Alfa is one of the world’s leading IT advisory companies, with research and consulting abilities. Alfa Nordics is a successful part of Alfa focused on consulting in Sweden, Norway and Denmark. Alfa Nordics will double their number of employees by the end of 2010 and we were asked to investigate how Alfa Nordics should enable this growth while keep being successful in having high profits, a strong brand, motivated employees and satisfied clients. By using theories about KBOs (Knowledge-Based Organizations) and conducting interviews with employees at Alfa Nordics we identified what makes Alfa Nordics successful today and what they should do to keep these success factors when growing. To keep their success within the organization Alfa should keep the execution teams small, recruit a resource manager and improve the knowledge exchange between the countries. To keep making successful engagements they should keep defining the problem in the best way for the client, ensuring sales and keep having the right employees. To keep their success in employing top consultants they should be visible in talented people environments, show that they are growing, develop a more thorough recruiting plan.

An Extension to the Composite Rule Induction System Discovering knowledge from data is an important task for knowledge management and development of intelligent systems, which is called knowledge acquisition or data mining. Many techniques have been developed for such purpose. For example, ID3, C4.5 (tree induction techniques) and Artificial Neural Networks are among the popular techniques in ¡§Classification and Prediction¡¨ area. However, these methods often use the same criteria to analyze nominal and non-nominal attributes, which is very likely to produce biased knowledge due to mis-match between data type and their algorithms. In Liang (1992), he proposed a composite approach called CRIS to inducing knowledge that introduces statistical concepts and data mining heuristics and found the composite method outperformed other methods including tree induction, discriminant analysis, and neural networks. However, the paper focuses on the classification of binary objects and did not describe how the approach can be applied to a problem with more than two classes in the dependent variable. In this research, we extend the previous approach to solve the problem with more than two classes. We also enhance the approach by adding steps to prioritizing attributes using their identification power and controlling the growth of generated hypothesis. In order evaluate the extended CRIS method, a prototype system, eCRIS, was developed and compared with a commercial data mining package, XLMiner3 (developed by Cytel Software Corporation) using three existing datasets in data mining research. The results indicate that the extended CRIS outperforms tree induction and backpropagation in neural networks in datasets that include both nominal and non-nominal data and performed equally well with them.

Abstract This text, referred to the manpower survey data in 1991 & 2003 obtained from the Accounting & Statistics Department, is aimed at making a study of the trend on the switch of occupation before and after the rise of the Knowledge-based Economy Age. The employees, having experiences of switch, are chosen from the data of the Accounting & Statistic Department for ongoing intersecting analysis of before and after their switch. This research has found that the turnover of occupation/profession, within the time before development of the knowledge-based economy Age of 1991, has been prone to the mass-labor industries, such as traditional manufacture, construction and etc. Amid those labor mobility, industries which having failing net turnover rate of 2003, include the ones of ¡§Professional, Scientific and Technical services¡¨ and ¡§Cultural, Sporting and Recreational Services.¡¨ It shows that Taiwan is appropriate to a new market with reconstructed labor and reacts clearly in that the supply of employees were not quick enough to catch reshuffled employment market. Possessing the first and second place among those industries are that ¡§Technicians and related¡¨ and ¡§Machine Operators & Fabricator¡¨ that are failing on the net turnover rate, are well in parallel with two industries of ¡§Construction¡¨ & ¡§Real Estate and Rental and Leasing ¡§ that are keeping minus on the net turnover rate. Furthermore, it shows that the traditional mass-labor industries have entailed labor to flow outward massively. The labor released from swift labor restructure is the major reason what causing the massive number of unemployment in the labor market. In the past twelve years, the structure of occupation of Taiwan¡¦s employees is changed from mass-labor to mass-technique, and developed toward the service-industry steadily. The dominant phenomenon existing together in current labor market are that both unemployment and insufficiency of labor.

Due to the complicated nature of medical information needs, the time constraints of clinicians, and the linguistic complexities and sheer volume of medical information, most medical questions go unanswered. It has been shown that nearly all of these questions can be answered with the presently available medical sources and that when these questions get answered, patient health benefits. In this work, we design and describe a framework for Evidence-Based medical information research and delivery, MedicInfoSys. This system leverages the strengths of knowledge-based workers and of mature knowledge-based technologies within the medical domain. The most critical element of this framework, is a search interface, PifMed. PifMed uses gold-standard MeSH categorization (presently integrated into medline) as the basis of a navigational structure, which allows users to browse search results with an interactive tree of categories. Evaluation by user study shows it to be superior to PubMed, in terms of speed and usability.

This thesis explores some possible approaches to better integration of archives with communities and engagement of archives with local community development initiatives. The study suggests that innovative usage of archival material can facilitate community engagement in the knowledge-based economy and support a broad range of community economic development initiatives. Archival public programming and the need for archivists to actively engage with existing and potential users is included in the discussion. Brandon, Manitoba is used as an example of a community that could benefit from the establishment of community archives.

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Supply Chain Management (SCM) is becoming increasingly important in the modern business world. In order to effectively manage and integrate a supply chain (SC), a deep understanding of overall SC operation dynamics is needed. This involves understanding how the decisions, actions and interactions between SC members affect each other, and how these relate to SC performance and SC disruptions. Achieving such an understanding is not an easy task, given the complex and dynamic nature of supply chains. Existing simulation approaches do not provide an explanation of simulation results, while related work on SC disruption analysis studies SC disruptions separately from SC operation and performance. This thesis presents a logic-based approach for modelling, simulating and explaining SC operation that fills these gaps. SC members are modelled as logicbased intelligent agents consisting of a reasoning layer, represented through business rules, a process layer, represented through business processes and a communication layer, represented through communicative actions. The SC operation model is declaratively formalised, and a rule-based specification is provided for the execution semantics of the formal model, thus driving the simulation of SC operation. The choice of a logic-based approach enables the automated generation of explanations about simulated behaviours. SC disruptions are included in the SC operation model, and a causal model is defined, capturing relationships between different types of SC disruptions and low SC performance. This way, explanations can be generated on causal relationships between occurred SC disruptions and low SC performance. This approach was analytically and empirically evaluated with the participation of SCM and business experts. The results indicate the following: Firstly, the approach is useful, as it allows for higher efficiency, correctness and certainty about explanations of SC operation compared to the case of no automated explanation support. Secondly, it improves the understanding of the domain for non-SCM experts with respect to their correctness and efficiency; the correctness improvement is significantly higher compared to the case of no prior explanation system use, without loss of efficiency. Thirdly, the logic-based approach allows for maintainability and reusability with respect to the specification of SC operation input models, the developed simulation system and the developed explanation system.

This thesis explores some possible approaches to better integration of archives with communities and engagement of archives with local community development initiatives. The study suggests that innovative usage of archival material can facilitate community engagement in the knowledge-based economy and support a broad range of community economic development initiatives. Archival public programming and the need for archivists to actively engage with existing and potential users is included in the discussion. Brandon, Manitoba is used as an example of a community that could benefit from the establishment of community archives.

This research has shown that a knowledge-based system is an effective tool to help novice simulation users interpret and understand simulation output. The thesis describes the development and empirical evaluation of the prototype. A simulation program which adopts the discrete-event simulation approach simulates the behaviour of a local area network protocol, i.e., the Ethernet, with different sets of parameter values. The knowledge-based system carries out the 'analysis' of the simulation output covering the protocol efficiency and throughput. The knowledge-based system summarises the simulation output and upon request from the user, provides explanations to a conclusion arrived at. The summary is the relationship between any pair of variables; and the explanation is the justification as to how the pair are related. The strategy for building the knowledge base using production rules is also elaborated. There are different functions performed by the different sets of rules (or rule-sets). Their major functions, In parallel with the development objective, are interpreting numerical data, presenting output to users and providing explanations interactively. The rules are grouped accordingly to make the knowledge bases easier to maintain. In the explanation aspect, the few approaches attempted by other researchers to improve expert system explanation is discussed. It is argued that a mere regurgitation of 'fired' rules to explain the Ethernet behaviour is not adequate in this case. To circumvent this problem, a 'constructive' approach to explanation is employed. The explanation procedure rewrites the 'fired' rules in a more understandable form than the if-then rules. Unnecessary parts of the rules are ommitted to make the explanations clearer. Finally, an experiment carried out to evaluate the effectiveness of the prototype is described in detail. The effectiveness is measured from a few different perspectives. These are test scores, completion time for the test and the users' degree of confidence, both in the interpretation and explanation tasks. The results show that although some responses are mixed, there is evidence to suggest that the knowledge-based simulation system environment is beneficial to the target users.

We introduce a new methodological framework, called Bewextra, for the creation of the knowledge of needs in organizations. The development of our framework builds on theoretical engagement with literature from several disciplines including visioning and philosophy of needs as well as empirical data from vision development processes we have accompanied. To the best of our knowledge it is the first theoretical work that describes learning from an envisioned future and the generation of need knowledge as an abductive process in a methodologically replicable way. The advantages and practical implications of our method introduced are discussed in detail.