This study uses global positioning systems (GPS) technology to compare and contrast the behaviour patterns of first-time and repeat visitors to Hong Kong. The use of GPS recorders, coupled with an analysis using Geographical Information System (GIS) software produces highly accurate, fine-grained information concerning the spatial and time–space patterns of the visitors. The study findings build on existing knowledge that first-timers tend to travel more widely throughout the destination while repeat visitors tend to confine their actions to a smaller number of locations. However, the data also revealed that first-timers and repeaters spend different amounts of time at the same attractions and visit during different times of the day. First-time visitors also tend to make one long, extended day trip from the hotel, while repeaters tend to make a number of shorter forays, returning to the hotel intermittently during the day.

In this article, we illustrate the importance of time in understanding theme park visitor activity patterns. The study that is described here made use of the GPS (Global Positioning System) technology to track and record the time–space trajectories of visitors at the PortAventura theme park in Catalonia, Spain. The findings suggest that visitors to theme parks do demonstrate distinct diurnal and intradiurnal mass behavior patterns or rhythms of activity. The investigation of temporal activity patterns holds two main advantages: the first is that compared with spatial activity patterns, it is more straightforward to aggregate, present, and compare temporal patterns; the second is that the external validity of temporal activity patterns is generally higher than that of spatial activity patterns. That is to say that temporal activity patterns are more likely to repeat themselves in other environments. Practical, theoretical, and methodological insights that can be relevant to both researchers and site managers are discussed.

Advances in commercial wearable devices are increasingly facilitating the collection and analysis of everyday physiological data. This article discusses the theoretical and practical aspects of using such ambulatory devices for the detection of episodic changes in physiological signals as a marker for mental state in outdoor environments. A pilot study was conducted to evaluate the feasibility of using commercial wearables in combination with location tracking technologies. The study measured physiological signals for fifteen participants, including heart rate, heart rate variability, and skin conductance. Participants’ signals were recorded during an outdoor walk that was tracked using a Global Positioning System logger. The walk was designed to pass through various types of environments including green, blue, and urban spaces, as well as a more stressful road crossing. The data that were obtained were used to demonstrate how biosensor information can be contextualized and enriched using location information. Significant episodic changes in physiological signals under real-world conditions were detectable in the stressful road crossing but not in the other types of environments. The article concludes that despite challenges and limitations of current off-the-shelf wearables, the utilization of these devices offers novel opportunities for evaluating episodic changes in physiological signals as a marker for mental state during everyday activities including in outdoor environments. Key Words: electrodermal activity, GPS, mental state, stress, wearable.

In this article we introduce the method of sequence alignment and its uses for creating tourist typologies based on temporal and spatial movements through a destination. The sequence alignment method was first developed in the 1980s by biochemists who wished to analyse DNA sequences; it was adapted for use in the social sciences towards the end of the 1990s. Unlike traditional quantitative methods, sequence alignment is concerned with the order (or sequence) of events. Thus, it is well suited for tourism research, as tourism involves the mobility of tourists through time and space. In this study, a database composed of 305 space-time sequences of visitors to Hong Kong was analysed. Data were obtained using global positioning system devices which were distributed among participants. The sequences were aligned using ClustalG, a sequence alignment computer program. The analysis resulted in the identification of various classifications of tourists in Hong Kong based on their time-space patterns.