Happimetrics: leveraging AI to untangle the surprising link between ethics, happiness and business success

By:

Gloor, Peter .A

Material type: Text

TextPublication details: Edward Elgar Publishing Ltd. Cheltenham 2022Description: 223 pISBN:

9781035312153

Subject(s):

Artificial intelligence--Industrial applications

DDC classification:

658.314 GLO

Summary: Based on 20 years of research, this book lays out a proven and tested method for reaching the goal of employee happiness, analyzing individuals’ communication patterns, and making them self-aware by mirroring their behaviour back to them in a privacy-respecting way. In doing so, Peter A. Gloor introduces artificial intelligence-based methods to identify personality, moral values, and ethics of individuals based on their body language and interaction with others. In this book readers will: • understand the basic concepts of groupflow – when teams collaborate at their best through intrinsic motivation and positive stress • learn how to use artificial intelligence (AI), machine learning (ML) and social network analysis (SNA) to analyze communication by tracking emotions, social networks, morals, and tribes • successfully use virtual mirroring to create entangled teams that work together in collaborative innovation networks (COINs) synchronized and in harmony for superior performance • understand how to implement virtual mirroring using these technologies. Groundbreaking and innovative, Happimetrics will be an invaluable resource for scholars and students in the fields of business analytics, information systems and organizational innovation. It will also be useful for HR professionals and AI developers who are looking to use predictive analytics to measure workforce performance.

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	Human Resource and Organization Behvaiour	658.314 GLO (Browse shelf(Opens below))	1	Available		006070

Browsing Indian Institute of Management LRC shelves, Shelving location: General Stacks, Collection: Human Resource and Organization Behvaiour Close shelf browser (Hides shelf browser)

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Previous	658.3128 AND Organization design: creating strategic and agile organizations	658.3128 HAR HBR guide to performance management	658.3128 HUG The emotionally intelligent team: understanding and developing the behaviors of success	658.314 GLO Happimetrics: leveraging AI to untangle the surprising link between ethics, happiness and business success	658.314 KEE The psychology of fear in organizations: how to transform anxiety into well-being, productivity and innovation	658.314 LAT Work motivation: history, theory, research, and practice	658.314 LEI Reinventing burnout and building engagement	Next

Based on 20 years of research, this book lays out a proven and tested method for reaching the goal of employee happiness, analyzing individuals’ communication patterns, and making them self-aware by mirroring their behaviour back to them in a privacy-respecting way. In doing so, Peter A. Gloor introduces artificial intelligence-based methods to identify personality, moral values, and ethics of individuals based on their body language and interaction with others.

In this book readers will:
• understand the basic concepts of groupflow – when teams collaborate at their best through intrinsic motivation and positive stress
• learn how to use artificial intelligence (AI), machine learning (ML) and social network analysis (SNA) to analyze communication by tracking emotions, social networks, morals, and tribes
• successfully use virtual mirroring to create entangled teams that work together in collaborative innovation networks (COINs) synchronized and in harmony for superior performance
• understand how to implement virtual mirroring using these technologies.

Groundbreaking and innovative, Happimetrics will be an invaluable resource for scholars and students in the fields of business analytics, information systems and organizational innovation. It will also be useful for HR professionals and AI developers who are looking to use predictive analytics to measure workforce performance.

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