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.

The construction industry is inherently multidisciplinary and has adopted many intellectual and technical business improvements from other industries in an effort to optimize productivity. In construction, management inactivity is the root cause of 30% of non-productive time. This has created an opportunity and need for standardized and structured repeatable procedures for new managerial strategies. A theoretical framework for Organizational Intelligence (OI), which encompasses the procedural ability of an organization to efficiently process, support, measure and reason through management issues, is proposed. The elements of organizational intelligence are divided into three types of intellectual capital: Human Capital, Organizational Capital, and Relational Capital. The performance of an organizational activity depends on the quality of these capitals that are available within an organization. An organization's Human Capital (HC) is the human resources within the organization that can be deployed to acquire and apply its knowledge to perform, respond, or control designated work with available organizational assets. Organizational Capital (OC) refers to the assets available to the organization to support the performance of organizational activities Relational Capital (RC), which combines human capital and organizational capital to perform, is needed specific organizational activities. In addition, the research uses human cognitive abilities as the basis of a fundamental structure from which to form new organizational cognitive abilities that are capable of presenting management processes as critical value creations. Organizational cognitive ability is suggested to define appropriate organizational resources in order to integrate and determine a rational selection of applicable technologies and improvements. This ability can develop knowledge with interconnected variables, namely intellectual capital, managerial process, and performance, all of which support organizational intelligence. From the theoretical framework for OI, a prototype (Intelligibility Learning Model), which determines the role of relationships in an organization's operation and use of resources, is formulated. A case based research then applies the prototype to a managerial process in the construction industry. The case research demonstrates that the Intelligibility Learning Model (ILM) could be use effectively by industry decision makers to improve performance of organizational activities. The identification and application of a theoretical framework constitutes the foundation of a new managerial theory, Organizational Intelligence Management. It thus provides a fundamental foundation that explains how the construction processes, knowledge, skills, and resources used for managerial activities function. This theory contributes and establishes a better understanding of management, from organizational resources through to final production. / Ph. D.

No

Yes / This paper, using data from 100 UK listed firms, investigates the relationship between audit committee characteristics and intellectual capital (IC) disclosure. We find that overall IC disclosure is positively associated with audit committee characteristics such as the size and frequency of meetings, and negatively associated with audit committee directors’ shareholding. We find no significant relationship between IC disclosure and audit committee independence and financial expertise. We also observe that the association between audit committee characteristics and IC disclosure varies with the IC components (i.e. human capital, structural capital and relational capital), suggesting that the underlying factors that drive various components of IC disclosure are different. These results have important implications for policy-makers in that they confirm that the effectiveness of audit committees in the corporate reporting processes is a function of certain characteristics.

Yes / In this paper, we investigate whether intellectual capital (IC) and financial disclosures jointly affect the firm’s cost of equity capital. In contrast to prior research, we disaggregate disclosures into IC and financial disclosures and examine whether the two disclosure types are jointly related to the cost of equity capital. We also investigate whether IC and financial disclosures have an interaction effect on the cost of equity capital. Using data for a sample of 125 UK firms, we find a negative relationship between the cost of equity capital and IC disclosure. We find that the relationship between financial disclosure and the cost of equity capital is magnified when combined with IC disclosure. Additionally, we find that IC and financial disclosures interact in shaping their effects on the cost of equity capital. Further analyses suggest that the effect of financial disclosure on the cost of equity capital is augmented for firms characterised by a medium level of IC disclosure. These results provide important insights into the relationship between disclosures and cost of equity capital and have policy and practical implications.