# Persuasive or Neutral? A Field Experiment on Generative AI in Online Travel Planning

arXiv: https://arxiv.org/abs/2509.14259 · HTML: https://mlsanity.com/paper/2509.14259/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 11 of its 53 references that are in the map.
- First posted on arXiv 12 Sep 2025.

## Builds on (most cited first, 11 of 11)

- [TravelPlanner: A Benchmark for Real-World Planning with Language Agents](https://mlsanity.com/paper/2402.01622/) (2024)
- [Plan-Then-Execute: An Empirical Study of User Trust and Team Performance When Using LLM Agents As A Daily Assistant](https://mlsanity.com/paper/2502.01390/) (2025)
- [TripTailor: A Real-World Benchmark for Personalized Travel Planning](https://mlsanity.com/paper/2508.01432/) (2025)
- [To the Globe (TTG): Towards Language-Driven Guaranteed Travel Planning](https://mlsanity.com/paper/2410.16456/) (2024)
- [VeriPlan: Integrating Formal Verification and LLMs into End-User Planning](https://mlsanity.com/paper/2502.17898/) (2025)
- [Touch Your Heart: A Tone-aware Chatbot for Customer Care on Social Media](https://mlsanity.com/paper/1803.02952/) (2018)
- [QUERT: Continual Pre-training of Language Model for Query Understanding in Travel Domain Search](https://mlsanity.com/paper/2306.06707/) (2023)
- [Do Expressions Change Decisions? Exploring the Impact of AI's Explanation Tone on Decision-Making](https://mlsanity.com/paper/2502.19730/) (2025)
- [SynthTRIPs: A Knowledge-Grounded Framework for Benchmark Query Generation for Personalized Tourism Recommenders](https://mlsanity.com/paper/2504.09277/) (2025)
- [Which linguistic cues make people fall for fake news? A comparison of cognitive and affective processing](https://mlsanity.com/paper/2312.03751/) (2023)
- [Roamify: Designing and Evaluating an LLM Based Google Chrome Extension for Personalised Itinerary Planning](https://mlsanity.com/paper/2504.10489/) (2025)

## Abstract (arXiv)

Generative AI (GenAI) offers new opportunities for customer support in online travel agencies, yet little is known about how its design influences user engagement, purchase behavior, and user experience. We report results from a randomized field experiment in online travel itinerary planning, comparing GenAI that expressed (A) positive enthusiasm, (B) neutral expression, and (C) no tone instructions (control). Users in group A wrote significantly longer prompts than those in groups B and C. At the same time, users in groups A and B were more likely to purchase subscriptions of the webservice. We further analyze linguistic cues across experimental groups to explore differences in user experience and explain subscription purchases and affiliate link clicks based on these cues. Our findings provide implications for the design of persuasive and engaging GenAI interfaces in consumer-facing contexts and contribute to understanding how linguistic framing shapes user behavior in AI-mediated decision support.