In this article, we introduce three-dimensional Serious Games (3DSGs) under an evidence-centered design (ECD) framework and use an organizational neuroscience-based eye-tracking measure to capture implicit behavioral signals associated with leadership skills. While ECD is a well-established framework used in the design and development of assessments, it has rarely been utilized in organizational research. The study proposes a novel 3DSG combined with organizational neuroscience methods as a promising tool to assess and recognize leadership-related behavioral patterns that manifest during complex and realistic social situations. We offer a research protocol for assessing task- and relationship-oriented leadership skills that uses ECD, eye-tracking measures, and machine learning. Seamlessly embedding biological measures into 3DSGs enables objective assessment methods that are based on machine learning techniques to achieve high ecological validity. We conclude by describing a future research agenda for the combined use of 3DSGs and organizational neuroscience methods for leadership and human resources.
Amazon's Mechanical Turk (MTurk) is an online crowdsourcing platform that is part of the digital gig economy, where MTurkers perform fast and repetitive gigs or microwork like taking surveys and performing data transcriptions, and are compensated for each completed task. The purpose of this research is to understand the work- and life-related implications for MTurkers. Drawing from the Psychology of Working Theory (PWT), we examined the role that income and volition play in determining satisfaction and stress among MTurkers. Results revealed that high volition MTurkers had higher job satisfaction, higher life satisfaction, and lower stress than low volition MTurkers. These findings help extend PWT to this contemporary and evolving form of working in the digital gig economy. Management scholars view gig work as an emerging trend and an addition to the list of notable research and practice gaps in organisational behaviour.
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