Price Strategy Implementation

Research output: Contribution to journalArticleAcademicpeer-review

3 Citations (Scopus)

Abstract

Consider a situation in which a company sells several different items to a set of customers. However, the company is not satisfied with the current pricing strategy and wishes to implement new prices for its items. Implementing these new prices in one single step might not be desirable, for example, because of the change in contract prices for the customers. Therefore, the company changes the prices gradually, such that the prices charged to a subset of the customers, the target market, do not differ too much from one period to the next. We propose a polynomial time algorithm to implement the new prices in the minimum number of time periods needed, given that the prices charged to the customers in the target market increase by at most a factor 1+delta, for a given delta > 0. Furthermore, we address the problem of maximizing the overall revenue during the price implementation over a given time horizon. For this problem, we describe a dynamic program for the case of integer price vectors, and a local search algorithm for arbitrary prices. Also, we present a mixed integer programming formulation for this problem and apply our algorithms in a practical study.

Original languageEnglish
Pages (from-to)420-426
Number of pages7
JournalComputers & Operations Research
Volume38
Issue number2
DOIs
Publication statusPublished - Feb 2011

Keywords

  • Pricing problems
  • Computational complexity
  • Local search
  • Mixed integer program

Cite this

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title = "Price Strategy Implementation",
abstract = "Consider a situation in which a company sells several different items to a set of customers. However, the company is not satisfied with the current pricing strategy and wishes to implement new prices for its items. Implementing these new prices in one single step might not be desirable, for example, because of the change in contract prices for the customers. Therefore, the company changes the prices gradually, such that the prices charged to a subset of the customers, the target market, do not differ too much from one period to the next. We propose a polynomial time algorithm to implement the new prices in the minimum number of time periods needed, given that the prices charged to the customers in the target market increase by at most a factor 1+delta, for a given delta > 0. Furthermore, we address the problem of maximizing the overall revenue during the price implementation over a given time horizon. For this problem, we describe a dynamic program for the case of integer price vectors, and a local search algorithm for arbitrary prices. Also, we present a mixed integer programming formulation for this problem and apply our algorithms in a practical study.",
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Price Strategy Implementation. / Berger, A.; Grigoriev, A.; van Loon, J.

In: Computers & Operations Research, Vol. 38, No. 2, 02.2011, p. 420-426.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Price Strategy Implementation

AU - Berger, A.

AU - Grigoriev, A.

AU - van Loon, J.

PY - 2011/2

Y1 - 2011/2

N2 - Consider a situation in which a company sells several different items to a set of customers. However, the company is not satisfied with the current pricing strategy and wishes to implement new prices for its items. Implementing these new prices in one single step might not be desirable, for example, because of the change in contract prices for the customers. Therefore, the company changes the prices gradually, such that the prices charged to a subset of the customers, the target market, do not differ too much from one period to the next. We propose a polynomial time algorithm to implement the new prices in the minimum number of time periods needed, given that the prices charged to the customers in the target market increase by at most a factor 1+delta, for a given delta > 0. Furthermore, we address the problem of maximizing the overall revenue during the price implementation over a given time horizon. For this problem, we describe a dynamic program for the case of integer price vectors, and a local search algorithm for arbitrary prices. Also, we present a mixed integer programming formulation for this problem and apply our algorithms in a practical study.

AB - Consider a situation in which a company sells several different items to a set of customers. However, the company is not satisfied with the current pricing strategy and wishes to implement new prices for its items. Implementing these new prices in one single step might not be desirable, for example, because of the change in contract prices for the customers. Therefore, the company changes the prices gradually, such that the prices charged to a subset of the customers, the target market, do not differ too much from one period to the next. We propose a polynomial time algorithm to implement the new prices in the minimum number of time periods needed, given that the prices charged to the customers in the target market increase by at most a factor 1+delta, for a given delta > 0. Furthermore, we address the problem of maximizing the overall revenue during the price implementation over a given time horizon. For this problem, we describe a dynamic program for the case of integer price vectors, and a local search algorithm for arbitrary prices. Also, we present a mixed integer programming formulation for this problem and apply our algorithms in a practical study.

KW - Pricing problems

KW - Computational complexity

KW - Local search

KW - Mixed integer program

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JF - Computers & Operations Research

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