بررسی تأثیر هوش مصنوعی بر رضایت مشتریان در خرید کالاهای مصرفی (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
در عصر حاضر که دوره اقتصاد دیجیتال است، فناوری های نوین موجب تغییرات بسیاری در مفاهیم و اجرای گام های مدیریت بازار شده است. هوش مصنوعی به عنوان یکی از این فناوری ها با کمک ابزارهای خود رفتار خرید مصرف کنندگان و در پی آن، میزان رضایت آنها را تحت تأثیر قرار داده است؛ از این رو هدف از پژوهش حاضر بررسی تأثیر هوش مصنوعی بر رضایت مشتریان در خرید کالاهای مصرفی است. پژوهش حاضر از نظر هدف، کاربردی و از نظر نحوه گردآوری داده ها توصیفی- پیمایشی است و رویکرد کمّی دارد. در این مطالعه برای گردآوری داده ها از پرسشنامه محقق ساخته آنلاین با بهره گیری از پرسشنامه های استاندارد و بهره گیری از پیشینه مرتبط استفاده شد. روایی پرسشنامه با پنل متخصصان و پایایی آن با محاسبه آلفای کرونباخ برای پرسشنامه (89/0) تأیید شد. همچنین، برای تجزیه و تحلیل داده ها از آزمون کولموگروف اسمیرنوف، آزمون همبستگی و مدل سازی معادله های ساختاری به کمک نرم افزارهای SPSS و LISER استفاده شد. آزمون فرضیه ها با استفاده از SEM تأیید کرد که هوش مصنوعی رضایت مشتری را به طور معنادار افزایش می دهد (β = 0.912) که این یافته ها ارتباط نظری میان هوش مصنوعی و رضایت مشتری را تأیید کرده است و پیامدهای عملی را برای بهینه سازی استراتژی های خرده فروشی آنلاین ارائه می دهد. در تبیین این فرضیه می توان گفت هوش مصنوعی قادر است فرآیند خرید را با ارائه توصیه های شخصی سازی شده و تحلیل داده های مشتریان بهبود دهد. ابزارهای هوش مصنوعی می توانند پاسخگویی به سؤال ها و مشکلات مشتریان را سریع تر و کارآمدتر کنند. این ویژگی ها نه تنها باعث کاهش زمان انتظار مشتریان می شود، به افزایش تجربه مثبت خرید کمک می کند.Examining the Impact of Artificial Intelligence on Customer Satisfaction in Consumer Goods Purchases
In today's digital economy, new technologies have transformed the concepts and implementation of market management strategies. Among these technologies, Artificial Intelligence (AI) has significantly influenced consumer purchasing behavior and, consequently, levels of customer satisfaction. This research was applied in nature, employed a descriptive survey method for data collection, and adopted a quantitative approach. Data were gathered through an online questionnaire developed by the researchers, which included standardized instruments on AI and customer satisfaction, along with relevant literature. The validity of the questionnaire was confirmed by a panel of experts and its reliability was established with a Cronbach’s alpha coefficient of 0.89. For data analysis, both descriptive and inferential statistics were used, including Kolmogorov-Smirnov tests, correlation tests, and Structural Equation Modeling (SEM), utilizing SPSS and LISREL software. The hypothesis tests revealed that AI had a significant impact on customer satisfaction when purchasing consumer goods. This finding suggested that AI could greatly enhance the customer purchasing experience by providing personalized recommendations and analyzing customer data. Furthermore, AI tools facilitated quicker and more efficient responses to customer inquiries and issues, reducing waiting times and contributing to a more positive shopping experience. Introduction Contemporary marketing increasingly relies on intelligent data, with technological advancements driving significant changes in its evolution. Simultaneously, the online shopping market is expanding rapidly, leading to heightened competition in this space. As a result, online shopping platforms play a crucial role in facilitating effective interactions between brands and consumers. New technologies aim to bridge these gaps and Artificial Intelligence (AI) stands out as a key innovation. AI enhances the online shopping experience by removing barriers and providing customers with access to product information, thereby increasing interaction and enabling more personalized services. However, there is a notable scarcity of reputable domestic research that addresses AI as a valuable marketing tool. Furthermore, findings from international studies may not be directly applicable to the Iranian market and business environment, necessitating localization. Given this context, it is essential for online retailers to gain a deeper understanding of how consumers perceive and utilize AI, as well as their levels of trust and satisfaction. Addressing the relationship between AI and customer satisfaction as a new marketing strategy has become an urgent necessity. Additionally, businesses must learn how to effectively leverage AI to enhance customer satisfaction. Therefore, this study aimed to investigate the impact of AI on customer satisfaction. Materials & Methods This research was descriptive in nature with an applied purpose and a quantitative approach for data collection. A quantitative method based on hypothesis formulation was selected given the availability of variables to be measured as AI tools. The statistical population comprised undergraduate and graduate students from the Computer Engineering Department at Lorestan University, who had at least one shopping experience and had utilized AI components provided by the store (such as chatbots and personalized recommendations). The selection of this group was based on their familiarity with the concepts and fundamental components of AI, ensuring that they could provide accurate and relevant responses to the questionnaires. This approach aimed to enhance the reliability of the data by excluding uninformed or unrelated individuals. The statistical population included 240 computer engineering students at Lorestan University, from which a sample of 150 was determined through stratified random sampling with proportional allocation. An online questionnaire developed by the researchers was used to collect data. The validity of the questionnaire was confirmed by a panel of experts and its reliability was established through a pilot test, yielding a Cronbach's alpha coefficient of 0.89. Finally, SPSS and LISREL software were employed to analyze and interpret the data. Research Findings Sub-hypothesis 1: The results of the regression analysis indicated that the chatbot variable in AI significantly impacted customer satisfaction, confirming the 1 st sub-hypothesis of the study. Chatbots enabled 24/7 customer service, allowing customers to resolve issues and access necessary information at any time. This enhanced accessibility and responsiveness could lead to increased customer satisfaction. Furthermore, chatbots provided quick and accurate responses to customer inquiries, improving the shopping experience and fostering a greater sense of satisfaction. Sub-hypothesis 2: The regression analysis results also confirmed the 2 nd sub-hypothesis regarding the effect of personalized recommendations in AI on customer satisfaction. Personalized recommendations created the impression that customers' needs and preferences were accurately understood and taken into account. By analyzing customer data and purchasing patterns, these recommendations aligned with each customer's specific needs, thereby increasing both satisfaction and loyalty. Sub-hypothesis 3: The findings from the regression analysis supported the 3 rd sub-hypothesis, which focused on the impact of an advanced shopping experience in AI on customer satisfaction. An advanced shopping experience encompassed user-friendly interfaces, personalized recommendations, real-time support via chatbots, and streamlined purchasing processes. These elements collectively enhanced convenience and enjoyment for customers during their shopping journey. Sub-hypothesis 4: The regression analysis results confirmed the 4 th sub-hypothesis related to the effect of Search Engine Optimization (SEO) enhanced by AI on customer satisfaction. AI-driven SEO optimally delivered content and products to customers, thereby improving the user experience. By employing AI algorithms, search engines could present search results that were more accurate and relevant to customer needs, which enhanced satisfaction during the search and purchasing process. Sub-hypothesis 5: Finally, the regression analysis indicated that voice and image recognition tools in AI significantly influenced customer satisfaction in purchasing consumer goods, confirming the 5 th sub-hypothesis. These tools enhanced the user experience by simplifying and personalizing the purchasing process, making it more intuitive and enjoyable for customers. Discussion of Results and Conclusion Main Hypothesis: With the confirmation of all sub-hypotheses, the main hypothesis was validated: AI significantly impacted customer satisfaction in the purchase of consumer goods. This assertion could be explained by the way AI enhanced the shopping experience through personalized recommendations and data analysis, which reduced waiting times and increased overall satisfaction. AI technology could identify customer purchasing patterns and provided product suggestions tailored to individual preferences and needs, thereby boosting customer satisfaction. Additionally, AI tools facilitated faster and more efficient responses to customer inquiries and issues. For instance, chatbots were readily available to answer common questions and resolve typical problems. These features not only minimized customer wait times, but also contributed to a more positive shopping experience. The following practical suggestions emerged from the research: Implementing gamification elements in the AI-driven shopping experience Creating personalized offers based on the analysis of shopping data Utilizing interactive audio and video tools to enhance customer support Acknowledgments This article is the outcome of a master's thesis in Business Management, specifically focusing on Marketing. We would like to extend our heartfelt gratitude for the material and moral support provided by Razi University, as well as the contributions of all participants involved in this research.
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