Knowledge Based Urban Development

The changing and challenging conditions of the 21st century have been significantly impacting our economy, society and built and natural environments. Today generation of knowledge—mostly in the form of technology and innovation—is seen as a panacea for the adaptation to changes and management of challenges (Yigitcanlar, 2010a). Making space and place that concentrate on knowledge generation, thus, has become a priority for many nations (van Winden, 2010). Along with this movement, concepts like knowledge cities and knowledge precincts are coined as places where citizenship undertakes a deliberate and systematic initiative for founding its development on the identification and sustainable balance of its shared value system, and bases its ability to create wealth on its capacity to generate and leverage its knowledge capabilities (Carrillo, 2006; Yigitcanlar, 2008a). In recent years, the term knowledge precinct (Hu & Chang, 2005) in its most contemporary interpretation evolved into knowledge community precinct (KCP). KCP is a mixed-use post-modern urban setting—e.g., flexible, decontextualized, enclaved, fragmented—including a critical mass of knowledge enterprises and advanced networked infrastructures, developed with the aim of collecting the benefits of blurring the boundaries of living, shopping, recreation and working facilities of knowledge workers and their families. KCPs are the critical building blocks of knowledge cities, and thus, building successful KCPs significantly contributes to the formation of prosperous knowledge cities. In the literature this type of development—a place containing economic prosperity, environmental sustainability, just socio‐spatial order and good governance—is referred as knowledge-based urban development (KBUD). This chapter aims to provide a conceptual understanding on KBUD and its contribution to the building of KCPs that supports the formation of prosperous knowledge cities.

Dubaization of Istanbul : insights from the knowledge-based urban development journey of an emerging local economy

Knowledge-based urban development (KBUD) has become a popular pursuit for cities especially from the developing countries to fast track the catching up process with their developed nation counterparts. Nevertheless, the KBUD progress for these cities is highly daunting and full of confronts. This paper aims to shed light on the major KBUD challenges of emerging local economies by undertaking an in-depth empirical investigation in one of these cities. The paper scrutinizes the prospects and constraints of Istanbul in her KBUD journey through comparative performance and policy context analyses. The findings reveal invaluable insights not only for Istanbul to reshape the policy context and better align the development with contemporary KBUD perspectives, but also for other emerging local economies to learn from these experiences.

Multimedia super corridor, Malaysia: Knowledge-based urban development lessons from an emerging economy

Purpose Knowledge-based urban development (KBUD) has been an effective strategy and an opportunity for emerging economies for catching up with the developed economies. The paper aims to investigate and provide insights on KBUD in the context of emerging economies. Design/methodology/approach The paper scrutinizes the Multimedia Super Corridor of Malaysia (MSC) by focusing on the planning, development and orchestration of the knowledge corridor. Findings The paper reveals a number of lessons and insights drawn from the development of MSC as the largest manifestation of KBUD initiative in Malaysia. Originality/value The paper provides lessons and recommendations on the planning, development and management of KBUD for emerging economies that are seeking a prosperous development.

Does size matter? Knowledge-based development of second-order city-regions in Finland

Achieving knowledge-based urban development (KBUD) profoundly depends on not only encouraging the development of economic activities, but also strengthening the societal, environmental and governance bases of city-regions. In recent years, a number of global city-regions have been investigated from the angle of this multidimensional perspective, which has provided a new comprehension in the development processes of primate city-regions. However, there is a knowledge gap in understanding how KBUD works in the second-order city-region (SOCR) context. This warrants more attention as SOCRs potentially help secure balanced development and territorial cohesion. This paper aims to empirically investigate KBUD performances of SOCRs in order to generate new insights. An assessment framework is utilised in the Finnish context, where the findings provide a nationally benchmarked snapshot of the degree of achievements of SOCRs based on numerous KBUD performance areas. The results shed light on the unique Finnish urban and regional development process, and provide lessons for other SOCRs.

Editorial: Dimensions of knowledge-based urban development

This issue marks the beginning of a new editorial cycle. In the seventh volume of the journal the editorial team will continue collating novel scientific and social developments in the broader field of ‘knowledge-based development’ to report to our readers. In this perspective, the first issue of the volume focuses on different dimensions of knowledge-based urban development. As Gabe et al. (2012, p.1179) indicate, “[i]t would be an understatement to suggest that knowledge plays a key role in today’s economy; for much of the developed world, it might be more accurate to assert that knowledge is today’s economy”. Thus, knowledge generation has been a priority for global city administrations, and there is a growing consensus amongst scholars, planners, politicians and industrialists in identifying knowledge-based urban development as a panacea to the burgeoning economic problems (Knight, 1995; Kunzmann, 2009; Yigitcanlar, 2010, 2011; Huggins and Strakova, 2012; Lönnqvist et al., 2014). Although, in the era of global knowledge economy, knowledge-based urban development is a critical factor for economic success (Pratt, 2000; Sheppard, 2002), it is not solely an economic policy. For many, knowledge-based urban development is a policy that targets building an urban setting to form perfect climates for business, people, and governance in an environmentally friendly atmosphere (Carrillo, 2006; Ergazakis et al., 2006; Angelidou et al., 2012). Each of these climates correspond to a dimension or domain of knowledge-based urban development – namely, economy, society, space, and governance (Carrillo et al., 2014). Each paper of this issue corresponds to at least one of these domains, or policy areas.

Reforming technology company incentive programs for achieving knowledge-based economic development:a Brazil-Australia comparative study

This doctoral thesis aims to demonstrate the importance of incentives to technology-based firms as a strategy to promote knowledge-based economic development (KBED). To remain competitive, technology-based firms must innovate and seek new markets; therefore, this study aims to propose an incentive model to technology-based firms as a strategy to promote knowledge-based urban development, according to framework described by Yigitcanlar (2011). This is an exploratory and descriptive research with a qualitative approach. Surveys were carried out with national trade associations that represented technology-based firms both in Brazil and Australia. After analysing the surveys, structured interviews were conducted with government representatives, trade associations and businessmen who had used financial support by the federal government. When comparing both countries, the study found the importance of direct incentives through tax incentives, for it is a less bureaucratic, quicker and more direct process for firms. We suggest to include the terms incentives in the framework of knowledge-based urban development, as one of the pillars that contribute to knowledge-based economic development.

Governance of learning mechanisms : evidence from construction firms

The focus of knowledge management (KM) in the construction industry is moving towards capability building for value creation. The study reported by this paper is motivated by recent assertions about the genesis and evolution of knowledge management capability (KMC) in the strategic management field. It attempts to shed light on the governance of learning mechanisms that develop KMC within the context of construction firms. A questionnaire survey was administered to a sample of construction contractors operating in the very dynamic Hong Kong market to elicit opinions on the learning mechanisms and business outcomes of targeted firms. On the basis of a total of 149 usable responses, structural equation modeling (SEM) analysis identified relationships among knowledge-governance mechanisms, knowledge processes, and business performance, thereby supporting the existence of strategic learning loops. The study findings provide evidence from the construction context for capability assertions that knowledge-governance mechanisms and processes form learning mechanisms that carry out strategic learning to create value, effect performance outcomes, and ultimately drive the evolution of KMC. The findings imply that it is feasible for managing construction firms to govern learning mechanisms through managing the capability-based holistic KM system, thereby reconfiguring KMC to match needs in the dynamic market environment over time.

Inferencing design styles using Baysian Networks

Reasoning with uncertain knowledge and belief has long been recognized as an important research issue in Artificial Intelligence (AI). Several methodologies have been proposed in the past, including knowledge-based systems, fuzzy sets, and probability theory. The probabilistic approach became popular mainly due to a knowledge representation framework called Bayesian networks. Bayesian networks have earned reputation of being powerful tools for modeling complex problem involving uncertain knowledge. Uncertain knowledge exists in domains such as medicine, law, geographical information systems and design as it is difficult to retrieve all knowledge and experience from experts. In design domain, experts believe that design style is an intangible concept and that its knowledge is difficult to be presented in a formal way. The aim of the research is to find ways to represent design style knowledge in Bayesian net works. We showed that these networks can be used for diagnosis (inferences) and classification of design style. The furniture design style is selected as an example domain, however the method can be used for any other domain.

Probability and story-telling : normative and descriptive models of juridical proof

The operation of the law rests on the selection of an account of the facts. Whether this involves prediction or postdiction, it is not possible to achieve certainty. Any attempt to model the operation of the law completely will therefore raise questions of how to model the process of proof. In the selection of a model a crucial question will be whether the model is to be used normatively or descriptively. Focussing on postdiction, this paper presents and contrasts the mathematical model with the story model. The former carries the normative stamp of scientific approval, whereas the latter has been developed by experimental psychologists to describe how humans reason. Neil Cohen's attempt to use a mathematical model descriptively provides an illustration of the dangers in not clearly setting this parameter of the modelling process. It should be kept in mind that the labels 'normative' and 'descriptive' are not eternal. The mathematical model has its normative limits, beyond which we may need to critically assess models with descriptive origins.

Situated interpretation in computational creativity

This paper describes, formalizes and implements an approach to computational creativity based on situated interpretation. The paper introduces the notions of framing and reframing of conceptual spaces based on empirical studies as the driver for this research. It uses concepts from situated cognition, and situated interpretation in particular, to be the basis of a formal model of the movement between conceptual spaces. This model is implemented using rules within interacting neural networks. This implementation demonstrates behaviour similar to that observed in studies of human designers.

Identifying the knowledge management structures in enterprise systems projects

Enterprise System (ES) implementation and management are knowledge intensive tasks that inevitably draw upon the experience of a wide range of people with diverse knowledge capabilities. Knowledge Management (KM) has been identified as a critical success factor in ES projects. Despite the recognized importance of managing knowledge for ES benefits realization, systematic attempts to conceptualize KM-structures have been few. Where the adequacy of KM-structures is assessed, the process and measures are typically idiosyncratic and lack credibility. Using the ‘KM-process’, itself based in sociology of knowledge, this paper conceptualizes four main constructs to measure the adequacy of KM-structures. The SEM model is tested using 310 responses gathered from 27 ES installations that had implemented SAP R/3. The findings reveal six constructs for KM-structure. Furthermore, the paper demonstrates the application of KM-structures in the context of ES using the Adaptive Structuration Theory. The results demonstrate that having adequate KM-structures in place, while necessary, is not sufficient. These rules and resources must be appropriated to have greater positive influence on the Enterprise System. Furthermore, the study provides empirical support for knowledge-based theory by illustrating the importance of knowledge use/re-use (vs. knowledge creation) as the most important driver in the process of KM.

A distributed knowledge management infrastructure based on a Topic Map grid

Modern enterprise knowledge management systems typically require distributed approaches and the integration of numerous heterogeneous sources of information. A powerful foundation for these tasks can be Topic Maps, which not only provide a semantic net-like knowledge representation means and the possibility to use ontologies for modelling knowledge structures, but also offer concepts to link these knowledge structures with unstructured data stored in files, external documents etc. In this paper, we present the architecture and prototypical implementation of a Topic Map application infrastructure, the ‘Topic Grid’, which enables transparent, node-spanning access to different Topic Maps distributed in a network.

Managing knowledge for enterprise systems in indian organizations: Case study insights

Many Enterprise Systems (ES) projects have reported nil or detrimental impacts despite the substantial investment in the system. Having expected positive outcomes for the organization and its functions through the weighty spend, the effective management of ES-related knowledge has been suggested as a critical success factor for these ES projects in ES implementations. This paper suggests theoretical views purporting the importance of understanding on knowledge management for ES success. To explain the complex, dynamic and multifaceted of knowledge management, we adopt the concepts in Learning Network Theory. We then conceptualized the impact of knowledge management on ES by analyzing five case studies in several industries in India, based on the Knowledge-based Theory of the Firm that captures the performance of the system.