Will they take this offer? A machine learning price elasticity model for predicting upselling acceptance of premium airline seating

2023 | Information & Management | Citations: 0

Authors: Thirumuruganathan, Saravanan; Emadi, Noora Al; Jung, Soon-gyo; Salminen, Joni; Robillos, Dianne Ramirez; Jansen, Bernard J.

Abstract: Employing customer information from one of the world’s largest airline companies ... Expand

Abstract: Employing customer information from one of the world’s largest airline companies, we develop a price elasticity model (PREM) using machine learning to identify customers likely to purchase an upgrade offer from economy to premium class and predict a customer’s acceptable price range. A simulation of 64.3 million flight bookings and 14.1 million email offers over three years mirroring actual data indicates that PREM implementation results in approximately 1.12 million (7.94%) fewer non-relevant customer email messages, a predicted increase of 72,200 (37.2%) offers accepted, and an estimated $72.2 million (37.2%) of increased revenue. Our results illustrate the potential of automated pricing information and targeting marketing messages for upselling acceptance. We also identified three customer segments: (1) Never Upgrades are those who never take the upgrade offer, (2) Upgrade Lovers are those who generally upgrade, and (3) Upgrade Lover Lookalikes have no historical record but fit the profile of those that tend to upgrade. We discuss the implications for airline companies and related travel and tourism industries. Collapse

Topics: electronic mail marketing management price management customer satisfaction application programming interface

Methods: autoencoder data transformation machine learning experiment principal component analysis

Theories: optimization theory decision theory

An Integer Programming Approach to Solving the Inverse Graph Model for Conflict Resolution with Two Decision Makers

2022 | Group Decision and Negotiation | Citations: 0

Authors: Han, Yu; Xu, Haiyan; Fang, Liping; Hipel, Keith W.

Abstract: Operational algorithms for solving the inverse problem for the graph model for c ... Expand

Abstract: Operational algorithms for solving the inverse problem for the graph model for conflict resolution are presented for the case of two decision makers (DMs) under a variety of solution concepts, including Nash stability (Nash), general metarationality (GMR), symmetric metarationality (SMR), and sequential stability (SEQ). The algorithms based on integer programming enable a DM, an analyst, or a mediator to obtain all of the preferences required to make a specified state to be an equilibrium or resolution. For the cases of Nash, GMR, and SMR, the respective inverse algorithm for the focal DM is formulated as a 0–1 integer linear programming problem even when both DMs’ preferences are unknown. For the situation of SEQ, when both DMs’ preferences are unknown, the focal DM’s algorithm is a 0–1 integer nonlinear programming problem while, under the condition that the opponent’s preferences are known, the focal DM’s 0–1 integer programming problem is linear. The usefulness of the algorithms developed is demonstrated by applying them to an illustrative dispute. Collapse

Methods: integer programming computational algorithm linear optimization integer linear programming

Theories: prisoner's dilemma

A dynamic shipment matching problem in hinterland synchromodal transportation

2020 | Decision Support Systems | Citations: 0

Authors: Guo, Wenjing; Atasoy, Bilge; van Blokland, Wouter Beelaerts; Negenborn, Rudy R.

Abstract: Hinterland intermodal transportation is the movement of containers between deep- ... Expand

Abstract: Hinterland intermodal transportation is the movement of containers between deep-sea ports and inland terminals by using trucks, trains, barges, or any combination of them. Synchromodal transportation, as an extension of intermodal transportation, refers to transport systems with dynamic updating of plans by incorporating real-time information. The trend towards spot markets and digitalization in hinterland intermodal transportation gives rise to online synchromodal transportation problems. This paper investigates a dynamic shipment matching problem in which a centralized platform provides online matches between shipment requests and transport services. We propose a rolling horizon approach to handle newly arrived shipment requests and develop a heuristic algorithm to generate timely solutions at each decision epoch. The experiment results demonstrate the solution accuracy and computational efficiency of the heuristic algorithm in comparison to an exact algorithm. The proposed rolling horizon approach outperforms a greedy approach from practice in total costs under various scenarios of the system. Collapse

Topics: decision support system price management

Methods: computational algorithm experiment business process modeling integer programming design science

A decision support framework for home health care transportation with simultaneous multi-vehicle routing and staff scheduling synchronization

2020 | Decision Support Systems | Citations: 0

Authors: Nasir, Jamal Abdul; Kuo, Yong-Hong

Abstract: Due to the ageing population and the prevalence of chronic diseases, Home Health ... Expand

Abstract: Due to the ageing population and the prevalence of chronic diseases, Home Health Care (HHC) practices are significantly increasing in developed countries to provide coordinated health related services to patients at their homes. Accordingly, the scope of HHC services is also expanding from typical nursing and postoperative care at home to cover all types of needs of elderly patients (e.g., personal care, drug delivery and meal services). This paper aims to address the pressing demand for HHC services and develop a novel and effective mathematical model and solution methodology for supporting health care service delivery decisions. Our decision support framework captures the real needs of HHC services, including the challenges of creating simultaneous schedules and route plans for a set of HHC staff and Home Delivery Vehicles (HDVs) under the requirements of syn­ chronization between HHC staff and HDVs visits, multiple visits to patients, multiple routes of HDVs and pickup/ delivery visits related precedence for HDVs. A Mixed Integer Linear Programming (MILP) model is developed to characterize the optimization problem. Considering the computational complexity of the problem, a Hybrid Genetic Algorithm (HGA) is proposed to suggest HHC planning decisions. The model formulation and proposed HGA are examined on real-life instances for demonstrating its practicality and randomly generated test instances for assessing the scalability of the proposed approach. The results show the effectiveness and efficiency of our solution methodology. Experimental results indicate that the proposed algorithm provided a good performance even with an increasing number of required synchronized services, whereas the heuristic tactics facilitate the HGA to produce better-quality solutions in a significantly shorter time. Our framework is expected to contribute to an important aspect of shared healthcare mobility. Collapse

Topics: Google+ application programming interface decision support

Methods: experiment mathematical model computational algorithm case study descriptive statistic

Solving Practical Railway Crew Scheduling Problems with Attendance Rates

2017 | Business & Information Systems Engineering | Citations: 0

Authors: Hoffmann, Kirsten; Buscher, Udo; Neufeld, Janis Sebastian; Tamke, Felix

Abstract: Arising from a practical problem in German rail passenger transport, a prototype ... Expand

Abstract: Arising from a practical problem in German rail passenger transport, a prototype for a multi-period railway crew scheduling problem with attendance rates for conductors is developed and evaluated in this paper. The consideration of attendance rates is of increasing importance in regional transport networks and requires decision support. For this purpose business analytics is applied in order to offer an approach to transform real-world data to concrete operational decision support (action). The focus here is on the analysis step using a new set covering model with several essential restrictions integrated for the first time. A hybrid column generation approach is applied, which solves the pricing problem by means of a genetic algorithm. The artifact is evaluated with the help of a case study of three real-world transport networks. It is shown that the hybrid solution approach is able to solve the problem more effectively and efficiently compared to conventional approaches used in practice. Collapse

Topics: decision support analytical information system price management programming language decision making

Methods: computational algorithm case study design artifact integer programming integer linear programming

Optimizing the timing and number of batches for compounded sterile products in an in-hospital pharmacy

2015 | Decision Support Systems | Citations: 0

Authors: Dobson, Gregory; Tilson, David; Tilson, Vera

Abstract: Hospital pharmacy departments have traditionally batched the production of a cat ... Expand

Abstract: Hospital pharmacy departments have traditionally batched the production of a category of medications called Compounded Sterile Products (CSP). Since the batches are intended to satisfy several hours, or even a day's worth of demand, the cancellation of orders by physicians can lead to the waste of a considerable amount of medication. The manager of the pharmacy department can choose to produce the CSP medication in one or more batches per day. In making this decision the manager is trading off two sorts of costs: (a) the “holding cost” of carrying inventory, which in this context is largely the cost of wasted doses, and (b) the “set up cost” of the labor for delivering the prepared medication to the various units of a hospital. Although this trade-off superficially resembles that of a classic batching problem, it turns out to be quite different. This is primarily because the sequence of batches must repeat in a 24-hour cycle and the holding cost, related to the waste of CSP medications, varies over the 24-hour cycle according to the pattern of order cancellations, which in turn depends on the schedule of physicians' reevaluating the treatments of patients under their care. In addition, the setup cost, related to the cost of the delivery, varies slightly with the cost of labor at different times of the day. While previous work has looked at the benefits of multiple batches per day, the problem has not been addressed in a mathematically rigorous manner. The contribution of this work is twofold. Firstly, it extends the considerable literature on lot sizing by introducing a formulation for deciding the optimal number and timing of batches as an integer programming problem that caters for, and minimizes, the novel forms of holding and setups costs described above. In doing so the inventory curves over time are modeled precisely. Secondly, a dynamic programming methodology for the optimization problem is developed that is solvable with just a few minutes of computing time. Thus the pharmacy manager can make rational decisions about the optimal number and timing of CSP production batches based on the specific patterns of costs and work practices found in his or her hospital. Collapse

Topics: manufacturing information system

Methods: dynamic programming experiment optimization model integer programming integer linear programming

A DSS for integrated distribution of empty and full containers

2009 | Decision Support Systems | Citations: 14

Authors: Bandeira, Denise Lindstrom; Becker, João Luiz; Borenstein, Denis

Abstract: A DSS integrating empty and full containers transshipment operations is presente ... Expand

Abstract: A DSS integrating empty and full containers transshipment operations is presented, addressing the typically unbalanced export/import containers trading problem. The problem is modeled as a network, where nodes represent customers, leasing companies, harbors and warehouses, while arcs represent transportation routes. The underlying mathematical model operates in stages, first prioritizing and adjusting full containers demands considering available empty containers supplies, and then statically optimizing costs. Transportation routes are registered and dynamically controlled, cyclically, for a given time horizon. The DSS is flexible, allowing several parameters to be configured. Experimental examples using randomly generated parameters were conducted to evaluate the effectiveness of the system. Collapse

Topics: decision support system application programming interface Visual Basic database system

Methods: experiment case study simulation integer programming optimization model

An agent for selecting optimal order set in EC marketplace

2004 | Decision Support Systems | Citations: 3

Authors: Choi, Hyung Rim; Kim, Hyun Soo; Park, Byung Joo; Park, Young Jae; Whinston, Andrew B.

Abstract: For most small manufacturing companies, the selection and completion of orders p ... Expand

Abstract: For most small manufacturing companies, the selection and completion of orders placed by buyers are closely linked to the load status of their production lines. The decision to accept an order, or the selection of optimal order set, critically depends on the production schedule when orders exceed production capacity. However, production scheduling is mainly performed by human experts, and small companies lack resources to implement such a task. As a result, most small manufacturers suffer from the difficulty to meet due dates or to make proper decision in accepting new orders. To address this problem, this paper develops an automatic agent that selects an optimal set of orders using commonly available Internet technology. The main engine of the selection agent is based on a typical job shop scheduling model, formulating and implementing it as an Integer Program (IP) model. We also translate IP into Genetic Algorithm (GA) to address its NP-hard problem. We conclude with a suggestion for an agent architecture that tackles Web-based order selection problems. Collapse

Topics: internet technology Java business-to-business production management database system

Methods: experiment computational algorithm case study integer programming mixed-integer programming