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Strategic analysis of technology and capacity investments in the liquefied natural gas industry


  • Sönmez, Erkut
  • Kekre, Sunder
  • Scheller-Wolf, Alan
  • Secomandi, Nicola


Energy plays a fundamental role in both manufacturing and services, and natural gas is rapidly becoming a key energy source worldwide. Facilitating this emergence is an expanding network of ocean-going vessels that enable the matching of natural gas supply and demand on a global scale. This is achieved through the transportation of liquefied natural gas (LNG) for eventual regasification at its destination. Until very recently, only one type of technology had been available for transporting and regasifying LNG: Conventional LNG vessels coupled with land based LNG regasification. But it is now possible to transport and regasify LNG onboard special LNG vessels. Companies such as Excelerate Energy and Höegh LNG are currently developing LNG supply chains based on this new technology. Motivated by these developments, we engaged executives at Excelerate Energy to facilitate an investigation of issues related to strategic technology selection, as well as choices around technology configuration and capacity for the incumbent and emerging technologies. The resulting analysis brings to light managerial principles delineating the impact of alternative LNG throughput models on decisions regarding how to deploy each technology option and how to configure and size their capacity. Our findings have additional potential relevance beyond our industry specific analysis.

Suggested Citation

  • Sönmez, Erkut & Kekre, Sunder & Scheller-Wolf, Alan & Secomandi, Nicola, 2013. "Strategic analysis of technology and capacity investments in the liquefied natural gas industry," European Journal of Operational Research, Elsevier, vol. 226(1), pages 100-114.
  • Handle: RePEc:eee:ejores:v:226:y:2013:i:1:p:100-114
    DOI: 10.1016/j.ejor.2012.10.042

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    References listed on IDEAS

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    1. Michal Kaut & Kjetil Midthun & Adrian Werner & Asgeir Tomasgard & Lars Hellemo & Marte Fodstad, 2014. "Multi-horizon stochastic programming," Computational Management Science, Springer, vol. 11(1), pages 179-193, January.


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