This handbook looks to provide academics and students with a comprehensive and holistic understanding of the phenomenon of innovation. Innovation spans a number of fields within the social sciences and humanities: Management, Economics, Geography, Sociology, Politics, Psychology, and History. Consequently, the rapidly increasing body of literature on innovation is characterized by a multitude of perspectives based on, or cutting across, existing disciplines and specializations. Scholars of innovation can come from such diverse starting points that much of this literature can be missed, and so constructive dialogues missed. The editors of The Oxford Handbook of Innovation have carefully selected and designed twenty-one contributions from leading academic experts within their particular field, each focusing on a specific aspect of innovation. These have been organized into four main sections, the first of which looks at the creation of innovations, with particular focus on firms and networks. Section Two provides an account of the wider systematic setting influencing innovation and the role of institutions and organizations in this context. Section Three explores some of the diversity in the working of innovation over time and across different sectors of the economy, and Section Four focuses on the consequences of innovation with respect to economic growth, international competitiveness, and employment. An introductory overview, concluding remarks, and guide to further reading for each chapter, make this handbook a key introduction and vital reference work for researchers, academics, and advanced students of innovation. Contributors to this volume - Jan Fagerberg, University of Oslo William Lazonick, INSEAD Walter W. Powell, Stanford University Keith Pavitt, SPRU Alice Lam, Brunel University Keith Smith, INTECH Charles Edquist, Linkoping David Mowery, University of California, Berkeley Mary O'Sullivan, INSEAD Ove Granstrand, Chalmers Bjorn Asheim, University of Lund Rajneesh Narula, Copenhagen Business School Antonello Zanfei, Urbino Kristine Bruland, University of Oslo Franco Malerba, University of Bocconi Nick Von Tunzelmann, SPRU Ian Miles, University of Manchester Bronwyn Hall, University of California, Berkeley Bart Verspagen , ECIS Francisco Louca, ISEG Manuel M. Godinho, ISEG Richard R. Nelson, Mario Pianta, Urbino Bengt-Ake Lundvall, Aalborg

The Oxford Handbook of Innovation

An overview of the self-organizing map algorithm, on which the papers in this issue are based, is presented in this article.

The Self-Organizing Map

Recommender systems have developed in parallel with the web. They were initially based on demographic, content-based and collaborative filtering. Currently, these systems are incorporating social information. In the future, they will use implicit, local and personal information from the Internet of things. This article provides an overview of recommender systems as well as collaborative filtering methods and algorithms; it also explains their evolution, provides an original classification for these systems, identifies areas of future implementation and develops certain areas selected for past, present or future importance.

http://romisatriawahono.net/lecture/rm/survey/information%20retrieval/Bobadilla%20-%20Recommender%20Systems%20-%202013.pdf

Recommender systems survey

Open Innovation: The New Imperative for Creating and Profiting from Technology

The authors examine the implications of electronic shopping for consumers, retailers, and manufacturers. They assume that near-term technological developments will offer consumers unparalleled opportunities to locate and compare product offerings. They examine these advantages as a function of typical consumer goals and the types of products and services being sought and offer conclusions regarding consumer incentives and disincentives to purchase through interactive home shopping vis-à-vis traditional retail formats. The authors discuss implications for industry structure as they pertain to competition among retailers, competition among manufacturers, and retailer-manufacturer relationships.

Interactive home shopping: Consumer, retailer, and manufacturer incentives to participate in

https://isiarticles.com/bundles/Article/pre/pdf/19986.pdf

A text-mining-based patent network: Analytical tool for high-technology trend

https://isiarticles.com/bundles/Article/pre/pdf/18064.pdf

An approach to discovering new technology opportunities: Keyword-based patent map approach

This paper presents a scheme for large engineering project risk management using a Bayesian belief network and applies it to the Korean shipbuilding industry. Twenty-six different risks were deduced from expert interviews and a literature review. A survey analysis was conducted on 252 experts from 11 major Korean shipbuilding companies in April 2007. The overall major risks were design change, design manpower, and raw material supply as internal risks, and exchange rate as external risk in both large-scale and medium-sized shipbuilding companies. Differences of project performance risks between large-scale and medium-sized shipbuilding companies were identified. Exceeding time schedule and specification discontent were more important to large-scale shipbuilding companies, while exceeding budget and exceeding time schedule were more important to medium-sized shipbuilding companies. The change of project performance risks was measured by risk reduction activities of quality management, and strikes at headquarters and subcontractors, in both large-scale and medium-sized shipbuilding companies. The research results should be valuable in enabling industrial participants to manage their large engineering project risks and in extending our understanding of Korean shipbuilding risks.

Yongtae Park

Papers

A text-mining-based patent network: Analytical tool for high-technology trend

An approach to discovering new technology opportunities: Keyword-based patent map approach

Large engineering project risk management using a Bayesian belief network

A systematic approach for identifying technology opportunities: Keyword-based morphology analysis

Customization of technology roadmaps according to roadmapping purposes: Overall process and detailed modules