Future Seniors and the Travel Industry

Persons over the age of 55 will soon comprise the majority of the travel industry. The impact of market size and potential is staggering. The author discusses the future senior travel market and provides recommendations for attracting and servicing this group.

Obesity and Air Travel: Weighing Up the Issues

It may soon be the norm for many airline passengers arriving at the check-in desk of any international airline with both stow- away and carry-on luggage to be asked to step onto the weighing scale as the airlines attempt to compete and remain operationally viable in what has become for most a cut-throat and highly litigious operating environment. The author's commentary seeks to highlight a number of the issues surrounding the current impasse. It is also intended to catalyze a more healthy and informed debate aimed at finding an acceptable resolution to this crisis prior to one being imposed which fails to satisfy the needs of either camp.

A Study of Online Hotel Reservations on Asia Pacific-Based, European-Based, and North American-Based Travel Websites

This paper reports a study that examined hotel reservation services on travel websites. Using a systematic search, 90 travel websites were selected with an equal number of North American-based, European-based, and Asia Pacfic-based websites. These regions represent the areas of the world with the most Internet users. Based on the developed framework of information quality, the contents of the selected travel websites were evaluated. Be empirical results indicated that the travel websites achieved different levels of quality in online information, and that North American-based websites performed significantly better in some attributes.

A New Vision: U.S Travel and Tourism Industry

Greg Farmer, U.S. Under Secretary of Commerce for Travel and Tourism, envisions a new proactive role for travel and tourism in the U.S. He has written this article especially for the FIU Hospitality Review.

Demographic, Behavioral and Perceptual Comparisons of U.S Visitor Experience with Group Package Tours and Free Independent Travel to China

U.S. visitor demand for the China travel experience is anticipated to rise significantly through 2105, causing the Chinese government to employ 100 million service providers over the next six years and raising concern about service delivery and perceptions of the on-site China experience. In an effort to better understand these issues concerning U.S. visitors, this study investigated two specific types of U.S. travelers to China: Group Package Tour (GPT) visitors and Free Independent Travel (FIT) visitors. Results indicated that GPT visitors were more likely to be older and have higher household income than FIT visitors. Four trip-related characteristics of GPT and FIT visitors were found to be significantly different, with GPT visitors showing higher levels of satisfaction with the overall China on-site travel experience.

Tequila at Sunrise: Spring Break Travel Motivations and Risk Behaviors of American Students in Acapulco, Mexico

Little research has been completed regarding spring break motivations and behaviors of American students in foreign destinations, specifically in Mexico. This paper looks at push and pull motivations in relation to drug and alcohol consumption and findings indicate greater drug and alcohol use among those who selected “party reputation” and “to go wild” as travel motivations. Binge drinking, sexual activity, and drug use among students on spring break in Acapulco, Mexico were also analyzed and compared to past findings within the United States. Results suggest that students are involved in heavy alcohol consumption and significant drug use. Additionally, high rates of sexual activity occur on spring break and results suggest low condom use, placing students at higher risks for the contraction of sexually transmitted infections.

Díaz-Ayala Library Travel Grants Now Available [Announcement]

This flyer announces the Díaz-Ayala Library Travel Grants for Spring and Summer 2013.

Freeway Travel Time Estimation and Prediction Using Dynamic Neural Networks

Providing transportation system operators and travelers with accurate travel time information allows them to make more informed decisions, yielding benefits for individual travelers and for the entire transportation system. Most existing advanced traveler information systems (ATIS) and advanced traffic management systems (ATMS) use instantaneous travel time values estimated based on the current measurements, assuming that traffic conditions remain constant in the near future. For more effective applications, it has been proposed that ATIS and ATMS should use travel times predicted for short-term future conditions rather than instantaneous travel times measured or estimated for current conditions. This dissertation research investigates short-term freeway travel time prediction using Dynamic Neural Networks (DNN) based on traffic detector data collected by radar traffic detectors installed along a freeway corridor. DNN comprises a class of neural networks that are particularly suitable for predicting variables like travel time, but has not been adequately investigated for this purpose. Before this investigation, it was necessary to identifying methods for data imputation to account for missing data usually encountered when collecting data using traffic detectors. It was also necessary to identify a method to estimate the travel time on the freeway corridor based on data collected using point traffic detectors. A new travel time estimation method referred to as the Piecewise Constant Acceleration Based (PCAB) method was developed and compared with other methods reported in the literatures. The results show that one of the simple travel time estimation methods (the average speed method) can work as well as the PCAB method, and both of them out-perform other methods. This study also compared the travel time prediction performance of three different DNN topologies with different memory setups. The results show that one DNN topology (the time-delay neural networks) out-performs the other two DNN topologies for the investigated prediction problem. This topology also performs slightly better than the simple multilayer perceptron (MLP) neural network topology that has been used in a number of previous studies for travel time prediction.

Correspondence course for travel counsellors : hospitality industry project

The purpose of this paper is to produce a travel counselling course which could be subscribed to by students from Canada and abroad, which, upon completion, would qualify them to work in a travel agency.

Understanding Immigrants' Travel Behavior in Florida: Neighborhood Effects and Behavioral Assimilation

The goal of this study was to develop Multinomial Logit models for the mode choice behavior of immigrants, with key focuses on neighborhood effects and behavioral assimilation. The first aspect shows the relationship between social network ties and immigrants’ chosen mode of transportation, while the second aspect explores the gradual changes toward alternative mode usage with regard to immigrants’ migrating period in the United States (US). Mode choice models were developed for work, shopping, social, recreational, and other trip purposes to evaluate the impacts of various land use patterns, neighborhood typology, socioeconomic-demographic and immigrant related attributes on individuals’ travel behavior. Estimated coefficients of mode choice determinants were compared between each alternative mode (i.e., high-occupancy vehicle, public transit, and non-motorized transport) with single-occupant vehicles. The model results revealed the significant influence of neighborhood and land use variables on the usage of alternative modes among immigrants. Incorporating these indicators into the demand forecasting process will provide a better understanding of the diverse travel patterns for the unique composition of population groups in Florida.