'I Will Follow You!' – How Recommendation Modality Impacts Processing Fluency and Purchase Intention

Schwede, Melanie; Zierau, Naim; Janson, Andreas; Hammerschmidt, Maik; Leimeister, Jan Marco

doi:10.2139/ssrn.4239822

Cited by 4 publications

(3 citation statements)

References 48 publications

(91 reference statements)

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“…Finally, it would be of interest to explore whether different AI settings (e.g., chatbots vs. voice assistants, touch screen gaming vs. keyboard gaming) would yield similar results (Elsharnouby et al, 2023). Additionally, the communication style of the AI agent could potentially play a significant moderating role and warrant further examination (Schwede et al, 2022).…”

Section: Discussionmentioning

confidence: 99%

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How gamifying AI shapes customer motivation, engagement, and purchase behavior

Elmashhara,

De Cicco,

Silva

et al. 2023

Psychology and Marketing

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Recently, firms started to gamify conversational artificial intelligence (AI) agents, such as chatbots, to improve purchase outcomes. This article explores strategies for incorporating gamification into AI systems by investigating the impact of utilitarian and hedonic motivations facilitated by gamified chatbots on various dimensions of customer engagement (cognitive, emotional, and behavioral), as well as the subsequent effects of these dimensions on customers' purchase behavior. By conducting one cross‐sectional and two experimental studies involving real interactions with gamified chatbots, this research identifies two crucial paths that warrant attention: an optimal path from hedonic motivation to behavioral engagement, resulting in enhanced purchase, and a detrimental path from utilitarian motivation to emotional engagement, which reduces purchase. Furthermore, the research compares the effects of two types of gamified chatbots and reveals that a game‐of‐chance‐based chatbot, as opposed to a knowledge‐sharing gamified chatbot, aligns with the optimal path, leading to higher purchasing while at the same time avoiding that customers feel obligated to play the game. Based on these findings, the article provides actionable insights for eliciting favorable psychological and behavioral responses through gamified AI interactions.

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Section: Discussionmentioning

confidence: 99%

“…Additionally, the communication style of the AI agent could potentially play a significant moderating role and warrant further examination (Schwede et al, 2022).…”

Section: Managerial Implicationsmentioning

confidence: 99%

How gamifying AI shapes customer motivation, engagement, and purchase behavior

Elmashhara,

De Cicco,

Silva

et al. 2023

Psychology and Marketing

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“…Fourth and finally, since our results are robust across both studies, the practical implications apply to different service settings. For example, in the first study the robot gave a medical diagnosis, and in the second study it recommended a medical product, so that we also provide practical insights for firm's endeavors regarding the deployment of robo-advisors, which should also provide valuable insights for future applications of HRI, such as conversational commerce (Brengman et al, 2021;Lim et al, 2022;Schwede et al, 2022).…”

Section: Practical Implicationsmentioning

confidence: 99%

Users taking the blame? How service failure, recovery, and robot design affect user attributions and retention

Mozafari¹,

Schwede²,

Hammerschmidt³

et al. 2022

Electron Markets

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Firms use robots to deliver an ever-expanding range of services. However, as service failures are common, service recovery actions are necessary to prevent user churn. This research further suggests that firms need to know how to design service robots that avoid alienating users in case of service failures. Robust evidence across two experiments demonstrates that users attribute successful service outcomes internally, while robot-induced service failures are blamed on the firm (and not the robot), confirming the well-known self-serving bias. While this external attributional shift occurs regardless of the robot design (i.e., it is the same for warm vs. competent robots), the findings imply that service recovery minimizes the undesirable external shift and that this effect is particularly pronounced for warm robots. For practitioners, this implies prioritizing service robots with a warm design for maximizing user retention for either type of service outcome (i.e., success, failure, and failure with recovery). For theory, this work demonstrates that attribution represents a meaningful mechanism to explain the proposed relationships.

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Charting the Evolution and Future of Conversational Agents: A Research Agenda Along Five Waves and New Frontiers

et al. 2023

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Conversational agents (CAs) have come a long way from their first appearance in the 1960s to today’s generative models. Continuous technological advancements such as statistical computing and large language models allow for an increasingly natural and effortless interaction, as well as domain-agnostic deployment opportunities. Ultimately, this evolution begs multiple questions: How have technical capabilities developed? How is the nature of work changed through humans’ interaction with conversational agents? How has research framed dominant perceptions and depictions of such agents? And what is the path forward? To address these questions, we conducted a bibliometric study including over 5000 research articles on CAs. Based on a systematic analysis of keywords, topics, and author networks, we derive “five waves of CA research” that describe the past, present, and potential future of research on CAs. Our results highlight fundamental technical evolutions and theoretical paradigms in CA research. Therefore, we discuss the moderating role of big technologies, and novel technological advancements like OpenAI GPT or BLOOM NLU that mark the next frontier of CA research. We contribute to theory by laying out central research streams in CA research, and offer practical implications by highlighting the design and deployment opportunities of CAs.

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'I Will Follow You!' – How Recommendation Modality Impacts Processing Fluency and Purchase Intention

Cited by 4 publications

References 48 publications

How gamifying AI shapes customer motivation, engagement, and purchase behavior

How gamifying AI shapes customer motivation, engagement, and purchase behavior

Users taking the blame? How service failure, recovery, and robot design affect user attributions and retention

Charting the Evolution and Future of Conversational Agents: A Research Agenda Along Five Waves and New Frontiers

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