An inventory pricing problem

Kincaid, W. M.; Darling, D. A.

doi:10.1016/0022-247x(63)90047-7

Cited by 93 publications

(70 citation statements)

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“…The earliest work concerning dynamic pricing appears to be that of Kincaid and Darling (1963). Since the deregulation of the US airline industry in the 1970s, the research on dynamic pricing continued to grow to provide tools for the industries.…”

Section: Introduction and Overviewmentioning

confidence: 99%

Dynamic price competition with discrete customer choices

Lin

Sibdari

2009

European Journal of Operational Research

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Section: Introduction and Overviewmentioning

confidence: 99%

Dynamic price competition with discrete customer choices

Lin

Sibdari

2009

European Journal of Operational Research

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“…The problem that the Retailer faces corresponds to the widely researched field of markdown optimisation, originally conducted by Kincaid and Darling (1963). Markdown optimisation deals with the problem of maximising expected total revenue by continuously adjusting prices, given that sales may only take place within a finite time horizon (Gallego & Van Ryzin 1994).…”

Section: Introductionmentioning

confidence: 99%

In-season retail sales forecasting using survival models

Hattingh¹,

Uys

2014

ORiON

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A large South African retailer (hereafter referred to as the Retailer) faces the problem of selling out inventory within a specified finite time horizon by dynamically adjusting product prices, and simultaneously maximising revenue. Consumer demand for the Retailer's fashion merchandise is uncertain and the identification of products eligible for markdown is therefore problematic. In order to identify products that should be marked down, the Retailer forecasts future sales of new products. With the aim of improving on the Retailer's current sales forecasting method, this study investigates statistical techniques, viz. classical time series analysis (Holt's smoothing method) and survival analysis. Forecasts are made early in the product life cycle and results are compared to the Retailer's existing forecasting method. Based on the mean squared errors of predictions resulting from each method, the most accurate of the methods investigated is survival analysis.

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“…Kincaid and Darling [7] were the first to study this problem, which they call ''inventory pricing problem'', and to characterize the function that the seller should use to update the price over the horizon. Elfving [3] notices that the special case of a single unit of inventory is similar to what is known as the ''secretary problem'' or the ''best choice problem'' (see [5]), except that the arrivals (of candidates, i.e., potential buyers in our problem) follow a point process and the decision maker has distributional information about the desirability of candidates.…”

Section: Introductionmentioning

confidence: 99%

“…Elfving [3] characterizes the unique curve in the presence of discounting. Stadje [10] derives conditions that are equivalent to those obtained in [7] for pricing a single or multiple units of inventory.…”

Section: Introductionmentioning

confidence: 99%

Performance bounds on optimal fixed prices

Şen¹

2013

Operations Research Letters

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a b s t r a c tWe consider the problem of selling a fixed stock of items over a finite horizon when the buyers arrive following a Poisson process. We obtain a general lower bound on the performance of using a fixed price rather than dynamically adjusting the price. The bound is 63.21% for one unit of inventory, and it improves as the inventory increases. For the one-unit case, we also obtain tight bounds: 89.85% for the constantelasticity and 96.93% for the linear price-response functions.

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An inventory pricing problem

Cited by 93 publications

References 0 publications

Dynamic price competition with discrete customer choices

Dynamic price competition with discrete customer choices

In-season retail sales forecasting using survival models

Performance bounds on optimal fixed prices

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