Pengaruh User Experience dan Effort Expectancy dalam Penerapan Fitur AI Terhadap Service Quality E-commerce Lazada
The Effect of User Experience and Effort Expectancy in the Implementation of AI Features on Lazada E-Commerce Service Quality
Penelitian ini bertujuan untuk menguji pengaruh User Experience dan Effort Expectancy dalam penerapan fitur kecerdasan buatan (AI) terhadap Service Quality pada platform e‑commerce Lazada. Metode penelitian menggunakan pendekatan kuantitatif dengan teknik analisis regresi linier berganda melalui aplikasi SPSS versi 30. Data diperoleh melalui survei penyebaran kuesioner online kepada responden Generasi Z (usia 17–26 tahun) berdomisili di Surabaya yang pernah menggunakan fitur AI Lazzie di aplikasi Lazada. Model penelitian ini mengintegrasikan kerangka Unified Theory of Acceptance and Use of Technology (UTAUT) dan konsep User Experience untuk menjelaskan hubungan antara variabel independen User Experience dan Effort Expectancy dengan variabel dependen Service Quality. Hasil penelitian diharapkan memberikan wawasan praktis bagi perusahaan e‑commerce dalam merancang dan mengoptimalkan fitur AI yang lebih user‑friendly serta efisien guna meningkatkan persepsi kualitas layanan digital dan loyalitas pelanggan.
This study aims to examine the influence of User Experience and Effort Expectancy in the implementation of artificial intelligence (AI) features on Service Quality on the Lazada e-commerce platform. The research method used a quantitative approach with multiple linear regression analysis techniques using SPSS version 30. Data were obtained through an online questionnaire survey distributed to 200 Generation Z respondents (aged 17–26) residing in Surabaya who had used the Lazzie AI feature on the Lazada app. This research model integrates the Unified Theory of Acceptance and Use of Technology (UTAUT) framework and the User Experience concept to explain the relationship between the independent variables User Experience and Effort Expectancy and the dependent variable Service Quality. The results are expected to provide practical insights for e-commerce companies in designing and optimizing more user-friendly and efficient AI features to improve perceived digital service quality and customer loyalty.