Service

Forecasting demand for pickups per hour in New York City for Uber

Application Area: 

Project Details

Term: 

2019

Students: 

Aniket Jain, Rachit Nagalia, Nakul Singhal, Ayush Anand, Priyakansha Paul, Prakhar Megotia

University: 

ISB

Presentation: 

Report: 

Uber is a ride-hailing company which was founded in San Francisco, California. Since its inception, it has expanded into multiple other businesses like ride sharing, food delivery etc and according to estimates, Uber has close to 100 million customers and operations in as many as 800 metropolitan areas. Given its ever-expanding scale, Uber continuously manages the gap between supply and demand through surge pricing, incentivising drivers and charging riders. There has, however, been a lot of backlash as surge pricing has gone above 20x at times.

Forecasting AsiaYo’s One Month Ahead Daily Room Occupancy in Different Cities for Supply Preparation

Application Area: 

Project Details

Term: 

Fall 2018

Students: 

Sz Wei Wu (Sandy), Cheng Che Liao (John), Min Sheng Wu (Akira), Kai Wei Pai (Kelvin)

University: 

NTHU

Presentation: 

Report: 

VIDEO

In this project, we collaborate with AsiaYo, an online B&B booking platform company headquartered in Taiwan, to work together on solving their business problem by using forecasting methods. One challenge facing AsiaYo is the revenue lost when they are lack of available rooms on holidays or special peak periods. Considering the enterprise level and resource, we find that it will be more affordable and understandable to focus our solution of this business problem on certain popular areas.

Predicting PicCollage users’ first purchase for targeted promotions

Application Area: 

Project Details

Term: 

Fall 2017

Students: 

Reggie Escobar . Eduardo Salazar Uni Ang . Lynn Pan

University: 

NTHU

Presentation: 

Report: 

PicCollage is an app to create amazing photo collages with custom stickers, fonts, background that makes creating collages a creative experience. It’s biggest revenue streams comes from In-app purchase where users could pay to remove watermark, add custom stickers, and backgrounds. Also the have popup ads; but because ads strategy is implemented different for Android and IOS users in this project the model is not using features extracted from ads behavior and the scope of the model proposed is directly extracted from the behavior when users create their first collage.

Identifying bookings with a high-risk of host rejection to improve customer service and customer satisfaction

Application Area: 

Project Details

Term: 

Fall 2017

Students: 

Arturo Heyner Cano Bejar, Tonny Kuo, Nick Danks, Kellan Nguyen

University: 

NTHU

Presentation: 

Report: 

AsiaYo! operates in a highly competitive industry serving as intermediary and agent between accommodation providers (hosts) and accommodation seekers (guests). High customer service is a critical business goal for AsiaYo!. Rejection of bookings by hosts can cause customer dissatisfaction and potentially loss of customers. Currently, AsiaYo! experiences a host rejection rate of 15% of orders. Rejection of a booking by the host triggers a reaction from the AsiaYo!

Forecasting the number of daily issues on GitHub repositories

Application Area: 

Project Details

Term: 

Fall 2016

Students: 

Aditya Utama Wijaya, Wen Lee, Cindy Soh, Renaud Jollet De Lorenzo, V K Sanjeed

University: 

NTHU

Presentation: 

Report: 

More business and government organizations developing IT solutions now use open-source repositories because of their reliability and rapid development. The bedrock of an open-source project is the community that uses, maintains, and creates new applications from it. This is because the more people who can see and test the code, the more likely any flaws will be caught and fixed quickly. Therefore, it becomes crucial for the foundation hosting the repository, to manage the massive number of issues submitted by users on a daily basis.

Forecasting Daily Number of User Problem Reports of Junyi Academy for Efficient Staff Allocation

Application Area: 

Project Details

Term: 

Fall 2016

Students: 

Chia Li Chien, Sherry Wu, Elisa Wang, Emily Wu

University: 

NTHU

Presentation: 

Report: 

Introduction of Our Client: Junyi Academy In this project, our client is Junyi Academy, a platform offering online learning resources for all ages. It provides practice exercises, instructional videos, and a personalized learning dashboard that empower learners to study at their own pace in and outside of the classroom. With high utilization ratio of the practice exercises, Junyi receives problems reported by users, which are called “user problem reports”. All the reports will be checked and then be distributed to the responsible team by operation team.

Forecasting restaurant sales using data from iChef, weather forecasts, and holiday information

Application Area: 

Project Details

Term: 

Fall 2016

Students: 

Nicholas Danks, Isaac Martinez, Mahsa Ashouri, Paul Rivera

University: 

NTHU

Presentation: 

Report: 

One of the largest challenges facing small and medium restaurants is that of competing against big chains with better information infrastructure – an advantage that allows the big chains to plan resource allocation more precisely based on demand and other factors. iChef provides this platform for small restaurants “making enterprise level technologies affordable and understandable for small restaurants”.

Forecasting the daily number of customers in each restaurant

Application Area: 

Project Details

Term: 

Fall 2016

Students: 

Edison Lee, Celia Chen, Sehyeon Jeong, Guan-Jie Chen, Web Yuan

University: 

NTHU

Presentation: 

Report: 

Business Problem

We are going to let manager of each restaurant know how busy they will be tomorrow by this business forecasting. The forecasted value would be used as a mental preparation of manager.

Data

Pages

Subscribe to Service