Personal Mobility Device and User Experience: A State-of-the-art Literature Review

Abstract

Background Personal Mobility Device (PMD) refers to ‘Smart Mobility’ or ‘Micro Mobility’ for one or two persons, and it is appreciated as an environmental-friendly means operated by electric resources (Burns, 2013). According to Transparency Market Research in 2016, the world’s personal transport market is expected to grow two times bigger from 2014 to 2023. In fact, PMD has various product types, competence levels and safety problems, so it cannot help covering many user experiences (UXs). Thus, this study aimed to analyze previous researches about PMD in terms of UX and usability. Method In this study, 160 papers were collected through five search engines with keyword combinations of UX (e.g., user interaction and interface) and PMD (e.g., Segway and electric vehicle). Through two filtering processes, the 19 papers were finally selected, and each was analyzed by the next six criteria; device types, research environments, participants, user experience factors, UX evaluation methodologies, and UX measurement. Results The results showed that Segway was the most common device type rather than electric vehicles, powered wheelchair, proposed product, E-scooter, E-bicycle, and E-bike. In addition, the outdoor environment accounted for the biggest percentage of researches beyond indoor, semi-outdoor, and online survey. People who participated in researches were usually expert and novice, who got used to handle the assigned PMD for each paper. A total of 26 UX factors (e.g., effectiveness, safety, usability, and acceptability) was collected and classified considering each experimental context; safety and usability turned out to be the most two important factors. From the UX methodological view, the PMD were usually evaluated by a questionnaire rather than by objective methods, which enable the participant to give more instinctive reactions and the researchers to gather quantitative data easily. In this way, UX objective measurements on previous researches were categorized into body observation (e.g., body angle on device), usage behavior (e.g., running distance) and compatibility on field (e.g., riding against traffic). Discussion & Conclusion The collected 28 UX factors were classified by a methodology whether it was objective or subjective measure, and it was called the UX factors framework for PMD in this study. First of all, the four main UX factors were determined: usability, satisfaction, acceptability and safety. The rest of 24 UX factors belonged to the corresponding main UX factors. For example, usability included compatibility (objectively measured factors; OMF), effectiveness, device performance, efficiency, and physical load (subjectively measured factors; SMF). Satisfaction included intuitive, customer-services-quality, charging, operability, comfort, predictability, mobility, and maintainability (SMF). Acceptability included compatibility (OMF), aesthetics, device learnability, cost, and training (SMF). Safety included stability, risk behavior (OMF), independency, guard, controllability, security, and testability (SMF). These results implied that most UX factors for PMD were usually measured subjectively rather than objectively. In particular, satisfaction had not been measured objectively even though it plays a significant role in UX factors with usability, acceptability, and safety. In other areas, some researches used objective measurements such as heart rate, EEG, or action log for sensing satisfaction (Gao, 2012; Taylor, 2015), so it is also possible to measure PMD satisfaction using objective methods. In this study, the previous researches about UX and PMD were analyzed to identify the trend of the UX research of PMD. A total of 19 papers were collected and classified by device type, research environment, participants, UX factors, evaluation method, and objective measurements. As a result, it was found that various UX factors were introduced, and the systematized UX factors framework was proposed. Through this UX framework, we expect to apply more objective measurements on UX factors of PMD in future researches.