The Transformative Potential of AI in Green Marketing Strategies
Keywords:
AI, Digital marketing, Green marketing strategies, Social-Media, SustainabilityAbstract
This paper explores how AI can greatly enhance green marketing strategies by improving customer targeting, providing personalized recommendations, optimizing supply chains, and accurately forecasting market trends. And addresses the challenges associated with data quality, privacy concerns, biases in algorithms, and transparency issues that need to be overcome for responsible AI implementation. The paper suggests practical recommendations for policymakers to promote ethical and sustainable use of AI in green marketing. It emphasizes the importance of collaboration among businesses, policymakers, and researchers to ensure responsible AI adoption.
References
Alhamad, A. M., Junoh, M. Z. B. M., & Eneizan, B. (2019). Green marketing strategies: Theoretical approach. American journal of economics and business management, 2(2), 77-94.
Amann, J., Blasimme, A., Vayena, E., Frey, D., & Madai, V. I. (2020). Explainability for artificial intelligence in healthcare: a multidisciplinary perspective. BMC medical informatics and decision making, 20(1), 1-9.
Anant, V., Donchak, L., Kaplan, J., & Soller, H. (2020). The consumer-data opportunity and the privacy imperative. Retrieved from McKinsey website: https://www. mckinsey. com/business-functions/risk-and-resilience/our-insights/the-consumer-data-opportunity-and-the-privacy-imperative.
Baqi, A., Abdeldayem, M.M., & Aldulaimi, S.H. (2022). Embedding Artificial Intelligence and Green Ideology in Formulating Corporate and Marketing Strategies. 2022 ASU International Conference in Emerging Technologies for Sustainability and Intelligent Systems (ICETSIS), 1-4.
Bashar, A., & Rabbani, M. R. (2021, November). Exploring the role of web personalization in consumer green purchasing behavior: A conceptual framework. In 2021 third international sustainability and resilience conference: Climate change (pp. 23-28). IEEE.
Bestari, D.K., & Butarbutar, D.A. (2021). Implementation of Green Marketing Strategies and Green Purchase Behavior as Efforts to Strengthen the Competitiveness of MSMEs in Indonesia.
Bhaskar, H. (2013). Green Marketing: A Tool For Sustainable Development. Clear International Journal of Research in Commerce & Management, 4(6).
Bleier, A., Goldfarb, A., & Tucker, C. (2020). Consumer privacy and the future of data-based innovation and marketing. International Journal of Research in Marketing, 37(3), 466-480.
Borah, P. S., Dogbe, C. S. K., Pomegbe, W. W. K., Bamfo, B. A., & Hornuvo, L. K. (2023). Green market orientation, green innovation capability, green knowledge acquisition and green brand positioning as determinants of new product success. European Journal of Innovation Management, 26(2), 364-385.
Cha, H. S., Wi, J. H., Park, C., & Kim, T. (2021). Sustainability calculus in adopting smart speakers—personalized services and privacy risks. Sustainability, 13(2), 602.
Chang, L., Taghizadeh-Hesary, F., & Mohsin, M. (2023). Role of artificial intelligence on green economic development: Joint determinates of natural resources and green total factor productivity. Resources Policy, 82, 103508.
Culnan, M. J., & Bies, R. J. (2003). Consumer privacy: Balancing economic and justice considerations. Journal of social issues, 59(2), 323-342.
Darban, K., & Kabbaj, S. (2021). Publicité digitale et achat de clics ciblés (CPC): Avantages et limites. Revue Marocaine de la Prospective en Sciences de Gestion, (4).
Darban, K., Kabbaj, S. & Khawla Esmaoui (2023). Crisis Management, Internet and AI: Information in the Age of COVID-19, and Future Pandemics. Mathematical Modeling and Intelligent Control for Combating Pandemics. Springer optimization and its applications. ISBN978-3-031-33182-4.
Feng, Y., Lai, K. H., & Zhu, Q. (2022). Green supply chain innovation: Emergence, adoption, and challenges. International Journal of Production Economics, 108497.
Frank, B. (2021). Artificial intelligence-enabled environmental sustainability of products: Marketing benefits and their variation by consumer, location, and product types. Journal of Cleaner Production, 285, 125242.
Grant, J. (2008). Green marketing. Strategic direction, 24(6), 25-27.
Hemker, S., Herrando, C., & Constantinides, E. (2021). The transformation of data marketing: how an ethical lens on consumer data collection shapes the future of marketing. Sustainability, 13(20), 11208.
Ikram, M. (2022). Transition toward green economy: Technological Innovation’s role in the fashion industry. Current Opinion in Green and Sustainable Chemistry, 100657.
Jaume-Palasi, L. (2019). Why we are failing to understand the societal impact of artificial intelligence. Social Research: An International Quarterly, 86(2), 477-498.
Jia, D., & Wu, Z. (2022). Development model of enterprise green marketing based on cloud computing. Wireless Communications and Mobile Computing, 2022.
Karim, D. (2023). Uncovering the Facebook Experience: Insights into Users’ Behavior and Motivations. International Journal of Advanced Scientific Innovation, 5(3).
Karjoth, G., Schunter, M., & Waidner, M. (2002, April). Platform for enterprise privacy practices: Privacy-enabled management of customer data.
Lwin, M., Wirtz, J., & Williams, J. D. (2007). Consumer online privacy concerns and responses: a power–responsibility equilibrium perspective. Journal of the Academy of Marketing Science, 35, 572-585.
Privacy Enhancing Technologies (pp. 69-84). Berlin, Heidelberg: Springer Berlin Heidelberg.
Kaur, B., Gangwar, V.P., & Dash, G. (2022). Green Marketing Strategies, Environmental Attitude, and Green Buying Intention: A Multi-Group Analysis in an Emerging Economy Context. Sustainability.
Kellmeyer, P. (2021). Big brain data: On the responsible use of brain data from clinical and consumer-directed neurotechnological devices. Neuroethics, 14(1), 83-98.
Lerman, L. V., Benitez, G. B., Müller, J. M., de Sousa, P. R., & Frank, A. G. (2022). Smart green supply chain management: A configurational approach to enhance green performance through digital transformation. Supply Chain Management: An International Journal, 27(7), 147-176.
Machová, R., Ambrus, R., Zsigmond, T., & Bakó, F. (2022). The impact of green marketing on consumer behavior in the market of palm oil products. Sustainability, 14(3), 1364.
Martin, K. (2016). Data aggregators, consumer data, and responsibility online: Who is tracking consumers online and should they stop?. The Information Society, 32(1), 51-63.
Mehrabi, N., Morstatter, F., Saxena, N., Lerman, K., & Galstyan, A. (2021). A survey on bias and fairness in machine learning. ACM Computing Surveys (CSUR), 54(6), 1-35.
Nahr, J. G., Nozari, H., & Sadeghi, M. E. (2021). Green supply chain based on artificial intelligence of things (AIoT). International Journal of Innovation in Management, Economics and Social Sciences, 1(2), 56-63.
Pastaltzidis, I., Dimitriou, N., Quezada-Tavarez, K., Aidinlis, S., Marquenie, T., Gurzawska, A., & Tzovaras, D. (2022, June). Data augmentation for fairness-aware machine learning: Preventing algorithmic bias in law enforcement systems. In 2022 ACM Conference on Fairness, Accountability, and Transparency (pp. 2302-2314).
Patwary, A.K., Mohamed, M., Rabiul, M.K., Mehmood, W., Ashraf, M.U., & Adamu, A.A. (2022). Green purchasing behaviour of international tourists in Malaysia using green marketing tools: theory of planned behaviour perspective. Nankai Business Review International.
Peattie, K., & Charter, M. (1992). Green marketing. The marketing book, 726.
Price, W. N., & Cohen, I. G. (2019). Privacy in the age of medical big data. Nature medicine, 25(1), 37-43.
Rahman, S.U., & Nguyen-Viet, B. (2022). Towards sustainable development: Coupling green marketing strategies and consumer perceptions in addressing greenwashing. Business Strategy and the Environment.
Roh, T., Noh, J., Oh, Y., & Park, K. S. (2022). Structural relationships of a firm's green strategies for environmental performance: The roles of green supply chain management and green marketing innovation. Journal of Cleaner Production, 356, 131877.
Sadriwala, M.F., & Sadriwala, K.F. (2022). Perceived Usefulness and Ease of Use of Artificial Intelligence on Marketing Innovation. Int. J. Innov. Digit. Econ., 13, 1-10.
Shin, D. (2020). User perceptions of algorithmic decisions in the personalized AI system: perceptual evaluation of fairness, accountability, transparency, and explainability. Journal of Broadcasting & Electronic Media, 64(4), 541-565.
Shin, D., & Park, Y. J. (2019). Role of fairness, accountability, and transparency in algorithmic affordance. Computers in Human Behavior, 98, 277-284.
Skačkauskienė, I., & Vilkaité-Vaitoné, N. (2022). Green Marketing – a New Norm: a Qualitative Evidence of Green Marketing Challenges and Future Perspectives in High-Low Context Communication Cultures. Cultural Management: Science and Education.
Sterne, J. (2017). Artificial intelligence for marketing: practical applications. John Wiley & Sons.
Su, H., Qu, X., Tian, S., Ma, Q., Li, L., & Chen, Y. (2022). Artificial intelligence empowerment: The impact of research and development investment on green radical innovation in high‐tech enterprises. Systems Research and Behavioral Science, 39(3), 489-502.
Tu, J. C., Chen, Y. Y., & Chen, S. C. (2017). The study of consumer green education via the internet of things with green marketing. EURASIA Journal of Mathematics, Science and Technology Education, 13(9), 6133-6145.
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.
Vilkaite-Vaitone, N., Skackauskiene, I., & Díaz-Meneses, G. (2022). Measuring green marketing: Scale development and validation. Energies, 15(3), 718.
Winston, P. H.(1984). Artificial intelligence. Addison-Wesley Longman Publishing Co., Inc..
Wisetsri, W. (2021). Systematic analysis and future research directions in artificial intelligence for marketing. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(11), 43-55.
Zhang, J. (2021). Development of internet supply chain finance based on artificial intelligence under the enterprise green business model. Mathematical Problems in Engineering, 2021, 1-10.
Zhang, Z. (2010). China in the transition to a low-carbon economy. Energy Policy, 38(11), 6638-6653.
Zheng, X., & Cai, Z. (2020). Privacy-preserved data sharing towards multiple parties in industrial IoTs. IEEE Journal on Selected Areas in Communications, 38(5), 968-979.
Zhao, P., Gao, Y., & Sun, X. (2022). How does artificial intelligence affect green economic growth?—Evidence from China. Science of The Total Environment, 834, 155306.
Zhou, Z. H. (2021). Machine learning. Springer Nature.
Zulaikha, S., Mohamed, H., Kurniawati, M., Rusgianto, S., & Rusmita, S. A. (2020). Customer predictive analytics using artificial intelligence. The Singapore Economic Review, 1-12.
Downloads
Published
How to Cite
License
Copyright (c) 2023 the Authors
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
