach was demonstrated through a case study of the innovation diffusion process in the Russian Federation construction industry. This highly complex innovation system could only be sufficiently understood using a SD model that was conceptualised, critiqued, codified, tested and utilised, by the relevant actors within that system (i.e., stakeholders). The IPSM approach facilitated the efficient formulation of the SD model for the case study application. The case study SD model simulation results indicate that sufficient government incentives and the active promotion of strong collaborative linkages between construction companies and universities are two key enablers of innovation development in the Russian Federation construction industry.

Threshold Effect of Knowledge Accumulation between Innovation Path and Innovation Performance: New Evidence from China’s High-tech Industry

In the process of transitioning from closed to open innovation, regions in developing countries need to understand how to choose the most effective path within the complex innovation system while considering their own innovation factors. Based on provincial panel data from China’s high-tech industry and the improved dynamic threshold model, we introduce the threshold of knowledge accumulation (KLA) into the non-linear mechanism between innovation paths and innovation performance to compare the dynamic threshold effect and its heterogeneity. This research provides interesting insights into innovation paths, showing that the relationship between the innovation path and innovation performance is significantly influenced by the threshold effect of KLA. As the level of KLA strengthens, its effects on each innovation path change. Overall, this article shows how KLA affects the relationship between the innovation path and innovation performance. The article concludes with a discussion of the implications of these insights for innovation management and policy.

The citation-based impact of complex innovation systems scales with the size of the system

The aim of this paper is to explore the power-law relationship between the publishing size of complex innovation systems and their citation-based impact. We analyzed articles and reviews from InCites™ database published by six complex innovation systems. We found scale-invariant properties in the complex innovation systems which were analyzed. These properties are evidenced in the power law correlation between complex innovation systems' citation-based impact and their size with a scaling exponent ź ź 1.19 ± 0.01. The results suggest citations to a complex innovation system tend to increase 21.19 or 2.28 times when the system doubles its size over time. These scale-invariant emergent properties are a common property of a complex innovation system. These properties can be quantified using the parameters of scale-invariant correlation. These parameters can be used to formulate measures and models useful for informing public policy about scale-invariant emerging properties of a complex innovation system, making comparisons of citation impact between complex systems of vastly different sizes, evaluating citation impact of complex innovation systems according to their size, long range planning, and elaborating rankings across complex innovation systems.

New narratives for innovation

Sociotechnical imaginaries are visions of desired social and technological futures created and sustained by stakeholders in science, industry and politics. Within the dominating innovation narratives there are a number of implicit and explicit beliefs that are both descriptive and normative. Technological optimism is the prevailing discourse, challenged by alternative imaginaries, among them a narrative of degrowth. In this paper we argue for the importance of producing more democratic and sustainable imaginations of future social and technological trajectories. We indicate how new narratives for innovation may include different perspectives and sources of knowledge, including heterodox economics, bio-economics, science and technology studies, and Post-Normal Science. The replacement of policy narratives, however, is not achieved through science speaking truth to power. If that were the case, policies would have changed a long time ago. The present analysis and discussion illustrates how the challenge of replacement is itself one that calls for a reflexive understanding of the relationship between knowledge, belief and agency in complex research and innovation (R&I) systems.

Organizing for innovation in complex innovation systems

Science and technology innovation has always depended on organizational innovation. But the complexity of many innovation systems now transforms the nature of this interdependence. The essay proposes a framework of organizing for twenty-first-century complex innovation systems that capture their emergent, situated, and integral nature. The framework disentangles the complex system into four distinct yet interdependent problems that must be set and solved (project, knowledge systems, strategy, and ecological connections). New research thrusts within and among the four problems are proposed.

Happy Birthday, AMD!

Academy of Management DiscoveriesVol. 2, No. 3 From the EditorHappy Birthday, AMD!Andy Van de VenAndy Van de VenCarlson School of Management University of MinnesotaPublished Online:25 Aug 2016https://doi.org/10.5465/amd.2016.0090AboutSectionsView articleView Full TextPDF/EPUB ToolsDownload CitationsAdd to favoritesTrack Citations ShareShare onFacebookTwitterLinkedInRedditEmail View articleREFERENCESAgar M. H. 1986. Speaking of ethnography. Qualitative research methods series, vol. 2, Beverly Hills, CA: Sage Publications. Google ScholarBurks A. W. 1946. Peirce’s theory of abduction. Philosophy of Science, 13: 301–306. Google ScholarDougherty D. 2016. Taking advantage of emergence: Productively innovating in complex innovation systems. Oxford, UK: Oxford University Press. Google ScholarHanson N. R. 1958. The logic of discovery. Journal of Philosophy, 55: 1073–1089. Google ScholarLocke K., Golden-Biddle K., & Feldman M. 2008. Making doubt generative: Rethinking the role of doubt in the research process. Organization Science, 19: 907. Google ScholarMagnani I. 2001. Abduction, reason, and science: Processes of discovery and explanation. New York, NY: Springer. Google ScholarMerton R. K. 1987. Three fragments from a sociologist’s notebooks: Establishing the phenomenon, Specified ignorance, and Strategic research materials. Annual Review of Sociology, 13: 1–28. Google ScholarPeirce C. Y. 1931–1958. In C. Hartshorne, P. Weiss, & A. W. Burks (Eds.), Collected papers of Charles Sanders Peirce, Volumes I–VIII. Cambridge, MA: Harvard University Press. Google ScholarTaylor J., & Van Every. 2000. The emergent organization: Communication as its site and surface. Mahwah, NJ: Erlbaum. Google ScholarVan de Ven A. H. 2007. Engaged scholarship: A guide for organizational and social research. Oxford, UK: Oxford University Press. Google ScholarWeick K. E. 1989. Theory construction as disciplined imagination. Academy of Management Review, 14: 516–531.Link , Google ScholarFiguresReferencesRelatedDetailsCited byLeveraging a Recessive Narrative to Transform Joe Paterno’s Image: Media Sensebreaking, Sensemaking, and Sensegiving During ScandalDerron G. Bishop, Linda Klebe Treviño, Dennis A. Gioia and Glen E. Kreiner31 December 2020 | Academy of Management Discoveries, Vol. 6, No. 4 Vol. 2, No. 3 Permissions Metrics in the past 12 months History Published online 25 August 2016 Published in print 1 September 2016 Information© Academy of Management DiscoveriesDownload PDF

Enabling technologies, lifecycle transitions, and industrial systems in technology foresight: Insights from advanced materials FTA

This paper investigates opportunities to enhance Future-oriented Technology Analysis (FTA) of emerging technologies within innovation systems. We address key challenges faced by policymakers developing innovation strategies for emerging technologies. In particular, we explore ways that FTA might be structured to investigate the complex innovation system journeys of novel technologies as they are developed, diffused, and deployed. In doing this, we draw on concepts from technology and operations management and related literatures to more carefully characterise the: (1) ‘technical infrastrucutre’ required to develop emerging technologies; (2) key technology transitions involved in diffusion; and (3) complex industrial value networks into which they may eventually get deployed.We investigate the extent to which these categories are already used within national technology foresight exercises. In particular, we review over 240 international FTA-related policy, strategy, and analysis documents for ‘advanced materials’. We find that – although generally used inconsistently and unsystematically within FTA – these categories repeatedly emerge as important elements in many policies, strategies, and underpinning foresight exercises. We conclude by arguing that these categories should be carefully considered in initial FTA design. And that, by doing so, FTA exercises may better reveal potential ‘innovation system failures’ and help policymakers coordinate policy actions in response.

The “life and death” of great Finnish fashion phones: A periodization of changing styles in Nokia phone design between 1992 and 2013

Visual aesthetics is an essential part of our experience of mobile devices, but the ways in which it is accounted for in design have largely been overlooked. We investigate whether an aesthetization of mobile design is taking place and, if so, how it is being pursued through institutional practices in organizations. We conduct a visual analysis of all Nokia phone releases between 1992 and 2013 complemented by an interview series with key actors. The study reveals a continuous increase in aesthetic variation between 1998 and 2008, which is visible in the variation of colors, forms, and materials. The period between 2003 and 2008, which we term the “Grand” period, marks the peak of aesthetization of Nokia’s devices. It exhibits great variation, and is visibly similar to aesthetics in the fashion industry. With the introduction of the slate form, we see a decrease in visual variation between 2009 and 2013. The interviews reveal how the visual design was driven by organizational strategies, such as customer segmentation in general, and an orientation toward the fashion industry, for example, in the creation of a fashion segment. The study reveals how aesthetic variation is weaved into a complex innovation system with sometimes conflicting demands deriving from, for instance, technology and user interaction.

What is a complex innovation system?

What is a complex innovation system?

Environmental innovation through transport policy. The implementation of the free fare policy on public transport in Tallinn, Estonia

Urban areas are of increasing relevance when it comes to sustainability. • First, about half of the world’s population now lives in cities (increasing to 60% by 2030). • Second, cities are nowadays responsible for levels of resource consumption and waste generation that are higher beyond their share on world population. • Third, cities are more vulnerable to disruptive events that can lead to restrictions on the provision of resources and to changes on the environment caused by climate change. • And fourth, because they concentrate key resources (political, social, cultural…), cities are seen as strategic scenarios where to experiment and develop solutions to cope with the prevailing sustainability challenges driven by the major social and environmental transformations. Urban agglomerations can be seen as complex innovation systems where human activities are shaped in order to transform societies towards sustainable development. For this paper, we focus on the case of an environmental innovation regarding transport policy, the implementation of the fare-free policy on public transport for all inhabitants of Tallinn, Estonia. Tallinn, with 414,000 inhabitants in 2015, is the capital of Estonia and the largest city in the country. Over the last two decades the share of public transport trips decreased dramatically. After a public opinion poll in 2012, in which over 75% of the participants voted for a fare-free public transportation system (FFPTS) in Tallinn, the new policy was implemented on 1st January 2013. From that date on inhabitants of Tallinn could use all public transport services (busses, trams, trolly-busses) operated by city-run operators for free. Later the fare-free system was implemented also on trains within Tallinn. In this paper we analyze the context, in which this policy was implemented, the main characteristics of its implementation and its actual situation. DOI: http://dx.doi.org/10.4995/CIT2016.2016.3532

What is a complex innovation system?

What is a complex innovation system?

What Is a Complex Innovation System?

Innovation systems are sometimes referred to as complex systems, something that is intuitively understood but poorly defined. A complex system dynamically evolves in non-linear ways giving it unique properties that distinguish it from other systems. In particular, a common signature of complex systems is scale-invariant emergent properties. A scale-invariant property can be identified because it is solely described by a power law function, f(x) = kxα, where the exponent, α, is a measure of scale-invariance. The focus of this paper is to describe and illustrate that innovation systems have properties of a complex adaptive system. In particular scale-invariant emergent properties indicative of their complex nature that can be quantified and used to inform public policy. The global research system is an example of an innovation system. Peer-reviewed publications containing knowledge are a characteristic output. Citations or references to these articles are an indirect measure of the impact the knowledge has on the research community. Peer-reviewed papers indexed in Scopus and in the Web of Science were used as data sources to produce measures of sizes and impact. These measures are used to illustrate how scale-invariant properties can be identified and quantified. It is demonstrated that the distribution of impact has a reasonable likelihood of being scale-invariant with scaling exponents that tended toward a value of less than 3.0 with the passage of time and decreasing group sizes. Scale-invariant correlations are shown between the evolution of impact and size with time and between field impact and sizes at points in time. The recursive or self-similar nature of scale-invariance suggests that any smaller innovation system within the global research system is likely to be complex with scale-invariant properties too.

Complex regional innovation networks and HEI engagement - the case of Chicago

This article considers how HEIs engage within local complex development networks in order to develop the urban metropolis, using the case of Chicago as a specific example. The data utilised in the study are based on document analysis and interviews with some 40 representatives of organisations within the Chicago metropolitan area, including regional HEIs. Qualitative content analysis was undertaken in order to determine core themes and discourses, and to build a logical chain of evidence to formulate our conclusions, which offer new thinking about the regional engagement role of HEIs within complex innovation systems. Our focus of analysis was the extent to which an adaptive and creative co-operation network of local triple helix actors had been created. Our study shows that creativity, the sharing of information, and acting and learning together are critical success factors in city development, and in particular in capitalising in the knowledge held by HEIs.

What is a Complex Innovation System?

Innovation systems are sometimes referred to as complex systems, something that is intuitively understood but poorly defined. A complex system dynamically evolves in non-linear ways giving it unique properties that distinguish it from other systems. In particular, a common signature of complex systems is scale-invariant emergent properties. A scale-invariant property can be identified because it is solely described by a power law function, f(x) = kx^α, where the exponent, α, is a measure of scale-invariance. The focus of this paper is to describe and illustrate that innovation systems have properties of a complex adaptive system. In particular scale-invariant emergent properties indicative of their complex nature that can be quantified and used to inform public policy. The global research system is an example of an innovation system. Peer-reviewed publications containing knowledge are a characteristic output. Citations or references to these articles are an indirect measure of the impact the knowledge has on the research community. Peer-reviewed papers indexed in Scopus and in the Web of Science were used as data sources to produce measures of sizes and impact. These measures are used to illustrate how scale-invariant properties can be identified and quantified. It is demonstrated that the distribution of impact has a reasonable likelihood of being scale-invariant with scaling exponents that tended toward a value of less than 3.0 with the passage of time and decreasing group sizes. Scale-invariant correlations are shown between the evolution of impact and size with time and between field impact and sizes at points in time. The recursive or self-similar nature of scale-invariance suggests that any smaller innovation system within the global research system is likely to be complex with scale-invariant properties too.

Innovation economics and the role of the innovative entrepreneur in economic theory

Innovation economics is poorly defined due to a plethora of meanings to innovation, and each having a distinctive diverse connection to economic analysis. This crucial aspect of economic development is only weakly integrated into the main body of economics. An excursion through the history of economic thought is conducted in order to find the innovative entrepreneur. This starts with early political economy and on to the cul-de-sac of neoclassical economics and then the early 20th Century dynamic paths for innovation of Joseph Schumpeter (from supply-side) and Michał Kalecki (from demand-side). The tour ends with the innovation systems work of a diverse set of modern heterodox economists. There is a lack of coherence on what innovation economics is, and the role of the innovative entrepreneur as the change agent tends to fade in the background of these complex innovation systems. A research strategy to overcome this problem ends the paper.

The Chinese innovation system during economic transition: A scale-independent view

This paper uses scale-independent indicators to explore the Chinese national and regional innovation systems during economic transition. Our perception of an innovation system is frequently informed by conventional indicators based on linear assumptions while actually innovation systems may behave differently. Scale-independent indicators characterize non-linear properties of an innovation system. They can give decision makers deeper insight into the dynamics of innovation systems, and they may lead to more practical public policies [Katz, J. S. (2006). Indicators for complex innovation systems. Research Policy, 35, 893–909]. As reported for the European and Canadian innovation systems the Chinese systems exhibited scaling correlations between GERD (Gross Expenditure on Domestic R&D) and GDP (Gross Domestic Product) over time and at points in time. The scaling factors of the correlations tell us that between 1995 and 2005 the Chinese GERD exhibited a strong non-linear tendency to increase with GDP. Furthermore they show that the GERD of the Western region is growing much slower than its GDP as compared with Eastern and Central regions. This observation has policy implications suggesting further improvements need to be made to the research infrastructure and funding of the Western region. The GDP–POP (Population) scaling factor shows that the ‘wealth intensity’ or GDP per capita is increasing much faster than the exponential growth of the Chinese population. In contrast the systemic GDP–POP scaling factor shows that regional development is non-linear. Finally, the paper–GDP and patent–GDP scaling factors tell us that outputs of science and technology for China are growing faster than economic growth. The systemic paper–GDP and patent–GDP scaling factors show that the growth rates are uneven across the provinces.