Purpose The purpose of this paper is to expand current knowledge about the recent trend of wearable technology to assess both its potential in the work environment and the challenges concerning the utilisation of wearables in the workplace. Design/methodology/approach After establishing exclusion and inclusion criteria, an independent systematic search of the ACM Digital Library, IEEE Xplore, ScienceDirect and Web of Science databases for relevant studies was performed. Out of a total of 359 articles, 34 met the selection criteria. Findings This review identifies 23 categories of wearable devices. Further categorisation of the devices based on their utilisation shows they can be used in the work environment for activities including monitoring, augmenting, assisting, delivering and tracking. The review reveals that wearable technology has the potential to increase work efficiency among employees, improve workers’ physical well-being and reduce work-related injuries. However, the review also reveals that technological, social, policy and economic challenges related to the use of wearable devices remain. Research limitations/implications Many studies have investigated the benefits of wearable devices for personal use, but information about the use of wearables in the work environment is limited. Further research is required in the fields of technology, social challenges, organisation strategies, policies and economics to enhance the adoption rate of wearable devices in work environments. Originality/value Previous studies indicate that occupational stress and injuries are detrimental to employees’ health; this paper analyses the use of wearable devices as an intervention method to monitor or prevent these problems. Introducing a categorisation framework during implementation may help identify which types of device categories are suitable and could be beneficial for specific utilisation purposes, facilitating the adoption of wearable devices in the workplace.

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Since the 1950s, artificial intelligence (AI) has been a recurring topic in research. However, this field has only recently gained significant momentum because of the advances in technology and algorithms, along with new AI techniques such as machine learning methods for structured data, modern deep learning, and natural language processing for unstructured data. Although companies are eager to join the fray of this new AI trend and take advantage of its potential benefits, it is unclear what implications AI will have on society now and in the long term. Using the five dimensions of sustainability to structure the analysis, we explore the impacts of AI on several domains. We find that there is a significant impact on all five dimensions, with positive and negative impacts, and that value, collaboration, sharing responsibilities; ethics will play a vital role in any future sustainable development of AI in society. Our exploration provides a foundation for in-depth discussions and future research collaborations.

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Big data is an emerging research area where common terminology is still evolving. Different perspectives to the research area and terminology exist, but a common definition for big data does not exist. We have performed a systematic mapping study in order to identify different big data definitions and their perspectives. As a result, we present a state-of-the-art review of the current status in big data definitions, discuss the shortcomings of the current definitions, and propose possible solutions for the shortcomings. The paper contributes to the emerging big data research by analyzing current definitions of big data from different perspectives, suggesting enhancement to the terminology as well as pointing out new research avenues. In addition, the article helps new researchers and practitioners to understand what big data is, and bridges the knowledge between theory and practice.

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Background Patient safety is key for healthcare across the world and education is critical in improving practice. We drew on existing links to develop the Shared LearnIng from Practice to improve Patient Safety (SLIPPS) group. The group incorporates expertise in education, research, healthcare, healthcare organisation and computing from Norway, Spain, Italy, the UK and Finland. In 2016 we received co-funding from the Erasmus + programme of the European Union for a 3-year project. Aim SLIPPS aims to develop a tool to gather learning events related to patient safety from students in each country, and to use these both for further research to understand practice, and to develop educational activities (virtual seminars, simulation scenarios and a game premise). Study outline The SLIPPS project is well underway. It is underpinned by three main theoretical bodies of work: the notion of diverse knowledge contexts existing in academia, practice and at an organisational level; the theory of reflective practice; and experiential learning theory. The project is based on recognition of the unique position of students as they navigate between contexts, experience and reflect on important learning events related to patient safety. To date, we have undertaken the development of the SLIPPS Learning Event Recording Tool (SLERT) and have begun to gather event descriptions and reflections. Conclusions Key to the ongoing success of SLIPPS are relationships and reciprocal openness to view things from diverse perspectives and cultures.