Online Fashion Gen Z Consumers^ Reviews in Post-Pandemic Covid-19- A Text Minning Approach Sudaryanto Sudaryanto- Wan Izyani Adilah Wan-Mohamad-Ivana Rosediana Dewi-Bambang Irawan
1Associate Professor Faculty of Economics and Business University of Jember, Jl. Kalimantan 37, Jember, East Java, Indonesia 68121, ORCID ID 0000-0001-9281-3962, email sudaryanto[at]unej.ac.id
2 Senior Lecturer Faculty of Business and Management, Universiti Sultan Zainal Abidin, 21300 Kuala Nerus, Terengganu, Malaysia, ORCID ID 0000-0002-0416-5940, email izyaniadilah[at]unisza.edu.my,
3Islamic Economics Department, Faculty of Economics and Business, University of Airlangga, Jl. Dharmawangsa, Surabaya, East Java, Indonesia, ORCID https://orcid.org/0000-0002-1987-5590
4 Senior Lecturer, Faculty of Economics and Business University of Jember, Jl. Kalimantan 37, Jember, East Java, Indonesia 681213
Abstract
Abstract:
This exploratory research is based on consumer e-word of mouth (e-Wom), on using e-commerce applications to purchase fashion products of Gen Z. The aim is to investigate factors dominant of the application services base on customer reviews. Ten thousand reviews were collected from e-Matahari, Zalora and Pomelo between 2020 to mid-2023. Using three angulation theories of electronic service quality (e-servqual) and psychoanalytic model theory from Sigmund Freud, consumers have structured mind (id, ego and superego) motives that encourage them to purchase. On the other hand, the e-servqual mentioned that a positive image of the service quality would influence the repurchase. The text mining analysis using the Orange application produces 10 topic keywords and a sentiment analysis. Using Social Semiotics Analysis (SSA), customer review items are tabulated and in cross items table and identified some comments as Id are more than ego and superego. This means that Gen Z consumers prefer to buy fashion products as an impact of stimulus as immediate gratification and instincts. Factors influencing reusing such e-commerce could contribute to quantitative research insight.
Keywords: customer value, text minning, qualitative approache, fashion, online words of mouth, culture, self construal, milenial generation
