使用机器学习评估和改进概率推理模型的补充材料

IF 1.5 Q3 MANAGEMENT Decision Pub Date : 2024-07-25 DOI:10.1037/dec0000233.supp
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Supplemental Material for Using Machine Learning to Evaluate and Enhance Models of Probabilistic Inference
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来源期刊
Decision
Decision MANAGEMENT-
CiteScore
2.30
自引率
0.00%
发文量
27
期刊介绍: The aim of the Journal, Decision, is to publish qualitative, quantitative, survey-based, simulation-based research articles at the national and sub-national levels. While there is no stated regional focus of the journal, we are more interested in examining if and how individuals, firms and governments in emerging economies may make decisions differently. Published for the management scholars, business executives and managers, the Journal aims to advance the management research by publishing empirically and theoretically grounded articles in management decision making process. The Editors aim to provide an efficient and high-quality review process to the authors. The Journal accepts submissions in several formats such as original research papers, case studies, review articles and book reviews (book reviews are only by invitation). The Journal welcomes research-based, original and insightful articles on organizational, individual, socio-economic-political, environmental decision making with relevance to theory and practice of business. It also focusses on the managerial decision-making challenges in private, public, private-public partnership and non-profit organizations. The Journal also encourages case studies that provide a rich description of the business or societal contexts in managerial decision-making process including areas – but not limited to – conflict over natural resources, product innovation and copyright laws, legislative or policy change, socio-technical embedding of financial markets, particularly in developing economy, an ethnographic understanding of relations at a workplace, or social network in marketing management, etc. Research topics covered in the Journal include (but not limited to): Finance and Accounting Organizational Theory and Behavior Decision Science Public Policy-Economic Insights Operation Management Innovation and Entrepreneurship Information Technology and Systems Management Optimization and Modelling Supply Chain Management Data Analytics Marketing Management Human Resource Management
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