Artificial Intelligence for Marketing: Systematic Literature Review
Keywords:
Artificial Intelligence, Marketing, Digital Marketing, Customer EngagementAbstract
This journal performs a Systematic Literature Review on Artificial Intelligence (AI) in marketing and its impact on various business aspects, innovation, and customer engagement. Artificial Intelligence in marketing refers to the combination of data analytics, machine learning and automation in marketing strategies to enhance decision-making, personalization, and consumer experiences. Currently, the rapid advancement of technology has heightened public interest in Artificial Intelligence applications, encouraging companies to adopt AI-driven marketing practices. This journal systematically reviews the literature related to Artificial Intelligence in marketing, focusing on its impact on business performance, efficiency, and customer interaction. The literature review utilizes the Watase Uake Website, initially gathering 143 articles published from 2019 to 2024, from which 57 journals were analyzed using specific criteria. This journal serves as a valuable resource for the development of future research, particularly in the areas of Artificial Intelligence applications in marketing and their implications for business and consumer engagement.
Downloads
References
Abrokwah-Larbi, K., & Awuku-Larbi, Y. (2024). The impact of artificial intelligence in marketing on the performance of business organizations: evidence from SMEs in an emerging economy. Journal of Entrepreneurship in Emerging Economies, 16(4), 1090-1117.
Abror, G., & Muharam, H. (2024). Impact of Ultramicro Holding on Financial Performance and Business Sustainability. Research Horizon, 4(4), 47-54.
Adwan, A. A., Kokash, H., Adwan, R. A., & Khattak, A. (2023). Data analytics in digital marketing for tracking the effectiveness of campaigns and inform strategy. International Journal of Data & Network Science, 7(2).
Ali, A. (2021). Determining mediating role of managerial commitment and technological capability between environmental management accounting and organisational efficiency: a case of middle eastern countries. Arthatama, 5(2), 27-38.
Amoako, G., Omari, P., Kumi, D. K., Agbemabiase, G. C., & Asamoah, G. (2021). Conceptual framework—artificial intelligence and better entrepreneurial decision-making: the influence of customer preference, industry benchmark, and employee involvement in an emerging market. Journal of Risk and Financial Management, 14(12), 604.
Anggraeni, A. I. (2020). Executive role in the use of information technology in public organisations. Arthatama, 4(1), 17-32.
Babatunde, S. O., Odejide, O. A., Edunjobi, T. E., & Ogundipe, D. O. (2024). The role of AI in marketing personalization: A theoretical exploration of consumer engagement strategies. International Journal of Management & Entrepreneurship Research, 6(3), 936-949.
Barney, J. B., Ketchen Jr, D. J., & Wright, M. (2011). The future of resource-based theory: revitalization or decline?. Journal of management, 37(5), 1299-1315.
Du, S., & Xie, C. (2021). Paradoxes of artificial intelligence in consumer markets: Ethical challenges and opportunities. Journal of Business Research, 129, 961-974.
Gao, Y., & Liu, H. (2023). Artificial intelligence-enabled personalization in interactive marketing: a customer journey perspective. Journal of Research in Interactive Marketing, 17(5), 663-680.
Grönroos, C. (2006). Adopting a service logic for marketing. Marketing theory, 6(3), 317-333.
Haleem, A., Javaid, M., Qadri, M. A., Singh, R. P., & Suman, R. (2022). Artificial intelligence (AI) applications for marketing: A literature-based study. International Journal of Intelligent Networks, 3, 119-132.
Han, R., Lam, H. K., Zhan, Y., Wang, Y., Dwivedi, Y. K., & Tan, K. H. (2021). Artificial intelligence in business-to-business marketing: a bibliometric analysis of current research status, development and future directions. Industrial Management & Data Systems, 121(12), 2467-2497.
Herman, E. (2022). Leveraging artificial intelligence in marketing for social good—An ethical perspective. Journal of Business Ethics, 179(1), 43-61.
Hu, P., Gong, Y., Lu, Y., & Ding, A. W. (2023). Speaking vs. listening? Balance conversation attributes of voice assistants for better voice marketing. International Journal of Research in Marketing, 40(1), 109-127.
Huang, M. H., & Rust, R. T. (2022). A framework for collaborative artificial intelligence in marketing. Journal of Retailing, 98(2), 209-223.
Hunt, S. D., & Madhavaram, S. (2020). Adaptive marketing capabilities, dynamic capabilities, and renewal competences: The “outside vs. inside” and “static vs. dynamic” controversies in strategy. Industrial Marketing Management, 89, 129–139.
Kitchenham, B., Brereton, O. P., Budgen, D., Turner, M., Bailey, J., & Linkman, S. (2009). Systematic literature reviews in software engineering–a systematic literature review. Information and software technology, 51(1), 7-15.
Kumar, V., Ashraf, A. R., & Nadeem, W. (2024). AI-powered marketing: What, where, and how?. International Journal of Information Management, 77, 102783.
Lusch, R. F., Vargo, S. L., & Wessels, G. (2008). Toward a conceptual foundation for service science: Contributions from service-dominant logic. IBM Systems Journal, 47(1), 5-14.
Manser Payne, E. H., Peltier, J., & Barger, V. A. (2021). Enhancing the value co-creation process: artificial intelligence and mobile banking service platforms. Journal of Research in Interactive Marketing, 15(1), 68-85.
Martini, B., Bellisario, D., & Coletti, P. (2024). Human-centered and sustainable artificial intelligence in industry 5.0: Challenges and perspectives. Sustainability, 16(13), 5448.
Mulyana, M., Din, M., Mustamin, M., Amir, A. M., Karim, F., & Betty, B. (2022). Local government own-source revenue and general allocation funds on capital expenditure: Economic growth as moderating variable. Arthatama, 6(1), 44-54.
Ofori, D., & Appiah-Nimo, C. (2022). Relationship management, competitive advantage and performance of hotels: a resource-based view. Journal of African Business, 23(3), 712-730.
Shankar, R., & Gupta, L. (2024). An integrated AI framework for managing organizational risk and climate change concerns in B2B market. Industrial Marketing Management, 117, 173-187.
Shifa, D., & Harto, P. (2024). The Impact of CSR Environmental Disclosure and Institutional Ownership on Company Value. Research Horizon, 4(4), 55-64.
Stone, M., Aravopoulou, E., Ekinci, Y., Evans, G., Hobbs, M., Labib, A., ... & Machtynger, L. (2020). Artificial intelligence (AI) in strategic marketing decision-making: a research agenda. The Bottom Line, 33(2), 183-200.
Subkhan, M. A., & Hutajulu, D. M. (2023). The Analysis of the Effect of Financial Deepening on Indonesia’s Economic Growth: A Longitudinal Analysis. Research Horizon, 3(1), 19-35.
Vargo, S. L., & Lusch, R. F. (2004). Evolving to a new dominant logic for marketing. Journal of marketing, 68(1), 1-17.
Wahyono, T., Satriyo, F. R., & Andriyani, A. (2024). The Role of Green Entrepreneurial Intention in Shaping Green Entrepreneurial Behavior: A Literature Review. Research Horizon, 4(4), 35-46.
Wang, X., Lin, X., & Shao, B. (2022). How does artificial intelligence create business agility? Evidence from chatbots. International journal of information management, 66, 102535.
Wijaya, J. (2021). Determination of Network Technology of Fixed Broadband with Fuzzy Multiple Criteria for Decision Making Method. Research Horizon, 1(6), 237-243.
Yanescha, N. Y. P. (2022). Analysis of factors affecting inflation in Indonesia 2015-2020. Research Horizon, 2(2), 330-344.
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.