| Studiju veids |
maģistra akadēmiskās studijas |
| Studiju programmas nosaukums |
Loģistikas sistēmu un piegādes ķēdes vadība |
| Nosaukums |
Lielu datu analīze un lietojumi loģistikas sistēmu un piegādes |
| Nosaukums angļu valodā |
Big Data Analysis and Applications in Logistics Systems and Supply Chain |
| Struktūrvienība |
12100 Informācijas tehnoloģijas institūts |
| Darba vadītājs |
Andrejs Romānovs |
| Recenzents |
Artis Teilāns |
| Anotācija |
The thesis describes the study on Big Data and its applications to overcome the challenges faced in Supply Chain and Logistics. The initial study focusses on knowing the Big Data and technological capabilities. Further study on applications in different fields of Supply Chains like Manufacturing, Procurement, Warehouse and Logistics transportation. A depth research is conducted on consumer behaviour in E-Commerce and the importance of predictive analytics. A case study supporting the predictive analytics is explained. Further research is conducted on transportation and logistics and it is found that last mile delivery is one of the major concept in parcel delivery and with the development of B2C business there is a huge demand in last mile delivery. Customers preference for instant delivery and same day shipping is also one of the main reasons to focus on last mile. The Research examines the current trends in last mile delivery. And Big Data applications for route optimization, crowd-sourced delivery, and other feasible solutions to optimize last mile. Finally, a case study on UPS data analytics and the challenges to increase the efficiency using Big Data is discussed. |
| Atslēgas vārdi |
Big Data, Last Mile, E-Commerce, Consumer Behaviour, Data analytics, Supply Chain. |
| Atslēgas vārdi angļu valodā |
Big Data, Last Mile, E-Commerce, Consumer Behaviour, Data analytics, Supply Chain. |
| Valoda |
eng |
| Gads |
2018 |
| Darba augšupielādes datums un laiks |
06.06.2018 14:53:31 |
