RETRACTED: Business intelligence for Industry 4.0: predictive models for retail and distribution
International Journal of Retail & Distribution Management
ISSN: 0959-0552
Article publication date: 6 June 2023
Retraction notice
The publisher of the International Journal of Retail & Distribution Management wishes to retract the following article, Chen, Z., Zhao, J. and Jin, C. (2023), “Business intelligence for Industry 4.0: predictive models for retail and distribution”, International Journal of Retail & Distribution Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJRDM-02-2023-0101
It has come to the attention of the publisher that there are concerns with the handling and peer review of these articles, which were submitted to the special issue ‘Recent trends and advances of information application use in retail, distribution and e-commerce: Marketing and management opportunities, challenges and solutions’. This special issue has now been cancelled. As a result of these concerns, the articles’ findings cannot be relied upon. As trust in the content is central to the integrity of the publication process, the Editor and Publisher have taken the decision to retract all of the articles within this special issue (listed above). The journal has not been able to confirm whether the authors were aware of this attempted manipulation of the publication process. The journal is committed to correcting the scientific record and will fully cooperate with any institutional investigations into this matter. The authors have been informed of this decision. The authors would like it to be noted that they are not in agreement with this retraction. This decision is in accordance with Emerald’s publishing ethics and the COPE guidelines on retractions. The publisher of the journal sincerely apologizes to the readers and authors, who were not found to be involved in any malpractice.
Abstract
Purpose
Textile and contemporary apparel manufacturers are adopting and integrating cutting-edge technologies to reduce their impact on the environment and gain an advantage in the marketplace. Most previous studies have ignored business intelligence systems (BIS), notably in the textile and apparel industry (T&A), in favor of looking at the larger picture of how big data would affect retail and distribution in a company. This is especially true for the T&As.
Design/methodology/approach
The authors report that they conducted 14 semi-structured interviews with 12 international luxury tourism service providers. In this case, researchers use snowball features and systematic techniques to select participants. A qualitative content analysis strategy is used to capture the focus of the interviews.
Findings
Problems with T&A company sustainability, opportunities to increase value creation via use of industry-leading business intelligence (BI) solutions and perceived roadblocks to BIS adoption were all found by the poll. Garment retail and distribution sector has benefited greatly from the increased use of Industry 4.0 technologies, especially those that provide better BI solutions. Determine the extent to which industry participation slows down or speeds up the process. The Company Information System (BIS) will help convince non-tech-savvy business owners of the financial, economic and environmental benefits of adopting certain technologies developed as part of the industry 4.0 movement.
Research limitations/implications
The authors of this research claim theirs is one of the first to investigate what variables affect the uptake of BIS, ultimately hoping to find out how BIS may be used by T&A businesses to tackle environmental issues through the use of Industry 4.0 technologies. The purpose of this study was to see whether BIS might aid T&A firms with their sustainability issues.
Practical implications
In the last several years, there has been a meteoric rise in interest in big data and business analytics among firms and educational institutions alike. This paper tries to introduce readers to the concept of business analytics in a way that is both academic and accessible, considering both the present and future of the field. This paper begins with a quick introduction, followed by a summary of the three distinct forms of predictive modeling discussed.
Originality/value
In an effort to help aspiring analytics professionals, they have identified, categorized and evaluated the nine distinct players that are now active in the analytics market. Following this, they will provide a high-level summary of the many different research projects currently being worked on by their group.
Keywords
Acknowledgements
Funding: The 2021 Hebei University of Environmental Engineering school-level education and teaching reform research project “Exploration on the Path of Ideological and Political Reform of the ‘Green Marketing Planning’ Course Based on the OBE Educational Concept” (Project No.: SZYJ202107).
Citation
Chen, Z., Zhao, J. and Jin, C. (2023), "RETRACTED: Business intelligence for Industry 4.0: predictive models for retail and distribution", International Journal of Retail & Distribution Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJRDM-02-2023-0101
Publisher
:Emerald Publishing Limited
Copyright © 2023, Emerald Publishing Limited