Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
- 주제(키워드) Behavior , Issue 151 , e-mass customization , consumer benefit , online retailing , consumer behavior , structural equation modeling , latent mean analysis , online survey
- 주제(기타) Multidisciplinary Sciences
- 관리정보기술 faculty
- 등재 SCIE, SCOPUS
- 발행기관 JOURNAL OF VISUALIZED EXPERIMENTS
- 발행년도 2019
- URI http://www.dcollection.net/handler/ewha/000000162189
- 본문언어 영어
- Published As http://dx.doi.org/10.3791/60035
- PubMed https://pubmed.ncbi.nlm.nih.gov/31609350
초록/요약
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.
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