Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/77559
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Logistics and Maritime Studies | - |
dc.creator | Cheng, Y | - |
dc.creator | Kuang, Y | - |
dc.creator | Shi, X | - |
dc.creator | Dong, C | - |
dc.date.accessioned | 2018-08-28T01:33:13Z | - |
dc.date.available | 2018-08-28T01:33:13Z | - |
dc.identifier.uri | http://hdl.handle.net/10397/77559 | - |
dc.language.iso | en | en_US |
dc.publisher | Molecular Diversity Preservation International (MDPI) | en_US |
dc.rights | © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). | en_US |
dc.rights | The following publication Cheng, Y.; Kuang, Y.; Shi, X.; Dong, C. Sustainable Investment in a Supply Chain in the Big Data Era: An Information Updating Approach. Sustainability 2018, 10, 403, 1-18 is available at https://dx.doi.org/10.3390/su10020403 | en_US |
dc.subject | Big data | en_US |
dc.subject | Information updating | en_US |
dc.subject | Supply chain management | en_US |
dc.subject | Sustainable investment | en_US |
dc.title | Sustainable investment in a supply chain in the big data era : an information updating approach | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 1 | en_US |
dc.identifier.epage | 18 | en_US |
dc.identifier.volume | 10 | en_US |
dc.identifier.issue | 2 | en_US |
dc.identifier.doi | 10.3390/su10020403 | en_US |
dcterms.abstract | We are now living in the big data era, where firms can improve their decision makings by adopting big data technology to utilize mass information. To explore the effects of the big data technology, we build an analytical model to study the sustainable investment in a supply chain, consisting of one manufacturer and one retailer, by using Bayesian information updating approach. We derive the optimal sustainable investment level for the manufacturer and the optimal order quantity for the retailer. Comparing the results with and without the big data technology, we find that whether the manufacturer should make more sustainable investment when the retailer adopts the big data technology depends on the service level at the retailer side. Interestingly, it is not always optimal for the retailer to adopt the big data technology. We identify the conditions under which the manufacturer and retailer are better off with the big data technology. In addition, we investigate the impact of the number of observations regarding the market information and find that the optimal decisions and profits increase in the number of the observations, if and only if the service level is low. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Sustainability, Feb. 2018, v. 10, no. 2, 403 | - |
dcterms.isPartOf | Sustainability | - |
dcterms.issued | 2018 | - |
dc.identifier.isi | WOS:000425943100126 | - |
dc.identifier.scopus | 2-s2.0-85041453580 | - |
dc.identifier.eissn | 2071-1050 | en_US |
dc.identifier.artn | 403 | en_US |
dc.description.validate | 201808 bcrc | en_US |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_IR/PIRA | en_US |
dc.description.pubStatus | Published | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Cheng_Information_Updating_Approach.pdf | 1.16 MB | Adobe PDF | View/Open |
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