Estimating the Demand for Service Bundles under Three-Part Tariffs
The practice of selling multiple products or services under nonlinear pricing has a long history in the business community. Consumers may face demand uncertainty when choosing a service plan, and preferences for multiple products or services may be inter-dependent. To examine a demand system with these features, we construct a two-stage discrete/continuous choice model for service bundle demand under three-part tariffs, allowing for interactive utility and preference correlations. Implementing a piecewise maximization approach to the consumer utility maximization problem, which is non-differentiable under three-part tariffs, we estimate the model via simulated method of moments. We then apply our model to data from a major wireless service provider in China. Finally, our counterfactual analysis simulates outcomes under three-part tariffs with interchangeable units. Compared to existing tariffs, the proposed ones contain fewer instruments without a significant loss of revenue. We also illustrate the implications of incorporating ex-post usage shocks in model estimates, elasticities and counterfactual outcomes
Year of publication: |
2019
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Authors: | Chen, Liang |
Other Persons: | Luo, Yao (contributor) ; Xiao, Ping (contributor) |
Publisher: |
[2019]: [S.l.] : SSRN |
Subject: | Leistungsbündel | Bundling strategy | Nachfrage | Demand | Theorie | Theory | Schätzung | Estimation | Preismanagement | Pricing strategy | Dienstleistung | Services |
Saved in:
freely available
Extent: | 1 Online-Ressource (52 p) |
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Type of publication: | Book / Working Paper |
Language: | English |
Notes: | Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments March 17, 2019 erstellt |
Other identifiers: | 10.2139/ssrn.3353982 [DOI] |
Classification: | L11 - Production, Pricing, and Market Structure Size; Size Distribution of Firms ; L96 - Telecommunications |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10012890524
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