Deep Learning Techniques for Demand Forecasting: Review and Future Research Opportunities

Arunkumar O N and Divya D.
Additional contact information
Arunkumar O N: Symbiosis Institute of Business Management, Symbiosis International University (Deemed), India
Divya D.: Division of IT, School of Engineering, Cochin University of Science and Technology, India

Information Resources Management Journal (IRMJ), 2022, vol. 35, issue 2, 1-24

Abstract: The aim of this study is to categorize research on the applications of deep learning techniques in demand forecasting and suggest further research directions. This study is based upon 56 papers published between 2017 and April 2021 in international peer-reviewed elite journals. The primary objective of this paper is to identify the major problem domains in demand forecasting; hence, the authors conduct a review of literature that utilizes deep learning techniques for demand forecasting and proposed directions for future research. After identifying the objective, a subject scrutiny of the important papers is done based on the publication quality. These identifications make additions to demand forecasting research in the resulting manner. For accomplishing this task, first, the authors classified the literature into nine major problem domains based on different issues discussed in the literature. Second, the literature is classified based on different deep leaning techniques used for solving the problem of demand forecasting. Third, seven research propositions are provided for future research.

Date: 2022
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IRMJ.291692 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:rmj000:v:35:y:2022:i:2:p:1-24

Access Statistics for this article

Information Resources Management Journal (IRMJ) is currently edited by George Kelley

More articles in Information Resources Management Journal (IRMJ) from IGI Global
Bibliographic data for series maintained by Journal Editor ().