Knowledge Warehouse: An Architectural Integration of Knowledge Management, Decision Support, Artificial Intelligence and Data Warehousing

Decision support systems (DSS) are becoming increasingly more critical to the daily operation of organizations. Data warehousing, an integral part of this, provides an infrastructure that enables businesses to extract, cleanse, and store vast amounts of data. The basic purpose of a data warehouse is to empower the knowledge workers with information that allows them to make decisions based on a solid foundation of fact. However, only a fraction of the needed information exists on computers; the vast majority of a firm’s intellectual assets exist as knowledge in the minds of its employees. What is needed is a new generation of knowledge-enabled systems that provides the infrastructure needed to capture, cleanse, store, organize, leverage, and disseminate not only data and information but also the knowledge of the firm. The purpose of this paper is to propose, as an extension to the data warehouse model, a knowledge warehouse (KW) architecture that will not only facilitate the capturing and coding of knowledge but also enhance the retrieval and sharing of knowledge across the organization. The knowledge warehouse proposed here suggests a different direction for DSS in the next decade. This new direction is based on an expanded purpose of DSS. That is, the purpose of DSS in knowledge improvement. This expanded purpose of DSS also suggests that the effectiveness of a DS will, in the future, be measured based on how well it promotes and enhances knowledge, how well it improves the mental model(s) and understanding of the decision maker(s) and thereby how well it improves his/her decision making

Internationalization strategies to India in three Finnish ICT SMEs

The size of the Indian market and its proximity to Finland does not have a positive correlation with the actual volume of business operations between the two countries. The ICT industry is a major sector where Finland’s strong expertise is valuable, but only sparingly do companies internationalize to serve the Indian market. The purpose of the study is to evaluate how cultural and business aspects of India affect the development of Finnish ICT SMEs’ operations in the market. To investigate these relationships the Indian culture is researched from a Finnish perspective and data is collected from three ICT SME case studies. In addition, the internationalization process of these SMEs is also evaluated theoretically and empirically. The combination of the analysis of cultural aspects and internationalization strategies allows drawing conclusions to the development of the operations in the three case studies and offer managers of ICT SMEs with more insight on the internationalization strategies to India. The observations are drawn from experienced international managers with responsibilities to operate the Indian operations of these ICT SMEs. The common factors and differentiations within the case studies are evaluated to give perspective into the challenges, opportunities, successes and failures that are experienced in the internationalization process. The findings include positive perceptions on the opportunities, ease of doing business and cultural fit with the Indian market for Finnish ICT SMEs. On the other hand, there are notable downsides to acknowledge for companies considering the Indian market in their internationalization strategy. In addition, this thesis illustrates the position of the Indian market entry within the global strategies of the case studies. Lastly, observations are made into the state of Indian and Finnish relationships for the future, which are commonly expected to be distinguishable.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Generalizing abstractions in form-based visual programming languages : from direct manipulation to static representation

We believe concreteness, direct manipulation and responsiveness in a visual programming language increase its usefulness. However, these characteristics present a challenge in generalizing programs for reuse, especially when concrete examples are used as one way of achieving concreteness. In this thesis, we present a technique to solve this problem by deriving generality automatically through the analysis of logical relationships among concrete program entities from the perspective of a particular computational goal. Use of this technique allows a fully general form-based program with reusable abstractions to be derived from one that was specified in terms of concrete examples and direct manipulation. Also addressed in this thesis is how to statically represent the generalized programs. In general, we address how to design better static representations. A weakness of many interactive visual programming languages is their static representations. Lack of an adequate static representation places a heavy cognitive burden on a VPL's programmers, because they must remember potentially long dynamic sequences of screen displays in order to understand a previously-written program. However, although this problem is widely acknowledged, research on how to design better static representations for interactive VPLs is still in its infancy. Building upon the cognitive dimensions developed for programming languages by cognitive psychologists Green and others, we have developed a set of concrete benchmarks for VPL designers to use when designing new static representations. These benchmarks provide design-time information that can be used to improve a VPL's static representation

A Framework to Simplify the Choice of Alternative Analysis and Selection Methods

This dissertation contributes a framework for analysts and engineering managers to investigate and choose alternative analysis and selection methods based upon their problem and its context. It began as an investigation into the alternative analysis and selection methods used in military planning. The existing military methods were inconsistent, violated the decision science body of knowledge, and provided no guidance to the practitioner on matching methods to problems. These challenges made it necessary to conduct this investigation. This research used a three-phase mixed methods approach. The first phase applied the general inductive method to the decision making body of knowledge to elicit an evaluation theme. The second phase used content analysis to identify evaluation criteria and satisficing to choose an evaluation framework structure. The completed framework is applied to the case of U.S. Army planning in phase three as a validation case study. This investigation\u27s results suggest that the proposed evaluation framework methodology is valid based upon the member checks and expert feedback on the case study. The research also contributes an expert-tested scalable collaborative online tool for alternative analysis and selection method research and selection. Finally, this dissertation recommends improvements for decision making in U.S. Army planning that have been validated by military planning and operations research experts