Abdullah Gok

Use of web mining in studying innovation

As enterprises expand and post increasing information about their business activities on their websites, website data promises to be a valuable source for investigating innovation. This article examines the practicalities and effectiveness of web mining as a research method for innovation studies. We use web mining to explore the R&D activities of 296 UK-based green goods small and mid-size enterprises. We find that website data offers additional insights when compared with other traditional unobtrusive research methods, such as patent and publication analysis. We examine the strengths and limitations of enterprise innovation web mining in terms of a wide range of data quality dimensions, including accuracy, completeness, currency, quantity, flexibility and accessibility. We observe that far more companies in our sample report undertaking R&D activities on their web sites than would be suggested by looking only at conventional data sources. While traditional methods offer information about the early phases of R&D and invention through publications and patents, web mining offers insights that are more downstream in the innovation process. Handling website data is not as easy as alternative data sources, and care needs to be taken in executing search strategies. Website information is also self-reported and companies may vary in their motivations for posting (or not posting) information about their activities on websites. Nonetheless, we find that web mining is a significant and useful complement to current methods, as well as offering novel insights not easily obtained from other unobtrusive sources.

Handbook of Innovation Policy Impact

Innovation underpins competitiveness, is crucial to addressing societal challenges, and its support has become a major public policy goal. But what really works in innovation policy, and why? This Handbook, compiled by leading experts in the field, is the first comprehensive guide to understanding the logic and effects of innovation polices. The Handbook develops a conceptualisation and typology of innovation policies, presents meta-evaluations for 16 key innovation policy instruments and analyses evidence on policy-mix. For each policy instrument, underlying rationales and examples are presented, along with a critical analysis of the available impact evidence. Providing access to primary sources of impact analysis, the book offers an insightful assessment of innovation policy practice and its evaluation.

The impact of direct support to R & D and innovation in firms

This paper is part of the Compendium of Evidence on the Effectiveness of Innovation Policy Intervention. It examines the evidence on schemes that aim to promote or enhance the performance of R&D activities within companies. More specifically, in order to avoid overlaps with other reports in this series, coverage is restricted to supply-side measures which provide finance, specifically in the form of grants or loans, to support R&D undertaken by firms alone. Overall, the available evidence on the operation of direct measures seems to focus on a number of outcomes and effects, including rationales, user characteristics, governance aspects, input additionality, output additionality and behavioural additionality effects. This set of outcomes and effects is used to structure the analysis of the evidence. The report notes that the impact of policy intervention exhibits a skewed distribution ? the ?average? success of a programme tends to be based on a small number of successful cases which is accompanied by a long ?tail? of less or non- successful cases, and that most of the studies reviewed consider one point in time and do not examine the longer time frame, thus the persistence of effects arising from the policy interventions was not generally measured. Two further main findings are that much of the academic literature focus on the issues of input and, to a lesser extent, output additionality, whereas policy evaluations tend to focus on the continued relevance of the rationale of intervention and on its implementation performance. The report concludes with a number of key lessons for policy makers.

The impact of research funding on scientific outputs: Evidence from six smaller European countries

We investigate the relationships between the citation impacts of scientific papers and the sources of funding that are acknowledged as having supported those publications. We examine several relationships potentially associated with funding, including first citation, total citations, and the chances of becoming highly cited. Furthermore, we explore the links between citations and types of funding by organization and also with combined measures of funding. In particular, we examine the relationship between funding intensity and funding variety and citation. Our empirical work focuses on six small advanced European economies, applying a zero inflated negative binomial model to a set of more than 240,000 papers authored by researchers from these countries. We find that funding is not related to the first citation but is significantly related to the number of citations and top percentile citation impact. Additionally, we find that citation impact is positively related to funding variety and negatively related with funding intensity. Finally there is an inverse relationship between the relative frequency of funding and citation impact. The results presented in the paper provide insights for the design of research programs and the structure of research funding and for the behavior and strategies of research and sponsoring organizations.

Science system path-dependencies and their influences: nanotechnology research in Russia

In this paper, we study the influence of path dependencies on the development of an emerging technology in a transitional economy. Our focus is the development of nanotechnology in Russia in the period between 1990 and 2012. By examining outputs, publication paths and collaboration patterns, we identify a series of factors that help to explain Russia’s limited success in leveraging its ambitious national nanotechnology initiative. The analysis highlights four path-dependent tendencies of Russian nanotechnology research: publication pathways and the gatekeeping role of the Russian Academy of Sciences; increasing geographical and institutional centralisation of nanotechnology research; limited institutional diffusion; and patterns associated with the internationalisation of Russian research. We discuss policy implications related to path dependence, nanotechnology research in Russia and to the broader reform of the Russian science system.

Graphene enterprise: mapping innovation and business development in a strategic emerging technology

This paper explores enterprise development and commercialization in the field of graphene. Firm characteristics and relationships, value chain positioning, and factors associated with product entry are examined for a set of 65 graphene-oriented small and medium-sized enterprises located in 16 different countries. As well as secondary sources and bibliometric methods to profile developments in graphene, we use computerized data mining and analytical techniques, including cluster and regression modeling, to identify patterns from publicly available online information on enterprise web sites. We identify groups of graphene small and medium-sized enterprises differentiated by how they are involved with graphene, the materials they target, whether they make equipment, and their orientation toward science and intellectual property. In general, access to finance and the firms’ location are significant factors that are associated with graphene product introductions. We also find that patents and scientific publications are not statistically significant predictors of product development in our sample of graphene enterprises. We further identify a cohort of graphene-oriented firms that are signaling plans to develop intermediate graphene products that should have higher value in the marketplace. Our findings suggest that policy needs to ensure attention to the introduction and scale-up of downstream intermediate and final graphene products and associated financial, intermediary, and market identification support. The paper demonstrates novel data methods that can be combined with existing information for real-time intelligence to understand and map enterprise development and commercialization in a rapidly emerging and growing new technology.

Mapping the patent landscape of synthetic biology for fine chemical production pathways

A goal of synthetic biology bio‐foundries is to innovate through an iterative design/build/test/learn pipeline. In assessing the value of new chemical production routes, the intellectual property (IP) novelty of the pathway is important. Exploratory studies can be carried using knowledge of the patent/IP landscape for synthetic biology and metabolic engineering. In this paper, we perform an assessment of pathways as potential targets for chemical production across the full catalogue of reachable chemicals in the extended metabolic space of chassis organisms, as computed by the retrosynthesis‐based algorithm RetroPath. Our database for reactions processed by sequences in heterologous pathways was screened against the PatSeq database, a comprehensive collection of more than 150M sequences present in patent grants and applications. We also examine related patent families using Derwent Innovations. This large‐scale computational study provides useful insights into the IP landscape of synthetic biology for fine and specialty chemicals production.

The Impact of Innovation Inducement Prizes

This paper is part of the Compendium of Evidence on the Effectiveness of Innovation Policy Intervention. This report brings together the existing evidence on the effects of innovation inducement prizes by drawing on a number of ex-ante and ex-post evaluations as well as limited academic literature. Innovation inducement prizes have a wide range of rationales and there is no agreed on dominant rationale in the literature. It is evident from the literature we analysed that the evidence on the impact of innovation inducement prizes is scarce. There are only a few evaluations or academic works that deal with the creation of innovation output and even those which deal with the innovation output only rarely deals with the additionality. Only a very limited number of studies looked at if innovation inducement prizes led to more innovation itself or innovation outputs. There is also a consensus that innovation inducement prizes are not a substitute for other innovation policy measures but are complementary under certain conditions. Prizes can be effective in creating innovation through more intense competition, engagement of wide variety of actors, distributing risks to many participants and by exploiting more flexible solutions through a less prescriptive nature of the definition of the problem in prizes. They can overcome some of the inherent barriers to other instruments, but if prizes are poorly designed, managed and awarded, they may be ineffective or even harmful.

Introduction: Making Sense of Innovation Policy

This chapter introduces the reader to the wealth of evidence in this Handbook, and provides guidance for the interpretation of its findings. It first presents the basic definitions and delineations of innovation policy and discusses innovation policy rationales and their limitations. The chapter then reflects on the different understandings of policy instruments and on the nature of policy impact, highlighting the benefits, value and limits of impact analysis. Against this background, a typology of innovation policy instruments is presented which has been developed for this Handbook to systematise the evidence and which allows distinct entry points for readers interested in different kinds of instruments. After providing an explanation of the methodology applied throughout the Handbook, the chapter closes with reflections on how to interpret the findings of the book.

Classification of Intangible Social Innovation Concepts

In social sciences, similarly to other fields, there is exponential growth of literature and textual data that people are no more able to cope with in a systematic manner. In many areas there is a need to catalogue knowledge and phenomena in a certain area. However, social science concepts and phenomena are complex and in many cases there is a dispute in the field between conflicting definitions. In this paper we present a method that catalogues a complex and disputed concept of social innovation by applying text mining and machine learning techniques. Recognition of social innovations is performed by decomposing a definitions into several more specific criteria (social objectives, social actor interactions, outputs and innovativeness). For each of these criteria, a machine learning-based classifier is created that checks whether certain text satisfies given criteria. The criteria can be successfully classified with an F1-score of 0.83–0.86. The presented method is flexible, since it allows combining criteria in a later stage in order to build and analyse the definition of choice.