When Metadata Collides: Lessons on Combining Records from Multiple Repository Systems.

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

Integrating Use of Customer Information Throughout Multiple Sales Channels to Create Customer Competence

Customer knowledge management (CKM) practices enable organizations to create customer competence with systematic use of customer information that is integrated throughout the organization. Nonetheless, organizations are not able to fully exploit the vast amount of data available. Previous research on use of customer information is limited especially in a multichannel environment. The aim of this study was to identify the main obstacles for utilizing customer information efficiently across multiple sales channels. The study was conducted as a single case study in order to gain deeper understanding of the research problem. The empirical findings indicate that lack of CKM practices and a common goal are major challenges obstructing effective utilization of customer information. Furthermore, decentralized organizational structure and insufficient analytical skills create obstacles for information sharing and capabilities to process information and create new knowledge. The implications of the study suggest that in order to create customer competence organizations should shift their focus from technology to the organizational factors affecting use of information and implement CKM practices throughout the organization.

Multiple sclerosis and pregnancy: clinical and immunological aspects

Background: Multiple Sclerosis (MS) is an autoimmune disease of the central nervous system that affects most commonly young women in their childbearing age. Previous studies have shown that MS relapse rate usually reduces during pregnancy and increases again after delivery. Patients with MS and their treating physicians are interested to know more about the risks the disease can cause to pregnancy and how pregnancy affects the disease. The reasons for increased relapse rate after delivery are not entirely clear, but loss of pregnancy related immune tolerance and changes in the hormonal status at the time of delivery seem to be of relevance. Aims and methods: The aims of this study were to follow the natural course of MS during and after pregnancy, evaluate pregnancy related risks among MS patients, follow the inflammatory response of MS patients during and after pregnancy and clarify the risk of relevant co-morbidities known to affect other autoimmune diseases after pregnancy and compare these results to healthy controls. This study was a part of a prospective nation-wide follow-up study of 60 Finnish MS patients. All eligible MS patients were enrolled in the study during the years 2003-2005. A prospective followup continued from early pregnancy until six months postpartum. MS relapses, EDSS scores and obstetric details were recorded. Blood samples were obtained from the patients at early, middle, and late pregnancy, after delivery and one month, three months and six months postpartum. Results: MS patients were no more likely to experience pregnancy or delivery complications than the Finnish mothers in general. The need of instrumental assistance, however, was higher among mothers with MS. Disease activity followed the course seen in previous studies. The majority of mothers (90.2%) breastfed their babies. Contrary to previous results, breastfeeding did not protect MS patients from disease worsening after delivery in present study. Mothers with active pre-pregnancy disease chose to breastfeed less frequently and started medication instead. MS patients presented with higher prevalence of elevated thyroid autoantibodies postpartum than healthy controls, but the rate of thyroid hormonal dysfunction was similar as that of healthy controls. The mode of delivery nor the higher rate of tissue damage assessed with C-reactive protein concentration were not predictive of postpartum relapses. The prevalence of gestational diabetes was slightly higher among mothers with MS compared to Finnish mothers in general, but postpartum depression was observed in similar rates. MS patients presented with significantly lower serum concentrations of vitamin D during pregnancy and postpartum than healthy controls. Conclusions: Childbearing can be regarded as safe for mothers with MS as it is for healthy mothers in general. Breastfeeding can be recommended, but it should be done only after careful evaluation of the individual risk for postpartum disease activation. Considering MS patients tend to develop thyroid antibody positivity after delivery more often than healthy controls and that certain treatments can predispose MS patients to thyroid hormonal dysfunction, we recommend MS mothers to be screened for thyroid abnormalities during pregnancy and after delivery. Increased risk for gestational diabetes should be kept in mind when following MS mothers and glucose tolerance test in early pregnancy should be considered. Adequate vitamin D supplementation is essential for MS mothers also during pregnancy and postpartum period.

Green supplier selection via Multiple Criteria Data Envelopment Analysis

An appropriate supplier selection and its profound effects on increasing the competitive advantage of companies has been widely discussed in supply chain management (SCM) literature. By raising environmental awareness among companies and industries they attach more importance to sustainable and green activities in selection procedures of raw material providers. The current thesis benefits from data envelopment analysis (DEA) technique to evaluate the relative efficiency of suppliers in the presence of carbon dioxide (CO2) emission for green supplier selection. We incorporate the pollution of suppliers as an undesirable output into DEA. However, to do so, two conventional DEA model problems arise: the lack of the discrimination power among decision making units (DMUs) and flexibility of the inputs and outputs weights. To overcome these limitations, we use multiple criteria DEA (MCDEA) as one alternative. By applying MCDEA the number of suppliers which are identified as efficient will be decreased and will lead to a better ranking and selection of the suppliers. Besides, in order to compare the performance of the suppliers with an ideal supplier, a “virtual” best practice supplier is introduced. The presence of the ideal virtual supplier will also increase the discrimination power of the model for a better ranking of the suppliers. Therefore, a new MCDEA model is proposed to simultaneously handle undesirable outputs and virtual DMU. The developed model is applied for green supplier selection problem. A numerical example illustrates the applicability of the proposed model.

Imaging Neuroinflammation in Progressive Multiple Sclerosis

Multiple sclerosis (MS) is a chronic autoimmune disease of the central nervous system CNS), where inflammation and neurodegeneration lead to irreversible neuronal damage. In MS, a dysfunctional immune system causes auto‐reactive lymphocytes to migrate into CNS where they initiate an inflammatory cascade leading to focal demyelination, axonal degeneration and neuronal loss. One of the hallmarks of neuronal injury and neuroinflammation is the activation of microglia. Activated microglia are found not only in the focal inflammatory lesions, but also diffusely in the normal‐appearing white matter (NAWM), especially in progressive MS. The purine base, adenosine is a ubiquitous neuromodulator in the CNS and also participates in the regulation of inflammation. The effect of adenosine mediated via adenosine A2A receptors has been linked to microglial activation, whereas modulating A2A receptors may exert neuroprotective effects. In the majority of patients, MS presents with a relapsing disease course, later advancing to a progressive phase characterised by a worsening, irreversible disability. Disease modifying treatments can reduce the severity and progression in relapsing MS, but no efficient treatment exists for progressive MS. The aim of this research was to investigate the prevalence of adenosine A2A receptors and activated microglia in progressive MS by using in vivo positron emission tomography (PET) imaging and [11C]TMSX and [11C](R)‐PK11195 radioligands. Magnetic resonance imaging (MRI) with diffusion tensor imaging (DTI) was performed to evaluate structural brain damage. Non‐invasive input function methods were also developed for the analyses of [11C]TMSX PET data. Finally, histopathological correlates of [11C](R)‐PK11195 radioligand binding related to chronic MS lesions were investigated in post‐mortem samples of progressive MS brain using autoradiography and immunohistochemistry. [11C]TMSX binding to A2A receptors was increased in NAWM of secondary progressive MS (SPMS) patients when compared to healthy controls, and this correlated to more severe atrophy in MRI and white matter disintegration (reduced fractional anisotropy, FA) in DTI. The non‐invasive input function methods appeared as feasible options for brain [11C]TMSX images obviating arterial blood sampling. [11C](R)‐PK11195 uptake was increased in the NAWM of SPMS patients when compared to patients with relapsing MS and healthy controls. Higher [11C](R)‐PK11195 binding in NAWM and total perilesional area of T1 hypointense lesions was associated with more severe clinical disability, increased brain atrophy, higher lesion load and reduced FA in NAWM in the MS patients. In autoradiography, increased perilesional [11C](R)‐PK11195 uptake was associated with increased microglial activation identified using immunohistochemistry. In conclusion, brain [11C]TMSX PET imaging holds promise in the evaluation of diffuse neuroinflammation in progressive MS. Being a marker of microglial activation, [11C](R)‐ PK11195 PET imaging could possibly be used as a surrogate biomarker in the evaluation of the neuroinflammatory burden and clinical disease severity in progressive MS.

Innovation process development and business process integration - a multiple case study

The main objective of this study was to find out the bases for innovation model formulation in an existing organization based on cases. Innovation processes can be analyzed based on their needs and based on their emphasis on the business model development or R&D. The research was conducted in energy sector within one company by utilizing its projects as cases for the study. It is typical for the field of business that development is slow, although the case company has put emphasis on its innovation efforts. Analysis was done by identifying the cases’ needs and comparing them. The results were that because of the variances in the needs of the cases, the applicability of innovation process models varies. It was discovered that by dividing the process into two phases, a uniform model could be composed. This model would fulfill the needs of the cases and potential future projects as well.

The Determinants of Financial Leverage of Large Publicly Listed Companies - Evidence from Nordic Telecom Sector

This thesis examines the determinants of financial leverage ratio of large publicly listed companies within Nordic Telecom sector. The study is done as a case study and it covers 5 case companies headquartered in Nordic countries during period of 2002 - 2014 and by using restated values of quarterly observations from each case company’s interim reports. The chosen hypotheses are tested with multiple linear regressions firm by firm. The Findings of the study showed that uniqueness of Telecom sector and the region of our sample could not provide us unequivocal determinants of leverage ratio within the sector. However, e.g. Pecking order theory’s statement of Liquidity was widely confirmed by 3 out of 5 case companies which is worth to be taken into account in the big picture. The findings also showed that theories and earlier empirical evidence are confirmed by our case companies individually and non-systematically. Though Telecom sector is considered as quite unique industry and we did not discover absolute common relationships that would have held through all the Nordic case companies, we got unique and valuable evidence to conduct the research of this sector in future.

Value added KPI service delivery with quality function deployment: Multiple case study in asset & real estate management

The aim of this study is to investigate value added service concept for an asset and real estate management case company. The initial purpose was to recognize the most value adding key performance indicators (KPIs) information delivered for its customers, real estate investors with value added service. The multiple case study strategy included two focus group interviews with five case interviews in total. Additionally, quality function deployment (QFD) was used in order to form up the service process. The study starts with introduction and methodology explaining the demand for the thesis study. The subsequent chapter presents the theoretical background on real estate management KPIs in four main points of views and quality function deployment from the service development point of view. The chapter also defines research gap for the case study. According to the case study interviews, the most favored KPIs to deliver for the clients are income maturity of lease agreements and leasing activity. These KPIs and quality characteristics are translated into the QFD. In total, the service QFD explains the service planning, process control, and action plan phases.

Market anomalies and tactical asset allocation: Utilising market anomalies in multiple asset class portfolios with the Black−Litterman model

This thesis discusses the basic problem of the modern portfolio theory about how to optimise the perfect allocation for an investment portfolio. The theory provides a solution for an efficient portfolio, which minimises the risk of the portfolio with respect to the expected return. A central feature for all the portfolios on the efficient frontier is that the investor needs to provide the expected return for each asset. Market anomalies are persistent patterns seen in the financial markets, which cannot be explained with the current asset pricing theory. The goal of this thesis is to study whether these anomalies can be observed among different asset classes. Finally, if persistent patterns are found, it is investigated whether the anomalies hold valuable information for determining the expected returns used in the portfolio optimization Market anomalies and investment strategies based on them are studied with a rolling estimation window, where the return for the following period is always based on historical information. This is also crucial when rebalancing the portfolio. The anomalies investigated within this thesis are value, momentum, reversal, and idiosyncratic volatility. The research data includes price series of country level stock indices, government bonds, currencies, and commodities. The modern portfolio theory and the views given by the anomalies are combined by utilising the Black-Litterman model. This makes it possible to optimise the portfolio so that investor’s views are taken into account. When constructing the portfolios, the goal is to maximise the Sharpe ratio. Significance of the results is studied by assessing if the strategy yields excess returns in a relation to those explained by the threefactormodel. The most outstanding finding is that anomaly based factors include valuable information to enhance efficient portfolio diversification. When the highest Sharpe ratios for each asset class are picked from the test factors and applied to the Black−Litterman model, the final portfolio results in superior riskreturn combination. The highest Sharpe ratios are provided by momentum strategy for stocks and long-term reversal for the rest of the asset classes. Additionally, a strategy based on the value effect was highly appealing, and it basically performs as well as the previously mentioned Sharpe strategy. When studying the anomalies, it is found, that 12-month momentum is the strongest effect, especially for stock indices. In addition, a high idiosyncratic volatility seems to be positively correlated with country indices on stocks.