Differentiating persuasive factors for tourism booking websites: towards matrix factorization

The main challenges to increasing sales, usually lie with persuasion techniques and recommender systems. Persuasion Systems models (PSDs) analyse persuasion context, identifies the key issues and subsequently, enables mapping of persuasion techniques to functional requirements. This paper investigat...

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Bibliographic Details
Main Authors: Lee, Chien-Sing *, Wong, Yew-Onn, Gui, Hui-Ying
Format: Book Section
Published: Institute Electrical and Electronics Engineers 2022
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Online Access:http://eprints.sunway.edu.my/2305/
https://ieeexplore.ieee.org/document/10064406
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Summary:The main challenges to increasing sales, usually lie with persuasion techniques and recommender systems. Persuasion Systems models (PSDs) analyse persuasion context, identifies the key issues and subsequently, enables mapping of persuasion techniques to functional requirements. This paper investigates persuasive factors for tourism booking websites, with the aim of utilizing derived significant factors at different stages, as the bases for weighted criteria analyses, and matrix factorization, integral in fuzzy logic computations. Two parallel case studies are carried out. The first tourism booking website is designed, based on Cialdini's persuasion techniques for the Malaysian hotel/tourism context, and tested with customers and travel agencies. The second study investigates social CRM and associations between gender, age and income on a group of different sample respondents. User evaluation indicates different weighted factors at the search, review and booking stages, as well as different perceptions, with regards to cross-selling. Comparative findings with successful cross-selling companies, such as Lazada and Shoppee further highlight three core influencing factors. These have enabled us to add specificity to some constructs in Oinas-Kukkonen and Harjumaa's PSD dialogue support model, for the sampled Malaysian contexts. This triangulated approach can enable more holistic derivation of requirements and prediction and derivation of initial rules for future decision support systems.