Impact of Dynamic Pricing on Consumer Behavior and Market Competition under Digital Transformation
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Keywords:
AI-Driven Pricing, Dynamic Pricing, Machine Learning In Pricing, Revenue Optimization, Pricing StrategiesAbstract
Integrating AI into various businesses has attracted much attention regarding its use in pricing
tactics. This article explores AI-driven pricing techniques, focusing on dynamic pricing and its significant
impact on consumer behavior and market competition. Facilitated by sophisticated machine learning
algorithms, dynamic pricing allows for real-time adjustments based on various variables, including demand,
competitive pricing, and market trends. This research examines the complex effects of AI-driven dynamic
pricing on customer behavior, focusing on how personalized and context-sensitive pricing influences
purchasing choices. Additionally, we examine the effects of dynamic pricing on market competitiveness,
assessing its ability to enhance revenue for organizations while maintaining fair and transparent procedures.
Through case studies from several sectors, we seek to explore the effectiveness of AI-driven pricing models
and their impact on market dynamics. This study discusses the intersection of AI, pricing strategies, and
market dynamics by comprehensively examining current literature, empirical investigations, and practical
applications. The findings presented here provide important insights for academics, practitioners, and
policymakers addressing the changing dynamics of AI in pricing and enhancing understanding of its
implications for consumer decisions and competitive market conditions. The paper demonstrates the
influence of price dynamics on consumer behavior, contributing to the scholarly discourse on incorporating
AI into business frameworks, especially on dynamic pricing tactics in competitive marketplaces. It offers
pragmatic recommendations for enterprises to enhance real-time pricing strategies by acknowledging the
significance of market competition and consumer preferences while emphasizing the potential risks of
elevated customer price sensitivity in dynamic pricing scenarios.
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References
S. F. Wamba, "Impact of artificial intelligence assimilation on firm performance: The mediating effects of organizational agility and customer agility," International Journal of Information Management, vol. 67, p. 102544, 2022.
V. Pillai, "Integrating AI-Driven Techniques in Big Data Analytics: Enhancing Decision-Making in Financial Markets," International Journal Of Engineering And Computer Science, vol. 12, no. 07, 2023.
D. Nunan and M. Di Domenico, "Value creation in an algorithmic world: Towards an ethics of dynamic pricing," Journal of Business Research, vol. 150, pp. 451-460, 2022.
X. Zhang and F. Dong, "Why do consumers make green purchase decisions? Insights from a systematic review," International journal of environmental research and public health, vol. 17, no. 18, p. 6607, 2020.
Y. Qu, V. Kumar, and Y. Zhao, "A dynamic model of the contract length and early termination: The roles of technology evolution and pricing strategy," Journal of Business Research, vol. 167, p. 114141, 2023.
F. Sudirjo, "Marketing Strategy in Improving Product Competitiveness in the Global Market," Journal of Contemporary Administration and Management (ADMAN), vol. 1, no. 2, pp. 63-69, 2023.
E. E. Piteli and C. Pitelis, "Platform oligopolies, anti-trust policy and sustainable development," Handbook of Industrial Development, pp. 357-381, 2023.
D. J. Teece, "The dynamic competition paradigm: Insights and implications," Colum. Bus. L. Rev., p. 373, 2023.
S. A. Mushtaq and M. M. Hafeez, "An Analysis of the Abuse of Dominance using Artificial Intelligence (AI) enabled Price Discrimination from a Law and Economics Perspective," Pakistan Social Sciences Review, vol. 8, no. 3, pp. 701-718, 2024.
P. Seele, C. Dierksmeier, R. Hofstetter, and M. D. Schultz, "Mapping the ethicality of algorithmic pricing: A review of dynamic and personalized pricing," Journal of Business Ethics, vol. 170, pp. 697-719, 2021.
T. J. Gerpott and J. Berends, "Competitive pricing on online markets: a literature review," Journal of Revenue and Pricing Management, vol. 21, no. 6, p. 596, 2022.
E. Shove, "Everyday practice and the production and consumption of time," in Time, consumption and everyday life: Routledge, 2020, pp. 17-33.
B. Haghpour, E. Sahabeh, and H. Halvari, "Opportunity cost in consumer behavior: Definitions, operationalizations, and ambiguities," International Journal of Consumer Studies, vol. 46, no. 5, pp. 1942-1959, 2022.
E. E. Pramiarsih, "CONSUMER BEHAVIOR IN THE DIGITAL ERA," INTERNATIONAL JOURNAL OF FINANCIAL ECONOMICS, vol. 1, no. 3, pp. 662-674, 2024.
A. Ivanov, "E-commerce Trends and their Impact on Traditional Retail: A Comprehensive Analysis," Center for Management Science Research, vol. 1, no. 2, pp. 12-21, 2023.
A. M. López-Fernández, "Price sensitivity versus ethical consumption: a study of Millennial utilitarian consumer behavior," Journal of Marketing Analytics, vol. 8, no. 2, pp. 57-68, 2020.
S. Dominique-Ferreira, H. Vasconcelos, and J. F. Proença, "Determinants of customer price sensitivity: an empirical analysis," Journal of Services Marketing, vol. 30, no. 3, pp. 327-340, 2016.
G.-Y. Ban and N. B. Keskin, "Personalized dynamic pricing with machine learning: High-dimensional features and heterogeneous elasticity," Management Science, vol. 67, no. 9, pp. 5549-5568, 2021.
C. Tomitza, U. Ibrahimli, and L.-V. Herm, "AI-BASED METHODS OF DYNAMIC PRICING IN E-COMMERCE: A SYSTEMATIZATION OF LITERATURE," 2024.
M. S. Gazi, M. R. Hasan, N. Gurung, and A. Mitra, "Ethical Considerations in AI-driven Dynamic Pricing in the USA: Balancing Profit Maximization with Consumer Fairness and Transparency," Journal of Economics, Finance and Accounting Studies, vol. 6, no. 2, pp. 100-111, 2024.
H. Sargeant and T. Groza, "Unleashing the Power of Algorithms in Antitrust Enforcement: Navigating the Boundaries of Bias and Opportunity," CPI Antitrust Chronicle, vol. 1, 2023.
V. Dunka, "AI-Based Dynamic Pricing Strategies in Retail: Utilizing Machine Learning for Real-Time Price Optimization, Competitive Analysis, and Customer Segmentation," African Journal of Artificial Intelligence and Sustainable Development, vol. 2, no. 2, pp. 339-380, 2022.
M. Avula and T. Sithole, "Artificial Intelligence's Potential to Improve Operational Efficiency and Customer Experience in the Hospitality and Tourism Sectors," in Impact of AI and Tech-Driven Solutions in Hospitality and Tourism: IGI Global, 2024, pp. 351-382.
J. Sidlauskiene, Y. Joye, and V. Auruskeviciene, "AI-based chatbots in conversational commerce and their effects on product and price perceptions," Electronic Markets, vol. 33, no. 1, p. 24, 2023.
A. Martinho, N. Herber, M. Kroesen, and C. Chorus, "Ethical issues in focus by the autonomous vehicles industry," Transport reviews, vol. 41, no. 5, pp. 556-577, 2021.
R. Raman, S. Gunasekar, D. Kaliyaperumal, and P. Nedungadi, "Navigating the Nexus of Artificial Intelligence and Renewable Energy for the Advancement of Sustainable Development Goals," Sustainability, vol. 16, no. 21, p. 9144, 2024.
