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17 December 2020 Internal Market Strategy of Offshore Oil Enterprises Based on Amoeba Operation Model
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Abstract

Hong, Y.; Li, Z.; Liu, Q., and Liu, S., 2020. Internal market strategy of offshore oil enterprises based on amoeba operation model. In: Liu, X. and Zhao, L. (eds.), Today's Modern Coastal Society: Technical and Sociological Aspects of Coastal Research. Journal of Coastal Research, Special Issue No. 111, pp. 209–213. Coconut Creek (Florida), ISSN 0749-0208.

With the rapid advance in technology and management innovation, many improvements have been made to the marine energy sector, which brings both opportunities and challenges. The improvement in oil industry maturity and global transaction makes the offshore oil market more competitive. Faced with this situation, offshore oil enterprises in the marine energy sector have to improve their management, operation efficiency, and tap endogenous growth potential. Amoeba Operation Model, as an application of internal marketization theory, has been proved to be effective against mobilizing the vitality of employees within the enterprise, improving business benefits, as well as solving big company diseases. Consequently, this study analyzes the internal marketization theory and the applicability of Amoeba Operation Model in offshore oil enterprises. The study puts forward several key points for offshore oil enterprises' usage of Amoeba Operation Model, including: business unit division, accounting and settlement relationships establishment, asset resources and budgets allocation, evaluation system and mechanism establishment, human resources and team leader selection, as well as cultural acknowledgment.

©Coastal Education and Research Foundation, Inc. 2020
Ying Hong, Zheng Li, Qiang Liu, and Siyu Liu "Internal Market Strategy of Offshore Oil Enterprises Based on Amoeba Operation Model," Journal of Coastal Research 111(sp1), 209-213, (17 December 2020). https://doi.org/10.2112/JCR-SI111-036.1
Received: 23 March 2020; Accepted: 27 July 2020; Published: 17 December 2020
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