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The use of innovative technologies by firm employees is a key factor in ensuring the competitiveness of firms. However, researchers and practitioners have been concerned about the willingness of technology end users to use innovative technologies. This study, therefore, aims to determine the factors affecting the intention to use marketing analytics technology.

This study surveyed 213 firm employees. The quantitative data collected was analysed using partial least squares structural equation modelling.

The results reveal that performance expectancy, facilitating conditions, attitudes and perceived trust have a positive and significant effect on intentions to use marketing analytics. Effort expectancy, social influence and personal innovativeness in information technology were found not to predict intentions to use marketing analytics.

This study has practical implications for firms seeking to enhance the use of marketing analytics technology in developing countries.

This study contributes to the use of UTAUT, perceived trust, personal innovativeness and user attitude in predicting the intentions to use marketing analytics technology.

This study examines the factors influencing intention to vaccinate against COVID-19 in a developing country context using the theory of planned behaviour (TPB) and health belief model (HBM).

Through a cross-sectional survey design, the study adopted a quantitative approach to data collection and analysis. The study used an online survey to collect data from 478 respondents eligible to take the COVID-19 vaccine in Ghana.

Attitude, social norm, perceived behavioural control, perceived susceptibility and cues to action were found to be predictors of COVID-19 vaccination intention. The results also showed that perceived severity, perceived benefits and perceived barriers did not predict COVID-19 vaccination intention.

To enhance the effectiveness of COVID-19 social marketing campaigns, social marketing theories such as the TPB and HBM can aid in assessing the intention of the target population to take the vaccines. An assessment of vaccination intention will help understand disease threat perception and behavioural evaluation. The consideration of the effect of demography on vaccination intention will aid in developing effective campaigns to satisfy the needs of segments.

This study adds to the limited research on understanding citizens’ intention to vaccinate against COVID-19 by combining the TPB and HBM to predict vaccination intention. The study contributes towards the use of social marketing practices to enhance the efficacy of vaccination campaigns.

This study aims to examine the factors affecting behavioural intention to use E-learning during the COVID-19 pandemic. The study applies the unified theory of acceptance and use of technology 2 (UTAUT2) to identify the factors that predict intention to use E-learning. Also, the study examines the effect of personal innovativeness in information technology and perceived financial cost on intention to use E-learning.

The study adopted a cross-sectional quantitative study design involving 617 university students. The data was collected through an online survey due to the COVID-19 restrictions. The proposed hypotheses were analysed using partial least squares structural equation modelling.

The study found that personal innovativeness in information technology, perceived financial cost, performance expectancy, hedonic motivation and social influence have a significant effect on the intention to use E-learning. Contrary to expectation, habits, effort expectancy and facilitating conditions did not predict intention to use E-learning.

The study was conducted on university students and did not include other school-going students and working professionals. Also, the study sample was not drawn from many universities. The study used a quantitative approach. The use of a mixed-methods approach could provide deeper insights into the factors affecting the intention to use E-learning in developing countries.

The practical implications inform policymakers and educational institutions on how E-learning adoption can be enhanced. In this context, social influence, performance expectancy, hedonic motivation, personal innovativeness and perceived financial cost are identified as predictors of intention to use E-learning. This study has implications for the development of E-learning systems and the promotion of the use of E-learning in the context of developing countries.

The study is amongst the few studies from a developing economy to use the UTAUT2 model to examine students’ intention to use E-learning. The study proposes the inclusion of personal innovativeness in information technology and perceived financial cost as factors predicting intention to use E-learning. Again, the study adopts importance-performance matrix analysis to provide decisional areas where management may improve for successful E-learning acceptance and use.