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While Augmented Reality (AR) glasses are now instrumental in industries for delivering work-related information, the current one-size-fits-all information provision of AR glasses fails to cater to diverse workers’ needs and environmental conditions. We propose a framework for harnessing Internet of thing (IoT) and wearable technology to improve the adaptability and customization of information provision by AR. As a preliminary exploration, this short paper develops a multi-modal data processing system for work performance classification in the aviation industry. Using machine learning algorithms for multi-modal feature extraction and classifier construction, this framework provides a more objective and consistent evaluation of work performance compared to single-modal approaches. The proposed analytics architecture can provide valuable insights for other industries struggling to implement IoT and mixed reality. [ABSTRACT FROM AUTHOR]

When encouraging customers to migrate to a digital communication channel, companies often factor age into their targeting strategy. Both the popular press and scholarly work generally believe that younger customers are more likely to opt into communication digitally. However, our empirical evidence from a large-scale field experiment shows that younger customers are not more likely to migrate to a digital communication channel. Besides, we propose two IT-embodied factors to better target customers in the context of digital communication, namely individual digital activeness and information seeking intensity. We find that customers with higher individual digital activeness, or those with lower information seeking intensity, are more likely to migrate to a digital communication channel. Our study thus offers implications for companies to focus more on customer IT-embodied characteristics instead of age. [ABSTRACT FROM AUTHOR]