The industrial metaverse enables citizen developers, employees without programming experience, to create virtual objects in immersive environments that can be translated into physical artifacts, and vice versa. However, many AR authoring tools still require advanced programming skills and spatial knowledge. As a result, they are often used primarily by experienced software developers. A Design Science Research approach with three successive design cycles was used in this thesis. The first design cycle addresses the lack of design knowledge related to metaverse content creation, with a specific focus on AR interaction techniques within AR authoring tools. Drawing on literature on AR interaction techniques and Effective Use Theory, we formulated two theoretically grounded initial design principles and evaluated them in a laboratory experiment involving 55 participants. The second design cycle addresses the lack of design knowledge on how to develop AR authoring tools that not only enable citizen developers to create metaverse content effectively, but also strengthen their intention to do so ensuring that the content they create can be used by peers within the industrial metaverse. We validated our proposed three design principles through two laboratory experiments and one case study, involving a total of 127 participants. The third design cycle of this thesis addresses the lack of design knowledge related to the psychological states of users when interacting with authoring tools in the metaverse. The aim was to analyze participants’ motor control movements in a laboratory experiment with 22 participants, in order to predict different psychological states using deception as an illustrative case, given its relevance in the context of the anonymous metaverse. This thesis provides several empirical insights for future authoring tools for the metaverse. First, we provide prescriptive design knowledge for the design of future AR interaction techniques in the application domain of the industrial metaverse for the development of AR instructions, through two theoretically grounded design principles. Second, we highlight the different sources of self-efficacy involved in the creation phase and usage phase of immersive content in the industrial metaverse. Finally, we demonstrate that psychological states such as deception affect users' motor control. The recording and analysis of users’ movements can therefore serve as an indicator of different user behaviors. This thesis makes several contributions to theory and practice. First, we advance the conceptual understanding of the industrial metaverse as a socio-technical system that uniquely integrates virtual and physical environments. Second, this thesis contributes to the SCT literature by contextualizing Social Cognitive Theory within the industrial metaverse. Third, this thesis also contributes to the field of affective computing by introducing the tracking of controller movements in the metaverse as a method for identifying user behavior. Finally, we contribute to the ongoing debate in cognitive psychology on whether truth or deception is the default mode of human communication.
Kay Hönemann (Wed,) studied this question.