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Impact of Pricing Schemes on a Market for Software-as-a-Service and Perpetual Software

Author

Listed:
  • Juthasit Rohitratana

    (TEMEP, College of Engineering, Seoul National University)

  • Jorn Altmann

    (TEMEP, College of Engineering, Seoul National University)

Abstract

In 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.

Suggested Citation

  • Juthasit Rohitratana & Jorn Altmann, 2012. "Impact of Pricing Schemes on a Market for Software-as-a-Service and Perpetual Software," TEMEP Discussion Papers 201288, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Mar 2012.
    • Handle: RePEc:snv:dp2009:201288
    as

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    File URL: http://temep-repec.my-groups.de/DP-88.pdf
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    References listed on IDEAS

    as
    1. Marcel Risch & Jorn Altmann, 2009. "Enabling Open Cloud Markets Through WS-Agreement Extensions," TEMEP Discussion Papers 200920, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Oct 2009.
    2. Harikesh Nair, 2007. "Intertemporal price discrimination with forward-looking consumers: Application to the US market for console video-games," Quantitative Marketing and Economics (QME), Springer, vol. 5(3), pages 239-292, September.
    3. Sonja Lehmann & Peter Buxmann, 2009. "Pricing Strategies of Software Vendors," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 1(6), pages 452-462, December.
    4. Jorn Altmann & Juthasit Rohitratana, 2009. "Software Resource Management Considering the Interrelation between Explicit Cost, Energy Consumption, and Implicit Cost: A Decision Support Model for IT Managers," TEMEP Discussion Papers 200936, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Nov 2009.
    5. Yasushi Masuda & Seungjin Whang, 1999. "Dynamic Pricing for Network Service: Equilibrium and Stability," Management Science, INFORMS, vol. 45(6), pages 857-869, June.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Jhih-Hua Jhang-Li & Cheng-Wei Chang, 2017. "Analyzing the operation of cloud supply chain: adoption barriers and business model," Electronic Commerce Research, Springer, vol. 17(4), pages 627-660, December.
    2. Frank Bodendorf & Manuel Lutz & Jörg Franke, 2021. "Valuation and pricing of software licenses to support supplier–buyer negotiations: A case study in the automotive industry," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(7), pages 1686-1702, October.
    3. Price, Michael & Tamm, Gerrit & Stantchev, Vladimir, 2012. "SaaS marketplaces: Visions from theory and experience from practice," 19th ITS Biennial Conference, Bangkok 2012: Moving Forward with Future Technologies - Opening a Platform for All 72513, International Telecommunications Society (ITS).
    4. In Lee, 2019. "Pricing schemes and profit-maximizing pricing for cloud services," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 18(2), pages 112-122, April.
    5. Luisanna Cocco & Michele Marchesi, 2016. "Modeling and Simulation of the Economics of Mining in the Bitcoin Market," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-31, October.
    6. Netsanet Haile & Jörn Altmann, 2017. "Evaluating Investments in Portability and Interoperability between Software Service Platforms," TEMEP Discussion Papers 2017136, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised May 2017.
    7. Lee, Sang-Gun & Chae, Seung Hoon & Cho, Kyung Min, 2013. "Drivers and inhibitors of SaaS adoption in Korea," International Journal of Information Management, Elsevier, vol. 33(3), pages 429-440.
    8. Kibae Kim & Songhee Kang & Jorn Altmann, 2014. "Cloud Goliath Versus a Federation of Cloud Davids: Survey of Economic Theories on Cloud Federation," TEMEP Discussion Papers 2014117, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Jul 2014.
    9. Netsanet Haile & Jorn Altmann, 2015. "Risk-Benefit-Mediated Impact of Determinants on the Adoption of Cloud Federation," TEMEP Discussion Papers 2015122, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised May 2015.
    10. Abhijit Dutt & Hemant Jain & Sanjeev Kumar, 2018. "Providing Software as a Service: a design decision(s) model," Information Systems and e-Business Management, Springer, vol. 16(2), pages 327-356, May.

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    More about this item

    Keywords

    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.;
    All these keywords.

    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, Pricing, and Design - - - General
    • D45 - Microeconomics - - Market Structure, Pricing, and Design - - - 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; Personnel Economics - - Business Administration - - - IT Management

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