تحلیل بیبلیومتریک تعامل هوش مصنوعی و تجربه مشتری: شناسایی ساختار دانش و روندهای آینده

خانلری, امیر; عبدالحسینی, رضا

doi:JABM.3.2.15564.350878.36792

تحلیل بیبلیومتریک تعامل هوش مصنوعی و تجربه مشتری: شناسایی ساختار دانش و روندهای آینده

نوع مقاله : استخراج از رساله دکتری

نویسندگان

امیر خانلری ¹

رضا عبدالحسینی ²

¹ دانشیار دانشکده مدیریت کسب و کار دانشگاه تهران.

² دانشجوی دکترای مدیریت بازاریابی، پردیس بین المللی کیش دانشگاه تهران، تهران، ایران.

JABM.3.2.15564.350878.36792

چکیده

هدف: این پژوهش به بررسی تعامل میان هوش مصنوعی (AI) و تجربه مشتری (CX) از طریق تحلیل بیبلیومتریک می‌پردازد. هوش مصنوعی با ارائه فناوری‌های نوین، نحوه تعامل شرکت‌ها با مشتریان را بهبود داده و تجربه آن‌ها را شخصی‌سازی کرده است. هدف این مطالعه، شناسایی روندهای پژوهشی، موضوعات کلیدی، چالش‌ها و فرصت‌های این حوزه و ترسیم مسیری برای تحقیقات آتی است.
روش: در این مطالعه، از تحلیل بیبلیومتریک برای بررسی علمی مقالات استفاده شده است. از میان 6827 مقاله شناسایی‌شده از پایگاه وب آف ساینس، پس از پالایش داده‌ها، 881 مقاله برای تحلیل انتخاب شد. ابزارهای به‌کاررفته شامل نرم‌افزار وس ویوئر و بسته بیبلیومتریکس در محیط آر استودیو بودند. این ابزارها امکان تحلیل شبکه‌های مفهومی و اجتماعی و بررسی هم‌رخدادی اصطلاحات کلیدی را فراهم کردند. علاوه بر این، تحلیل زمانی مقالات، همکاری‌های علمی و شناسایی نویسندگان برجسته انجام شد.
یافته‌ها: یافته‌ها نشان می‌دهند که کشورهای چین، ایالات متحده، هند و انگلستان پیشروترین کشورها در این حوزه هستند. تحلیل هم‌رخدادی واژگان سه محور اصلی شامل شخصی‌سازی تجربه مشتری، بهینه‌سازی بازاریابی و چالش‌های اخلاقی را شناسایی کرد. همچنین، شبکه‌های هم‌نویسندگی سه خوشه کلیدی را نشان دادند: تحلیل احساسات مشتری، مدل‌سازی پیش‌بینی‌کننده در بازاریابی، و ابعاد اخلاقی هوش مصنوعی.
نتیجه‌گیری: نتایج پژوهش نشان می‌دهد که هوش مصنوعی می‌تواند رضایت مشتری، وفاداری و تعاملات شخصی‌سازی‌شده را ارتقا دهد. ابزارهایی مانند چت‌بات‌ها و سیستم‌های پیشنهاددهی، خدمات سریع‌تر و دقیق‌تری ارائه می‌دهند. با این حال، چالش‌هایی مانند حفظ حریم خصوصی، شفافیت داده‌ها و مسائل اخلاقی وجود دارند که نیازمند توجه ویژه در طراحی استراتژی‌های مبتنی بر هوش مصنوعی هستند. این پژوهش به ضرورت ایجاد تعادل میان کارایی فناوری و اصول اخلاقی تأکید کرده و پیشنهادهایی برای مدیران و سیاست‌گذاران ارائه داده است. یافته‌ها می‌توانند مبنای طراحی استراتژی‌های مؤثر در صنایع دیجیتال و شخصی‌سازی خدمات باشند.

کلیدواژه‌ها

هوش مصنوعی

تجربه مشتری

ساختار دانش

بیبلیومتریک

موضوعات

بازاریابی

عنوان مقاله English

The Bibliometric Analysis of the Interaction Between Artificial Intelligence and Customer Experience: Identifying Knowledge Structure and Future Trends

نویسندگان English

Amir Khanlari ¹

Reza Abdolhoseini ²

¹ Associate Prof., Faculty of Business Management, University of Tehran, Tehran, Iran.

² Ph.D. Candidate in Marketing Management, Kish International Campus, University of Tehran, Tehran, Iran.

چکیده English

Objective: The interaction between Artificial Intelligence (AI) and Customer Experience (CX) has become a significant and multifaceted domain in marketing and management research. The rapid evolution of AI technologies has transformed customer engagement, enabling unprecedented levels of personalization, data-driven decision-making, and operational efficiency. This study conducts a bibliometric analysis to systematically examine the relationship between AI and CX. It identifies key trends, challenges, thematic clusters, and opportunities, highlighting AI's transformative role in optimizing customer experiences. Additionally, it explores how organizations can integrate AI into customer-centric strategies to achieve sustainable competitive advantages and long-term growth.
Methodology: A bibliometric methodology was applied using Web of Science data. From 6,827 articles, 881 were selected based on publication year, relevance, and document type. Tools like VOSviewer and Bibliometrix analyzed conceptual frameworks, social networks, and key term co-occurrence. Temporal trends, influential authors, and international collaboration patterns were reviewed to map AI-CX research. This approach provided a detailed exploration of AI’s conceptual, social, and practical implications for customer experience.
Findings: The analysis identified China, the U.S., India, and the U.K. as key contributors to AI-CX research based on publication volume and impact. Co-occurrence analysis highlighted three themes: customer interaction personalization, marketing optimization, and AI-related ethical challenges. Social network analysis revealed three research clusters: sentiment analysis, predictive marketing models, and AI's ethical implications in decision-making. These clusters show the shift from technological advancements to practical AI applications in customer engagement. The study also noted an increasing convergence of technology with customer experience strategies.
Conclusion: The findings demonstrate that AI is essential for enhancing customer satisfaction, loyalty, and personalized interactions. AI-driven tools, such as chatbots and predictive analytics, improve service speed, efficiency, and accuracy. However, ethical challenges, including data privacy, algorithmic transparency, and biases, require urgent attention. Balancing technological efficiency with ethical responsibility ensures sustainable AI adoption. Aligning AI with organizational goals transforms customer experiences and drives business success. Addressing challenges and leveraging opportunities unlock AI’s potential for innovation. The study highlights the need for interdisciplinary collaboration and innovative strategies to meet evolving digital consumer demands in an AI-driven world.

کلیدواژه‌ها English

Artificial Intelligence

Bibliometric Analysis

Customer Experience

Knowledge Structure

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