This area will focus on logistics, supply chain management and intermodal transportation for freight.
Activities will be centered on establishing the Buffalo-Niagara region as a logistics hub, by leveraging the region’s transportation/logistics assets, and by strengthening ties with Canada. To do this, the institute will partner with the railroad and trucking industry and logistics companies.
Freight transportation, which is the one of the most important components of the transportation system, will significantly affect the overall performance and recovery processes of systems under multiple hazard situations. On one hand, the commercial vehicle flows compete with passenger car flows for the capacities of road networks, and thus increase the level of congestion. On the other hand, effective freight movement is the key to the success of any transportation risk management or recovery systems, particularly in the multiple hazard situations involving large-scale disasters. In this context, this task is intended to integrate a freight travel demand forecasting component into the transportation risk-management research under multiple hazard situations, with an emphasis on commercial vehicle movements. With the addition of the freight-travel demand model, the improved framework of risk management will have the capacity to assess the impacts of multiple hazards on both passenger and freight transportation, and thus result in a complete risk assessment and management system. The focus of this task will be on how to model freight travel demand under multiple hazard situations, including earthquakes, inclement weather, major accidents on highway bridges and critical links, emergency evacuations, and combinations consisting of two or more of such hazards.
The economic vitality of the “Golden Horseshoe,” a densely populated and industrialized region which encompasses Ontario and parts of New York State including the Buffalo-Niagara Region, is heavily dependent upon the ability to move goods freely and efficiently across the Canadian-US border. This highlights the critical importance of the Niagara Frontier borders, which in fact is one of the busiest international crossings in the United States. In recent years, and as a result of the continued increase in travel demand across the border coupled with the need for tighter security and inspection procedures after September 11, border crossing delay has become a critical problem with tremendous economic and social costs. The purpose of this project is to develop a prototype system for border crossing traffic management system, whose ultimate goal would be to direct the Niagara Frontier border-destined traffic in an optimal fashion that would maximize system efficiency and minimize the negative impacts of border crossing delays. The proposed prototype consists of two components. The first component is a predictive tool to forecast the short-term border crossing travel times and delays at three key border crossings in the region (i.e. the Peace Bridge, the Rainbow Bridge, and the Lewiston-Queenston Bridge). The second component is a Decision Support System (DSS) for optimally routing border-destined traffic based on the predicted border crossing travel times derived from the predictive tool. Data for building the predictive model will be obtained from the Niagara International Transportation Technology Coalition (NITTEC), a coalition of fourteen different agencies in Western New York and Southern Ontario region that employs the latest Intelligent Transportation Systems (ITS) technologies to monitor and manage regional traffic.
The increasing attention and popularity gained by social media and social networking services over the past several years have brought new opportunities for e-commerce, known as "social commerce". This project, funded by IBM, looks to model order fulfillment with local brick-and-mortar stores for traditional retailers and further reduce its operation and transportation costs by leveraging "Social Commerce", enhanced by Big Data in social networks. In pursuit of this goal, this research consists of two major components. First, this study will develop a mathematic formulation to model order fulfillment process with Same Day Delivery. Second, the project plans to build an ensemble simulation model to test the concept of a new strategy, which combines "Big Data" in social network to enhance order fulfillment process. The core idea is to allow customers' online orders to be delivered by a network of "Social Transportation", which consists of friends' daily travel routines (trip chains), potentially intercepting packages at local stores and the target customer's locations at home, work, gym, etc. The proposed project will serve as a theoretic foundation to leverage social networks to improve online order fulfillment with same day delivery from local stores.
The new trends in supply chain and logistics have led to a new geography of warehousing in urban areas. This study is among the first to systematically and empirically explore the geography of warehousing, using the New York metropolitan region, one of the largest cities and the busiest freight hubs in the world, as the study area. Various spatial analyses are conducted to explore the spatial distribution patterns of the warehousing establishments. The empirical results show three major geographic characteristics of the warehouses, including: (1) clustered establishments to take advantage of the economies of scale; (2) concentration of establishments in the main market of freight activities and end customers; and (3) proximity to transportation networks being a significant factor affecting location decisions. Several policy implications are also suggested for warehousing and logistics oriented planning and decision making.