Assessing advertising in a hierarchical decision model

Many destination marketing organizations in the United States and elsewhere are facing budget retrenchment for tourism marketing, especially for advertising. This study evaluates a three-stage model using Random Coefficient Logit (RCL) approach which controls for correlations between different non-independent alternatives and considers heterogeneity within individual’s responses to advertising. The results of this study indicate that the proposed RCL model results in a significantly better fit as compared to traditional logit models, and indicates that tourism advertising significantly influences tourist decisions with several variables (age, income, distance and Internet access) moderating these decisions differently depending on decision stage and product type. These findings suggest that this approach provides a better foundation for assessing, and in turn, designing more effective advertising campaigns.

General mental ability as moderator of personality traits as predictors of early career success

In this paper, we examine the effects of general mental ability (GMA) and the personality traits defined in the big five model on extrinsic and intrinsic indicators of career success, in a sample of 130 graduates who were in the early stages of their careers. Results from hierarchical regression analyses indicated that GMA does not predict any of the success indicators. In contrast, the combination of GMA and three of the Big Five Personality traits, conscientiousness, neuroticism, and openness, is significantly associated with greater early career success and has incremental predictive validity.

Academic Achievement in Early Adolescence: The Influence of Cognitive and Non-Cognitive Variables

The present study examined the predictive effects of intellectual ability, self-concept, goal orientations, learning strategies, popularity and parent involvement on academic achievement. Hierarchical regression analysis and path analysis were performed among a sample of 1398 high school students (mean age = 12.5; SD =.67) from eight education centers from the province of Alicante (Spain). Cognitive and non-cognitive variables were measured using validated questionnaires, whereas academic achievement was assessed using end-of-term grades obtained by students in nine subjects. The results revealed significant predictive effects of all of the variables. The model proposed had a satisfactory fit, and all of the hypothesized relationships were significant. These findings support the importance of including non-cognitive variables along with cognitive variables when predicting a model of academic achievement.

A demand-driven analysis of tourist accommodation price: A quantile regression of room bookings

Tourist accommodation expenditure is a widely investigated topic as it represents a major contribution to the total tourist expenditure. The identification of the determinant factors is commonly based on supply-driven applications while little research has been made on important travel characteristics. This paper proposes a demand-driven analysis of tourist accommodation price by focusing on data generated from room bookings. The investigation focuses on modeling the relationship between key travel characteristics and the price paid to book the accommodation. To accommodate the distributional characteristics of the expenditure variable, the analysis is based on the estimation of a quantile regression model. The findings support the econometric approach used and enable the elaboration of relevant managerial implications.