Masterstrokes and markets: a bibliometric journey through art's value

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CREDIT: MINGJUN GUO, XUERONG LI, YUNJIE WEI

The art market, blending culture and commerce, has long intrigued economists and enthusiasts. A new article offers a comprehensive bibliometric analysis over five decades, examining pricing mechanisms and efficiency metrics. It highlights the COVID-19 pandemic's role in accelerating digital transformations within the market. This analysis provides valuable insights for future research, offering a robust foundation for understanding the dynamic interplay between art, economics, and culture.

The art market, with its centuries-old history, has undergone significant transformations, especially in recent decades. Scholars have examined various aspects, from art pricing and artist branding to the implications of digital platforms and regulatory measures. Despite extensive research, gaps remain in understanding the full scope of market efficiency and the evolving dynamics influenced by technological advancements and global events. Due to these challenges, there is a pressing need for comprehensive studies that delve deeper into these areas, especially in light of recent shifts in market behavior and regulatory landscapes.

A recent review (DOI: 10.1016/j.dsm.2024.03.006) by researchers from the Academy of Mathematics and Systems Science at the Chinese Academy of Sciences, published in Data Science and Management on April 13, 2024, provides a thorough bibliometric analysis of the art market spanning the last 50 years. Utilizing big data and various analytical methods, the study maps out significant trends, influential works, and emerging themes within the art market.

The study utilized a comprehensive dataset from the Web of Science Core Collection, encompassing 912 pieces of literature on the art market from 1972 to 2021. Through descriptive statistical analysis and various bibliometric methods, including co-citation and co-word analysis, the researchers identified key trends and shifts in research focus. Notably, the study found a consistent annual increase in research interest in the art market, with significant shifts from hedonic art prices to topics such as artist brand management, digital art platforms, and anti-money laundering supervision. The analysis highlighted the substantial impact of the COVID-19 pandemic in expediting digital transformations within the art market. Additionally, the study revealed five primary research clusters: anonymous painting and artistic brands, hedonic art price indices, digital art platforms, anti-money laundering regulation, and market efficiency. Each cluster represents a critical area of focus within the field, providing a detailed roadmap for future research directions.

Dr. Yunjie Wei, a corresponding author from the Academy of Mathematics and Systems Science, stated, "Our findings illuminate the evolving priorities within art market research, particularly the growing importance of digital platforms and regulatory measures. This comprehensive analysis not only maps out past trends but also highlights critical areas for future exploration, offering valuable insights for scholars and practitioners alike."

The study's findings have significant implications for both academic research and practical applications within the art market. By identifying key trends and emerging areas of focus, it provides valuable insights for scholars and practitioners, including art dealers, auction houses, and regulatory bodies. These insights help navigate the complexities of digital transformation and regulatory compliance. The study underscores the necessity for ongoing monitoring and analysis to keep pace with the rapidly evolving art market landscape, ensuring that stakeholders remain informed and adaptive to new trends and regulatory demands.

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Media contact:

Name: Yajuan Zhao

Email: dsm@xjtu.edu.cn

Expert contact: weiyunjie@amss.ac.cn

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JOURNAL

Data Science and Management

DOI

10.1016/j.dsm.2024.03.006 

ARTICLE TITLE

Bibliometric analysis of the art market: from art price to market efficiency