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The theme park industry has experienced steady growth for many years, and it has developed into a global phenomenon. Monitoring visitor satisfaction is critical to help ensure a satisfying overall experience, customer value, and repeat visits. Here, we examine ten years of customer satisfaction tracking data collected at a major US theme park. The study focuses on identifying significant factors influencing customer evaluation of and satisfaction with the overall theme park experience. The key findings reveal that visitors evaluate the theme park primarily on overall park experience and value, park food quality, value, and variety, and park cleanliness and atmosphere. Satisfaction with the total cost of the park visit is primarily predicted by perceptions of the admission price/value, general enjoyment, and customer expectations of the experience. Additional findings concerning the important role of expectations and prior park experiences in visitor satisfaction are detailed. [ABSTRACT FROM AUTHOR]

Attracting both tourists and local consumers, art museums are an important part of the U.S. hospitality and tourism industry. In light of rapidly increasing operating costs and decreasing funding, U.S. art museums have begun more market-oriented efforts to broaden their appeal and accessibility, thereby increasing awareness and visitation. These nonprofit organizations compete broadly with other leisure activities for consumers' discretionary time. Here, a recently developed model of service convenience is used as the theoretical framework for our exploration of important art museum services and components of service convenience. Four focus group discussions were conducted among art museum visitors. The findings suggest that various factors influence decision, access, and transaction convenience, which, in turn, influence the overall perceptions of service convenience. Hypotheses and a conceptual model are developed and discussed, along with future research directions. [ABSTRACT FROM AUTHOR]

Analysis of covariance (ANCOVA) integrates analysis of variance (ANOVA) and regression. The basic advantages of ANCOVA over ANOVA are: (1) generally greater power, and (2) reduction in bias caused by differences between groups that exist before experimental treatments are administered. ANCOVA has numerous possible applications in the evaluation of simulation output, especially where the values of covariates are not known until after the simulation experiment is completed. These covariates are uncontrolled experimental variables that influence the response but are themselves unaffected by the experimental factors. This paper provides an application of multiple analysis of covariance (MANCOVA) to a simulation experiment to determine whether an intermodal transfer and blending facility should add commodity handling and storage capacity. A discrete simulation model of the plant generated cash flows from several proposed capital projects. These cash flows indicated that capacity expansion was a prudent decision. However, when the treatment means for the various combinations of additional capacity were adjusted by MANCOVA for the same levels of operating volume and scheduling performance, the adjusted cash flows produced unacceptable financial returns. In this example, the increased precision of the MANCOVA model suggested that plant management should not invest in additional storage and commodity handling capacity. [ABSTRACT FROM AUTHOR]