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請用此 Handle URI 來引用此文件: http://scholars.ntou.edu.tw/handle/123456789/25625
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dc.contributor.authorLin, Cheng-Shengen_US
dc.contributor.authorYen, Chun-Changen_US
dc.contributor.authorShyu, Chin-Shyangen_US
dc.contributor.authorTsao, Hsiao-Changen_US
dc.date.accessioned2025-05-27T08:55:53Z-
dc.date.available2025-05-27T08:55:53Z-
dc.date.issued2024/12/1-
dc.identifier.issn1607-9264-
dc.identifier.urihttp://scholars.ntou.edu.tw/handle/123456789/25625-
dc.description.abstractThe rise of vertical farms offers new opportunities for climate change and agricultural development. Vertical farms use greenhouses and AI technology applications to overcome the agricultural problems of climatic factors and labour shortages. It also leads to the problem of high electricity bills and other operating costs, which affects the operating efficiency. This study aims to analyse the operational efficiency and input-output resource allocation of vertical farms. This study uses a dynamic network DEA model to analyse the first-stage energy efficiency stage, second-stage operating efficiency and overall efficiency of the world's top 8 vertical farms from 2018 to 2022. The research results are as follows: 1. The first-stage input (solar power generation and water-saving equipment) is sufficient, and the intermediate output of the vertical farm (the higher the power generation, the greater the water saving) is prone to economies of scale, and the impact on the vertical farm in the first stage will be Brings positive operational efficiencies to the department. 2. The COVID-19 epidemic has had a significant positive impact on the power generation and energy saving efficiency of the first phase of vertical farms, which means that the energy input and output of vertical farms have been better distributed during the epidemic, and indirectly affected the second phase. stage operational efficiency as well as the overall operational efficiency of the vertical farm. 3. According to the slack variable analysis, in order for vertical farms to achieve the best overall operating efficiency, both input and output factors need to be reallocated and adjusted. Among them, operating costs (power costs) need to be reduced by 38.68%, which is the largest adjustment among all input factor resources. Vertical farms use modern, high-tech artificial intelligence to stabilise crop value supply chains and provide many other functional benefits. However, their operational efficiency is severely hampered by high electricity costs. Therefore, effectively reducing the electricity costs of vertical farm operations will be the key to their success or failure.en_US
dc.language.isoEnglishen_US
dc.publisherLIBRARY & INFORMATION CENTER, NAT DONG HWA UNIVen_US
dc.relation.ispartofJOURNAL OF INTERNET TECHNOLOGYen_US
dc.subjectVertical farmsen_US
dc.subjectDynamic network DEA modelen_US
dc.subjectArtificial intelligenceen_US
dc.titleAgriculture with Energy Conservation and AI Technology: Analysis of Operational Efficiency of Vertical Farmsen_US
dc.typejournal articleen_US
dc.identifier.doi10.70003/160792642024122507007-
dc.identifier.isiWOS:001387859200007-
dc.relation.journalvolume25en_US
dc.relation.journalissue7en_US
dc.relation.pages1023-1034en_US
dc.identifier.eissn2079-4029-
item.grantfulltextnone-
item.openairetypejournal article-
item.cerifentitytypePublications-
item.languageiso639-1English-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.fulltextno fulltext-
crisitem.author.deptGeneral Education Center-
crisitem.author.deptPhysical Education Office-
crisitem.author.deptNational Taiwan Ocean University,NTOU-
crisitem.author.parentorgNational Taiwan Ocean University,NTOU-
crisitem.author.parentorgGeneral Education Center-
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