Thesis (M.M.S.) - Carleton University, 2005. / Includes bibliographical references (p. 134-140). Also available in electronic format on the Internet.

Thesis (M.S.)--Ohio University, November, 1997. / Title from PDF t.p.

Thesis (D. Min.)--Midwestern Baptist Theological Seminary, 2003. / "May 1, 2003." Includes bibliographical references (leaves 117-118).

Thesis (Ph. D.)--University of Arizona, 1997. / eContent provider-neutral record in process. Description based on print version record.

Thesis (D. Min.)--Midwestern Baptist Theological Seminary, 2003. / "May 1, 2003." Includes bibliographical references (leaves 117-118).

Thesis (Ph. D.)--Duke University, 2007. / Includes bibliographical references.

Do maximizers maximize across decision domains? An assumption underlying the literature on maximizing is that the tendency to strive to make the best choice spans domains. The current research provides a direct test of this assumption by examining the association between trait maximizing and domain-specific maximizing, consisting of maximizing measures in a wide range of decisions (consumer goods, services and experiences, and life decisions). Study 1 tested this association at two different time points in order to minimize common method bias. Study 2 was a highpowered pre-registered cross-sectional replication. Results of both studies showed that trait maximizing was associated with higher maximizing tendencies across all three decision domains. However, in line with prior research suggesting that people generally maximize less in experiential than in material domains, trait maximizing was associated with maximizing in services and experiences significantly less than with maximizing in consumer goods or in life decisions. These results provide empirical support for a central tenet of maximizing theory and suggest useful directions for future research.

This research explores the online purchase decision-making behaviour of consumers by introducing a comprehensive approach that covers two different viewpoints: a) individual-level behaviour and b) market-level behaviour. Individual-level behaviour enhances our understanding of how purchase decision-making processes unfold and whether they differ for different individuals. Drawing from decision analysis and consumer behaviour literature, four segments of online consumers are introduced based on two individual factors: decision making style and knowledge of the product. Archetypal behaviour of each segment is identified addressing variations in the process and process outcome for different groups. In addition, market-level behaviour investigates the actual behaviour of consumers in relation with different retailers in the market; it is based on the aggregated behaviour of 60,000 individuals. Not only behaviour in a particular website but also cross-visiting behaviour of consumers comparing multiple retailers is examined. For this purpose, a multi-level mixed-method approach is designed. Video recording sessions, think-aloud method, interviews and questionnaires are used to capture the dynamic decision-making process, segment consumers and measure the outcome of the process at individual level. Business process modeling approach and an adaptation of path configuration method are selected for modelling the process. Data from an Internet panel data provider, comScore, is analyzed to explore the market-behaviour of consumers visiting multiple retailers. A set of measurement frameworks, that have been developed to fully exploit the research potential of Internet panel data, are designed for this research. Two sectors of banking and mobile network providers are selected; this research methodology enables a much more detailed evaluation of online behaviour and can be applied in other consumer markets.A conceptual model of online purchase decision making is proposed synthesizing theory from three disciplines: consumer behaviour, decision analysis and Information Systems. This model is able to explain the complexities and dynamic nature of real-life decision-making processes. The results of individual-level analysis show that the synthesized model has an enhanced descriptive power. Purchase decision-making processes in the two sectors appear to be highly complex with a large number of iterations, being more unstructured in banking sector. The process is found to be influenced by the both individual characteristics and each segment exhibits a certain typology of behaviour. Behaviour in terms of the way stages are performed is identical across the two sectors; whereas it differs in relation to intensity of decision-making cycles, duration of the process and the process outcome, being a function of product/ market characteristics.The findings of market-level analysis revealed that banking websites are preliminary visited for using online banking services; despite the high portion of visitors, the intensity of research in these websites is low. On the contrary, mobile network providers attract a higher portion of consumers with purchase intentions and enjoy more intensive research. Consumers have a small consideration set in both sectors; and consider certain banks/providers rather than using the accessibility of all alterative on the Internet. It is evident that comparison sites play an important role in both markets affecting the behaviour of online consumers. Finally, the research stresses the use of the Internet as a complementary channel offering specific benefits in each sector.

The purpose of this thesis is to understand how implicit processes determine individual and organisational behaviour in the context of business to business (B2B) decision making. A broad literature review suggests that implicit cognition has a significantly more powerful influence than therefore assumed. The author calls for further research into the motivations driving professional behaviour in B2B situations as new study challenges the classical economic theory of the homo economicus, and focuses on the role of implicit motives as a possible driver. As a first objective, the study attempts to reveal a typical structure of implicit motives based on hierarchy and gender. The second objective is to delineate the interplay between the implicit motives and the decision making process in B2B. The third objective is to examine the consequences and implications for business to business marketing. The methodology is based on an interdisciplinary mixed method approach. To address the gaps in existing knowledge, an experiment and a survey (n=175) in different sectors were conducted. For the analysis, a variety of techniques such as operant motive tests, cluster- and multivariate analysis were employed to analyse the empirical response. Semi-structured qualitative in-depth interviews (n=8) were carried out to detect the consequences and the implications of the new findings for practice. The findings of the research indicate that marketing is much more a selective communication as assumed. The impact of marketing communication is not always consciously perceived by customers and the most part is implicit. In conclusion, there seems to be an interplay between implicit motives and the B2B decision making process. Hypotheses about the interplay of implicit motives and business to business decision making were confirmed in personal, management and group decision experiments. As a contribution to existing theory on the subject, it can be postulated that rational choice in B2B decision making may play a limited role. In addition marketing experts from various industry sectors emphasise the importance and the potential impacts for future B2B marketing. Experts stress the need to reveal the real motivational drivers in marketing communication.

Land is a finite natural resource that is increasingly getting exhausted as a result of land contamination. Land is made up of soil and groundwater, both of which have many functions for which we depend on, including provision of food and water, supporting shelter, natural flood defence, carbon sequestration, etc. Contaminants in land also pose a number of threats to public health and the environment; other natural resources; and have detrimental effects on property such as buildings, crops and livestock. The most effective method of dealing with these contaminants is to cleanup and return the sites to beneficial use. The cleanup process involves making a choice from amongst competing remediation technologies, where the wrong choice may have disastrous economic, environmental and/or social impacts. Contaminated land management is therefore much broader than the selection and implementation of remedial solutions, and requires extensive data collection and analysis at huge costs and effort. The need for decision support in contaminated land management decision-making has long been widely recognised, and in recent years a large number of Decision Support Systems (DSS) have been developed. This thesis presents the development of a Web-based knowledge-based DSS as an integrated management framework for the risk assessment of human health from, and sustainable management of, contaminated land. The developed DSS is based on the current UK contaminated land regime, published guidelines and technical reports from the UK Environment Agency (EA) and Department for Environment, Food and Rural Affairs (DEFRA) and other Government agencies and departments. The decision-making process of the developed DSS comprises of key stages in the risk assessment and management of contaminated land: (i) preliminary qualitative risk assessment; (ii) generic quantitative risk assessment; and (iii) options appraisal of remediation technologies and remediation design. The developed DSS requires site specific details and measured contaminant concentrations from site samples as input and produces a site specific report as output. The DSS output is intended to be used as information to support with contaminated land management decision-making.