RETRACTED: Predictable inventory management within dairy supply chain operations
International Journal of Retail & Distribution Management
ISSN: 0959-0552
Article publication date: 23 May 2023
Retraction notice
The publisher of the International Journal of Retail & Distribution Management wishes to retract the following article. Huerta-Soto, R., Ramirez-Asis, E., Tarazona-Jiménez, J., Nivin-Vargas, L., Norabuena-Figueroa, R., Guzman-Avalos, M. and Reyes-Reyes, C. (2023), “Predictable inventory management within dairy supply chain operations”, International Journal of Retail & Distribution Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJRDM-01-2023-0051
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
With the current wave of modernization in the dairy industry, the global dairy market has seen significant shifts. Making the most of inventory planning, machine learning (ML) maximizes the movement of commodities from one site to another. By facilitating waste reduction and quality improvement across numerous components, it reduces operational expenses. The focus of this study was to analyze existing dairy supply chain (DSC) optimization strategies and to look for ways in which DSC could be further improved. This study tends to enhance the operational excellence and continuous improvements of optimization strategies for DSC management
Design/methodology/approach
Preferred reporting items for systematic reviews and meta-analyses (PRISMA) standards for systematic reviews are served as inspiration for the study's methodology. The accepted protocol for reporting evidence in systematic reviews and meta-analyses is PRISMA. Health sciences associations and publications support the standards. For this study, the authors relied on descriptive statistics.
Findings
As a result of this modernization initiative, dairy sector has been able to boost operational efficiency by using cutting-edge optimization strategies. Historically, DSC researchers have relied on mathematical modeling tools, but recently authors have started using artificial intelligence (AI) and ML-based approaches. While mathematical modeling-based methods are still most often used, AI/ML-based methods are quickly becoming the preferred method. During the transit phase, cloud computing, shared databases and software actually transmit data to distributors, logistics companies and retailers. The company has developed comprehensive deployment, distribution and storage space selection methods as well as a supply chain road map.
Practical implications
Many sorts of environmental degradation, including large emissions of greenhouse gases that fuel climate change, are caused by the dairy industry. The industry not only harms the environment, but it also causes a great deal of animal suffering. Smaller farms struggle to make milk at the low prices that large farms, which are frequently supported by subsidies and other financial incentives, set.
Originality/value
This paper addresses a need in the dairy business by giving a primer on optimization methods and outlining how farmers and distributors may increase the efficiency of dairy processing facilities. The majority of the studies just briefly mentioned supply chain optimization.
Keywords
Citation
Huerta-Soto, R., Ramirez-Asis, E., Tarazona-Jiménez, J., Nivin-Vargas, L., Norabuena-Figueroa, R., Guzman-Avalos, M. and Reyes-Reyes, C. (2023), "RETRACTED: Predictable inventory management within dairy supply chain operations", International Journal of Retail & Distribution Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJRDM-01-2023-0051
Publisher
:Emerald Publishing Limited
Copyright © 2023, Emerald Publishing Limited