Robust Multi-Product Pricing

Lim, Andrew; Shanthikumar, J. George; Watewai, Thaisiri

doi:10.2139/ssrn.1078012

Cited by 19 publications

(26 citation statements)

References 34 publications

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“…Models with finite inventory are considered by Besbes and Zeevi (2012), Gallego and Talebian (2012) and Lim et al (2008). Besbes and Zeevi (2012) extend Besbes and Zeevi (2009) to a setting where multiple products share the same finite resources.…”

Section: Multiple Productsmentioning

confidence: 99%

Dynamic pricing and learning: Historical origins, current research, and new directions

Boer

2015

Surveys in Operations Research and Management Science

307

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Dynamic pricing and learning is a research topic that has received a considerable amount of attention in recent years, from different scientific communities: operations research and management science, marketing, economics, econometrics, and computer science. We survey these literature streams: we provide a brief introduction to the historical origins of quantitative research on pricing and demand estimation, point to different subfields in the area of dynamic pricing, and provide an in-depth overview of the available literature on dynamic pricing and learning. We discuss relations with methodologically related research areas, and identify several important directions for future research.

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Section: Multiple Productsmentioning

confidence: 99%

Dynamic pricing and learning: Historical origins, current research, and new directions

Boer

2015

Surveys in Operations Research and Management Science

307

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“…Lim and Shanthikumar (2007) and Thiele (2006) study this in a single-product setting, and Lim et al (2008), Thiele (2009) in a multiproduct setting. A potential drawback of these robust approaches is that no learning takes place, despite the accumulation of sales data.…”

Section: Non-bayesian Approachesmentioning

confidence: 99%

“…The authors develop a pricing rule in a rolling horizon framework, and illustrate its behavior by a computational study. Finally, a robust optimization approach to multi-product pricing under demand uncertainty is studied by Lim et al (2008).…”

Section: Multiple Productsmentioning

confidence: 99%

Dynamic Pricing and Learning: Historical Origins, Current Research, and New Directions

Boer

2013

SSRN Journal

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“…Perakis and Roels (2007) analyze robust capacity controls for network revenue management using the maximin and minimax regret criteria. Lim et al (2008) extend their relative entropy approach from the single product, see Lim and Shanthikumar (2007), to multi products cases and a proposed a risk-sensitive pricing problem involving a risk sharing rule. Mitra and Wang (2005) discuss various risk indices for risk modeling of network revenue management problems.…”

Section: Related Literaturementioning

confidence: 99%

List pricing versus dynamic pricing: Impact on the revenue risk

Koenig

Meissner

2010

European Journal of Operational Research

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We consider the problem of a firm selling multiple products that consume a single resource over a finite time period. The amount of the resource is exogenously fixed. We analyze the difference between a dynamic pricing policy and a list price capacity control policy. The dynamic pricing policy adjusts prices steadily resolving the underlying problem every time step, whereas the list pricing policy sets static prices once but controls the capacity by allowing or preventing product sales.As steady price changes are often costly or unachievable in practice, we investigate the question of how much riskier it is to apply a list pricing policy rather than a dynamic pricing policy. We conduct several numerical experiments and compare expected revenue, standard deviation, and conditional-value-at-risk between the pricing policies. The differences between the policies show that list pricing can be a useful strategy when dynamic pricing is costly or impractical.

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Robust Multi-Product Pricing

Cited by 19 publications

References 34 publications

Dynamic pricing and learning: Historical origins, current research, and new directions

Dynamic pricing and learning: Historical origins, current research, and new directions

Dynamic Pricing and Learning: Historical Origins, Current Research, and New Directions

List pricing versus dynamic pricing: Impact on the revenue risk

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