The effects of chatbots’ attributes on customer relationships with brands: PLS-SEM and importance–performance map analysis

Abstract

PurposeMany firms are investing in digital services to improve customer experiences. Virtual service agents, or “e-service agents” (“e-agents”) such as chatbots, are examples of these efforts. Chatbots are types of virtual-assistant software programs that interact with users through speech or text. This paper aims to investigate whether the perceived hedonic and utilitarian attributes of chatbots can influence customer satisfaction and, consequently, their relationships with brands.Design/methodology/approachData were collected through a questionnaire-based survey among a sample of Italian consumers. A convenience sampling technique was used. Data were then analyzed through Partial Least Squares Structural Equation Modeling to provide a prediction-oriented model assessment. The findings were then complemented with an importance–performance map analysis (IPMA) to gain more detailed insights and actionable guidelines for managers.FindingsThe findings highlighted that the perceived hedonic and utilitarian attributes of chatbots positively influenced customer satisfaction and improved customer relationships with the brands. However, the IMPA highlighted that the performance levels of two most important attributes – system quality and experience with chatbot – could be improved resulting in additional improvements of customer satisfaction.Practical implicationsThis study suggests the importance of firms’ investments in and adoption of e-agents to strengthen consumer–brand relationships and of considering both the hedonic and utilitarian attributes of their e-agents.Originality/valueThis article attempts to enrich and consolidate the growing body of literature concerning the impacts of new technologies – and, specifically, chatbots – in service marketing.

Investigating chatbot users’ e-satisfaction and patronage intention through social presence and flow: Indian online travel agencies (OTAs)

“…The present research work’s focus revolves around the three crucial research questions: first , to study the impact of CUC on e-satisfaction and patronage intention . The study revealed that the usability cues of chatbots highly satisfied their users ( β = 0.48, p < 0.001), validated by other researchers in HCI (Magno and Dossena, 2022; Orden-Mejía and Huertas, 2022; Ruan and Mezei, 2022; Telner, 2021). CUC significantly influenced e-satisfaction, which subsequently impacted patronage intention ( β = 0.66, p < 0.001), contributing to the theoretical literature on chatbots.…”

“…CUC is the most critical construct of the study. Magno and Dossena (2022) highlight the significance of chatbot attributes or cues as vital in influencing e-satisfaction and enhancing customer relationships with businesses. Additionally, Orden-Mejía and Huertas's (2022) findings reveal that chatbot attributes: informativeness, empathy and interactivity predicted satisfaction.…”

Guest editorial: The 24th excellence in services international conference – EISIC conference

“…This article contributes to service management literature by providing suggestions both for scholars who engage in academic research and digital services and software providers. Magno and Dossena (2023) focused on detecting customer satisfaction and users' relationships with brands when they interact with virtual service agents (i.e. chatbots).…”

“…The contributions grouped in this cluster investigate the role that digitalization plays in (1) boosting learning activities for human capital development (Barile et al ., 2023), (2) improving the digital service quality process (Brunetti et al ., 2023), (3) detecting user satisfaction (Magno and Dossena, 2023), (4) service quality practices (Schiavone et al ., 2023), (5) increasing quality assurance of automated hand hygiene monitoring service through the ISO certifications (Ortiz and Karapetrovic, 2023) and (6) fostering antifragility in the context of small and medium-sized service companies (service SMEs) (Corvello et al ., 2023).…”

“…Magno and Dossena (2023) focused on detecting customer satisfaction and users' relationships with brands when they interact with virtual service agents (i.e. chatbots).…”