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PENGARUH KUALITAS LAYANAN AI-CHATBOT TERHADAP USER TRUST, CONSUMER EXPERIENCE, CONSUMER ENGAGEMENT, PERCEIVED PRIVACY RISK, DENGAN PERCEIVED INTRUSIVENESS SEBAGAI VARIABEL MODERATOR SERTA DAMPAKNYA PADA PURCHASE INTENTION : Survei pada Pengguna AI-Chatbot di E-Commerce Zalora Indonesia

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RINGKASAN

Muhammad Syarifudin, Program Magister, Fakultas Ilmu Administrasi
Universitas Brawijaya, Malang. Pengaruh Kualitas Layanan AI-Chatbot Terhadap
User Trust, Consumer Experience, Consumer Engagement, Perceived Privacy
Risk, dengan Perceived Intrusiveness sebagai Variabel Moderator Serta
Dampaknya pada Purchase Intention (Survei pada Pengguna AI-Chatbot di E
Commerce Zalora Indonesia). Komisi Pembimbing, Ketua, Prof. Dr. Drs. Edy
Yulianto, MP., Anggota Agung Nugroho L.I.F., S.AB., M.Bus Sys.Pro, Ph,D

Transformasi layanan pelanggan berbasis kecerdasan buatan (AI) telah
menjadi strategi penting bagi e-commerce dalam meningkatkan kualitas layanan
dan pengalaman konsumen. Namun, efektivitas AI-chatbot dalam mendorong niat
beli (purchase intention) belum banyak diteliti secara komprehensif, khususnya
dengan mempertimbangkan peran variabel psikologis pengguna dan faktor
gangguan (perceived intrusiveness). Penelitian ini mengangkat permasalahan
mengenai bagaimana kualitas layanan AI-chatbot Zalora Indonesia memengaruhi
purchase intention, baik secara langsung maupun tidak langsung melalui user
trust, consumer experience, consumer engagement, dan perceived privacy risk,
dengan perceived intrusiveness sebagai variabel moderator.

Tujuan utama penelitian ini adalah: (1) menguji pengaruh kualitas layanan
AI-chatbot terhadap user trust, consumer experience, consumer engagement, dan
perceived privacy risk; (2) menguji pengaruh user trust, consumer experience,
consumer engagement, dan perceived privacy risk terhadap purchase intention;
(3) menganalisis peran mediasi dari user trust, consumer experience, dan
consumer engagement pada hubungan kualitas layanan AI-chatbot terhadap
purchase intention; serta (4) menguji efek moderasi perceived intrusiveness pada
hubungan antara kualitas layanan AI-chatbot dan consumer experience.
Penelitian ini menggunakan pendekatan kuantitatif dengan desain
eksplanatori. Data primer diperoleh melalui survei daring kepada 387 responden
pengguna Zalora Indonesia yang pernah berinteraksi dengan AI-chatbot dalam
enam bulan terakhir. Pengumpulan data dilakukan menggunakan kuesioner
terstruktur dengan skala Likert lima poin. Analisis data meliputi statistik deskriptif,
pengujian model pengukuran (validitas dan reliabilitas), serta pengujian model
struktural menggunakan Partial Least Squares Structural Equation Modeling (PLS
SEM) dengan SmartPLS 4. Evaluasi prediksi dilakukan menggunakan pendekatan
PLS Predict untuk mengukur relevansi prediktif model.

Hasil penelitian menunjukkan bahwa kualitas layanan AI-chatbot
berpengaruh positif signifikan terhadap user trust, consumer experience,
consumer engagement, dan purchase intention, tetapi tidak signifikan terhadap
perceived privacy risk. Selanjutnya, user trust, consumer experience, dan
consumer engagement terbukti memediasi pengaruh kualitas layanan AI-chatbot
terhadap purchase intention, sedangkan perceived privacy risk tidak memiliki
pengaruh mediasi. Analisis moderasi menunjukkan bahwa perceived intrusiveness
memperkuat hubungan antara kualitas layanan AI-chatbot dan consumer
experience, mengindikasikan adanya fenomena functional intrusiveness, yaitu
kondisi di mana pengguna tetap menerima gangguan selama interaksi jika
manfaat layanan dianggap relevan dan bernilai.
Dari sisi kontribusi teoretis, penelitian ini memperkaya kerangka Stimulus
Organism–Response (S–O–R) dengan memasukkan perceived intrusiveness
sebagai variabel moderator, serta mengonfirmasi relevansi prediksi terbaik pada

konstruk consumer experience melalui analisis PLS Predict. Kontribusi praktis
penelitian ini meliputi rekomendasi bagi pengelola e-commerce untuk
meningkatkan kualitas layanan AI-chatbot dengan fokus pada aspek kecepatan
respon, personalisasi rekomendasi, interaktivitas, dan kehadiran sosial, serta
mengurangi persepsi risiko privasi melalui transparansi pengelolaan data.
Temuan penelitian ini diharapkan memberikan landasan konseptual dan
praktis dalam mengembangkan strategi layanan berbasis AI yang mampu
menciptakan pengalaman konsumen positif sekaligus meningkatkan niat beli di
platform e-commerce.

Kata Kunci: AI-chatbot, kualitas layanan, user trust, consumer experience,
consumer engagement, perceived privacy risk, perceived intrusiveness, purchase
intention, S–O–R.

SUMMARY

Muhammad Syarifudin, Master’s Program, Faculty of Administrative
Sciences, Universitas Brawijaya, Malang. The Effect of AI-Chatbot Service Quality
on User Trust, Consumer Experience, Consumer Engagement, and Perceived
Privacy Risk, with Perceived Intrusiveness as a Moderating Variable and Its Impact
on Purchase Intention (A Survey on AI-Chatbot Users in Zalora Indonesia E
Commerce). Supervisory Committee: Chairperson, Prof. Dr. Drs. Edy Yulianto,
MP.; Member, Agung Nugroho L.I.F., S.AB., M.Bus Sys.Pro, Ph.D.

The rapid development of artificial intelligence (AI) has transformed digital
service interactions, particularly in e-commerce platforms, where AI-powered
chatbots are increasingly utilized to enhance customer experience, foster
engagement, and influence purchase decisions. Despite its widespread adoption,
the effectiveness of AI-chatbots in shaping purchase intention remains
underexplored, especially when psychological mechanisms and disruptive factors
such as perceived intrusiveness are considered. This research addresses the
critical question of how AI-chatbot service quality impacts purchase intention both
directly and indirectly through user trust, consumer experience, consumer
engagement, and perceived privacy risk, with perceived intrusiveness serving as
a moderating variable.

The primary objectives of this study are to: (1) examine the effect of AI
chatbot service quality on user trust, consumer experience, consumer
engagement, and perceived privacy risk; (2) investigate the influence of these
psychological constructs on purchase intention; (3) assess the mediating roles of
user trust, consumer experience, and consumer engagement in the relationship
between AI-chatbot service quality and purchase intention; and (4) analyze the
moderating role of perceived intrusiveness on the link between AI-chatbot service
quality and consumer experience.

A quantitative explanatory research design was adopted, employing an
online survey distributed to 387 respondents who had interacted with Zalora
Indonesia’s AI-chatbot within the past six months. Data were collected through a
structured questionnaire using a five-point Likert scale. The data analysis involved
descriptive statistics, measurement model evaluation (validity and reliability), and
structural model assessment using Partial Least Squares Structural Equation
Modeling (PLS-SEM) via SmartPLS 4. Additionally, PLS Predict was employed to
evaluate the model’s predictive relevance, with particular attention to consumer
experience as a key construct.

The findings reveal that AI-chatbot service quality has a significant positive
effect on user trust, consumer experience, consumer engagement, and purchase
intention, but no significant effect on perceived privacy risk. Furthermore, user
trust, consumer experience, and consumer engagement act as mediators in the
relationship between AI-chatbot service quality and purchase intention, while
perceived privacy risk does not play a significant role. Importantly, perceived
intrusiveness was found to positively moderate the relationship between AI-chatbot
service quality and consumer experience, highlighting the phenomenon of
functional intrusiveness a condition where consumers are willing to tolerate
perceived interruptions if the AI-chatbot’s service quality and personalization
provide high perceived value.
From a theoretical perspective, this research extends the Stimulus
Organism–Response (S–O–R) framework by integrating perceived intrusiveness

as a moderator, thereby offering a more nuanced understanding of digital
consumer behavior in AI-mediated environments. The study also confirms
predictive validity through PLS Predict analysis, emphasizing the central role of
consumer experience as a determinant of purchase intention.
In practical terms, the results provide actionable insights for e-commerce
platforms like Zalora to enhance their AI-chatbot services. Key recommendations
include focusing on response accuracy, real-time personalization, social presence,
and interactive design to strengthen user trust and engagement while maintaining
transparency in data privacy practices. By minimizing perceived privacy risks and
optimizing user experience, companies can drive stronger purchase intentions and
achieve sustainable competitive advantage in the digital marketplace.
Overall, this research contributes to both theory and practice by elucidating the
psychological mechanisms underlying AI-chatbot interactions and demonstrating
how perceived intrusiveness when strategically managed can enhance, rather than
hinder, consumer experience and purchase behavior.
Keywords: AI-chatbot, service quality, user trust, consumer experience, consumer
engagement, perceived privacy risk, perceived intrusiveness, purchase intention,
S–O–R

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

TES 658,8 SYA p 2025 K1

Penerbit

Malang : Program Magister Ilmu Administrasi Bisnis Fakultas Ilmu Administrasi Universitas Brawijaya Malang., 2025

Deskripsi Fisik

xxii, 276 Halaman ; Ilus : 29,5 cm

Bahasa

Indonesia

ISBN/ISSN

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Klasifikasi

658,8

Tipe Isi

text

Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

PUrchase Intention
Kualitas Layanan
Service quality
Tesis / Thesis
AI-chatbot
user trust, consumer experience
consumer engagement
perceived privacy risk
perceived intrusiveness
purchase intention
S–O–R.
consumer engagement

Info Detail Spesifik

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Pernyataan Tanggungjawab

Muhammad Syarifudin

Versi lain/terkait

Lampiran Berkas

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