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In a world characterized by turmoil and unpredictability, businesses face the challenge of setting prices that successfully balance profitability and consumer appeal. The rise of artificial intelligence (AI) has been viewed as a potential game-changer in this area, offering a promising solution to help navigate uncertain times. However, recent global disruptions, such as the COVID-19 pandemic, have revealed the limitations of traditional AI models to adapt to drastic changes.

A new development emerges from this landscape thanks to the work of UC Riverside School of Business professors Mingyu "Max" Joo and Hai Che, along with collaborators from Baruch College and Ohio State University. They have created an innovative deep-learning model that combines historical sales data with economic demand theory. This breakthrough has the potential to transform how businesses understand and predict consumer behavior, especially during challenging times.

The essence of their research highlights a significant shift in perspective. Traditionally, AI models relied solely on historical sales data, often neglecting the complexities of consumer behavior during unforeseen events. Joo and Che's model integrates fundamental principles of economic theory, creating a new paradigm for pricing predictions.

Through the application of economic theory, the researchers have successfully quantified the unpredictable nature of consumer behavior during extraordinary circumstances—a challenge that has long confounded conventional AI models. By analyzing the interactions between external influences like pandemics or economic shocks and pricing strategies, their model offers hope for businesses navigating uncertain terrains.

The past year has underscored the weaknesses of traditional AI models, and this breakthrough serves as a timely reminder of the value that diverse perspectives bring. The combination of AI and economic theory not only provides a clearer understanding of consumer behavior but also showcases the transformative potential of interdisciplinary collaboration.

Validation of their model during the COVID-19 pandemic highlights its resilience. While conventional AI models struggled under immense disruptions, Joo and Che's approach demonstrated exceptional accuracy, significantly reducing generalization errors. This development paves the way for a new era in pricing predictions.

This work offers a compelling glimpse into a future where advanced AI techniques and established economic principles converge to form a robust and adaptable framework.

In an era marked by uncertainty, these advancements highlight AI's transformative potential when combined with diverse perspectives. They pave the way for a future in which businesses can confidently navigate uncharted waters with insight and expertise.