Social Network Analysis

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

Models that depict innovation as a smooth, well-behaved linear process badly misspecify the nature and direction of the causal factors at work. Innovation is complex, uncertain, somewhat disorderly, and subject to changes of many sorts. Innovation is also difficult to measure and demands close coordination of adequate technical knowledge and excellent market judgment in order to satisfy economic, technological, and other types of constraints—all simultaneously. The process of innovation must be viewed as a series of changes in a complete system not only of hardware, but also of market environment, production facilities and knowledge, and the social contexts of the innovation organization.

An Overview of Innovation

What makes organizations so similar? We contend that the engine of rationalization and bureaucratization has moved from the competitive marketplace to the state and the professions. Once a set of organizations emerges as a field, a paradox arises: rational actors make their organizations increasingly similar as they try to change them. We describe three isomorphic processes-coercive, mimetic, and normative—leading to this outcome. We then specify hypotheses about the impact of resource centralization and dependency, goal ambiguity and technical uncertainty, and professionalization and structuration on isomorphic change. Finally, we suggest implications for theories of organizations and social change.

The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields (Chinese Translation)

Partnerships between companies receive a great deal of attention from top managers and researchers at the time of their formation. This attention results largely from the common perception that the initial structuring of partnerships and establishment of common goals determines partnership outcomes and success. In Alliance Advantage, Doz and Hamel shift the focus away from deal making to the internal processes within the partnership and the unfolding interactions among partners that play an important and relatively unexplored role in shaping outcomes. Focusing on the underlying reasons why companies enter alliances and the processes by which they continually learn from their interactions and re-evaluate common--and individual--goals, the authors paint a sophisticated picture of alliance dynamics over time. The authors challenge organizations to define their objectives for alliance formulation and consider whether their own corporate culture provides an "alliance ready" atmosphere.

Alliance advantage : the art of creating value through partnering

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Logic models: a tool for telling your programs performance story

Using Logic Models

This document provides guidance for evaluators who conduct impact assessments to determine the “realized” economic benefits and costs, energy, environmental benefits, and other impacts of the Office of Energy Efficiency and Renewable Energy’s (EERE) R&D programs. The focus of this Guide is on realized outcomes or impacts of R&D programs actually experienced by American citizens, industry, and others.

Overview of Evaluation Methods for R&D Programs. A Directory of Evaluation Methods Relevant to Technology Development Programs

As research and innovation have become central to the economy, the challenge of managing these activities has taken on greater importance. Studies have focused on the impact of organizational variables on research activities, such as work environment, human resource factors, and managerial practices. But little attention has been paid to the effect of differences among types of research projects. While the notion that differences exist among research projects is acknowledged, particularly in the research & development portfolio literature, there have been relatively few studies into the dimensions by which research projects, and needs of project team members, differ. Further, there is little recognition that these differences translate into the need for different research project management practices. The objective of this paper is to investigate differences among research projects along three dimensions, amount of funding, complexity of project teams, and research orientation. These dimensions are selected because of their central theoretical importance in the organizational literature, as well as posing a number of different challenges for research management. This study looked at 18 research projects at a national laboratory and analyzed the responses of project members to a comprehensive research environment survey conducted in 2001. The results of the analysis indicate that there are significant differences between types of projects along three dimensions and suggest ways that research performance can be improved through management intervention.

Investigating differences among research projects and implications for managers

In this paper, we argue that a new policy model for science and technology is needed and must be evolutionary in nature. The paper proposes utilizing the idea innovation network theory as a framework for assessing sectoral innovation patterns and identifies six types, or “arenas,” of research that are linked to innovation within these networks. Following the idea innovation network theory, the paper argues that two societal trends, the fragmentation of markets and the growth of knowledge, are driving organizations toward greater functional differentiation. Successful innovation will occur when these differentiated organizations become closely linked within innovation networks that integrate the arenas of research. The paper argues that this framework has predictive power, in that it allows the identification of path-dependent blockages or gaps within idea innovation chains that prevent the emergence of effective innovation networks in different countries. Policy makers can play an important role by fostering the development of tightly coupled networks that include organizations involved in each of the types of research. The paper provides empirical support for the framework using a cross-national European study of the telecommunications and pharmaceutical industries.

Gretchen Jordan

Papers

Logic models: a tool for telling your programs performance story

Using Logic Models

Overview of Evaluation Methods for R&D Programs. A Directory of Evaluation Methods Relevant to Technology Development Programs

Investigating differences among research projects and implications for managers

Ideas, innovations, and networks: a new policy model based on the evolution of knowledge