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Springer Understanding the Role of Business Analytics: Some Applications

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Description

Product Description This book encompasses empirical evidences to understand the application of data analytical techniques in emerging contexts. Varied studies relating to manufacturing and services sectors including healthcare, banking, information technology, power, education sector etc. stresses upon the systematic approach followed in applying the data analytical techniques; and also analyses how these techniques are effective in decision-making in different contexts. Especially, the application of regression modeling, financial modelling, multi-group modeling, cluster analysis, and sentiment analysis will help the readers in understanding critical business scenarios in the best possible way, and which later can help them in arriving at best solution for the business related problems. The individual chapters will help the readers in understanding the role of specific data analytic tools and techniques in resolving business operational issues experienced in manufacturing and service organisations in India and in developing countries.   The book offers a relevant resource that will help readers in the application and interpretation of data analytical statistical practices relating to emerging issues like customer experience, marketing capability, quality of manufactured products, strategic orientation, high-performance human resource policy, employee resilience, financial resources, etc.  This book will be of interest to a professional audience that include  practitioners, policy makers, NGOs, managers and employees as well as academicians, researchers and students. From the Back Cover This book encompasses empirical evidences to understand the application of data analytical techniques in emerging contexts. Varied studies relating to manufacturing and services sectors including healthcare, banking, information technology, power, education sector etc. stresses upon the systematic approach followed in applying the data analytical techniques; and also analyses how these techniques are effective in decision-making in different contexts. Especially, the application of regression modeling, financial modelling, multi-group modeling, cluster analysis, and sentiment analysis will help the readers in understanding critical business scenarios in the best possible way, and which later can help them in arriving at best solution for the business related problems. The individual chapters will help the readers in understanding the role of specific data analytic tools and techniques in resolving business operational issues experienced in manufacturing and service organisations in India and in developing countries.   The book offers a relevant resource that will help readers in the application and interpretation of data analytical statistical practices relating to emerging issues like customer experience, marketing capability, quality of manufactured products, strategic orientation, high-performance human resource policy, employee resilience, financial resources, etc.  This book will be of interest to a professional audience that include  practitioners, policy makers, NGOs, managers and employees as well as academicians, researchers and students. About the Author Dr Hardeep Chahal is a professor in the Department of Commerce, University of Jammu, India. Her research interests focuses on services marketing with emphasis on consumer satisfaction and loyalty, service quality, brand equity and market orientation. Her work has been published in refereed international journals like Managing Service Quality, International Journal of Healthcare Quality and Assurance, International Journal of Bank Marketing, Journal of Relationship Marketing, Journal of Health Management, Journal of Relationship Marketing, Management Research Review, Total Quality Management and Excellence, Corporate Governance, Global Business Review etc. She has also co-edited books such as "Sustainable Competitive Advantage: A Road to Success"

Product Specifications

Format
Hardcover
Domain
Amazon UK
Release Date
06 October 2018
Listed Since
30 May 2018

Barcode

No barcode data available

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