Understanding the complex and dynamic nature of experiences requires the use of proper measurement tools. As interest grows in the objective measurement of experiences within tourism and hospitality, there is an urgent need to consolidate and synthesize these studies. Thus, this study investigated prevalent objective measurement techniques via a systematic review. We analyzed physiological measures such as electroencephalography (EEG), heart rate variability (HRV), skin conductance (SC), and facial electromyography (fEMG) along with behavioral measures, including eye tracking and location tracking. This review identified 100 empirical studies that employed objective measurement to examine tourism and hospitality experiences over the last decade, highlighting trends, research contexts and designs, and the synergies between different methods. Our discussion on methodological issues and best practices will help researchers and practitioners identify the best tools to capture people’s experiences and promote more standardized practices and comparable findings on studying experiences in tourism and hospitality settings.
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Recent advancements in mobile sensing and wearable technologies create new opportunities to improve our understanding of how people experience their environment. This understanding can inform urban design decisions. Currently, an important urban design issue is the adaptation of infrastructure to increasing cycle and e-bike use. Using data collected from 12 cyclists on a cycle highway between two municipalities in The Netherlands, we coupled location and wearable emotion data at a high spatiotemporal resolution to model and examine relationships between cyclists' emotional arousal (operationalized as skin conductance responses) and visual stimuli from the environment (operationalized as extent of visible land cover type). We specifically took a within-participants multilevel modeling approach to determine relationships between different types of viewable land cover area and emotional arousal, while controlling for speed, direction, distance to roads, and directional change. Surprisingly, our model suggests ride segments with views of larger natural, recreational, agricultural, and forested areas were more emotionally arousing for participants. Conversely, segments with views of larger developed areas were less arousing. The presented methodological framework, spatial-emotional analyses, and findings from multilevel modeling provide new opportunities for spatial, data-driven approaches to portable sensing and urban planning research. Furthermore, our findings have implications for design of infrastructure to optimize cycling experiences.
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Understanding how experiences unfold requires measuring participants' emotions, especially as they move from location to location. Measuring and mapping emotions over space is technically challenging, however. While a number of technologies to record and spatially resolve emotion data exist, they have not been systematically compared. We present emotion data collected at a natural and military heritage site in the Netherlands using three different methods, namely retrospective self report, experience reconstruction, and physiology. These data are applied to three corresponding mapping methods. The resulting maps lead to divergent findings, demonstrating that spatial mapping of emotion data accentuates differences between distinct dimensions of emotions.
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