2026-09-23T10:44:10Zhttps://bura.brunel.ac.uk/oai/request

oai:bura.brunel.ac.uk:2438/79122014-11-01T13:19:35Zcom_2438_23com_2438_58col_2438_168col_2438_3672

O'Keefe, B Hair, Jr, JF Price, D Abril, Raul Mario 2014-01-20T11:11:04Z 2014-01-20T11:11:04Z 2005 http://bura.brunel.ac.uk/handle/2438/7912 This thesis was submitted for the degree of Doctor of Business Administration and awarded by Brunel University on behalf of Henley Management College. 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. iii Submitted by Terese Jonsson (terese.jonsson@brunel.ac.uk) on 2014-01-20T11:10:43Z No. of bitstreams: 1 517935.pdf: 71979774 bytes, checksum: 16671f9d8321702b626c2d34892abdaf (MD5) Approved for entry into archive by Terese Jonsson(terese.jonsson@brunel.ac.uk) on 2014-01-20T11:11:04Z (GMT) No. of bitstreams: 1 517935.pdf: 71979774 bytes, checksum: 16671f9d8321702b626c2d34892abdaf (MD5) Made available in DSpace on 2014-01-20T11:11:04Z (GMT). No. of bitstreams: 1 517935.pdf: 71979774 bytes, checksum: 16671f9d8321702b626c2d34892abdaf (MD5) Teradata, NCR en http://bura.brunel.ac.uk/bitstream/2438/7912/1/FulltextThesis.pdf Customer relationship management Data warehouses Data quality Problem enactment The inner and inter construct associations of the quality of data warehouse customer relationship data for problem enactment Thesis