Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/330610 
Authors: 
Year of Publication: 
2024
Citation: 
[Journal:] Journal of Revenue and Pricing Management [ISSN:] 1477-657X [Volume:] 24 [Issue:] 5 [Publisher:] Palgrave Macmillan [Place:] London [Year:] 2024 [Pages:] 449-453
Publisher: 
Palgrave Macmillan, London
Abstract: 
Nonlinear pricing is a form of price differentiation in which the average price per unit is a nonlinear decreasing function of demand. It is widely used in many industries such as telecommunications or utilities. Rationales for using nonlinear pricing are manifold, ranging from taking account of decreasing marginal utilities of customers to building up switching costs. As with other forms of price differentiation, the potential for capturing consumer surplus and increasing profits is considerable. Nonlinear pricing schemes come in various forms, such as discounts, buy-one-get-one, power shopping, two-part tariffs, and block-tariffs. All these forms are well known. However, little is said about how exactly to systematically derive an optimal nonlinear pricing scheme. In this paper, I propose a new systematic empirical approach using a modified least deviations Spline regression-estimator.
Subjects: 
Price differentiation
Nonlinear pricing
Optimization
Spline regression
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
Document Version: 
Published Version

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