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Present a method to impute missing data from a chaotic time series, in this case lightning prediction data, and then use that completed dataset to create lightning prediction forecasts.

Using the technique of spatiotemporal kriging to estimate data that is autocorrelated but in space and time. Using the estimated data in an imputation methodology completes a dataset used in lightning prediction.

The techniques provided prove robust to the chaotic nature of the data, and the resulting time series displays evidence of smoothing while also preserving the signal of interest for lightning prediction.

The research is limited to the data collected in support of weather prediction work through the 45th Weather Squadron of the United States Air Force.

These methods are important due to the increasing reliance on sensor systems. These systems often provide incomplete and chaotic data, which must be used despite collection limitations. This work establishes a viable data imputation methodology.

Improved lightning prediction, as with any improved prediction methods for natural weather events, can save lives and resources due to timely, cautious behaviors as a result of the predictions.

Based on the authors’ knowledge, this is a novel application of these imputation methods and the forecasting methods.

A major part of knowledge management for knowledge-intensive firms such as professional service firms is the increasing focus on thought leadership. Despite being a well-known term, it is poorly defined and analysed in the academic and practitioner literature. The aim of this article is to answer three questions. First, what is thought leadership? Second, what tensions exist when seeking to create thought leadership in knowledge-based organisations? Third, what further research is needed about thought leadership? The authors call for cross-disciplinary and academic–practitioner approaches to understanding the field of thought leadership.

The authors review the academic and practitioner literature on thought leadership to provide a rich oversight of how it is defined and can be understood by separating inputs, creation processes and outcomes. The authors also draw on qualitative data from 12 in-depth interviews with senior leaders of professional service firms.

Through analysing and building on previous understandings of the concept, the authors redefine thought leadership as follows: “Knowledge from a trusted, eminent and authoritative source that is actionable and provides valuable solutions for stakeholders”. The authors find and explore nine tensions that developing thought leadership creates and propose a framework for understanding how to engage with thought leadership at the industry/macro, organisational/meso and individual/micro levels. The authors propose a research agenda based on testing propositions derived from new theories to explain thought leadership, including leadership, reducing risk, signalling quality and managing social networks, as well as examining the suggested ways to resolve different tensions.

To the best of the authors’ knowledge, they are the first to separate out thought leadership from its inputs, creation processes and outcomes. The authors show new organisational paradoxes within thought leadership and show how they can play out at different levels of analysis when implementing a thought leadership strategy. This work on thought leadership is set in a relatively under-explored context for knowledge management researchers, namely, knowledge-intensive professional service firms.