Anticipating Strategic Risks by Fuzzy-based Scenario Monitoring on the Example of Oil Price Developments
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TY - BOOK
T1 - Anticipating Strategic Risks by Fuzzy-based Scenario Monitoring on the Example of Oil Price Developments
AU - Frieß, Bernhard Josef
N1 - no embargo
PY - 2009
Y1 - 2009
N2 - The increasing dynamism in the business environment enlarges the gap between required and available response time to external changes. Therefore the anticipation of strategic risks at an early stage is essential especially in turbulent times. The petroleum upstream industry faces an unstable environment which creates various strategic risks. Aside to the economic crisis the opportunistic behaviour concerning the access to reserves or the emerging national oil companies are key concerns of international oil companies. Internally cost controlling and the influence of changing fiscal terms, and the operations in more and more marginal and mature fields represent other challenges. An even higher uncertainty is initiated by the unpredictability of the oil price, which is primar-ily responsible for the economic wealth of an oil company and determines their strategies and project decisions. Scenarios are adequate methods to deal with uncertainty at this ex-tent and provide a basis for the preparation of the business for future developments of the oil price. To take advantage of oil price scenarios it is necessary to monitor them by a comparison with actual developments. Instead of waiting until a certain limit for an influencing factor is achieved it is preferable to anticipate also moderate changes which indicate the develop-ment towards a specific scenario path. The application of fuzzy models for this purpose allow the representation of the underlying system and disclose the membership of the ac-tual situation to the scenario paths even in the case of marginal changes. As a consequence the combination of the two methods represents an improvement of strategic early warning systems and transforms uncertainty to a determined risk.
AB - The increasing dynamism in the business environment enlarges the gap between required and available response time to external changes. Therefore the anticipation of strategic risks at an early stage is essential especially in turbulent times. The petroleum upstream industry faces an unstable environment which creates various strategic risks. Aside to the economic crisis the opportunistic behaviour concerning the access to reserves or the emerging national oil companies are key concerns of international oil companies. Internally cost controlling and the influence of changing fiscal terms, and the operations in more and more marginal and mature fields represent other challenges. An even higher uncertainty is initiated by the unpredictability of the oil price, which is primar-ily responsible for the economic wealth of an oil company and determines their strategies and project decisions. Scenarios are adequate methods to deal with uncertainty at this ex-tent and provide a basis for the preparation of the business for future developments of the oil price. To take advantage of oil price scenarios it is necessary to monitor them by a comparison with actual developments. Instead of waiting until a certain limit for an influencing factor is achieved it is preferable to anticipate also moderate changes which indicate the develop-ment towards a specific scenario path. The application of fuzzy models for this purpose allow the representation of the underlying system and disclose the membership of the ac-tual situation to the scenario paths even in the case of marginal changes. As a consequence the combination of the two methods represents an improvement of strategic early warning systems and transforms uncertainty to a determined risk.
KW - strategisches Management
KW - strategisches Risikomanagement
KW - Erdölindustrie
KW - strategische Frühaufklärung
KW - Szenariomanagement
KW - Fuzzy Logik
KW - strategic management
KW - strategic risk management
KW - petroleum opstream industry
KW - strategic early warning sSystem
KW - scenario management
KW - Fuzzy Logic
M3 - Doctoral Thesis
ER -