Artificial Intelligence Enabled Management
De Gruyter (Verlag)
978-3-11-117105-0 (ISBN)
Companies in developing countries are adopting Artificial Intelligence applications to increase efficiency and open new markets for their products. This book explores the multifarious capabilities and applications of AI in the context of these emerging economies and its role as a driver for decision making in current management practices.
Artificial Intelligence Enabled Management argues that the economic problems facing academics, professionals, managers, governments, businesses and those at the bottom of the economic pyramid have a technical solution that relates to AI. Businesses in developing countries are using cutting-edge AI-based solutions to improve autonomous delivery of goods and services, implement automation of production and develop mobile apps for services and access to credit. By integrating data from websites, social media and conventional channels, companies are developing data management platforms, good business plans and creative business models. By increasing productivity, automating business processes, financial solutions and government services, AI can drive economic growth in these emerging economies. Public and private sectors can work together to find innovative solutions that simultaneously alleviate poverty and inequality and increase economic mobility and prosperity.
The thought-provoking contributions in this book also bring attention to new barriers that have emerged in the acceptance, use, integration and deployment of AI by businesses in developing countries and explore the often-overlooked drawbacks of AI adoption that can hinder or even cause value loss. The book is a must-read for policymakers, researchers, and anyone interested in understanding the critical role of AI in the emerging economy perspective.
Dr Rubee Singh is Assistant Professor of Human Resource at the Institute of Business Management, GLA University, India. Her areas of research are sustainability, digital HRM, green HRM, circular economy, corporate social responsibility, Industry 4.0, and artificial intelligence.
Dr Shahbaz Khan is Assistant Professor and Area-Cochair of Operation Management/Business Analytics/Supply Chain at the Institute of Business Management, GLA University, India. His research interests are supply chain management, human resource management, Halal supply chain management, circular economy and sustainability, Industry 4.0, performance measurement, process management and benchmarking, and decision modelling for sustainable business.
Prof. Anil Kumar is Senior Lecturer (Associate Professor) at Guildhall School of Business and Law, London Metropolitan University (LMU), London, U.K. His areas of research are sustainability science, green/sustainable supply chain management, customer retention, green purchasing behaviour, sustainable procurement, sustainable development, circular economy, Industry 4.0, performance measurement, human capital in supply chain and operations; decision modelling for sustainable business, and integration of operations with other areas.
Prof. Vikas Kumar is Professor of Operations and Supply Chain Management and Director of Research at Bristol Business School, University of the West of England (UWE), UK. He is also a visiting Professor at Ton Duc Thang University, Ho Chi Minh City, Vietnam. His current research interests include sustainability, circular economy, food supply chains, operational excellence, and Industry 4.0.
| Erscheinungsdatum | 27.04.2024 |
|---|---|
| Zusatzinfo | 9 b/w and 24 col. ill., 23 b/w tbl. |
| Verlagsort | Berlin/Boston |
| Sprache | englisch |
| Maße | 170 x 240 mm |
| Gewicht | 612 g |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Wirtschaft ► Betriebswirtschaft / Management ► Unternehmensführung / Management | |
| Schlagworte | Artificial Intelligence • Big Data • Decision Making • Economic Growth • emerging economies • Entwicklungsländer • Künstliche Intelligenz • Schwellenländer |
| ISBN-10 | 3-11-117105-1 / 3111171051 |
| ISBN-13 | 978-3-11-117105-0 / 9783111171050 |
| Zustand | Neuware |
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