Online information seeking behavior: Models of information source selection and information seeker satisfaction

Search engines currently dominate the information seeking market. To be in a better position to compete with search engines, every content website needs to understand 1) the underlying reasons behind source selection and information seekers satisfaction and 2) what can be optimized to gain a competitive advantage. To provide this understanding, this dissertation developed an information source selection model in the market of local information seeking to investigate how different types of information sources were perceived differently and how users utilizing different sources were different.;An online survey was conducted to test the information source selection model. Data analysis results showed that direct experience, involvement, intensity of information seeking, habit strength of using search engines, perceived search skill, perceived ease of use, and perceived trustworthiness were significant in discriminating the three information source types. The data also suggested that even though search engines dominated the market of local information seeking, local information websites still have a chance to compete with search engines. Implementable suggestions and future directions were provided for local information websites.;To further explore what determines information seeker satisfaction, in the second part of this dissertation, the author collected information seekers' recommendation statements. A grounded theory approach was employed to derive an information seeker satisfaction model using the IS success model as the framework. The data analysis results suggested that quality of user-generated content is one of the key factors of information seeker satisfaction and that information topic has a moderating effect on the relationship between the quality and its antecedents. The results also showed that no matter which type of information people sought, they always want to know what other people have experienced. User-generated content enriches content websites and influences information seeker satisfaction. Implementable suggestions were provided for product, health, and local information websites.;The contribution of this dissertation is (1) to contribute to academic research by proposing an information source selection model and by proposing an information seeker satisfaction model (2) to contribute to industry practice by offering insights into people's local information seeking behavior, by identifying factors that impact information seekers satisfaction, and by providing implementable suggestions to the content websites.