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Digital transformations are altering service models and care delivery methods in healthcare. Artificial Intelligence (AI) represents the next wave of transformation in healthcare. This study aims to understand patient perceptions of AI and its impact on value co-creation.

A conceptual model was developed to investigate how value co-creation operant resources (digital self-efficacy and relational service quality) impact value co-creation engagement (shared decision-making) and value co-creation outcomes (anticipatory AI value co-creation and intention to adopt AI). Data were collected from 332 respondents and analyzed using structural equation modeling.

The results indicate that the value co-creation process for AI technologies is a function of inputs, experiences and AI outputs. Operant resources were found to be positively associated with shared decision-making. However, not all operant resources directly and positively impacted AI outcomes. The indirect and positive mediated relationships through shared decision-making to AI outcomes suggest an interactive AI value co-creation process.

AI technologies are still in early stages of consumer adoption in healthcare. Future research is warranted that investigates the validity of the model through maturing service life cycles.

Customer perceptions of new digital innovations are formed in the context of previous digital experiences. Marketers need to understand how customers view their current non-AI technologies. Strong engagement and perceived value of current technologies will help ease customers into the usage of AI technologies.

This study investigates the unique stages of the value co-creation process for AI technologies in healthcare. The results demonstrate that the value co-creation process is a function of inputs, tech-enabled experiences and AI outputs.

Using the lenses of social exchange and reactance theories, this study examines the relationships between abusive supervision and both turnover intentions and job satisfaction. The moderating role of employee depression in the relationship between abusive supervision and these specific work outcomes is also investigated, by incorporating the conservation of resources theory.

Quantitative data were collected from a sample of 221 frontline retail employees, across shopping malls in the Caribbean nation of Trinidad. A 3-step multiple hierarchical regression analysis was performed to test the relationships.

The findings provided support for the propositions that abusive supervision predicts job satisfaction and turnover intentions, respectively. Employee depression moderated the relationship between abusive supervision and job satisfaction but did not moderate the relationship between abusive supervision and turnover intentions.

While existing research has explored the relationships between abusive supervision, job satisfaction and turnover intentions, limited studies have investigated the moderating role of employee depression. This study contributes to understanding this pervasive workplace issue by investigating a relatively unexplored moderating effect.