Prognosis of after spot volumes at the Scandinavian electricity market

The Thesis is dedicated to development of an operative tool to support decision making in after spot trading on the Nordic electricity market. The basics of the Nordic electricity market, trading mechanisms on the spot and after spot markets are presented in the Thesis. Mathematical equations that describe electricity balance condition in the power system are offered. The main driving factors that impact deviation of actual electricity balance from the scheduled one (object) in the power system have been explored and mathematically defined. The behavioral model of the object and principal trends in change of state of the object under an impact of the driving factors are determined with the help of regression analysis made in Microsoft Office Excel. The behavioral model gives an indication for the total regulation volume (Elbas trades volume, volume of regulation market, balance power) for a certain hour that serves as the base input in estimating prices on the after spot markets. Proposals for development of methodologies of forecasting the after spot electricity prices are offered.

The Effects of Service Quality, Customer Satisfaction and Customer Perceived Value on Behavioral Intentions

The intent of this research was to develop a model that describes the extent to which customer behavioral intentions are influenced by service quality, customer satisfaction and customer perceived value in the business-to-business service context. Research on customer behavioral intentions is quite fragmented and no generalized model has been presented. Thus, there was need for empirical testing. This study builds on the services marketing theory and assesses the relationships between the identified constructs. The data for the empirical analysis was collected via a quantitative online survey and a total of 226 usable responses were obtained for further analysis. The model was tested in an employment agency service setting. The measures used in this survey were first assessed by using confirmatory factor analysis (CFA) after which the hypothesized relationships were further verified using structural equation modeling (SEM) in LISREL 8.80. The analysis identified that customer satisfaction played a pivotal role in the model as it was the only direct antecedent of customer behavioral intentions, however, customer perceived value showed a strong indirect impact on buying intentions via customer satisfaction. In contrast to what was hypothesized, service quality and customer perceived value did not have a direct positive effect on behavioral intentions. Also, a contradicting finding with current literature was that sacrifice was argued to have a direct but positive impact on customer perceived value. Based on the findings in this study, managers should carefully think of their service strategies that lead to their customers’ favorable behavioral intentions.

Brand attitudes influence on city brand image, and their impact on behavioral intention

The main objective of this Master’s Thesis was to examine the perceived city brand image of tourists and residents. It was aimed to accomplish by examining first the contribution of city attributes and marketing communications on forming brand attitudes, and then discover how the brand attitudes influence on city brand image. The impact of brand attitudes and city brand image on behavioral intention was also reviewed. The empirical part of the thesis was conducted with a quantitative method through online-based survey. The sample (n = 492) consisted of tourists and residents of the case city. The data was analyzed with statistical analyses by SPSS program. Brand attitudes, based on the main attributes, were calculated through multi-attribute attitude model. The results confirmed exposure to marketing communications has direct and positive influence on brand attitudes, especially the offline marketing communications. The findings revealed brand attitudes impact directly on city brand image perception. Brand attitudes and brand image dimensions had direct impact on tourists and residents’ behavioral intention. The findings provide important information for the city marketers. They increase marketers understanding on how target population perceives the city brand image and how it impacts on their future behavior. This thesis reveals the perception of current city brand image and gives guidance on what to emphasize in city branding to increase city’s attractiveness in conjunction with its economic development. Furthermore, the created framework can be utilized also in the future researches.

Visual analytics for behavioral and niche market segmentation

Companies require information in order to gain an improved understanding of their customers. Data concerning customers, their interests and behavior are collected through different loyalty programs. The amount of data stored in company data bases has increased exponentially over the years and become difficult to handle. This research area is the subject of much current interest, not only in academia but also in practice, as is shown by several magazines and blogs that are covering topics on how to get to know your customers, Big Data, information visualization, and data warehousing. In this Ph.D. thesis, the Self-Organizing Map and two extensions of it – the Weighted Self-Organizing Map (WSOM) and the Self-Organizing Time Map (SOTM) – are used as data mining methods for extracting information from large amounts of customer data. The thesis focuses on how data mining methods can be used to model and analyze customer data in order to gain an overview of the customer base, as well as, for analyzing niche-markets. The thesis uses real world customer data to create models for customer profiling. Evaluation of the built models is performed by CRM experts from the retailing industry. The experts considered the information gained with help of the models to be valuable and useful for decision making and for making strategic planning for the future.

Model-based testing of software systems : functionality and performance

Software is a key component in many of our devices and products that we use every day. Most customers demand not only that their devices should function as expected but also that the software should be of high quality, reliable, fault tolerant, efficient, etc. In short, it is not enough that a calculator gives the correct result of a calculation, we want the result instantly, in the right form, with minimal use of battery, etc. One of the key aspects for succeeding in today's industry is delivering high quality. In most software development projects, high-quality software is achieved by rigorous testing and good quality assurance practices. However, today, customers are asking for these high quality software products at an ever-increasing pace. This leaves the companies with less time for development. Software testing is an expensive activity, because it requires much manual work. Testing, debugging, and verification are estimated to consume 50 to 75 per cent of the total development cost of complex software projects. Further, the most expensive software defects are those which have to be fixed after the product is released. One of the main challenges in software development is reducing the associated cost and time of software testing without sacrificing the quality of the developed software. It is often not enough to only demonstrate that a piece of software is functioning correctly. Usually, many other aspects of the software, such as performance, security, scalability, usability, etc., need also to be verified. Testing these aspects of the software is traditionally referred to as nonfunctional testing. One of the major challenges with non-functional testing is that it is usually carried out at the end of the software development process when most of the functionality is implemented. This is due to the fact that non-functional aspects, such as performance or security, apply to the software as a whole. In this thesis, we study the use of model-based testing. We present approaches to automatically generate tests from behavioral models for solving some of these challenges. We show that model-based testing is not only applicable to functional testing but also to non-functional testing. In its simplest form, performance testing is performed by executing multiple test sequences at once while observing the software in terms of responsiveness and stability, rather than the output. The main contribution of the thesis is a coherent model-based testing approach for testing functional and performance related issues in software systems. We show how we go from system models, expressed in the Unified Modeling Language, to test cases and back to models again. The system requirements are traced throughout the entire testing process. Requirements traceability facilitates finding faults in the design and implementation of the software. In the research field of model-based testing, many new proposed approaches suffer from poor or the lack of tool support. Therefore, the second contribution of this thesis is proper tool support for the proposed approach that is integrated with leading industry tools. We o er independent tools, tools that are integrated with other industry leading tools, and complete tool-chains when necessary. Many model-based testing approaches proposed by the research community suffer from poor empirical validation in an industrial context. In order to demonstrate the applicability of our proposed approach, we apply our research to several systems, including industrial ones.