The present paper aims to analyse the main barriers and drivers that obstacle and push the adoption of an eBusiness standard, such as eBIZ, and IoT technology, such as RFId, within the fashion industry. This purpose represents the first step of the European project “eBIZ 4.0—Enhancing textile/clothing sector by eBIZ and RFIds technologies adoption”, aiming to promote the integration between RFId technology and eBIZ standard for improving data interoperability among companies operating along the fashion supply chain. The tool used for this kind of analysis has been an online survey dispatched to the mailing list of all the project partners belong to different European Community countries and involving both software houses and fashion companies. The survey results have been crossed with the external variables that characterize the analysed companies, in order to classify the evidences related to one or another cluster of companies similar in terms of external variables such as dimension, headquarter location, industry segment. © Springer Nature Switzerland AG 2019.
eBusiness standards and IoT technologies adoption in the fashion industry: Preliminary results of an empirical research
De Sabbata, P.;Ciaccio, G.;Brutti, A.
2019-01-01
Abstract
The present paper aims to analyse the main barriers and drivers that obstacle and push the adoption of an eBusiness standard, such as eBIZ, and IoT technology, such as RFId, within the fashion industry. This purpose represents the first step of the European project “eBIZ 4.0—Enhancing textile/clothing sector by eBIZ and RFIds technologies adoption”, aiming to promote the integration between RFId technology and eBIZ standard for improving data interoperability among companies operating along the fashion supply chain. The tool used for this kind of analysis has been an online survey dispatched to the mailing list of all the project partners belong to different European Community countries and involving both software houses and fashion companies. The survey results have been crossed with the external variables that characterize the analysed companies, in order to classify the evidences related to one or another cluster of companies similar in terms of external variables such as dimension, headquarter location, industry segment. © Springer Nature Switzerland AG 2019.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
