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Web archiving is the practice of preserving websites as a historical record. It is a technologically-challenging endeavor that has as its goal the creation of a high-quality archived website that looks and behaves exactly like the original website. Despite the importance of the notion of quality, comprehensive definitions of Information Quality (IQ) in a web archive have yet to be developed. Currently, the field has no single, comprehensive theory that describes what is a high-quality or low-quality archived website. Furthermore, most of the research that has been conducted on web archives has been system-centered and not user-centered, leading to a dearth of information on how humans perceive web archives. This dissertation seeks to remedy this problem by presenting a user-centered grounded theory of IQ for web archives. It answers two research questions: 1) What is the definition of information quality (IQ) for web archives? and 2) How can IQ in a web archive be measured? The theory presented is grounded on data obtained from users of the Internet Archive's Archive-It system, the largest web-archiving subscription service in the United States. Also presented are mathematical definitions for each dimension of IQ, which can then be applied to measure the quality of a web archive.

Boundary spanners-in-practice are individuals who inhabit more than one social world and bring overlapping place perspectives to bear on the function(s) performed within and across each world. Different from nominated boundary spanners, they are practitioners responsible for the 'translation' of each small world's perspectives thereby increasing collaboration effectiveness to permit the small worlds to work synergistically. The literature on Knowledge Management (KM) has emphasized the organizational importance of individuals performing boundary spanning roles by resolving cross-cultural and cross-organizational knowledge system conflicts helping teams pursue common goals through creation of "joint fields" - a third dimension that is co-jointly developed between the two fields or dimensions that the boundary spanner works to bridge. The Copeland and O'Connor Nondeterministic Model of Engineering Design Activity was utilized as the foundation to develop models of communication mechanics and dynamics when multiple simultaneous interactions of the single nondeterministic user model, the BSIP and two Subject Matter Experts (SMEs), engage during design activity in the Problem-Solving Space. The Problem-Solving Space defines the path through the volumes of plausible answers or 'solution spaces' that will satisfice the problem presented to the BSIP and SMEs. Further model refinement was performed to represent expertise seeking behaviors and the physical and mental models constructed by boundary spanners-in-practice during knowledge domain mapping. This was performed by mapping the three levels of communication complexity (transfer, translation and transformation) to each knowledge boundary (syntactic, semantic and pragmatic) that must be bridged during knowledge domain mapping.

During team decision-making practices information is often shared among team members as part of the decision making process. Knowledge sharing involves one team member sharing information so that other team members can encode the knowledge to make their own mental representation of the new information (Huan & Jiang, 2012). Unfortunately, the literature has shown that new information is not always shared between team members during decision making processes (Stasser & Titus, 1985). When teams make decisions without considering all the information available poor decisions can result. This research study tests a team conceptual model derived by Turner (2013) addressing attitudes toward knowledge sharing. Structural equation modeling was conducted to test a portion of Turner’s (2013) team conceptual model. The tested model included the independent variables of psychological safety, team conflict, team cohesion, and transactive memory systems. The dependent variable for the dissertation was knowledge sharing.

Effective supply chain management gains much attention from industry and academia because it helps firms across a supply chain to reduce cost and improve customer service level efficiently. Focusing on one of the key challenges of the supply chains, namely, demand uncertainty, this dissertation extends the work of Zhao, Xie, and Leung so as to examine the effects of forecasting method selection coupled with information sharing on supply chain performance in a dynamic business environment. The results of this study showed that under various scenarios, advanced forecasting methods such as neural network and GARCH models play a more significant role when capacity tightness increases and is more important to the retailers than to the supplier under certain circumstances in terms of supply chain costs. Thus, advanced forecasting models should be promoted in supply chain management. However, this study also demonstrated that forecasting methods not capable of modeling features of certain demand patterns significantly impact a supply chain's performance. That is, a forecasting method misspecified for characteristics of the demand pattern usually results in higher supply chain costs. Thus, in practice, supply chain managers should be cognizant of the cost impact of selecting commonly used traditional forecasting methods, such as moving average and exponential smoothing, in conjunction with various operational and environmental factors, to keep supply chain cost under control. This study demonstrated that when capacity tightness is high for the supplier, information sharing plays a more important role in effective supply chain management. In addition, this study also showed that retailers benefit directly from information sharing when advanced forecasting methods are employed under certain conditions.

Due to rapid environmental change, today's business requires a more collaborative management to ensure positive performance. One of the important means that can help firms adapt successfully to a changing environment is knowledge management. The management of information and knowledge as key to retaining competitive advantage and has recently evolved into a more strategically focused research topic for both business and academic study. Managing knowledge, however, is deemed difficult because many companies recognize the importance of their proprietary knowledge and are not willing to share it freely. Recognizing this weakness, many countries have promoted the development of regional clusters where firms can co-develop their competences and competitive advantage against the world's best competitors by sharing knowledge, resources, and innovative capabilities. Other than industrial clusters, trust is also considered an important factor in knowledge management study. Trust reduces the need to monitor others' behaviors, formalize procedures, and it lowers transaction costs. At the macro level, trust can enhance organizations' core competencies and sustain their competitive advantages through co-evolution. This may occur through the development of group collaborations, cooperative relationships, and networks. The study adopted a field survey research method and used multiple regressions as the data analysis technique. The dependent variable in the study was organizational adaptation, while the independent variables were knowledge management, trust and industrial cluster. Data were collected using survey of key informants from 943 companies. The results of the analysis suggested that knowledge management does have significant influence on organizational adaptation and both industrial cluster and trust impact on organizational learning activities. The major contribution of this study is that it offers a more holistic approach in studying knowledge management by adding a new element: knowledge applying. Moreover, this study offers an initial attempt to test industrial cluster in hopes of advancing the research in management related fields.

Converting individual knowledge into organizational knowledge can be difficult because individuals refuse to share knowledge for a number of different reasons. Creating an atmosphere of fairness plays an important role in the creation of a knowledge-sharing climate. This dissertation proposes that perceptions of organizational justice are crucial building blocks of that environment, leading to knowledge sharing. Data was collected using a field survey of IT managers representing a broad spectrum of the population in terms of organizational size and industry classification. The survey instrument was developed based on the adaptation of previously validated scales in addition to new items where no existing measures were found. Hypotheses regarding the influence of distributional, procedural, and interactional justice on knowledge sharing processes were tested using structural equation modeling techniques. Based on the theory of reasoned action, which states that attitudes and subjective norms are the major determinants of a person's intention, the hypotheses examining the relationship between attitude toward knowledge sharing, subjective norm and the intention to share knowledge were supported. However, results did not support the hypothesis exploring the relationship between the organizational climate and the intention to share knowledge. The results show that all three types of justice constructs are statistically significant antecedents of organizational climate and interactional justice is an antecedent of an attitude toward knowledge sharing. The study attempts to merge streams of research from sociology and organizational behavior by investigating organizational justice and knowledge management. It contributes to theory by the development of the survey instrument, comprised of seven constructs that were developed by incorporating multiple theories to address various aspects of knowledge sharing and provide application to practice and research. It is relevant to IT managers who need to know how to design information systems that are most effective in distributing knowledge throughout organizations.

Knowledge management is a major concern for organizations today, and in spite of investments in technology, knowledge transfer remains problematic. This study sought to determine whether a relationship exists among participant group demographics (experience), implementation of an integrated knowledge transfer system (best practices model), knowledge transfer barriers, and knowledge transfer project (Web-based training) outcome in a virtual organization. The participant organization was a network of individuals and groups who practice patient advocacy in the research and treatment of cancer. These advocates volunteer in various capacities and are not collocated nor do they report to any single organizational entity. Volunteer participants were randomly assigned to a treatment or control condition. The treatment participants received a training supplement based upon a best practices knowledge transfer model. All participants reviewed a Web-based communications training module scheduled for deployment by the participant organization. Upon completion of the training program, participants were instructed to practice specific techniques from the program. At the end of this period, participants completed an online survey that measured demographics, perceived barriers to the knowledge transfer, and project outcome. Knowledge transfer barriers were defined as knowledge, source, recipient, and organizational context characteristics that inhibit the expected transfer. Project outcome was a composite score of items measuring completion time, budget, and satisfaction of the user. Multiple regression identified two significant predictor variables, source (the training program and implementation) and experience (amount of time spent in advocacy practice). Additional analyses found knowledge (causal ambiguity and unproven knowledge) and the experimental treatment condition to show a strong relationship with the explained variance of the dependent variable, knowledge transfer project outcome. Results suggest that an online training implementation is a valid tool for certain specific transfer design characteristics. Experience was a negative predictor of outcome, suggesting that participant-specific level of training material may produce improved outcome. Furthermore, knowledge in the form of evidence that the material is useful as well as explanation of the cause and effect linkage is a factor in a more successful transfer. Finally, the application of a knowledge transfer system designed around organization-specific variables shows promise as a factor in enhanced knowledge transfer in Web-based training in virtual organizations. Further research is suggested to provide additional insight into the predictive value of these variables.

The Analytic Hierarchy Process (AHP) is a multi-attribute decision making method that structures a decision problem hierarchically in terms of its objective, attributes, sub-attributes, and alternatives.