A business engineering approach to client relationship management in a knowledge based firm

This thesis examines Customer Relationship Management and how the capabilities of an organisation to innovate can be enhanced via its implementation in a Knowledge Based Firm. The research identifies current customer knowledge components within an organisation and identifies for future use, CRM components for implementation within a Knowledge Based Firm. Opinions from a panel of experts' are identified for best practice customer relationship strategy, the most important CRM processes and identification of customer knowledge components that will form the basis of implementing a successful CRM to gain a competitive advantage through enhancing the innovative capability for a Knowledge Based Firm.

Knowledge and the City : Concepts, Applications and Trends of Knowledge-Based Urban Development

This book underlines the growing importance of knowledge for the competitiveness of cities and their regions. Examining the role of knowledge - in its economic, socio-cultural, spatial and institutional forms - for urban and regional development, identifying the preconditions for innovative use of urban and regional knowledge assets and resources, and developing new methods to evaluate the performance and potential of knowledge-based urban and regional development, the book provides an in-depth and comprehensive understanding of both theoretical and practical aspects of knowledge-based development and its implications and prospects for cities and regions.

Developing Co-operating Legal Knowledge Based Systems

In attempting to build intelligent litigation support tools, we have moved beyond first generation, production rule legal expert systems. Our work supplements rule-based reasoning with case based reasoning and intelligent information retrieval. This research, specifies an approach to the case based retrieval problem which relies heavily on an extended object-oriented / rule-based system architecture that is supplemented with causal background information. Machine learning techniques and a distributed agent architecture are used to help simulate the reasoning process of lawyers. In this paper, we outline our implementation of the hybrid IKBALS II Rule Based Reasoning / Case Based Reasoning system. It makes extensive use of an automated case representation editor and background information.

The IKBALS project: multi-modal reasoning in legal knowledge based systems

In attempting to build intelligent litigation support tools, we have moved beyond first generation, production rule legal expert systems. Our work integrates rule based and case based reasoning with intelligent information retrieval. When using the case based reasoning methodology, or in our case the specialisation of case based retrieval, we need to be aware of how to retrieve relevant experience. Our research, in the legal domain, specifies an approach to the retrieval problem which relies heavily on an extended object oriented/rule based system architecture that is supplemented with causal background information. We use a distributed agent architecture to help support the reasoning process of lawyers. Our approach to integrating rule based reasoning, case based reasoning and case based retrieval is contrasted to the CABARET and PROLEXS architectures which rely on a centralised blackboard architecture. We discuss in detail how our various cooperating agents interact, and provide examples of the system at work. The IKBALS system uses a specialised induction algorithm to induce rules from cases. These rules are then used as indices during the case based retrieval process. Because we aim to build legal support tools which can be modified to suit various domains rather than single purpose legal expert systems, we focus on principles behind developing legal knowledge based systems. The original domain chosen was theAccident Compensation Act 1989 (Victoria, Australia), which relates to the provision of benefits for employees injured at work. For various reasons, which are indicated in the paper, we changed our domain to that ofCredit Act 1984 (Victoria, Australia). This Act regulates the provision of loans by financial institutions. The rule based part of our system which provides advice on the Credit Act has been commercially developed in conjunction with a legal firm. We indicate how this work has lead to the development of a methodology for constructing rule based legal knowledge based systems. We explain the process of integrating this existing commercial rule based system with the case base reasoning and retrieval architecture.

Innovating urban policymaking and planning mechanisms to deliver knowledge-based agendas : a methodological approach

This paper aims to develop a comprehensive approach to innovate urban policymaking and planning to successfully deliver the knowledge-based agenda. The paper, first, examines the concept of knowledge-based urban development, which has become a popular urban development policy and strategy in recent years, through a comprehensive review of the literature. It, then, introduces and discusses a novel methodological approach for effective policymaking and planning mechanism to deliver the knowledge-based agenda of cities. The paper, with the proposed methodology, brings together urban policymaking and planning approaches, and introduces a novel way to assess knowledge-based urban development achievements and potentials of emerging and prosperous knowledge cities. The paper, thus, provides an invaluable instrument to inform local and regional decision and plan making mechanisms to deliver their knowledge-based agendas and help them in moving towards building their sustainable knowledge cities.

Transcript and metabolite profiling for the evaluation of tobacco tree and poplar as feedstock for the bio-based industry

The global demand for food, feed, energy and water poses extraordinary challenges for future generations. It is evident that robust platforms for the exploration of renewable resources are necessary to overcome these challenges. Within the multinational framework MultiBioPro we are developing biorefinery pipelines to maximize the use of plant biomass. More specifically, we use poplar and tobacco tree (Nicotiana glauca) as target crop species for improving saccharification, isoprenoid, long chain hydrocarbon contents, fiber quality, and suberin and lignin contents. The methods used to obtain these outputs include GC-MS, LC-MS and RNA sequencing platforms. The metabolite pipelines are well established tools to generate these types of data, but also have the limitations in that only well characterized metabolites can be used. The deep sequencing will allow us to include all transcripts present during the developmental stages of the tobacco tree leaf, but has to be mapped back to the sequence of Nicotiana tabacum. With these set-ups, we aim at a basic understanding for underlying processes and at establishing an industrial framework to exploit the outcomes. In a more long term perspective, we believe that data generated here will provide means for a sustainable biorefinery process using poplar and tobacco tree as raw material. To date the basal level of metabolites in the samples have been analyzed and the protocols utilized are provided in this article.

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.

A knowledge-based clustering scheme

In this paper the notion of conceptual cohesiveness is precised and used to group objects semantically, based on a knowledge structure called ‘cohesion forest’. A set of axioms is proposed which should be satisfied to make the generated clusters meaningful.

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.

A knowledge-based approach to pattern generation

Pattern Cognition is looked at from the functional view point. The need for knowledge in synthesizing such patterns is explained and various aspects of knowledge-based pattern generation are highlighted. This approach to the generation of patterns is detailed with a concrete example.

Knowledge-based clustering

In the knowledge-based clustering approaches reported in the literature, explicit know ledge, typically in the form of a set of concepts, is used in computing similarity or conceptual cohesiveness between objects and in grouping them. We propose a knowledge-based clustering approach in which the domain knowledge is also used in the pattern representation phase of clustering. We argue that such a knowledge-based pattern representation scheme reduces the complexity of similarity computation and grouping phases. We present a knowledge-based clustering algorithm for grouping hooks in a library.