Internationalization of IT company: Case study of a Finnish MOOC platform

The interest to small and media size enterprises’ (SMEs) internationalization process is increasing with a growth of SMEs’ contribution to GDP. Internet gives an opportunity to provide variety of services online and reach market niche worldwide. The overlapping of SMEs’ internationalization and online services is the main issue of the research. The most SMEs internationalize according to intuitive decisions of CEO of the company and lose limited resources to worthless attempts. The purpose of this research is to define effective approaches to online service internationalization and selection of the first international market. The research represents single holistic case study of local massive open online courses (MOOCs) platform going global. It considers internationalization costs and internationalization theories applicable to online services. The research includes preliminary screening of the markets and in-depth analysis based on macro parameters of the market and specific characteristics of the customers and expert evaluation of the results. The specific issues as GILT (Globalization, Internationalization, Localization and Translation) approach and Internet-enabled internationalization are considered. The research results include recommendations on international market selection methodology for online services and for effective internationalization strategy development.

Online MBPeT dashboard : enabling performance testing as a service in the cloud

In this thesis, tool support is addressed for the combined disciplines of Model-based testing and performance testing. Model-based testing (MBT) utilizes abstract behavioral models to automate test generation, thus decreasing time and cost of test creation. MBT is a functional testing technique, thereby focusing on output, behavior, and functionality. Performance testing, however, is non-functional and is concerned with responsiveness and stability under various load conditions. MBPeT (Model-Based Performance evaluation Tool) is one such tool which utilizes probabilistic models, representing dynamic real-world user behavior patterns, to generate synthetic workload against a System Under Test and in turn carry out performance analysis based on key performance indicators (KPI). Developed at Åbo Akademi University, the MBPeT tool is currently comprised of a downloadable command-line based tool as well as a graphical user interface. The goal of this thesis project is two-fold: 1) to extend the existing MBPeT tool by deploying it as a web-based application, thereby removing the requirement of local installation, and 2) to design a user interface for this web application which will add new user interaction paradigms to the existing feature set of the tool. All phases of the MBPeT process will be realized via this single web deployment location including probabilistic model creation, test configurations, test session execution against a SUT with real-time monitoring of user configurable metric, and final test report generation and display. This web application (MBPeT Dashboard) is implemented with the Java programming language on top of the Vaadin framework for rich internet application development. The Vaadin framework handles the complicated web communications processes and front-end technologies, freeing developers to implement the business logic as well as the user interface in pure Java. A number of experiments are run in a case study environment to validate the functionality of the newly developed Dashboard application as well as the scalability of the solution implemented in handling multiple concurrent users. The results support a successful solution with regards to the functional and performance criteria defined, while improvements and optimizations are suggested to increase both of these factors.

Exploring the feasibility of applying data mining for library reference service improvement : a case study of Turku Main Library

Data mining, as a heatedly discussed term, has been studied in various fields. Its possibilities in refining the decision-making process, realizing potential patterns and creating valuable knowledge have won attention of scholars and practitioners. However, there are less studies intending to combine data mining and libraries where data generation occurs all the time. Therefore, this thesis plans to fill such a gap. Meanwhile, potential opportunities created by data mining are explored to enhance one of the most important elements of libraries: reference service. In order to thoroughly demonstrate the feasibility and applicability of data mining, literature is reviewed to establish a critical understanding of data mining in libraries and attain the current status of library reference service. The result of the literature review indicates that free online data resources other than data generated on social media are rarely considered to be applied in current library data mining mandates. Therefore, the result of the literature review motivates the presented study to utilize online free resources. Furthermore, the natural match between data mining and libraries is established. The natural match is explained by emphasizing the data richness reality and considering data mining as one kind of knowledge, an easy choice for libraries, and a wise method to overcome reference service challenges. The natural match, especially the aspect that data mining could be helpful for library reference service, lays the main theoretical foundation for the empirical work in this study. Turku Main Library was selected as the case to answer the research question: whether data mining is feasible and applicable for reference service improvement. In this case, the daily visit from 2009 to 2015 in Turku Main Library is considered as the resource for data mining. In addition, corresponding weather conditions are collected from Weather Underground, which is totally free online. Before officially being analyzed, the collected dataset is cleansed and preprocessed in order to ensure the quality of data mining. Multiple regression analysis is employed to mine the final dataset. Hourly visits are the independent variable and weather conditions, Discomfort Index and seven days in a week are dependent variables. In the end, four models in different seasons are established to predict visiting situations in each season. Patterns are realized in different seasons and implications are created based on the discovered patterns. In addition, library-climate points are generated by a clustering method, which simplifies the process for librarians using weather data to forecast library visiting situation. Then the data mining result is interpreted from the perspective of improving reference service. After this data mining work, the result of the case study is presented to librarians so as to collect professional opinions regarding the possibility of employing data mining to improve reference services. In the end, positive opinions are collected, which implies that it is feasible to utilizing data mining as a tool to enhance library reference service.

Key factors affecting purchase intention in Russian online context

Russian e-commerce has drawn a lot of attention in academic publications as well as in public media lately. The market is growing with a speed of rocket offering companies enormous business opportunities. However, combination of Russian culture, consumer online purchasing and decision-making process forms a subject yet completely unknown. From international online business perspective it is vital for companies to know how a culture affects consumer’s purchase decision and what are the key elements that need to be modified in order to successfully expand online operations to Russian market. Here, the main purpose is to define the key factors affecting Russian consumer’s online purchase intention. In order to answer the main research question, firstly the role of culture in purchase intention context is researched. Secondly, focus is drawn to the factors that affect online purchase intention. Lastly, it is researched how Russian culture is affecting e-commerce attributes modification. The objective is not only to expand the theoretical understanding of the subject but also to provide companies with a clear vision on how the online operations should be conducted in Russian online market. Ranganathan’s and Jha’s conceptual framework was chosen as a ground theory in this study. Here, three main categories Computer Self-Efficacy and Past Online Experience, Website Quality and Costumer Concerns form basis for the study. Various articles and academic literature supplemented this theoretical approach. Qualitative research method was adapted and the study was conducted through five expert interviews. As a conclusion it can be stated that culture forms a ground for entire purchase decision-making process in online context. Results from the interviews were grouped according to main three theoretic categories and placed with Ranganathan’s and Jha’s original framework. This formed a new theoretical framework that defines diverse factors affecting specifically Russian consumer’s online purchase intention. This study suggests that following factors need to be taking into serious consideration in Russian online context: photography style, detailed product and company information, colors, language, product variety, reviews, recommendations, strong social media presence, fast check out and minimalistic order information, counterfeit fear, cash on delivery payment, training and guidance, extensive customer service, consumers’ insecurity, inexperience, high interest for technology and their individualistic personality.