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چاپ مقاله ISI

DR. Majid Aghlmand

دانلود پایان نامه مدیریت کسب و کار و امور شهری pdf

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عنوان فارسی:
ظرفیت مدیریت و مدیریت آب شهری یکپارچه در بوستون، ماساچوست: پیامدهایی برای ایجاد انعطاف پذیری آب و هوا

عنوان انگلیسی:


Integrated Urban Water Management and Governance Capacity in Boston, Massachusetts: Implications for Building Climate Resilience

Abstract
For the City of Boston, climate change impacts are both a current reality and a future consideration. Leaders are working to address environmental hazards such as extreme heat, stormwater flooding, and coastal and riverine flooding, which represent the City’s climate vulnerabilities and urban water challenges. Integrated urban water management (IUWM) is a model that upholds sustainability goals while also increasing adaptive capacity for climate resiliency, though implementation tends be difficult. Because water governance is essential to IUWM, this inquiry assesses Boston’s governance capacity related to its water challenges by conducting interviews with local water managers via guidance from City Blueprint® Approach. Results indicate opportunities for organizational partnerships to realize a collaborative advantage, to enhance cross-stakeholder learning, and to promote redundancy in governance frameworks. Recommendations to advance these opportunities encourage an IUWM approach in Boston to increase the City’s climate resilience in light of urban water challenges.

 

عنوان فارسی:
مقالاتی در مورد مدیریت درآمد در تحرک شهری

عنوان انگلیسی:


Essays on Revenue Management in Urban Mobility

Abstract
The essays in this dissertation lie at the intersection of revenue management, urban mobility, and technology. Some of the most well-studied problems in operations management and operations research have been inspired by the transportation sector. For instance, the traveling salesman problem, the vehicle routing problem, freight logistics, airline fleet planning, port operations, and rail scheduling are set in the transportation industry. In this dissertation, we restrict our analysis to urban mobility, which focuses on transportation in metropolitan cities. Urban mobility has evolved dramatically over the past decade due to advances in technology, in particular, the mobile phone. Bike-sharing, ride-sharing, and vehicle sharing are possible today because of the growth and popularity of mobile phones. Because of this growth, users are able to access train and bus schedules in real-time, pay fares, and instantaneously reserve and check-out shared cars, bikes, electric scooters, and other types of shared vehicles. While this accessibility provides users with more flexibility, the systems are also increasingly difficult to operate and manage. One way to address this operational complexity involves using tools and methods from revenue management. More generally, using price and discounts as levers to shape customer behavior in a way that improves the system's service level, revenue, customer satisfaction, and other key performance metrics.
This dissertation is made up of four essays across three chapters that address questions in operating systems in urban mobility, and we use techniques from revenue management to study how these systems can operate more effectively.
In Chapter 1, we study free-ride policies as a mechanism to incentivize users of a "dockless" or "free-floating" electric vehicle sharing system (EVSS) to park vehicles at charging stations in order to maintain a charged fleet. A balanced system has a fleet that is adequately charged and evenly dispersed throughout the city. If left to unfold naturally, the system would fall out of balance, and revenue and customer experience might suffer. Most sharing systems use manual repositioning to achieve this balance, but we consider pricing incentives as an alternative method. We develop an infinite horizon dynamic program to analyze free-ride policies. We focus on an EVSS that offers free rides to customers if they return vehicles to charging stations. We build on this initial formulation to construct a mixed-integer program that outputs intuitive, battery-threshold rules for when to offer free rides. We also extend the model to accommodate more general discount-based policies. In a discrete-event simulation model using real data from an EVSS, we compare the performance of this simple policy against other sophisticated policies, including the commonly used fine-based policy, which fines users for street-parking vehicles with low battery. We first find that the simple threshold-based policy performs close to a more sophisticated, black-box policy in terms of revenue. We also discover that the free-ride policies generate customer utilities that are ten times higher than fine-based policies, but also generate less revenue. However, free-ride policies can be less costly to implement since they rely on manual repositioning up to 65–75% less than the benchmarking policies. Our simulation reveals this three-dimensional trade-off between customer satisfaction, revenue, and operational complexity. Our results are robust under many demand patterns and under a variety of network settings.

 

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