Business and social sciences | Online ISSN 3067-8919
RESEARCH ARTICLE   (Open Access)

Advancing Consumer Behaviour Through Al: A Data-Driven Perspective on Online Scam Prevention and Trust Building

Fahim Rahman1*, Sonia Nashid2, Ispita Jahan3, Ariful Islam4, Sonia Khan Papia5, Al Akhir4

+ Author Affiliations

Business and Social Sciences 1 (1) 1-8 https://doi.org/10.25163/business.1110375

Submitted: 01 September 2023 Revised: 10 November 2023  Published: 12 November 2023 


Abstract

Background: The escalating use of online transactions has created significant challenges regarding consumer protection together with risk supervision and digital platform trust. The application of Artificial Intelligence functions as a robust system which delivers consumer data analytics while recognizing irregularities and builds trust through preemptive digital threat prevention. Methods: The research obtains data through a survey of 115 United States participants who include online shoppers and digital banking customers as well as e-service users. A structured questionnaire collected data which assessed how participants viewed AI-based protection tools and their trust toward digital platforms and their perspectives on risk management methods. Researchers evaluated the collected responses through descriptive statistics and performed comparative analysis between different demographic segments. Results: Research demonstrates that 78 % of participants believe AI stands as a vital element for internet security. The research data reveals that younger internet users between 18 and 34 years old exhibit higher trust levels toward AI security protocols than older generations. AI-based authentication systems including biometric verification lead 65 % of respondents to trust online platforms more. Conclusion: The research revealed that 42 % of participants showed concerns about their personal information being mishandled because of insufficient transparency and data privacy protection measures. Digital risk prevention and consumer trust in online spaces receive growing influence from AI technologies. The survey shows most participants understand the benefits of AI-based online security yet privacy concerns remain critical to address immediately.

Keywords: Artificial Intelligence, Consumer Insights, Online Scam, Trust Building, Scam Prevention

References

Ali, S. S., & Choi, B. J. (2020). State-of-the-art artificial intelligence techniques for distributed smart grids: A review. Electronics, 9(6), 1030. https://doi.org/10.3390/electronics9061030

Andronie, M., Lazaroiu, G., Iatagan, M., U?a, C., ?tefanescu, R., & Coco?atu, M. (2021). Artificial intelligence-based decision-making algorithms, Internet of Things sensing networks, and deep learning-assisted smart process management in cyber-physical production systems. Electronics, 10(20), 2497. https://doi.org/10.3390/electronics10202497

Bawack, R. E., Wamba, S. F., Carillo, K. D. A., & Akter, S. (2022). Artificial intelligence in e-commerce: A bibliometric study and literature review. Electronic Markets, 32(1), 297–338. https://doi.org/10.1007/s12525-022-00537-z

Brem, A., Giones, F., & Werle, M. (2021). The AI digital revolution in innovation: A conceptual framework of artificial intelligence technologies for the management of innovation. IEEE Transactions on Engineering Management, 70(2), 770–776. https://doi.org/10.1109/TEM.2021.3109983

Chintalapati, S., & Pandey, S. K. (2021). Artificial intelligence in marketing: A systematic literature review. International Journal of Market Research, 64(1), 38–68. https://doi.org/10.1177/14707853211018428

Chopra, R., & Sharma, G. D. (2021). Application of artificial intelligence in stock market forecasting: A critique, review, and research agenda. Journal of Risk and Financial Management, 14(11), 526. https://doi.org/10.3390/jrfm14110526

Cowls, J., Tsamados, A., Taddeo, M., & Floridi, L. (2021). The AI gambit: Leveraging artificial intelligence to combat climate change—Opportunities, challenges, and recommendations. AI & Society, 38(1), 283–307. https://doi.org/10.1007/s00146-021-01294-x

Cui, X., Lai, V., & Liu, C. (2008). Research on consumer behaviour in online auctions: Insights from a critical literature review. Electronic Markets, 18(4), 345–361. https://doi.org/10.1080/10196780802420752

Davenport, T., Guha, A., Grewal, D., & Bressgott, T. (2019). How artificial intelligence will change the future of marketing. Journal of the Academy of Marketing Science, 48(1), 24–42. https://doi.org/10.1007/s11747-019-00696-0

Fenwick, D., Daim, T. U., & Gerdsri, N. (2009). Value driven technology road mapping (VTRM) process integrating decision making and marketing tools: Case of Internet security technologies. Technological Forecasting and Social Change, 76(8), 1055–1077. https://doi.org/10.1016/j.techfore.2009.04.005

Fischer, E., & Reuber, R. (2007). The good, the bad, and the unfamiliar: The challenges of reputation formation facing new firms. Entrepreneurship Theory and Practice, 31(1), 53–75. https://doi.org/10.1111/j.1540-6520.2007.00163.x

Hermann, E. (2021). Leveraging artificial intelligence in marketing for social good—An ethical perspective. Journal of Business Ethics, 179(1), 43–61. https://doi.org/10.1007/s10551-021-04843-y

Huang, Z., Chen, H., Hsu, C., Chen, W., & Wu, S. (2003). Credit rating analysis with support vector machines and neural networks: A market comparative study. Decision Support Systems, 37(4), 543–558. https://doi.org/10.1016/S0167-9236(03)00086-1

Indriasari, E., Gaol, F. L., & Matsuo, T. (2019). Digital banking transformation: Application of artificial intelligence and big data analytics for leveraging customer experience in the Indonesia banking sector. 2019 12th International Congress on Advanced Applied Informatics (IIAI-AAI), 863–868. https://doi.org/10.1109/IIAI-AAI.2019.00175

Javalgi, R. G., Radulovich, L. P., Pendleton, G., & Scherer, R. F. (2005). Sustainable competitive advantage of Internet firms. International Marketing Review, 22(6), 658–672. https://doi.org/10.1108/02651330510630276

Johnson, M., Jain, R., Brennan-Tonetta, P., Swartz, E., Silver, D., Paolini, J., Mamonov, S., & Hill, C. (2021). Impact of big data and artificial intelligence on industry: Developing a workforce roadmap for a data driven economy. Global Journal of Flexible Systems Management, 22(3), 197–217. https://doi.org/10.1007/s40171-021-00272-y

Kakatkar, C., Bilgram, V., & Füller, J. (2019). Innovation analytics: Leveraging artificial intelligence in the innovation process. Business Horizons, 63(2), 171–181. https://doi.org/10.1016/j.bushor.2019.10.006

Khrais, L. T. (2020). Role of artificial intelligence in shaping consumer demand in e-commerce. Future Internet, 12(12), 226. https://doi.org/10.3390/fi12120226

Kietzmann, J., Paschen, J., & Treen, E. (2018). Artificial intelligence in advertising. Journal of Advertising Research, 58(3), 263–267. https://doi.org/10.2501/JAR-2018-035

Kumar, V., Rajan, B., Venkatesan, R., & Lecinski, J. (2019). Understanding the role of artificial intelligence in personalized engagement marketing. California Management Review, 61(4), 135–155. https://doi.org/10.1177/0008125619859317

Latif, S., Usman, M., Manzoor, S., Iqbal, W., Qadir, J., Tyson, G., Castro, I., Razi, A., Boulos, M. N. K., Weller, A., & Crowcroft, J. (2020). Leveraging data science to combat COVID-19: A comprehensive review. IEEE Transactions on Artificial Intelligence, 1(1), 85–103. https://doi.org/10.1109/TAI.2020.3020521

Mariani, M. M., & Wamba, S. F. (2020). Exploring how consumer goods companies innovate in the digital age: The role of big data analytics companies. Journal of Business Research, 121, 338–352. https://doi.org/10.1016/j.jbusres.2020.09.012

Mikalef, P., Conboy, K., & Krogstie, J. (2021). Artificial intelligence as an enabler of B2B marketing: A dynamic capabilities micro-foundations approach. Industrial Marketing Management, 98, 80–92. https://doi.org/10.1016/j.indmarman.2021.08.003

Paschen, J., Wilson, M., & Ferreira, J. J. (2020). Collaborative intelligence: How human and artificial intelligence create value along the B2B sales funnel. Business Horizons, 63(3), 403–414. https://doi.org/10.1016/j.bushor.2020.01.003

Smith, A. D., & Rupp, W. T. (2003). Strategic online customer decision making: Leveraging the transformational power of the Internet. Online Information Review, 27(6), 418–432. https://doi.org/10.1108/14684520310510055

Sriram, V. P., Shaikh, A. A., Sumana, B. K., Kumar, A., Dhiman, V., & Naved, M. (2022). Consumer behaviour on digital marketing platforms—Specifically in terms of consumer loyalty using machine learning. In Smart innovation, systems and technologies (pp. 377–386). https://doi.org/10.1007/978-981-19-0108-9_40

Sun, H., Chen, J., & Fan, M. (2020). Effect of live chat on traffic-to-sales conversion: Evidence from an online marketplace. Production and Operations Management, 30(5), 1201–1219. https://doi.org/10.1111/poms.13320

Syam, N., & Sharma, A. (2018). Waiting for a sales renaissance in the fourth industrial revolution: Machine learning and artificial intelligence in sales research and practice. Industrial Marketing Management, 69, 135–146. https://doi.org/10.1016/j.indmarman.2017.12.019

Van Esch, P., & Black, J. S. (2021). Artificial intelligence (AI): Revolutionizing digital marketing. Australasian Marketing Journal, 29(3), 199–203. https://doi.org/10.1177/18393349211037684

Verma, S., Sharma, R., Deb, S., & Maitra, D. (2021). Artificial intelligence in marketing: Systematic review and future research direction. International Journal of Information Management Data Insights, 1(1), 100002. https://doi.org/10.1016/j.ijimei.2020.100002

Wirth, N. (2018). Hello marketing, what can artificial intelligence help you with? International Journal of Market Research, 60(5), 435–438. https://doi.org/10.1177/1470785318776841


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