Maritime Commerce in Greater Philadelphia: Assessing Industry Trends and Growth Opportunities for Delaware River Ports

Maritime Commerce in Greater Philadelphia: Assessing Industry Trends and Growth Opportunities for Delaware River Ports is an evaluation of existing port conditions along the Delaware River and market-driven opportunities for expansion. The report includes an economic impact analysis, Delaware River port descriptions, global trends, and recommended strategies for ports growth. Key findings include:Region-wide port activity generates $69 million in tax revenues for state governments across Greater Philadelphia and more than$11 million in Philadelphia Wage Tax revenues.Each on-site port job supports two jobs from port activity and employee spending. Total regional port-related employment is 12,000+ jobs.Delaware River ports import nearly 1/2 of the nation's cocoa beans, almost 1/3 of the bananas, and a 1/4 of all fruit and nuts.Growing maritime commerce in Greater Philadelphia will require collaboration among Delaware River ports to leverage existing strengths and strategically invest in regional infrastructure improvements

COMPETITIVE STORE CLOSING DURING AN ECONOMIC DOWNTURN: A MATHEMATICAL PROGRAMMING APPROACH

A game theoretic mixed integer program model is introduced to determine optimal store closing decisions in a competitive market. The model considers the case of two rival firms seeking to downsize operations in a region. Both firms are looking to reduce operating costs by closing a number of stores while minimizing demand lost to its rival. We assume a competitive game and apply the model is to find the equilibrium store closing decisions. The model is first applied to a competitive environment for a single period and then incorporated into a solution procedure for a multi period game. The model facilitates the analysis of different strategies that can be used by a retail chain to maximize revenue in depressed market conditions. We find that the profitability is not always the most important factor to consider when determining the number and locations of stores to be closed and that an increase in demand variance will increase the likelihood that an unprofitable store will be kept open for an extended period of time. Our results further indicate that, depending on individual store characteristics it may be optimal to close a profitable store. Our results provide guidelines for developing effective strategies to systematically reduce the number of stores so that net revenue is maximized while competitive pressure is exerted on rival stores

The Impact of Information Technology(IT) in Trade Facilitation on Small and Medium Enterprises (SMEs) in Sri Lanka

This paper examine the extent of automation of trade facilitation in Sri Lanka and to assess the impact of automation on SMEs in the country.Impace of Information Techonology, SMEs, Sri Lanka

Spatio-temporal Modelling of Accessibility to Train Stations for Park and Ride (PnR) Users

Accessibility has been of critical importance to physical planning over the past 60 years. This study mainly focuses a spatial methodology framework to understand measure and model the Park and Ride (PnR) users’ accessibility to train stations, specifically including the characteristics of catchment areas, directional accessibility to train stations, spatial modelling of train stations’ catchment areas, and spatio-temporal modelling of accessibility to train stations

Assessing transport accessibility for healthcare facility reconfiguration using GIS and multilevel modelling

Transport accessibility to healthcare facilities is a major issue in the United Kingdom, as recently demonstrated by the shift away from providing healthcare in acute hospitals to care closer to home . Common measures of accessibility focus on the creation of distance or travel time contours around a destination and devote less attention to individual differences such as user perceptions, their transport usage, and area-wide factors including income deprivation, safety and security. Failure to account for such factors may result in imperfect decision making in terms of healthcare relocation and reconfiguration. This thesis therefore aims to develop a user-based accessibility model by focusing on both individual socio-economic (e.g. age, gender, access to transport modes) and area-wide characteristics (e.g. income deprivation, public transport provision, safety and security). In order to identify important factors that affect accessibility and to develop the user-based accessibility model, two revealed preference questionnaire surveys were undertaken at Loughborough and Hinckley. The purpose of the first questionnaire was to understand underlying factors affecting accessibility to a healthcare facility. The results revealed that both individual and area-wide factors affect transport accessibility to a healthcare facility. The purpose of the second questionnaire was conducted to capture data relating to users perception of accessibility and their socio-economic factors so as to develop a user-perception based accessibility model. Network-based travel time and travel distance as well as public transport provision data from a respondent home to a healthcare facility were generated using a GIS technique. Individual-level questionnaire data were then integrated with the other secondary datasets (e.g. Census, Index of Multiple Deprivation, Accidents) using postcodes of survey respondents. Both single-level and multilevel mixed-effects linear regression models were employed to develop a relationship between user-perceptions relating to accessibility and the factors influencing accessibility. Multilevel models that can control data from the two levels (i.e. individuals nested within local areas) provided better goodness-of-fit statistics compared with those of single-level regression models. The results indicate that travel distance by car, number of available direct bus services, age, and destination choices affect user-perceptions of accessibility to a healthcare facility. For instance, if travel distance by car increases by one mile then the perception of accessibility to a healthcare facility decreases by four units (on a scale of 0-100). Surprisingly, many area-wide factors such as security and safety, income deprivation were found to be statistically insignificant. In order to see which healthcare facility is more accessible, calibrated multilevel models along with number of people within the catchment area were then employed to predict the overall accessibility score related to a healthcare facility. This is important for policy makers in healthcare facility relocation and reconfiguration with respect to user perception of transport accessibility. Also it would be valuable to organisations that need to make decisions based on their users perceptions who are the real decision makers as to whether to use a facility or not

Examination of Regional Transit Service Under Contracting: A Case Study in the Greater New Orleans Region, Research Report 10-09

Many local governments and transit agencies in the United States face financial difficulties in providing adequate public transit service in individual systems, and in providing sufficient regional coordination to accommodate transit trips involving at least one transfer between systems. These difficulties can be attributed to the recent economic downturn, continuing withdrawal of the state and federal funds that help support local transit service, a decline in local funding for transit service in inner cities due to ongoing suburbanization, and a distribution of resources that responds to geographic equity without addressing service needs. This study examines two main research questions: (1) the effect of a “delegated management” contract on efficiency and effectiveness within a single transit system, and (2) the effects of a single private firm—contracted separately by more than one agency in the same region—on regional coordination, exploring the case in Greater New Orleans. The current situation in New Orleans exhibits two unique transit service conditions. First, New Orleans Regional Transit Authority (RTA) executed a “delegated management” contract with a multinational private firm, outsourcing more functions (e.g., management, planning, funding) to the contractor than has been typical in the U.S. Second, as the same contractor has also been contracted by another transit agency in an adjacent jurisdiction—Jefferson Transit (JeT), this firm may potentially have economic incentives to improve regional coordination, in order to increase the productivity and effectiveness of its own transit service provision. Although the limited amount of available operation and financial data has prevented us from drawing more definitive conclusions, the findings of this multifaceted study should provide valuable information on a transit service contracting approach new to the U.S.: delegated management. This study also identified a coherent set of indices with which to evaluate the regional coordination of transit service, the present status of coordination among U.S. transit agencies, and barriers that need to be resolved for regional transit coordination to be successful

Data-driven Methodologies and Applications in Urban Mobility

The world is urbanizing at an unprecedented rate where urbanization goes from 39% in 1980 to 58% in 2019 (World Bank, 2019). This poses more and more transportation demand and pressure on the already at or over-capacity old transport infrastructure, especially in urban areas. Along the same timeline, more data generated as a byproduct of daily activity are being collected via the advancement of the internet of things, and computers are getting more and more powerful. These are shown by the statistics such as 90% of the world’s data is generated within the last two years and IBM’s computer is now processing at the speed of 120,000 GPS points per second. Thus, this dissertation discusses the challenges and opportunities arising from the growing demand for urban mobility, particularly in cities with outdated infrastructure, and how to capitalize on the unprecedented growth in data in solving these problems by ways of data-driven transportation-specific methodologies. The dissertation identifies three primary challenges and/or opportunities, which are (1) optimally locating dynamic wireless charging to promote the adoption of electric vehicles, (2) predicting dynamic traffic state using an enormously large dataset of taxi trips, and (3) improving the ride-hailing system with carpooling, smart dispatching, and preemptive repositioning. The dissertation presents potential solutions/methodologies that have become available only recently thanks to the extraordinary growth of data and computers with explosive power, and these methodologies are (1) bi-level optimization planning frameworks for locating dynamic wireless charging facilities, (2) Traffic Graph Convolutional Network for dynamic urban traffic state estimation, and (3) Graph Matching and Reinforcement Learning for the operation and management of mixed autonomous electric taxi fleets. These methodologies are then carefully calibrated, methodically scrutinized under various performance metrics and procedures, and validated with previous research and ground truth data, which is gathered directly from the real world. In order to bridge the gap between scientific discoveries and practical applications, the three methodologies are applied to the case study of (1) Montgomery County, MD, (2) the City of New York, and (3) the City of Chicago and from which, real-world implementation are suggested. This dissertation’s contribution via the provided methodologies, along with the continual increase in data, have the potential to significantly benefit urban mobility and work toward a sustainable transportation system