e-commerce

This is the dataset for the project "Incorporating Infrastructure and Vehicle Technology Requirements, Changes in Demand, and Decarbonization Policies Considerations into Freight Planning."

The tasks of this project employ different combinations of methods to enable the prediction of e-commerce shopping behaviors for each metropolitan statistical areas of interest at the individual level as well as the quantitative calculation of externalities. Methods used include Weighted Multinomial Logit models, time series forecasting, and Monte Carlo (MC) simulations.

These datasets contain the raw data collected from the two separate but related surveys to explore the potential of automated parcel lockers as an alternative for residence deliveries.

This project proposes to improve vehicle utilization and energy efficiency by modeling and evaluating the innovative shared mobility services for freight, with a specific focus on on-demand food delivery. Overall, the shared mobility service has great potential to reduce freight transportation VMT cost and emission. With well-designed delivery policy, the on-demand food delivery can mitigate traffic in the urban city and bring a greener transportation system.

In this paper, focusing on meal delivery, the researchers proposed an eco-friendly on-demand meal delivery (ODMD) system to maximize the utilities of electric vehicles (EVs) to mitigate greenhouse gas (GHG) emissions and maintain low operational cost and delay cost.

This study investigates the potential ramifications of e-commerce on shopping behaviors, travel, and residential deliveries by the year 2050. The study underscores the significance of contemplating the implementation of clean energy fleets and effective transportation strategies to mitigate the negative externalities related to shopping activities.

This study unravels underlying shopping behaviors–both in-store and online–using the 2016 American Time Use Survey (ATUS) data, and develops an econometric behavioral model to understand the factors that affect shopping decisions.

This research examines the factors that can help explain the differences between users and non-users of online shopping in the U.S.A. during April and May 2020 to help understand the barriers to home-based shopping accessibility.

This study leverages the 2018 California Panel Study of Emerging Transportation Trends to analyze the factors that influence consumer decisions to purchase different merchandise online.