Impact of Pricing Schemes on a Market for Software-as-a-Service and Perpetual Software
AbstractIn this paper, we present an agent-based simulation system that allows modeling the interactions between software buyers and vendors in a software market. The market offers Software-as-a-Service (SaaS) and perpetual software (PS) licenses under different pricing schemes. Four dynamic pricing schemes are analyzed: derivative-follower pricing, demand-driven pricing, skimming pricing, and penetration pricing. Customer (buyer) agents respond to these prices by selecting the most appropriate software license scheme based on four criteria using the Analytic Hierarchy Process (AHP) decision support mechanism. The four decision criteria relate to finance, software capability, organization, and vendor. The simulation results show that the demand-driven pricing scheme is the most effective method but hard to implement since it requires perfect knowledge about market conditions. As an alternative, penetration pricing and skimming pricing could be used. In addition to this, it can be stated that SaaS is most attractive for small enterprises while PS is attractive for large enterprises.
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Bibliographic InfoPaper provided by Seoul National University; Technology Management, Economics, and Policy Program (TEMEP) in its series TEMEP Discussion Papers with number 201288.
Length: 32 pages
Date of creation: Mar 2012
Date of revision: Mar 2012
Publication status: Published in Journal of Future Generation Computer Systems Journal, Elsevier, 2012.
SaaS; Software-as-a-Service pricing; perpetual software pricing; agent-based simulation; Analytic Hierarchy Process (AHP); dynamic pricing; decision support; demand-driven pricing; derivative-follower pricing; penetration pricing; skimming pricing.;
Find related papers by JEL classification:
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
- C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- D40 - Microeconomics - - Market Structure and Pricing - - - General
- D45 - Microeconomics - - Market Structure and Pricing - - - Rationing; Licensing
- D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
- L24 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Contracting Out; Joint Ventures
- L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
- M15 - Business Administration and Business Economics; Marketing; Accounting - - Business Administration - - - IT Management
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-04-17 (All new papers)
- NEP-CMP-2012-04-17 (Computational Economics)
- NEP-IND-2012-04-17 (Industrial Organization)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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Quantitative Marketing and Economics,
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