The literature identifies perceptions of data quality as a key factor influencing a wide range of attitudes and behaviors related to data in organizational settings (e.g. decision confidence). In particular, there is an overwhelming consensus that effective customer relationship management, CRM, depends on the quality of customer data. Data warehouses, if properly implemented, enable data integration which is a key attribute of data quality. The literature highlights the relevance of formulating problem statements because this will determine the course of action. CRM managers formulate problem statements through a cognitive process known as enactment. The literature on data quality is very fragmented. It posits that this construct is of a high order nature (it is dimensional), it is contextual and situational, and it is closely linked to a utilitarian value. This study addresses all these disperse views of the nature of data quality from a holistic perspective. Social cognitive theory, SCT, is the backbone for studying data quality in terms of information search behavior and enhancements in formulating problem statements. The main objective of this study is to explore the nature of a data warehouse's customer relationship data quality in situations where there is a need for understanding a customer relationship problem. The research question is What are the inner and inter construct associations of the quality of data warehouse customer relationship data for problem enactment? To reach this objective, a positivistic approach was adopted complemented with qualitative interventions along the research process. Observations were gathered with a survey. Scales were adjusted using a construct-based approach. Research findings confirm that data quality is a high order construct with a contextual dimension and a situational dimension. Problem sense making enhancements is a dependent variable of data quality in a confirmed positive association between both constructs. Problem sense making enhancements is also a high order construct with a mastering experience dimension and a self-efficacy dimension. Behavioral patterns for information search mode (scanning mode orientation vs. focus mode orientation) and for information search heuristic (template heuristic orientation vs. trial-and-error heuristic orientation) have been identified. Focus is the predominant information search mode orientation and template is the predominant information search heuristic orientation. Overall, the research findings support the associations advocated by SCT. The self-efficacy dimension in problem sense making enhancements is a discriminant for information search mode orientation (focus mode orientation vs. scanning mode orientation). The contextual dimension in data quality (i.e. data task utility) is a discriminant for information search heuristic (template heuristic orientation vs. trial-and-error heuristic orientation). A data quality cognitive metamodel and a data quality for problem enactment model are suggested for research in the areas of data quality, information search behavior, and cognitive enhancements.

Abstract Title: How to assess risks in weak links in cold chain distribution process? Authors: Shuchang Lu, Yufan Gu & Radzion Predko Tutor: Åsa Gustafsson Examiner: Dr. Lars-Olof Rask Course: 4FE06E - Master Thesis Research Questions: • Why do cold chain products have quality risk? -  What kind of weak links exist in distribution process of cold chain? -  What kind of risks exist in weak links of distribution process of cold chain? -  How to assess risks in weak links of distribution process of cold chain? Background: The increasing food wastes and starving people have made food preserved by cold chain as a significant and profitable issue. An effective and efficiency cold chain can make a big difference in the whole food supply chain around the world. With the improvements of modern technologies, cold chain distribution is experiencing changes. Purpose: To identify weak links in distribution channel of cold chain products. What kind of risks exist in these weak inks and how to assess them. Method: Positivistic is used throughout the paper. Multiple exploratory case study is our way of research our problems. Data were gathered from interview, documents and company’s website. Conclusions: Human handling in delivery process, the way retailers deal with frozen products, how do different participants manage their resources and safety of product and its quality are main reasons for quality risk. Risks in weak links can cause product quality problem in cold chain distribution channel. Therefore, assess these risks can help managers to deal with them. Keywords: Cold chain distribution, quality problem, weak link, risk