In the 21st century, supply chain operations and relationships among supply chain partners have become highly challenging, necessitating new approaches, e.g., the development of new models. Supply Chain Strategies, Issues and Models discusses supply chain issues and models with examples from actual industrial cases. Expert authors with a wide spectrum of knowledge working in various areas of supply chain management from various geographical locations offer refreshing, novel and insightful ideas and address possible solutions using established theories and models. Supply Chain Strategies, Issues and Models features studies that have used mathematical modeling, statistical analyses and also descriptive qualitative studies. The chapters cover many relevant themes related to supply chains and logistics including supply chain complexity, information sharing, quality (six sigma), electronic Kanbans, inventory models, scheduling, purchasing and contracts. To facilitate easy reading, the chapters that deal with supply chain related issues are first, followed by studies on inventory, scheduling, purchasing and logistics. This book can be used as a useful resource of supply chain management by academics, students and practitioners. This book can serve as a helping tool in managerial decision making for investments in collaboration and information exchange to improve forecasts, scheduling and inventory management, and for supply chain managers to leverage product and process complexities into competitive advantage. Some interesting mathematical models can appeal to students and researchers interested in modeling the impact of information sharing in supply chains.

This book discusses supply chain issues and models with examples from actual case studies. Recent advances in sustainability, supply chains and technologies have brought promising potential for the management of sustainable global and local supply chains. While most of the current literature seem to consider developments in the field of sustainable supply chains and in the field of Industry 4.0 as two distinct entities, this book attempts to explore the synergy in bringing these two distinct fields together. The book features chapters on management of sustainability and industry 4.0 on supply chains as a whole, with several case studies on issues related to the application of sustainable supply chains in specific application sectors. They employ mathematical modeling and statistical analyses, as well as descriptive qualitative studies. They cover a range of application areas including multiple sectors (restaurant, manufacturing, logistics, furniture, food and insurance), domains (supply chains, logistics, marketing, and reverse logistics) and multiple country contexts (UK and India). The potential links between sustainability and the recent technological innovations from Industry 4.0 have been explored in detail. The book offers a valuable tool for managerial decision-making on the current practice and future potential on the use of Industry 4.0 tools for sustainable supply chains to facilitate competitive advantage with case studies in various industry sectors. In addition, some intriguing mathematical models will appeal to students and researchers interested in modeling the logistics process and the application of evolutionary game theory for integrating the social and economic aspects of sustainable supply chains. Some of these supply chain issues have been addressed in a previous book by the Editors.

Multiple Criteria Decision Making (MCDM) is a subfield of Operations Research, dealing with decision making problems. A decision-making problem is characterized by the need to choose one or a few among a number of alternatives. The field of MCDM assumes special importance in this era of Big Data and Business Analytics. In this volume, the focus will be on modelling-based tools for Business Analytics (BA), with exclusive focus on the sub-field of MCDM within the domain of operations research. The book will include an Introduction to Big Data and Business Analytics, and challenges and opportunities for developing MCDM models in the era of Big Data.

In the 21st century, supply chain operations and relationships among supply chain partners have become highly challenging, necessitating new approaches, e.g., the development of new models. Supply Chain Strategies, Issues and Models discusses supply chain issues and models with examples from actual industrial cases. Expert authors with a wide spectrum of knowledge working in various areas of supply chain management from various geographical locations offer refreshing, novel and insightful ideas and address possible solutions using established theories and models. Supply Chain Strategies, Issues and Models features studies that have used mathematical modeling, statistical analyses and also descriptive qualitative studies. The chapters cover many relevant themes related to supply chains and logistics including supply chain complexity, information sharing, quality (six sigma), electronic Kanbans, inventory models, scheduling, purchasing and contracts. To facilitate easy reading, the chapters that deal with supply chain related issues are first, followed by studies on inventory, scheduling, purchasing and logistics. This book can be used as a useful resource of supply chain management by academics, students and practitioners. This book can serve as a helping tool in managerial decision making for investments in collaboration and information exchange to improve forecasts, scheduling and inventory management, and for supply chain managers to leverage product and process complexities into competitive advantage. Some interesting mathematical models can appeal to students and researchers interested in modeling the impact of information sharing in supply chains.

This book discusses supply chain issues and models with examples from actual case studies. Recent advances in sustainability, supply chains and technologies have brought promising potential for the management of sustainable global and local supply chains. While most of the current literature seem to consider developments in the field of sustainable supply chains and in the field of Industry 4.0 as two distinct entities, this book attempts to explore the synergy in bringing these two distinct fields together. The book features chapters on management of sustainability and industry 4.0 on supply chains as a whole, with several case studies on issues related to the application of sustainable supply chains in specific application sectors. They employ mathematical modeling and statistical analyses, as well as descriptive qualitative studies. They cover a range of application areas including multiple sectors (restaurant, manufacturing, logistics, furniture, food and insurance), domains (supply chains, logistics, marketing, and reverse logistics) and multiple country contexts (UK and India). The potential links between sustainability and the recent technological innovations from Industry 4.0 have been explored in detail. The book offers a valuable tool for managerial decision-making on the current practice and future potential on the use of Industry 4.0 tools for sustainable supply chains to facilitate competitive advantage with case studies in various industry sectors. In addition, some intriguing mathematical models will appeal to students and researchers interested in modeling the logistics process and the application of evolutionary game theory for integrating the social and economic aspects of sustainable supply chains. Some of these supply chain issues have been addressed in a previous book by the Editors.

Multiple Criteria Decision Making (MCDM) is a subfield of Operations Research, dealing with decision making problems. A decision-making problem is characterized by the need to choose one or a few among a number of alternatives. The field of MCDM assumes special importance in this era of Big Data and Business Analytics. In this volume, the focus will be on modelling-based tools for Business Analytics (BA), with exclusive focus on the sub-field of MCDM within the domain of operations research. The book will include an Introduction to Big Data and Business Analytics, and challenges and opportunities for developing MCDM models in the era of Big Data.