Revenue Management Techniques Applied To The Parking Industry
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Revenue Management Techniques Applied To The Parking Industry
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Author : Daniel Rojas
language : en
Publisher:
Release Date : 2006
Revenue Management Techniques Applied To The Parking Industry written by Daniel Rojas and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.
ABSTRACT: The time spent searching for a parking space increases air pollution, driver frustration, and safety problems impacting among other issues, traffic congestion and as consequence the environment. In the United States, parking represents a $20 billion industry (National Parking Association, 2005), and research shows that a car is parked on average 90 percent of the time. To alleviate this problem, more parking facilities should be built or intelligent models to better utilize current facilities should be explored. In this thesis, a general methodology is proposed to provide solutions to the parking problem. First, stated preference data is used to study drivers' choice/behavior. Parking choices are modeled as functions of arrival time, parking price, age, income and gender. The estimated values show that choice is relatively inelastic with respect to distance and more elastic with respect to price. The data is used to estimate the price elasticity that induces drivers to change their behavior. Second, neural networks are used to predict space availability using data provided by a parking facility. The model is compared with traditional forecasting models used in revenue management. Results show that neural networks are an effective tool to predict parking demand and perform better than traditional forecasting models. Third, the price elasticity that induces drivers to change their choice or behavior is determined. Finally, taking as an input the forecasting results obtained from the neural network and the price elasticity, parking spaces are optimally allocated at different price levels to optimize facility utilization and increase revenue. This research considers a parking facility network consisting of multiple parking lots with two, three and four fare classes and utilizes revenue management techniques as a mean to maximize revenue and to stimulate and diversify demand. The output indicates the number of parking spaces that should be made available for early booking to ensure full utilization of the parking lot, while at the same time attempting to secure as many full price parking spaces to ensure maximization of revenue.
Revenue Management Made Easy For Midscale And Limited Service Hotels
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Author : Ira Vouk
language : en
Publisher: Ira Vouk
Release Date :
Revenue Management Made Easy For Midscale And Limited Service Hotels written by Ira Vouk and has been published by Ira Vouk this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Everything you need to know about Revenue Management practice in under 100 pages, in simple language, with clear and easy-to-understand examples. From the originator of the ARPAR performance index (#ARPAR). This books brings a fresh view on Revenue Management and describes the tools that are relevant and effective today. After you start applying these strategies – you’ll start noticing the difference in less than a month, guaranteed. It contains both theoretical knowledge (using simple and clear explanations) and practical advice (including specific steps and examples) on how to Revenue Manage your hotel and significantly grow your RevPAR and your bottom line. You’ll get insider tips, such as: how to properly implement dynamic pricing, how to look at your STR report to make sure your occupancy rates are balanced with your ADR, and the proper way to use overbooking to grow your revenue during periods of peak demand. Do this right and you’ll be able to achieve great results in no time. So whether you are a professional certified Revenue Manager, a GM looking to improve your hotel’s RevPAR or a student searching for additional knowledge on this discipline – this book will help you become more knowledgeable and more successful.
Essays On Revenue Management In Urban Mobility
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Author : Rajpal Bobby Singh Nyotta
language : en
Publisher:
Release Date : 2021
Essays On Revenue Management In Urban Mobility written by Rajpal Bobby Singh Nyotta and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
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. In the remaining chapters, we are motivated by the claim that 30% of metropolitan traffic is a result of individuals searching or "cruising" for parking (Shoup, 2017). It is theorized that this cruising behavior causes superfluous traffic congestion that can be assuaged and mitigated with more effective pricing polices. In particular, pricing policies that ensure there is at least one open spot available on each block at all times under regular demand. With this in mind, Chapters 2 and 3 examine how to develop dynamic pricing policies that both maximize revenue and address traffic congestion, with Chapter 2 focusing on estimating key parameters that feed into the pricing models and Chapter 3 focusing on developing the price optimization models. In order to develop such pricing policies, one needs to know the price and spatial elasticity of parking, where price elasticity is a measure of the change in demand in response to a price change and the spatial elasticity is a measure of how much money a customer would require to park a mile or a block away from their destination. Using data from our industry partner, a venture-backed technology company that develops a software-as-a-service (SaaS) platform to manage parking, permitting, and micro-mobility for municipalities and organizations throughout the world, we are able to empirically estimate both of these values in Chapter 2. In this chapter, the context is parking-specific and the estimates are unique to the data from our partner city. However, we believe that our approach and the estimates can be used across urban mobility applications, and beyond, as these elasticities are often assumed to be known or given in many classic revenue management problems. In Chapter 2.1, the first essay of Chapter 2, we estimate the price elasticity after a 20% price increase in a mid-sized U.S. city and find the average price elasticity of parking demand is between -3.42 and -1.57, which is higher than existing estimates (Lehner and Peer, 2019). One reason our study could be producing higher estimates is because, as far as we know, our work is the first to use transactions data from a mobile phone application for parking payments, which is more accurate and detailed than the data used in the existing literature. With our model, we can also measure how long it takes for customers to learn about and respond to the price change. Despite the price change being publicly advertised, we find that customers do not respond to the price change until they experience it firsthand. In Chapter 2.2, the second essay of Chapter 2, we estimate the spatial elasticity. We perform our estimation using a panel dataset of parking transactions spanning 21 months in a large U.S. city. During this time frame, there was an unannounced pricing error where two neighboring blocks were discounted by 67% for 16 months. We find that customers require approximately $81 to walk an additional mile to their intended destination. This estimate increases 13% in the presence of rain and 36% during the morning rush hour. In Chapter 3, the final chapter of this dissertation, we study optimal, dynamic pricing policies for a system, or network, of reusable resources, where a parking spot on a city block can be interpreted as a resource that can be "reused" after it is vacated. We focus our analysis on a single reusable product (i.e., a single zone or block with a fixed number of parking spaces) and aim to set the price as a function of the number of occupied spaces. Our objective is to maximize the long-run average revenue under Markovian assumptions (i.e., Poisson arrival and exponential usage times). In queuing theory, such a model is known as an Erlang loss system. We reformulate this objective function using a metric that we term the "conditional entry-state distribution." There does not exist a method for computing this metric, so in Chapter 3, we develop an algorithm that converges to the metric's true value for any Erlang loss system. We also provide analysis on the performance and speed of the algorithm.
Sustainable Parking Management
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Author : Nada Milosavljevic
language : en
Publisher: Elsevier
Release Date : 2019-06-15
Sustainable Parking Management written by Nada Milosavljevic and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-15 with Law categories.
Sustainable Parking Management provides the latest research findings in the field, encouraging transport planners and policymakers to use parking policy as a tool for managing parking and transport systems. The book teaches up-to-date parking management techniques for selecting parking policies and understanding parking behavior when faced with policy interventions. It shows when to apply each policy, how to include user attitudes in policy definition, and how to model user behavior when refining parking policies. In addition, it stresses the need to reduce overall city driving and the need to allow users to choose the transport mode that best suits their needs. As the growth of cities and car dependency worldwide has led to parking problems resulting in increased traffic congestion, pollution, and overall urban chaos, this book creates a model to help deal with the fallout. Offers step-by-step procedures for defining sustainable parking policies Synthesizes the latest research into one source Links theoretical knowledge with hands-on best practices from around the world Includes learning aids, such as chapter openers, textboxes, end-of-chapter review questions, and a glossary
A Sales Technique
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Author : Walton Dunphy
language : en
Publisher:
Release Date : 2021-05-10
A Sales Technique written by Walton Dunphy and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-10 with categories.
Broadly speaking, Revenue Management is the use of analytical data, which can help to predict the behavior of customers, so that product availability and price can be optimized to generate the maximum amount of revenue possible. Revenue management looks to drive higher revenues, margins, and profitability for the entire company. Companies within the hospitality industry that implement revenue management typically experience a three to six percent increase in revenues. This book is about the basis of Revenue Management, the best tools that need to be applied, it covers the importance of good online marketing and how to manage your online reputation. It includes some practical cases and examples. If you want to understand Revenue Management in a concise way through real examples, this is the book for you!
A Sales Technique
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Author : Bennett Tokich
language : en
Publisher:
Release Date : 2021-05-12
A Sales Technique written by Bennett Tokich and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-12 with categories.
Broadly speaking, Revenue Management is the use of analytical data, which can help to predict the behavior of customers, so that product availability and price can be optimized to generate the maximum amount of revenue possible. Revenue management looks to drive higher revenues, margins, and profitability for the entire company. Companies within the hospitality industry that implement revenue management typically experience a three to six percent increase in revenues. This book is about the basis of Revenue Management, the best tools that need to be applied, it covers the importance of good online marketing and how to manage your online reputation. It includes some practical cases and examples. If you want to understand Revenue Management in a concise way through real examples, this is the book for you!
Parking Management Best Practices
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Author : Todd Litman
language : en
Publisher: Routledge
Release Date : 2020-03-04
Parking Management Best Practices written by Todd Litman and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-04 with Architecture categories.
This book is a blueprint for developing an integrated parking plan. It explains how to determine parking supply and affect parking demand, as well as how to calculate parking facility costs. It also offers information about shared parking, parking maximums, financial incentives, tax reform, pricing methods, and other management techniques. What types of locations benefit from parking management? Places with perceived parking problems. Areas with rapidly expanding population, business activity, or traffic. Commercial districts and other places with compact land-use patterns. Urban areas in need of redevelopment and infill. Places with high levels of walking or public transit or places that want to encourage those modes. Districts where parking problems hinder economic development. Areas with high land values Neighborhoods concerned with equity, including fairness to nondrivers. Places with environmental concerns. Unique landscapes or historic districts in need of preservation,"
Improving Parking Garage Efficiency Using Reservation Optimization Techniques
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Author : Arjun Rao
language : en
Publisher:
Release Date : 2011
Improving Parking Garage Efficiency Using Reservation Optimization Techniques written by Arjun Rao and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Parking garages categories.
Parking in urban and suburban districts is becoming increasingly problematic due the information gap between the parking garages and the average commuter. This thesis describes and evaluates techniques that can be implemented by parking garages to augment parking garage efficiency. The issues studied in this thesis were i) Real-time tracking of car position ii) maximizing the number of reservations made for the parking garage by re-arrangement of existing reservations (Reservation Defragmentation) and iii) maximizing revenue for the parking garage through increased occupancy (Revenue Management). For the tracking problem, in order to be able to track the real-time position of the vehicle inside the parking garage, we have proposed two techniques. The first one involves a high accuracy algorithm that takes as input a higher number of sensor values (high accuracy) and the second one is a lower cost algorithm that takes as input fewer number of sensor values (low cost). We simulated various conditions of sensor failure rate and determined our metric to be number of tracked points as a percentage of the path to the destination. We determined limitations of these algorithms with respect to maximum speed of cars and inter-car distance. For the reservation defragmentation problem, we looked at increasing occupancy efficiency for i) Next day reservations and ii) Current day reservations. For this problem, we implemented three algorithms. For next day reservations, we established metrics to determine the efficiency of the algorithm including number of free parking spots created and reduction in lengths of free space in between the reservations. For current day reservations, our metric was the increase in maximum occupancy observed due to defragmentation. For increased revenue management, we suggested the application of two techniques: Booking limits and Overbooking. In booking limits, two-fare class of parking was suggested and the number of spots that need to be reserved for higher class (Capacity of garage - booking limit) was determined for probability distributions of customer arrival such as Poisson distribution. Since the practice of overbooking is done in order to compensate for the no-shows that occur despite reservations made, we have suggested an algorithm to determine the amount of overbooking based on a Gaussian distribution of customer 'no-shows'. We obtained the following results for the algorithms implemented. In case of the tracking algorithm, as the sensor failure rate increased, the inaccuracy of the two proposed algorithms also increased. For 2% failure rate, we track 0.4% of the incoming cars inaccurately (given that a tracking is marked as correct if 75% or less of all sensors along the path of the car fail). In case of reservation defragmentation, we obtained best results for Recursive First-Fit algorithm. For next day reservation defragmentation, using a mean of 15% cancellation of reservations resulted in 14.6% decrease in occupied parking spots which can then lead to increased occupancy and 46.3% decrease in inter-reservation free space sizes for a 1000 arrival reservation system. The reservations were exponentially distributed with a mean of 20 reservations/hour. For current day reservations, we were able to increase maximum occupancy of the parking garage by 5.5% using Recursive First Fit algorithm. Among other conditions, we have evaluated Poisson arrival distribution with corporate arrival rate 100 cars/hour (Flintsch et al., 2006) [56] and corporate fare twice of leisure fare. For this condition, protection level (number of parking slots reserved for corporate class) is determined to be 20% of garage capacity. We also evaluated Binomial distribution with probability of incoming customer to be corporate customer as 0.5 and corporate fare twice of leisure fare. For this condition, protection level is determined to be 50% of garage capacity. We evaluated overbooking for several combinations of No-show rates, mean and standard deviation values and the highest amount of overbooking we obtained was 1.93 times maximum garage capacity and this implies that permitting this number of reservations for the parking garage would minimize the number of parking spots being under-utilized and increase the revenue of the parking garage operator due to effective use of parking spots. The algorithms have been simulated for different arrival distributions (for Revenue Management), different arrival rates (tracking) as well as variable durations of stay (reservation defragmentation). Besides the problems mentioned, there are certain other aspects, such as generalizing the tracking algorithms for parking garages of arbitrary layouts represents the work that needs to be done in the future.
Manage Revenue
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Author : Johan Hammer
language : en
Publisher:
Release Date : 2018-12-14
Manage Revenue written by Johan Hammer and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-14 with categories.
Manage Revenue explains essential principles behind successful revenue management and how to effectively apply these principles in your hotel. These are proven principles that the author has successfully used in his own career as a hotel revenue manager. Since the revenue management and distribution scenes evolve at a rapid pace, the goal of this book is to make sure the lessons contained within will be as relevant in 10 years as it is in 2018. You will learn about revenue management basics, forecasting, booking windows, pace, value pricing, direct bookings, pricing, displacements analysis, group pricing, and much more. Your role as a revenue manager is to be a hungry, data-driven general who combines your own experience with data. Once you have some experience to lean back on, this is an unbeatable formula for success.This book is written for beginners as well as experienced hospitality professionals. The book provides you with a step-by-step framework to practice successful revenue management, and it can be used as your playbook to revert back to whenever you need guidance.
Revenue Playbook
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Author : Johan Hammer
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2017-06-20
Revenue Playbook written by Johan Hammer and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-20 with categories.
The Revenue Playbook is the personal assistant every hotel revenue manager needs. Use it to organize the simple rules of revenue management revealed in Revenue Superstar and make them actionable. With it, tune out the noise from the digital world as you become more effective at making forecasts, pricing rooms, and maximizing hotel profits.