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.

Over the past decade, there has been a change in the citizen–government relationship. Citizens have moved from a traditional face–to–face communication with their government, to an electronic interaction through the use of e–government systems. Emerging technology has enabled citizens to communicate with their government remotely. However, trust in e–government systems has been a problem. E–government systems lack personal interaction, and this creates resistance and uncertainty. Citizens also have a concern about turning over information to the government due to the concern that the information could be used to harm them. This predictive study was designed to determine citizens’ trust in e–government systems. In Phase one, a key list of e–government’s information quality (IQ) characteristics was developed through literature research, and via an open–ended questionnaire delivered to a focus group of about 20 citizens. After the first phase, key IQ factors that affect trust in e–government systems were determined using Keeney’s approach. IQ characteristics collected from the open–ended questionnaire in the first phase were grouped based on their similarities and categorized based on the four IQ categories proposed by Y. W. Lee (1997). In Phase two, 363 citizens were surveyed via the Internet to determine their level of trust in e–government systems. Exploratory factor analysis (EFA) via principal component analysis (PCA) was used to determine the key IQ factors that affect citizens’ trust in e–government systems. A theoretical model was proposed, and the ordinal logistic regression (OLR) statistical method was used to formulate model and test predictive power. OLR developed the predictive model using IQ factors as the independent variables and trust as the dependent variables. OLR helped determine the relative weight of each of the IQ factors when predicting user’s trust in e–government systems. Based on the results, the three IQ factors: accuracy/dependability, accessibility/completeness, and representational were confirmed to have positive weights on citizens’ trust in e–government systems. Additionally, results demonstrated that two factors – –accessibility/completeness and representational had a significant contribution to trust. Accuracy/dependability showed a positive weight on the dependent variable, trust, but was not a significant contributor to trust. Results from the Mann–Whitney U Test determined that there were no significant differences between males and females on trust in e–government systems. The study makes two important contributions to the Information Systems body of knowledge. First, it investigated the IQ factors that citizens feel are important in e–government systems. IQ is important for information systems success. IQ in e–government systems is important for persuading citizens to trust e–government systems. Second, it investigated key IQ factors contributing to citizens’ trust in e–government systems. Trust in the IQ of e–government systems is crucial to the success of such Web–based technology due to its involvement with most citizenry as users.

Yes / The continuous use of eGovernment services is a de facto for its prosperity and success. A generalised sense of citizens' self-efficacy, expectations, and satisfaction offer opportunities for governments to further retain needed engagements. This study examines the factors influencing citizens' continuance use of eGovernment services. Through the integration of Social Cognitive Theory, Expectation Confirmation Theory, DeLone and McLean IS success model, and E-S-QUAL, a survey of 471 citizens in the UK, engaging in online public services, found that prior experience, social influence, information quality, and service quality, personal outcome expectation, and satisfaction, are significant predictors of citizens' intention to use eGovernment, when they are regulated, through citizens' self-efficacy. The present study extends the roles of pre-adoption and post-adoption by offering a self-regulating process. Therefore, it demonstrates how critical it is for the government's leaders to understand the patterns of the long-term process for electronic systems continually. / There is a corrigendum for this paper at https://doi.org/10.1016/j.giq.2020.101492. Elvira Ismagilova was not included as an author on the original record when she should have been.

There has been much advancement in the field of data and information quality (DIQ) since two decades ago. However, despite a large number of the theoretical and empirical studies in this field, there is a lack of understanding about the mechanisms and dynamics of forming, adjusting and changing organisational users’ (information consumers) assumptions and expectations based on which they perceive the quality of information required for making decision in order to perform a task within an organisational environment. Although it is already known that information consumers perceive the quality of information according to the requirements of the organisational task and the context of use, how the task requirements affect information consumers’ expectations of information quality has been a black-box in the body of literature. The main objective of this research is to contribute to the literature of DIQ by exploring the role of the setting of a task within an organisational context in the formation, development and change of information consumers’ underlying expectations of information quality. Information consumers’ assumptions and expectations are called information quality (IQ) frames by this research. Moreover, this research examines the role of IT artefacts, which are used to support performing the task, in these dynamics. As an organisational task is usually performed by a group, the role of the task group of which information consumers are members is investigated by this research. Having adopted a multi-case study design, this thesis has targeted seven different task groups in seven different organisations from multiple industries. This in-depth qualitative research also employs interviews as the main source of data and documents as the secondary source of data. The collected data and empirical evidence is analysed using the thematic analysis and pattern coding. This study’s theoretical contributions to the body of literature are as follows. Firstly, the findings indicate that information consumers should not be simply categorised into domain-specific experts or novices for understanding the mechanisms that affect their IQ frames. Regarding the domain of the task, an information consumer might have domain-related experience that differentiates him from both an expert and a novice. Moreover, this study found that the organisational-specific experience plays a significant role in these dynamics. Secondly, four different settings of a task within an organisational context have been recognised and the insights have been provided into the likely impact of each setting on IQ frames. The findings show that the setting of a task that affects IQ frames is enforced by the interplay between the degree of situatedness of the task and the degree of its explicitness. Thirdly, this research contends that the role of other members of a task group contributes directly to the setting of a task rather than directly influencing their colleague’s IQ frames. Fourthly, this thesis confirms that the organisational resource limitations and the time pressure, which were already mentioned in the literature, affect how information consumers perceive the quality of information but the empirical evidence reveals that other types of pressure such as the pressure of a competitive market has a similar role, therefore, it is argued that in general the organisational pressure impacts the way information consumers perceive information quality. However, this thesis argues that this influence is mediated by the setting of a task. In other words, the organisational pressure can increase the degree of situatedness of a task within an organisational context. Finally, the findings of this study indicate that information consumers’ interpretation of how an IT artefact enables a task within an organisational context is the key mechanism through which the IT artefact can participate in forming, adjusting or changing their IQ frames. The interpreted type of an IT artefact, its interpreted capabilities, the organisational intervention and the IT support by IT technicians of an organisations are the main four factors that govern the influence of the IT artefact on information consumers’ IQ frames. In addition, the computing environment in which the IT artefact operates in, information consumers’ level of IT knowledge and prior experience of using the IT artefact can be involved indirectly in these dynamics. The theoretical contributions of this research have led to the development of a framework for IQ frames and the underlying dynamics have been explained in detail. In addition to the theoretical contributions, this study has a number of practical implications for organisations and management regarding the importance of the organisational settings in how information quality is judged by organisational users (information consumers).

The improvements of technical documents quality influence the popularity of its relevant product; as the customers do not like to waste their time in the help desk’s queue, they will be more satisfied if they can independently solve their problems through the technical manuals in an acceptable time. Moreover, the cost of support issues will decrease for the product providers. In addition, the help desk team members could have more time to support the rest of unresolved issues in a better-qualified way. To afford the mentioned benefits, we have done the current thesis to estimate the usability of the documents before publishing them. As the result of such prediction, the technical documentation writers could have a goal-driven approach to improve the quality of their products or services’ manuals. Furthermore, as different structural metrics have been observed in this research, the result of the thesis could create an opportunity to have multi-discipline improvement in Information Quality (IQ) process management.

This thesis focuses on investigating the relationship between improvements in information quality and the benefits and performance of e-Government organisations. As information quality is a multidimensional measure, it is very crucial to determine what aspects of it are critical to organisations to help them to devise effective information quality improvement strategies. These strategies are potentially capable of changing government organisational structures and business processes. To develop effective information quality improvement strategies, it is important to explore the relationships between information quality (‘cause’) and organisational benefits and performance (‘effect’). The limited research on information quality and organisations performance focuses on private sectors and pays little attention to governments and public organisations. To the best of the author’s knowledge, there is no single study which covers the relationships between information quality and organisations performance in Kuwait. E-Government success literature has rarely investigated information quality as a contributor to the success of e-Government initiatives. This thesis makes a step forward and contributes to the body of knowledge by examining the nature, direction and strength of the connections between information quality and the success of e-Government initiatives as it proposes and discusses a conceptual model (Figure 3.6) and contextual framework by means of which organisations performance and information quality research can be viewed. This thesis adopts a hypothetic-deductive and inductive approach with mixed methods, to conduct the present study. Quantitative and qualitative methods were then utilised to empirically validate the conceptual framework. The author claims that the relationships between information quality and strategic benefits along with institutional value were in upright agreement. Similarly, both qualitative and quantitative analyses highlighted that improvement in different aspects of information quality can lead to a better organisational image. Usability and usefulness attributes of information quality came on the top of the key influencers on both strategic benefits and institutional value. Furthermore, analyses highlighted some differences among information sharing participants’ views regarding the relationship between constructs investigated in this research. Figure 6.5 presents a revised research model including the new constructs, such as, cost savings, improved decision-making, and increased citizen satisfaction, which have been found to be affected by information quality and affect organisational performance.