Analytics Applications in Fashion Supply Chain Management—A Review of Literature and Practice
| Autor: | Christina Stahl, Christoph M. Flath, Nikolai Stein |
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| Rok vydání: | 2023 |
| Předmět: | |
| Zdroj: | IEEE Transactions on Engineering Management. 70:1258-1282 |
| ISSN: | 1558-0040 0018-9391 |
| Popis: | Fashion companies’ chance to survive the current pandemic is much dependent on their analytics skills. Despite this urge and the arising possibilities in the “data era,” analytics activities are still underestimated and scattered across different fashion supply chain functions. Therefore, this article positions itself at the important intersection of analytics and fashion supply chain management. This article analyzed analytics applications across all relevant supply chain functions within the fashion industry. We conducted our literature review with a focus on different forms of data-driven decision making applied within fashion supply chain functions. We systematically compared the findings from a structured literature review and a content analysis of corporate annual reports and detailed state-of-the-art analytics examples. We highlight deviations in the analytics level: Research papers have a strong focus on advanced analytics methods while most companies are struggling to establish descriptive analytics capabilities. Based on this, we derive and detail managerial and research implications. Having created a holistic overview, this article presents itself as a cornerstone for further analytics-focused research within the fashion industry. Also, it provides managers with insights into the current landscape of analytics applications and develops the vision of a future analytics-driven fashion supply chain. |
| Databáze: | OpenAIRE |
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