Data sharing: a collaborative model for a green textile/clothing supply chain

Kuo, Tsai‐Chi; Hsu, Chia‐Wei; Huang, Samuel H.; Gong, Dah-Chuan

doi:10.1080/0951192x.2013.814157

Cited by 41 publications

(28 citation statements)

References 41 publications

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“…The exploration of these aspects in empirical researches (in survey and case studies, for example) appears to be a promising path. In this direction, Kuo et al (2014) study points to the company's interest in establishing green SCs and proves, through the study of an illustrative case in a textile/clothing SC, that the sharing of data related to environmental impacts is a key factor of success for developing this kind of chain. The authors point out that there is a space for future researches that will examine in the different SCs (not only in the textile/clothing industry) how the information related to environmental impacts (e.g., carbon emission information) is shared by the agents in these chains.…”

Section: A Bibliometric Analysis Of International Literature On Collamentioning

confidence: 88%

“…Klassen and Vachon's (2003) paper addresses the environmental approach to collaboration in SC, focusing on environmental investment. The studies of Vachon and Klassen (2008) and Kuo et al (2014) also deal with the environmental issue but focusing on collaborative activities and data sharing, respectively. Chong and Zhou (2014) analyze the relation between the adoption of e-SC integration and performance in service innovation from the perspective of SC management.…”

Section: Research Type and Paper Approachmentioning

confidence: 99%

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Uma análise bibliométrica da literatura internacional sobre colaboração na cadeia de suprimentos

Oliveira

Santos

Becker

et al. 2016

BASE

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Section: A Bibliometric Analysis Of International Literature On Collamentioning

confidence: 88%

Section: Research Type and Paper Approachmentioning

confidence: 99%

Uma análise bibliométrica da literatura internacional sobre colaboração na cadeia de suprimentos

Oliveira

Santos

Becker

et al. 2016

BASE

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“…Unsustainable and unregulated production and consumption are contributing to the degradation of the global environment [16]. Proper monitoring and analysis in the textile and apparel supply chain is necessary to minimize its environmental impact [17]. A literature review on the apparel supply chain is as follows.…”

Section: Literature Reviewmentioning

confidence: 99%

Data Analysis of Shipment for Textiles and Apparel from Logistics Warehouse to Store Considering Disposal Risk

et al. 2019

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Given the rapid diversification of products in the textile and apparel industry, manufacturers face significant new challenges in production. The life cycle of apparel products has contracted and is now, generally, a several-week season, during which time a majority of products are supposed to be sold. Products that do not sell well may be sold at a price lower than the fixed price, and products that do not sell at all within the sales period may eventually become forced disposal. This creates long-term management and environmental problems. In practice, shipping personnel determine when to ship products to stores after reviewing product sales information. However, they may not schedule or structure these shipments properly because they cannot effectively monitor sales for a large number of products. In this paper, shipment is considered to reduce the risk of product disposal on the premise of selling at a fixed price. Although shipment quantities are determined by various factors, we only consider the change in inventory at the logistics warehouse, since it is difficult to incorporate all factors into the analysis. From cluster analysis, it is found that shipping personnel should recognize a policy to sell products gradually over time. Furthermore, to reduce the risk of disposal, we forecast the inventory from conditional probability and are able to extract products out of a standard grouping using past data.

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“…Various advantages of implementing effective information exchange and data sharing were highlighted in other studies, e.g. improved sustainability and environmental-friendly products in textile and apparel industry through efficient information sharing (Kuo et al 2014), improved supply chain coordination through forecasting (Xu, Dong, and Evers 2001), or supplier forecasting performance (Trapero, Kourentzes, and Fildes 2012). Other studies concentrated on problems related to forecasting and planning during information sharing, e.g.…”

Section: Implementation and Examination Of Information Sharingmentioning

confidence: 99%

What modelling research on supply chain collaboration informs us? Identifying key themes and future directions through a literature review

Gustafsson

2018

International Journal of Production Research

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Although research regarding supply chain collaboration has been increasing, studies reviewing supply chain collaboration remains limited. This review paper categorises supply chain collaboration and identifies different themes in this research field. Articles were collected based on a designed keywords list and specific subject restrictions in citation databases. Textmining technology and conceptual criteria were used to categorise and screen articles into different categories. Finally, cluster analysis was used to group articles and identify emerging themes. From the year 1999 to 2017, a total of 678 articles regarding supply chain collaboration were found. These were sorted into six categories: levels of collaboration, industries, supply chain stages, company scales, forms/methods of collaboration and typology of article, and into corresponding sub-categories. 380 articles employing modelling approach where collaboration forms the core of analysis were screened for hierarchical cluster analysis, resulting in four clusters: information sharing paradigm, joint decision-making paradigm, resource sharing paradigm and coordinating contract paradigm. Eleven themes were finally identified based on the four clusters. The number of articles in the field of supply chain collaboration shows an increasing trend by year. However, most of the collaborations discussed were still at a low level. It is expected to explore a higher level of collaborations and related themes in future research.

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Data sharing: a collaborative model for a green textile/clothing supply chain

Cited by 41 publications

References 41 publications

Uma análise bibliométrica da literatura internacional sobre colaboração na cadeia de suprimentos

Uma análise bibliométrica da literatura internacional sobre colaboração na cadeia de suprimentos

Data Analysis of Shipment for Textiles and Apparel from Logistics Warehouse to Store Considering Disposal Risk

What modelling research on supply chain collaboration informs us? Identifying key themes and future directions through a literature review

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