Information technology (IT) is a key enabler of modern business practices, yet reliably effective IT systems remain a significant challenge for many organizations. The consequences when systems fail to behave as expected becomes ever-more problematic as IT dependence grows. Therefore, methods for assessing IT effectiveness and generating actionable recommendations for improvement are key drivers of success. For this reason, large organizations often adopt IT best practice frameworks such as COBIT, ITIL or ISO/IEC standards which can offer greater assurances of IT effectiveness. However smaller organizations are rarely able to adopt these frameworks due, in part, to resource constraints, and a preference to eschew authoritative practices in favour of informal guides to action. Consequently, a significant research gap is the lack of IT effectiveness approaches for organizations unable or unwilling to adopt formal IT best practice frameworks. This thesis presents an alternative norms-based approach to IT effectiveness which some organizations might find more suitable. Norms are informal beliefs (e.g. ‘using a complex password helps safeguard data’) which motivate behaviours and can often be expressed using non-technical language. We review the literature to formulate a predictive model connecting norms to IT quality. Employing a scientific methodology defensible on philosophical grounds and accepted research practices, we distil a set of IT effectiveness norms from the COBIT 4.1 IT governance framework and adapt theories of motivation to justify our assertion that IT effectiveness norms can motivate actions. Our work is signficant in its formulation of an alternative approach for assessing IT operations and improving organizational IT outcomes. Our survey instrument –validated in four studies, which include a non-profit and government organization, multiple small businesses, a large pharmaceutical company and a university –is a light-weight and reliable assessment tool. Our predictive model is able to explain 26% of observed variance, and can offer actionable and non-technical insights which can improve organizational outcomes. A norms-based approach may bring many of the same IT effectiveness benefits offered by formal IT best practices into organizations, such as small businesses, which lack the resources for their implementation. This approach may also help bridge important communication gaps between IT professionals and others in the organization by providing a different, less technical perspective for framing, assessing, diagnosing, and communicating about IT processes.

This thesis is about hiring processes in the university sector. More particularly, the focus is to identify if the employment of lecturers obeys the principle of objectivity, impartiality and meritocracy. The thesis is based on a so-called mixed method research. Partly, the extent of compliance is tested in a quantitative survey of six Swedish universities, partly each one of the 73 employment notices is analyzed in a qualitative text analysis. The source of information is public government documents from the examined universities. The survey is limited only to include employments until further notice. Therefore, all sorts of temporary employments are excluded. The focus is on the academic subjects of social science, sociology and political economy. Furthermore, the thesis only investigates employments from the years of 2011-2019. To create an understanding in what way the state institutions should handle their exercise of power, the theory Quality of Government (QoG) is being used. The theory is also used for analysis and as an inspiration for the assay scheme, which is used to assess if the employments are considered “narrower” or “more open”. The variables used in the survey are; notification time, number of applicants, the use of peer review, language of the announcement, and a type of “employment conversion”, made possible by law. The result of the thesis shows that there is an extensive amount of employments which in one way or another violates the principle of impartiality. For example: 24 percent of the employments has less than 2 applicants. 17 percent of the employments is missing impartial peer reviews. 89 percent of the employments are only given noticed in Swedish. 29 percent of the announcement texts are written in a narrow, excluding way. To sum up, we can see indications of partial employments. There are distinctive variations between the universities and among the academic subjects. The most important conclusion of this thesis is that all partial employments are a problem, with shortcomings in quality and in public trust as consequences.

One of the main aims of the underlying research is to respond to continuous calls for introducing and measuring a sound economic definition for best practice disclosure quality (e.g. Beyer et al., 2010) that is derived from a reliable guidance framework (Botosan, 2004) using an innovative natural language processing technique (Berger, 2011). It also aims to examine the impact of corporate governance on best practice disclosure quality. Finally, it aims to examine the joint effect of both best practice disclosure quality and corporate governance on firm value. The thesis contributes to disclosure studies in three principal ways. First, it introduces a new measure for best practice disclosure quality. Further tests show that the proposed measure is reliable and valid. A novel feature of this measure is that it captures all qualitative dimensions of information issued by the Accounting Standards Board, 2006 (ASB) Operating and Financial Review (OFR) Reporting Statement. Second, it uses machine-readable OFR statements for financial years ending in 2006-2009, and develops a language processing technique through constructing five keyword lists. Third, it examines the extent to which disclosure quantity provides a proper proxy for disclosure quality. The analysis shows that disclosure quantity is not a good proxy for disclosure quality. Accordingly, results derived, using quantity as a proxy for quality, are questionable. Results of the association between disclosure quality and corporate governance mechanisms suggest that the most effective governance mechanisms in improving disclosure quality are leadership structure, audit committee meeting frequency, and audit firm size. Using a wide set of corporate governance mechanisms, the study also contributes to three research strands and explains the inconclusive results in relation to the association between disclosure quality, corporate governance mechanisms and firm value. It provides empirical evidence as to which governance mechanisms promote the quality of voluntarily disclosed information in large UK firms. Additionally, it provides empirical evidence as to the joint effect of best practice disclosure quality, corporate governance mechanisms on firm value in the UK. Results also show that best practice disclosure quality enjoys a substitutive relationship with two corporate governance mechanisms (audit committee independence and audit committee size) and a complementary association with board independence in relation to firm value. The study has various research and policy implications. It suggests new research avenues for re-examining disclosure relationships, especially research areas that do not have persuasive conclusions such as the economic consequences of disclosure quality. Such research may inform both regulators and managers as to the costs and benefits of disclosure quality to both firms and stakeholders. It also provides feedback on the current disclosure practices by firms so that policy-makers can modify reporting frameworks/guidance accordingly.

This master thesis is about Big Data Governance and about software, which is used for this purposes. Because Big Data are huge opportunity and also risk, I wanted to map products which can be easily use for Data Quality and Big Data Governance in one platform. This thesis is not only on theoretical knowledge level, but also evaluates five key products (from my point of view). I defined requirements for every kind of domain and then I set up the weights and points. The main objective is to evaluate software capabilities and compere them.

Water is critical for food production, food security, and health. Water quality management influences freshwater sustainability, land, and energy administration. Global agriculture accounts for more than 70% of all water consumption; the fertilizer, manure, and pesticide overspills are chief sources of water pollution worldwide. On a global scale, food-related waste directly impacts local food production and water resource management. The purpose of this multiple-case study on the food and beverage (FB) industry in the State of Georgia was to identify successful strategies for improving water management efficiency. The concepts of systems thinking, adaptive resource management, and integrated water resource management provided the conceptual framework for the study. Data were collected via personal interviews with 2 global supply chain leaders in the FB industry and 1 water expert in the public water utility system in Georgia. The findings showed 10 themes: sustainability; mission-driven culture; ethical responsibility; water quality and governance; food safety and sanitation; water conservation and climatic trends; waste management; nutrition and the freeze drying method; knowledge sharing and collaboration; and water detention and retention systems. The study results are intended to contribute to social change by providing information to global supply chain leaders, policy makers, entrepreneurs, and sustainability leaders to implement sustainability beyond the environmental value; these findings will also help achieve a positive posture on resource overconsumption and waste management for efficient and complex decision making within a worldwide spectrum.

In recent years there has been an increasing interest in understanding how organizations can utilize big data in their process management to create value and improve their processes. This is due to new challenges for process management which have arisen from increasing competition and the complexity of large data sets due to technological advancements. These large data sets have been described by scholars as big data which involves data that are so complex traditional data analysis software are not sufficient in managing or analyzing them. Because of the complexity of handling such great volumes of data there is a big gap in practical examples where organizations have incorporated big data in their process management. Therefore, in order to fill relevant gaps and contribute to advancements in this field, this thesis will explore how big data can contribute to improved process management. Hence, the aim of this thesis entailed investigating how, why and to what extent big data is used in process management. As well as to outline the purpose and challenges of using big data in process management. This was accomplished through a literature review and a survey, respectively, in order to understand how big data had previously been used to create value and improve processes in organizations. From the extensive literature review, an analysis matrix of how big data is used in process management is provided through the intersections between big data and process management dimensions. The analysis matrix showed that most of the instances in which big data was used in process management were in process analysis & improvement and process control & agility. Simply put, organizations used big data in specific activities involved in process management but not in a holistic manner. Furthermore, the limited findings from the survey indicate that the main challenges and purposes of big data use in Swedish organizations are the complexity of handling data and making statistically better decisions, respectively.

This thesis carries out empirical investigations of the possible impacts of institutions relating to different aspects of innovation, namely incremental innovation activities, collaborative research and development (R&D) activities and radical innovation outcomes. It comprises three studies. The first empirical study focuses on examining the impact of financial constraints and intellectual property rights (IPR) protection on incremental innovation. Using firm-level data from transition countries and employing a two-step probit model with endogenous regressors, this study provides evidence that both financing constraints and strong IPR protection are negatively associated with the incremental innovation activities of firms. Results also confirm that financing constraints faced by firms are significantly influenced by the overall levels of development of financial institutions within a country. The second empirical study looks at the effects of contracting institutions and intellectual property institutions on firms’ collaborative research and development (R&D) activities in developing and transition countries. By employing the Cragg double-hurdle model, this study finds that efficient contract enforcement has a positive effect on the likelihood of firms engaging in R&D partnership and the intensity of firms' expenditures on collaborative R&D. On the other hand, the decision of firms to participate in R&D partnerships and their level of expenditure on collaborative R&D are adversely affected by the strength of IPR protection. The third empirical study investigates the influences of a set of institutions on producing new-to-the-world technologies, as measured by patents. This study is conducted by using a large panel dataset of 98 developed and developing countries over a period of 23 years. Building on the idea production framework, the unconditional quantile regression (UQR) estimates of this study show that along with key research inputs (i.e., existing knowledge stock and resources devoted to R&D), the strength of IPR protection, quality of governance and functioning of financial institutions are also significant determinants of the patent output of a country. The UQR methodology also demonstrates that the effects of institutions on patent production are heterogeneous throughout the various quantiles of patent output distribution. This thesis, therefore, offers an example of how the new institutional economics (NIE) theory is applicable in analysing innovation performances. The findings of this thesis propose useful policy directions that can assist policymakers and managers in accelerating innovation and technological development. / Ministry of Public Administration, the Government of the People’s Republic of Bangladesh