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Yoga Adiyanto. "The Future of Virtual Shopping Assistants : AI-Powered Solutions for a Personalized Marketplace Experience." Green Inflation: International Journal of Management and Strategic Business Leadership 2, no. 2 (2025): 59–73. https://doi.org/10.61132/greeninflation.v2i2.323.
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The advancement of artificial intelligence (AI) technology has transformed the paradigm of shopping experiences on e-commerce platforms. This article examines the future of AI-powered virtual shopping assistants designed to provide personalized solutions in the digital marketplace experience. Virtual shopping assistants, driven by technologies such as chatbots, voice assistants, and machine learning, enable consumers to receive more relevant product recommendations and a shopping experience tailored to their preferences. This study aims to explore how the implementation of AI-powered virtual shopping assistants can enhance customer loyalty, sales conversion, and consumer satisfaction in online marketplaces. Using a mixed-method approach involving in-depth interviews and quantitative surveys, the research identifies consumer perceptions of this technology and its impact on their purchasing decisions. Findings reveal that consumers who engage with AI-powered virtual shopping assistants report more personalized and satisfying shopping experiences, contributing to increased loyalty and sales conversion for e-commerce platforms. This article provides practical insights for marketplace managers to optimize the use of AI in creating more personalized and responsive shopping experiences. Furthermore, this research opens opportunities for further exploration of AI integration across various digital shopping channels.
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Manke, Priyanka, Akanksha Bele, Razaan Rizvi, Vidha Naik, and Harsh Singh. "Virtual Personal Shopping Assistant (VSPA)." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem42453.
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In recent years, advancements in artificial intelligence (AI) and augmented reality (AR) have led to the development of virtual personal shopping assistants (VPSAs) that enhance the online shopping experience. This paper presents a comprehensive overview of a VPSA that utilizes camera technology for virtual try-ons and clothing recommendations. The system leverages AI algorithms for personalized recommendations, combining user preferences, body measurements, and fashion trends. Through the use of augmented reality, users can virtually try on clothes in real time, allowing them to visualize how items will fit and look without needing to visit a physical store. The VPSA also employs machine learning models to analyze user preferences, past purchases, and social media trends to curate personalized shopping suggestions. The system improves over time by learning from user interactions, providing increasingly accurate recommendations. By merging computer vision, AR, and AI-driven recommendations, the VPSA offers a seamless and immersive shopping experience that can revolutionize online fashion retail. This virtual shopping assistant not only enhances user satisfaction by reducing uncertainty in fit and style but also boosts retailers' conversion rates by minimizing returns and improving customer retention. The integration of such technologies promises a future where the convenience of online shopping matches, or even surpasses, that of traditional brick-and-mortar experiences.
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Sivakumar, R. D. Assistant Professor Department of Computer Science, and S. Former Assistant Professor of Business Administration Brindha. "VIRTUAL ASSISTANTS AND CHATBOTS IN RETAIL." Indian Journal of Research and Development Systems in Technologization 1, no. 4 (2024): 1–11. https://doi.org/10.5281/zenodo.12643572.
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<em>Today, virtual assistants and chatbots are playing a very important role in retail to boost the customer experience, reduce costs, and change the way of selling the products. The aim of this paper is to study the virtual assistants and chatbots for retail business in terms of feasibility, advantages, and drawbacks. Consumer services in the form of Virtual Assistants enabled with Artificial Intelligence (AI) and Natural Language Processing (NLP) mechanisms enhance the support and selling propositions to consumers improving customer satisfaction and retention. They can be employed as virtual assistants in the retail websites as well as the messaging apps where they interact with customers, answer questions, offer updates on order status, and provide other services. Organizations should embrace and implement virtual assistants and chatbots as they drive down the operational costs of retail especially in the sectors of customer advocacy. However, there are concerns that need to be addressed including data security, accuracy of responses as well as compatibility with other systems. However, the future of virtual assistants and chatbots in retail seems rather bright due to the continuous improvements in the technologies used and the growing adoption of automated services by consumers. This paper concludes by discussing the future vision to explore, such as voice assistants and personal shopping which are likely to revolutionize the future of retail with a brand new level of efficiency and customer satisfaction.</em>
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Ali, MD Mohsin, S. Vamshi, S. Shiva, and S. Bhanu Prakash. "Virtual Assistant Using Supervised Learning." International Journal for Research in Applied Science and Engineering Technology 11, no. 6 (2023): 3239–45. http://dx.doi.org/10.22214/ijraset.2023.54262.
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Abstract: Todays modern world, everything got evoluted including technology from vacuum tubes to nanoelectronics.Now a days the total world is in single palm of human in the form of mobile.But these days we aren’t using hands, instead we using voice commands to wake electronics devices like mobiles,it is not only in mobiles, also in every electronics.This type of usage is possible by embedding a virtual assistant into electronics. Virtual Assistants are software programs that help you ease your day to day tasks, such as showing weather report, creating reminders, making shopping lists etc. They can take commands via text (online chat bots) or by voice. This paper delivers steps to build a web based virtual assistant using supervised learning to achieve goals which cannot done by the VA’s in market.And as this model uses supervised learning, so there will be limited commands and data to maintain it in our control.
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Anushree, P., and S. Prakash. "The Role of AI Chatbots and Virtual Shopping Assistants in Shaping Festive Season Purchase Decisions." Thiagarajar College of Preceptors Edu Spectra 7, no. 1 (2025): 46–56. https://doi.org/10.34293/eduspectra.v7i1.07.
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Artificial Intelligence (AI) is transforming the retail industry, with virtual shopping assistants and chatbots enhancing online shopping through personalized recommendations, real-time support, and seamless navigation. As digital retail becomes essential for customer engagement, especially during festive seasons, AI tools play a significant role in creating convenient, tailored shopping experiences. Despite the growing role of AI in retail, limited research exists on its impact on consumer trust, satisfaction, and purchasing decisions during major shopping events like festivals. Given that festivals are some of the largest shopping events, understanding the role of AI in influencing consumer behaviour is essential for businesses aiming to boost engagement and drive sales. In recent times, companies predominantly focus on youngsters, considering their tech-savvy nature and active engagement with AI-driven platforms, that plays a vital role in festive season purchasing decisions. Therefore, the present study aims at examining the impact of AI-driven interactions on satisfaction, trust, and purchase intentions during festivals among students between the age group of 17 - 23 years of arts and science colleges in Madurai. It is proposed to collect primary data using convenient sampling method using Google form. The collected data will be analysed using Microsoft Excel, Percentage Analysis, and Garret Ranking and provide suggestions for the companies to strengthen customer engagement and loyalty by offering insights into effective AI integration, enabling a more personalized, efficient, and satisfying shopping experience for customers.
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G. Takale, Dattatray. "Revolutionizing Customer Interaction: NLP-Powered Virtual Shopping Assistants and Sentiment Analysis in E-commerce." JOURNAL OF FIREWALL SOFTWARE AND NETWORKING 2, no. 2 (2024): 1–5. http://dx.doi.org/10.48001/jofsn.2024.221-5.
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The title of the research article investigates the revolutionary influence that Natural Language Processing (NLP) and sentiment analysis have had on the interactions that customers have with businesses that are involved in e-commerce. Among the primary goals are the investigation of the applications of natural language processing (NLP) in the powering of virtual shopping assistants and the evaluation of the relevance of sentiment analysis in comprehending the level of customer pleasure. An in-depth assessment of the current literature, case studies of successful implementations, and an analysis of customer evaluations and attitudes are all components of the technique. The results highlight the critical role that natural language processing plays in the enhancement of virtual shopping assistants, the improvement of product suggestions, and the simplification of the process of making a purchase choice. Additionally, sentiment analysis is essential for determining the feelings and feedback of customers, which in turn influences the strategic decisions that are made by organisations that deal in e-commerce enterprises.
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Calahorra-Candao, Guillermo, and María José Martín-de Hoyos. "From Typing to Talking: Unveiling AI’s Role in the Evolution of Voice Assistant Integration in Online Shopping." Information 15, no. 4 (2024): 202. http://dx.doi.org/10.3390/info15040202.
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This study develops a theoretical framework integrating the Technology Acceptance Model (TAM) and Uses and Gratifications Theory (UGT) to predict and understand the acceptance of voice shopping intentions, particularly through AI-driven voice assistants. This research delves into the dual aspects of AI voice shopping platforms: the functional attributes outlined by the TAM and personal gratifications highlighted by the UGT, such as enjoyment, performance expectancy, and perceived safety. It uncovers a favorable user attitude towards voice shopping, emphasizing the significant role of performance expectancy and perceived utility on behavioral intentions. Key insights include the critical importance of security and privacy for user trust and the acceptance of new AI technologies, and the necessity of a balanced approach that merges functional, emotional, and security aspects for successful AI integration in daily technology use. Contrary to expectations, this study reveals a weak relationship between social norms and perceived usefulness, suggesting a misalignment with societal expectations. This research enriches the understanding of voice shopping using virtual assistants, offering valuable insights into consumer behavior and AI technology acceptance. It highlights practical implications for AI research, the development of voice-based software, and AI-driven advertising strategies, emphasizing the communication of benefits and emotional resonance in voice-enabled AI assistants for consumer purchases.
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Researcher. "AI-Powered E-Commerce: Enhancing Search & Order Placement with Generative Models." ISCSITR- International Journal of Artificial Intelligence (ISCSITR-IJAI) 6, no. 1 (2025): 44–59. https://doi.org/10.5281/zenodo.14929575.
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Artificial intelligence's incorporation into e-commerce signifies a revolutionary change in online retail operations, radically altering how companies engage with their clientele and run their enterprises. This thorough analysis looks at the effects of AI in four primary areas: future implications, checkout and security, shopping assistance, and search and discovery. The article describes how multi-modal search, natural language processing, and enhanced personalization are just a few of the ways AI-powered technologies have transformed client experiences. While providing strong protection against fraud, the deployment of blockchain-integrated security measures and intelligent shopping assistants has improved operational efficiency. Significant gains in customer interaction, conversion rates, and operational efficiency throughout the e-commerce ecosystem are illustrated in the study.
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Ntumba, Charles, Samuel Aguayo, and Kamau Maina. "Revolutionizing Retail: A Mini Review of E-commerce Evolution." Journal of Digital Marketing and Communication 3, no. 2 (2023): 100–110. http://dx.doi.org/10.53623/jdmc.v3i2.365.
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This review article delves into the transformative journey of e-commerce, tracing its inception in the mid-1990s, characterized by visionary companies such as Amazon, eBay, Alibaba, PayPal, and Dell. These pioneers laid the foundation for a digital commerce revolution, with technological innovations, particularly in mobile technology, reshaping the e-commerce landscape and providing users with seamless, on-the-go shopping experiences. The integration of augmented reality (AR) and virtual reality (VR) further bridged the gap between physical and digital realms, offering immersive product interactions. Artificial intelligence (AI) emerged as a transformative force, utilizing algorithms to analyze user data and personalize online shopping experiences. AI-driven chatbots and virtual assistants enhanced customer support, contributing to an overall personalized shopping journey. The predictive capabilities of AI enabled platforms to anticipate user behavior and strategically deploy personalized recommendations. Evolving consumer behavior, influenced by the convenience of online shopping and social media, is a central theme, with the rise of conscious consumers emphasizing sustainability and ethical practices in purchasing decisions. Looking forward, future trends in e-commerce include the continued dominance of AI in refining personalization, the potential of blockchain for transparency and security, and the integration of the Internet of Things (IoT) for a more connected shopping experience. AR, VR, voice commerce, and cross-border e-commerce are anticipated to play significant roles.
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PRABHASH, PANDEY, KUMAR MADDHESHIYA VISHAL, RITESH SOHAN SINHA, and KUMAR TIWARI PUNEET. "A Study on "Consumer Attitude towards Digital Voice Assistants." International Journal of Innovative Science and Research Technology 8, no. 3 (2023): 108–18. https://doi.org/10.5281/zenodo.7735548.
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Usage of digital voice assistants is increasing rapidly among consumers around the world, in 2020, 4.2 billion digital voice assistants were being used and they are projected to grow to 8.4 billion units by 2024. Looking to the rapid usage of voice assistants it is crucial to analyze consumers attitude and preferences towards it. Digital voice assistants are highly complex and voice enabled artificial intelligence based technologies. Consumers use digital voice assistants to perform a series of tasks such as making call, online shopping, listening to music, etc. This article critically examinesthe frequency of usage of virtual assistants across different age groups. We analyzed that younger user, used the voice assistants more frequently and they used voice assistants for a variety of tasks. On the other hand, elder people relied less on these assistants and used it rarely. Also, we analyzed gender-based differences in awareness of consumers regarding virtual assistants and learning rate of consumers of different age group. In this study, 120 survey responses from a variety of consumers were analyzed. Customers attitude was measured using sampling method. So we have decided to study consumers attitude towards digital voice assistants and various factors which influence consumers attitude. The population of the study is students and faculties of lovely professional university, phagwara. The sample size is 120(60 males and 60 females) and we have used sampling method for the study. Our findings indicate that males have higher awareness rate as compared to females, and younger people found it easy to use voice assistants on their own. On the other hand, elderly people felt the need of a technical person to use voice assistants. The research also found that various factors such as Accuracy, Confidentiality, Functionality and Ads free greatly influence consumers attitude towards voice assistants. We analyzed the consumers preference towards these factors. It is expected that this study will help marketers to better understand consumers attitude about voice assistants and they can build better relations with consumers.
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Bhuiyan, Mohammad Shafiquzzaman. "The Role of AI-Enhanced Personalization in Customer Experiences." Journal of Computer Science and Technology Studies 6, no. 1 (2024): 162–69. http://dx.doi.org/10.32996/jcsts.2024.6.1.17.
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The purpose of this research study is to investigate how AI-driven-personalization chatbots and virtual assistants might improve customer experiences across different types of businesses. It investigates if artificial intelligence is able to cater goods, services, and marketing to the preferences of customers. The areas of retail and hospitality, together with finance, are the primary emphasis of this article. This study investigates the ways in which artificial intelligence can improve retail virtual shopping assistants and product recommendations. This article investigates the use of artificial intelligence (AI) chatbots in the hotel industry to give individualized booking experiences and recommendations. This study investigates the ways in which artificial intelligence-driven communications and individualized financial advice can improve customer service. Through the use of case studies and data analysis, the author of this study analyzes the practical uses of AI-powered personalization as well as the benefits to the customer experience. The findings are an attempt to illustrate that AI is capable of personalizing their experiences and engaging customers across a variety of industries.
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Calahorra-Candao, Guillermo, and María José Martín-de Hoyos. "The effect of anthropomorphism of virtual voice assistants on perceived safety as an antecedent to voice shopping." Computers in Human Behavior 153 (April 2024): 108124. http://dx.doi.org/10.1016/j.chb.2023.108124.
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Harpreet Singh. "The Metaverse Revolution: Transforming the Future of Retail." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 2 (2025): 109–15. https://doi.org/10.32628/cseit251112391.
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This comprehensive article explores the transformative impact of the Metaverse on the retail industry, examining how this immersive digital realm is revolutionizing traditional commerce paradigms. It investigates the convergence of cutting-edge technologies with innovative retail strategies, highlighting the evolution from static retail spaces to dynamic, AI-driven environments. It delves into real-time customer intelligence systems, adaptive retail environments, and sophisticated technical infrastructure components, including edge computing, blockchain, and artificial intelligence. The article examines practical applications such as virtual showrooms, AI-powered shopping assistants, hyper-personalized marketing, and supply chain optimization. Through extensive analysis of current industry research and market trends, this article demonstrates how the Metaverse is fundamentally reshaping customer interactions, operational efficiency, and business models in the retail sector. It reveals the critical role of emerging technologies in creating seamless, personalized shopping experiences that bridge physical and digital retail environments, while also addressing the challenges and opportunities presented by this digital transformation.
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Lima, Michelle Lins de. "THE FASHION REVOLUTION WITH ARTIFICIAL INTELLIGENCE: PERSONALIZATION, EXPERIENCE, AND SUSTAINABILITY." Revista ft 29, no. 145 (2025): 04–05. https://doi.org/10.69849/revistaft/ch10202504040804.
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Artificial intelligence (AI) is reshaping the fashion industry, promoting more personalized and efficient shopping experiences. The integration of AI with data analysis allows brands to predict consumer trends and offer recommendations tailored to the individual preferences of each consumer. Brands are leveraging large volumes of data, such as purchase histories and online interactions, to adapt their offerings and create unique shopping experiences. AI has transformed customer service, with the use of chatbots and virtual assistants providing continuous support, helping consumers make more informed and personalized decisions. In addition to enhancing the customer experience, AI is also promoting more sustainable practices in fashion, such as on-demand production and personalized clothing. These practices enable the creation of custom-made pieces, catering to the preferences and demands of consumers while reducing waste. By using AI tools to create personalized clothing, brands can offer an experience more aligned with the customer’s desires, while minimizing the need for large inventories, contributing to a more sustainable future. Recent studies highlight the crucial role of AI in building stronger customer loyalty by creating more engaging and personalized shopping experiences. AI’s ability to analyze data and understand consumer behavior enables brands to connect with their customers on a deeper level, promoting a more efficient and effective shopping experience. In this way, artificial intelligence is not only transforming the fashion shopping experience but also shaping a more connected, creative, and sustainable future for the industry.
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Pauser, Sandra, and Udo Wagner. "Judging a Book by Its Cover: Assessing the Comprehensibility and Perceived Appearance of Sign Language Avatars." Marketing ZFP 42, no. 3 (2020): 48–62. http://dx.doi.org/10.15358/0344-1369-2020-3-48.
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The use of avatars is gaining popularity in today’s digitalized world. These computer-animated agents not only act as virtual shopping assistants to compensate for the impersonal feel of an online store, but are also frequently employed in gaming and social networking, and have recently served as animated characters for translation in the deaf community. New technological developments (sign language avatars) offer significant advantages for deaf users in daily interactions. This article explores how attitudes towards avatars, and subsequent satisfaction with the design company involved, can be increased through various measures. This experimental study manipulates the physical traits of signing avatars (gender, hairstyle, and dress) and analyses the outcomes in terms of their perceived properties, appearance, and comprehensibility, as well as more direct indicators of success (attitudes towards these avatars and satisfaction with the company). An industry partner cooperated in the empirical study to ensure the external validity of the findings.
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Gaikwad, Prof Dnyanesh. "AI Enabled E-commerce Platform." International Journal for Research in Applied Science and Engineering Technology 13, no. 6 (2025): 567–74. https://doi.org/10.22214/ijraset.2025.72128.
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An overview of AI-based e-commerce plat forms and their effects on the online retail sector is given in this survey. Businesses are starting to use artificial intelligence (AI) to improve customer experience, streamline processes, and boost revenue development in the e-commerce industry as a result of the technology’s rapid advancement. This research offers a thorough ex amination of the state of AI-based e-commerce platforms today, stressing their salient characteristics, advantages, difficulties, and potential. The first part of the poll introduced artificial intelligence (AI) and how it relates to e-commerce. It looks at how artificial intelligence (AI) technologies— like computer vision, machine learning, natural language processing, and recommendation systems—are being incorporated into e-commerce platforms to provide intelligent customer support, enhance product search and discovery, and offer personalized shopping experiences. Additionally, it explores the role of AI in enhancing customer engagement through chatbots, virtual assistants, and personalized marketing campaigns.
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Upasana, Das. "AI Powered Consumer Behavior in e-Commerce." International Journal of Contemporary Research in Multidisciplinary 3, no. 4 (2024): 01–13. https://doi.org/10.5281/zenodo.12679257.
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As the e-commerce industry continues to evolve, artificial intelligence (AI) has emerged as a powerful tool for understanding and influencing consumer behavior. This review explores the convergence of e-commerce and consumer behavior, emphasizing the significant influence of AI-driven personalization on market trends. AI-powered technologies have the ability to analyze vast amounts of data in real-time, providing valuable insights into consumer preferences, shopping patterns, and decision-making processes. By leveraging AI algorithms, e-commerce retailers can personalize the shopping experience, recommend products, and optimize pricing strategies to maximize sales and customer satisfaction. Additionally, AI can streamline the purchasing process by offering chatbots for customer support, virtual assistants for product recommendations, and predictive analytics for inventory management. The investigation explores how machine learning algorithms can be used to forecast customer preferences, expedite the purchase process, and create a more customized shopping experience. The review also examines the difficulties and moral dilemmas posed by AI-powered personalization as e-commerce develops. To give a thorough grasp of the wider ramifications of AI in influencing consumer behavior, issues like algorithmic bias, data privacy, and the careful balancing act between personalization and intrusiveness are studied. This analysis provides insightful information about the mutually beneficial interaction between e-commerce and consumer behavior, highlighting the revolutionary potential of AI-powered personalization and its impact on developing market trends. Businesses must comprehend and take advantage of AI-driven tactics in order to remain competitive as they navigate the digital landscape. This combination of data-driven insights and automated decision-making has the potential to revolutionize the way consumers interact with online retailers, ultimately shaping the future of e-commerce
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Rigas, Dimitrios, Hammad Akhtar Hussain, and Nazish Riaz. "Online Branding and Marketing." International Journal of Sociotechnology and Knowledge Development 8, no. 2 (2016): 27–38. http://dx.doi.org/10.4018/ijskd.2016040103.
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Multimodal is quite established as communication metaphor in user interfaces and there is at least some limited prima facie case that can be used to influence positively consumer behaviour. This paper explores the perceptions of users to interactive multimodal e-branding and its effect on the consumer purchase decision. A sample of 200 respondents, was used as a basis to explore marketing techniques on social media and multimodal influence on consumer purchase decisions. The results and their analysis indicated that advertisements or messages to users with audio, video and text on in combination are the most effective forms of compiling multimodal messages that aim to advertise, persuade and eventually lead to a purchase on the e-commerce and social media platforms. The data also pointed to the use of multimodal Virtual Shopping Assistants. These findings provide an overall viewpoint on user perception that can be used as a basis for a series of empirical experiments in simulations to identify the specific user influence under particular user context and multimodal messages.
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Liu, Yijia. "A Study of the Impact of Emerging Digital Marketing Technologies on Consumer Behaviour." International Journal of Global Economics and Management 5, no. 2 (2024): 7–15. https://doi.org/10.62051/ijgem.v5n2.02.
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With the advent of the digital era, emerging digital marketing technologies have had a profound impact on consumer behaviour. This thesis explores the definition and classification of digital marketing technologies, analyses their specific impact on consumer behaviour, and delves into the relationship between technological adaptation and changes in consumer behaviour. The thesis provides an overview of how emerging technologies such as personalised marketing, social media marketing, augmented reality (AR) and virtual reality (VR) technologies, as well as voice assistants and smart home devices, are changing the way consumers make shopping decisions and interact with brands. The paper explores how these technologies are influencing consumers' purchasing decisions by improving perceived convenience, enhancing user engagement and providing personalised experiences. At the same time, the paper discusses the challenges of data privacy protection, legal and regulatory compliance, and ethics, and looks at the future direction of technology development, emphasising the importance of striking a balance between innovation and privacy protection. By systematically analysing these issues, the paper provides valuable insights and recommendations for companies when formulating their digital marketing strategies, in order to drive sustainable market development and consumer experience.
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Rattan, Ratnesh Kumar, and Manoj Kumar Yadav. "ARTIFICIAL INTELLIGENCE: DERIVATIVE ADVANCE ADVANTAGE IN E-COMMERCE." INTERNATIONAL JOURNAL OF ADVANCED RESEARCH IN COMMERCE, MANAGEMENT & SOCIAL SCIENCE 08, no. 01(II) (2025): 113–18. https://doi.org/10.62823/ijarcmss/8.1(ii).7254.
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Artificial intelligence (AI) has revolutionized the world of e-commerce in recent years. With its ability to process huge amounts of data, analyze customer behavior, and make accurate predictions, AI has become an essential tool for businesses looking to increase their sales and stay ahead of competition. AI's ability to constantly improve makes it a key asset in e-commerce. This means that AI can learn from past data and experiences and use that knowledge to improve its performance over time. With AI-powered chat bots and virtual assistants becoming increasingly popular in online shopping platforms, businesses are able to provide personalized customer service 24/7 without the need for human intervention. Chat bots assist customers with their queries and collect information about their preferences for targeted marketing. Another key advantage of using AI in e-commerce is its ability to optimize pricing strategies through dynamic pricing algorithms. Moreover, AI-powered recommendation engines have become vital tools for e-commerce retailers. By analyzing customer data such as browsing history and purchase patterns, these engines provide personalized product suggestions that are highly relevant to each individual shopper.
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Bouhlal, Hind, and Noureddine Belahcen. "The Influence of Conversational AI on Consumer Behavior and Counterfactual Thinking: A Systematic Review." European Scientific Journal, ESJ 21, no. 4 (2025): 69. https://doi.org/10.19044/esj.2025.v21n4p69.
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This document evaluates the development and importance of conversational AI, chatbots, and virtual assistants in shaping human behavior and decision-making,particularly in the context of e-commerce. It is designed to investigate the impact of AI on the personalization of user experiences, and maps how the automation of decision-making affects cognitive processes like counterfactual thinking and regret. The findings sugest that while conversational AI enhances the shopping experience through personalized product recommendations, it can also trigger cognitive biases such as regret by exposing consumers to alternative options, leading them to reconsider their initial choices. This raises concerns about AI risk mitigation, particularly regarding transparency, psychographic profiling,and the emotional influence of AI-driven decision-making. Importantly,the study highlights that consumers do not inherently dislike AI; rather,they seek a more ethical and culturally aware approach to its implementation. A responsible AI design could not only improve user experience but also strengthen consumer trust in AI-driven products and services.To fully understand tese dynamics, longitudinal studies are needed to assess the long-term effects of conversational AI on consumer satisfaction, loyalty,and decision-making. Additionally,cross-cultural comparisons will provide deeper insights into how consumer perceptions and interactions with AI vary across different markets.
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Jamakhandi, Harish. "Understanding Consumer Preferences in E-Commerce: A Data-Driven Approach." Journal of Research & Development 17, no. 1 (2025): 153–60. https://doi.org/10.5281/zenodo.14964139.
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<strong><em>Abstract</em></strong> <em>In an era characterized by the rapid growth of e-commerce, understanding consumer preferences has become a critical driver of strategic decision-making, prompting the need for a comprehensive, data-driven approach to unravel the complexities of online purchasing behavior, which is increasingly influenced by a combination of psychological, sociocultural, and technological factors; this study aims to explore the intersection of these dimensions through the development of a conceptual framework that integrates existing theories of consumer behavior, such as the Theory of Planned Behavior (TPB), Technology Acceptance Model (TAM), and Unified Theory of Acceptance and Use of Technology (UTAUT), with novel insights drawn from recent big data analytics, particularly focusing on how real-time, granular consumer data, such as browsing patterns, transaction history, sentiment analysis from social media, and clickstream data, can be utilized to gain deeper insights into the preferences, motivations, and decision-making processes of online shoppers; leveraging advanced techniques in machine learning, predictive modeling, and natural language processing, this paper proposes a multi-layered model that not only accounts for traditional demographic and psychographic variables but also incorporates contextual factors such as personalized recommendations, user interface design, and the role of artificial intelligence (AI) in shaping personalized shopping experiences, all while addressing the potential biases and ethical concerns associated with consumer data collection and privacy; the findings of this theoretical exploration provide a nuanced understanding of the interplay between consumer trust, convenience, and perceived risk, shedding light on how different e-commerce platforms can tailor their offerings based on consumer-specific patterns and preferences, thus enhancing user engagement, conversion rates, and long-term customer loyalty; furthermore, the study discusses the implications of evolving consumer expectations in the digital marketplace, where factors such as omnichannel experiences, cross-platform consistency, and the integration of virtual assistants and chatbots are becoming increasingly pivotal in shaping the online shopping journey; ultimately, this paper serves as a foundational work for both scholars and practitioners, offering new directions for research in the domain of e-commerce consumer behavior and providing actionable insights for businesses looking to innovate and optimize their e-commerce strategies in a data-driven, ethically responsible manner.</em>
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Echegu, Darlington Arinze. "Artificial Intelligence (AI) in Customer Service: Revolutionising Support and Engagement." IAA Journal of Scientific Research 11, no. 2 (2024): 33–39. http://dx.doi.org/10.59298/iaajsr/2024/112.3339.
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Customer service, marketing, human resource management, finance, accounting, product and service development, healthcare, commerce, and manufacturing are just a few of the areas where artificial intelligence (AI) has completely changed the game. AI enhances decision-making and work processes by means of machine learning algorithms, automation, and predictive analytics. AI makes it possible to personalise, target adverts accurately, and forecast sales in marketing. Through recruiting, performance reviews, and training of employees, AI in human resource management raises productivity and engagement. Demand forecasting, inventory control, and condition based monitoring are all made easier in factory management by artificial intelligence. Maintaining compliance requirements, AI also helps with risk reduction, financial reporting, and fraud prevention. AI enhances consumer happiness and competitiveness in product creation via use of data analytics, modelling, and suggestions. AI also aids in strategic planning and decision-making in healthcare and life sciences. In retail and e-business, AI improves stocking management, customer profiling, and shopping experiences. This review examines AI in Customer Service: Revolutionising Support and Engagement. We utilised relevant published data (2004–2014) from diverse, reliable databases. Findings suggest that other trends like creative AI, XAI, and quantum computing, as well as collaboration between human beings and AI, continue to advance. As a result, ethical concerns remain a critical element to address when it comes to the application of AI, identifying both threats and opportunities. Finally, we note that AI continues to be a formidable and revolutionary force in organisations, enhancing value creation while promoting ethical principles. Keywords: Artificial Intelligence, Customer Service, Chatbots, Virtual Assistants, Predictive Analytics, Manufacturing, Creative AI
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Deshmukh, Prof Anushree, Smit Shah, Heena Puthran, and Naisargi Shah. "Virtual Shopping Assistant for Online Fashion Store." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (2022): 110–17. http://dx.doi.org/10.22214/ijraset.2022.42099.
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Abstract: A new way for individuals to interact with computer systems will be done through chatbots or conversational interfaces. Historically, introducing a matter answered by a software package involves employing a program or filling out a type. The technology at the core of the increase of the chatbot is NLP i.e., Natural Language Processing. Sequence to Sequence (often abbreviated to seq2seq) fashions is a specific type of Recurrent Neural Network architectures that we commonly use (but no longer restricted) to clear up complicated Language issues like Machine Translation, Question Answering, growing Chatbots, Text Summarization, and so forth. Recent advances in machine learning have greatly improved the accuracy and effectiveness of NLP, creating chatbots a viable choice for several organizations like e-commerce, Customer service, Conversational apps, social media, Sales/Marketing/Branding, as Voice modules, Travel industry, Medicine, Hospitality, Human Resources etc. An NLP primarily based chatbot is a pc software or synthetic brain that communicates with a patron by means of textual or sound strategies This improvement in NLP is firing a great deal of additional analysis and research which should lead to continued growth in the effectiveness of chatbots in the years to come. Stochastic gradient descent (often abbreviated SGD) is an iterative approach for optimizing an goal characteristic with appropriate smoothness homes (e.g. differentiable or sub differentiable). Usage of Chatbots can also prove to be beneficial in ways like economically offering 24/7 service, improving customer satisfaction, reaching a younger demographic, reducing costs, increasing revenue and much more. Keywords: Chatbots, Natural Language Processing (NLP), Stochastic Gradient Descent (SGD), Sequential Model, Machine Learning
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Mah, Pascal Muam, Iwona Skalna, and John Muzam. "Natural Language Processing and Artificial Intelligence for Enterprise Management in the Era of Industry 4.0." Applied Sciences 12, no. 18 (2022): 9207. http://dx.doi.org/10.3390/app12189207.
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Introduction: The advances in the digital era have necessitated the adoption of communication as the main channel for modern business. In the past, business negotiations, profiling, seminars, shopping, and agreements were in-person but today everything is almost digitalized. Objectives: The study aims to examine how the Internet of things (IoTs) connects text-object as part of NLP and AI responding to human needs. Also, how precipitated changes in the business environment and modern applications such as NLP and AI embedded with IoTs services have changed business settings. Problem statement: As communication takes lead in the business environment, companies have developed sophisticated applications of NLP that take human desires and fulfill them instantly with the help of text, phone calls, smart records, and chatbots. The ease of communication and interaction has shown a greater influence on customer choice, desires, and needs. Modern service providers now use email, text, phone calls, smart records, and virtual assistants as first contact points for almost all of their dealings, customer inquiries, and most preferred trading channels. Method: The study uses text content as part of NLP and AI to demonstrate how companies capture customers’ insight and how they use IoTs to influence customers’ reactions, responses, and engagement with enterprise management in Industry 4.0. The “Behavior-oriented drive and influential function of IoTs on Customers in Industry 4.0” concept was used in this study to determine the influence of Industry 4.0 on customers. Results: The result indicates the least score of 12 out of 15 grades for all the measurements on a behavior-oriented drive and influential function of IoTs on customers. Conclusion: The study concluded that NLP and AI are the preferred system for enterprise management in the era of Industry 4.0 to understand customers’ demands and achieve customer satisfaction. Therefore, NLP and AI techniques are a necessity to attain business goals.
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Olubusola Odeyemi, Oluwafunmi Adijat Elufioye, Noluthando Zamanjomane Mhlongo, Andrew Ifesinachi Daraojimba, Funmilola Olatundun Olatoye, and Kehinde Feranmi Awonuga. "AI in E-commerce: Reviewing developments in the USA and their global influence." International Journal of Science and Research Archive 11, no. 1 (2024): 1460–68. http://dx.doi.org/10.30574/ijsra.2024.11.1.0232.
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The integration of Artificial Intelligence (AI) in the field of E-commerce has witnessed significant developments in the United States, subsequently influencing global trends and practices. This study explores the recent advancements and their broader impact on the E-commerce landscape. In the USA, AI technologies have become integral to enhancing customer experiences and optimizing operational efficiency in E-commerce platforms. Machine learning algorithms are increasingly employed for personalized recommendations, creating a more tailored shopping experience for users. Natural Language Processing (NLP) applications enable improved customer interactions through chatbots and virtual assistants, streamlining customer service processes. Furthermore, AI-driven predictive analytics has revolutionized inventory management and demand forecasting, allowing E-commerce businesses to optimize stock levels, reduce costs, and minimize out-of-stock situations. This data-driven approach not only enhances operational efficiency but also contributes to a more sustainable and resilient supply chain. The influence of AI in the USA has transcended domestic boundaries, shaping global E-commerce practices. As American E-commerce giants implement cutting-edge AI technologies, other nations look to adopt similar strategies to remain competitive in the global market. The adoption of AI is particularly pronounced in emerging E-commerce markets, where technological advancements play a pivotal role in leapfrogging traditional retail models. Despite these advancements, challenges such as data privacy concerns and ethical considerations surrounding AI algorithms persist. Striking a balance between innovation and responsible AI implementation is crucial to ensuring sustained growth and societal trust in E-commerce platforms (Ilugbusi et al., 2020). AI has become a transformative force in the USA's E-commerce sector, triggering a ripple effect on a global scale. As the technological landscape evolves, a comprehensive understanding of the developments in the USA provides valuable insights for E-commerce stakeholders worldwide, guiding them in harnessing the full potential of AI for future growth and innovation.
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Mustafa Ayobami Raji, Hameedat Bukola Olodo, Timothy Tolulope Oke, Wilhelmina Afua Addy, Onyeka Chrisanctus Ofodile, and Adedoyin Tolulope Oyewole. "E-commerce and consumer behavior: A review of AI-powered personalization and market trends." GSC Advanced Research and Reviews 18, no. 3 (2024): 066–77. http://dx.doi.org/10.30574/gscarr.2024.18.3.0090.
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In the dynamic landscape of electronic commerce (e-commerce), understanding and adapting to evolving consumer behavior is critical for the sustained success of online businesses. This review delves into the intersection of e-commerce and consumer behavior, focusing on the transformative role of Artificial Intelligence (AI)-powered personalization and its impact on market trends. The advent of AI has revolutionized the way e-commerce platforms engage with and cater to individual consumer preferences. AI-powered personalization techniques leverage advanced algorithms to analyze vast datasets, enabling the delivery of highly tailored and relevant content, product recommendations, and user experiences. This review explores the intricate mechanisms of AI-driven personalization, examining how it enhances customer engagement, satisfaction, and loyalty. Furthermore, the study investigates the prominent market trends shaped by AI in e-commerce. From chatbots and virtual assistants facilitating seamless customer interactions to predictive analytics optimizing inventory management, AI is driving innovation across various facets of the online retail landscape. The analysis delves into the integration of machine learning algorithms in predicting consumer preferences, streamlining the purchasing process, and fostering a more personalized shopping journey. As e-commerce continues to evolve, the review also explores the challenges and ethical considerations associated with AI-powered personalization. Issues such as data privacy, algorithmic bias, and the delicate balance between customization and intrusiveness are examined to provide a comprehensive understanding of the broader implications of AI in shaping consumer behavior. Ultimately, this review offers valuable insights into the symbiotic relationship between e-commerce and consumer behavior, shedding light on the transformative power of AI-powered personalization and its influence on emerging market trends. As businesses navigate the digital landscape, understanding and harnessing the potential of AI-driven strategies become imperative for staying competitive and meeting the evolving expectations of tech-savvy consumers.
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Mustafa, Ayobami Raji, Bukola Olodo Hameedat, Tolulope Oke Timothy, Afua Addy Wilhelmina, Chrisanctus Ofodile Onyeka, and Tolulope Oyewole Adedoyin. "E-commerce and consumer behavior: A review of AI-powered personalization and market trends." GSC Advanced Research and Reviews 18, no. 3 (2024): 066–77. https://doi.org/10.5281/zenodo.11217093.
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In the dynamic landscape of electronic commerce (e-commerce), understanding and adapting to evolving consumer behavior is critical for the sustained success of online businesses. This review delves into the intersection of e-commerce and consumer behavior, focusing on the transformative role of Artificial Intelligence (AI)-powered personalization and its impact on market trends. The advent of AI has revolutionized the way e-commerce platforms engage with and cater to individual consumer preferences. AI-powered personalization techniques leverage advanced algorithms to analyze vast datasets, enabling the delivery of highly tailored and relevant content, product recommendations, and user experiences. This review explores the intricate mechanisms of AI-driven personalization, examining how it enhances customer engagement, satisfaction, and loyalty. Furthermore, the study investigates the prominent market trends shaped by AI in e-commerce. From chatbots and virtual assistants facilitating seamless customer interactions to predictive analytics optimizing inventory management, AI is driving innovation across various facets of the online retail landscape. The analysis delves into the integration of machine learning algorithms in predicting consumer preferences, streamlining the purchasing process, and fostering a more personalized shopping journey. As e-commerce continues to evolve, the review also explores the challenges and ethical considerations associated with AI-powered personalization. Issues such as data privacy, algorithmic bias, and the delicate balance between customization and intrusiveness are examined to provide a comprehensive understanding of the broader implications of AI in shaping consumer behavior. Ultimately, this review offers valuable insights into the symbiotic relationship between e-commerce and consumer behavior, shedding light on the transformative power of AI-powered personalization and its influence on emerging market trends. As businesses navigate the digital landscape, understanding and harnessing the potential of AI-driven strategies become imperative for staying competitive and meeting the evolving expectations of tech-savvy consumers.
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Mhatre, Asst.Prof. Rajavi. "E-commerce and Consumer Behaviour: A review of AI-powered personalization and market trends." International Journal of Advance and Applied Research 6, no. 25(B) (2025): 156–59. https://doi.org/10.5281/zenodo.15315551.
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<strong>Abstract:</strong> In the ever-changing world of electronic commerce (e-commerce), it is essential for online businesses to comprehend and adapt to changing consumer behaviours to achieve lasting success. This review examines the intersection of e-commerce and consumer behaviour, emphasizing the significant impact of Artificial Intelligence (AI)-enhanced personalization on market trends. The emergence of AI has transformed how e-commerce platforms interact with and meet the distinct preferences of consumers. AI-driven personalization methods utilize complex algorithms to analyse extensive datasets, allowing for the provision of highly customized and relevant content, product suggestions, and user experiences. This review investigates the sophisticated processes behind AI-enabled personalization, highlighting how it improves customer engagement, satisfaction, and loyalty. Additionally, the study looks into the key market trends influenced by AI in e-commerce. From chatbots and virtual assistants that facilitate smooth customer interactions to predictive analytics that enhance inventory management, AI is fostering innovation across numerous aspects of the online retail sector. The analysis also addresses the application of machine learning algorithms in predicting consumer preferences, simplifying the buying process, and cultivating a more personalized shopping experience. As e-commerce progresses, this review further considers the challenges and ethical issues tied to AI-driven personalization. Topics such as data privacy, algorithmic bias, and the careful balance between customization and intrusiveness are discussed to provide a thorough understanding of AI's wider effects on consumer behaviour. Ultimately, this review presents valuable perspectives on the intertwined relationship between e-commerce and consumer behaviour, illuminating the transformative influence of AI-enabled personalization and its effects on emerging market trends. As companies traverse the digital realm, it is crucial to comprehend and leverage the potential of AI-driven approaches to remain competitive and satisfy the changing demands of tech-savvy consumers.
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Jain, Shubham, Gabriele Obermeier, Andreas Auinger, Dirk Werth, and Gabriel Kiss. "Design Principles of a Mixed-Reality Shopping Assistant System in Omnichannel Retail." Applied Sciences 13, no. 3 (2023): 1384. http://dx.doi.org/10.3390/app13031384.
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New digital technologies furnish retail managers with new means to enhance consumer experiences in omnichannel retailing. Conceptual academic literature and industry emphasize the promising use of immersive digital displays and their potential benefits for retailers. In this research, we present the design of a personal shopping assistance system that is based on optical see-through mixed-reality technology. Microsoft HoloLens 2 was leveraged as the archetype to realize this novel system, facilitating consumer information search and decision making. The design incorporates various shopping assistance elements (i.e., product information, reviews, recommendations, product availability, videos, a virtual cart, and an option to buy). Users can interact with these elements with gesture-based inputs to navigate through the interface. A qualitative study with 35 participants was conducted to collect users’ feedback and perceptions about the mixed-reality shopping assistant system. Derived from the qualitative feedback, we propose seven design principles that aim to support future designs and developments of mixed-reality shopping applications for head-mounted displays in omnichannel retail: rigor, informativeness, tangibility, summary, comparability, flexibility and holism.
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Thadepalli, Srivani, and Mr Uday Choudhary. "Synergy of Real and Digital Worlds - Promising Insights for the Future Generations of Fashion." International Journal of Recent Technology and Engineering (IJRTE) 13, no. 1 (2024): 22–26. http://dx.doi.org/10.35940/ijrte.a8054.13010524.
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Digital transformation (DT) is reshaping the fashion industry, revolutionizing the way brands, retailers, and consumers interact. It is not a fad but a necessary step towards innovation and survival in today's business context. Implementing digital transformation requires a bespoke approach that addresses specific challenges and goals within the existing framework of each brand or retailer. Fashion brands are leveraging digital technologies throughout their value chain, from product design and production to marketing and distribution. Computer-aided design (CAD) software, predictive analytics, and 3D printing are streamlining the design and prototyping phases, reducing time-to market and improving product quality. Technologies like 3D body scanning, seamless garments and digitized looms are also being adopted. Brands like Hugo Boss are using smart factories that incorporate robotics, artificial intelligence (AI), analytics, and the Internet of Things (IoT) to increase efficiency. Moreover, digital integrated supply chain platforms, such as blockchain, are enabling faster and more efficient production by connecting brands with manufacturers and suppliers globally. The adoption of digital solutions extends to the production of futuristic textiles, digital clothing and virtual model / digital show stoppers. Retailers are also embracing DT to enhance the customer experience and expand their reach. E-commerce has become a crucial channel, allowing retailers to sell products online and reach a wider customer base. Many retailers are investing in robust online platforms and incorporating augmented reality (AR) and virtual reality (VR) technologies to offer immersive in-store shopping experiences. Data analytics and AI are being used to personalize recommendations and offers, enhancing customer engagement and loyalty. In-store virtual assistants or kiosks are worth mentioning in light of digital clientele. Social media platforms play a vital role in the fashion industry's digital transformation. Fashion brands are partnering with social media influencers to promote their products and reach a larger audience. Additionally, collaborative consumption models are emerging through digital apps, supporting sustainability efforts such as zero waste, recycling, and sharing goods or services. Consumers are benefiting from greater convenience, choice, and personalized experiences in the digital fashion landscape. They have access to a wide array of products from around the world and can find inspiration and style ideas on social media platforms. User generated content and reviews facilitate informed purchase decisions. Mobile technology advancements have blurred the lines between online and offline retail experiences, enabling consumers to shop anytime and anywhere. Adaptability, inclusivity, diversity, authenticity and traceability of product life cycle (Blockchain) have become driving instincts of Gen Zers and Millennials at purchase points. However, traditional industry players and small independent retailers face increased competition from e-commerce giants, necessitating their adaptation to digital technologies to remain relevant. The COVID 19 pandemic has accelerated this shift and normalized the idea of going digital. This paper presents an in-depth review of how digital transformations have various players within the fashion Industry with special reference to the brands, designers and enterprises implementing these for their evolution and progression to thrive in this rapidly evolving landscape.
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Srivani, Thadepalli. "Synergy of Real and Digital Worlds - Promising Insights for the Future Generations of Fashion." International Journal of Recent Technology and Engineering (IJRTE) 13, no. 1 (2024): 22–26. https://doi.org/10.35940/ijrte.A8054.13010524.
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<strong>Abstract:</strong> Digital transformation (DT) is reshaping the fashion industry, revolutionizing the way brands, retailers, and consumers interact. It is not a fad but a necessary step towards innovation and survival in today's business context. Implementing digital transformation requires a bespoke approach that addresses specific challenges and goals within the existing framework of each brand or retailer. Fashion brands are leveraging digital technologies throughout their value chain, from product design and production to marketing and distribution. Computer-aided design (CAD) software, predictive analytics, and 3D printing are streamlining the design and prototyping phases, reducing time-to-market and improving product quality. Technologies like 3D body scanning, seamless garments and digitized looms are also being adopted. Brands like Hugo Boss are using smart factories that incorporate robotics, artificial intelligence (AI), analytics, and the Internet of Things (IoT) to increase efficiency. Moreover, digital-integrated supply chain platforms, such as blockchain, are enabling faster and more efficient production by connecting brands with manufacturers and suppliers globally. The adoption of digital solutions extends to the production of futuristic textiles, digital clothing and virtual model / digital show stoppers. Retailers are also embracing DT to enhance the customer experience and expand their reach. E-commerce has become a crucial channel, allowing retailers to sell products online and reach a wider customer base. Many retailers are investing in robust online platforms and incorporating augmented reality (AR) and virtual reality (VR) technologies to offer immersive in-store shopping experiences. Data analytics and AI are being used to personalize recommendations and offers, enhancing customer engagement and loyalty. In-store virtual assistants or kiosks are worth mentioning in light of digital clientele. Social media platforms play a vital role in the fashion industry's digital transformation. Fashion brands are partnering with social media influencers to promote their products and reach a larger audience. Additionally, collaborative consumption models are emerging through digital apps, supporting sustainability efforts such as zero waste, recycling, and sharing goods or services. Consumers are benefiting from greater convenience, choice, and personalized experiences in the digital fashion landscape. They have access to a wide array of products from around the world and can find inspiration and style ideas on social media platforms. Usergenerated content and reviews facilitate informed purchase decisions. Mobile technology advancements have blurred the lines between online and offline retail experiences, enabling consumers to shop anytime and anywhere. Adaptability, inclusivity, diversity, authenticity and traceability of product life cycle (Blockchain) have become driving instincts of Gen Zers and Millennials at purchase points. However, traditional industry players and small independent retailers face increased competition from e-commerce giants, necessitating their adaptation to digital technologies to remain relevant. The COVID-19 pandemic has accelerated this shift and normalized the idea of going digital. This paper presents an in-depth review of how digital transformations have various players within the fashion Industry with special reference to the brands, designers and enterprises implementing these for their evolution and progression to thrive in this rapidly evolving landscape.
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Romanchuk, Lyubov, Dmytro Shchytov, and Mykola Mormul. "ARTIFICIAL INTELLIGENCE IN E-COMMERCE: MAIN DIRECTIONS, BENEFITS, AND POTENTIAL RISKS." Український економічний часопис, no. 8 (February 28, 2025): 108–15. https://doi.org/10.32782/2786-8273/2025-8-19.
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Introduction. The article examines the role of artificial intelligence (AI) in the development and transformation of e-commerce, as well as its impact on key aspects of business in the modern digital environment, analyzes the benefits of integrating AI into e-commerce, such as improved customer satisfaction, increased operational efficiency, and enhanced decision-making capabilities, and the role of AI in improving marketing strategies through targeted advertising and recommendation systems, leading to a more personalized shopping experience. Purpose. The aim of the article is to identify areas of use of artificial intelligence in e-commerce, highlight and substantiate threats and obstacles in this process, as well as offer a proposal for cooperation between AI and e-commerce specialists. Methods. The basis for solving the set goal were the methods of comparative analysis, survey, generalization and grouping, statistical analysis, modeling, forecasting and empirical calculation. Results. The article systematizes the main areas of application of AI in e-commerce, in particular, personalization of purchases, which allows creating individualized offers for users, automation of customer service through chatbots and virtual assistants, effective inventory management through demand forecasting and analysis of large volumes of data. Along with the benefits, attention is also paid to the potential risks that companies face when implementing AI. These may include increasing market inequality due to the concentration of technological capabilities in large corporations, as well as potential unemployment due to the automation of jobs. The paper provides a comprehensive analysis of how AI can change the e-commerce landscape, in particular to increase its efficiency and competitiveness, but also emphasizes the need for a cautious approach to the implementation of new technologies. It stresses the importance of ensuring that AI systems are transparent, explainable, and accountable in order to gain consumer trust. The article highlights the importance of establishing clear regulatory frameworks and ethical guidelines to ensure that AI is used responsibly and transparently in business operations. The article also suggests the importance of ongoing research and development to address the emerging challenges related to AI implementation. Finally, an example of a simulation model developed in Python that can be used in e-commerce to optimize logistics and warehousing is provided, demonstrating the practical application of AI to improve business processes.
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Villegas-Ch, William, Rodrigo Amores-Falconi, and Eduardo Coronel-Silva. "Design Proposal for a Virtual Shopping Assistant for People with Vision Problems Applying Artificial Intelligence Techniques." Big Data and Cognitive Computing 7, no. 2 (2023): 96. http://dx.doi.org/10.3390/bdcc7020096.
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Accessibility is an increasingly important topic for Ecommerce, especially for individuals with vision problems. To improve their online experience, the design of a voice assistant has been proposed to allow these individuals to browse and shop online more quickly and efficiently. This voice assistant forms an intelligent system that can understand and respond to users’ voice commands. The design considers the visual limitations of the users, such as difficulty reading information on the screen or identifying images. The voice assistant provides detailed product descriptions and ideas in a clear, easy-to-understand voice. In addition, the voice assistant has a series of additional features to improve the shopping experience. For example, the assistant can provide product recommendations based on the user’s previous purchases and information about special promotions and discounts. The main goal of this design is to create an accessible and inclusive online shopping experience for the visually impaired. The voice assistant is based on a conversational user interface, allowing users to easily navigate an eCommerce website, search for products, and make purchases.
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Soni, Shreya, Sakshi Aglawe, Shilpi Saxena, et al. "Revolutionizing VR Shopping: Integrating Chatbots with Augmented Reality for Enhanced Experiences." Recent Trends in Artificial Intelligence & Its Applications 4, no. 1 (2025): 88–102. https://doi.org/10.46610/rtaia.2025.v04i01.010.
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Virtual Reality (VR) shopping is revolutionizing e-commerce by offering immersive and interactive experiences. However, challenges such as user engagement, personalization, and seamless assistance hinder its widespread adoption. Traditional online shopping lacks real-time customer support and personalized recommendations, leading to lower user satisfaction. To address these issues, this study proposes integrating AI-powered chatbots with Augmented Reality (AR) in VR shopping environments. AI-driven chatbots provide instant responses, tailored recommendations, and seamless guidance, enhancing user interaction and engagement. By analyzing consumer behavior and preferences, these chatbots enable hyper-personalized shopping experiences. Simultaneously, AR enhances product visualization, allowing users to interact with virtual products more realistically. This integration bridges the gap between digital and physical shopping, offering an interactive and dynamic experience. Customers can receive AI-driven product suggestions, visualize items in real-time, and make informed purchasing decisions. Additionally, chatbot-AR synergy ensures continuous engagement by providing interactive assistance, answering queries, and guiding users through virtual stores. This study evaluates the effectiveness of chatbot-AR integration using qualitative and quantitative metrics such as user satisfaction, decision-making efficiency, and engagement levels. The findings suggest that combining AI-powered chatbots with AR significantly enhances the VR shopping landscape, making it more intuitive, customer-centric, and efficient. This research contributes to the advancement of VR commerce by demonstrating how intelligent AI systems can revolutionize online retail. The proposed approach has the potential to set a new standard in immersive e-commerce, paving the way for future AI-driven shopping innovations.
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Pfeiffer, Jella, Thies Pfeiffer, Martin Meißner, and Elisa Weiß. "Eye-Tracking-Based Classification of Information Search Behavior Using Machine Learning: Evidence from Experiments in Physical Shops and Virtual Reality Shopping Environments." Information Systems Research 31, no. 3 (2020): 675–91. http://dx.doi.org/10.1287/isre.2019.0907.
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How can we tailor assistance systems, such as recommender systems or decision support systems, to consumers’ individual shopping motives? How can companies unobtrusively identify shopping motives without explicit user input? We demonstrate that eye movement data allow building reliable prediction models for identifying goal-directed and exploratory shopping motives. Our approach is validated in a real supermarket and in an immersive virtual reality supermarket. Several managerial implications of using gaze-based classification of information search behavior are discussed: First, the advent of virtual shopping environments makes using our approach straightforward as eye movement data are readily available in next-generation virtual reality devices. Virtual environments can be adapted to individual needs once shopping motives are identified and can be used to generate more emotionally engaging customer experiences. Second, identifying exploratory behavior offers opportunities for marketers to adapt marketing communication and interaction processes. Personalizing the shopping experience and profiling customers’ needs based on eye movement data promises to further increase conversion rates and customer satisfaction. Third, eye movement-based recommender systems do not need to interrupt consumers and thus do not take away attention from the purchase process. Finally, our paper outlines the technological basis of our approach and discusses the practical relevance of individual predictors.
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Mohammad, Sinan M. P., K.P Shabeer, P. Abhinav, Jaseem V. K. Muhammed, and Muhammad. "STORIO - Automated Store Solutions." Recent Trends in Cloud Computing and Web Engineering 6, no. 1 (2023): 12–23. https://doi.org/10.5281/zenodo.10403859.
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<em>Shopping is a ubiquitous activity that plays a vital role in our daily lives. It provides a means for consumers to acquire the products and services they need or desire, and it is a key component of the global economy. However, the traditional method of shopping can be time-consuming and stressful, with long queues and limited assistance for customers.</em> <em>To address these challenges, we propose a novel system that aims to enhance the shopping experience for both customers and retailers. Our system offers a range of features that assist customers in shopping for products, making payments, and receiving personalized recommendations. Additionally, it provides store owners with advanced capabilities for inventory management, sales projection, and supplier notification.</em> <em>Our system is designed to be user-friendly and intuitive, with a simple and intuitive interface that can be easily accessed through mobile devices or in-store kiosks. It leverages the latest technologies, including machine learning and data analytics, to provide customers with personalized recommendations based on their shopping history and preferences. It also enables retailers to optimize their inventory management and sales strategies, leading to increased profitability and customer satisfaction.</em> <em>In summary, our proposed system offers a comprehensive solution to the challenges of traditional shopping, providing a more efficient, convenient, and personalized shopping experience for customers while enabling retailers to improve their operations and profitability.</em> <strong> </strong>
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Manfredi, Gilda, Gabriele Gilio, Vincenzo Baldi, Hiba Youssef, and Ugo Erra. "VICO-DR: A Collaborative Virtual Dressing Room for Image Consulting." Journal of Imaging 9, no. 4 (2023): 76. http://dx.doi.org/10.3390/jimaging9040076.
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In recent years, extended reality has increasingly been used to enhance the shopping experience for customers. In particular, some virtual dressing room applications have begun to develop, as they allow customers to try on digital clothes and see how they fit. However, recent studies found that the presence of an AI or a real shopping assistant could improve the virtual dressing room experience. In response to this, we have developed a collaborative synchronous virtual dressing room for image consulting that allows customers to try on realistic digital garments chosen by a remotely connected human image consultant. The application has different features for the image consultant and the customer. The image consultant can connect to the application, define a database of garments, select different outfits with different sizes for the customer to try, and communicate with the customer through a single RGB camera system. The customer-side application can visualize the description of the outfit that the avatar is wearing, as well as the virtual shopping cart. The main purpose of the application is to offer an immersive experience, ensured by the presence of a realistic environment, an avatar that resembles the customer, a real-time physically-based cloth simulation algorithm, and a video-chat system.
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Kautish, Pradeep, and Rajesh Sharma. "Managing online product assortment and order fulfillment for superior e-tailing service experience." Asia Pacific Journal of Marketing and Logistics 31, no. 4 (2019): 1161–92. http://dx.doi.org/10.1108/apjml-05-2018-0167.
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PurposeThe purpose of this paper is to bridge together seemingly disparate yet interconnected paradigmatic antecedents of e-tailing and servicescape, i.e., product assortment, order fulfillment, shopping assistance and its consequences for shopping efficiency.Design/methodology/approachThe proposed conceptual model is well grounded in the extensive literature from e-tailing as well as retailing domain and to assess the plausibility of the model. Total 246 female online apparel shoppers were surveyed from an Indian university and the data were analyzed using structural equation modeling through SmartPLS.FindingsThe outcomes of the study indicate that the e-customer may derive a substantial share of shopping assistance and service interface through product assortment offered by e-tailing sites. Customer-perceived performance of this e-shopping process – a crucial element of e-tail servicescape – directly affects the shopping assistance, along with order fulfillment capability of retail scope.Research limitations/implicationsThe study used a sample of graduate students at a north-west university in India, which limits the generalizability of the research to other consumer groups. The paper links a significant body of literature within a conceptually developed framework and identifies key research areas in the e-tailing realm.Practical implicationsBy better understanding the role of product assortment as a value-added feature in online value co-creation process, the e-tail managers can leverage the proposed integrated capability to improve e-tailing performance and customer outcomes in the form of business.Social implicationsWith rapid advancements in internet-led communication, we are witnessing the dawn of a new era of e-tail innovations around us which is expected to change the way people experience shopping.Originality/valueThis research is an attempt to enrich the level of understanding about online shopping environment in light of relationships among virtual and physical facets of e-tail, i.e., product assortment, order fulfillment, shopping assistance and shopping efficiency. The authors investigate customer-perceived product assortment performance in e-tailing and its significances on shopping outcomes.
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BOTLÍKOVÁ, Milena, Josef BOTLÍK, and Jana STUCHLÍKOVÁ. "Information Accessibility of Restaurant Companies in Moravian-Silesian Region." Journal of Environmental Management and Tourism 13, no. 1 (2022): 242. http://dx.doi.org/10.14505/jemt.v13.1(57).22.
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The literature agrees that the most affected sector during the COVID 19 pandemic was tourism. The period of pandemics associated with social distance has completely transformed the hotel and catering business. Covid 19 has launched new trends in the provision of catering services. Many restaurants have changed their product offerings, focusing on fast food. The stone establishments became online establishments with the virtual operation of the restaurant. Information accessibility has become one of the key success factors and competitive advantages of companies in the restaurant equipment segments. The article deals with the analysis and evaluation of the current state of information accessibility of restaurant facilities in the Moravian-Silesian Region in the context of specific groups. Within this analysis, persons with visual problems, which include not only the visually impaired but also the elderly, were found for a specific group. The analysis was based on the observation of 276 restaurant facilities in the Moravian-Silesian Region and the subsequent classification of individual entities based on clustering into classes. The selection of information accessibility factors was based on a search of literature and sources. From the point of view of a specific group, it is the contrast of fonts, alternative texts and other elements of barriers, etc. In conclusion, it can be assessed that restaurants in the region use web applications, but there are still barriers for a specific group.
 Like many other industries, the tourism segments had been affected by information technology. Today, customers commonly use the Internet to search for destinations and to book accommodation services. Portals for import services (pizza delivery, etc.) are now also used in gastronomic services. The time of covid strengthened this trend even more. As a result of the complete closure of restaurants and restaurants in hotel facilities, companies have had to launch new approaches to service delivery, in particular focusing on their product import services, which are, however, based on the Internet applications. At present, the key factor in purchasing decisions is the accessibility of the company's website, i.e. Web presentation for all specific groups. In covid times, web tools have become an element from the point of view of restaurant-customer interaction. The individual tools applied to the creation of corporate websites offer shopping for people with special needs without the presence of assistants, which increases the personal self-sufficiency of these people. According to Castiglioni and Gaj (2020), it is necessary for people (and businesses) to radically change their approach to life and adapt to security conditions after the outbreak of Covid 19 in many countries, services that would otherwise be unattainable at the time of the lockdown. Websites of tourism enterprises (accommodation and catering services, cultural heritage goals) significantly belong to the competitiveness of the destination (Kourtesopoulou, et al., 2020; Luna-Nevarez, Hyman, 2012), which is a means of transport to the destination and improve the quality of life of the population.
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Doungtap, Surasachai, Jenq-Haur Wang, and Varinya Phanichraksaphong. "Comparative Analysis of SAAS Model and NPC Integration for Enhancing VR Shopping Experiences." Applied Sciences 14, no. 15 (2024): 6573. http://dx.doi.org/10.3390/app14156573.
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This article examines the incorporation of the Shopping Assistance Automatic Suggestion (SAAS) model into Virtual Reality (VR) environments in order to improve the online shopping experience. The SAAS model employs sophisticated deep learning methods to offer customized product recommendations, which are conveyed by non-player characters (NPCs) via voice-based interactions. Our goal is to develop an interactive shopping experience that replicates real-life interactions by integrating AI-powered recommendations with immersive VR technology. We gather and standardize data from several open commerce databases, such as Amazon Product and Customer Reviews. The SAAS model, in conjunction with GPT-3, BERT, and T5, undergoes training and testing to evaluate its effectiveness across multiple criteria. The results demonstrate that the SAAS model surpasses other models in delivering contextually aware and pertinent recommendations. The integration process outlines the specific steps involved in capturing, processing, and transforming user interactions in virtual reality (VR) into vocal suggestions provided by non-player characters (NPCs). This strategy improves customization and utilizes the immersive features of virtual reality to effectively engage people. The results of our research establish a higher standard for e-commerce, with the goal of enhancing the user experience of online purchasing by making it more instinctive, engaging, and pleasurable.
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Bigne, Enrique, Carla Ruiz, and Rafael Curras-Perez. "Furnishing your home? The impact of voice assistant avatars in virtual reality shopping: A neurophysiological study." Computers in Human Behavior 153 (April 2024): 108104. http://dx.doi.org/10.1016/j.chb.2023.108104.
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Nze, Stella Udoka. "AI-Powered Chatbots." Global Journal of Human Resource Management 12, no. 6 (2024): 34–45. http://dx.doi.org/10.37745/gjhrm.2013/vol12n63445.
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Artificial Intelligence (AI)-powered chatbots have emerged as a transformative technology, fundamentally changing how businesses and organizations engage with their customers by providing real-time, personalized communication. These chatbots, driven by sophisticated algorithms, utilize Natural Language Processing (NLP) and Machine Learning (ML) to understand, interpret, and respond to human language in a manner that is contextually appropriate and relevant. As a result, AI-powered chatbots enhance both user experience and operational efficiency by automating routine interactions, reducing response times, and providing consistent, high-quality service. The integration of AI chatbots spans multiple sectors, including customer service, healthcare, education, and e-commerce. In customer service, chatbots are deployed to manage high volumes of inquiries, troubleshoot issues, and offer personalized assistance around the clock, thereby freeing human agents to focus on more complex tasks. In healthcare, AI-powered chatbots are utilized to facilitate patient engagement by providing initial diagnoses, managing appointment schedules, offering medication reminders, and delivering health information. Educational institutions employ these chatbots to interact with students, answer frequently asked questions, facilitate administrative processes, and support learning through personalized tutoring. Meanwhile, in e-commerce, chatbots serve as virtual shopping assistants, offering product recommendations, guiding users through their purchasing journey, and resolving post-purchase concerns. This paper delves into the development and deployment methodologies of AI-powered chatbots, examining the various approaches and technologies used to build robust and efficient chatbot systems. The discussion highlights key components such as NLP, ML, reinforcement learning, and deep learning techniques that contribute to the chatbot’s ability to understand user intent, handle natural language conversations, and learn from past interactions to improve future responses. Additionally, the paper analyzes chatbot architecture, including front-end interfaces, dialogue management systems, and backend integration, to provide a comprehensive understanding of the chatbot ecosystem. The literature review presented in this paper synthesizes findings from recent studies and publications, identifying the current trends, advancements, and challenges in implementing AI chatbots across different domains. It evaluates the effectiveness of chatbots in achieving key performance indicators such as customer satisfaction, response accuracy, operational efficiency, and cost savings. The review also highlights areas where AI chatbots have proven to be most effective and identifies potential limitations, including data privacy concerns, integration challenges with existing legacy systems, and the limitations of current NLP models in understanding context, sarcasm, or nuanced language. This paper further discusses the benefits and challenges associated with deploying AI-powered chatbots. Benefits such as 24/7 availability, scalability, reduced operational costs, and enhanced customer engagement are explored in detail, demonstrating how chatbots can deliver substantial value to organizations. Conversely, the paper also addresses challenges such as ensuring data security and privacy, overcoming natural language understanding (NLU) limitations, mitigating biases in AI models, and managing customer expectations when interacting with non-human agents. In addition, this paper provides a forward-looking perspective on the potential future developments of AI chatbots. It explores emerging trends such as multimodal chatbots that integrate voice, text, and visual inputs; advancements in emotion recognition to enable more empathetic and human-like interactions; and the rise of explainable AI, where chatbots can provide transparency in their decision-making processes.To illustrate these concepts, the paper includes diagrams that depict the architecture of AI chatbot systems, the flow of natural language processing, and the integration of various components such as databases, machine learning models, and user interfaces. These visual aids provide a clearer understanding of the technical and functional aspects of chatbot development and deployment. Overall, this paper aims to provide a comprehensive analysis of AI-powered chatbots, detailing their applications, benefits, challenges, and future potential. It serves as a guide for businesses, researchers, and technology developers interested in leveraging AI chatbots to enhance communication, streamline operations, and create a more engaging user experience. By critically examining both the opportunities and the limitations, this research offers valuable insights into the strategic implementation of AI chatbots across diverse industries.
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Agarwal, Sanchit, Jan Jezabek, Arijit Biswas, Emre Barut, Bill Gao, and Tagyoung Chung. "Building Goal-Oriented Dialogue Systems with Situated Visual Context." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 11 (2022): 13149–51. http://dx.doi.org/10.1609/aaai.v36i11.21710.
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Goal-oriented dialogue agents can comfortably utilize the conversational context and understand its users' goals. However, in visually driven user experiences, these conversational agents are also required to make sense of the screen context in order to provide a proper interactive experience. In this paper, we propose a novel multimodal conversational framework where the dialogue agent's next action and their arguments are derived jointly conditioned both on the conversational and the visual context. We demonstrate the proposed approach via a prototypical furniture shopping experience for a multimodal virtual assistant.
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Moodley, Marlini, and Sershan Naidoo. "Factors Contributing to Online or In-store Shopping among Academics from a Private Higher Education Institution in South Africa." International Review of Management and Marketing 13, no. 6 (2023): 19–28. http://dx.doi.org/10.32479/irmm.14732.
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The aim of the study was to determine the factors contributing to online or in-store shopping behaviour among academics from a private higher education institution in South Africa. In addition, the study examined types of products or services consumers are likely to purchase in-store and online and particular aspects relating to store atmosphere, as well as the challenges that were experienced using both modes of shopping. The study was conducted at a private higher education institution. A cross-sectional quantitative study was conducted among all the academics in the organisation. The study show that the majority of respondents belonged to generation X and Y and that they are more inclined to purchase from both in-store and online stores rather than a singular mode of shopping. However, there is an element of fear, anxiety and uncertainty that customers face when purchasing online. This is motivated by the Stimulus-Organism-Response (SOR) model. Factors that influence the overall purchasing decision for both online and in-store shopping include accessibility, convenience, delivery service, store aesthetics (atmosphere and ambience) and the availability of an assistant. Recommendations for retail marketing managers include the fact that they should consider a hybrid model of both in-store and online shopping. Moreover, invest in enhancing the store image of both physical stores as well as virtual online stores as the subtle atmospheric cues trigger impulse purchasing.
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Jinyoung Hwang. "Impact of Augmented Reality (AR) and Virtual Reality (VR) on Retail." Magna Scientia Advanced Research and Reviews 12, no. 1 (2024): 295–307. https://doi.org/10.30574/msarr.2024.12.1.0165.
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This research explores the prospective change that Augmented Reality (AR) and Virtual Reality (VR) bring to the retail business, including sales interactions, individualization, sales results, and managerial analytics. AR augment physical space with digital content and VR involves the complete creation of a virtual world reminiscent of the physical shopping environment. These technologies mediate the gap between conventional physical store and e-store, providing distinctive solutions like augmented reality fitting and real-life assistant interfaces. As this study is based on a quantitative, cross-sectional survey research design, data is collected by means of self-administered online questionnaires in order to capture consumers’ attitude and behaviour concerning AR and VR. The result shows how these technologies enhance customer interactions, improved customer satisfaction, better sales as well as trying to minimize returns. Furthermore, the combination of AR and VR facilitate the creation of new competitive advantages for retailers such that unique shopping experiences can be provided. It also helps in practicing sustainable business by avoiding the compulsion for physical stock and lowering the logistic expenses. This research gives practical recommendations about applications and further perspective of AR and VR use in the retail business, which can contribute to its transformation based on these technologies. Ultimately, this research underscores the pivotal role of AR and VR in shaping the future of retail, driving innovation, and fostering stronger connections between brands and consumers. effectively utilize Artificial Intelligence while ensuring they remain competitive in the global marketing landscape.
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Matsumura, Reo, and Masahiro Shiomi. "An Animation Character Robot That Increases Sales." Applied Sciences 12, no. 3 (2022): 1724. http://dx.doi.org/10.3390/app12031724.
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Performing the role of a shopping assistant is one promising application for social robots. Robot clerks can provide a richer experience for customers and increase sales; however, the scant opportunities for interaction with customers in real shopping environments is a typical drawback. We solve this problem by developing a unique networked salesclerk system that consists of a virtual agent that acts through the customer’s smartphone and a physical agent that performs as a robot salesclerk in an actual store environment. Toward this capability, in cooperation with Production I.G. Inc., an animation production company, we adopted a character named Tachikoma from “Ghost in the Shell: Stand Alone Complex” (commonly known as the S.A.C. series) when designing the appearance and features of both agents. We conducted a field test to investigate how our system contributed to the sales of Ghost in the Shell anime-themed products, and the results showed the advantages of our system for increasing sales.
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Tiwari, Ashish, and Ritu Garg. "A Optimized Taxonomy on Spot Sale Services Using Mathematical Methodology." International Journal of Security and Privacy in Pervasive Computing 14, no. 1 (2022): 1–21. http://dx.doi.org/10.4018/ijsppc.313048.
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In reality, the most appropriate cloud standards are significant ideas for application administrations. OSCCS technique calculation gives a spot-like market in virtual space to the end clients. The OSCCS gives an on-spot showcasing framework in the virtual universe of processing. As fluffy hypothesis is giving the specific outcomes and close to correct outcomes that is the reason that authors have taken the idea of fluffy unpleasant set hypothesis in their OSCCS approach. This sort of approach depends on the determination of the best ideal cost and season of asset allotment to an end client by the suppliers in virtual advertising. The allotments of assets depend on powerful on-request demand upkeep so the end-client gets the cloud administration on a business premise like in continuous shopping advertising on events. By the OSCCS deals approach framework, an end client can get the assistance at the ideal expense. The OSCCS calculation is mimicked in cloud test systems.
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Gillespie, Rachel, Emily DeWitt, Angela C. B. Trude, et al. "Barriers and Facilitators of Online Grocery Services: Perceptions from Rural and Urban Grocery Store Managers." Nutrients 14, no. 18 (2022): 3794. http://dx.doi.org/10.3390/nu14183794.
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Online grocery shopping has expanded rapidly in the U.S., yet little is known about the retailer’s perceptions of online grocery services, which can aid in the expansion of services. Furthermore, many barriers to online grocery utilization persist across geographic areas, especially among Supplemental Nutrition Assistance Program (SNAP)-authorized retailers. This study captured perceived barriers and facilitators of online grocery shopping for managers of SNAP-authorized retailers. Qualitative semi-structured interviews were conducted with managers (n = 23) of grocery stores/supermarkets in urban and rural areas across four different states: TN, KY, NC, and NY. Grocery store managers offering online ordering (n = 15) and managers from brick-and-mortar stores without online services (n = 8) participated in the interviews. Three primary themes emerged among managers offering online ordering: (1) order fulfillment challenges, (2) perceived customer barriers, and (3) perceived customer benefits. Among managers at brick-and-mortar locations without online services, four major themes emerged: (1) thoughts on implementing online shopping, (2) COVID-19 pandemic impacts, (3) competition with other stores, and (4) benefits of maintaining brick-and-mortar shopping. This study provides a deeper understanding of retailers’ experience and perceptions of online grocery services among stores authorized to accept SNAP benefits. This perspective is necessary to inform policies and enhance the evolving virtual food marketplace for SNAP customers.
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Lii, Yuan-Shuh, May-Ching Ding, and Chih-Hung Hung. "Consumer Price Search Behaviors in Online Shopping." Asian Journal of Economics, Business and Accounting 23, no. 19 (2023): 242–48. http://dx.doi.org/10.9734/ajeba/2023/v23i191087.
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Aims: Simultaneously, the decelerating economy in the real world due to the covid-19 has intensified the competition in the virtual world, forcing online retailers to consider how to steering effective price promotion strategies to attract customers and to increase their purchase intentions. Online retailers are either struggling to find ways to formulate their online price promotion strategies or simply adopt the offline price promotion strategies. However, the Internet provides online shoppers with the benefit of searching and evaluate price information efficiently and effectively, greatly reduces consumers’ information search costs. Under this circumstance, the effect of offline price promotion strategies on consumers’ price perceptions and purchase decision may become a hinderance instead of an assistance. Overall, the price information provided by the Internet influences consumer perceptions and reactions to online shopping. The purpose of this research is to provide insight into consumers’ online price search behavior and consumers’ reactions to online price promotion.
 Methodology: An in-depth discussion of the literature review on online consumer price search behavior was applied. Specifically, the literature review covers the issues of price comparison search engine, price comparison refund policy, price promotion, and semantic cues related to consumer price perception and purchase intention.
 Conclusion: These research propositions can help online retailers to gain a deeper understanding of consumer price search behavior, response to price information, and promotions. Consequently, online retailers are able to better formulate price communication strategies effectively. This price scheme can influence consumer price search behavior and then purchase intention.