Detecting Leadership Opportunities in Group Discussions Using Off-the-Shelf VR Headsets.

The absence of some forms of non-verbal communication in virtual reality (VR) can make VR-based group discussions difficult even when a leader is assigned to each group to facilitate discussions. In this paper, we discuss if the sensor data from off-the-shelf VR devices can be used to detect opportunities for facilitating engaging discussions and support leaders in VR-based group discussions. To this end, we focus on the detection of suppressed speaking intention in VR-based group discussions by using personalized and general models. Our extensive analysis of experimental data reveals some factors that should be considered to enable effective feedback to leaders. In particular, our results show the benefits of combining the sensor data from leaders and low-engagement participants, and the usefulness of specific HMD sensor features.

Sensing the Intentions to Speak in VR Group Discussions.

While virtual reality (VR) technologies enable remote communication through the use of 3D avatars, it is often difficult to foster engaging group discussions without addressing the limitations to the non-verbal communication among distributed participants. In this paper, we discuss a technique to detect the intentions to speak in group discussions by tapping into intricate sensor data streams from VR headsets and hand-controllers. To this end, we developed a prototype VR group discussion app equipped with comprehensive sensor data-logging functions and conducted an experiment of VR group discussions (N = 24). We used the quantitative and qualitative experimental data to analyze participants' experiences of group discussions in relation to the temporal patterns of their different speaking intentions. We then propose a sensor-based mechanism for detecting speaking intentions by employing a sampling strategy that considers the temporal patterns of speaking intentions, and we verify the feasibility of our approach in group discussion settings.

Dynamic simulation of green technology innovation in large construction companies.

The construction sector plays an important role in environmental sustainable development and the green economy. Green technology innovation in the construction sector can improve the energy, cost, and environmental performance of the industry. The lagging effects of influential factors for green technology innovation have yet to be fully understood. This study aims to explore the process of green technology innovation in large construction companies based on the innovation value chain theory and through a system dynamics (SD) approach. The results revealed the dynamic interaction between various influencing factors of green technology innovation in the construction industry. The effects of different knowledge bases and market shares show heterogeneity when the influencing factors are considered as an integrated system. The study helps researchers and practitioners gain a better understanding of the nature of green technology innovation from a systematic view. Suggestions are provided for decision-makers and practitioners to better manage green technology innovation.