The influence of AI on price forecasting. The view of the academic community

In the context of the impressive development of Big Data, AI algorithms have proven their efficiency in processing and analyzing large volumes of data. Price prediction was no exception. In the modern economic fields, the need for advanced prediction models, with increased efficiency, has become mor...

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Published inJournal of business economics and management Vol. 26; no. 1; pp. 231 - 254
Main Authors Ciuverca, Alexandra-Cristina-Daniela, Oprea, Simona‑Vasilica
Format Journal Article
LanguageEnglish
Published Vilnius Vilnius Gediminas Technical University 03.04.2025
Subjects
Accuracy
Algorithms
Artificial intelligence
Big Data
Consumer goods
Efficiency
Forecasting
Informatics
LDA
Methods
Natural language processing
Predictions
price prediction
Prices
Sentiment analysis
Trends
Volatility
AI
LDA
price prediction
volatility
sentiment analysis
research publication
Online AccessGet full text
ISSN1611-1699
2029-4433
2029-4433
DOI10.3846/jbem.2025.23544

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Abstract In the context of the impressive development of Big Data, AI algorithms have proven their efficiency in processing and analyzing large volumes of data. Price prediction was no exception. In the modern economic fields, the need for advanced prediction models, with increased efficiency, has become more and more important. Thus, the interest in the potential of AI solutions in terms of price prediction for all industries has also grown progressively. The present study aims to capture, by using several Natural Language Processing techniques, the feeling that the academic community has in relation to the subject of price prediction and the way in which opinions have evolved over the years. For this purpose, the abstracts of the works indexed in the Clarivate WoS that addressed this topic are included in the current analysis. The scores obtained after the analysis reveal a slightly positive attitude towards the subject, but nevertheless quite reserved. The main topics existing in these articles are also extracted by means of Latent Dirichlet Allocation. Our analysis makes contributions to the formulation of the position that specialists in the scientific community have in relation to price prediction and AI evolution. Further, it provides new research directions for future studies.
AbstractList In the context of the impressive development of Big Data, AI algorithms have proven their efficiency in processing and analyzing large volumes of data. Price prediction was no exception. In the modern economic fields, the need for advanced prediction models, with increased efficiency, has become more and more important. Thus, the interest in the potential of AI solutions in terms of price prediction for all industries has also grown progressively. The present study aims to capture, by using several Natural Language Processing techniques, the feeling that the academic community has in relation to the subject of price prediction and the way in which opinions have evolved over the years. For this purpose, the abstracts of the works indexed in the Clarivate WoS that addressed this topic are included in the current analysis. The scores obtained after the analysis reveal a slightly positive attitude towards the subject, but nevertheless quite reserved. The main topics existing in these articles are also extracted by means of Latent Dirichlet Allocation. Our analysis makes contributions to the formulation of the position that specialists in the scientific community have in relation to price prediction and AI evolution. Further, it provides new research directions for future studies.
In the context of the impressive development of Big Data, AI algorithms have proven their efficiency in processing and analyzing large volumes of data. Price prediction was no exception. In the modern economic fields, the need for advanced prediction models, with increased efficiency, has become more and more important. Thus, the interest in the potential of AI solutions in terms of price prediction for all industries has also grown progressively. The present study aims to capture, by using several Natural Language Processing techniques, the feeling that the academic community has in relation to the subject of price prediction and the way in which opinions have evolved over the years. For this purpose, the s of the works indexed in the Clarivate WoS that addressed this topic are included in the current analysis. The scores obtained after the analysis reveal a slightly positive attitude towards the subject, but nevertheless quite reserved. The main topics existing in these articles are also extracted by means of Latent Dirichlet Allocation. Our analysis makes contributions to the formulation of the position that specialists in the scientific community have in relation to price prediction and AI evolution. Further, it provides new research directions for future studies.
Author Ciuverca, Alexandra-Cristina-Daniela
Oprea, Simona‑Vasilica
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SubjectTerms Accuracy
Algorithms
Artificial intelligence
Big Data
Consumer goods
Efficiency
Forecasting
Informatics
LDA
Methods
Natural language processing
Predictions
price prediction
Prices
Sentiment analysis
Trends
Volatility
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Title The influence of AI on price forecasting. The view of the academic community
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