Artificial intelligence and marketing innovation: The mediating role of organizational culture
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DOIhttp://dx.doi.org/10.21511/im.20(3).2024.14
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Article InfoVolume 20 2024, Issue #3, pp. 170-181
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The rapid advancement of artificial intelligence (AI) is transforming the e-commerce landscape, prompting businesses to adopt innovative marketing strategies. This study investigates the relationship between AI applications and marketing innovation in Egyptian e-commerce retailers, with a focus on the mediating role of organizational culture. The research employed a quantitative approach, utilizing a survey to gather data from 260 Egyptian e-retail store owners, managers, and marketers. The findings reveal a significant positive correlation between AI applications and marketing innovation, with organizational culture playing a crucial mediating role. The correlation coefficient (R) between AI and organizational culture was found to be 0.76, indicating that AI explains 57% of the variance in organizational culture. Similarly, the correlation coefficient (R) between AI and marketing innovation was 0.70, suggesting that AI explains 49% of the variance in marketing innovation. Path analysis further demonstrated a significant indirect effect of AI on marketing innovation through organizational culture. The study concludes that the integration of AI into marketing strategies can substantially enhance innovation, particularly when complemented by a supportive organizational culture. It underscores the importance for e-commerce retailers to invest in AI technologies and cultivate a culture that embraces technological advancements to drive marketing innovation and achieve sustainable competitive advantage.
Acknowledgment
The authors are thankful to the Deanship of Graduate Studies and Scientific Research at University of Bisha for supporting this work through the Fast-Track Research Support Program.
- Keywords
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JEL Classification (Paper profile tab)M14, M31, O39
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References29
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Tables15
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Figures2
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- Figure 1. Research Model
- Figure 2. Path analysis model showing the impact of artificial intelligence on marketing innovation through the mediation of organizational culture
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- Table 1. Distribution of study sample individuals by activity
- Table 2. Measures of the research variables and the number of items in the survey
- Table 3. Reliability and Internal consistency coefficients of the research variables using Cronbach’s alpha
- Table 4. Results of one-way ANOVA test
- Table 5. Table of multiple comparisons around the concept of artificial intelligence
- Table 6. Results of one-way ANOVA test
- Table 7. Table of multiple comparisons regarding organizational culture
- Table 8. Results of one-way ANOVA test
- Table 9. Table of multiple comparisons regarding marketing innovation
- Table 10. Output of simple linear regression analysis method
- Table 11. Artificial intelligence applications and organizational culture
- Table 12. Output of simple linear regression analysis method
- Table 13. Artificial intelligence applications and marketing innovation
- Table 14. Output of simple linear regression analysis method
- Table 15. Results of path analysis
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- Afifah, Wahyu Aroyssi, J., Raihan Fathin, M., & Ilmi Priabas, Y. (2022). Marketing Innovation in the Digital Communication Era. International Journal of Research and Applied Technology (INJURATECH), 2(1), 240-246.
- Aiswarya, S., Rahman, A. F., & Vijaykumar, M. (2024). The impact of AI on employment and organisation in the industrial working environment of the future. International Journal of Research GRANTHAALAYAH, 12(3).
- Babatunde, S., Odejide, O., Edunjobi, T., & Ogundipe, D. (2024). The role of AI in marketing personalization: A theoretical exploration of consumer engagement strategies. International Journal of Management & Entrepreneurship Research, 6, 936-949.
- Balducci, B., & Marinova, D. (2018). Unstructured data in marketing. Journal of the Academy of Marketing Science, 46(4), 557-590.
- Behl, A., Pereira, V., Jayawardena, N., Nigam, A., & Mangla, S. (2023). Gamification as an innovation: A tool to improve organizational marketing performance and sustainability of international firms. International Marketing Review, 41(1), 107-137.
- Chou, S., Horng, J., Liu, C., Yu, T., & Kuo, Y. (2022). Identifying the critical factors for sustainable marketing in the catering: The influence of big data applications, marketing innovation, and technology acceptance model factors. Journal of Hospitality and Tourism Management, 51, 11-21.
- 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(3), 24-42.
- Dekimpe, M. G. (2020). Retailing and retailing research in the age of big data analytics. International Journal of Research in Marketing, 37(1), 3-14.
- Farseev, A. (2023). Under the Hood of Social Media Advertising: How Do We Use AI Responsibly for Advertising Targeting and Creative Evaluation. In WSDM ‘23: Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining (pp. 1281-1282).
- Fousiani, K., Michelakis, G., Minnigh, P. A., & De Jonge, K. M. M. (2024). Competitive organizational climate and artificial intelligence (AI) acceptance: The moderating role of leaders’ power construal. Frontiers in Psychology, 15.
- Gacanin, H., & Wagner, M. (2019). Artificial intelligence paradigm for customer experience management in next-generation networks: Challenges and perspectives. IEEE Network, 33(2), 188-194.
- Grewal, D., Hulland, J., Kopalle, P. K., & Karahanna, E. (2020). The future of technology and marketing: A multidisciplinary perspective. Journal of the Academy of Marketing Science, 48, 1-8.
- Han, M., Light, J., Xia, S., Galhotra, S., Castro Fernandez, R., & Xu, H. (2023). A Data-Centric Online Market for Machine Learning: From Discovery to Pricing. arXiv preprint arXiv:2310.17843 [cs.LG].
- Huang, M. H., & Rust, R. T. (2020). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49, 1-21.
- Huang, M. H., & Rust, R. T. (2021). A framework for Collaborative Artificial Intelligence in Marketing. Journal of Retailing, 98(2), 209-223.
- Joudeh, J., Allan, M., Ahmad Zamil, A., Alfityani, A., Dandis, A., Nusairat, N., & Al-Gasawneh, J. (2023). The impact of marketing strategy on the marketing innovation and the marketing comparative advantage in the Jordanian furniture industry. Journal of Southwest Jiaotong University, 57, 395-412.
- Kumari, C. S., Deepu, B. S. V. V., G, D., & Surampudi, V. K. S. (2023). FMCG Market Analysis for Wholesalers and Retailers Using Machine Learning. In Proceedings of 3rd International Conference on Pervasive Computing and Social Networking (ICPCSN), Salem, India (pp. 323-328).
- Kusumawati, I., & Yulistiyono, A. (2022). The influence of organizational culture, business strategy for increase in performance organizational tourism. International Journal of Sustainable Development, 1(1).
- Ma, S., & Fildes, R. (2021). Retail sales forecasting with meta-learning. European Journal of Operational Research, 288, 111-128.
- Marchand, A., & Marx, P. (2020). Automated product recommendations with preference-based explanations. Journal of Retailing, 96(3), 328-343.
- Miller, G. J. (2022). Artificial Intelligence Project Success Factors—Beyond the Ethical Principles. In E. Ziemba & W. Chmielarz (Eds.), Information Technology for Management: Business and Social Issues (FedCSIS-AIST ISM 2021 2021). (pp. 65-96). Lecture Notes in Business Information Processing, vol 442. Springer, Cham.
- Muis, I., Adhi, T., & Kamalia, R. (2024). The Impact of Digital Marketing and Innovation on Marketing Performance is Influenced through the Development of a Competitive Advantage. Revista de Gestão Social e Ambiental, 18.
- Murár, P., & Kubovics, M. (2023). Using AI to Create Content Designed for Marketing Communications. European Conference on Innovation and Entrepreneurship, 18, 660-668.
- Osman, A. M., Liu, Y., & Wang, Z. (2023). Influence of organizational culture on construction firms’ performance: The mediating roles of innovation and marketing capabilities. Buildings, 13(2), 308.
- Sánchez-Cartas, J. M., & Katsamakas, E. (2024). AI pricing algorithms under platform competition. Electronic Commerce Research.
- Seranmadevia, R., & Kumara, A. S. (2019). Experiencing the AI emergence in Indian retail: Early adopter’s approach. Management Science Letters, 9, 33-42.
- Shanti, A., Jebreel, M., Qabajeh, M., Nassoura, A., & Airout, R. (2023). The role of organizational antecedents in fostering accounting intelligence adoption: The mediating influence of organizational culture. Human Systems Management, 1-17.
- 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, 255-275.
- Wirth, N. (2018). Hello marketing, what can artificial intelligence help you with? International Journal of Market Research, 6(5), 435-438.