Augmented Play Spaces (APS) are (semi-) public environments where playful interaction isfacilitated by enriching the existing environment with interactive technology. APS canpotentially facilitate social interaction and physical activity in (semi-)public environments. Incontrolled settings APS show promising effects. However, people’s willingness to engagewith APSin situ, depends on many factors that do not occur in aforementioned controlledsettings (where participation is obvious). To be able to achieve and demonstrate thepositive effects of APS when implemented in (semi-)public environments, it is important togain more insight in how to motivate people to engage with them and better understandwhen and how those decisions can be influenced by certain (design) factors. TheParticipant Journey Map (PJM) was developed following multiple iterations. First,based on related work, and insights gained from previously developed andimplemented APS, a concept of the PJM was developed. Next, to validate and refinethe PJM, interviews with 6 experts with extensive experience with developing andimplementing APS were conducted. Thefirst part of these interviews focused oninfluential (design) factors for engaging people into APS. In the second part, expertswere asked to provide feedback on thefirst concept of the PJM. Based on the insightsfrom the expert interviews, the PJM was adjusted and refined. The Participant JourneyMap consists of four layers: Phases, States, Transitions and Influential Factors. There aretwo overarchingphases:‘Onboarding’and‘Participation’and 6statesa (potential)participant goes through when engaging with an APS:‘Transit,’‘Awareness,’‘Interest,’‘Intention,’‘Participation,’‘Finishing.’Transitionsindicate movements between states.Influential factorsare the factors that influence these transitions. The PJM supportsdirections for further research and the design and implementation of APS. Itcontributes to previous work by providing a detailed overview of a participant journeyand the factors that influence motivation to engage with APS. Notable additions are thedetailed overview of influential factors, the introduction of the states‘Awareness,’‘Intention’and‘Finishing’and the non-linear approach. This will support taking intoaccount these often overlooked, key moments in future APS research and designprojects. Additionally, suggestions for future research into the design of APS are given.
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To investigate the digital aspect of travel among vulnerable-to-exclusion groups, Customer Journey Mapping [CJM] was used to gain qualitative and quantitative in-depth knowledge of the experiences of elderly people, low-income citizens, wheelchair users, blind people and women. Due to COVID-19 the developed CJM method questioned participants about past trips over the phone or MS teams. This generated 36 interviews. Main outcomes: the elderly do not struggle with operating ticket machines or transport cards but are insecure about operating apps, finding information and rely on social ties. Low-income participants have good digital capabilities but suffer financial stress and prefer to pay cash. People in wheelchairs plan extensively in advance but receive limited support. Screen readers are crucial for blind people, and 69% of the women felt limited by safety; none of the men did.
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The capacity to deal with digital transformation is a valuable asset for established organizations, and employees play a crucial role in this process. This study contributes to the understanding of employees’ sensemaking of digital transformation in the tour operating industry. Using prior digital transformation research, construal-level theory (CLT), and dynamic change perspectives, our scholarly work focuses on the complexities of organizational change in a digital transformation context. Although employees generally support digital transformation, our findings show that their perceptions change over time across a range of specific challenges experienced during the employee change journey. Our findings stress the importance of adopting a social exchange lens in digital transformation knowledge as this represents deep structure change that might cause well-designed transformation processes to fail. Implications for hospitality and tourism management are discussed.
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