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Proximity and Innovation: A Critical Assessment

The original edition of this book summarized more than a decade of work on communications flow in science and engineering organizations, showing how human and organizational systems could be restructured to bring about improved productivity and better person-to-person contact. While many studies have been done since then, few of them invalidate the general conclusions and recommendations Allen offers. In a new preface he points out new developments, noting areas that need some modification, elaboration, or extension, and directing readers to the appropriate journal articles where the findings, are reported. The first three chapters provide an overview of the communication system in technology, present the author's research methods, and describe differences in the career paths and goals of engineers and scientists that cause special problems for organizations. The book then discusses how technological information is acquired by the R & D organization, shows how critical technical communication within the laboratory is for R & D performance, and originates the idea of the \"gatekeeper,\" the person who links his or her organization to the world at large. Concluding chapters take up the influence of formal and informal organization and of architecture and office layouts on communication. Many of these ideas have been successfully incorporated by architects and managers in the design of new R & D facilities and complexes. Suggested Citation Handle: RePEc:mtp:titles:0262510278 Download reference as HTML Thomas J. Allen, 1984. \"Managing the Flow of Technology: Technology Transfer and the Dissemination of Technological Information Within the R&D Organization,\" MIT Press Books, The MIT Press, edition 1, volume 1, number 0262510278, November. More services and features MyIDEAS Follow serials, authors, keywords & more New papers by email Subscribe to new additions to RePEc Author registration Public profiles for Economics researchers MPRA Upload your paper to be listed on RePEc and IDEAS EconAcademics Blog aggregator for economics research Plagiarism Cases of plagiarism in Economics Rankings Various rankings of research in Economics & related fields RePEc Genealogy Who was a student of whom, using RePEc RePEc Biblio Curated articles & papers on various economics topics Job market papers RePEc working paper series dedicated to the job market Fantasy league Pretend you are at the helm of an economics department Services from the StL Fed Data, research, apps & more from the St. Louis Fed IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.

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Managing the Flow of Technology: Technology Transfer and the Dissemination of Technological Information Within the R&D Organization (Book Review)

Developments in methodologies, agglomeration, and a range of applied issues have characterized recent advances in regional and urban studies. Volume 5 concentrates on these developments while treating traditional subjects such as housing, the costs and benefits of cities, and policy issues beyond regional inequalities. Contributors make a habit of combining theory and empirics in each chapter, guiding research amid a trend in applied economics towards structural and quasi-experimental approaches. Clearly distinguished from the New Economic Geography covered by Volume 4, these articles feature an international approach that positions recent advances within the discipline of economics and society at large. * Editors are recognized as leaders and can attract an international list of contributors* Regional and urban studies interest economists in many subdisciplines, such as labor, development, and public economics* Table of contents combines theoretical and applied subjects, ensuring broad appeal to readers

Handbook of regional and urban economics

The Strategy Process: Concept, Context, Cases

While the effects of non-geographic aggregation on inference are well studied in economics, research
on geographic aggregation is rather scarce. This knowledge gap together with the use of aggregated
spatial units in previous firm location studies result in a lack of understanding of firm location determinants at the microgeographic level. Suitable data for microgeographic location analysis has become available only recently through the emergence of Volunteered Geographic Information (VGI), especially the OpenStreetMap (OSM) project, and the increasing availability of official (open) geodata. In this paper, we use a comprehensive dataset of three million street-level geocoded firm observations to explore the location pattern of software firms in an Exploratory Spatial Data Analysis (ESDA). Based on the ESDA results, we develop a software firm location prediction model using Poisson regression and OSM data. Our findings demonstrate that the model yields plausible predictions and OSM data is suitable for microgeographic location analysis. Our results
also show that non-aggregated data can be used to detect information on location determinants, which are superimposed when aggregated spatial units are analysed, and that some findings of previous firm location studies are not robust at the microgeographic level. However, we also conclude that the lack of high-resolution geodata on socio-economic population characteristics causes systematic prediction errors, especially in cities with diverse and segregated populations.

https://www.econstor.eu/bitstream/10419/172000/1/1007199741.pdf

Analysing and predicting micro-location patterns of software firms

We analyse the geographic proximity of innovative firms to different types of knowledge sources in an urban environment on a microgeographic scale. Based on a comprehensive panel data set of manufa...

Knowledge proximity and firm innovation: A microgeographic analysis for Berlin:

Innovation is considered as a main driver of economic growth. Promoting the development of innovation through STI (science, technology and innovation) policies requires accurate indicators of innovation. Traditional indicators often lack coverage, granularity as well as timeliness and involve high data collection costs, especially when conducted at a large scale. In this paper, we propose a novel approach on how to create firm-level innovation indicators at the scale of millions of firms. We use traditional firm-level innovation indicators from the questionnaire-based Community Innovation Survey (CIS) survey to train an artificial neural network classification model on labelled (innovative/non-innovative) web texts of surveyed firms. Subsequently, we apply this classification model to the web texts of hundreds of thousands of firms in Germany to predict their innovation status. Our results show that this approach produces credible predictions and has the potential to be a valuable and highly cost-efficient addition to the existing set of innovation indicators, especially due to its coverage and regional granularity. The predicted firm-level probabilities can also directly be interpreted as a continuous measure of innovativeness, opening up additional advantages over traditional binary innovation indicators.

Predicting innovative firms using web mining and deep learning

Existing approaches to model innovation ecosystems have been mostly restricted to qualitative and small-scale levels or, when relying on traditional innovation indicators such as patents and questionnaire-based survey, suffered from a lack of timeliness, granularity, and coverage. Websites of firms are a particularly interesting data source for innovation research, as they are used for publishing information about potentially innovative products, services, and cooperation with other firms. Analyzing the textual and relational content on these websites and extracting innovation-related information from them has the potential to provide researchers and policy-makers with a cost-effective way to survey millions of businesses and gain insights into their innovation activity, their cooperation, and applied technologies. For this purpose, we propose a web mining framework for consistent and reproducible mapping of innovation ecosystems. In a large-scale pilot study we use a database with 2.4 million German firms to test our framework and explore firm websites as a data source. Thereby we put particular emphasis on the investigation of a potential bias when surveying innovation systems through firm websites if only certain firm types can be surveyed using our proposed approach. We find that the availability of a websites and the characteristics of the website (number of subpages and hyperlinks, text volume, language used) differs according to firm size, age, location, and sector. We also find that patenting firms will be overrepresented in web mining studies. Web mining as a survey method also has to cope with extremely large and hyper-connected outlier websites and the fact that low broadband availability appears to prevent some firms from operating their own website and thus excludes them from web mining analysis. We then apply the proposed framework to map an exemplary innovation ecosystem of Berlin-based firms that are engaged in artificial intelligence. Finally, we outline several approaches how to transfer firm website content into valuable innovation indicators.

/pdf/web-mining-for-innovation-ecosystem-mapping-a-framework-and-3wqkksgery.pdf

Web mining for innovation ecosystem mapping: a framework and a large-scale pilot study

In the light of digitalization and recent EU policy initiatives, information is an important asset that organizations of all sizes and from all sectors should secure. However, in order to provide common requirements for the implementation of an information security management system, the internationally well-accepted ISO/IEC 27001 standard has not shown the expected growth rate since its publication more than a decade ago. In this article, we apply web mining to explore the adoption of ISO/IEC 27001 through a series of 2664 out of more than 900 000 German firms from the Mannheim Enterprise Panel dataset that refers to this standard on their websites. As a result, we present a ‘‘landscape’’ of ISO/IEC 27001 in Germany, which shows that firms not only seek certifications themselves but often refer on their websites to partners who are certified instead. Consequently, we estimate a probit model and find that larger and more innovative firms are more likely to be certified to ISO/IEC 27001 and that almost half of all certified firms belong to the information and communications technology (ICT) service sector. Based on our findings, we derive implications for policy makers and management and critically assess the suitability of web mining to explore the adoption of management system standards.

/pdf/exploring-the-adoption-of-the-international-information-588ip2i0y0.pdf

Jan Kinne

Papers

Analysing and predicting micro-location patterns of software firms

Knowledge proximity and firm innovation: A microgeographic analysis for Berlin:

Predicting innovative firms using web mining and deep learning

Web mining for innovation ecosystem mapping: a framework and a large-scale pilot study

Exploring the Adoption of the International Information Security Management System Standard ISO/IEC 27001: A Web Mining-Based Analysis