Thesis supervisor: Miklós Pakurár
Location of studies (in Hungarian): University of Debrecen, Faculty of Economics and Business Abbreviation of location of studies: UD
Description of the research topic:
Information sharing means the distribution of critical and proprietary information to supply chain partners. The main types of information that can be shared within a supply chain include inventory, customer demand, order information, operations plan, customer requirement, or financial information. The supply chain members can reap benefits in terms of reductions in inventory levels and cost savings from forming partnerships with one another. Big data is a term used to describe the massive volume of both structured and unstructured data that is too large that it is difficult to process using conventional database and software techniques. Big data and predictive analytics help to improve customer service and reduce some costs such as warehouse and operation costs, as well as delivery time. The goal of the research is to understand how to build the information sharing system between members in the depth in complex real supply chain, which can help companies to maximize their profit in overall supply chain.
Required language skills: english Recommended language skills (in Hungarian): english Number of students who can be accepted: 1
Deadline for application: 2019-03-15
2024. IV. 17. ODT ülés Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).
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