Srinivas Prasad – författare

The terrorist attacks of September 11, 2001, ushered in an age of anxiety along with the new century, an anxiety that has affected the international business climate in a variety of subtle and not-so-subtle ways. For one, the cost of doing business internationally has increased, for global firms and host countries alike. For another, understanding shifting geopolitical conditions in the developing world has become more crucial than ever to grasp if the world's multinationals—whether of American, British, European, or Japanese origin—are to take the best advantage of new market opportunities. These market opportunities are well within the experience range and grasp of the multinational consumer product and industrial firms as well as service enterprises. But the same corporate methodologies that were employed in decades past are unlikely to be sufficient for the age of anxiety that is upon us. The contributions assembled here offer the benefits of the collective wisdom of mature scholars with decades of consulting experience along with fresh ideas and new research hypotheses.

This series summarizes current thinking in the field of comparative management. The series is intended to make an academic contribution through focused essays, presenting material in a fashion suitable for both scholars and advanced students.

This volume introduces the AICM Distinguished Scholar Award and Research Forum which recognizes individuals who have made outstanding scholarly contributions to the cross-national or cross-cultural study of organizations and management. This volume offers an important article by Professor Harry C. Triandis of the University of Illinois who was the recipient of the 1998 AICM Distinguished Scholar Award, with commentaries by leading researchers in the areas of international organizational behavior and human resource management. Additional articles cover a wide range of management topics with an international focus, including: organizational risk taking, corporate governance, performance appraisal, distributive justice values, strategic human resource management, and expatriate performance. These articles, along with the Research Forum papers, present a rich diversity of theoretical and methodological approaches and represent some of the best thinking in the field.

Advances in International Management (AIM) is a research annual devoted to advancing the cross-border study of organizations and management practices from a global, regional, or comparative perspective, with emphasis on interdisciplinary inquiry that integrates ideas from multiple academic disciplines.It publishes conceptual and empirical papers that deal with international topics from any area within the management field, including strategy, organization theory and behavior, human resource management, business ethics, entrepreneurship, technology management and others. The organizations studied can be domestic or multinational and the level of analysis can be macro or micro. To be accepted for publication a paper must make a significant contribution to advancing knowledge about international management through some combination of new theoretical insights, managerial application, methodology or data.AIM has a particular interest in publishing the following types of manuscripts:Comprehensive, state-of-the-art literature reviews that integrate diverse research streams and identify promising directions for future investigations Analytical essays that offer new conceptual models or theoretical perspectives and use these frameworks as a foundation for developing research propositions Empirical articles that report results from exploratory or hypothesis-testing studies based on quantitative and/or qualitative methodologiesMethodological papers that refine existing methodologies or develop new ones for investigating particular issues or topics central to international management research.

BIG DATA ANALYTICS AND MACHINE INTELLIGENCE IN BIOMEDICAL AND HEALTH INFORMATICS Provides coverage of developments and state-of-the-art methods in the broad and diversified data analytics field and applicable areas such as big data analytics, data mining, and machine intelligence in biomedical and health informatics. The novel applications of Big Data Analytics and machine intelligence in the biomedical and healthcare sector is an emerging field comprising computer science, medicine, biology, natural environmental engineering, and pattern recognition. Biomedical and health informatics is a new era that brings tremendous opportunities and challenges due to the plentifully available biomedical data and the aim is to ensure high-quality and efficient healthcare by analyzing the data. The 12 chapters in??Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics??cover the latest advances and developments in health informatics, data mining, machine learning, and artificial intelligence. They have been organized with respect to the similarity of topics addressed, ranging from issues pertaining to the Internet of Things (IoT) for biomedical engineering and health informatics, computational intelligence for medical data processing, and Internet of Medical Things??(IoMT). New researchers and practitioners working in the field will benefit from reading the book as they can quickly ascertain the best performing methods and compare the different approaches. Audience Researchers and practitioners working in the fields of biomedicine, health informatics, big data analytics, Internet of Things, and machine learning.

BIG DATA ANALYTICS AND MACHINE INTELLIGENCE IN BIOMEDICAL AND HEALTH INFORMATICS

Provides coverage of developments and state-of-the-art methods in the broad and diversified data analytics field and applicable areas such as big data analytics, data mining, and machine intelligence in biomedical and health informatics.

The novel applications of Big Data Analytics and machine intelligence in the biomedical and healthcare sector is an emerging field comprising computer science, medicine, biology, natural environmental engineering, and pattern recognition. Biomedical and health informatics is a new era that brings tremendous opportunities and challenges due to the plentifully available biomedical data and the aim is to ensure high-quality and efficient healthcare by analyzing the data.

The 12 chapters in??Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics??cover the latest advances and developments in health informatics, data mining, machine learning, and artificial intelligence. They have been organized with respect to the similarity of topics addressed, ranging from issues pertaining to the Internet of Things (IoT) for biomedical engineering and health informatics, computational intelligence for medical data processing, and Internet of Medical Things??(IoMT).

New researchers and practitioners working in the field will benefit from reading the book as they can quickly ascertain the best performing methods and compare the different approaches.

Audience

Researchers and practitioners working in the fields of biomedicine, health informatics, big data analytics, Internet of Things, and machine learning.

BIG DATA ANALYTICS AND MACHINE INTELLIGENCE IN BIOMEDICAL AND HEALTH INFORMATICS

Provides coverage of developments and state-of-the-art methods in the broad and diversified data analytics field and applicable areas such as big data analytics, data mining, and machine intelligence in biomedical and health informatics.

The novel applications of Big Data Analytics and machine intelligence in the biomedical and healthcare sector is an emerging field comprising computer science, medicine, biology, natural environmental engineering, and pattern recognition. Biomedical and health informatics is a new era that brings tremendous opportunities and challenges due to the plentifully available biomedical data and the aim is to ensure high-quality and efficient healthcare by analyzing the data.

The 12 chapters in??Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics??cover the latest advances and developments in health informatics, data mining, machine learning, and artificial intelligence. They have been organized with respect to the similarity of topics addressed, ranging from issues pertaining to the Internet of Things (IoT) for biomedical engineering and health informatics, computational intelligence for medical data processing, and Internet of Medical Things??(IoMT).

New researchers and practitioners working in the field will benefit from reading the book as they can quickly ascertain the best performing methods and compare the different approaches.

Audience

Researchers and practitioners working in the fields of biomedicine, health informatics, big data analytics, Internet of Things, and machine learning.

This series summarizes current thinking in the field of comparative management. The series is intended to make an academic contribution through focused essays, presenting material in a fashion suitable for both scholars and advanced students.