Online buyers’ perspectives regarding Online Trading Market Recommender System Services: an examination of their levels of satisfaction, preferences, and preference differences

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dc.contributor.advisor Peiris, A en
dc.contributor.author Sun, Huijie en
dc.date.accessioned 2015-01-29T22:12:34Z en
dc.date.issued 2015 en
dc.identifier.citation 2015 en
dc.identifier.uri http://hdl.handle.net/2292/24334 en
dc.description Full text is available to authenticated members of The University of Auckland only. en
dc.description.abstract Online trading markets (OTM) are gaining market share at an increasing rate, compared to traditional physical markets (TPM), because OTM have unique features such as not being limited by place and time. Both OTM and TPM treat their customers as their most important asset, and satisfying them by providing the products or services they require as the main prerequisite for the success of business. Recommender System (RS), widely incorporated in OTM, are designed using different algorithms to provide customised recommendation services for online buyers to assist in their shopping processes. However, providing RS services to customers doesn’t necessarily mean that these RS services always satisfy customers adequately. Moreover, there are various OTM designed for various niche markets. They differ from each other due to various characteristics such as target markets, operating concepts, and market size. Online buyers are compelled to comply with specific online shopping processes designed by builders of these OTM. This in turn seems to have an impact on the loyalty of online buyers, and their online buying behaviours. Although shopping habits of OTM buyers may be different from OTM to OTM, due to their differences, they can also be similar in OTM with similar characteristics. To ensure that the results were representative, five popular OTM were selected: Amazon, eBay, Trade Me, Alibaba and Gmarket. A Questionnaire-based survey was carried out with the aim of understanding online buyers’ requirements for recommendations, to asssit in the process of their shopping. It must be noted that the aim of this survey is not to compare the five OTM used in the survey. Structured query language (SQL) and statistics software ‘R’ were used together to clean and process the data for further analysis. Chi-squared tests and multivariate analysis were used for data analysis. A total of 366 respondents took part in this survey. The analysis results showed, firstly, that most online buyers are aware that OTM provide RS services and they are very willing to use these services, but that some items in the RS services do not satisfy them completely. Secondly, online buyers from different OTM have different RS service preferences that were well categorised and modelled by the research results - indicating that the OTM have many opportunities to attract more online buyers by improving their RS services. en
dc.publisher ResearchSpace@Auckland en
dc.relation.ispartof Masters Thesis - University of Auckland 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 Restricted Item. Available to authenticated members of The University of Auckland. en
dc.rights.uri https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm en
dc.rights.uri http://creativecommons.org/licenses/by-nc-sa/3.0/nz/ en
dc.title Online buyers’ perspectives regarding Online Trading Market Recommender System Services: an examination of their levels of satisfaction, preferences, and preference differences en
dc.type Thesis en
thesis.degree.grantor The University of Auckland en
thesis.degree.level Masters en
dc.rights.holder Copyright: The Author en
pubs.elements-id 474292 en
pubs.record-created-at-source-date 2015-01-30 en


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