Application of intervention analysis to evaluate the impacts of special events on freeways

In China in particular, large, planned special events (e.g., the Olympic Games, etc.) are viewed as great opportunities for economic development. Large numbers of visitors from other countries and provinces may be expected to attend such events, bringing in significant tourism dollars. However, as a direct result of such events, the transportation system is likely to face great challenges as travel demand increases beyond its original design capacity. Special events in central business districts (CBD) in particular will further exacerbate traffic congestion on surrounding freeway segments near event locations. To manage the transportation system, it is necessary to plan and prepare for such special events, which requires prediction of traffic conditions during the events. This dissertation presents a set of novel prototype models to forecast traffic volumes along freeway segments during special events. Almost all research to date has focused solely on traffic management techniques under special event conditions. These studies, at most, provided a qualitative analysis and there was a lack of an easy-to-implement method for quantitative analyses. This dissertation presents a systematic approach, based separately on univariate time series model with intervention analysis and multivariate time series model with intervention analysis for forecasting traffic volumes on freeway segments near an event location. A case study was carried out, which involved analyzing and modelling the historical time series data collected from loop-detector traffic monitoring stations on the Second and Third Ring Roads near Beijing Workers Stadium. The proposed time series models, with expected intervention, are found to provide reasonably accurate forecasts of traffic pattern changes efficiently. They may be used to support transportation planning and management for special events.

Soft power as the new norm: How the Chinese-Russian strategic partnership (soft) balances American hegemony in an era of unipolarity

This study explores how great powers not allied with the United States formulate their grand strategies in a unipolar international system. Specifically, it analyzes the strategies China and Russia have developed to deal with U.S. hegemony by examining how Moscow and Beijing have responded to American intervention in Central Asia. The study argues that China and Russia have adopted a soft balancing strategy of to indirectly balance the United States at the regional level. This strategy uses normative capabilities such as soft power, alternative institutions and regionalization to offset the overwhelming material hardware of the hegemon. The theoretical and methodological approach of this dissertation is neoclassical realism. Chinese and Russian balancing efforts against the United States are based on their domestic dynamics as well as systemic constraints. Neoclassical realism provides a bridge between the internal characteristics of states and the environment which those states are situated. Because China and Russia do not have the hardware (military or economic power) to directly challenge the United States, they must resort to their software (soft power and norms) to indirectly counter American preferences and set the agenda to obtain their own interests. Neoclassical realism maintains that soft power is an extension of hard power and a reflection of the internal makeup of states. The dissertation uses the heuristic case study method to demonstrate the efficacy of soft balancing. Such case studies help to facilitate theory construction and are not necessarily the demonstrable final say on how states behave under given contexts. Nevertheless, it finds that China and Russia have increased their soft power to counterbalance the United States in certain regions of the world, Central Asia in particular. The conclusion explains how soft balancing can be integrated into the overall balance-of-power framework to explain Chinese and Russian responses to U.S. hegemony. It also suggests that an analysis of norms and soft power should be integrated into the study of grand strategy, including both foreign policy and military doctrine.

Book Review: Tourism in China: Exotic Land Revealed

There is no better way to lean about tourism in China than from renowned expert in the field. Alan Lew. PhD. and professor at Northern Arizona University, Lawrence Yu, Ph.D. and associate professor in the Department of Tourism and Hospitality Management at George Washington University. John Ap, Ph.D. and associate professor in tourism management at Hong Kong Polytechnic University and Zhang Guangrui, director of the Tourism Research Centre, Chinese Academy of Social Sciences in Beijing, China, have contributed to and edited a collection of writings detailing the development of tourism in this fascinating and exotic land.

Application of Intervention Analysis to Evaluate the Impacts of Special Events on Freeways

In China in particular, large, planned special events (e.g., the Olympic Games, etc.) are viewed as great opportunities for economic development. Large numbers of visitors from other countries and provinces may be expected to attend such events, bringing in significant tourism dollars. However, as a direct result of such events, the transportation system is likely to face great challenges as travel demand increases beyond its original design capacity. Special events in central business districts (CBD) in particular will further exacerbate traffic congestion on surrounding freeway segments near event locations. To manage the transportation system, it is necessary to plan and prepare for such special events, which requires prediction of traffic conditions during the events. This dissertation presents a set of novel prototype models to forecast traffic volumes along freeway segments during special events. Almost all research to date has focused solely on traffic management techniques under special event conditions. These studies, at most, provided a qualitative analysis and there was a lack of an easy-to-implement method for quantitative analyses. This dissertation presents a systematic approach, based separately on univariate time series model with intervention analysis and multivariate time series model with intervention analysis for forecasting traffic volumes on freeway segments near an event location. A case study was carried out, which involved analyzing and modelling the historical time series data collected from loop-detector traffic monitoring stations on the Second and Third Ring Roads near Beijing Workers Stadium. The proposed time series models, with expected intervention, are found to provide reasonably accurate forecasts of traffic pattern changes efficiently. They may be used to support transportation planning and management for special events.