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Data-driven decision making for sustainable business growth

Record Type:	Electronic resources : Monograph/item
Title/Author:	Data-driven decision making for sustainable business growthedited by Ismail Qasem.
other author:	Qasem, Ismail.
Published:	Cham :Springer Nature Switzerland :2025.
Description:	xv, 1074 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Decision makingData processing.
Online resource:	https://doi.org/10.1007/978-3-031-96530-2
ISBN:	9783031965302$q(electronic bk.)

Data-driven decision making for sustainable business growth
Data-driven decision making for sustainable business growth[electronic resource] /edited by Ismail Qasem. - Cham :Springer Nature Switzerland :2025. - xv, 1074 p. :ill. (some col.), digital ;24 cm. - Studies in systems, decision and control,v. 6072198-4190 ;. - Studies in systems, decision and control ;v.3..

1.The Roles of Paid Promotion, Social Media Marketing, and Electronic Word of Mouth to Improve the Visitors Intentions in Solo Safari Zoo, Indonesia -- 2.Marketing to Gen Z in Batam: Service Quality, Customer Satisfaction & Purchase Intention -- 3.The role of auditors in reducing the expectations gap in auditing -- 4.Managing The Integration Of Building Information Modelling (BIM) And Lean Construction (LC) -- 5.Financial Technology Adoption By Micro-Entrepreneurs: Adding Financial Literacy Skills Will Improve MSME Performance -- 91.Adaptive Leadership: Nurturing Team Resilience and Agility Through Technological Transformation -- 92.Perceived Productivity through Life Skill Training: Moderation Effect of Work Environment -- 93.Implications of Full Range Leadership on Teenagers' Self-Esteem: The Role of Salesian Institutions in Higher Education -- 94.Social Media An Influencing Factor On Investment Decisions Of Salaried Gen Millennials.

This book provides a comprehensive guide to data-driven decision-making for sustainable business growth. It offers practical insights and methodologies for leveraging data analytics to enhance sustainability initiatives and drive business success. Designed for business professionals, data scientists, and sustainability practitioners, the book bridges the gap between data science and sustainable business practices. By integrating data-driven strategies with sustainability goals, it addresses the critical need for informed decision-making in today's data-centric business environment. The main topics covered in this book include data analytics for sustainability, predictive modelling, big data applications, and the role of artificial intelligence in decision-making. These topics are crucial as they enable businesses to make informed decisions, optimize resource use, and improve overall sustainability performance. The book also explores case studies of successful data-driven sustainability initiatives, providing real-world examples and actionable insights. The relevance of these topics is significant in the modern business landscape, where data is a valuable asset. This book not only highlights the importance of data-driven decision-making for sustainability but also provides practical tools and techniques to implement these strategies effectively. It aims to empower businesses to harness the power of data for sustainable growth, enhancing their competitive advantage and contributing to a more sustainable future. The problem this book sets out to solve is the lack of clear guidance on integrating data analytics with sustainability initiatives. Many businesses struggle to utilize data effectively to achieve their sustainability goals. This book offers a roadmap for leveraging data to drive sustainable business practices, showcasing best practices and innovative approaches. The target audience for this book includes business leaders, data analysts, sustainability officers, researchers, and students in business and data science fields. By offering a blend of theoretical knowledge and practical applications, this book aims to equip readers with the skills needed to make data-driven decisions for sustainable business growth.

ISBN: 9783031965302$q(electronic bk.)

Standard No.: 10.1007/978-3-031-96530-2doiSubjects--Topical Terms:

235779
Decision making
--Data processing.

LC Class. No.: HD30.23

Dewey Class. No.: 658.403

Data-driven decision making for sustainable business growth
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505 0 $a 1.The Roles of Paid Promotion, Social Media Marketing, and Electronic Word of Mouth to Improve the Visitors Intentions in Solo Safari Zoo, Indonesia -- 2.Marketing to Gen Z in Batam: Service Quality, Customer Satisfaction & Purchase Intention -- 3.The role of auditors in reducing the expectations gap in auditing -- 4.Managing The Integration Of Building Information Modelling (BIM) And Lean Construction (LC) -- 5.Financial Technology Adoption By Micro-Entrepreneurs: Adding Financial Literacy Skills Will Improve MSME Performance -- 91.Adaptive Leadership: Nurturing Team Resilience and Agility Through Technological Transformation -- 92.Perceived Productivity through Life Skill Training: Moderation Effect of Work Environment -- 93.Implications of Full Range Leadership on Teenagers' Self-Esteem: The Role of Salesian Institutions in Higher Education -- 94.Social Media An Influencing Factor On Investment Decisions Of Salaried Gen Millennials.
520 $a This book provides a comprehensive guide to data-driven decision-making for sustainable business growth. It offers practical insights and methodologies for leveraging data analytics to enhance sustainability initiatives and drive business success. Designed for business professionals, data scientists, and sustainability practitioners, the book bridges the gap between data science and sustainable business practices. By integrating data-driven strategies with sustainability goals, it addresses the critical need for informed decision-making in today's data-centric business environment. The main topics covered in this book include data analytics for sustainability, predictive modelling, big data applications, and the role of artificial intelligence in decision-making. These topics are crucial as they enable businesses to make informed decisions, optimize resource use, and improve overall sustainability performance. The book also explores case studies of successful data-driven sustainability initiatives, providing real-world examples and actionable insights. The relevance of these topics is significant in the modern business landscape, where data is a valuable asset. This book not only highlights the importance of data-driven decision-making for sustainability but also provides practical tools and techniques to implement these strategies effectively. It aims to empower businesses to harness the power of data for sustainable growth, enhancing their competitive advantage and contributing to a more sustainable future. The problem this book sets out to solve is the lack of clear guidance on integrating data analytics with sustainability initiatives. Many businesses struggle to utilize data effectively to achieve their sustainability goals. This book offers a roadmap for leveraging data to drive sustainable business practices, showcasing best practices and innovative approaches. The target audience for this book includes business leaders, data analysts, sustainability officers, researchers, and students in business and data science fields. By offering a blend of theoretical knowledge and practical applications, this book aims to equip readers with the skills needed to make data-driven decisions for sustainable business growth.
650 0 $a Decision making $x Data processing. $3 235779
650 1 4 $a Computational Intelligence. $3 338479
650 2 4 $a Data Engineering. $3 839346
650 2 4 $a Business Informatics. $3 918833
700 1 $a Qasem, Ismail. $3 1005346
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830 0 $a Studies in systems, decision and control ; $v v.3. $3 678532
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950 $a Business and Management (SpringerNature-41169)