Reforming technology company incentive programs for achieving knowledge-based economic development:a Brazil-Australia comparative study

This doctoral thesis aims to demonstrate the importance of incentives to technology-based firms as a strategy to promote knowledge-based economic development (KBED). To remain competitive, technology-based firms must innovate and seek new markets; therefore, this study aims to propose an incentive model to technology-based firms as a strategy to promote knowledge-based urban development, according to framework described by Yigitcanlar (2011). This is an exploratory and descriptive research with a qualitative approach. Surveys were carried out with national trade associations that represented technology-based firms both in Brazil and Australia. After analysing the surveys, structured interviews were conducted with government representatives, trade associations and businessmen who had used financial support by the federal government. When comparing both countries, the study found the importance of direct incentives through tax incentives, for it is a less bureaucratic, quicker and more direct process for firms. We suggest to include the terms incentives in the framework of knowledge-based urban development, as one of the pillars that contribute to knowledge-based economic development.

Hybrid learning scheme for data mining applications

Classification of large datasets is a challenging task in Data Mining. In the current work, we propose a novel method that compresses the data and classifies the test data directly in its compressed form. The work forms a hybrid learning approach integrating the activities of data abstraction, frequent item generation, compression, classification and use of rough sets.

Hybrid learning scheme for data mining applications

Classification of large datasets is a challenging task in Data Mining. In the current work, we propose a novel method that compresses the data and classifies the test data directly in its compressed form. The work forms a hybrid learning approach integrating the activities of data abstraction, frequent item generation, compression, classification and use of rough sets.

Data mining approaches to software fault diagnosis

Automatic identification of software faults has enormous practical significance. This requires characterizing program execution behavior and the use of appropriate data mining techniques on the chosen representation. In this paper, we use the sequence of system calls to characterize program execution. The data mining tasks addressed are learning to map system call streams to fault labels and automatic identification of fault causes. Spectrum kernels and SVM are used for the former while latent semantic analysis is used for the latter The techniques are demonstrated for the intrusion dataset containing system call traces. The results show that kernel techniques are as accurate as the best available results but are faster by orders of magnitude. We also show that latent semantic indexing is capable of revealing fault-specific features.

Shareholder/Stakeholder Value Management, Company Growth and

There has been considerable discussion in the literature about the relative merits of shareholder value management and stakeholder value management, but relatively little empirical research has been reported concerning the relationship between these types of management and financial performance. The present study puts forward a hypothesis that true shareholder value management also encompasses stakeholder value management. This combination of shareholder/stakeholder value management is hypothesised to be associated with superior financial performance and sales growth. Using a sample of chief financial officers' ratings of the contemporary management accounting techniques economic value added and the balanced scorecard to represent the two management types, the study found evidence in support of the hypothesis.

Strategic Priorities, Company Performance and Attitudes Towards Management Accounting Techniques: an Empirical Study

The study investigates whether there is an association between different combinations of emphasis on generic strategies (product differentiation and cost efficiency) and perceived usefulness of management accounting techniques. Previous research has found that cost leadership is associated with traditional accounting techniques and product differentiation with a variety of modern management accounting approaches. The present study focuses on the possible existence of a strategy that mixes these generic strategies. The empirical results suggest that (a) there is no difference in the attitudes towards the usefulness of traditional management accounting techniques between companies that adhere either to a single strategy or a mixed strategy; (b) there is no difference in the attitudes towards modern and traditional techniques between companies that adhere to a single strategy, whether this is product differentiation or cost efficiency, and c) companies that favour a mixed strategy seem to have a more positive attitude towards modern techniques than companies adhering to a single strategy