Spatial restructuring of cities in the age of knowledge economy : insights from Australian cities

In the age of knowledge economy, knowledge production, and where, how and by whom it is produced, has become one of the most important factors in determining the quality of life and competitiveness of a city. In different parts of the world, cities that are the centres of knowledge production are branded under different names, e.g. knowledge city, creative city, ubiquitous eco city, smart city. This paper focuses on the core building block of these cities: ‘knowledge precincts’ that are the catalytic magnet infrastructures impacting knowledge production. The paper discusses the increasing importance of knowledge-based urban development within the paradigm of knowledge economy, and the role of knowledge community precincts as an instrument to seed the foundation of knowledge production. This paper explores knowledge based urban development, particularly knowledge community precinct development, potentials of Sydney, Melbourne and Brisbane, and benchmarks them against Boston. The paper also draws conclusions and recommendations for other cities considering knowledge based development.

Analysing policy values in a knowledge economy

This fascinating handbook defines how knowledge contributes to social and economic life, and vice versa. It considers the five areas critical to acquiring a comprehensive understanding of the knowledge economy: the nature of the knowledge economy; social, cooperative, cultural, creative, ethical and intellectual capital; knowledge and innovation systems; policy analysis for knowledge-based economies; and knowledge management. In presenting the outcomes of an important body of research, the handbook enables knowledge policy and management practitioners to be more systematically guided in their thinking and actions. The contributors cover a wide disciplinary spectrum in an accessible way, presenting concise, to-the-point discussions of critical concepts and practices that will enable practitioners to make effective research, managerial and policy decisions. They also highlight important new areas of concern to knowledge economies such as wisdom, ethics, language and creative economies that are largely overlooked.

Managing knowledge transfer as a strategic approach to competitive advantage

Knowledge has been recognised as a source of competitive advantage. Knowledge-based resources allow organisations to adapt products and services to the marketplace and deal with competitive challenges that enable them to compete more effectively. One factor critical to using knowledge-based resources is the ability to transfer knowledge as a dimension of the learning organisation. There are many elements that may influence whether knowledge transfer can be effectively achieved in an organisation such as leadership, problem-solving behaviours, support structures, change management capabilities, absorptive capacity and the nature of the knowledge. An existing framework was applied in a case study to explain how knowledge transfer can be managed effectively and to identify emerging issues or additional factors involved in the process. As a result, a refined framework is proposed that provides a better understanding for the effective management of knowledge transfer processes that can provide a competitive advantage.

Research training and national innovation systems in Australia, Finland and the United States : a policy and systems study supported by 30 case studies of research students in the fields of geospatial science, wireless communication, biosciences, and materials science and engineering

Reforms to the national research and research training system by the Commonwealth Government of Australia sought to effectively connect research conducted in universities to Australia's national innovation system. Research training has a key role in ensuring an adequate supply of highly skilled people for the national innovation system. During their studies, research students produce and disseminate a massive amount of new knowledge. Prior to this study, there was no research that examined the contribution of research training to Australia's national innovation system despite the existence of policy initiatives aiming to enhance this contribution. Given Australia's below average (but improving) innovation performance compared to other OECD countries, the inclusion of Finland and the United States provided further insights into the key research question. This study examined three obvious ways that research training contributes to the national innovation systems in the three countries: the international mobility and migration of research students and graduates, knowledge production and distribution by research students, and the impact of research training as advanced human capital formation on economic growth. Findings have informed the concept of a research training culture of innovation that aims to enhance the contribution of research training to Australia's national innovation system. Key features include internationally competitive research and research training environments; research training programs that equip students with economically-relevant knowledge and the capabilities required by employers operating in knowledge-based economies; attractive research careers in different sectors; a national commitment to R&D as indicated by high levels of gross and business R&D expenditure; high private and social rates of return from research training; and the horizontal coordination of key organisations that create policy for, and/or invest in research training.

Electronic telephone directory listings : preferred sampling frame for a population-based study of childhood cancer in Australia

PURPOSE: We report our telephone-based system for selecting community control series appropriate for a complete Australia-wide series of Ewing's sarcoma cases. METHODS: We used electronic directory random sampling to select age-matched controls. The sampling has all listed telephone numbers on an up-dated CD-Rom. RESULTS: 95% of 2245 telephone numbers selected were successfully contacted. The mean number of attempts needed was 1.94, 58% answering at the first attempt. On average, we needed 4.5 contacts per control selected. Calls were more likely to be successful (reach a respondent) when made in the evening (except Saturdays). The overall response rate among contacted telephone numbers was 92.8%. Participation rates among female and male respondents were practically the same. The exclusion of unlisted numbers (13.5% of connected households) and unconnected households (3.7%) led to potential selection bias. However, restricting the case series to listed cases only, plus having external information on the direction of potential bias allow meaningful interpretation of our data. CONCLUSION: Sampling from an electronic directory is convenient, economical and simple, and gives a very good yield of eligible subjects compared to other methods.

GYAN: A methodology for rule extraction from artificial neural networks

Artificial neural network (ANN) learning methods provide a robust and non-linear approach to approximating the target function for many classification, regression and clustering problems. ANNs have demonstrated good predictive performance in a wide variety of practical problems. However, there are strong arguments as to why ANNs are not sufficient for the general representation of knowledge. The arguments are the poor comprehensibility of the learned ANN, and the inability to represent explanation structures. The overall objective of this thesis is to address these issues by: (1) explanation of the decision process in ANNs in the form of symbolic rules (predicate rules with variables); and (2) provision of explanatory capability by mapping the general conceptual knowledge that is learned by the neural networks into a knowledge base to be used in a rule-based reasoning system. A multi-stage methodology GYAN is developed and evaluated for the task of extracting knowledge from the trained ANNs. The extracted knowledge is represented in the form of restricted first-order logic rules, and subsequently allows user interaction by interfacing with a knowledge based reasoner. The performance of GYAN is demonstrated using a number of real world and artificial data sets. The empirical results demonstrate that: (1) an equivalent symbolic interpretation is derived describing the overall behaviour of the ANN with high accuracy and fidelity, and (2) a concise explanation is given (in terms of rules, facts and predicates activated in a reasoning episode) as to why a particular instance is being classified into a certain category.

Knowledge infrastructure : managing the assets of creative urban regions

Urban infrastructure along the hard forms such as roads, electricity, water and sewers also includes the soft forms such as research, training, innovation and technology. Knowledge and creativity are keys to soft infrastructure and socioeconomic development. Many city administrations around the world adjust their endogenous development strategies increasingly by investing in soft infrastructure and aiming for a knowledge-based development. At this point, the mapping and management of knowledge asset of cities has become a critical issue for promoting creative urban regions. The chapter scrutinizes the relations between knowledge assets and urban infrastructures and examines the management model to improve soft infrastructure provision.

Making space and place for knowledge production : socio-spatial development of knowledge community precincts

In the knowledge era the importance of making space and place for knowledge production is clearly understood worldwide by many city administrations that are keen on restructuring their cities as highly competitive and creative places. Consequently, knowledge-based urban development and socio-spatial development of knowledge community precincts have taken their places among the emerging agendas of the urban planning and development practice. This chapter explores these emerging issues and scrutinizes the development of knowledge community precincts that have important economic, social and cultural dimensions on the formation of competitive and creative urban regions. The chapter also sheds light on the new challenges for planning discipline, and discusses the need for and some specifics of a new planning paradigm suitable for dealing with 21st Century’s socio-economic development and urbanization problems.

Evaluating sustainability of urban development and its contribution to a knowledge-base development

Purpose – The purpose of the paper is to discuss the components of urban sustainability as to their implications about knowledge-base economy and society Design/methodology/approach – An indexing model which can be used by the local government specifically in Australia is presented to generate sustainable urban development policies. The model consists of sustainable neighbourhood indicators and employs a spatial indexing method to measure the sustainability performance of the urban settings Originality/value – This methodology puts in evidence about the use of indexing methodology in the assessment of sustainable neighbourhood performance Practical implications – This model could be considered as a practical decision aid tool for local government planning agencies for the evaluation of development scenarios Keywords – knowledge-based urban development, sustainable urban development, sustainable transport, sustainability assessment Paper type – Academic Research Paper

Informational city

Many cities worldwide face the prospect of major transformation as the world moves towards a global information order. In this new era, urban economies are being radically altered by dynamic processes of economic and spatial restructuring. The result is the creation of ‘informational cities’ or its new and more popular name, ‘knowledge cities’. For the last two centuries, social production had been primarily understood and shaped by neo-classical economic thought that recognized only three factors of production: land, labor and capital. Knowledge, education, and intellectual capacity were secondary, if not incidental, factors. Human capital was assumed to be either embedded in labor or just one of numerous categories of capital. In the last decades, it has become apparent that knowledge is sufficiently important to deserve recognition as a fourth factor of production. Knowledge and information and the social and technological settings for their production and communication are now seen as keys to development and economic prosperity. The rise of knowledge-based opportunity has, in many cases, been accompanied by a concomitant decline in traditional industrial activity. The replacement of physical commodity production by more abstract forms of production (e.g. information, ideas, and knowledge) has, however paradoxically, reinforced the importance of central places and led to the formation of knowledge cities. Knowledge is produced, marketed and exchanged mainly in cities. Therefore, knowledge cities aim to assist decision-makers in making their cities compatible with the knowledge economy and thus able to compete with other cities. Knowledge cities enable their citizens to foster knowledge creation, knowledge exchange and innovation. They also encourage the continuous creation, sharing, evaluation, renewal and update of knowledge. To compete nationally and internationally, cities need knowledge infrastructures (e.g. universities, research and development institutes); a concentration of well-educated people; technological, mainly electronic, infrastructure; and connections to the global economy (e.g. international companies and finance institutions for trade and investment). Moreover, they must possess the people and things necessary for the production of knowledge and, as importantly, function as breeding grounds for talent and innovation. The economy of a knowledge city creates high value-added products using research, technology, and brainpower. Private and the public sectors value knowledge, spend money on its discovery and dissemination and, ultimately, harness it to create goods and services. Although many cities call themselves knowledge cities, currently, only a few cities around the world (e.g., Barcelona, Delft, Dublin, Montreal, Munich, and Stockholm) have earned that label. Many other cities aspire to the status of knowledge city through urban development programs that target knowledge-based urban development. Examples include Copenhagen, Dubai, Manchester, Melbourne, Monterrey, Singapore, and Shanghai. Knowledge-Based Urban Development To date, the development of most knowledge cities has proceeded organically as a dependent and derivative effect of global market forces. Urban and regional planning has responded slowly, and sometimes not at all, to the challenges and the opportunities of the knowledge city. That is changing, however. Knowledge-based urban development potentially brings both economic prosperity and a sustainable socio-spatial order. Its goal is to produce and circulate abstract work. The globalization of the world in the last decades of the twentieth century was a dialectical process. On one hand, as the tyranny of distance was eroded, economic networks of production and consumption were constituted at a global scale. At the same time, spatial proximity remained as important as ever, if not more so, for knowledge-based urban development. Mediated by information and communication technology, personal contact, and the medium of tacit knowledge, organizational and institutional interactions are still closely associated with spatial proximity. The clustering of knowledge production is essential for fostering innovation and wealth creation. The social benefits of knowledge-based urban development extend beyond aggregate economic growth. On the one hand is the possibility of a particularly resilient form of urban development secured in a network of connections anchored at local, national, and global coordinates. On the other hand, quality of place and life, defined by the level of public service (e.g. health and education) and by the conservation and development of the cultural, aesthetic and ecological values give cities their character and attract or repel the creative class of knowledge workers, is a prerequisite for successful knowledge-based urban development. The goal is a secure economy in a human setting: in short, smart growth or sustainable urban development.

Preface [From The Third Knowledge City World Summit 2010 proceedings]

‘Knowledge’ is a resource, which relies on the past for a better future. In the 21st century, more than ever before, cities around the world depend on the knowledge of their citizens, their institutions and their firms and enterprises. The knowledge image, the human competence and the reputation of their public and private institutions and corporations profiles a city. It attracts investment, qualified labour and professionals, as well as students and researchers. And it creates local life spaces and professional milieus, which offer the quality of life to the citizens that are seeking to cope with the challenges of modern life in a competitive world. Integrating knowledge-based development in urban strategies and policies, beyond the provision of schools and locations for higher education, has become a new ambitious arena of city politics. Coming from theory to practice, and bringing together the manifold knowledge stakeholders in a city and preparing joint visions for the knowledge city is a new challenge for city managers, urban planners and leaders of the civic society . It requires visionary power, creativity, holistic thinking, the willingness to cooperate with all groups of the local civil society, and the capability to moderate communication processes to overcome conflicts and to develop joint action for a sustainable future.

Urban, regional, national and global knowledge capital [Guest editorial]

Purpose – The purpose of this paper is to introduce the JKM 2010 annual special issue on knowledge based development (KBD) with reference to the multi-level analysis characteristic of the field. ----- ----- Design/methodology/approach – A description of the knowledge management approach at ESOC (European Space Operations Centre of the European Space Agency) is provided first. At the core of this approach is the breakdown of knowledge in individual technical domains followed by coverage analysis and criticality assessment. Such a framework becomes the reference for best knowledge acquisition, transfer and storage locus identification and subsequent knowledge management practices and guidelines. ----- ----- Findings – KBD provides an integrated framework to account for multidisciplinary analyses and multilevel practices in knowledge capital generation, distribution and utilization. ----- ----- Originality/value – The collection of papers included in the annual special issue on KBD provides a representative, composite view of the research topics and applications concerns in the field. Involving a number of disciplines and levels of analysis, issues ranging from the technological gatekeeper to global knowledge flows show the interdependence of KBD concepts and tools.

The role of the built environment in the creation, cultivation and acquisition of a knowledge-base

This chapter explores the role of the built environment in the creation, cultivation and acquisition of a knowledge base by people populating the urban landscape. It examines McDonald’s restaurants as a way to comprehend the relevance of the physical design in the diffusion of codified and tacit knowledge at an everyday level. Through an examination of space at a localised level, this chapter describes the synergies of space and the significance of this relationship in navigating the global landscape.

Selected new training documents to update user profile

Relevance Feedback (RF) has been proven very effective for improving retrieval accuracy. Adaptive information filtering (AIF) technology has benefited from the improvements achieved in all the tasks involved over the last decades. A difficult problem in AIF has been how to update the system with new feedback efficiently and effectively. In current feedback methods, the updating processes focus on updating system parameters. In this paper, we developed a new approach, the Adaptive Relevance Features Discovery (ARFD). It automatically updates the system's knowledge based on a sliding window over positive and negative feedback to solve a nonmonotonic problem efficiently. Some of the new training documents will be selected using the knowledge that the system currently obtained. Then, specific features will be extracted from selected training documents. Different methods have been used to merge and revise the weights of features in a vector space. The new model is designed for Relevance Features Discovery (RFD), a pattern mining based approach, which uses negative relevance feedback to improve the quality of extracted features from positive feedback. Learning algorithms are also proposed to implement this approach on Reuters Corpus Volume 1 and TREC topics. Experiments show that the proposed approach can work efficiently and achieves the encouragement performance.