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.

Green supply chain management practices and firm performance: evidence from Finland

In order to address the increasing stakeholder requirements for environmentally sustainable products and processes, firms often need the participation of their supply chain partners. Green supply chain management has emerged as a set of managerial practices that integrate environmental issues into supply chain management. If implemented successfully, green supply chain management can be a way to achieve competitive advantage while enhancing the environmental sustainability of the firm. The overall purpose of this dissertation is to contribute to the discussion on green supply chain management practices from the perspective of their drivers and performance implications. The theoretical background arises from the literature on competitive strategy, firm performance and green supply chain management. The research questions are addressed by analysing firm-level data from manufacturing, trading and logistics firms operating in Finland. The empirical data comes from two consecutive Finland State of Logistics surveys in 2012 and 2014, combined with financial reporting data from external databases. The data is analysed with multiple statistical methods. First, the thesis contributes to the discussion of the drivers of GSCM practices. To enhance the understanding of the relationship between competitive strategy and GSCM practices, a conceptual tool to describe generic competitive strategy approaches was developed. The findings suggest that firms pursuing marketing differentiation are more likely to be able to compete by having only small environmental effects and by adopting a more advanced form of external green supply chain management, such as a combination of strong environmental collaboration and the increased environmental monitoring of suppliers. Furthermore, customer requirements for environmental sustainability are found to be an important driver in the implementation of internal GSCM practices. Firms can respond to this customer pressure by passing environmental requirements on to their suppliers, either through environmental collaboration or environmental monitoring. Second, this thesis adds value to the existing literature on the effects of green supply chain management practices on firm performance. The thesis provides support for the idea that there is a positive relationship between GSCM practices and firm performance and enhances the understanding of how different types of GSCM practices are related to 1) financial, 2) operational and 3) environmental performance in manufacturing and logistics. The empirical results suggest that while internal GSCM practices have the strongest effect on environmentalperformance, environmental collaboration with customers seems to be the most effective way to improve financial performance. In terms of operational performance, the findings were more mixed, suggesting that the operational performance of firms is more likely to be affected by firm characteristics than by the choices they make regarding their environmental collaboration. This thesis is also one of the first attempts to empirically analyse the relationship between GSCM practices and performance among logistics service providers. The findings also have managerial relevance. Management, especially in manufacturing and logistics industries, may benefit by gaining knowledge about which types of GSCM practice could provide the largest benefits in terms of different performance dimensions. This thesis also has implications for policy-makers and regulators regarding how to promote environmentally friendly activities among 1) manufacturing; 2) trading; and 3) logistics firms.