Applying an emass customization program as a research tool to evaluate consumer benefits

Minjung Park, Jungmin Yoo

Research output: Contribution to journalArticlepeer-review


As many scholars and practitioners study personalization and relationship marketing, it is important to provide personalization such as mass customization through marketing technology. The purpose of this study is to examine how to conduct consumer research using an online survey and analysis of data. This study examines consumers' perceived benefits while customizing a product as well as emotional product attachment, attitudes toward a customization program, and loyalty intentions in the context of online retailing. In addition, this study investigates how consumer responses are different based on individual characteristics such as fashion innovativeness. An online survey company in South Korea recruited 290 female apparel shoppers who purchased apparel online. To enhance external validity, this study used an existing retail website with a well-established mass customization program. After completing the customization program, participants complete the online questionnaire. Structural equation modeling (SEM) and latent mean analyses (LMAs) are then performed for analyses. This study stresses the importance of testing measurement invariance for mean comparisons. Before the SEM and LMA, this study follows the hierarchy of invariance tests (configural invariance test, metric invariance test, and scalar invariance test), which are not considered by traditional approaches such as ANOVA. These statistical analyses provide applicability of the invariance test procedures and LMA to consumer behaviors. The conclusions of mean differences have integrity and validity because they are guided by a sophisticated statistical procedure to ensure measurement invariance.

Original languageEnglish
Article numbere60035
JournalJournal of Visualized Experiments
Issue number151
StatePublished - 2019

Bibliographical note

Funding Information:
The data has been modified from Park and Yoo’s study29. This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of KOREA (NRF = 2016S1A5A2A03927809).

Publisher Copyright:
© 2019 Journal of Visualized Experiments.


  • Behavior
  • Consumer behavior
  • Consumer benefit
  • E-mass customization
  • Issue 151
  • Latent mean analysis
  • Online retailing
  • Online survey
  • Structural equation modeling


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