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This study examines factors that affect customer lifetime value (CLV) in fast-food restaurants (FFRs) in Jordan. These factors are relational benefits, brand experiences, service quality (SQ), satisfaction, trust and commitment.

An online survey was collected from a sample of 503 respondents. The authors used SPSS to test the constructs' relationships and analyse the data. SmartPLS was used to test the hypotheses.

In contrast to previous studies, not all dimensions of brand experiences and relational benefits had a significant and positive influence on relationship marketing outcomes (satisfaction, trust and commitment). On the other hand, results demonstrated that SQ had a significant and positive influence on relationship marketing outcomes. Furthermore, research reveals that satisfaction, trust and commitment significantly and positively influenced CLV.

Those FFRs that seek to enhance CLV should build solid and sustainable bonds with their customers. This paper concludes by stating its implications, its limitations and the opportunities available for future research.

This study, which is unique in the Middle East, includes essential strategies for managing customer relationship that can be universally applied to improve customer benefits and maximise the performance of businesses.

This study aims to examine the influence of the derived attributes of embedded artificial intelligence-mobile smart speech recognition (AI-MSSR) technology, namely perceived usefulness, perceived ease of use (PEOU) and perceived enjoyment (PE) on consumer purchase intention (PI) through the chain relationships of attitudes to AI and consumer smart experience, with the moderating effect of consumer innovativeness and Generation (Gen) X and Gen Y in fashion retail.

The study employed a quantitative survey strategy, drawing a sample of 836 respondents from Sri Lanka and India representing Gen X and Gen Y. The data analysis was carried out using smart partial least squares structural equation modelling (PLS-SEM).

The findings show a positive relationship between the perceived attributes of MSSR and consumer PI via attitudes towards AI (AAI) and smart consumer experiences. In addition, consumer innovativeness and Generations X and Y have a moderating impact on the aforementioned relationship. The theoretical and managerial implications of the study are discussed with a note on the research limitations and further research directions.

To multiply the effects of embedded AI-MSSR and consumer PI in fashion retail marketing, managers can develop strategies that strengthen the links between awareness, knowledge of the derived attributes of embedded AI-MSSR and PI by encouraging innovative consumers, especially Gen Y consumers, to engage with embedded AI-MSSR.

This study advances the literature on embedded AI-MSSR and consumer PI in fashion retail marketing by providing an integrated view of the technology acceptance model (TAM), the diffusion of innovation (DOI) theory and the generational cohort perspective in predicting PI.