Dynamic price competition with discrete customer choices

Lin, Kyle Y.; Sibdari, Soheil

doi:10.1016/j.ejor.2007.12.040

Cited by 80 publications

(46 citation statements)

References 29 publications

(26 reference statements)

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“…Penelitian mengenai model dynamic pricing pada dua penerbangan paralel yang dimiliki oleh satu maskapai yang sama pernah dilakukan oleh Rusdiansyah et al [11,12], Putri dan Rusdiansyah [10]. Selain itu, beberapa penelitian yang ada pada literatur yang membahas masalah dynamic pricing pada dua maskapai yang saling berkompetisi antara lain Li dan Hua [6], Lin dan Sibdari [7] dan Mart dan Talluri [8].…”

Section: *Penulis Korespondensiunclassified

“…Kriteria tersebut dapat berupa kriteria sisa waktu penjualan, sisa kursi yang belum terjual, harga kompetitor, dan lain sebagainya. Sisa kursi yang belum terjual sampai waktu penjualan berakhir akan menjadi suatu nilai (revenue) yang masih dapat diselamatkan melalui kursi yang sudah terjual dengan melakukan strategi penetapan harga secara dinamis (Lin dan Sibdari [7]). Strategi penetapan harga secara dinamis tersebut dilakukan untuk menjual kursi yang sama dengan kelas harga yang berbeda kepada konsumen yang bersedia membayar pada kelas harga tersebut.…”

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Model Dynamic Pricinguntuk Penetapan Harga Tiket Pesawat Terbang Berbasis Waktu dan Persediaan Kursi dengan Mempertimbangkan Keputusan Kompetitor

Rusdiansyah¹,

Dwi²,

Puspitasari³

2013

jti

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Abstract:In the airline business nowadays the competition between airlinesis very tight. The decision of pricing of an airline will affect significantly the demand and revenue of other airlines. This study develops a model of Airline Revenue Management (ARM). We build an ARM model under competitive environment. The model considers the change of the competitor's ticket for two parallel flights and should be made based on time and seat inventory. Specifically, we develop a model of dynamic programming to obtain the optimal ticket price based on the remaining seats, the rest of the time, as well as changes in competitors' ticket prices in order to generate maximum revenue expectation. This study conducted a series of numerical experiment scenarios to demonstrate the behavior of the model to the revenue expectation.Keywords: Airline Revenue Management, dynamic pricing, dynamic programming, expected revenue. PendahuluanPerkembangan industri penerbangan turut meningkatkan tingkat persaingan antar maskapai. Persaingan yang ketat mendorong maskapai penerbangan untuk mampu merumuskan strategi dalam memaksimalkan pendapatannya. Kebijakan pengelolaan permintaan serta seluruh metodologi dan sistem yang dibutuhkan untuk membuatnya dengan tujuan memaksimalkan pendapatan disebut revenue management (RM) (Tallury dan Ryzin [13]). Penerapan revenue management di maskapai penerbangan disebut dengan Airlines Revenue Management (ARM). ARM yang diterapkan di maskapai penerbangan dengan tujuan untuk memaksimalkan pendapatan melalui pengelolaan sumber daya yang dimiliki secara optimal. Dapat dikatakan ARM adalah bagaimana memperoleh pendapatan yang maksimum melalui pengelolaan kursi yang tersedia. Maskapai melakukan pengelolaan perolehan pendapatan dengan ARM karena beberapa kondisi seperti permintaan kursi yang bersifat tidak pasti (unpredictable), kelebihan kursi penerbangan yang tidak laku dijual tidak dapat disimpan yang kemudian hal ini menjadi opportunity cost, fleksibilitas penumpang dalam memilih kelas atau jadwal penerbangan sehingga dapat dibagi menjadi beberapa segmen penumpang, kapasitas kursi yang disediakan yang berjumlah tetap sesuai dengan armada pesawat. Dynamic pricing adalah sebuah strategi dalam ARM yaitu berupa pengaturan penetapan harga yang bertujuan untuk meningkatkan pendapatan maskapai penerbangan. Penggunaan dynamic pricing sangat tepat untuk diterapkan pada industri penerbangan yang memiliki karakteristik harga tiket pesawat terbang yang dinamis. Pada waktu tertentu (sebelum waktu kebergangkatan dan selama waktu penjualan), harga tiket pesawat terbang akan berbeda dengan harga tiket pesawat terbang pada waktu sesaat sebelum keberangkatan. Pada umumnya, harga tiket pesawat terbang sangat tinggi pada saat menjelang waktu keberangkatan. Ketika waktu penjualan (selling horizon time) masih panjang, maka harga tiket pesawat terbang cenderung rendah. Penetapan harga tersebut ditentukan berdasarkan beberapa kriteria. Kriteria tersebut dapat berupa kriteria sisa waktu penjualan, sisa kursi yang belum terjual, harga k...

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Section: *Penulis Korespondensiunclassified

unclassified

Model Dynamic Pricinguntuk Penetapan Harga Tiket Pesawat Terbang Berbasis Waktu dan Persediaan Kursi dengan Mempertimbangkan Keputusan Kompetitor

Rusdiansyah¹,

Dwi²,

Puspitasari³

2013

jti

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“…Others use statistical learning methods and heuristics based on mathematical estimations of the optimal price [1]. While most DyP models are monopolies, there are some that model competitors in the marketplace as well [14], [15], [16]. In this work we deal with a duopoly market, though the firm does not model a competitor explicitly.…”

Section: Related Workmentioning

confidence: 99%

Adaptive Strategies for Dynamic Pricing Agents

Ramezani

Bosman

Poutré

2011

2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology

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Abstract-Dynamic Pricing (DyP) is a form of Revenue Management in which the price of a (usually) perishable good is changed over time to increase revenue. It is an effective method that has become even more relevant and useful with the emergence of Internet firms and the possibility of readily and frequently updating prices. In this paper a new approach to DyP is presented. We design adaptive dynamic pricing strategies and optimize their parameters with an Evolutionary Algorithm (EA) offline while the strategies can deal with stochastic market dynamics quickly online. We design two adaptive heuristic dynamic pricing strategies in a duopoly where each firm has a finite inventory of a single type of good. We consider two cases, one in which the average of a customer population's stochastic valuation for each of the goods is constant throughout the selling horizon and one in which the average customer valuation for each good is changed according to a random Brownian motion. We also design an agent-based software framework for simulating various dynamic pricing strategies in agent-based marketplaces with multiple firms in a bounded time horizon. We use an EA to optimize the parameters for each of the pricing strategies in each of the settings and compare the strategies with other strategies from the literature. We also perform sensitivity analysis and show that the optimized strategies work well even when used in settings with varied demand functions.

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“…Xu and Hopp [27] studied a multiseller dynamic pricing game where demand arrivals are governed by a geometric Brownian motion, the demand-price relation falls into a special family, and only the lowest-priced seller sells. Lin and Sibdari [16] showed that subgame-perfect equilibria exist for a discrete-time dynamic pricing game where opponents' inventory levels are observable.…”

Section: Literature Surveymentioning

confidence: 99%

A nonatomic‐game model for timing clearance sales under competition

Yang

Xia

et al. 2014

Naval Research Logistics

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Abstract:We deal with dynamic revenue management (RM) under competition using the nonatomic-game approach. Here, a continuum of heterogeneous sellers try to sell the same product over a given time horizon. Each seller can lower his price once at the time of his own choosing, and faces Poisson demand arrival with a rate that is the product of a price-sensitive term and a market-dependent term. Different types of sellers interact, and their respective prices help shape the overall market in which they operate, thereby influencing the behavior of all sellers. Using the infinite-seller approximation, which deprives any individual seller of his influence over the entire market, we show the existence of a certain pattern of seller behaviors that collectively produce an environment to which the behavior pattern forms a best response. Such equilibrium behaviors point to the suitability of threshold-like pricing policies. Our computational study yields insights to RM under competition, such as profound ways in which consumer and competitor types influence seller behaviors and market conditions.

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Dynamic price competition with discrete customer choices

Cited by 80 publications

References 29 publications

Model Dynamic Pricinguntuk Penetapan Harga Tiket Pesawat Terbang Berbasis Waktu dan Persediaan Kursi dengan Mempertimbangkan Keputusan Kompetitor

Model Dynamic Pricinguntuk Penetapan Harga Tiket Pesawat Terbang Berbasis Waktu dan Persediaan Kursi dengan Mempertimbangkan Keputusan Kompetitor

Adaptive Strategies for Dynamic Pricing Agents

A nonatomic‐game model for timing clearance sales under competition

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