决策辅助工具
决策支持系统
任务(项目管理)
计算机科学
决策质量
决策分析
认知负荷
匹配(统计)
证据推理法
决策工程
启发式
产品(数学)
资源(消歧)
认知
知识管理
R型铸件
商业决策图
决策模型
人工智能
机器学习
心理学
工程类
病理
神经科学
统计
医学
系统工程
替代医学
团队效能
数学
计算机网络
几何学
作者
Chuan‐Hoo Tan,Hock-Hai Teo,Izak Benbasat
标识
DOI:10.1287/isre.1080.0232
摘要
This research explores how consumers use online decision aids with screening and evaluation support functionalities under varying product attribute-load conditions. Drawing on resource-matching theory, we conducted a 3 × 2 factorial experiment to test the interaction between decision aid features (i.e., low versus high-screening support, and aids with weight assignment and computation decision tools) and attribute load (i.e., large versus small number of product attributes) on decision performance. The findings reveal that: (1) where the decision aids render cognitive resources that match those demanded for the task environment, consumers will process more information and decision performance will be enhanced; (2) where the decision aids render cognitive resources that exceed those demanded for the task environment, consumers will engage in less task-related elaboration of decision-making issues to the detriment of decision performance; and (3) where the decision aids render cognitive resources that fall short of those demanded for the task environment, consumers will use simplistic heuristic decision strategies to the detriment of decision performance or invest additional effort in information processing to attain a better decision performance if they perceive the additional investments in effort to be manageable.
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