|With the growth of data storage reaching exponential rates, search technologies are critical components of today’s information systems. Understanding how individuals use these search technologies and what individual factors influence success in searching for solutions will allow improved design and training in the use of search technologies. The series of essays in this dissertation strive to address these issues.
Essay 1 explores how motivation dispositions and ethical beliefs effect the selection of alternatives solutions to a problem. This conceptual essay integrates the theories of self-regulatory focus, motivation theory, ethical decision-making, and image theory. By focusing on the errors associated with selecting too many or too few alternatives in a consideration set, a set of eight proposals emerge on how best to avoid these errors. Implications for these theories as well as for practice provide suggestions for empirically testing these proposals and applying the results to managerial contexts.
Essay 2 reports results from an empirical study in how individual regulatory dispositions and context specific beliefs effects on the size of the consideration set in an online auction purchase. Results indicate that self-regulatory focus and trusting stance are important factors in predicting the number of auctions considered in an online auction marketplace.
Essay 3 reports results from two empirical studies examining the differences between a product search and information search. In both studies, dispositional factors were modeled to be antecedent to the number of alternatives considered for a solution. Results indicated that dispositional factors of self-regulatory focus and trusting stance were important in a product search but not in an information search.
Taken together, these three essays offer a new perspective for analyzing human interaction with search technologies. Results suggest design changes to a variety of search technologies that are context specific. Further research can extend these findings and build a better understanding on how to effectively search for information to solve problems in spite of the growing volumes of data.