In search of information systems value : a case study of the EHR benefits realisation efforts of three Swedish hospitals.

The Swedish public health care organisation could very well be undergoing its most significant change since its specialisation during the late 19th and early 20th century. At the heart of this change is a move from using manual patient journals to electronic health records (EHR). EHR are complex integrated organisational wide information systems (IS) that promise great benefits and value as well as presenting great challenges to the organisation. The Swedish public health care is not the first organisation to implement integrated IS, and by no means alone in their quest for realising the potential benefits and value that it has to offer. As organisations invest in IS they embark on a journey of value-creation and capture. A journey where a costbased approach towards their IS-investments is replaced with a value-centric focus, and where the main challenges lie in the practical day-to-day task of finding ways to intertwine technology, people and business processes. This has however proven to be a problematic task. The problematic situation arises from a shift of perspective regarding how to manage IS in order to gain value. This is a shift from technology delivery to benefits delivery; from an ISimplementation plan to a change management plan. The shift gives rise to challenges related to the inability of IS and the elusiveness of value. As a response to these challenges the field of IS-benefits management has emerged offering a framework and a process in order to better understand and formalise benefits realisation activities. In this thesis the benefits realisation efforts of three Swedish hospitals within the same county council are studied. The thesis focuses on the participants of benefits analysis projects; their perceptions, judgments, negotiations and descriptions of potential benefits. The purpose is to address the process where organisations seek to identify which potential IS-benefits to pursue and realise, this in order to better understand what affects the process, so that realisation actions of potential IS-benefits could be supported. A qualitative case study research design is adopted and provides a framework for sample selection, data collection, and data analysis. It also provides a framework for discussions of validity, reliability and generalizability. Findings displayed a benefits fluctuation, which showed that participants’ perception of what constituted potential benefits and value changed throughout the formal benefits management process. Issues like structure, knowledge, expectation and experience affected perception differently, and this in the end changed the amount and composition of potential benefits and value. Five dimensions of benefits judgment were identified and used by participants when finding accommodations of potential benefits and value to pursue. Identified dimensions affected participants’ perceptions, which in turn affected the amount and composition of potential benefits. During the formal benefits management process participants shifted between judgment dimensions. These movements emerged through debates and interactions between participants. Judgments based on what was perceived as expected due to one’s role and perceived best for the organisation as a whole were the two dominant benefits judgment dimensions. A benefits negotiation was identified. Negotiations were divided into two main categories, rational and irrational, depending on participants’ drive when initiating and participating in negotiations. In each category three different types of negotiations were identified having different characteristics and generating different outcomes. There was also a benefits negotiation process identified that displayed management challenges corresponding to its five phases. A discrepancy was also found between how IS-benefits are spoken of and how actions of IS benefits realisation are understood. This was a discrepancy between an evaluation and a realisation focus towards IS value creation. An evaluation focus described IS-benefits as well-defined and measurable effects and a realisation focus spoke of establishing and managing an on-going place of value creation. The notion of valuescape was introduced in order to describe and support the understanding of IS value creation. Valuescape corresponded to a realisation focus and outlined a value configuration consisting of activities, logic, structure, drivers and role of IS.

Building the ‘Digital’ Library: Routes to Managing our Institutional Digital Learning, Teaching and Research Assets Together

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

Biogas production in regional integrated biodegradable waste treatment – Possibilities for improving energy performance and reducing GHG emissions

The greatest threat that the biodegradable waste causes on the environment is the methane produced in landfills by the decomposition of this waste. The Landfill Directive (1999/31/EC) aims to reduce the landfilling of biodegradable waste. In Finland, 31% of biodegradable municipal waste ended up into landfills in 2012. The pressure of reducing disposing into landfills is greatly increased by the forthcoming landfill ban on biodegradable waste in Finland. There is a need to discuss the need for increasing the utilization of biodegradable waste in regional renewable energy production to utilize the waste in a way that allows the best possibilities to reduce GHG emissions. The objectives of the thesis are: (1) to find important factors affecting renewable energy recovery possibilities from biodegradable waste, (2) to determine the main factors affecting the GHG balance of biogas production system and how to improve it and (3) to find ways to define energy performance of biogas production systems and what affects it. According to the thesis, the most important factors affecting the regional renewable energy possibilities from biodegradable waste are: the amount of available feedstock, properties of feedstock, selected utilization technologies, demand of energy and material products and the economic situation of utilizing the feedstocks. The biogas production by anaerobic digestion was seen as the main technology for utilizing biodegradable waste in agriculturally dense areas. The main reason for this is that manure was seen as the main feedstock, and it can be best utilized with anaerobic digestion, which can produce renewable energy while maintaining the spreading of nutrients on arable land. Biogas plants should be located close to the heat demand that would be enough to receive the produced heat also in the summer months and located close to the agricultural area where the digestate could be utilized. Another option for biogas use is to upgrade it to biomethane, which would require a location close to the natural gas grid. The most attractive masses for biogas production are municipal and industrial biodegradable waste because of gate fees the plant receives from them can provide over 80% of the income. On the other hand, directing gate fee masses for small-scale biogas plants could make dispersed biogas production more economical. In addition, the combustion of dry agricultural waste such as straw would provide a greater energy amount than utilizing them by anaerobic digestion. The complete energy performance assessment of biogas production system requires the use of more than one system boundary. These can then be used in calculating output–input ratios of biogas production, biogas plant, biogas utilization and biogas production system, which can be used to analyze different parts of the biogas production chain. At the moment, it is difficult to compare different biogas plants since there is a wide variation of definitions for energy performance of biogas production. A more consistent way of analyzing energy performance would allow comparing biogas plants with each other and other recovery systems and finding possible locations for further improvement. Both from the GHG emission balance and energy performance point of view, the energy consumption at the biogas plant was the most significant factor. Renewable energy use to fulfil the parasitic energy demand at the plant would be the most efficient way to reduce the GHG emissions at the plant. The GHG emission reductions could be increased by upgrading biogas to biomethane and displacing natural gas or petrol use in cars when compared to biogas CHP production. The emission reductions from displacing mineral fertilizers with digestate were seen less significant, and the greater N2O emissions from spreading digestate might surpass the emission reductions from displacing mineral fertilizers.

Adaptive Markov chain Monte Carlo and Bayesian filtering for state space models

This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.

Decision making and decision support in service systems

This thesis is a literature study that develops a conceptual model of decision making and decision support in service systems. The study is related to the Ä-Logi, Intelligent Service Logic for Welfare Sector Services research project, and the objective of the study is to develop the necessary theoretical framework to enable further research based on the research project results and material. The study first examines the concepts of service and service systems, focusing on understanding the characteristics of service systems and their implications for decision making and decision support to provide the basis for the development of the conceptual model. Based on the identified service system characteristics, an integrated model of service systems is proposed that views service systems through a number of interrelated perspectives that each offer different, but complementary, implications on the nature of decision making and the requirements for decision support in service systems. Based on the model, it is proposed that different types of decision making contexts can be identified in service systems that may be dominated by different types of decision making processes and where different types of decision support may be required, depending on the characteristics of the decision making context and its decision making processes. The proposed conceptual model of decision making and decision support in service systems examines the characteristics of decision making contexts and processes in service systems, and their typical requirements for decision support. First, a characterization of different types of decision making contexts in service systems is proposed based on the Cynefin framework and the identified service system characteristics. Second, the nature of decision making processes in service systems is proposed to be dual, with both rational and naturalistic decision making processes existing in service systems, and having an important and complementary role in decision making in service systems. Finally, a characterization of typical requirements for decision support in service systems is proposed that examines the decision support requirements associated with different types of decision making processes in characteristically different types of decision making contexts. It is proposed that decision support for the decision making processes that are based on rational decision making can be based on organizational decision support models, while decision support for the decision making processes that are based on naturalistic decision making should be based on supporting the decision makers’ situation awareness and facilitating the development of their tacit knowledge of the system and its tasks. Based on the proposed conceptual model a further research process is proposed. The study additionally provides a number of new perspectives on the characteristics of service systems, and the nature of decision making and requirements for decision support in service systems that can potentially provide a basis for further discussion and research, and support the practice alike.

Rigorous development of safety-critical systems

Nowadays, computer-based systems tend to become more complex and control increasingly critical functions affecting different areas of human activities. Failures of such systems might result in loss of human lives as well as significant damage to the environment. Therefore, their safety needs to be ensured. However, the development of safety-critical systems is not a trivial exercise. Hence, to preclude design faults and guarantee the desired behaviour, different industrial standards prescribe the use of rigorous techniques for development and verification of such systems. The more critical the system is, the more rigorous approach should be undertaken. To ensure safety of a critical computer-based system, satisfaction of the safety requirements imposed on this system should be demonstrated. This task involves a number of activities. In particular, a set of the safety requirements is usually derived by conducting various safety analysis techniques. Strong assurance that the system satisfies the safety requirements can be provided by formal methods, i.e., mathematically-based techniques. At the same time, the evidence that the system under consideration meets the imposed safety requirements might be demonstrated by constructing safety cases. However, the overall safety assurance process of critical computerbased systems remains insufficiently defined due to the following reasons. Firstly, there are semantic differences between safety requirements and formal models. Informally represented safety requirements should be translated into the underlying formal language to enable further veri cation. Secondly, the development of formal models of complex systems can be labour-intensive and time consuming. Thirdly, there are only a few well-defined methods for integration of formal verification results into safety cases. This thesis proposes an integrated approach to the rigorous development and verification of safety-critical systems that (1) facilitates elicitation of safety requirements and their incorporation into formal models, (2) simplifies formal modelling and verification by proposing specification and refinement patterns, and (3) assists in the construction of safety cases from the artefacts generated by formal reasoning. Our chosen formal framework is Event-B. It allows us to tackle the complexity of safety-critical systems as well as to structure safety requirements by applying abstraction and stepwise refinement. The Rodin platform, a tool supporting Event-B, assists in automatic model transformations and proof-based verification of the desired system properties. The proposed approach has been validated by several case studies from different application domains.

Designing new learning experiences? : exploring corporate E-learners’ self-regulated learning

The context of this study is corporate e-learning, with an explicit focus on how digital learning design can facilitate self-regulated learning (SRL). The field of e-learning is growing rapidly. An increasing number of corporations use digital technology and elearning for training their work force and customers. E-learning may offer economic benefits, as well as opportunities for interaction and communication that traditional teaching cannot provide. However, the evolving variety of digital learning contexts makes new demands on learners, requiring them to develop strategies to adapt and cope with novel learning tools. This study derives from the need to learn more about learning experiences in digital contexts in order to be able to design these properly for learning. The research question targets how the design of an e-learning course influences participants’ self-regulated learning actions and intentions. SRL involves learners’ ability to exercise agency in their learning. Micro-level SRL processes were targeted by exploring behaviour, cognition, and affect/motivation in relation to the design of the digital context. Two iterations of an e-learning course were tested on two groups of participants (N=17). However, the exploration of SRL extends beyond the educational design research perspective of comparing the effects of the changes to the course designs. The study was conducted in a laboratory with each participant individually. Multiple types of data were collected. However, the results presented in this thesis are based on screen observations (including eye tracking) and video-stimulated recall interviews. These data were integrated in order to achieve a broad perspective on SRL. The most essential change evident in the second course iteration was the addition of feedback during practice and the final test. Without feedback on actions there was an observable difference between those who were instruction-directed and those who were self-directed in manipulating the context and, thus, persisted whenever faced with problems. In the second course iteration, including the feedback, this kind of difference was not found. Feedback provided the tipping point for participants to regulate their learning by identifying their knowledge gaps and to explore the learning context in a targeted manner. Furthermore, the course content was consistently seen from a pragmatic perspective, which influenced the participants’ choice of actions, showing that real life relevance is an important need of corporate learners. This also relates to assessment and the consideration of its purpose in relation to participants’ work situation. The rigidity of the multiple choice questions, focusing on the memorisation of details, influenced the participants to adapt to an approach for surface learning. It also caused frustration in cases where the participants’ epistemic beliefs were incompatible with this kind of assessment style. Triggers of positive and negative emotions could be categorized into four levels: personal factors, instructional design of content, interface design of context, and technical solution. In summary, the key design choices for creating a positive learning experience involve feedback, flexibility, functionality, fun, and freedom. The design of the context impacts regulation of behaviour, cognition, as well as affect and motivation. The learners’ awareness of these areas of regulation in relation to learning in a specific context is their ability for design-based epistemic metareflection. I describe this metareflection as knowing how to manipulate the context behaviourally for maximum learning, being metacognitively aware of one’s learning process, and being aware of how emotions can be regulated to maintain volitional control of the learning situation. Attention needs to be paid to how the design of a digital learning context supports learners’ metareflective development as digital learners. Every digital context has its own affordances and constraints, which influence the possibilities for micro-level SRL processes. Empowering learners in developing their ability for design-based epistemic metareflection is, therefore, essential for building their digital literacy in relation to these affordances and constraints. It was evident that the implementation of e-learning in the workplace is not unproblematic and needs new ways of thinking about learning and how we create learning spaces. Digital contexts bring a new culture of learning that demands attitude change in how we value knowledge, measure it, define who owns it, and who creates it. Based on the results, I argue that digital solutions for corporate learning ought to be built as an integrated system that facilitates socio-cultural connectivism within the corporation. The focus needs to shift from designing static e-learning material to managing networks of social meaning negotiation as part of a holistic corporate learning ecology.

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.

Formal development of resilient distributed systems

Resilience is the property of a system to remain trustworthy despite changes. Changes of a different nature, whether due to failures of system components or varying operational conditions, significantly increase the complexity of system development. Therefore, advanced development technologies are required to build robust and flexible system architectures capable of adapting to such changes. Moreover, powerful quantitative techniques are needed to assess the impact of these changes on various system characteristics. Architectural flexibility is achieved by embedding into the system design the mechanisms for identifying changes and reacting on them. Hence a resilient system should have both advanced monitoring and error detection capabilities to recognise changes as well as sophisticated reconfiguration mechanisms to adapt to them. The aim of such reconfiguration is to ensure that the system stays operational, i.e., remains capable of achieving its goals. Design, verification and assessment of the system reconfiguration mechanisms is a challenging and error prone engineering task. In this thesis, we propose and validate a formal framework for development and assessment of resilient systems. Such a framework provides us with the means to specify and verify complex component interactions, model their cooperative behaviour in achieving system goals, and analyse the chosen reconfiguration strategies. Due to the variety of properties to be analysed, such a framework should have an integrated nature. To ensure the system functional correctness, it should rely on formal modelling and verification, while, to assess the impact of changes on such properties as performance and reliability, it should be combined with quantitative analysis. To ensure scalability of the proposed framework, we choose Event-B as the basis for reasoning about functional correctness. Event-B is a statebased formal approach that promotes the correct-by-construction development paradigm and formal verification by theorem proving. Event-B has a mature industrial-strength tool support { the Rodin platform. Proof-based verification as well as the reliance on abstraction and decomposition adopted in Event-B provides the designers with a powerful support for the development of complex systems. Moreover, the top-down system development by refinement allows the developers to explicitly express and verify critical system-level properties. Besides ensuring functional correctness, to achieve resilience we also need to analyse a number of non-functional characteristics, such as reliability and performance. Therefore, in this thesis we also demonstrate how formal development in Event-B can be combined with quantitative analysis. Namely, we experiment with integration of such techniques as probabilistic model checking in PRISM and discrete-event simulation in SimPy with formal development in Event-B. Such an integration allows us to assess how changes and di erent recon guration strategies a ect the overall system resilience. The approach proposed in this thesis is validated by a number of case studies from such areas as robotics, space, healthcare and cloud domain.

Finnish perceptions on management accounting systems: towards an upgraded sophistication model

This study is based on a large survey study of over 1500 Finnish companies’ usage, needs and implementation difficulties of management accounting systems. The study uses quantitative, qualitative and mixed methods to answer the research questions. The empirical data used in the study was gathered through structured interviews with randomly selected companies of varying sizes and industries. The study answers the three research questions by analyzing the characteristics and behaviors of companies working in Finland. The study found five distinctive groups of companies according to the characteristics of their cost information and management accounting system use. The study also showed that the state of cost information and management accounting systems depends on the industry and size of the companies. It was found that over 50% of the companies either did not know how their systems could be updated or saw systems as inadequate. The qualitative side also highlighted the needs for tailored and integrated management accounting systems for creating more value to the managers of companies. The major inhibitors of new system implementation were the lack of both monetary and human resources. Through the use of mixed methods and design science a new and improved sophistication model is created based on previous research results combined with the information gathered from previous literature. The sophistication model shows the different stages of management accounting systems in use and what companies can achieve with the implementation and upgrading of their systems.

Energy aware software for many-core systems

Many-core systems provide a great potential in application performance with the massively parallel structure. Such systems are currently being integrated into most parts of daily life from high-end server farms to desktop systems, laptops and mobile devices. Yet, these systems are facing increasing challenges such as high temperature causing physical damage, high electrical bills both for servers and individual users, unpleasant noise levels due to active cooling and unrealistic battery drainage in mobile devices; factors caused directly by poor energy efficiency. Power management has traditionally been an area of research providing hardware solutions or runtime power management in the operating system in form of frequency governors. Energy awareness in application software is currently non-existent. This means that applications are not involved in the power management decisions, nor does any interface between the applications and the runtime system to provide such facilities exist. Power management in the operating system is therefore performed purely based on indirect implications of software execution, usually referred to as the workload. It often results in over-allocation of resources, hence power waste. This thesis discusses power management strategies in many-core systems in the form of increasing application software awareness of energy efficiency. The presented approach allows meta-data descriptions in the applications and is manifested in two design recommendations: 1) Energy-aware mapping 2) Energy-aware execution which allow the applications to directly influence the power management decisions. The recommendations eliminate over-allocation of resources and increase the energy efficiency of the computing system. Both recommendations are fully supported in a provided interface in combination with a novel power management runtime system called Bricktop. The work presented in this thesis allows both new- and legacy software to execute with the most energy efficient mapping on a many-core CPU and with the most energy efficient performance level. A set of case study examples demonstrate realworld energy savings in a wide range of applications without performance degradation.

Motor Types Comparison Determining Efficiency in Pumping Systems

Pumping, fan and compressor systems consume most of the motor electricity power in both the industrial and services sectors. A variable speed drive brings relevant improvements in a fluid system leading to energy saving that further on can be translated into Mtons reduction of CO 2 emissions. Standards and regulations are being adopted for fluid handling systems to limit the less efficiency pumps out of the European market on the coming years and a greater potential in energy savings is dictated by the Energy Efficiency Index (EEI) requirements for the whole pumping system and integrated pumps. Electric motors also have an International Efficiency (IE) classification in order to introduce higher efficiency motors into the market. In this thesis, the applicability of mid-size common electric motor types to industrial pumping system took place comparing the motor efficiency characteristics with each other and by analyzing the effect of motor dimensioning on the pumping system and its impact in the energy consumption.