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Agent-Based Simulations of the Software Market under Different Pricing Schemes for Software-as-a-Service and Perpetual Software

Author

Listed:
  • Juthasit Rohitratana

    () (Technology Management, Economics, and Policy Program (TEMEP), Seoul National University)

  • Jorn Altmann

    () (Technology Management, Economics, and Policy Program (TEMEP), Seoul National University)

Abstract

In this paper, we present agent-based simulations that model the interactions between software buyers and vendors in a software market that offers Software-as-a-Service (SaaS) and perpetual software (PS) licensing under different pricing schemes. In particular, scenarios are simulated, in which vendor agents dynamically set prices. Customer (or buyer) agents respond to these prices by selecting the software license scheme according to four fundamental criteria using Analytic Hierarchy Process (AHP) as decision support mechanism. These criteria relate to finance, software capability, organization, and vendor. Three pricing schemes are implemented for our simulations: derivative-follower (DF), demand-driven (DD), and competitor-oriented (CO). The results show that DD scheme is the most effective method but hard to implement since it requires perfect knowledge about market conditions. This result is supported through a price sensitivity analysis

Suggested Citation

  • Juthasit Rohitratana & Jorn Altmann, 2010. "Agent-Based Simulations of the Software Market under Different Pricing Schemes for Software-as-a-Service and Perpetual Software," TEMEP Discussion Papers 201064, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Jul 2010.
  • Handle: RePEc:snv:dp2009:201064
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    File URL: ftp://147.46.237.98/DP-64.pdf
    File Function: First version, 2010
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    References listed on IDEAS

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    1. Fu, Feng & Liu, Lianghuan & Wang, Long, 2008. "Empirical analysis of online social networks in the age of Web 2.0," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(2), pages 675-684.
    2. Galeotti, Andrea & Goyal, Sanjeev & Kamphorst, Jurjen, 2006. "Network formation with heterogeneous players," Games and Economic Behavior, Elsevier, vol. 54(2), pages 353-372, February.
    3. Junseok Hwang & Jorn Altmann & Kibae Kim, 2009. "The Structural Evolution of the Web2.0 Service Network," TEMEP Discussion Papers 200914, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Sep 2009.
    4. Wagner, Caroline S. & Leydesdorff, Loet, 2005. "Network structure, self-organization, and the growth of international collaboration in science," Research Policy, Elsevier, vol. 34(10), pages 1608-1618, December.
    5. Galeotti, Andrea & Goyal, Sanjeev & Kamphorst, Jurjen, 2006. "Network formation with heterogeneous players," Games and Economic Behavior, Elsevier, vol. 54(2), pages 353-372, February.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Khin Swe Latt & Jorn Altmann, 2010. "A Cost-Benefit-Based Analytical Model for Finding the Optimal Offering of Software Services," TEMEP Discussion Papers 201070, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Dec 2010.
    2. 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.

    More about this item

    Keywords

    Software-as-a-Service pricing; perpetual software pricing; agent-based simulation; Analytic Hierarchy Process (AHP); dynamic pricing; decision support;

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • 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
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • L23 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Organization of Production
    • 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
    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics

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