Pengembangan Model Analisis Livestreaming Commerce untuk Rekomendasi Peningkatan Dorongan Membeli Impulsif Menggunakan Metode Partial Least Square – Structural Equation Modeling

Akbar, Aufaka Bahi (2025) Pengembangan Model Analisis Livestreaming Commerce untuk Rekomendasi Peningkatan Dorongan Membeli Impulsif Menggunakan Metode Partial Least Square – Structural Equation Modeling. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Dalam era digital yang semakin dinamis, livestreaming commerce (LSC) telah menjadi kanal pemasaran strategis dalam industri e-commerce di Indonesia. Fenomena ini berkembang pesat melalui platform seperti Shopee Live, LazLive, dan Tokopedia Play, yang memicu munculnya perilaku pembelian impulsif konsumen. Penelitian ini bertujuan mengidentifikasi faktor psikologis yang memengaruhi urge to buy impulsively (UBI) dalam konteks LSC. Meskipun pertumbuhan LSC sangat signifikan, pemahaman mendalam mengenai dinamika perilaku konsumen masih terbatas. Oleh karena itu, penelitian ini mengembangkan model komprehensif dengan mengintegrasikan customer engagement (CE), telepresence (TEL), dan consumption vision (CON) sebagai prediktor UBI. Data dikumpulkan dari 224 responden melalui survei online menggunakan instrumen berbasis skala Likert 7 poin yang telah divalidasi. Analisis data dilakukan dengan Partial Least Square Structural Equation Modeling (PLS-SEM) untuk mengevaluasi outer model, inner model, serta pengaruh langsung dan tidak langsung antarvariabel laten. Hasil menunjukkan bahwa CE berpengaruh langsung signifikan terhadap UBI, sementara TEL dan CON memengaruhi UBI baik secara langsung maupun tidak langsung. Temuan ini memberikan kontribusi teoretis melalui pendekatan holistik dan integrasi variabel psikologis dalam kerangka LSC, sekaligus rekomendasi praktis bagi pelaku industri untuk meningkatkan strategi pemasaran digital. Model yang dikembangkan juga memiliki relevansi tinggi bagi bisnis e-commerce di Indonesia dan kawasan ASEAN.
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In the increasingly dynamic digital era, livestreaming commerce (LSC) has emerged as a strategic marketing channel in Indonesia’s e-commerce industry. This phenomenon is rapidly growing through platforms such as Shopee Live, LazLive, and Tokopedia Play, which have triggered impulsive purchasing behaviors among consumers. This study aims to identify the psychological factors influencing urge to buy impulsively (UBI) within the LSC context. Despite the rapid growth of LSC, in-depth understanding of consumer behavior dynamics remains limited. Therefore, this research develops a comprehensive model by integrating customer engagement (CE), telepresence (TEL), and consumption vision (CON) as predictors of UBI. Data were collected from 224 respondents through an online survey using a validated 7-point Likert scale instrument. Data analysis was conducted using Partial Least Square Structural Equation Modeling (PLS-SEM) to evaluate the outer model, inner model, and both direct and indirect effects among latent variables. The results show that CE has a significant direct effect on UBI, while TEL and CON influence UBI significantly both directly and indirectly. These findings contribute theoretically by offering a holistic approach and integrating psychological constructs into the LSC framework, as well as providing practical insights for industry players to enhance digital marketing strategies. The developed model also holds high relevance for e-commerce businesses in Indonesia and other ASEAN markets.

Item Type: Thesis (Other)
Uncontrolled Keywords: Livestreaming commerce (LSC), urge to buy impulsively (UBI), customer engagement (CE), telepresence (TEL), consumption vision (CON), PLS-SEMtelepresence (TEL), consumption vision (CON), PLS-SEM
Subjects: H Social Sciences > HB Economic Theory > HB801 Consumer behavior.
H Social Sciences > HF Commerce > HF5415.15 Branding (Marketing)
H Social Sciences > HF Commerce > HF5548.32 Electronic commerce.
Divisions: Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Information System > 57201-(S1) Undergraduate Thesis
Depositing User: Aufaka Bahi Akbar
Date Deposited: 24 Jul 2025 04:17
Last Modified: 24 Jul 2025 04:17
URI: http://repository.its.ac.id/id/eprint/121066

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