title: Customer satisfaction factors in online retail: Online review analysis
metadata.name: dc.contributor.author
metadata.value: Haddadi, Mehran
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Rebiazina, Vera A.
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2023-05-18T11:13:37Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2023-05-18T11:13:37Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2023-03
metadata.lang: -
metadata.name: dc.identifier.citation
metadata.value: Haddadi M., Rebiazina V. A. 2023. Customer satisfaction factors in online retail: Online review analysis. Vestnik of Saint Petersburg University. Management 22 (1): 3–22. http://doi.org/10.21638/11701/spbu08.2023.101
metadata.lang: en_GB
metadata.name: dc.identifier.other
metadata.value: http://doi.org/10.21638/11701/spbu08.2023.101
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/41469
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value: This paper aims to analyze online customers’ reviews and gain insight into customer satisfaction
  factors drawn from a big user-generated content of US online retailers. This user-generated
  content has become more insightful, especially in the CO VID-19 era as the result of a rapid
  increase in online shopping. This study uses a big textual data of 5 340 786 online reviews which
  was collected from the platform bizratesurvey.com. The study focuses on individual customers’
  reviews of 839 US online retailers. Word frequency analysis and latent dirichlet allocation methods
  were used to process the data. The results revealed three main topics related to the ease of use,
  product, and delivery that were mentioned by highly satisfied customers of US online retailers.
  The authors have labeled the topics properly by considering at least twenty of the most probable
  words in each topic. The results provide a pathway for online retail executives for enhancing
  shopping experiences through the ease of purchasing, the improvement of product quality and
  delivery for customers. Practitioners can replicate the process of data analysis fulfilled in this
  study in order to monitor customer feedback. The findings also provide a new way of using big
  textual data from customer reviews in further studies.
metadata.lang: en_GB
metadata.name: dc.description.sponsorship
metadata.value: This research has been conducted within the fundamental research project “Digitalization as a driving
  force of open innovation and co-creation: Implications for value creation and value capture” as a part of the
  HSE Graduate School of Business Research Program in 2021–2023 (Protocol No.23 dated 22.06.2021 of the
  HSE GSB Research Committee).
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: en
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: St Petersburg State University
metadata.lang: en_GB
metadata.name: dc.relation.ispartofseries
metadata.value: Vestnik of St Petersburg University. Management;Volume 22; Issue 1
metadata.lang: -
metadata.name: dc.subject
metadata.value: COVID-19
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: customer satisfaction
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: online retail
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: text analytics
metadata.lang: en_GB
metadata.name: dc.subject
metadata.value: online review
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: Customer satisfaction factors in online retail: Online review analysis
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Article
metadata.lang: en_GB
resources.filename: 932.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/41469/1/932.pdf
resources.format: Adobe PDF
resources.size: 2,22 MB