Twitter Enabled Supplier Status Assessment

• Main Authors: Maria Belen Vargas Saballos, 凡莉琳
• Other Authors: Chuan-Jun Su
• Format: Others
• Language: en_US
• Online Access: http://ndltd.ncl.edu.tw/handle/46131201185924728739

碩士 === 元智大學 === 工業工程與管理學系 === 102 === The supplier selection has always been one of the most crucial tasks in the procurement process of the supply Chain Management (SCM). Any purchasing is only as good as the suppliers that it buys from. The adequate selection of suppliers makes a strategic difference to an organization’s ability to reduce cost and improve the quality of its product. Over the years the market has become globalized and organizations that once focused on domestic sourcing later sought from suppliers around the world due to the motives ranging from cost to quality. However, the global sourcing makes the process of supplier selection riskier and more complex. In order to effectively select an international supplier, risk and uncertainty regarding the potential candidates have become a vital criteria within the supplier selection process. The data required for confronting the criteria needs to be specific and up-to-date; however, it is difficult if not impossible for organizations to acquire this information from traditional data sources such as MIS (Management Information System) and ERP (Enterprise Resource Planning) due to the limitations these sources offer. Lacking sufficient information has made their decision process in the global supplier selection more challenging and time consuming. Without reliable data sources regarding suppliers’ background and current status an optimal decision cannot be made Nowadays, data is more available than ever before, we have entered the Big Data era with the prominence of social networks such as Twitter, Facebook, Linkedin, which furnish both as a source of news and a source of views. We now have access to global insights and knowledge regarding international suppliers. In this research, we propose a Twitter Enabled Supplier Status Assessment (TESSA) tool that can assist companies in their global supplier selection process. TESSA firstly retrieves a target supplier’s related information from the most popular microblog Twitter and then obtains potential risk and uncertainty regarding the supplier through text mining. The discovered risks and uncertainties are classified into socio-political, financial, economic and environmental categories for companies making better decision on their global supplier selection process.