Facility location planning to mitigate strategic conflict in joint operations

S. Chowdhury
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Abstract

Purpose This paper aims to deal with a real-life strategic conflict in joint operations (JOs) for facility location decision and planning in an oil and gas field that stretches over two countries and tries to develop a basis for mitigating such conflict. Design/methodology/approach This paper develops a novel approach using integer linear programming (ILP) to determine optimal facility location considering technical, economic and environmental factors. Strategic decision-making in JOs is also influenced by business priorities of individual partner, sociopolitical issues and other covert factors. The cost-related quantitative factors are normalized using inverse normalization function as these are to be minimized, and qualitative factors that are multi-decision-making criteria are maximized, thus transforming both qualitative and quantitative factors as a single objective of maximization in ILP model. Findings The model identifies the most suitable facility location based on a wide range of factors that would provide maximum benefit in the long term, which will help decision-makers and managers. Research limitations/implications The model can be expanded incorporating other quantitative and qualitative factors such as tax incentives by the government, local bodies and government regulations. Practical implications The applicability of the model is not limited to JOs or oil/gas field, but is applicable to a wide range of sectors. Originality/value The model is transparent and based on rational and scientific basis, which would help in building consensus among the dissenting parties and aid in mitigating strategic conflict. Such type of model for mitigating strategic conflict has not been reported/used before.
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减少联合作战中战略冲突的设施选址规划
目的本文旨在处理两国油气田设施选址决策和规划联合行动中的现实战略冲突,并试图为缓解此类冲突奠定基础。设计/方法论/方法本文开发了一种新的方法,使用整数线性规划(ILP)来确定考虑技术、经济和环境因素的最佳设施位置。JO的战略决策也受到个人合作伙伴的业务优先级、社会政治问题和其他隐蔽因素的影响。使用逆归一化函数对成本相关的定量因素进行归一化,因为这些因素要最小化,并且作为多决策标准的定性因素被最大化,从而将定性和定量因素转换为ILP模型中最大化的单个目标。发现该模型根据一系列因素确定了最合适的设施位置,这些因素将在长期内提供最大效益,这将有助于决策者和管理者。研究局限性/含义该模型可以扩展,包括其他定量和定性因素,如政府、地方机构和政府法规的税收优惠。实际含义该模型的适用性不仅限于JO或油气田,而且适用于广泛的行业。独创性/价值该模型是透明的,基于理性和科学的基础,这将有助于在持不同意见的各方之间建立共识,并有助于缓解战略冲突。这种缓解战略冲突的模式以前从未报告/使用过。
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来源期刊
CiteScore
9.40
自引率
0.00%
发文量
31
期刊介绍: The Journal of Global Operations and Strategic Sourcing aims to foster and lead the international debate on global operations and strategic sourcing. It provides a central, authoritative and independent forum for the critical evaluation and dissemination of research and development, applications, processes and current practices relating to sourcing strategically for products, services, competences and resources on a global scale and to designing, implementing and managing the resulting global operations. Journal of Global Operations and Strategic Sourcing places a strong emphasis on applied research with relevant implications for both knowledge and practice. Also, the journal aims to facilitate the exchange of ideas and opinions on research projects and issues. As such, on top of a standard section publishing scientific articles, there will be two additional sections: "The Industry ViewPoint": in this section, industrial practitioners from around the world will be invited (max 2 contributions per issue) to present their point of view on a relevant subject area. This is intended to give the journal not just an academic focus, but a practical focus as well. In this way, we intend to reflect a trend that has characterised the past few decades, where interests and initiatives in research, academia and industry have been more and more converging to the point of collaborative relationships being a common practice. "Research Updates - Executive Summaries". In this section, researchers around the world will be given the opportunity to present their research projects in the area of global sourcing and outsourcing by means of an executive summary of their project. This will increase awareness of the on-going research projects in the area and it will attract interest from industry.
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