Book Review: Knowledge Matters: Technology, Innovation, and Entrepreneurship in Innovation Networks

    By: PDMA Headquarters on Oct 04, 2013

    Book Review: Knowledge Matters: Technology, Innovation, and Entrepreneurship in Innovation Networks and Knowledge Clusters      

    By: Elias G. Carayannis and Piero Formica . Hampshire, UK: Palgrave MacMillan, 2008. 267 + xix pages. 
    Review by: Carla Kuesten

    This book offers notes from 18 contributors—professors, engineers, leaders, presidents, advisors, research fellows, and lecturers. The focus of the book is on “profiling, analyzing, benchmarking, and modeling in socio-technical terms, ways, and means that creativity, invention and innovation are manifested and flourish in select American, European and Asian knowledge-based innovation networks andknowledge clusters that may also serve as catalysts and accelerators of new and sustainable technological venture formation and growth” (p. xv). The book highlights critical success and failure factors and lessons learned through presentation of conceptual and empirical studies. The purpose of the book is “the identification and articulation of insights that could inform both public sector policies and private sector practices” to render them more effective and efficient (p. xv).

    Working definitions used throughout the book helpful to the reader are provided. “Mode 3” is a multilateral, multinodal, multimodal, and multilevel systems approach to the conceptualization, design, and management of real and virtual, “knowledge-stock” and “knowledge-flow,” and modalities that catalyze, accelerate, and support the creation, diffusion, sharing, absorption, and use of co-specialized knowledge assets. Innovation networks are real and virtual infra-structures and infra-technologies that serve to nurture creativity, trigger invention, and catalyze innovation in a public and/or private domain context. “Knowledge Clusters” are agglomerations of co-specialized, mutually complementary, and reinforcing knowledge assets in the form of “knowledge stocks” and “knowledge flows” that exhibit self-organizing, learning-driven, dynamically adaptive competences and trends in the context of an open systems perspective” (p. xvii).

    By way of introduction, the concentration of public money on a “citadel” of a few select academic institutions for the dual purpose of education and research is questioned and challenged with what matters more creation of a free “co-opetitive” environment and the importance of formation of affinity groups and the marketplace-through “glocalizing” (globalizing and localizing), structured into “knowledge-ducts” with flow of “knowledge nuggets” such as innovation networks and knowledge clusters (Carayannis and Gonzalz,2003). National governments are encouraged to deploy public resources in accordance with three key strategies: increase independence of universities, introduce more competition, and channel funds to departments that excel in mastery of the entire knowledge chain (creation, diffusion, conversion, and entrepreneurial exploitation of scientific and technical knowledge). The book suggests academics will become entrepreneurs of the mind—in the business of “growing” people intellectually, culturally, and spiritually. Entrepreneurs are the backbone of progressive first-world countries; with the 3 C's of entrepreneurial success cited as: charismacharacter, and culture, performing a function that corresponds to knowledge energy. Entrepreneurship activities are governed through “modes.” “Mode 1” is relations based and is driven by behavioral rules that allow communication and exchange to take place without rigid, formal contracts; “Mode 2” is a rule-based governance regime subject to regulations with high fixed cost and framework of legislation, regulation, formal contracts, and enforcement by courts.

    For future knowledge flow from universities to firms, knowledge transfer needs trustful, outward looking knowledge brokers with excellent interpersonal skills, commercial awareness, and contractual experience. Reforms must encompass greater autonomy for universities, a risk-based approach to university regulation, and removal of obstacles. Measures to influence patterns of knowledge transfer to shape increasing knowledge flow include: mobility (movement of people), knowledge transfer partnerships (collaboration between source of knowledge and business user), incentives to scientists, relationship promoters, knowledge transfer funds, “start on campus” and “incubators of entrepreneurial ideas,” and a code of governance for universities. Knowledge transfer is a process for flow of knowledge (research, skills, experience, and ideas) along the knowledge chain, thereby putting knowledge into action and economic return. Collaborative integration and impediments in transfers are discussed along with results across eight universities to identify the main features between entrepreneurship-orientated academic and business. Improved relevance of university research should be adopted by stimulating academic-industry interaction, identifying market opportunities, encouraging researchers to bring their research to market, and incenting the career for researchers. Government-sponsored programs are growing that encourage professors to found companies based on their research.

    Mesoeconomic plexus level refers to a locus where productive relationships are articulated and where technological knowledge emerges (beyond national and regional levels). The complex adaptive systems (CAS) offer a context, integrating various theories of industrial organization, and social networks. The book examines orthodox approaches to innovation and technological change, relational structure of mesoeconomic plexuses as a source of competitive advantage, and formulates a hypothesis that these plexuses can be treated as complex adaptive systems.

    Business cluster formation and evolution and the “innovation ecosystem” that facilitates the formation of business clusters as a process versus a “state” are shared through the example of the Bangalore ICT Cluster. Different requirements at different stages of cluster development were noted and discussed; stages identified are: incubation, nucleation, agglomeration, and attrition. Industrial clusters are recognized as important for economic development of a region. Governments were encouraged with the important task of preparing grounds and people's minds for cluster development initiatives in developing countries.

    Network organizations, the coordination between cooperative relations of firms, universities, research laboratories, suppliers, and customers that links a variety of agents (students, scientists, research work groups, employers, enterprises and business partners, policy makers, and services—banks or venture capital firms) and their functional principles of complementary and reciprocity are described using the position regulation of Science and Technology Parks within the innovation network. Interpersonal networks are considered important channels as well as interactions for establishment of networks of innovating firms; location and capital are deemed less important. The technology park provides more than just facilities—offering connection with good technical knowledge but also relevant market knowledge.

    A conceptual framework effecting competitive advantage of regions is discussed with consideration of economic interdependencies and agglomeration of specialized capabilities and knowledge. The impact on competitive advantage and transfer of useful knowledge through appropriation, either formally (via rivalry, governance, or coordination of the system) or informally (socially) with the latter called out as extraordinary, is discussed in the context of innovation system performance.

    Knowledge-level innovation analyses are introduced as powerful tools to exploit the impact of innovations on company strategy to avert unintended diversification with product innovation-based strategies, manage resource allocation, and utilize four product innovation strategy knowledge bases (technology, end user, brand, and business). A case study is presented applying all four knowledge bases with key insights to understand: (1) innovation as an emerging micro-diversification strategy, (2) deeper approach to innovation-based diversification, (3) drivers of product innovation are related to diversification mechanisms, (4) need for double-loop learning (seeing beyond borders of existing product categories), and (5) innovation and competing companies' analyses, providing richer results on innovation's strengths and weaknesses.

    University and academic spin-offs are investigated with emphasis on antecedent conditions and nature of the linkages and means of sustaining them. Network relations are characterized by a small number of strong ties with high trust and informality. Boundary-spanning individuals between academic and business worlds are considered vital for successful spin-offs. Four cases of spin-offs are presented.

    A nonlinear relationship between patent strength and innovation is explained. The model treats innovation sequentially, current innovation building on past technology with tournament winners in a better position to win future tournaments. Patent protection strength and re-innovation around the winning patent can increase competition. Increasing patent protection increases incentives to innovate but also leads to less knowledge spillovers.

    A framework for a consumer learning roadmap that builds upon innovation adoption and consumers' knowledge development and the firm as shaper of the consumer's knowledge base is shared with the premise that innovating firms are active in triggering, monitoring, and guiding consumers, highlighting the importance of cooperation between R&D and marketing.

    Knowledge economy is explored and refers to the “economy in which the production, distribution, and usage (consumption) of knowledge is the crucial factor, which is based on the occupation and collocation of intelligence, with science and technology as the leading guidance,” where “science and technology constitute a primary productive force” put forward by Deng Xiaoping, ex-leader of China (p. 238). Examination and the concept of the knowledge economy is against the background of China's evolution and economic achievements. The author addresses the question “What is knowledge?” by extending the 4 Ws—“know-what,” “know-why,” “know-how,” and “know-who” with “know-when” and “know-why” and the question “know-quantity.” Trends and the future of knowledge economy for the modern world close the book.

    This book is a dense and a conceptually heavy read, likely best understood by economists and strategists. It is not distilled or written for easy assimilation for business managers to quickly adopt for organizational change. Yet, the concepts and approaches presented are intriguing and important considerations for academicians and business organizations interested in enhancing and advancing their innovation-based competitive positions through the use of knowledge networks and innovation clusters.

    Released: October 4, 2013, 11:31 am | Updated: October 30, 2013, 12:01 pm
    Keywords: PDMA Blog


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