Over the years, India has emerged as the third largest start-up ecosystem in the world, earning itself the reputation of being the emerging land for delivering unicorns. It has become one of the most attractive regions in the world for initiating and scaling up new business ideas. Many venture capitalists have invested in India's start-up ecosystem, and the government has also launched a variety of schemes to promote this growth. Indian organisations have become more competitive, making their global presence felt and expanding their reach into new industries and sectors.What factors have been pivotal for the growth of Indian start-ups? How did the Indian ecosystem evolve to fuel this growth? Is the role of leadership in start-ups more crucial than in other organisations?This book, through its diverse range of chapters, not only provides answers to the above questions, but also makes sincere efforts to highlight the innovative potential that start-ups carry and the leadership that is required to sail them through global competition. The book also provides an insight on the race of unicorns and how Indian start-ups have been extremely successful in bagging this coveted title. This edited book is a must-read for budding entrepreneurs and researchers who aim to understand and conduct research on Indian start-ups and their ecosystem support.

This book provides a comprehensive and contemporary source of reference for the gig economy for sustainable businesses with a focus on Industry 4.0. It covers the theoretical and practical implications of the rise of an alternative system in the era of technology-driven business entities; and explains the emergence of the gig economy as a crucial factor in devising approaches that will help in ensuring better decision making. As the COVID-19 pandemic rages on, investors and corporations are attempting to overcome the turbulence in financial markets over the past few months. Governments and economists are scrambling to mitigate the impacts of lockdowns. Many businesses have transferred to a remote working system, and the critical challenge remains to make this form of work and business productive, efficient, and sustainable. Against this backdrop, the book provides an overview of the gig economy from varied perspective such as general business and economics; ethics, governance, and legal issues; diffusion of IT in the workplace; sustainability; future of workforce and workplaces during and post-pandemic scenarios. This edited volume also highlights several challenges and opportunities for managing the diverse workforce in the prevailing situation which has no precedence. With its discussions on the impact of the gig economy on the business world, the book carries appeal for scholars in the business, human resource professionals, industry practitioners, corporates, and policy advocates interested in learning about evolution, automation, marketing, and sustainability in the gig economy.

This book provides a comprehensive and contemporary source of reference for the gig economy for sustainable businesses with a focus on Industry 4.0. It covers the theoretical and practical implications of the rise of an alternative system in the era of technology-driven business entities; and explains the emergence of the gig economy as a crucial factor in devising approaches that will help in ensuring better decision making. As the COVID-19 pandemic rages on, investors and corporations are attempting to overcome the turbulence in financial markets over the past few months. Governments and economists are scrambling to mitigate the impacts of lockdowns. Many businesses have transferred to a remote working system, and the critical challenge remains to make this form of work and business productive, efficient, and sustainable. Against this backdrop, the book provides an overview of the gig economy from varied perspective such as general business and economics; ethics, governance, and legal issues; diffusion of IT in the workplace; sustainability; future of workforce and workplaces during and post-pandemic scenarios. This edited volume also highlights several challenges and opportunities for managing the diverse workforce in the prevailing situation which has no precedence. With its discussions on the impact of the gig economy on the business world, the book carries appeal for scholars in the business, human resource professionals, industry practitioners, corporates, and policy advocates interested in learning about evolution, automation, marketing, and sustainability in the gig economy.

1) This book offers a comprehensive account of managing and strategising global business in times of crisis. 2) With the help of case studies, it discusses the 5 R’s of crisis management - Resolve, Resilience, Return, Re-imagination & Reform (5 R’s) 3) This book will be of interest to departments of Business management and Finance across UK.

1) This book offers a comprehensive account of managing and strategising global business in times of crisis. 2) With the help of case studies, it discusses the 5 R’s of crisis management - Resolve, Resilience, Return, Re-imagination & Reform (5 R’s) 3) This book will be of interest to departments of Business management and Finance across UK.

This book explores emerging research and pedagogy in analytics and data science that have become core to many businesses as they work to derive value from data. The chapters examine the role of analytics and data science to create, spread, develop and utilize analytics applications for practice. Selected chapters provide a good balance between discussing research advances and pedagogical tools in key topic areas in analytics and data science in a systematic manner. This book also focuses on several business applications of these emerging technologies in decision making, i.e., business analytics. The chapters in Analytics and Data Science: Advances in Research and Pedagogy are written by leading academics and practitioners that participated at the Business Analytics Congress 2015. Applications of analytics and data science technologies in various domains are still evolving. For instance, the explosive growth in big data and social media analytics requires examination of the impact of these technologies and applications on business and society. As organizations in various sectors formulate their IT strategies and investments, it is imperative to understand how various analytics and data science approaches contribute to the improvements in organizational information processing and decision making. Recent advances in computational capacities coupled by improvements in areas such as data warehousing, big data, analytics, semantics, predictive and descriptive analytics, visualization, and real-time analytics have particularly strong implications on the growth of analytics and data science.

This important new volume presents recent research in healthcare information technology and analytics. Individual chapters look at such issues as the impact of technology failure on electronic prescribing behavior in primary care; attitudes toward electronic health records; a latent growth modeling approach to understanding lifestyle decisions based on patient historical data; designing an integrated surgical care delivery system using axiomatic design and petri net modeling; and failure in a dynamic decision environment, particularly in treating patients with a chronic disease. Other chapters look at such topics as the impact of information technology integration in integrated delivery systems; operations and supply chain control for inventory management in a health system pharmacy; decision-theoretic assistants based on contextual gesture recognition; evaluating emergency response medical information systems; clinical decision support in critical care; virtual worlds in healthcare; and natural language processing for understanding contraceptive use at the VA.

This book constitutes the proceedings of the 9th International Workshop on Enterprise and Organizational Modeling and Simulation, EOMAS 2013, held in conjunction with CAiSE 2013 in Valencia, Spain, in June 2013.

Tools and methods for modeling and simulation are widely used in enterprise engineering, organizational studies and business process management. In monitoring and evaluating business processes and the interactions of actors in a realistic environment, modeling and simulation have proven to be both powerful, efficient and economic, especially if complemented by animation and gaming elements.

The ten contributions in this volume were carefully reviewed and selected from 22 submissions. They explore the above topics, address the underlying challenges find and improve solutions, and show the application of modeling and simulation in the domains of enterprises, their organizations and underlying business processes.

This book presents the select proceedings of the 3rd International Conference on Computational and Experimental Methods in Mechanical Engineering (ICCEMME 2020). The book discusses the recent researches and concrete findings in the field of mechanical design and automation with its allied branches. Various topics covered in this book include modeling and simulation, application of modelling to complex real-world systems, application of machine or deep learning in mechanical problems, artificial intelligence, vehicle design, robotics, vehicle dynamics and control, biomechanics, and vibration-related problems. Given its content, the book will be useful for beginners, researchers, and professionals interested in the field of mechanical engineering.

This book presents the select proceedings of the 3rd International Conference on Computational and Experimental Methods in Mechanical Engineering (ICCEMME 2020). The book discusses the recent researches and concrete findings in the field of mechanical design and automation with its allied branches. Various topics covered in this book include modeling and simulation, application of modelling to complex real-world systems, application of machine or deep learning in mechanical problems, artificial intelligence, vehicle design, robotics, vehicle dynamics and control, biomechanics, and vibration-related problems. Given its content, the book will be useful for beginners, researchers, and professionals interested in the field of mechanical engineering.

This book constitutes the thoroughly refereed proceedings of the 9th International Conference on Design Science Research in Information Systems and Technology, DESRIST 2014, held in Miami, FL, USA in May 2014. The 19 full papers, 7 research-in-progress papers and 18 short papers describing prototype demonstrations were carefully reviewed and selected from 71 submissions. The papers are organized in topical sections on design science; emerging themes; meta issues; methods; supporting business processes; team support; work-in-progress papers and prototypes.

This book constitutes the post conference proceedings of the 7th International Workshop on Enterprise and Organizational Modeling and Simulation, EOMAS 2011, held in conjunction with CAiSE 2011 in London, UK, in June 2011. Enterprises are purposefully designed systems used to fulfill certain functions. An extended enterprise and organizational study involves both analysis and design activities, in which modeling and simulation play prominent roles. The related techniques and methods are effective, efficient, economic, and widely used in enterprise engineering, organizational study, and business process management. The 14 contributions in this volume were carefully reviewed and selected from 29 submissions, and they explore these topics, address the underlying challenges, find and improve on solutions, and demonstrate the application of modeling and simulation in the domains of enterprises, their organizations and underlying business processes.

Explore clustering algorithms used with Apache Mahout About This Book * Use Mahout for clustering datasets and gain useful insights * Explore the different clustering algorithms used in day-to-day work * A practical guide to create and evaluate your own clustering models using real world data sets Who This Book Is For This book is for developers who want to try out clustering on large datasets using Mahout. It will also be useful for those users who don't have background in Mahout, but have knowledge of basic programming and are familiar with basics of machine learning and clustering. It will be helpful if you know about clustering techniques with some other tool. What You Will Learn * Explore clustering algorithms and cluster evaluation techniques * Learn different types of clustering and distance measuring techniques * Perform clustering on your data using K-Means clustering * Discover how canopy clustering is used as pre-process step for K-Means * Use the Fuzzy K-Means algorithm in Apache Mahout * Implement Streaming K-Means clustering in Mahout * Learn Spectral K-Means clustering implementation of Mahout In Detail As more and more organizations are discovering the use of big data analytics, interest in platforms that provide storage, computation, and analytic capabilities has increased. Apache Mahout caters to this need and paves the way for the implementation of complex algorithms in the field of machine learning to better analyse your data and get useful insights into it. Starting with the introduction of clustering algorithms, this book provides an insight into Apache Mahout and different algorithms it uses for clustering data. It provides a general introduction of the algorithms, such as K-Means, Fuzzy K-Means, StreamingKMeans, and how to use Mahout to cluster your data using a particular algorithm. You will study the different types of clustering and learn how to use Apache Mahout with real world data sets to implement and evaluate your clusters. This book will discuss about cluster improvement and visualization using Mahout APIs and also explore model-based clustering and topic modelling using Dirichlet process. Finally, you will learn how to build and deploy a model for production use. Style and approach This book is a hand's-on guide with examples using real-world datasets. Each chapter begins by explaining the algorithm in detail and follows up with showing how to use mahout for that algorithm using example data-sets.