Information Processing In Firms

企业中的信息处理

• 批准号: 9223917
• 负责人: Timothy Van Zandt
• 金额: $ 6.76万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1993
• 资助国家: 美国
• 起止时间: 1993-03-15 至 1995-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9223917&HistoricalAwards=false
• 关键词: Information; Processing; Firms

The study of returns to scale in firms has traditionally focused on technological returns to scale in the production process. However, as the scale of a firm's production process grows, so does its administrative apparatus. The task of much of this administrative apparatus is information processing, including communication and decision-making. This task is important to the performance of the firm, and hence relevant to returns to scale. This research uses a model of stochastic control with explicit and costly computation of policies, coupled with a parallel processing model of information processing in organizations. It is expected that a variety of results will be obtained for which returns depend on assumptions on the statistical properties of the information to be processed and on the loss function. Further studies include a locational model of scale, explicit models of the firm with scale measured by physical inputs and outputs rather than by the informational size of the environment, and a distributed computational model of information processing. This research works across the frontier between computer science and economics. It relates information processing and organization design and function, and will enhance our understanding of a problem of long standing and great importance in economics.

传统上，对企业规模收益的研究主要集中在 生产过程中的技术回报。 然而，在这方面， 随着企业生产过程规模的扩大， 行政机构 这种行政管理的任务 设备是信息处理，包括通信和 决策的 这项任务对执行 公司，因此与规模收益相关。 本研究使用一个模型的随机控制与明确的， 策略计算成本高，再加上并行处理 组织中的信息处理模型。 预计 将获得各种结果，而回报取决于 对信息统计特性的假设， 处理和损失函数。 进一步的研究包括 规模区位模型，企业规模的显性模型 以实际投入和产出衡量，而不是以 环境的信息大小，以及分布式 信息处理的计算模型 这项研究跨越了计算机科学和 和经济学。 它涉及信息处理和组织 设计和功能，并将加强我们对一个 这是经济学中一个长期存在的重要问题。