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The purpose of this paper is to describe the perception of real teamwork and sustainable quality culture as well as success factors for achieving a sustainable quality culture within an organisation, focusing on top management teams (TMTs). An additional purpose is to explore the relationship between real teamwork and sustainable quality culture.

A mixed-methods design focusing on TMTs was used. Four TMTs were open-sampled and located in different parts of Sweden. The data were collected through questionnaires and focus group discussions between April 2022 and December 2022. Follow-up meetings were thereafter held with the participants. A meta-analysis was conducted of the data from the four TMTs.

Two overarching conclusions of this study were: to follow the developed methodology can be one way to increase TMTs' abilities for real teamwork alongside a sustainable quality culture, and the results also showed the importance of a systems view, emotional commitment and continuous improvement for improving real teamwork and creating a sustainable quality culture.

Practical implications were suggestions on how to increase the TMTs' abilities for real teamwork alongside a sustainable quality culture. A deepened understanding of real teamwork and a sustainable quality culture was also achieved by the participants.

The novelty of this paper is the use of a new methodology for assessing teamwork and sustainable quality culture. To the authors' knowledge, no similar research has previously been performed to investigate teamwork alongside a sustainable quality culture, focusing on TMTs.

The purpose was to present a developed, tested and evaluated methodology for assessing teamwork and sustainable quality culture, focusing on top management teams (TMTs).

The developed methodology was based on a convergent mixed-method design, including two data collection methods: questionnaire and focus group discussion. Two pilot tests were performed with two TMTs. This design involved analysing, merging and interpreting data, first separately by data collection method and theme and then in a meta-interpretation. Lastly, there was a follow-up meeting for evaluating results.

Findings from the study were that the methodology can be used to assess teamwork and sustainable quality culture, and the results also showed the strength of using two data collection methods to provide a broader picture of teamwork and sustainable quality culture. A follow-up meeting validated the results and provided additional value to the two TMTs in the form of suggestions on how to improve their teamwork and sustainable quality culture.

Applying this methodology can guide TMTs in how to improve their teamwork and sustainable quality culture within their organisations.

This is a new methodology, containing a developed questionnaire and an interview guide, aiming to assess and evaluate teamwork within TMTs and sustainable quality culture. The practice of the methodology adds value to both TMTs and their organisations, as well as provides a theoretical and methodological contribution to research on teamwork and sustainable quality culture.

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.