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

有效的以证据为基础的管理决策，无论是单独做出还是集体做出，都是组织成功的关键因素；这是一项复杂的任务，涉及对各种来源的信息进行搜索、处理、集成和上下文化。由于决策者面临着过多的数据和管理问题的维度不断增加，这种复杂性进一步加剧。此外，组织决策越来越多地在群体环境中做出，在这种环境中，决策可能变得两极分化。最后，信息通信技术和全球网络的进步，以及与COVID-19相关的限制，增加了虚拟团队中群体决策的流行。本研究项目将加强和支持组织的循证管理决策。文献表明，基于证据的决策可以被看作是一个动态过程，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）的支持下，获取、解释和使用证据作为其组织背景下决策的基础。因此，本研究将结合传统的人机交互研究方法（如调查、访谈）和决策科学的专业知识，以及尖端的神经生理学测量（如脑电图、瞳孔测量、皮肤电导以及眼动等行为测量），以实现以下目标：1)了解现实的个人/群体循证管理决策情境中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（如框架、代表性）的情况；2)开发可定制的决策辅助工具，以最好地支持个人和群体（包括同地和虚拟）环境中的循证管理决策。该研究项目将利用麦克马斯特数字化转型研究中心（由申请人创建）相对独特的神经系统基础设施，该基础设施是通过最近的多个CFI基础设施拨款获得的。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，可以全面了解受试者如何在各种情况下解释和使用决策中的证据。该研究项目将显著促进我们对组织中基于证据的管理决策的理解，并产生指导方针和工具，以减少决策者的认知负担，提高决策结果。它将为研究生和本科生提供充足的培训机会。通过这个项目，学生将有机会发展最先进的人机交互技能，神经系统技术和决策辅助设计，使用跨学科的研究方法。

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.