Strategic capability development : a multi-level case study of the role of knowledge integration within product innovation

Capability development is at the heart of creating competitive advantage. This thesis intends to conceptualise Strategic Capability Development as a renewal of an organisation's existing capability in line with the requirements of the market. It followed and compared four product innovation projects within Iran Khodro Company (IKCO), an exemplar of capability development within the Iranian Auto industry. Findings show that the maturation of strategic capability at the organisational level has occurred through a sequence of product innovation projects and by dynamically shaping the learning and knowledge integration processes in accordance with emergence of the new structure within the industry. Accordingly, Strategic Capability Development is conceptualised in an interpretive model. Such findings are useful for development of an explanatory model and a practical capability development framework for managing learning and knowledge across different product innovation projects.

Life cycle modelling and design knowledge development in 3D virtual environments : final report

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This final report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

Life Cycle Modelling and Design Knowledge Development in 3D Virtual Environments

Experience plays an important role in building management. “How often will this asset need repair?” or “How much time is this repair going to take?” are types of questions that project and facility managers face daily in planning activities. Failure or success in developing good schedules, budgets and other project management tasks depend on the project manager's ability to obtain reliable information to be able to answer these types of questions. Young practitioners tend to rely on information that is based on regional averages and provided by publishing companies. This is in contrast to experienced project managers who tend to rely heavily on personal experience. Another aspect of building management is that many practitioners are seeking to improve available scheduling algorithms, estimating spreadsheets and other project management tools. Such “micro-scale” levels of research are important in providing the required tools for the project manager's tasks. However, even with such tools, low quality input information will produce inaccurate schedules and budgets as output. Thus, it is also important to have a broad approach to research at a more “macro-scale.” Recent trends show that the Architectural, Engineering, Construction (AEC) industry is experiencing explosive growth in its capabilities to generate and collect data. There is a great deal of valuable knowledge that can be obtained from the appropriate use of this data and therefore the need has arisen to analyse this increasing amount of available data. Data Mining can be applied as a powerful tool to extract relevant and useful information from this sea of data. Knowledge Discovery in Databases (KDD) and Data Mining (DM) are tools that allow identification of valid, useful, and previously unknown patterns so large amounts of project data may be analysed. These technologies combine techniques from machine learning, artificial intelligence, pattern recognition, statistics, databases, and visualization to automatically extract concepts, interrelationships, and patterns of interest from large databases. The project involves the development of a prototype tool to support facility managers, building owners and designers. This Industry focused report presents the AIMMTM prototype system and documents how and what data mining techniques can be applied, the results of their application and the benefits gained from the system. The AIMMTM system is capable of searching for useful patterns of knowledge and correlations within the existing building maintenance data to support decision making about future maintenance operations. The application of the AIMMTM prototype system on building models and their maintenance data (supplied by industry partners) utilises various data mining algorithms and the maintenance data is analysed using interactive visual tools. The application of the AIMMTM prototype system to help in improving maintenance management and building life cycle includes: (i) data preparation and cleaning, (ii) integrating meaningful domain attributes, (iii) performing extensive data mining experiments in which visual analysis (using stacked histograms), classification and clustering techniques, associative rule mining algorithm such as “Apriori” and (iv) filtering and refining data mining results, including the potential implications of these results for improving maintenance management. Maintenance data of a variety of asset types were selected for demonstration with the aim of discovering meaningful patterns to assist facility managers in strategic planning and provide a knowledge base to help shape future requirements and design briefing. Utilising the prototype system developed here, positive and interesting results regarding patterns and structures of data have been obtained.

A conceptual analysis of strategic capability development within product innovation projects

Strategic capability development refers to the renewal of the organisational capabilities which are sources of competitive advantage. The aim of this paper is to examine how strategic capability and competitive advantage build up over time. Recent literature points to the integration of dynamic capability and ambidexterity perspectives in explaining organisational capability development. Literature analysis reveals the role of knowledge integration and product innovation in integrating dynamic capability and ambidexterity. However, little attention has yet been paid to knowledge integration within innovation projects as a context for capability development. Accordingly, this paper aims to develop a conceptual framework for strategic capability development focusing on the role of knowledge integration within product innovation projects. This framework contributes to identifying and emphasising the role of micro processes in capability renewal which in turn enhances our understanding of strategic capability development.

Strategic options development and analysis: the case of the brazilian railways

Judging by their success in Europe, Asia and North America, passenger and cargo railways are appreciated as the key to infrastructural development in Brazil. The issues are complex and steeped in uncertainty, as well as political and economic agendas, and a wide array of intersecting issues such as business and unionized interests, agricultural and industrial geographical spreads, as well as the emergence of alternative power sources. Not only are the issues systemic, but railway development itself always comes as a physical network structure. The situation under consideration, in other words, is systemic from both the soft and hard systems point of view, thus promising a rich context for systems studies. As an initial attempt in understanding the situation at hand, the research reported here applied the problem structuring approach known as Strategic Options Development and Analysis (SODA) in order to map and analyze issues facing the Brazilian railways. Strategic options for the future development of the railways were identified and analyzed, and ways forward for future research are proposed. In addition, the report serves as an initial knowledge base that can guide future systemic planning studies in the industry.

Strategic knowledge serendipity and arbitrage & intellectual venture capitalists: An emerging breed of knowledge entrepreneurs; and Part II: Global and Local (GloCal) knowledge logistics for innovation and competitiveness. ACES Working Papers, August 2009

Strategic Knowledge: While entrepreneurship may occur as a natural result of personal drive, it occurs most often, most robustly and is most sustainable in an environment designed to encourage it. Potential entrepreneurs become active entrepreneurs when the conditions are most supportive of their commercial opportunities and their business thus helping channel the two key qualities they exhibit as individuals obsessed maniacs and clairvoyant oracles (Carayannis, GWU Lectures, 2000-2005) and (Carayannis et at, 2003a) towards the generation of sustainable wealth. So far, entrepreneurial scholars who turn into intellectual venture capitalists by founding knowledge-driven companies remain one of the least explored specie in the territory of entrepreneurship. GloCal: The increasing engagement of firms within global knowledge and production networks and their ability to source knowledge globally as well as locally (GloCally), for the development of innovation capacities will shape the future of UK's knowledge resources and its role in the global economy. Practices such as off-shoring R&D activities are widely adopted, creating challenging, and not very well understood, issues related to cross-country and inter-firm knowledge and technology flows. We seek to address the internationalisation and networking of research and innovation activities, including the roles and strategies of enterprises, universities, research centres, governments in a cross-country and inter-sectoral way, to assess the impact and the implications for sustaining and enhancing the competitiveness of UK firms and other British knowledge producers and users.

The BEE Undergraduate Model for Knowledge Development applied to the QUT Spatial Science Course : Diversity in Surveying Curriculum

This paper provides an overview of the current QUT Spatial Science undergraduate program based in Brisbane, Queensland, Australia. It discusses the development and implementation of a broad-based educational model for the faculty of built environment and engineering courses and specifically to the course structure of the new Bachelor of Urban Development (Spatial Science) study major. A brief historical background of surveying courses is discussed prior to the detailing of the three distinct and complementary learning themes of the new course structure with a graphical course matrix. Curriculum mapping of the spatial science major has been undertaken as the course approaches formal review in late 2010. Work-integrated learning opportunities have been embedded into the curriculum and a brief outline is presented. Some issues relevant to the tertiary surveying/ spatial sector are highlighted in the context of changing higher education environments in Australia.

Micro foundations of strategic capability development : a case study within the auto industry

The importance of firms’ adaptation processes is prominent in today’s business environment which is characterised by ever changing customers, technologies, and competition. Ever since Schumpeter’s (1942) classic work strategic renewal has been found crucial for firms’ adaptation to environmental change. The role of strategic renewal in firms’ adaptation processes includes development of capabilities for the purpose of sustainability of competitive advantage against environmental changes.

Environmental priorities in strategic product development

This paper reports some results from a major research project on the integration of environmental issues into design in the electrical and electronic industry. Product development practice and ecodesign methods were examined along with qualitative data from 19 manufacturers, using interviews and an action research methodology. A four-stage framework for ecodesign practice resulted: first, to make an environmental assessment from a life cycle viewpoint; then to communicate the analysis and collect feedback; thirdly to prioritize the environmental issues and finally to complete the design using relevant tools and methods. This 'ARPI' framework (analyse, report, prioritize, improve) applies to both strategic and operational levels. Initial testing of the framework in collaborating companies highlighted difficulties with communication with design teams; the role of 'ecodesign champions' is explained. Other challenges are the development of customized tools and the training of designers. The study concludes that the prioritization step is critical, as it simplifies and clarifies the tasks in design that take place after formulation of the specification. Copyright (C) 2000 John Wiley and Sons, Ltd. and ERP Environment.

Evaluation of strategic knowledge of students through authentic tasks of writingin science classroom

The difficulties at evaluating strategic knowledge have been connected to the use of deconxetualized tests that, at the end, do not involve the use of this knowledge. For this reason, an interest in developing authentic writing tasks that offer advantages for these kinds of evaluation have arisen. Throughout this research, authentic writing tasks were developed in a natural sciences class, with the purpose of evaluating the students' strategic knowledge. Different instruments were used to collect data, e.g. Interviews, questionnaires, a self-inform, as well as three samples of writing by the students, with the objective of analyzing the changes that occurred between one and the others, as well as to determine the decisions that students made in order to complete the assigned tasks successfully. An authentic writing task gives great opportunities to evaluate strategic knowledge. These tasks lead students to arrange their knowledge about the topic in hand, organize and adapt it to fit the objectives and the audience, also, it allows them to control and adjust their decisions on the task. This last stage became the perfect opportunity to take notes on the knowledge and regulation of cognitive processes that the students brought into play, as well as to evaluating their understanding of writing and the demands given on the different discursive genres. As a result, the students showed different degrees of strategic knowledge in the task. The students who showed a better strategic knowledge trust in their structural abilities know about discursive genres and have a good performance in basic linguistic abilities. The students who showed weak strategic knowledge distrust their writing skills, seem extremely worried about organizing the content of their texts, fail when checking their writings, and overlook or are unaware of the basic requirements of the discursive genre they are asked to exemplify. It appears that the previous knowledge and experiences at writing the students have been exposed to may affect the strategic knowledge shown when writing in this subject.