It has become generally accepted to refer to today‟s global economy as a knowledge-based economy, since knowledge has increasingly become the resource, instead of a resource for wealth creation. The ability of businesses to harness the potential of intangible assets such as knowledge has become far more decisive than their ability to manage physical assets. In the implementation of knowledge management activities, knowledge sharing is recognised as an integral task and key enabler of knowledge management. Although knowledge sharing is regarded as one of the most crucial factors in the effective management of knowledge, in knowledge-intensive businesses in particular, it has also been established that most employees are reluctant to share knowledge. Research further confirms that the factors that promote or discourage knowledge-sharing behaviour in businesses are poorly understood and that knowledge management systems fail as a result of the misunderstanding of individual characteristics that could influence knowledge sharing. Moreover, the focus of knowledge-sharing literature, in terms of the unit of analysis, is rarely at an individual/micro level, although the role of individuals in the knowledge-sharing process is critical as tacit knowledge resides within the individual and knowledge sharing starts with individuals. Given the importance of understanding knowledge sharing of individuals in knowledge-intensive businesses – but noting the lack of existing systematic, integrated research that focuses on individual-related factors influencing knowledge sharing – the purpose of this study was to fill the gap in the current literature. As such, the primary objective of this research was to identify and empirically investigate the individual-related factors influencing the Knowledge-sharing intention of individual employees in knowledge-intensive businesses. The literature review revealed twelve constructs, namely Individuals’ awareness, Intrinsic motivation, Extrinsic motivation, Transactional psychological contract breach, Relational psychological contract breach, Relationship conflict, Task conflict, Extraversion, Neuroticism, Openness to experience, Agreeableness and Conscientiousness that could influence the dependent variable Knowledge-sharing intention in knowledge-intensive businesses. Various moderating relationships between the dependent and independent variables were also proposed, while seven demographic variables (Age, Gender, Language, Highest qualification, Ethnic background, Organisational tenure and Job tenure of the respondent) were identified as potential control variables. Each construct in the hypothesised model of individual-related factors influencing Knowledge-sharing intention was defined and operationalised using items sourced from validated measuring instruments in previous studies. Several self-generated items based on secondary sources were also formulated. A structured questionnaire was made available to respondents identified by means of the convenience sampling technique, and the data collected from 597 usable questionnaires was subjected to various statistical analyses. An exploratory factor analysis (EFA) was conducted which confirmed the unique factors present in the data, and Cronbach-alpha coefficients were calculated to confirm the reliability of the measuring instrument. Structural equation modelling (SEM) was the main statistical procedure used to test the significance of the relationships hypothesised between the various independent and dependent variables. A subset of SEM, namely general linear modelling (GLM) was used to determine the influence of selected demographic variables on Knowledge-sharing intention and to assess various moderating relationships as proposed in the hypothesised model. The main findings of this study were that personality traits are strong predictors of individual employees‟ willingness to share knowledge, and that the maturity of individuals, in terms of realising the significance and value of sharing their knowledge with others, and in recognising the intrinsic benefits of sharing, influence Knowledge-sharing intention. The main limitations of the study were the use of a convenience sampling technique to collect the data, as well as the dependence of self-report by respondents, which could lead to response bias. This study has added to the body of knowledge management research, in particular knowledge-sharing research, by investigating selected individual-related factors influencing the Knowledge-sharing intention of individuals in a particular subset of businesses, namely knowledge-intensive businesses, and focusing on a particular type of knowledge, namely tacit knowledge. From a business‟s perspective, this study offers recommendations and suggestions for managing these individual-related factors in such a way as to increase knowledge sharing among employees, and as a result, the effectiveness and competitive advantage of knowledge-intensive businesses.

Thesis (MTech (Business Information Systems))--Cape Peninsula University of Technology, 2017. / The aim of this study was to explore the social determinants for the institutionalisation of knowledge sharing within an organisation. Institutionalisation offers stabilising benefits and contributes to nurturing a culture of knowledge sharing. Systematic sharing of knowledge cannot take place unless there are procedures, policies and guidelines for knowledge sharing. Giddens’s concept of duality of structure was used as the theoretical lens. Institutionalisation is considered to be rules that are shared and that recognise categories of social actors and their applicable activities or relationships (Barley & Tolbert, 1997). Challenges arise when knowledge sharing is not as efficient as it should be due to many constraints. One of them is inadequate procedures and policies for knowledge sharing. Systematic sharing of knowledge cannot take place unless there are procedures, guidelines and policies for knowledge sharing (Riege 2005). Sharing of knowledge cannot be effective if suitable procedures and processes are not in place (Riege, 2005:28-32). The research used a mixed method approach and employed an interpretive case study methodology. A focus group was conducted from a qualitative stance, followed by a survey from a quantitative perspective with senior, medium and junior-level staff members working within the Development Information and Geographic Information Systems department of a selected municipality in the Western Cape, South Africa. The sample represents a hundred percent of the population being all sixty staff members for the DI & GIS department, from which seven were used for the focus group from the qualitative perspective and the remainder for the quantitative survey. For the qualitative side, content analysis was used to analyse data generated from the focus group, while a descriptive statistical analysis was employed to analyse the data gathered from the quantitative survey. The findings suggest that organisational structure, policies, processes, corporate governance and technology are major enablers for the institutionalisation of knowledge sharing in an organisation. Management support and organisational culture were also recognised as social factors for knowledge sharing institutionalisation. New strategies for reinforcing efforts to nurture and invigorate the institutionalisation of knowledge sharing within an organisation were generated and presented as a general framework.

Este estudo procura identificar, medir e avaliar as práticas dos empregadores do Brasil e do Canadá em relação à gestão do capital intelectual de seus desenvolvedores de software, comumente chamados de programadores. O trabalho condensa, através da revisão e análise dos principais autores do assunto, os pressupostos básicos da boa gestão do capital intelectual. Tais pressupostos foram determinados especificamente para os desenvolvedores de software, que são agentes nucleares na indústria da tecnologia da informação, tecnologia essa que é onipresente em todas as instituições modernas. A partir desses pressupostos básicos, foram definidos 13 Índices de Capital Intelectual, que possibilitaram a criação de um questionário eletrônico disponibilizado na internet, no qual profissionais do Brasil e do Canadá responderam após serem convidados através do disparo em massa de mensagens de e-mail, gerando assim os dados primários. Os 13 Índices de Capital Intelectual propostos são: Índice de Instrução, Índice de Treinamento, Índice do Sistema de Conhecimento Organizacional, Índice Ocupacional, Índice de Satisfação, Índice Motivacional, Índice Vocacional, Índice de Coleguismo, Índice do Poder de Decisão (empowerment), Índice de Contato Direto com Clientes, Índice de Rotatividade, Índice Hierárquico e Índice do Papel Contábil. Através de uma metodologia original proposta pelo autor, os resultados da pesquisa de campo, fartamente ilustrados com gráficos, mostraram que os respondentes do Canadá obtiveram melhor resultado em 7 índices, enquanto que os brasileiros superaram os canadenses nos demais 6 índices. / This study aims to identify, measure, and evaluate the practices of employers in Brazil and Canada in relation to the management of intellectual capital of its software developers, commonly called programmers. The study condenses, through the review and analysis of the principal authors of the subject, the basic assumptions of the good management of intellectual capital. These assumptions were determined specifically for software developers, who are nuclear agents in the information technology industry, the technology that is omnipresent in all modern institutions. From these basic assumptions, were defined 13 Intellectual Capital Indexes, which enabled the creation of an electronic questionnaire available on the Internet, in which professionals from Brazil and Canada responded after being invited through a mass e-mail sending, generating the primary data. The 13 Intellectual Capital Indexes proposed are: Education Index, Training Index, Organizational Knowledge System Index, Occupational Index, Satisfaction Index, Motivational Index, Vocational Index, Comradeship Index, Empowerment Index, Index of Direct Contact with Customers, Turnover Index, Hierarchical Index, and Accounting Role Index. Using an original methodology proposed by the author, the results of field research, fully illustrated with charts, showed that respondents in Canada obtained better results in 7 indexes, while the Brazilians beat the Canadians in the other 6 indexes.

M.A. (Psychology) / Despite well over two millennia of philosophical speculation and just under a century of objective, standardized measurement, students of intelligence are far from unanimous in their agreement on a formal definition of the concept. Biological, psychological and operational definitions have each been advanced' and criticized in their turn. The majority of definitions, particularly of the psychological variety, have been variously rejected as circular, question begging, over-inclusive or value-laden. Such definitions have included the capacity for learning; the capacity to act purposefully, think rationally and deal effectively with one's environment; the ability to perceive or educe relations; and the ability for abstract thinking, to mention but a few...

This research commenced by looking at what the knowledge economy is and what the driving forces are. In order to decide on how knowledge in this new economy can be managed, it was first necessary to define the concept of knowledge. The difference between tacit and explicit knowledge and the interaction between the two were discussed and at the end ways of managing this knowledge were investigated. In a discussion of the term knowledge management it was concluded that it can be regarded as the handling of tacit and explicit objects of knowledge through information systems, so that it enhances innovation and learning in the enterprise. However, when this knowledge is used for creating economic value, it becomes an item of capital and it is therefore necessary to determine what Intellectual Capital is. The history of Intellectual Capital was discussed and in defining Intellectual Capital seven different models for Intellectual Capital were studied. It was found that Intellectual Capital is subdivided into three major components, viz. Human Capital, Structural Capital and Customer Capital. Each of these components was then thoroughly described and discussed. The aim of the research was to study the explicit management and measurement models of Intellectual Capital that would improve understanding of the mechanisms by which value is created and extracted. The different approaches that can be followed in managing Intellectual Capital were investigated. It was concluded that the three major components cannot be seen as independent from each other and must therefore be managed as a whole. The management of the interaction between the three components can be seen as the management of the intellectual assets of an organisation and this consists of two phases, viz. value creation and value extraction. In order to determine how successful an organisation is in managing its Intellectual Capital this management needs to be measured. The vehicle for measuring performance is a model with a set of indicators in each of the three major components. It was found that measurement models can be divided into four major categories: • Market capitalisation methods • Return on assets methods • Direct intellectual capital methods, and • Scorecard methods. Twenty-seven different models were investigated in order to understand which indicators were necessary to measure Intellectual Capital in an organisation. In order to propose a new framework a study was firstly done on what a framework should look like and which elements should be included. Thereafter an investigation was done to determine which indicators should be included in such a framework. As it was found that such a framework is very organisation-specific, a brief overview of the RAU was given and according to the strategic objectives of the University as set out in the three-year rolling plan a set of indicators was decided upon. It was necessary that each of these indicators indicate whether the University had been successful in the key performance area through the management of its Intellectual Capital. The criteria and indicators identified were applied in the composition of a new model in an effort to find a suitable model for use at universities. The evaluation process turned up the scorecard models as the most suitable for applying in this instance. An attempt was therefore made to modify and adjust these types of models to answer all the requirements of the University. Meeting the requirement that indicators from all three major components must be present was possible. Efforts to adapt existing models in such a way that sub-components can also be measured were met successfully. This model was then tested at RAU and it was measured whether the management of Intellectual Capital contributed to reaching the University’s strategic goals. / Prof. A.S.A. Du Toit

In a globalized world where competition has risen, it has become more and more popular for companies to outsource non-core activities. The main reasons for doing so are due to cost reductions, improving organizational focus, better flexibility and improve product quality, delivery and service. As outsourcing is increasingly growing in popularity, the problems associated is more prominent. For some companies outsourcing is a bridge to all the related benefits, while for some companies it can be a nightmare. When the expectations aren't met, the focal firm will have to re-evaluate the decision. The decision to will therefore to renegotiate with the vendor, switch to another vendor or to backsource. Backsourcing is when activities which previously has been outsourced is brought back in-house. Previous research on backsourcing has focused on functions such as information technology and information system. Little attention has been given towards production and the risk involved. In order for the vendor to produce, knowledge need to be shared. This can be complicated for knowledge-intensive firms considering their value creating resource is knowledge which derives from their intellectual capital. As the know-how of the product is shared to the vendor, the research made is transferred. If the knowledge-intensive firm is dissatisfied with the entered outsourcing agreement, and wishes to end the agreement the know-how will still continue to be shared. Causing the focal firm to feel locked-in with the vendor. If they choose to backsource, the risks related to the shared knowledge appears. As the knowledge is already shared, the question if it can be prevented arises. Which leads to our research questions: RQ1: What are the risks related to intellectual capital when backsourcing? RQ2: How can these risks be prevented? To answer these questions, a case study from a knowledge-intensive firm who faces this problem is examined with our theoretical framework. The risk identified were opportunistic behaviour with the shared intellectual capital, reputational risk, risk with reintegrating intellectual capital, investment risk and risk from earlier contractual arrangement. To prevent these revealed to be difficult but not impossible. To summarize the preventing measure identified, they revolve around legal protection from well-written contracts and patents, careful execution plan, use of external expertise and by avoiding high investment through establishing a pilot plant.

La presente investigación analiza el capital intelectual (CI) como determinante de la rentabilidad financiera de los bancos. Para lo cual, se analizó 43 empresas del sector bancario de Perú, Chile y Colombia durante 2014 hasta 2018 en un panel de datos balanceados. La metodología utilizada tiene en cuenta la relación estática y dinámica, entre el CI y el rendimiento financiero. Para evaluar la relación estática se aplica regresiones de datos de panel como pooled OLS y efectos fijos (FE). Mientras que para evaluar la relación dinámica se aplica el modelo GMM para resolver problemas de endogeneidad. Los hallazgos obtenidos demuestran que un aumento en las inversiones de CI conduce a una mayor rentabilidad financiera de la empresa. Los componentes del CI (como el capital estructural y capital humano) también indican un impacto positivo con respecto a las medidas de rentabilidad, respaldando así la teoría de dependencia de recursos (RD) y del aprendizaje organizacional (OL). Dado que hay pocas investigaciones realizadas para países en desarrollo, la originalidad está en evaluar el impacto que se tiene en la rentabilidad financiera a través del CI, para economías emergentes como la de Perú, Chile y Colombia. / The present investigation analyses the intellectual capital (CI) as a determinant of the financial profitability of the banks. For which, 43 companies in the banking sector of Peru, Chile and Colombia were analysed during 2014 until 2018 in a balanced data panel. The methodology used takes into account the static and dynamic relationship between the IC and financial performance. To evaluate the static relationship, panel data regressions such as pooled OLS and fixed effects (FE) are applied. While to evaluate the dynamic relationship the GMM model is applied to solve endogeneity problems. The findings obtained show that an increase in CI investments leads to greater financial profitability of the company. The components of the IC (such as structural capital and human capital) also indicate a positive impact with respect to profitability measures, thus supporting the theory of resource dependence (RD) and organizational learning (OL). Since there is little research done for developing countries, the originality is to evaluate the impact on financial profitability through the IC, for emerging economies such as Peru, Chile and Colombia. / Trabajo de investigación

The pertinent investment in intangible assets is expected to lead to a firm's higher productivity and competitiveness. This study suggests that a restaurant firm should identify core intangible assets for its business, manage them systematically, and measure their value contribution. The essential thrust is to identify key intangible value resources and establish their measurement, which then helps measure the financial contribution of each intangible asset and make an investment decision on it. Thus, this study was purported to identify key organization-centric intangible value assets in the context of the casual dining restaurant industry, develop their measurement, and examine their contribution on a firm's market value. Findings will help improve understanding of what intangible assets are critical and apply the concept to a strategic and operational management. Based on an in-depth literature review covering a wide range of areas, the following six of the most widely agreed upon domains of organizational capital were identified: innovation capital, organizational process capital, organizational culture capital, organizational learning capital, information system capital, and intellectual property capital. This structure of the six most important domains of organizational capital was verified through subsequent interviews with five experts, the pilot test with ten experts, and three rounds of the Delphi survey. Seventeen sub-dimensions were identified through the literature review, interviews, the pilot test, and the Delphi study with professionals. This industry-specific categorical system helps a firm identify and manage various types of intangible resources more precisely and efficiently. Furthermore, it can enable restaurant management to clearly understand how to cope with different types of intangible resources and how to gather, create, use, share, and develop them more appropriately. The findings can be grouped into the following conclusions. Seventy measurement indicators were developed to measure a firm's organizational capitals. Unlike using subjective perceptual measurement scales, the measured values using the objective measurement scales are consistent regardless of time or people. Therefore, the financial value (or contribution) of each of the six organizational capitals can be estimated more precisely along with the data of firms' market value. / Ph. D.

Student Number: 9305986E School of Accountancy Faculty of Commerca, Law and Management / Academic and commercial interest in the corporate governance practices of publicly listed companies has increased significantly in the past five to ten years. High-profile corporate failures such as Enron and Worldcom have heightened the interest in corporate governance practices. This research study's primary aim is to explore the contribution of board structure to company performance in South Africa. The majority of prior corporate governance literature has centered and focused on the relationship between board structure and company performance where performance is measured in terms of traditional measures. This research study follows the themes of Mitchell Williams, which diverges from this prior body of literature in two primary ways; first the relationship between board structure and company performance is investigated where performance is defined by intellectual capital performance and second unlike the majority of prior literature that utilised data from the United States, data was collected and analysed from a sample of South African companies listed on the JSE Securities Exchange.

No description available.