Over the last decades, dynamic pricing has become increasingly popular. To solve pricing problems, however, is particularly challenging if the customers' and competitors' behavior are both strategic and unknown. Reinforcement Learning (RL) methods are promising for solving such dynamic problems...

Dynamic pricing strategy is a well-known method for utility pricing used in many parts of the world and is rapidly growing in trend due to its ability to adjust utility pricing to the utmost real-time calculations. One such method is what we call Time-of-Use (TOU), a strategy that adjusted...

Cinema operators have so far behaved more conservatively in terms of their price management. In the course of the digital transformation, there are many opportunities for price innovations. The implementation of yield management strategies in the cinema industry would have a positive impact on...

Effective pricing strategies are critical for optimizing revenue and maintaining competitiveness in transportation supply chains, particularly in multi-channel environments. This paper presents a machine learning-driven dynamic pricing approach designed to optimize ticket prices across multiple...

Abstract We suggest a dynamic pricing model for selling extra seats - seat reservations for unoccupied seats that provide additional space alongside regular reservations. Such extra space tickets share the resources of the main product and leverage the unused capacity, offering significant...

Abstract In this paper, we introduce a nonlinear dynamic pricing model in the presence of multiunit demand, enabling firms to quote separate prices for each batch size. This approach diverges from traditional models by accounting for two-dimensional customer heterogeneity in product attraction...

Abstract Due to exponentially growing state and action spaces, network dynamic pricing problems are analytically intractable such that state-of-the-art approaches rely on heuristics. Reinforcement learning has successfully been applied in various complex domains, but its successful applicability...

Much like small ripples in a stream, which get lost in the larger waves, small changes in retail prices often fly under the radar of public perceptions, while large price changes appear as marketing moves associated with demand and competition. Unnoticed, these could increase consumers’...

Over the last decades, dynamic pricing has become increasingly popular. To solve pricing problems, however, is particularly challenging if the customers' and competitors' behavior are both strategic and unknown. Reinforcement Learning (RL) methods are promising for solving such dynamic problems...

This paper studies the relationship between optimal dynamic pricing for network goods and the coordination of consumers' adoption decisions. We show that based on risk dominance criterion, consumers face the risk of coordination failure, and introductory pricing is optimal if the risk is higher...

In various sectors, such as retail, firms encounter customers with multiunit demand and often implement nonlinear pricing to accommodate this demand structure. While effective, this pricing strategy lacks the adaptability offered by dynamic pricing, a trend gaining significance in the retail...

Precise demand forecasting and agile pricing strategies are crucial in modern business. This study aims to enhance these strategies by evaluating the efficacy of Holt-Winters Exponential Smoothing (HWES) and Autoregressive Integrated Moving Average (ARIMA) models. The study assesses their...

Purpose This study aims to explore the impact of locational and seasonal factors on the financial performance of short-term rental properties in Margaret River, Western Australia. It seeks to address the gap in understanding how these factors influence key financial metrics such as average daily...

This paper studies the relationship between optimal dynamic pricing for network goods and the coordination of consumers' adoption decisions. We show that based on risk dominance criterion, consumers face the risk of coordination failure, and introductory pricing is optimal if the risk is higher...

Abstract Amid the rapid growth of online retail, last-mile delivery faces significant challenges, including the cost-effective delivery of goods to all delivery locations. Our work contributes to this stream by applying dynamic pricing techniques to effectively model the possible involvement of...

Während Revenue Management in der Hotellerie bereits recht verbreitet ist, gibt es bisher nur wenige Übertragungen auf den Markt der Ferienimmobilien. Revenue Management für Ferienimmobilien geht diesen Schritt. Von der privaten Vermietung einzelner Objekte bis zur hunderte Objekte...

In most major cities today, various shared mobility systems such as car or bike sharing exist. Maintaining these systems is challenging, and, thus, public and private providers strive to improve operational performance. An important metric which is regularly recorded and monitored in practice...

Nowadays, customers as well as retailers look for increased sustainability. Recommerce markets – which offer the opportunity to trade-in and resell used products – are constantly growing and help to use resources more efficiently. To manage the additional prices for the trade-in and the...

Linking decision systems, negotiating agents, management accounting, and computational accounting, this paper aims at exploring dynamic pricing strategies of a synthetic business-to-consumer online operation and a comparative analysis of evolving strategy-specific pricing optimization. Five...

The pricing of public transportation is a frequently debated subject, and a notable current trend is leaning towards flat-rate pricing. In the previous year, Germany introduced a flat-rate ticket, enabling individuals to access public transportation across the entire country for just 9 euros per...

In most major cities today, various shared mobility systems such as car or bike sharing exist. Maintaining these systems is challenging, and, thus, public and private providers strive to improve operational performance. An important metric which is regularly recorded and monitored in practice...

This paper is devoted to the development of heuristics for the dynamic pricing problem. A discrete time model of dynamic pricing on the fixed time horizon is proposed. It is applicable to products that satisfy two properties: 1) product value expires at a certain predetermined date, and 2)...

Nowadays, customers as well as retailers look for increased sustainability. Recommerce markets – which offer the opportunity to trade-in and resell used products – are constantly growing and help to use resources more efficiently. To manage the additional prices for the trade-in and the...

In the challenging environment of attended home deliveries, pricing delivery options can play a crucial role to ensure profitability and service quality of retailers. To differentiate between standard and premium delivery options, many retailers include time windows of various lengths and fees...

Time-varying prices are thought to be critical for increasing economic efficiency of the power system. However, a rigorous assessment of the evidence from field trials that use time-of-use pricing, critical peak pricing, etc. in households is missing. This machine learning-assisted systematic...

Linking decision systems, negotiating agents, management accounting, and computational accounting, this paper aims at exploring dynamic pricing strategies of a synthetic business-to-consumer online operation and a comparative analysis of evolving strategy-specific pricing optimization. Five...