When decision support systems fail: Insights for strategic information systems from Formula 1
When decision support systems fail: Insights for strategic information systems from Formula 1
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DOI：
10.1016/j.jsis.2018.03.002
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发表时间：
2018-09-01
影响因子：
7
通讯作者：
Haefliger, Stefan
中科院分区：
文献类型：
--
作者：
Aversa, Paolo;Cabantous, Laure;Haefliger, Stefan
决策支持系统 (DSS) 是复杂的工具，越来越多地利用大数据，用于设计和实施个人和组织级别的战略决策。然而，当组织过度依赖其潜力时，结果可能是决策失败，特别是当这些工具在高压和动荡的条件下应用时。片面的理解和单一的解释会阻碍从失败中学习。我们从实践的角度出发，研究了一级方程式赛车中战略失败的标志性案例。我们的方法整合了决策者以及组织和物质环境，确定了战略失败的三个相互关联的来源，值得决策者使用决策支持系统和大数据进行调查：（1）决策的情境性质和可供性； (2)决策认知的分布式性质； (3) DSS 的性能。我们概述了具体的研究问题及其对公司绩效和竞争优势的影响。最后，我们提出了一个议程，可以帮助及时缩小战略信息系统研究的差距。
Decision support systems (DSS) are sophisticated tools that increasingly take advantage of big data and are used to design and implement individual- and organization-level strategic decisions. Yet, when organizations excessively rely on their potential the outcome may be decision-making failure, particularly when such tools are applied under high pressure and turbulent conditions. Partial understanding and unidimensional interpretation can prevent learning from failure. Building on a practice perspective, we study an iconic case of strategic failure in Formula 1 racing. Our approach, which integrates the decision maker as well as the organizational and material context, identifies three interrelated sources of strategic failure that are worth investigation for decision-makers using DSS and big data: (1) the situated nature and affordances of decision-making; (2) the distributed nature of cognition in decision-making; and (3) the performativity of the DSS. We outline specific research questions and their implications for firm performance and competitive advantage. Finally, we advance an agenda that can help close timely gaps in strategic IS research.