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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.

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.

The purpose of this paper is to differentiate the production process within services from the dominant manufacturing-based production process, with the objective of delineating the production process in services and highlighting its implication for service productivity.

This study critically reviewed the extant literature on the production processes in manufacturing and services from a multidisciplinary perspective and proposed a framework for the service production process and its relationship with service productivity.

The production process for services differs from the dominant manufacturing-based production process and entails an input, transformation process and outcome dimensions. Therefore, any advancement in services, particularly the conceptualisation and measurement of service productivity, is dependent on the application of a service-specific production process.

The understanding and delineation of the production process in services would further scholarly understanding of what is means to be productive in services and the impact on the validity of the conceptualisation and measurement of service productivity and other service-related concepts.

The proposed service-based production process can further managerial understanding of the measurement and management of productivity in services.

This paper delineates the production process in services and highlighted its implication for service productivity. This study, therefore, is a step forward in developing service-specific concepts and measures, particularly service productivity.