Workplace information literacy and innovative work behaviour: new article in press with the Journal of Documentation

Journal of Documentation 2021 Workplace information literacy: a bridge to the development of Innovative Work Behaviour is a new paper about information-related determinants of Innovative Work Behaviour (IWB). I co-authored this paper with Dr Lyndsey Middleton, drawing on the findings of Lyndsey’s ESRC/Skills Development Scotland-funded doctoral research* completed within the Centre for Social Informatics. The paper was accepted for publication in the Journal of Documentation last week.

The most regularly cited determinants of the development of IWB are organisational culture and leadership, employee skills and aptitudes, access to resources, and training. The aim of the empirical work reported in the paper was to investigate a further set of possible information-related determinants. The main contribution of the study – achieved through the application of theory from Information Science – is the identification of the importance of workplace IL and information sharing to IWB. In particular, we argue that workplace IL may serve as a bridge between workplace learning and the development of IWB.

A further contribution of the research reported in the paper is demonstration of the value of a mixed methods approach to explore IL in workplace contexts. This research is one of few studies on workplace IL that centres on the analysis of both quantitative and qualitative data sets (unlike the majority that rely purely on the analysis of qualitative data).

The full citation of the paper is: Middleton, L. & Hall, H. (2021 in press). Workplace information literacy: a bridge to the development of Innovative Work Behaviour. Journal of Documentation. The full text manuscript is available from the Edinburgh Napier repository.

*We are currently advertising our eighth fully-funded PhD studentship under this scheme. If you are interested in completing a PhD in a super supportive environment in a beautiful city, please see the blog post Fully-funded PhD opportunity: labour market intelligence and machine learning. Applications are due by 4pm Monday 21st June 2021.

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