AbstractOnline customer reviews play an important role in supporting online shoppers in researching products and making purchase decisions. The majority of online shoppers read customer reviews as an important reference in online shopping. However, traditionally, while reviews can be sorted by recency or star rating, the online shopper is presented with a long list of reviews to read through to find those they might find useful. In response, Tesco, Mothercare, Nike and others have recently introduced improvements to their online customer reviews systems. In Nike’s customer reviews system, there are breakdowns of details and star ratings across four dimensions; Size, Comfort, Fit and Durability. By adding dimensions these oblige reviewers to address issues of supposed relevance to shoppers who can attend to one or other depending on their priority. While such an approach can improve the value of reviews and the ability to access information, the decision on what the content should be and how it should be presented is not sourced from user studies. This thesis builds on recent innovation by taking a user-centred approach which attempts to establish options of the best ways of producing, organising and viewing reviews through user studies.
To this end, an ethnographically-informed observation methodology is chosen to carry out this research. This work revealed that users think about online shopping in terms of dimensions including value for money, functionality, customer service and so on. These dimensions, presented in [Chapter 6], were produced through coding and analysis of user videos and interviews, validated through inter-rater correlation coefficients. These same dimensions can be used as tags for reviews, which can be attached by users. This concept was developed as a high fidelity demonstrator and evaluated in both attitude and actual-use forms within the Technology Acceptance Model evaluation framework. The work shows that a tagging approach to review production and organisation is a useful and easily implemented hence directing the user to the relevant information that they seek for and need without the same old common hassle – the longer search time.
|Date of Award||Jul 2020|
|Supervisor||Rahat Iqbal (Supervisor), John Halloran (Supervisor) & David Croft (Supervisor)|
Supporting online purchases by analysing and organising customer reviews
Dzulkefly, N. H. (Author). Jul 2020
Student thesis: Doctoral Thesis › Doctor of Philosophy