{"title":"技术升级与创新权衡的分析模型","authors":"C. Liu, Young Chan","doi":"10.4018/ijban.288515","DOIUrl":null,"url":null,"abstract":"We propose two analytical models to characterize the relationship between technological upgrading and innovation in the oil & gas industry. The first one is an “optimization model” which focuses on the trade-offs between profit maximization and environmental compliance cost. The other has been developed based on “predator-prey” model which captures the dynamics of biological systems. Our study contributes to the strategic planning process for sustainable development by providing the insight that optimal allocation process is determined by multiple operational factors, including a firm’s competitive ranking among its industrial competitors, industrial consent on the concurrent rate of return on capital investment, the projected demand of oil & gas in future, and a change in environmental compliance cost. Further, we add to the robustness of the optimal allocation process by providing binding conditions of the set of solutions.","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analytical Models to Characterize Trade-Offs Between Technological Upgrading and Innovation\",\"authors\":\"C. Liu, Young Chan\",\"doi\":\"10.4018/ijban.288515\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We propose two analytical models to characterize the relationship between technological upgrading and innovation in the oil & gas industry. The first one is an “optimization model” which focuses on the trade-offs between profit maximization and environmental compliance cost. The other has been developed based on “predator-prey” model which captures the dynamics of biological systems. Our study contributes to the strategic planning process for sustainable development by providing the insight that optimal allocation process is determined by multiple operational factors, including a firm’s competitive ranking among its industrial competitors, industrial consent on the concurrent rate of return on capital investment, the projected demand of oil & gas in future, and a change in environmental compliance cost. Further, we add to the robustness of the optimal allocation process by providing binding conditions of the set of solutions.\",\"PeriodicalId\":0,\"journal\":{\"name\":\"\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/ijban.288515\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijban.288515","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Analytical Models to Characterize Trade-Offs Between Technological Upgrading and Innovation
We propose two analytical models to characterize the relationship between technological upgrading and innovation in the oil & gas industry. The first one is an “optimization model” which focuses on the trade-offs between profit maximization and environmental compliance cost. The other has been developed based on “predator-prey” model which captures the dynamics of biological systems. Our study contributes to the strategic planning process for sustainable development by providing the insight that optimal allocation process is determined by multiple operational factors, including a firm’s competitive ranking among its industrial competitors, industrial consent on the concurrent rate of return on capital investment, the projected demand of oil & gas in future, and a change in environmental compliance cost. Further, we add to the robustness of the optimal allocation process by providing binding conditions of the set of solutions.