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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.

This study proposes a self-regulatory framework to enhance safety performance at the construction stage among building developers.

Extant literature identified 137 potential factors that influence the construction safety performances of building developers. Focus group discussions and interviews were conducted with 11 panels of experts and professionals. The Relative Importance Index (RII) was used to analyse the response feedback described in a similar paper. In this study, the survey tool used was set up with 40 variables grouped into eight latent variables in the framework, which were agreed and certified as “extremely important” by the panel. Based on random sampling, data were collected from 229 valid respondents. Structural equation modelling (SEM) technique using Smart PLS software was then used to analyse the respondent's feedback.

The results show that safety administration and processes, effective communication of safety behaviour, significantly influenced safety performance on a construction site with β values of 0.330 and 0.431 along with t values of 3.005 and 2.547 at p < 0.1, respectively. These factors, among others, provide a distinct approach to understanding and improving on-site construction safety. The study findings will potentially benefit building professionals and other stakeholders by improving awareness of safety practices.

The study may not have covered all possible factors that influence the construction safety performance of building developers. Also, the generalizability and transferability of the research outcome to the construction industry wide use is also limited when reference is made to the characteristics of the research respondents and/or participants. In addition, validation of the framework by five professionals is rather small.

Theoretically, the framework through the identified factors provide a distinct approach to understanding and improving on-site construction safety through voluntary adherence to self-regulatory standard where there are no enforceable laws and regulations to promote safety. The study findings will potentially benefit building professionals and other stakeholders by improving awareness of the health and safety practices of the construction industry.

Many research efforts have developed frameworks and models for construction safety. However, the particularity of these frameworks to countries other than Nigeria requires similar research to be conducted to enhance the safety performance of building developers.

The purpose of this paper is to investigate the impact of four important influencing factors on user satisfaction with an in-house developed ERP module in a large oil and gas company in Saudi Arabia. It explores whether communication campaigns, training, benefits, ease of use (EoU) are key antecedents of user satisfaction, and examine the mediating effects of EoU and benefits on satisfaction.

A questionnaire was developed and distributed to a sample of 104 ERP users who were actively engaged in the ERP system implementation process. The partial least square method was used to test the research model. Baron and Kenny’s approach was used to test the mediating effects.

The proposed research model explained 62.7 percent of the variance in ERP user satisfaction. The results showed that EoU fully mediates the relationship between the training and communications and the benefits. Both EoU and benefits fully mediate the relationship between training and satisfaction and partially mediate the relationship between communications and satisfaction.

The findings of this study imply that training programs and communication campaigns should be designed in such a way that foster the EoU and convey and convince the ERP stakeholders about the benefits and values of ERP systems.

This study extends the understanding of salient factors affecting the ERP satisfaction in a different setting, namely in an oil & gas industry of a developing country. Although academic research of ERP satisfaction is abundant, this study contributes to the field by examining the mediating effects which rarely tackled in the extant research studies.

This study aims to examine the research pattern and growth trends of published research on a unified theory of acceptance and use of technology 2 (UTAUT2) from 2012 to 2019. The study also examines the research scope of UTAUT2 for future researchers.

This study has adopted a bibliometric approach followed by a structured literature review analysis to synthesize the research on UTAUT2 since 2012. In total, 163 documents were analyzed for type of studies, theories and frameworks, methodologies, author wise collaboration, organizations that contributed to the body of knowledge in the UTAUT2 research and journals that published studies in this domain. VOSviewer and Tableau were used for the data visualization, whereas TCCM, which means theory (T), context (C), characteristics (C) and methodology (M) framework is used to propose the future research directions.

The findings reveal research on UTAUT2 is growing. The structured literature analysis of the top 15 cited articles further analyzed the parsimony of new models in detail. In addition, the study highlights the inception by and promoters of UTAUT2 in a separate section. The data for this study was collected by searching the title, abstract and keywords of documents in the Scopus database.

This study is based on research papers, published in the UTAUT2 research area, that have been extracted from the Scopus database by keywords only. Future studies can also perform a meta-analysis of various clusters generated by bibliometric analysis.

This study is useful for practitioners to devise strategies for increasing technology acceptance, adoption and utilization in the times to come.

To the best of the authors’ knowledge, this study is one of the very few and early studies, which examined patterns and growth trends of the UTAUT2 studies with the TCCM framework, to suggest scope for future research studies.