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Development of a Travelers' Information Search Behavior Model
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In the dynamic global environment of today, understanding how travelers acquire information is important for marketing management decisions (Srinivasan 1990; Wilkie and Dickson 1985). For destination marketing managers, understanding information search behavior of travelers is crucial for designing effective marketing communication campaigns because information search represents the primary stage at which marketing can provide information and influence travelers' vacation decisions. Therefore, conceptual and empirical examinations of tourist information search behavior have a long tradition in tourism marketing literature (Etzel and Wahlers, 1985; Fodness and Murray, 1997, 1998, 1999; Perdue, 1985; Schul and Crompton, 1983; Snepenger and Snepenger 1993; Woodside and Ronkainen, 1980). Even though several studies examined travelers information search behavior and the factors that are likely to affect it, they all examined travelers' prior product knowledge as a uni-dimensional construct, most often referred to as destination familiarity or previous trip experiences (Woodside and Ronkainen, 1980). However, consumer behavior literature suggests that the prior product knowledge is not a uni-dimensional construct (Alba and Hutchinson). Alba and Hutchinson (1987) propose that prior product knowledge has two major components, familiarity and expertise, and cannot be measured by a single indicator. In addition, in tourism, little research has been done on the factors that are likely to influence travelers' prior product knowledge and, therefore, their information search behavior. The purpose of this study is to examine travelers' information search behavior by studying the effects of travelers' familiarity and expertise on their information search behavior and identifying the factors that are likely to influence travelers' familiarity and expertise and their information search behavior. A travelers' information search behavior model and a measurement instrument to assess the constructs of the model were designed for the use of this study. The model proposed that the type of information search (internal and/or external) that is likely to be utilized will be influenced by travelers' familiarity and expertise. In addition, travelers' involvement, learning, prior visits and cost of information search are proposed to influence travelers' familiarity and their information search behavior. Even though a very complex travelers' information search behavior model was proposed, only the effects of travelers' prior product knowledge (familiarity and expertise) on travelers' information search behavior were empirically tested due to the complex nature of the model. First the proposed measurement scales were pretested on 224 consumers. After making sure that proposed measures of each construct were valid and reliable, a survey of 470 consumers of travel/tourism services who reside in Virginia was conducted. Structural Equation Modeling (i.e., LISREL) analysis was performed to test the fit of the model. Results of the study confirmed that travelers' prior product knowledge has two components, familiarity and expertise, and expertise is a function of familiarity. Both familiarity and expertise affect travelers' information search behavior. While the effect of familiarity on internal search is positive and on external search is negative, the effect of expertise on internal search is negative and on external search is positive. The study identified a U-shaped relationship between travelers' prior product knowledge and external information search. At early stages of learning (low familiarity), travelers are likely to rely on external information sources to make their vacation decisions. As their prior product knowledge (familiarity) increases they tend to make their vacation decisions based on what is in their memory, therefore, reliance on external information sources decreases. However, as they learn more (become experts), they realize that they need more detailed information to make their vacation decisions. As a result, they start searching for additional external information to make their vacation decisions.