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The awareness of having a good information quality (IQ) in organizations has been increasing in the past decades. Despite that the well-accepted definition of information quality emphasizes the fitness of information to its consumers, IQ itself is known as context sensitive (Wang and Strong, 1996). It may be perceived differently depending on different contexts. This thesis presents a study of investigating IQ under the lens of practice theory. Practice theory intends to reveal the very idea of how the nexuses of human activities are organized (Schatzki, 2001). In this thesis, IQ was interpreted under the lens of Swidler’s perspective on practice theory specifically (2001), who stresses culture as the core that lies behind every aspect of social causation. The purpose of this study is to gain an in-depth knowledge on information quality. The empirical setting in this study is the sibling support system in Sweden, which has a rather unique organizational context as they do not have a classic top-down organizational structure and standard working procedure. The inquiry of this study focuses on three aspects; how IQ is perceived under this particular organizational context and the reasons behind it, also whether IQ is context sensitive in this type of organization. A mixed methods research was performed as the research methodology. A questionnaire was firstly sent out to the participants, and then interviews were followed up in order to obtain more detailed information. The contribution includes an account on a new perception on IQ under this specific organizational setting, and why it is perceived in such a way. Also the answer to whether IQ is context sensitive in this kind of organization is argued. Further secondary findings on the issues raised from the applied questionnaire are presented, as they are unexpectedly uncovered but worth attention for future IQ studies. This study presents a new angle of perceiving IQ, which offers certain reference value to future relevant studies.

This study analyzes the impact of information quality on option returns. I find that firms with low-quality information have call option returns that are significantly lower than firms with high information quality. The findings hold in- and out-of-sample, over different time periods, and are robust to a battery of asset pricing tests. The results suggest that the risk caused by poor information quality has a powerful and non-diversifiable impact on the expected returns of option contracts. Further analysis shows that these results are important when examining the cross-sectional link between stock returns and information quality. Firms with low information quality and equity that is "option-like" have significantly lower future stock returns than firms with high information quality. If this option-like effect is not controlled for in empirical tests, the association between information quality and the cross-section of stock returns is often flat. This is especially true for accounting-based proxies of information quality.

This study analyzes the impact of information quality on option returns. I find that firms with low-quality information have call option returns that are significantly lower than firms with high information quality. The findings hold in- and out-of-sample, over different time periods, and are robust to a battery of asset pricing tests. The results suggest that the risk caused by poor information quality has a powerful and non-diversifiable impact on the expected returns of option contracts. Further analysis shows that these results are important when examining the cross-sectional link between stock returns and information quality. Firms with low information quality and equity that is "option-like" have significantly lower future stock returns than firms with high information quality. If this option-like effect is not controlled for in empirical tests, the association between information quality and the cross-section of stock returns is often flat. This is especially true for accounting-based proxies of information quality.

This dissertation consists of two essays, in which I examine the effects of incomplete or noisy information on expected risk premium in equity markets. In the first essay I provide empirical evidence demonstrating that an information-quality (IQ) factor, built on accrual-based information precision measure, is priced. This result still stands after controlling for factors, such as size, Book-to-Market (B/M) ratio, and liquidity. To explain this empirical observation, I derive a continuous-time model in the spirit of Merton’s (1973) Intertemporal Capital Asset Pricing Model (ICAPM) to examine how systematic IQ risk affects security returns. Unique to my model, imprecise information influences the pricing of an asset through its covariance with: (i) stock return; (ii) market return; and (iii) market-wide IQ. In equilibrium, the aggregate effect of these covariance terms (proportional to IQ-related betas) represents the systematic component of IQ risk and therefore requires a risk premium to compensate for it. My empirical test confirms that the aggregate effect of systematic IQ risk is significant and robust to the inclusion of other risk sources, such as liquidity risk. In the second essay I extend a recent complete information stock valuation model with incomplete information environment. In practice, mean earnings-per-share growth rate (MEGR) is random and unobservable. Therefore, asset prices should reflect how investors learn about the unobserved state variable. In my model investors learn about MEGR in continuous time. Firm characteristics, such as stronger mean reversion and lower volatility of MEGR, make learning faster and easier. As a result, the magnitude of risk premium due to uncertainty about MEGR declines over learning horizon and converges to a long-term steady level. Due to the stochastic nature of the unobserved state variable, complete learning is impossible (except for cases with perfect correlation between earnings and MEGR). As a result, the risk premium is non-zero at all times reflecting a persistent uncertainty that investors hold in an incomplete information environment.

This dissertation consists of two essays, in which I examine the effects of incomplete or noisy information on expected risk premium in equity markets. In the first essay I provide empirical evidence demonstrating that an information-quality (IQ) factor, built on accrual-based information precision measure, is priced. This result still stands after controlling for factors, such as size, Book-to-Market (B/M) ratio, and liquidity. To explain this empirical observation, I derive a continuous-time model in the spirit of Merton’s (1973) Intertemporal Capital Asset Pricing Model (ICAPM) to examine how systematic IQ risk affects security returns. Unique to my model, imprecise information influences the pricing of an asset through its covariance with: (i) stock return; (ii) market return; and (iii) market-wide IQ. In equilibrium, the aggregate effect of these covariance terms (proportional to IQ-related betas) represents the systematic component of IQ risk and therefore requires a risk premium to compensate for it. My empirical test confirms that the aggregate effect of systematic IQ risk is significant and robust to the inclusion of other risk sources, such as liquidity risk. In the second essay I extend a recent complete information stock valuation model with incomplete information environment. In practice, mean earnings-per-share growth rate (MEGR) is random and unobservable. Therefore, asset prices should reflect how investors learn about the unobserved state variable. In my model investors learn about MEGR in continuous time. Firm characteristics, such as stronger mean reversion and lower volatility of MEGR, make learning faster and easier. As a result, the magnitude of risk premium due to uncertainty about MEGR declines over learning horizon and converges to a long-term steady level. Due to the stochastic nature of the unobserved state variable, complete learning is impossible (except for cases with perfect correlation between earnings and MEGR). As a result, the risk premium is non-zero at all times reflecting a persistent uncertainty that investors hold in an incomplete information environment.

By tradition, archival sciences has emerged in a context with defined information processes, with explicit information producers and custodians to which consumers make requests for the information. In this process, the archival science has developed methods and strategies to preserve authentic and reliable records and by that providing trustworthy information. In an online society, people are using the internet to get information for different purposes. Even though there is no legal obligation to guarantee the authenticity, it is of societal importance that the end users get trustworthy information. In this online context, open data is a trend that is growing fast over the world and it is interesting because its conditions raises many questions regarding authenticity. Since open data is free to reuse, link and combine with other information, and it is preferably in primary format it raises questions about how to maintain the integrity and identity of the information, which is the constituents of authenticity as it is used in this work. The idea in this essay is to discuss challenges with maintaining the authenticity for open data and also identify possible measures to promote authentic open data information on the web, so that the end users get the possibilities to assess its trustworthiness and fit for use. The essay is a qualitative text analyses, with the theoretical base in the InterPARES project results. Open Government Working groups 8 principles and Open Knowledge Foundations definition is discussed, as is also the discussion from other disciplines about provenance on the web, and ideas from digital records forensic. The results indicate that there are great challenges to maintain the authenticity of open data but there are also some solutions. Recorded provenance and traceability are key factors to enable the evaluation of the authenticity. But first the concept authenticity has to be interpreted in a wider sense. There is a need to maintain the authenticity of the parts, the data, in the information. Because the information is used in parts and if the new information created from it will be reliable, it need accurate data with established identity.

Advances in information technology have made a significant influence on healthcare. Among technological breakthroughs, Internet has revolutionized the way people have access to health information. People increasingly use the Internet to search for, exchange and post health information on various types of websites. Internet offers invaluable benefits to its users; nevertheless, this very freedom to post information and the resulting enormous body of information is also one of the major sources of concerns. There have been misgivings about the quality of online health information since the Internet has been introduced. The 'top-down' approaches to control the quality of online health information proved to be neither practical nor desirable. The advent of web 2.0 (read and write version of web) enables user-driven approaches to improve the quality of information through 'bottom-up' approaches. The critical question is what type of bottom-up approach is suitable to provide online users with high quality health information. Drawing on the market design literature, this research proposes a framework to understand and address (improve) the problem of quality of online health information. The research aims to identify the conditions under which a market for exchange of online health information works efficiently and then study the mechanisms to achieve the efficiency conditions and maximise quality. It also highlights the literature gaps for designing an online market that ensure the quality of exchanged health information. The research collected data from question and answer platforms to carry the empirical analysis. One hundred actual question and answers from nine platforms (900 in total) were collected. The quality of health information was determined by medical expert assessors and related design features were collected form Internet. Statistical algorithmic modelling was adopted for data analysis. Supervised learning methods and mainly regression tree method was used to investigate the relationship between design and quality of health information. The study uncovers the mechanisms and design features that are associated with the quality of health information. It reveals the interaction between design features that lead to high quality health information. The results particularly highlight the importance of experts' participation in the platform for increasing health information quality. It also shed light on the importance of financial incentives in enhancing health information quality. Building on the empirical findings, the research proposes four design scenarios of an online health information market and their respective outcome in terms of quality. The research opens a new perspective for researchers on how to tackle the problem of quality of online health information by framing this problem as a 'market design' issue. It provides important design lessons for managers and designers on how to enhance the quality of online health information in their platforms. It gives policy makers empirically supported guidance for recognising and promoting online procedures that lead to production of high quality online health information.

In view of international digitalization and information trend, and to cope with the New 1-9 Curriculum education policy, the Taiwanese increasingly value information technology education development and methods. The researcher integrates Big6 information skills to school base curriculum with topic study process. A new teaching plan consisting two cycles is developed to test on a sample of 35 fourth graders. The researcher demonstrates the first cycle, and the students actively process the second cycle. The two-cycle teaching plan is to train students to utilize Big6 information skills in researches and promote students¡¦ capabilities of team work, demonstration, presentation, and critique. The researcher conducted and analyzed the data based on three sources consisting quantitative measuring tools, records, and reflections. Quantitative measuring tools include information technology usage investigation, information skill level self-check list, and deliberated comment tables. Records involve students¡¦ learning diaries, teacher¡¦s observant diaries and the teams¡¦ self-checked lists. Reflections engage teacher¡¦s and students¡¦ self reflections. The results of this research are as follows: 1. Big6 skills suit to harmoniously utilize in the two-cycle senior topic instruction program. 2. Applying Big6 skills in project-based learning promotes most students¡¦ learning in five areas including Big6 skills in research processes and study methods, topic-related information, research team work skills, information skills, and critically deliberating behavior. 3. Tested sample showed higher motivation in this process. 4. The researcher could acquire the growing expertise, which includes grasping the value of research, promoting the abilities of designing and compiling instruction program, enhancing the skill of applying and integrating the information technology, utilizing ¡§divided teams project-base¡¨ instruction model for research, and creating the students¡¦ accomplishment with accessing diversificately.

Thesis submitted in fulfilment of the requirements for the degree Master of Technology: Information Technology In the Faculty of Informatics and Design at the Cape Peninsula University of Technology / Dealing with information quality issues remains a serious concern for organisations. With the fact that modern organisations generate much higher volumes of information than they did in the past, with more variety and at a higher velocity, this concern is only expected to increase. Information quality is a complex topic and there is no single view shared by stakeholders on the quality of information within an organisation’s value chain and information quality issues experienced by stakeholders are also different. In this study, the topic of information quality is addressed through the following research questions: How do information stakeholders view the quality of information throughout the information value chain of a retail organisation? What kind of information quality issues do business stakeholders experience throughout the information value chain of a retail organisation? And how are stakeholder decisions affected by information quality when producing or consuming information at the different touch points of the information value chain? An interpretive research approach was chosen for this study to explore this complex topic. The research was conducted in two phases. A literature review in which different concepts related to information quality were investigated was the first phase. In the second phase, a specific business case was investigated before findings from the two phases were analysed and discussed In response to the main research questions, the findings of the research indicated that information quality is complex and there is no single view shared by all stakeholders involved in an information value chain.