Advances in Cross-Cultural Decision Making (Advances in Human Factors and Ergonomics Series)

The primary focus of the Cross Cultural Decision Making field is specifically on the intersections between psychosocial theory provided from the social sciences and methods of computational modeling provided from computer science and mathematics. While the majority of research challenges that arise out of such an intersection fall quite reasonably under the rubric of "human factors", although these topics are broad in nature, this book is designed to focus on crucial questions regarding data acquisition as well as reconciliation of mathematical and psychosocial modeling methodologies. The utility of this area of research is to aid the design of products and services which are utilized across the globe in the variety of cultures and aid in increasing the effectiveness of cross-cultural group collaboration. To aid a researcher in defining the requirements and metrics for this complex topic applications and use cases of CCDM can be found in sections: I. Applications of Human, Social, Culture Behavioral Modeling Technology IV. Cross Cultural Decision Making: Implications for Individual and Team Training X. Tactical Culture Training: Narrative, Personality, and Decision-Making XII. Use Cases of Cross Cultural Decision Making Theories and techniques for understanding, capturing, and modeling the components of Culture are covered in these sections: II. Assessing and Developing Cross-Cultural Competence III. Civilizational Change: Ideological, Economic, and Historical Change V. Cultural Models for Decision Making VI. Extracting Understanding from Diverse Data Sources VII. Hybrid & Multi-Model Computational Techniques for HSCB Applications IX. Socio-cultural Models and Decision-Making VIII. Sense Making in Other Cultures: Dynamics of Interaction XI. Understanding The science and technology provided in this book represents the latest available from the international community. It is hoped that this content can be used to tackle two of the biggest challenges in this area: 1) U