Pricing local search engines for company websites

  • Authors:
  • Xun Liang;Yangbo He;Rong-Chang Chen;Jian Yang

  • Affiliations:
  • Institute of Computer Science and Technology, Peking University, Beijing 100871, China and Department of Economics and Operations Research, Stanford University, Palo Alto, CA 94305, USA;Institute of Computer Science and Technology, Peking University, Beijing 100871, China;Department of Logistics Engineering and Management, National Taichung Institute of Technology;Institute of Computer Science and Technology, Peking University, Beijing 100871, China

  • Venue:
  • Electronic Commerce Research and Applications
  • Year:
  • 2008

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Abstract

Ever since the dramatic boom of the Internet, web search engines have appealed to both researchers' and developers' attention to a noticeable pitch. In order to enhance the website efficiency, a number of companies rent the company-wide local search engines from the search engine providers. Since web service renting serves as a promising alternative of web service purchase within the web industrial framework, how to effectively price such kind of search engines becomes an important as well as impending issue, with which practitioners and researchers confront. In this paper, we present a pricing model, which is based on the discrete-time independent incremental process, for the local search engines of the company website. The stopping time is defined in this work and the expected revenue for the web-search-engine providers over the rental horizon is also derived. Due to the considerable complexity and difficulty to obtaining an analytical solution for estimation of the expected revenue, the optimal monthly rental is discussed and exemplified through empirical experiments. By maximizing the revenue, two different strategies are investigated by allowing different initial lock-in periods and offering a coupon for waiving certain amount of fee for initial use. The experiments illustrate the best rental and sale price scenarios.