“Can Chatbots Foster Co-Creation in Collaborative Holiday Planning?” An Expectancy-Value Perspective

Document Type

Article

Source of Publication

Information Systems Frontiers

Publication Date

7-17-2026

Abstract

Group holiday planning offers opportunities for shared understanding and stronger social bonds. Yet, it is often difficult to coordinate a group holiday due to conflicting preferences, fragmented information, and the effort required to reach a consensus. Chatbots can help expedite this process by generating options, tailoring recommendations, and accommodating diverse preferences. While prior research has largely examined users’ perceptions of dyadic (single-user) chatbots for holiday planning, the role of chatbots in polyadic, group-based co-creation remains underexplored. To address this gap, we adopt an expectancy–value theory (EVT) perspective to conceptualize collaborative holiday planning with chatbots. We model travelers’ reasons for using a chatbot, such as interaction quality, customization, information quality, and perspective-taking, as well as reasons against using it, including perceived low-quality advice and privacy concerns, as formative predictors of attitudes and, ultimately, willingness to co-create. In a live multi-user chatroom integrating an AI-powered chatbot, 112 participants were organized into 56 pairs, each collaboratively planning a holiday and subsequently reporting their perceptions. Findings indicate that interaction quality, customization, information quality, and especially perspective-taking strengthen reasons for using chatbots, which in turn enhance attitudes and increase willingness to co-create. Conversely, privacy concerns and low-quality advice strengthen reasons against chatbot use, although they do not significantly diminish attitudes. Further, personal values further amplify reasons for using the chatbot. This study extends EVT into the domain of human–AI group collaboration, offering design implications for developing effective polyadic travel-planning chatbots.

ISSN

1387-3326

Publisher

Springer Science and Business Media LLC

Disciplines

Computer Sciences

Keywords

Co-planning, Human-AI collaboration, Polyadic chatbot, Travel

Scopus ID

105044766593

Indexed in Scopus

yes

Open Access

no

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