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This paper attempts to theorise about China’s strategy in combating the coronavirus pandemic with an embryonic framework - 3H (Heart-Head-Hand) framework. By adopting a descriptive approach, the paper introduces the case of coronavirus outbreak in China and how the public health administration coped with it. The 3H framework has been applied to analyse China’s strategy, and the framework’s assumptions are initially tested.

The pandemic case is created based on credible reports, press releases from different respected sources, World Health Organization (WHO) statistics, interview transcripts and broadcasting stations’ video clippings. Interpretive analysis with pragmatism approach has been conducted in analysing the data and information collected. Triangulation, wherever possible, has been done to validate the data and information.

As an exploratory study, its findings show that 3H framework distinguishes the effectiveness of a country’s strategy and practice for combating the pandemic. Countries, which failed to observe the assumed principles of 3H domains tend to have much more infected cases and deaths.

The 3H framework conceptualised a holistic management approach and its assumptions have been initially tested with this pandemic case. The framework shows its predictability value for a country’s pandemic management effectiveness.

This paper aims to assess the application of seven statistical and data mining techniques to second-stage data envelopment analysis (DEA) for bank performance.

Different statistical and data mining techniques are used to second-stage DEA for bank performance as a part of an attempt to produce a powerful model for bank performance with effective predictive ability. The projected data mining tools are classification and regression trees (CART), conditional inference trees (CIT), random forest based on CART and CIT, bagging, artificial neural networks and their statistical counterpart, logistic regression.

The results showed that random forests and bagging outperform other methods in terms of predictive power.

This is the first study to assess the impact of environmental factors on banking performance in Middle East and North Africa countries.