Article
Transportation Science & Technology
Wei Liu, Fangni Zhang, Hai Yang
Summary: This paper models the joint equilibrium of destination and parking choices in cities under hybrid supply of curbside parking and shared parking. The existence and uniqueness/non-uniqueness of the joint equilibrium are discussed, as well as the pricing strategies of private and public shared parking operators and their relationship to travelers' choices. Numerical results are presented to illustrate the model and analytical results, providing further understanding.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Management
Gregory DeCroix, Xiaoyang Long, Jordan Tong
Summary: The study shows that quality variability reduces firm revenues and leads to a downward bias in customer beliefs about quality. Through dynamic personalized pricing strategies, firms can mitigate the negative effects of quality variability. The research also indicates that significant revenue gains can be achieved through dynamic pricing, especially when quality variability is large, customers react strongly to recent experiences, and/or mean service quality is high.
OPERATIONS RESEARCH
(2021)
Article
Management
Zhi Pei, Xu Dai, Yilun Yuan, Rui Du, Changchun Liu
Summary: With the rapid development of modern logistics systems, drone-based delivery service is being piloted globally to reduce labor costs in the courier industry and avoid geographical and demographic disturbances. The integration of a shared drone pool is crucial for service providers to survive and prosper, emphasizing the importance of revenue management and service quality.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2021)
Article
Management
Woonghee Tim Huh, Hongmin Li
Summary: The study examines a utility-based customer-choice model where customers may purchase multiple products. It analyzes the firm's optimal pricing problem and shows that the optimal solution is ordered based on a price-independent index. The study also extends to consider a stochastic model that accounts for customer heterogeneity.
OPERATIONS RESEARCH
(2022)
Article
Transportation Science & Technology
Guipeng Jiao, Mohsen Ramezani
Summary: Ridesourcing services from transportation network companies (TNCs) have been found to worsen traffic conditions by increasing the number of unoccupied vehicles. As an alternative, ridesharing combines similar itineraries to counteract the negative effects of ridesourcing. This study proposes a dynamic discount pricing strategy to incentivize ridesharing, showing substantial economic benefits for the platform and drivers in both short and long terms.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2022)
Article
Environmental Studies
Qingyu Ma, Yanan Xin, Hong Yang, Kun Xie
Summary: The rise of shared electric scooter systems has provided urban areas with a new solution for micro-mobility. This study explores the integration of shared e-scooters with public transportation systems and compares their usage to shared bikes and taxis for connecting trips from/to metro stations. The results show that the preferences for shared e-scooters vary depending on land use and time period, and differ from shared bikes and taxis.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2022)
Article
Computer Science, Interdisciplinary Applications
Yang Yang, Wan -Ling Chu, Cheng-Hung Wu
Summary: This research proposes a revenue management framework for perishable products, which can quickly learn customer preferences before the selling season begins and generate optimal pricing decisions. The numerical study shows that the revenue difference caused by unknown preferences is small compared to the known preferences.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Chemistry, Analytical
Lei Zhu, Jinghui Wang, Yuqiu Yuan, Wei Wu
Summary: The initial hype around Automated Vehicle (AV) technologies has subsided, and it is now being realized that near-term deployment of AV technologies will be in the form of low-speed shared automated shuttles in geofenced districts with a high density of trip demand. A modeling and simulation toolkit that can act as a decision support tool for early-stage AMD deployments is desired for answering the questions such as (i) for a series of given conditions, what is the expected mode split for shared automated vehicle (SAV) services? (ii) what level-of-service and network performance can be anticipated for that mode share of SAVs? The framework proposed in this study demonstrates efficacy in solving the mode split equilibrium in an AMD.
Article
Economics
Wenwei Zhang, Min Xu, Shuaian Wang
Summary: This study proposes a comprehensive modeling and optimization framework for the joint self-service station location and service price optimization problem. It aims to reduce the vehicle routing cost of the dedicated fleet by shifting customers from home-delivery service to cost-effective self-service.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2023)
Article
Environmental Studies
Xiang Yan, Xilei Zhao, Andrea Broaddus, Joshua Johnson, Sivaramakrishnan Srinivasan
Summary: This study evaluates the impact of shared e-scooters on public transit and driving reduction. Survey results show that shared e-scooters have been used as a mode of transportation to connect with transit and replace car trips. The study also reveals that certain demographics, such as males, non-Whites, and individuals without a college degree, are more likely to use shared e-scooters.
TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
(2023)
Article
Computer Science, Information Systems
Ahmed Jaber, Jamil Hamadneh, Balint Csonka
Summary: This research focuses on the preferences of micro-mobility users in urban areas, specifically shared electric bikes, shared conventional bikes, and shared electric scooters. A discrete choice modeling approach is used to study the preferences of people through developing a transport choice model. The results indicate that travelers prefer using bikes more than e-bikes and e-scooters, and e-scooter is the least favored by travelers. Factors such as parking type and socio-demographic variables are found to be significant in micro-mobility modes in urban areas.
Article
Management
Hakjin Chung, Hyun-Soo Ahn, So Yeon Chun
Summary: This study examines the impact of point redemption on seller's pricing and inventory decisions. The results show that point redemption can significantly affect pricing and reduce price fluctuations caused by dynamic pricing policies. Implementing discretionary policies can greatly increase the seller's revenue.
M&SOM-MANUFACTURING & SERVICE OPERATIONS MANAGEMENT
(2022)
Article
Transportation Science & Technology
Shelly Etzioni, Ricardo A. Daziano, Eran Ben-Elia, Yoram Shiftan
Summary: This study models the choice between different shared automated transportation services using a hybrid choice model, identifying two latent classes of users based on factors like time style orientation and seating designation. The research shows that factors such as time style and seating designation play a significant role in determining users' preference for shared rides and automated transit.
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
(2021)
Article
Green & Sustainable Science & Technology
Eva Ayaragarnchanakul, Felix Creutzig, Aneeque Javaid, Nattapong Puttanapong
Summary: Individual motorized vehicles in urban environments are oversupplied and inefficient, but shared mobility offers a more efficient use of vehicles. Commuters value time and fuel costs, but dislike walking, waiting, and searching for parking. Shared taxis have the potential to be used as a door-to-door mode of transportation.
Article
Engineering, Civil
Ning Wang, Jiahui Guo
Summary: The research models the multiaction dynamic dispatching of Shared Autonomous Electric Vehicles (SAEVs) based on Markov Decision Process (MDP) and optimization, showing that the optimization model with long-term return can decrease user waiting time and increase total revenue. The Kuhn-Munkres algorithm ensures computational effectiveness, and integrating combinatorial optimization theory with reinforcement learning theory is an effective approach to solving the multiaction dynamic dispatching problem of SAEVs.
JOURNAL OF ADVANCED TRANSPORTATION
(2021)
Article
Operations Research & Management Science
Jochen Goensch, Michael Hassler, Rouven Schur
Review
Management
Jochen Goensch
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2020)
Article
Management
Rouven Schur, Jochen Goensch, Michael Hassler
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2019)
Article
Management
Benedikt Finnah, Jochen Goensch, Florian Ziel
Summary: This paper addresses the decision problem of an owner of an energy storage who trades on two energy markets, considering ramping times and the influence of price forecasts on expected profit. Approximate dynamic programming is used to solve the problem and is compared with other approaches in a numerical study.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Operations Research & Management Science
Matthias Soppert, Claudius Steinhardt, Christian Mueller, Jochen Goensch
Summary: Shared mobility systems have become an integral part of urban transportation, and pricing optimization is crucial for increasing profits. This paper introduces a differentiated, profit-maximizing pricing problem based on the origin of rentals in shared mobility systems. A temporal decomposition approach based on approximate dynamic programming is proposed to solve the problem. Computational experiments show the benefits of capturing network effects in pricing and the accuracy of the proposed approach in predicting profits. A case study based on Share Now data from Florence, Italy, demonstrates a profit increase of around 9% compared to the industry standard of constant uniform minute prices.
TRANSPORTATION SCIENCE
(2022)
Article
Management
Matthias Soppert, Claudius Steinhardt, Christian Mueller, Jochen Goensch, Prasanna M. Bhogale
Summary: Shared mobility systems, particularly free-floating systems, are growing rapidly and require accurate optimization models for pricing and vehicle re-location. Existing models based on station-based systems do not adequately account for the unique characteristics of free-floating systems, resulting in overestimated rentals, suboptimal decisions, and lost profits. This study introduces novel analytical matching functions specifically designed for free-floating systems, incorporating additional parameters such as customers' maximum walking distance and zone sizes. The computational study shows that these functions significantly improve accuracy compared to the existing approach, leading to more profitable pricing decisions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Management
Sebastian Spindler, Matthias Soppert, Claudius Steinhardt
Summary: This study revisits the valid inequalities proposed by Kharbeche and Haouari (2013) for mixed-integer programming in a two-machine flow shop scheduling problem. It points out an incorrect inequality that excludes optimal solutions, leading to suboptimal solutions. To address this, a new valid inequality is formulated based on the correct dominance criteria. Numerical analysis shows that 10% to 22% of solutions obtained using the incorrect inequality are suboptimal, resulting in a maximum loss of 12% in objective function value.
JOURNAL OF THE OPERATIONAL RESEARCH SOCIETY
(2022)
Article
Operations Research & Management Science
Christian Mueller, Jochen Goensch, Matthias Soppert, Claudius Steinhardt
Summary: Free-floating vehicle sharing systems offer flexibility but also face the challenge of vehicle accumulation at low-demand locations. Dynamic pricing based on customer-centricity, utilizing real-time location data and customer behavior, can effectively counter these imbalances and increase profits.
TRANSPORTATION SCIENCE
(2023)
Article
Operations Research & Management Science
Christian Jaeck, Jochen Goensch, Hans Doermann-Osunaa
Summary: The distribution of passenger vehicles is a complex and costly task for automotive OEMs. This paper presents two methodologies to approximate realistic load factors for modern auto carriers, considering their flexibility and constraints. Computational experiments using real-world data show that the proposed approaches can improve load capacity and reduce costs compared to current industry solutions.
TRANSPORTATION SCIENCE
(2023)