This volume is the last (IV) of four under the main themes of Digitizing Agriculture and Information and Communication Technologies (ICT). The four volumes cover rapidly developing processes including Sensors (I), Data (II), Decision (III), and Actions (IV). Volumes are related to 'digital transformation" within agricultural production and provision systems, and in the context of Smart Farming Technology and Knowledge-based Agriculture. Content spans broadly from data mining and visualization to big data analytics and decision making, alongside with the sustainability aspects stemming from the digital transformation of farming. The four volumes comprise the outcome of the 12th EFITA Congress, also incorporating chapters that originated from select presentations of the Congress. The focus in this volume is on the directions of Agriculture 4.0 which incorporates the transition to a new era of action in the Agricultural sector, represented by the evolution of digital technologies in 4 aspects: Big Data, Open Data, Internet of Things (IoT), and Cloud Computing. Under the heading of "Action," 14 Chapters investigate the implementation of cutting-edge technologies on real world applications. It will become apparent to the reader that the penetration of ICT in agriculture can result in several benefits related to the sustainability of the sector and to yield the maximum benefits, successful management is required. The entire discussion highlights the importance of proper education in the adoption of innovative technologies starting with the adaption of educational systems to the new era and moving to the familiarization of farmers to the new technologies. This book covers topics that relate to the digital transformation of farming. It provides examples and case studies of this transformation from around the world, examines the process of diffusion of digital technologies, and assesses the current and future sustainability aspects of digital agriculture. More specifically, it deals with issues such as: Challenges and opportunities from the transition to Agriculture 4.0 Safety and health in agricultural work automation The role of digital farming on regional-spatial planning The enrollment of Social Media in IoT-based agriculture The role of education in digital agriculture Real-life implementation cases of smart agriculture around the world

This book presents innovative operations research applications in business, specifically industrial engineering and its sub-disciplines. It investigates new perspectives in operations research and management science with regard to research methods, the research context, and industrial engineering, offering readers a broad range of new approaches to management problems. The book features the latest work of researchers who have worked with Professor Fusun Ulengin or built upon her work in their academic careers. Written in honor of Prof. Ulengin, this book was edited by her former Ph.D. students, who are now experts in operations research, multiple criteria decision making, competitiveness, logistics, and supply chain management. Prof. Ulengin's impact in academia is visible in the range of topics and methodologies featured in this book: Location and transportation problems, competitiveness of nations, food supply chains, debt collection, mathematical modelling, multiple criteria decision making, data envelopment analysis, random forests, and Bayesian networks.

Operations research tools are ideally suited to providing solutions and insights for the many problems health policy-maker's face. Indeed, a growing body of literature on health policy analysis, based on operations research methods, has emerged to address the problems mentioned above and several others. The research in this field is often multi-disciplinary, being conducted by teams that include not only operations researchers but also clinicians, economists and policy analysts. The research is also often very applied, focusing on a specific question driven by a decision-maker and many times yielding a tool to assist in future decisions. The goal of this volume was to bring together a group of papers by leading experts that could showcase the current state of the field of operations research applied to health-care policy. There are 18 chapters that illustrate the breadth of this field. The chapters use a variety of techniques, including classical operations research tools, such as optimization, queuing theory, and discrete event simulation, as well as statistics, epidemic models and decision-analytic models. The book spans the field and includes work that ranges from highly conceptual to highly applied. An example of the former is the chapter by Kimmel and Schackman on building policy models, and an example of the latter is the chapter by Coyle and colleagues on developing a Markov model for use by an organization in Ontario that makes recommendations about the funding of new drugs. The book also includes a mix of review chapters, such as the chapter by Hutton on public health response to influenza outbreaks, and original research, such as the paper by Blake and colleagues analyzing a decision by Canadian Blood Services to consolidate services. This volume could provide an excellent introduction to the field of operations research applied to health-care policy, and it could also serve as an introduction to new areas for researchers already familiar with the topic. The book is divided into six sections. The first section contains two chapters that describe several different applications of operations research in health policy and provide an excellent overview of the field. Sections 2 to 4 present policy models in three focused areas. Section 5 contains two chapters on conceptualizing and building policy models. The book concludes in Section 6 with two chapters describing work that was done with policy-makers and presenting insights gained from working directly with policy-makers.

The authors contend that current knowledge management efforts in organizations need to be re-focused so that they can be better poised for success. Topics discussed include: missing capabilities of knowledge management, knowledge management in strategic alliances, customer knowledge management, knowledge markets, and knowledge management systems, among others. The authors take a pragmatic approach to knowledge management and present the material in a jargon free and accessible way.

The book consolidates systems thinking as a new world-hypothesis that is already suggesting itself behind the advancement of quantum mechanics and Ashby's cybernetics. In particular, it shows how Einstein's misgivings about quantum mechanics boil down to his persistence in defending the principle of contiguity at the root of the modern cosmology and, in relation to neo-cybernetics, the book rediscovers Ashby's theory of adaptive behaviour enabling a new synthesis between physiology, psychology and ethology that has implications for systems practice. Furthermore, this new "cosmology" comes with a new "anthropology" that informs utopics, the science of utopic systems, and sheds new light on the actual founding fathers of the domain of human science. In particular, the book provides an understanding of how our human world works and how it is being constituted by utopic systems that look into the future to realize something possible. Finally, it points the way to the future unification of knowledge bringing together systems philosophy and systems science given that world-hypothesis is what makes logically possible the development and consolidation of all the different domains of science.

This book takes the reader through real-world examples for how to characterize and measure the productivity and performance of NFPs and education institutions-that is, organisations that produce value for society, which cannot be measured accurately in financial KPIs. It focuses on how best to frame non-profit performance and productivity, and provides a suite of tools for measurement and benchmarking. It further challenges the reader to consider alternative and appropriate uses of quantitative measures, which are fit-for-purpose in individual contexts. It is true that the risk of misusing quantitative measures is ever-present. But does that risk outweigh the benefits of forming a more precise and shared understanding of what could generate better outcomes? There will always be concerns about policy and performance management. Goodheart's Law states that once a measure becomes a target, it is no longer a good measure. This book helps to strike a meaningful balance between what can be measured, what cannot, and how best to use quantitative information in sectors that are often averse to being held up to the light and put on a scale by outsiders.

Primarily an introduction to the theory of stochastic processes at the undergraduate or beginning graduate level, the primary objective of this book is to initiate students in the art of stochastic modelling. However it is motivated by significant applications and progressively brings the student to the borders of contemporary research. Examples are from a wide range of domains, including operations research and electrical engineering. Researchers and students in these areas as well as in physics, biology and the social sciences will find this book of interest.

The book offers a comprehensive survey of interval-valued intuitionistic fuzzy sets. It reports on cutting-edge research carried out by the founder of the intuitionistic fuzzy sets, Prof. Krassimir Atanassov, giving a special emphasis to the practical applications of this extension. A few interesting case studies, such as in the area of data mining, decision making and pattern recognition, among others, are discussed in detail. The book offers the first comprehensive guide on interval-valued intuitionistic fuzzy sets. By providing the readers with a thorough survey and important practical details, it is expected to support them in carrying out applied research and to encourage them to test the theory behind the sets for new advanced applications. The book is a valuable reference resource for graduate students and researchers alike.

This book aims to provide new research methods, theories and applications from various areas of management and engineering. In detail, the included scientific papers analyze and describe communication processes in the fields of logistics, informatics, service sciences and other related areas. The variety of the papers delivers added value for both scholars and practitioners. Information and communication technologies have been providing an effective network infrastructure and development platform for logistics and service operations. To meet the needs of consumers and to promote core competences, many institutions and firms have been developing new types of services. This proceeding focus on "AI and data driven technical and management innovation in logistics, informatics and services." In detail, the included scientific papers analyze the latest fundamental advances in the state of the art and practice of logistics, informatics, service operations and service science. This book is the documentation of the conference "11th International Conference on Logistics, Informatics and Service Sciences," which took place at the Shandong University. Due to the impact of COVID-19, LISS 2021 took place online as a virtual conference.

The book offers a comprehensive, practice-oriented introduction to the field of fuzzy mathematical programming (FMP) as key topic of modern analytics. FMP plays a fundamental role in dealing with a varied range of problems, such as those concerning smart cities, sustainability, and renewable energies. This book includes an introduction to the basic concepts, together with extensive information on the computational-intelligence-based optimization models and techniques that have been used to date. Special emphasis is given to fuzzy transportation problems. The book is a valuable resource for researchers, data scientists and practitioners dealing with computational-intelligence-based optimization models for analytics.

Management of supply chains has been evolving rapidly over the last few years due to the inception of Industry 4.0, where businesses adopt automation technologies and data exchanges leading to dynamic and interconnected supply chain systems. Emphasizing on analytical approaches such as predictive and prescriptive modeling, this book presents state-of-the-art original research work dealing with advanced analytical models for the design, planning, and operation of the supply chain to provide faster and smarter decisions in the era of digitization. In particular, the book integrates machine learning and operations research models for faster and smarter decisions, presents prescriptive analytics models for strategic, tactical, and operational decision making in the supply chain, and addresses recent challenges such as sustainability in the supply chain, supply chain visibility, and supply chain digitalization. Key concepts are illustrated using real-life case studies, making the book a valuable reference for researchers, technical professionals, and students.

Implementing a food safety management system (FSMS) is a regulatory requirement for every firm in global food supply chains. At any scale, it could be influenced by many factors since the global food supply chains consist of a large number of stakeholders involved with an enormous variety of structures, the logistics of which will undoubtedly change rapidly, scale-up and diversify continuously. This book contains five chapters that aim to give an in-depth exploration of critical success factors (CSF) for food safety management in global supply chains. To fill the identified research gaps, the authors present empirical evidence from their research to verify critical success factors and their relationships with FSMS. Furthermore, the impact of supplier selection and supply chain relationships on food safety management in global supply chains are explored to identify Best Practice in FSMS implementation. This book will appeal to scholars working in food safety management, supply chain management and the impact of globalisation.

This book offers a concise introduction to the field of financial economics and presents, for the first time, recent behavioral finance research findings that help us to understand many puzzles in traditional finance. Tailor-made for master's and PhD students, it includes tests and exercises that enable students to keep track of their progress. Parts of the book can also be used at the bachelor level.

Cognition-driven decision support system (DSS) has been recognized as a paradigm in the research and development of business intelligence (BI). Cognitive decision support aims to help managers in their decision making from human cognitive aspects, such as thinking, sensing, understanding and predicting, and fully reuse their experience. Among these cognitive aspects, decision makers situation awareness (SA) and mental models are considered to be two important prerequisites for decision making, particularly in ill-structured and dynamic decision situations with uncertainties, time pressure and high personal stake. In today s business domain, decision making is becoming increasingly complex. To make a successful decision, managers SA about their business environments becomes a critical factor.

This book presents theoretical models as well practical techniques of cognitiondriven DSS. It first introduces some important concepts of cognition orientation in decision making process and some techniques in related research areas including DSS, data warehouse and BI, offering readers a preliminary for moving forward in this book. It then proposes a cognition-driven decision process (CDDP) model which incorporates SA and experience (mental models) as its central components. The goal of the CDDP model is to facilitate cognitive decision support to managers on the basis of BI systems. It also presents relevant techniques developed to support the implementation of the CDDP model in a BI environment. Key issues addressed of a typical business decision cycle in the CDDP model include: natural language interface for a manager s SA input, extraction of SA semantics, construction of data warehouse queries based on the manger s SA and experience, situation information retrieval from data warehouse, how the manager perceives situation information and update SA, how the manager s SA leads to a final decision. Finally, a cognition-driven DSS, FACETS, and two illustrative applications of this system are discussed."

This book focuses on the adoption of a Dynamic Performance Management (DPM) approach to support the planning and management of urban transportation systems. DPM allows one to embrace a dynamic and systemic perspective and, as a result, to frame the contribution of different stakeholders, in terms of outcome-based performance, at an inter-institutional level. The discussed DPM approach allows one to focus on the causal relationships and feedback processes that characterize urban transportation systems' governance. Particularly, through the adoption of such an approach, it is possible to identify outcome-based performance measures that help to monitor and drive the governance network toward the creation of public value for the reference communities.Strategic Planning for Urban Transportation: A Dynamic Performance Management Approach begins with an examination of urban transportation, highlighting the main criticalities and future challenges of managing it. Next, the book examines the governance of urban transportation including how to identify and engage stakeholders. Finally, the book introduces the main application of DPM and system dynamics to urban areas, with specific regards to transportation. The framework is outlined, and a case study is provided as a practical example of how to apply the model. This book should be useful to urban transportation decision-makers at both the managerial and political level.

30th European Symposium on Computer Aided Chemical Engineering, Volume 47 contains the papers presented at the 30th European Symposium of Computer Aided Process Engineering (ESCAPE) event held in Milan, Italy, May 24-27, 2020. It is a valuable resource for chemical engineers, chemical process engineers, researchers in industry and academia, students, and consultants for chemical industries.

This volume is the third (III) of four under the main themes of Digitizing Agriculture and Information and Communication Technologies (ICT). The four volumes cover rapidly developing processes including Sensors (I), Data (II), Decision (III), and Actions (IV). Volumes are related to 'digital transformation" within agricultural production and provision systems, and in the context of Smart Farming Technology and Knowledge-based Agriculture. Content spans broadly from data mining and visualization to big data analytics and decision making, alongside with the sustainability aspects stemming from the digital transformation of farming. The four volumes comprise the outcome of the 12th EFITA Congress, also incorporating chapters that originated from select presentations of the Congress. The focus of this book (III) is on the transformation of collected information into valuable decisions and aims to shed light on how best to use digital technologies to reduce cost, inputs, and time, toward becoming more efficient and transparent. Fourteen chapters are grouped into 3 Sections. The first section of is dedicated to decisions in the value chain of agricultural products. The next section, titled Primary Production, elaborates on decision making for the improvement of processes taking place with the farm under the implementation of ICT. The last section is devoted to the development of innovative decision applications that also consider the protection of the environment, recognizing its importance in the preservation and considerate use of resources, as well as the mitigation of adverse impacts that are related to agricultural production. Planning and modeling the assessment of agricultural practices can provide farmers with valuable information prior to the execution of any task. This book provides a valuable reference for them as well as for those directly involved with decision making in planning and assessment of agricultural production. Specific advances covered in the volume: Modelling and Simulation of ICT-based agricultural systems Farm Management Information Systems (FMIS) Planning for unmanned aerial systems Agri-robotics awareness and planning Smart livestock farming Sustainable strategic planning in agri-production Food business information systems

This book summarizes years of research in the field of fuzzy relational programming, with a special emphasis on geometric models. It discusses the state-of-the-art in fuzzy relational geometric problems, together with key open issues that must be resolved to achieve a more efficient application of this method. Though chiefly based on research conducted by the authors, who were the first to introduce fuzzy geometric problems, it also covers important findings obtained in the field of linear and non-linear programming. Thanks to its balance of basic and advanced concepts, and its wealth of practical examples, the book offers a valuable guide for both newcomers and experienced researcher in the fields of soft computing and mathematical optimization.

The second edition of Leadership offers a unique, highly-applied academic treatise on leadership, uniquely blending a chronological analysis of the last 100 years of leadership theory with exclusive CEO interviews. The case studies, expert insights and other teaching aids are timely and hard hitting, making this textbook relevant, insightful and informative, while a research chapter empowers the reader to competently question the leaders that shape our world. The world has turned on its political and corporate axis since the first edition of Leadership was published, and it became necessary to produce a second edition that fully encapsulated, respected and observed these changes. Numerous new case studies, discussion starters and examples subsequently reflect today's volatile technological, political, financial and social shifts, while exclusive interviews with successful CEOs powerfully blend theory with practice. Readers will learn the importance of navigating leadership in the most testing of times. A new chapter, 'Researching leadership', offers the reader the opportunity to develop significantly as a leadership researcher and to ably question reality in a post-truth world. A self-leadership chapter equips the reader to develop their own leadership capabilities, while retaining the ability to avoid destructive leadership. Ultimately, readers will become empowered to appreciate the complex, intersectional nature of leadership and to learn what it takes to lead in today's politically, technologically and socially tumultuous world. This book will be particularly engaging for students and educators at secondary school, college, undergraduate and postgraduate level, and for leadership/management consultants. While the book's primary role remains as a core text for leadership, management and business modules, it will also be of interest to students on many other courses (e.g. psychology, politics, sociology). Packed with teaching resources which educators will find particularly useful, Leadership is the only textbook of its kind to offer such an applied view of this subject via the inclusion of 12 (mostly CEO) expert insights. The first edition was an "Amazon Hot New Release", so this second edition might also hold interest for a general readership.

This book introduces readers to an evolutionary learning approach, specifically genetic programming (GP), for production scheduling. The book is divided into six parts. In Part I, it provides an introduction to production scheduling, existing solution methods, and the GP approach to production scheduling. Characteristics of production environments, problem formulations, an abstract GP framework for production scheduling, and evaluation criteria are also presented. Part II shows various ways that GP can be employed to solve static production scheduling problems and their connections with conventional operation research methods. In turn, Part III shows how to design GP algorithms for dynamic production scheduling problems and describes advanced techniques for enhancing GP's performance, including feature selection, surrogate modeling, and specialized genetic operators. In Part IV, the book addresses how to use heuristics to deal with multiple, potentially conflicting objectives in production scheduling problems, and presents an advanced multi-objective approach with cooperative coevolution techniques or multi-tree representations. Part V demonstrates how to use multitask learning techniques in the hyper-heuristics space for production scheduling. It also shows how surrogate techniques and assisted task selection strategies can benefit multitask learning with GP for learning heuristics in the context of production scheduling. Part VI rounds out the text with an outlook on the future. Given its scope, the book benefits scientists, engineers, researchers, practitioners, postgraduates, and undergraduates in the areas of machine learning, artificial intelligence, evolutionary computation, operations research, and industrial engineering.

This volume presents techniques and theories drawn from mathematics, statistics, computer science, and information science to analyze problems in business, economics, finance, insurance, and related fields. The authors present proposals for solutions to common problems in related fields. To this end, they are showing the use of mathematical, statistical, and actuarial modeling, and concepts from data science to construct and apply appropriate models with real-life data, and employ the design and implementation of computer algorithms to evaluate decision-making processes. This book is unique as it associates data science - data-scientists coming from different backgrounds - with some basic and advanced concepts and tools used in econometrics, operational research, and actuarial sciences. It, therefore, is a must-read for scholars, students, and practitioners interested in a better understanding of the techniques and theories of these fields.

This book demonstrates that innovative ideas are systematically constructed in the creative space spanned by the dimensions of systems thinking and knowledge management. Readers will be introduced to this proposition in the final chapter, after learning about the key innovation theories, design thinking, systems thinking, and idea creation methods in systems science and knowledge science. The content provided throughout the book supports knowledge creation in various fields, the management of research and business projects, and the creation of promotion stories for products and services. Practitioners who are seeking to create innovative ideas can systematically learn the minimum theories and methods required, while graduate students will be equipped to link their research to innovation by learning the essence of systems science and knowledge science and considering selected issues. Lastly, the book includes suggestions for future research directions in knowledge science.

This book analyses decision-making in dynamic economic environments. By applying a wide range of methodological approaches, combining both analytical and computational methods, the contributors examine various aspects of optimal firm behaviour and relevant policy areas. Topics covered include optimal control, dynamic games, economic decision-making, and applications in finance and economics, as well as policy implications in areas such as pollution regulation. This book is dedicated to Christophe Deissenberg, a well-known and distinguished scholar of economic dynamics and computational economics. It appeals to academics in the areas of optimal control, dynamic games and computational economics as well as to decision-makers working in policy domains such as environmental policy.

This book has resulted from the activities of IFAC TC 5.2 "Manufacturing Modelling for Management and Control". The book offers an introduction and advanced techniques of scheduling applications to cloud manufacturing and Industry 4.0 systems for larger audience. This book uncovers fundamental principles and recent developments in the theory and application of scheduling methodology to cloud manufacturing and Industry 4.0. The purpose of this book is to present recent developments in scheduling in cloud manufacturing and Industry 4.0 and to systemize these developments in new taxonomies and methodological principles to shape this new research domain. This book addresses the needs of both researchers and practitioners to uncover the challenges and opportunities of scheduling techniques' applications to cloud manufacturing and Industry 4.0. For the first time, it comprehensively conceptualizes scheduling in cloud manufacturing and Industry 4.0 systems as a new research domain. The chapters of the book are written by the leading international experts and utilize methods of operations research, industrial engineering and computer science. Such a multi-disciplinary combination is unique and comprehensively deciphers major problem taxonomies, methodologies, and applications to scheduling in cloud manufacturing and Industry 4.0.

Global Logistics Network Modelling and Policy provides guidelines on quality policy, covering investments, management and planning for port and hinterland infrastructure, roads, railways and inland waterway ports. The book first describes the authors' concept and formulation models, followed by a description and analysis of the applied data. As shipping companies fiercely compete in an effort to achieve greater efficiency and impact infrastructure policy and plan for the entire supply chain, they need tactics that drive quality transportation policy and new ways to model and simulate worldwide cargo movements, all while estimating demand and capacity of systems. This book provides quantitative tools for modeling, analysis, and simulation of worldwide, inter-modal cargo movement - helping forecast the impacts of logistics and related policies in each region of the world. It covers useful applications for every region of the world, allowing policymakers to tailor results for their own specific uses.