Lars-Erik Casper Ferm

This study investigates how anthropomorphic language and chatbot schema (a customer’s cognitive framework for understanding and interacting with a chatbot) jointly influence customer electronic word-of-mouth (eWOM). Across two experiments, we examine how anthropomorphic language (such as empathetic language and emojis) impacts customers’ engagement with chatbots. Study 1 provides directional evidence suggesting that anthropomorphic language is associated with greater eWOM when a chatbot schema was active, but not when it is inactive. Study 2 demonstrates that the effects of anthropomorphic language on authenticity and eWOM are contingent on the chatbot’s competence. Together, these findings suggest that linguistic cues may improve chatbot interactions, beyond their visual appearance. This research has implications for marketing practitioners, helping them to formulate effective strategies based on chatbot disclosure and competence.

Purpose: The purpose of this study is to identify, analyze and explain the implications that could arise for service settings if artificial intelligence (AI) systems develop, or are perceived to develop, consciousness – the ability to acknowledge their own existence and the capacity for positive or negative experiences. Design/methodology/approach: This study proposes and explores four hypothetical scenarios in which conscious AI in service could manifest. We contextualize our resulting typology in the health service context and integrate extant literature on technology-enabled service, AI consciousness and AI ethics into the narrative. Findings: This study provides a unique theoretical contribution to service research in the form of a Type IV theory. It enables future service researchers to apprehend, explain and predict how functionally conscious AI in service might unfold. Practical implications: The ethical use of conscious AI in service could emerge as a distinct competitive advantage in the future. Achieving this outcome involves speculative yet actionable recommendations that include training, guiding and controlling how humans engage with such systems; developing appropriate wellbeing protocols for functionally conscious AI systems and establishing AI rights and governance frameworks. Originality/value: An increasingly prolific public discourse acknowledges that conscious AI systems may emerge. Against this backdrop, this study aims to systematically explore a question that is perhaps the most critical and timely, but also inherently speculative, in relation to AI in service research by introducing much-needed theory and terminology.

Consumer financial decisions, traditionally viewed as rational, are increasingly recognized as being influenced by emotions and intuition. This study examines how imagery and emotions in financial contexts influence decision‐making, specifically in hypothetical loan approvals where loan application documents include carefully selected imagery. Using a mixed‐method approach, including neuromarketing methodologies such as eye‐tracking and galvanic skin response (GSR), and a between‐subjects experimental design utilizing self‐report data, this study provides unique and granular insights into financial decision‐making. In Study 1, respondents were individuals with 2 years of relevant education and business experience who were expected to apply for business loans themselves in the near future. Results indicate, via neuromarketing measures, that emotions, when influenced by imagery, take precedence over financial data in decision‐making. Men (vs. women) respondents were more (vs. less) likely to approve applications with positive imagery. In Study 2, self‐reported data revealed a discrepancy between emotional responses and self‐reports across 320 participants. Overall, the results (1) show that specific imagery can influence loan approvals and (2) provide further evidence to the extant literature on the role of emotions in decision‐making in an often perceived “calculative” financial context.

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Purpose: Artificial intelligence (AI) has become a pivotal technology in both marketing and daily life. Despite extensive research on the benefits of AI, its adverse effects on customers have received limited attention.Design/methodology/approach: We employed meta-analysis to synthesise effect sizes from 45 studies encompassing 50 independent samples (N = 19,503) to illuminate the negative facets of AI's impact on customer responses.Findings: Adverse effects of AI, including privacy concern, perceived risks, customer alienation, and uniqueness neglect, have a negative and significant effect on customers' cognitive (perceived benefit, trust), affective (attitude and satisfaction) and behavioural responses (purchase, loyalty, well-being). Additionally, moderators in AI (online versus offline), customer (age, male vs. female), product (hedonic vs. utilitarian, high vs. low involvement), and firm level (service vs. manufacturing) and national level (individualism, power distance, masculinity, uncertainty avoidance, long-term orientation) moderate these relationships.Practical implications: Our findings inform marketing managers about the drawbacks of utilising AI as part of their value proposition and provide recommendations on how to minimise these effects in different contexts. Additionally, policymakers need to consider the dark side of AI, especially among the vulnerable groups.Originality/value: This paper is among the first research studies that synthesise previous research on the dark side of AI, providing a comprehensive view of its diminishing impact on customer responses.

This study measures the effects of chatbot anthropomorphic language on customers' perception of chatbot competence and authenticity on customer engagement while taking into consideration the moderating roles of humanlike appearance and brand credibility. We conducted two experimental studies to examine the conceptual framework. Study 1 tests the moderating effect of a chatbot's anthropomorphic appearance on the relationship between chatbots' language and customer engagement. Study 2 tests the moderating effect of brand credibility on the relationship between a chatbot's anthropomorphic language and customer engagement. The findings confirm that the interaction between humanlike appearance via the use of avatars and anthropomorphic language, such as using emojis, in conversations with customers influences customer engagement, and that this effect is mediated by perceived chatbot competence and authenticity. Further, the positive effect of anthropomorphic language on perceived competence, and subsequently on authenticity and engagement, is only significant when the brand credibility was low (vs. high). This study offers insights into the effect of chatbots' anthropomorphic language and provides suggestions on how to devise efficient strategies for engaging customers using chatbots.