Contribution to supply chain management and incentive modeling with application from the upstream oil and gas industry

Abstract

The general subject of this thesis is incentive modeling related to inter-organizational relationships and supply chain management in the oil and gas industry. More specifically, it ncludes an embedded multiple case study and outlines five of the single most important challenges to overcome in inter-organizational relationships in the integrated operations environment. Further, it analyzes and optimizes the value of incentive-based contracts with risks and rewards. The thesis addresses the issues and challenges related to inter-organizational relationships, supply chain management and incentive modeling. The main objectives for this thesis are to study the inter-organizational relationships and supply chain management in the oil and gas industry and develop an incentive-based model for better collaboration through the dynamical gain and release of resources between the involved parties. In addition, the aims of the thesis are to: • Study the relationships between the involved parties in the inter-organizational relationship context and present the five most important findings.

• Analyze the differences between a fixed price contract and an incentive-based contract with risk (a punishment for lower performance than agreed) and reward (benefit for better performance than agreed). This will occur by: o Performing a joint welfare analysis between the operator (principal) and service provider (agent); and o Conducting an individual profit maximization analysis between the operator and service provider

• Optimize the gain and release of resources in an inter-organizational relationship setting between the operator and service providers, and between the service providers through balancing payment and contribution between the parties given the following conditions: a social choice function, incentive compatibility, participation constraints and implementing a revelation principle. The thesis consists of two parts. Part I outlines and provides the used theories and summarizes part II. Further part I discusses the relationship between the literature and the main research questions and objectives and relates the theory to the findings in part II. Part II includes papers that address several topics related to the research questions and objectives in the thesis. Part II is seen as the main scientific contribution to the thesis. Its main contributions are as follows: Paper 1, Sund, K. A. and Bratvold, R. B. (2008) Integrated operations: How effective is the current relationship between operating companies and suppliers? Proceedings of SPE Intelligent Energy Conference and Exhibition, Amsterdam, The Netherlands. Here, we focus on improving collaboration between operators and suppliers. This offers perhaps the greatest challenge and, we believe, the greatest potential for achieving the much anticipated value creation from integrated operations. We contribute to this by identifying the key disconnects between operating companies and suppliers. We found the key disconnects with the development and use of an embedded multiple case study, focusing the inter-organizational relationships among one large operator, three large service providers and several small service providers on the Norwegian Continental Shelf. Paper 2, Sund, K. A. (2008) Developing New Resources: How to Gain Dynamic Capabilities and Competitive Advantages from Integrated Operations in the Upstream Oil & Gas Industry. Proceedings of The Third Annual Meeting of Smart Fields Consortium, Stanford University, California, USA. I found that selected companies in the oil and gas industry could use incentive-based contracts with risks and rewards to bring about competitive advantages and dynamic capability. This is gained through better project planning and execution, better information sharing, the avoidance of goal incongruence, the avoidance of inappropriate key performance indicators and the avoidance of suboptimal resource allocation. The findings were obtained using an embedded multiple case study. Paper 3, Sund, K. A. and Hausken, K. (2010) Fixed Price Contract Versus Incentive-Based Contract in the Oil and Gas Industry. Submitted for possible publication in the International Journal of Global Energy Issues (IJGEI). We outline how the incentive-based contract and the fixed price contract affect the profits and time usage differently. Both actors prefer incentive-based contracts when the project is completed in less than the estimated time and the service provider’s variable income is low, or the project is completed in more than the estimated time and the punishment is intermediate. The operator prefers fixed price contracts and the service provider prefers incentive-based contracts when the project is completed in less than the estimated time and the service provider’s variable income is high, or the project is completed in more than the estimated time and the punishment is lenient. The operator prefers incentive-based contracts and the service provider prefers fixed price contracts when the project is completed in more than the estimated time and the punishment is harsh. Both actors never jointly prefer fixed price contracts. The two actors collectively always prefer incentive-based contracts. These results were obtained with an individual maximization and a joint welfare analysis. We find the results remarkable given the current prevalence of fixed price contracts. The result follows since costs associated with moral hazard, adverse selection, monitoring and coordination decrease with the use of incentive-based contracts. Paper 4, Sund K. A. (2010) Dynamic Resource Allocation with Self-Interested Agents in the Upstream Oil & Gas Industry. Accepted for publication in the Journal of Operations and Supply Chain Management (JOSCM), 3(2), 78-97. This paper analyzes resource allocation between principal–agent and agent–agent in the upstream oil and gas industry. I incorporate the parties’ preferences in a principal–agent model. Further, I optimize the resource allocation between the parties because they are self-interested with the use of incentive-based contracts with risks and rewards. My optimization determines that to realize the highest profit, the principal and the involved agents should avoid any agents becoming dominant. Hence, the volume of sourced items from the agents should not vary too much. I further outline the on-boarding process of new agents in the network. In the end, I outline how the network needs to compensate for the potential loss of income for some of the agents if the network should fulfill the incentive-compatibility condition and participation constraint and ensure that the network evolves positively.