Enhancing Evidence-based Managerial Decisions through Customized Decision Support: A Neuro-Information Systems' Approach

有效的循证管理决策，无论是个人还是群体，都是组织成功的关键因素;这是一项复杂的任务，涉及对来自各种来源的信息进行搜索、处理、整合和情境化。随着决策者面临过多的数据和管理问题的不断增加，这种复杂性进一步加剧。此外，越来越多的组织决策是在群体环境中做出的，在这种环境中，决策可能会变得两极分化。最后，信息和通信技术以及全球网络的进步，以及与COVID-19相关的限制，增加了虚拟团队中群体决策的普遍性。该研究计划将加强和支持组织中基于证据的管理决策。文献表明，基于证据的决策可以被视为一个动态过程，通过这个过程，决策者（个人或群体），在信息技术（即，决策辅助工具），获取、解释和使用证据作为其组织背景下决策的基础。因此，本研究将联合收割机传统的人机交互研究方法（例如，调查，访谈）和决策科学的专业知识与尖端的神经生理学措施（例如，EEG、瞳孔测量和皮肤电导，以及诸如眼球运动的行为测量），以实现以下目标：1）理解在现实的个人/群体循证管理决策情况下的证据收集和决策的实时认知和大脑机制，包括涉及各种认知偏差的情况（例如，框架，代表性）; 2）开发可定制的决策辅助工具，以最好地支持个人和团体（共同定位和虚拟）环境中基于证据的管理决策。该研究计划将利用麦克马斯特数字化转型研究中心（由申请人创立）相对独特的NeuroIS基础设施，这些基础设施通过最近的多个CFI基础设施赠款获得保障。心理学，行为学和神经生理学方法的融合提供了一个独特的机会，以全面了解受试者如何在各种环境中解释和使用决策证据。拟议的研究计划将大大提高我们对组织中循证管理决策的理解，并产生指导方针和工具，以减少决策者的认知负担，改善决策结果。它将为研究生和本科生提供充足的培训机会。通过该项目，学生将有机会发展最先进的人机交互、NeuroIS技术以及使用跨学科研究方法设计决策辅助工具的技能。

Effective evidenced-based managerial decision-making, whether made individually or in groups, is a critical success factor for organizations; it is a complex task involving the searching, processing, integration, and contextualization of information from a wide variety of sources. This complexity has been further exacerbated as decision makers face an overabundance of data and an ever-increasing dimensionality to managerial problems. Furthermore, organizational decisions are increasingly made in group settings where decisions can become polarized. Finally, the advancement of information and communication technologies and global networks, as well as COVID-19 related restrictions, have increased the prevalence of group decisions made in virtual teams. This research program will enhance and support evidence-based managerial decision making in organizations. The literature shows that evidence-based decision making can be viewed as dynamic processes through which decision makers (individuals or groups), supported by information technology (i.e., decision aids), obtain, interpret, and use evidence as a basis for decision making within their organizational context. Accordingly, this research will combine traditional human-computer interaction research methods (e.g., surveys, interviews) and expertise in decision sciences with cutting edge neurophysiological measures (e.g., EEG, pupillometry, and skin conductance, as well as behavioural measures such as eye movements) to achieve the following objectives: 1) understand the real-time cognitive and brain mechanisms of evidence gathering and decision making in realistic individual/group evidence-based managerial decision making situations, including those involving various cognitive biases (e.g., framing, representativeness); 2) develop customizable decision aids to best support evidence-based managerial decision making in individual and group (both co-located and virtual) settings. This program of research will leverage the relatively unique NeuroIS infrastructure at the McMaster Digital Transformation Research Centre (founded by the Applicant) secured through multiple recent CFI infrastructure grants. The fusion of psychological, behavioural, and neurophysiological approaches affords a unique opportunity to gain a comprehensive understanding of how subjects interpret and use evidence in decision making in a variety of settings. The proposed program of research will significantly advance our understanding of evidence-based managerial decision making in organizations and result in guidelines and tools to reduce decision makers' cognitive burden and improve decision making outcomes. It will provide ample training opportunities for both graduate and undergraduate students. Through this program, students will have opportunities to develop skills in state-of-the-art human-computer interaction, NeuroIS techniques and the design of decision aids using interdisciplinary research methodologies.