Value chain collaboration and coordination

今天，世界在环境、经济和政治方面发生了巨大而迅速的变化，以建立可持续的生物经济。此外，加拿大已承诺到2030年将温室气体排放量减少30%，以满足巴黎协定。为了实现这一雄心勃勃的目标，加拿大的自然资源发挥着重要作用。自然资源价值链（VC）包括多个工业部门，包括森林和农业等可再生能源以及矿产等不可再生能源。这些复杂的风险投资涉及许多公共和私人组织，例如，这些组织由社会经济、技术和环境力量驱动，确定了一系列目标，尽管它们可能有共同的目标，但这些目标往往相互冲突。 该提案的长期目标是开发工程分析，以实现对自然资源风险投资的有效和可持续管理，为社会带来所有潜在价值。短期目标是开发决策工具，使风险投资的运输部分的利益相关者之间能够进行协作。合作已表明可将成本和温室气体减少5-15%，但找到支持这一点的机制至关重要。一旦知道了供给点和需求点，运输计划如下。首先，找到最佳路线;这考虑了距离，油耗，时间等方面，但也考虑了安全性和压力。第二，有一个支付的路线，通常遵循一个简单的商定公式。然而，付款是平均平衡的，但在详细的路线水平上，付款并不反映实际成本。原因是，例如，安全和压力等因素不是成本驱动因素，燃料消耗也没有明确包括在内。只要所有路由都属于一家公司，这种方法就有效。然而，当有合作时，公司之间的路线混合，付款变得不公平。因此，许多潜在的合作没有付诸实施。确定了一套工作包，以满足短期目标，这也创造了一个激励的研究环境，多学科的研究培训的HQP，以满足社会的挑战。第一部分是专注于开发无偏见和透明的分析工具，以建立运输模型，基本上将复杂和多目标的路线规划与支付原则相结合。这将使一个支持和激励利益相关者之间合作的工业标准成为可能。第二部分着重于各种机制和费用分摊分配，以使合作伙伴能够在更复杂的情况下开展合作，供应或需求的季节性波动或运营执行的不同效率。最后，我们提出了一个决策剧场，它是可能的，在实践中实施和分析协作规划。

Today, there are large and rapid changes in the world on the environmental, economic and political fronts to establish a sustainable bioeconomy. Also, Canada has committed to reduce its GHG emissions by 30% until 2030 in order to meet the Paris Agreement. To meet this ambitious target, Canadas natural resources play an important role. Natural resources value chains (VCs) include multiple industrial sectors including renewables such as forests and agriculture, as well as non-renewables such as minerals. These complex VCs involve many public and private organisations, e.g., small and large private companies, governments, First Nations communities, hunters, and tourist representatives, which are driven by socio-economical, technological and environmental forces defining a set of objectives that often are conflicting although they may share common goals. The long-term objective of this proposal is to develop engineering analytics to enable an efficient and sustainable management of natural resource VCs for all potential values to society. The short-term goals are to develop decision tools to enable collaboration among stakeholders in the transportation part of the VC. Collaboration has shown to reduce costs and GHG with 5-15% but it is critical to find mechanisms to support this. Once supply and demand points are known, the transportation planning is as follows. First, the best possible route is found; this considers aspects such as distance, fuel consumption, time but also safety and stress. Second, there is a payment for the route which typically follow a simple agreed formula. However, the payment is balanced in average but on a detailed route level, the payment does not reflect the actual cost. Reason are, e.g., that factors like safety and stress are not cost drivers and fuel consumption is not explicitly included. The approach does work as long as all routes belongs to one company. However, when there is a collaboration, routes are mixed between the companies and payments become unfair. As a result, many potential collaborations are not put into practice. A set of work packages are identified to meet the short-term objectives which also create a stimulating research environment for multidisciplinary research training of HQPs to meet societal challenges. The first part is focusing on developing non-biased and transparent analytics tools to establish transport models that essentially integrates the complex and multi-objective route planning with the payment principles. This will enable an industrial standard that supports and motivates collaboration among stakeholders. The second part focus on mechanisms and cost sharing allocations to enable partners to collaborate despite more complex situations, e.g., seasonal fluctuations in supply or demand or different efficiencies in the operational execution. Finally, we propose a decision theatre where it is possible to implement and analyze collaborative planning in practice.