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Student attritions in tertiary educational institutes may play a significant role to achieve core values leading towards strategic mission and financial well-being. Analysis of data generated from student interaction with learning management systems (LMSs) in blended learning (BL) environments may assist with the identification of students at risk of failing, but to what extent this may be possible is unknown. However, existing studies are limited to address the issues at a significant scale.

This study develops a new approach harnessing applications of machine learning (ML) models on a dataset, that is publicly available, relevant to student attrition to identify potential students at risk. The dataset consists of the data generated by the interaction of students with LMS for their BL environment.

Identifying students at risk through an innovative approach will promote timely intervention in the learning process, such as for improving student academic progress. To evaluate the performance of the proposed approach, the accuracy is compared with other representational ML methods.

The best ML algorithm random forest with 85% is selected to support educators in implementing various pedagogical practices to improve students’ learning.

Theorising from the intersection of supply chain and information systems (IS) literature, this study aims to investigate supply chain integration (SCI) as a multidimensional construct in the context of cloud-based technology and explores the effect of cloud-enabled SCI on supply chain performance, which will eventually improve firm sustainability from a resource-based view (RBV). In addition, the moderating effect of top management is explored.

Using cross-sectional survey data collected from a sample of 105 Australian retail firms, this study used structural equation modelling to test the hypothesised relationship of cloud-enabled SCI with performance in a theoretical model.

Results show that cloud-based technology has positive effect on SCI, and the cloud-enabled SCI is positively related to supply chain performance which eventually influenced firm sustainability. Further, top management intervention moderates the relationship between supplier and internal integration with supply chain performance. But it is found to have no moderating effect on the relationship between customer integration and supply chain performance.

Recognising the potential benefits of emerging cloud-based technologies reported in this study, retail managers need to understand that higher order SCI requires the support of cloud-based technology to improve supply chain performance and firm sustainability.

This research extends prior research of information and communication technologies-enabled SCI and its effect on supply chain performance which overly remains inconsistent. In addition, IS literature abounds with discussion on cloud computing technology per se, and its adoption in supply chain is overly rhetoric. This study fills this gap by conceptualising the multiple dimensions of SCI enabled by cloud-based technology and the way it affects supply chain and firm sustainable performance. Investigating SCI in context of cloud-based technology is a unique contribution in this study. The moderating effect of top management in this decision also adds to the current body of literature.

Significance of Knowledge The functional name of the Holy Quran is ‘huda’, the guiding light. It focuses divine light on each and every object separating thereby the right from the wrong' (al‐furqan). As this is accomplished by dint of knowledge (al‐ 'ilm). All these three guiding elements namely huda, furqan and ilm, are lined‐up by Allah, the Lord Providence (Rabb‐ulalamin), for earthly welfare (hasanah) and other‐worldly salvation (falah) of human beings. In Quranic context, knowledge, therefore, carries a great significance.