The Impact of Quality Attribute on Purchase Intention Take Unboxing Video as an Example

Derrick Yang, Min Yuan Ma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The unboxing video has become the most popular video online. Companies cooperated with video creators such as YouTubers to broadcast product advertising, which has achieved significant results. The goal of the cooperation video is trying to enhance the purchase intention of the audience just like traditional advertising. However, it is hard to understand how the unboxing video is so attractive to the audience. This study aims to explore the quality attribute that can enhance purchase intention from the unboxing video and understand the hidden attribute behind it. Through the Kano quality model, we can classify the quality attribute to understand the factors hidden behind the videos. The result shows that in order to enhance the purchase intention, firsthand product information must be concluded and allow the audience to fasten understanding of the product information. The further generation of several emotions such as surprise, avoiding regrets, and granting stress relief could have a positive impact on the video. This research hopes to provide not only to the company, but also YouTubers, advertisement directors, marketing strategy departments or the related industries a reference in the future.

Original languageEnglish
Title of host publicationProceedings of the 8th International Conference on Kansei Engineering and Emotion Research, KEER 2020
EditorsHiroko Shoji, Shinichi Koyama, Toshimasa Yamanaka, Takeo Kato, Keiichi Muramatsu, Pierre Lévy, Kuohsiang Chen, Anitawati Mohd Lokman
PublisherSpringer
Pages88-96
Number of pages9
ISBN (Print)9789811578007
DOIs
Publication statusPublished - 2020
Event8th International Conference on Kansei Engineering and Emotion Research, KEER 2020 - Tokyo, Japan
Duration: 2020 Sep 72020 Sep 9

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1256 AISC
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference8th International Conference on Kansei Engineering and Emotion Research, KEER 2020
CountryJapan
CityTokyo
Period20-09-0720-09-09

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

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