Design and Implementation of An Adaptive Tourist Recommendation System

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dc.contributor.advisor Sundaram, D en
dc.contributor.advisor Arthanari, T en
dc.contributor.author Etaati, Leila en
dc.date.accessioned 2016-09-05T00:16:07Z en
dc.date.issued 2016 en
dc.identifier.uri http://hdl.handle.net/2292/30210 en
dc.description.abstract The Internet has significantly influenced tourism by providing a vast amount of information for travellers. However, as the number of choices increases for travellers, the decision making process becomes more complicated. Moreover, each traveller has specific characteristics that affect his/her decision making process during travel. Travellers’ age, gender, cultural background, marital status, travel experiences, purpose/s of travel, and preferences frame the selection of destinations, activities, and accommodation. Travellers have different decision making styles. Although some prefer to book travel packages before travel, others would rather book accommodation, transportation, and activities during travel. Travellers seek certain items at different travel stages. For instance, they seek recommendations on the budget and length of travel before travel, and they search for available activities during travel. Furthermore, the travel products decision making process is interrelated. For example, the selection of travel destination affects the decision making process about activities, transportation, and car rentals. In recent years, researchers have proposed Tourist Recommendation Systems (TRS) and Context- Aware Travel Systems with the aim of addressing issues and requirements. Yet researchers have so far failed to address key travellers’ needs. They are insufficiently adaptive and adaptable. Moreover, they have a narrow perspective about the traveller, existing travel contexts, travel products, travel processes, and travellers’ perspectives. Current tourist systems fail to sufficiently integrate and collaborate with other travel information providers. As a result, they are unable to reach a holistic view regarding recent travel information and contexts. To address the problems and issues raised, we adopt a design science oriented multi-methodological approach that contains observation, theory building, implementation, and evaluation phases. This thesis blends models and theories from various related disciplines to cope with the identified problems in the design and implementation of adaptive tourist recommendation systems. It also synthesizes ideas, processes, models, and frameworks of travel, psychology, tourist decision making, organizational decision making, recommendation systems, decision support systems, and adaptive systems. This research proposes and implements concepts, models, conceptual frameworks, system frameworks, and architecture for the design of an adaptive tourist recommendation system that addresses the aforementioned problems. The proposed artefacts are integrated, collaborative, holistic, and adaptive to travel information, contexts, processes, and perspectives. The proposed concepts, models, conceptual frameworks, system frameworks, architecture, and implementation have been evaluated via different approaches. en
dc.publisher ResearchSpace@Auckland en
dc.relation.ispartof PhD Thesis - University of Auckland en
dc.relation.isreferencedby UoA99265005910602091 en
dc.rights Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.title Design and Implementation of An Adaptive Tourist Recommendation System en
dc.type Thesis en
thesis.degree.discipline Information Systems and Operations Management en
thesis.degree.grantor The University of Auckland en
thesis.degree.level Doctoral en
thesis.degree.name PhD en
dc.rights.holder Copyright: The author en
dc.rights.accessrights http://purl.org/eprint/accessRights/OpenAccess en
pubs.elements-id 540777 en
pubs.record-created-at-source-date 2016-09-05 en


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