Search results

A Digital Twin (DT) is a digital replica of an artefact which is updated on real-time or semi–real-time basis. In 2017, Gartner listed DT as one of the top 10 emerging technologies of the year. Since then, there have been numerous attempts to develop architecture and reference models for DTs, and in some studies, DT construction for real-world case studies is reported. This chapter attempts to provide a contextualised background on DT for smart cities. It also discusses various stakeholders involved in devising and/or employing DTs in a smart city. The chapter concludes with a set of recommendations for the training requirements of final DT users.

By virtue of affecting how people perceive and respond to challenges, mindsets are conceivably consequential for, though relatively under-studied, in careers research. This paper thereby highlights the importance of bridging the mindsets and careers literature.

I review literature describing the ontology of mindsets, before reviewing what is currently known about mindsets in the careers domain. This is followed by theorizing about mindset dynamics in pressing career challenges, and providing avenues for future research.

I outline some of the major implications of fixed and growth mindsets as they (potentially) relate to career-relevant cognitions, emotions and behaviors. I also formulate an agenda for future research with regard to what we study, who we study and how we, as scholars, can study mindsets in careers.

This review enables looking back on the state of mindsets and careers research. The theorizing herein about mindset dynamics in careers also invites scholars to look toward exciting research possibilities about how mindsets can shape careers in ways not yet realized.