Forecast Monthly Demand of Automobiles to increase sales for automotive company

Application Area: 

Project Details

Term: 

Fall 2014

Students: 

Fang-I Liao, Tzu Yi Lin, Po-Wei Huang , Louie Lu

University: 

NTHU

Presentation: 

Report: 

Our client is an automotive corporation (e.g. Suzuki) who sell automobiles and motorcycles in Taiwan. Our forecasting goal is to forecast the demand of automobile in 2015 of four of Taiwan’s largest cities: Taipei, New Taipei, Taichung, and Kaohsiung. The forecast results will be used to set promotional plans among regions and seasons, and measure amount of automobile to import in 2015. Potential business benefits include reducing costs (inventory costs and advertisement at lower sales seasons), and improving marketing strategies (targeting the right seasons).

Forecasting Tourist Volume in Northeast and Yilan Coast National Scenic Area to better allocate Human Resources

Application Area: 

Project Details

Term: 

Fall 2014

Students: 

AnYu Luo, ChienMin Kao, Xi Wang, Daisin Li

University: 

NTHU

Presentation: 

Report: 

Our business goal is try to better allocate human resource in Northeast and Yilan Coast National Scenic Area Due to the tourism industry booming in Taiwan the past five years, the domestic and foreign tourists are increasing. we select ocean park, hiking trail, rock climbing area, diving space and camp site. These five locations are directly under different units. Try to organize the staffs between these five locations.

Forecasting demand for trailers for efficient use and customized service

Application Area: 

Project Details

Term: 

Fall 2014

Students: 

Yu-Ning Kao, Jou-yu Huang, Ting-Ju Wang, Chin Chang

University: 

NTHU

Presentation: 

Report: 

In this project, our data source is the stakeholders who are Jouyu’s family business. It is kind of transport industry. The business model is to transport customers’ excavators to the destination they require through the trailers whom the stakeholders own. However, since the stakeholders are used to manually record the trips that customers require, they predict the next demand only based on their experience. Without the assistant of technology, stakeholders are unable to anticipate the demand of trailers in the future accurately.

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