Purpose In this invited paper, the authors aim to offer an integrated marketing communications (IMC) framework for understanding how disparate customer touchpoints impact consumer engagement and profitability in an omni-channel environment. For each aspect of the framework, the authors recommend areas for further research. Design/methodology/approach The authors review literature linking personal and electronic channels of communication in an omni-channel context to consumer engagement, with an emphasis on channel and message unity. Findings Five major research areas were identified: research that better links omni-channel and IMC theory and practice; conceptual and empirical research that helps operationalize the consumer-brand engagement construct, including its antecedents and consequences; Build understanding of off- and on-line consumer-brand touchpoints and how they may enhance engagement and profitability; how omni-channel IMC best monetizes buyer–seller relationships; and omni-channel IMC in other consumer decision contexts. Practical implications The emergence of omni-channel marketing is breaking down the silos across available consumer-brand touchpoints. The intersection of effective omni-channel marketing and IMC strategic and tactical initiatives offers marketers an opportunity to engage their customers and to form profitable relationships. Originality/value The authors proposed an omni-channel IMC Framework and a research agenda for advancing the field. As this is a new area of inquiry, the authors argue for the development of other comprehensive frameworks, both for general omni-channel IMC conceptualizations.

Purpose The purpose of this study is to investigate the relationships that influence the value co-creation process and lead to consumer comfort with artificial intelligence (AI) and mobile banking (AIMB) service platforms. Design/methodology/approach A conceptual model was developed to investigate the value-in-use perceptions of AI-based mobile banking applications via five antecedents: baseline perceptions of current bank service delivery; service delivery configuration benefits; general data security; safety perceptions of specific mobile banking services; and perceptions of AI service delivery. Data were collected from 218 respondents and analyzed using structural equation modeling. Findings This study highlights the role and importance of the sequential relationships that impact the assessment of AIMB. The findings suggest that service delivery and the customer’s role in value co-creation change as AI is introduced into a digital self-service technology channel. Furthermore, AIMB offers transaction-oriented (utilitarian) value propositions more so than relationship-oriented (hedonic) value propositions. Research limitations/implications The sample consisted on digital natives. Additional age cohorts are needed. Practical implications As financial institutions redirect their business models toward digital self-service technology channels, the need for customers to feel comfortable while interacting with an AI agent will be critical for enhancing the customer experience and firm performance. Originality/value The authors extend the service-dominant logic (SDL) literature by showing that value co-creation is a function of both firms’ technologies and consumers’ value-in-use, a finding that appears to be unique in the literature. The authors advance the digital transformation literature by evaluating AIMB as an interactive process that requires an understanding of key technology constructs, including perceptions of baseline service relationships, desired service configurations, security and safety issues and whether AI is useful for value co-creation. To the best of the authors’ knowledge, this is the first SDL framework that investigates interactive and structural relationships to explain value-in-use perceptions of AIMB.

Purpose Innovative firms have rapidly developed artificial intelligence (AI) capabilities into their service ecosystems, essentially changing perceptions of what is service quality and service delivery in their respective industries. Nonetheless, the issues surrounding AI services remain relatively unknown. The purpose for this paper is to offer a digital servitization framework for understanding how AI services impact value perceptions, consumer engagement and firm performance measures. The authors use the financial service ecosystem to explore this topic. Design/methodology/approach The authors explore relevant literature on digital servitization, service-dominant logic and AI/disruptive innovation. Next, a conceptual framework, organized by AI-Service Exchange Antecedents, Context of AI Usage and Digital Servitization Consequences, is developed. The authors conceptualize consequences for consumers and firms. Findings The main findings suggest that the linkages between consumers, financial institutions and fintech companies with AI usage in a service ecosystem should be identified; how value is created among multiple SD Logic-AI network actors should be analyzed; and the effects of AI-consumer interactions (lower-level and higher levels of engagement) on firm performance measures should be explored. Research limitations/implications The conceptual framework identifies gaps in the literature and suggests research questions for future studies. Practical implications This paper may assist practitioners with the development of AI-enabled banking activities that involve direct consumer engagement. Originality/value To the authors’ best knowledge, this research agenda is the first comprehensive framework for understanding value co-creation in the context of AI in financial services, linking antecedents, usage and consequences.

Purpose The rapid growth of technology, including artificial intelligence (AI), in the banking industry has played a disrupting role in traditional banking channels. This study aims to investigate factors that influence the attitudes and perceptions of digital natives pertaining to mobile banking and comfort interacting with AI-enabled mobile banking activities. Design/methodology/approach Data were collected from 218 digital natives. This paper uses multivariate regression and two separate multiple regression analyses to examine the differential effects of technology-based (i.e. attitudes toward AI, relative advantage, perceived trust and security in specific mobile banking activities) and non-technology based (i.e. need for service, quality of service) factors on mobile banking usage and AI-enabled mobile banking services. Findings This study identifies determining factors for mobile banking and AI-enabled mobile banking services. Results indicate a divide in how digital natives perceive relative advantage between our two dependent variables. Consistent with previous studies, the relative advantage construct has the most impact on mobile banking usage. However, relative advantage was not significant for AI-enabled mobile banking, suggesting an extra layer of complexity that goes beyond convenient fast banking. Research limitations/implications A limitation of this study is that it does not incorporate age groups outside of digital natives. Further research is needed to test for differential effects between age groups. In addition, the discovery of no significant impact of relative advantage on AI mobile banking warrants more research on the similarities and differences between mobile banking and AI-enabled mobile banking. Practical implications To better appeal to digital natives, it is suggested that the banking industry emphasize mobile banking’s anywhere/anytime access to financial accounts, as this is important to college-age customers who may not live near their local banking institution. Moreover, the paper suggests that improvement to mobile banking features for one-on-one interpersonal contact with bank employees is needed. Originality/value This study addresses the gap in the understanding of how digital natives perceive mobile banking in comparison to AI-enabled mobile banking services.

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