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Predictive analytics is impacting many diverse areas, ranging from baseball and epidemiology to forecasting and customer relationship management. Manufacturers, retailers, software companies, and consultants are creatively discovering new applications of big data using predictive analytics in supply chain management and logistics. In practice, predictive analytics is generally atheoretical; however, we develop a 2 × 2 model to explain the role of predictive analytics in the theory development process. This 2 × 2 model shows that in our discipline we have traditionally taken one path to theory development, but that predictive analytics can be a salient component of a comprehensive theory development process. The model points to a number of research questions that need to be addressed by our research community. These questions are not just highly relevant to the academic community but also in urgent need of answers to help practitioners execute the right strategies with greater precision and efficiency. We also discuss how one disruptive trend, the maker movement, changes the nature of who the producers are in the supply chain, making big data even more valuable. As we engage in higher levels of dialogue we will be able to make meaningful progress addressing these vital research topics.  相似文献   
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以色列是世界上技术创新和投资活动最为活跃的地区之一,其民用科技研发投入占GDP的比重高居世界第一。科技工作实行首席科学家负责制,主要政府部门设有首席科学家办公室。本文对2010年以色列科技发展的重大政策动向、研究与开发支出、新的科技统计数据与指标、知识产权保护、高科技产业发展以及科技成果和国际科技合作动态等情况进行了综合评述。  相似文献   
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While data science, predictive analytics, and big data have been frequently used buzzwords, rigorous academic investigations into these areas are just emerging. In this forward thinking article, we discuss the results of a recent large‐scale survey on these topics among supply chain management (SCM) professionals, complemented with our experiences in developing, implementing, and administering one of the first master's degree programs in predictive analytics. As such, we effectively provide an assessment of the current state of the field via a large‐scale survey, and offer insight into its future potential via the discussion of how a research university is training next‐generation data scientists. Specifically, we report on the current use of predictive analytics in SCM and the underlying motivations, as well as perceived benefits and barriers. In addition, we highlight skills desired for successful data scientists, and provide illustrations of how predictive analytics can be implemented in the curriculum. Relying on one of the largest data sets of predictive analytics users in SCM collected to date and our experiences with one of the first master's degree programs in predictive analytics, it is our intent to provide a timely assessment of the field, illustrate its future potential, and motivate additional research and pedagogical advancements in this domain.  相似文献   
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余松烈院士是我国现代小麦栽培学奠基人。本文通过解读余松烈院士汇报工作、反映问题、献言献策的各类信件,从侧面反映其在小麦栽培学研究领域精益求精、刻苦钻研的工作状态,展示其为小麦产业振兴上下奔走、鞠躬尽瘁的责任意识,凸显其全心全意为国为民的科学家精神。  相似文献   
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