Continuous improvements in digitized practices have created opportunities for businesses to develop more streamlined processes. This not only leads to higher success in day-to-day production, but it increases the overall success of businesses. Enterprise Information Systems and the Digitalization of Business Functions is a key resource on the latest advances and research for a digital agenda in the business world. Highlighting multidisciplinary studies on data modeling, information systems, and customer relationship management, this publication is an ideal reference source for professionals, researchers, managers, consultants, and university students interested in emerging developments for business process management.

The vast amount of information that must be considered to solve inherently ill-structured and complex strategic problems creates a need for tools and techniques to help decision-makers recognize the complexity of this process and develop a rational model for strategy evaluation. Decision Making Theories and Practices from Analysis to Strategy is a definitive focus on analytical strategic decision-making. This work is comprised of sophisticated tools and methodologies developed by researchers and vendors to improve decision making for business strategy. Extracting from a wide range of disciplines, including accounting, finance, information systems, international management, marketing, organizational management, operations research, production and operations management, and strategic management, this volume provides a conceptual and a utilitarian guide to decision making, perfect for both researchers and practicing professionals alike.

Big data analytics utilizes a wide range of software and analytical tools to provide immediate, relevant information for efficient decision-making. Companies are recognizing the immense potential of BDA, but ensuring the data is appropriate and error-free is the largest hurdle in implementing BDA applications. The Handbook of Research on Organizational Transformations through Big Data Analytics not only catalogues the existing platforms and technologies, it explores new trends within the field of big data analytics (BDA). Containing new and existing research materials and insights on the various approaches to BDA; this publication is intended for researchers, IT professionals, and CIOs interested in the best ways to implement BDA applications and technologies.

There is an immense amount of information to be considered when attempting to solve complex strategic problems. To recognize the complexity of this process, the creation of tools and techniques are essential to aid decision makers in developing a rational model for strategy evaluation. Management Theories and Strategic Practices for Decision Making brings together a collection of research aiming to provide communication for the management of new methodologies to solve strategic problems and applying decision making approaches. This reference is useful for government agencies, practicing managers, academic and research institutions interested in bringing together strategic decision-making and decision sciences.

Businesses are collecting massive amounts of data every day as a way to better understand their processes, competition, and the markets they serve. This data can be used to increase organizational productivity and performance; however, is essential that organizations collecting large data sets have the tools available to them to fully understand the data they are collecting. Organizational Productivity and Performance Measurements Using Predictive Modeling and Analytics takes a critical look at methods for enhancing an organization's operations and day-to-day activities through the effective use of data. Focusing on a variety of applications of predictive analytics within organizations of all types, this critical publication is an essential resource for business managers, data scientists, graduate-level students, and researchers.

As there is a vast amount of information to consider when offering quality services, organisations have developed techniques for identifying risk factors to be taken into consideration when constructing effective business strategies. Developing Business Strategies and Identifying Risk Factors in Modern Organizations presents new methodologies currently being utilised to formulate and solve strategic issues in order to escape the jeopardy of possible business risks. By highlighting a multitude of sciences and their influences on modern organisations; this book is an essential reference for decision makers and researchers in business, industry, government, and academia.

Using interdisciplinary approaches to strategic management can strengthen the decision making process. Incorporating various methods will also encourage productivity, expand knowledge of participants, and increase technical proficiency. Analytical Approaches to Strategic Decision-Making: Interdisciplinary Considerations aims to integrate different techniques into the world s fast-changing and dynamic society to better equip all readers and practitioners with the most effective knowledge. Managers, CEOs, researchers, and academics in the fields of business and leadership will all benefit from this valuable resource through an enhanced understanding of best practices in decision-making and management."

Global markets and competition have forced companies to operate in a physically distributed environment to take the advantage of benefits of strategic alliances between partnering firms. With global operations in place, there is a need for suitable Enterprise Information Systems (EIS) such as Enterprise Resource Planning (ERP) and E-Commerce (EC) for the integration of extended enterprises along the supply chain with the objective of achieving flexibility and responsiveness. Enterprise Information Systems and Advancing Business Solutions: Emerging Models is to provide comprehensive coverage and understanding of various enterprise information systems (EIS) such as enterprise resource planning (ERP) and electronic commerce (EC) and their implications on supply chain management and organizational competitiveness. Design, development, and implementation issues of EIS including ERP and EC will be discussed. These include organizational, people, and technological issues of EIS. This title will also expand the knowledge on ERP and EC and in turn help researchers and practitioners to develop suitable strategies, tactics, and operational policies for EIS and for improving communication in organizations.

The intensity of global competition and ever-increasing economic uncertainties has led organizations to search for more efficient and effective ways to manage their business operations. Data envelopment analysis (DEA) has been widely used as a conceptually simple yet powerful tool for evaluating organizational productivity and performance. Fuzzy DEA (FDEA) is a promising extension of the conventional DEA proposed for dealing with imprecise and ambiguous data in performance measurement problems. This book is the first volume in the literature to present the state-of-the-art developments and applications of FDEA. It is designed for students, educators, researchers, consultants and practicing managers in business, industry, and government with a basic understanding of the DEA and fuzzy logic concepts.

This edited volume is brought out from the contributions of the research papers presented in the International Conference on Data Science and Business Analytics (ICDSBA- 2017), which was held during September 23-25 2017 in ChangSha, China. As we all know, the field of data science and business analytics is emerging at the intersection of the fields of mathematics, statistics, operations research, information systems, computer science and engineering. Data science and business analytics is an interdisciplinary field about processes and systems to extract knowledge or insights from data. Data science and business analytics employ techniques and theories drawn from many fields including signal processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition, visualization, descriptive analytics, predictive analytics, prescriptive analytics, uncertainty modeling, big data, data warehousing, data compression, computer programming, business intelligence, computational intelligence, and high performance computing among others. The volume contains 55 contributions from diverse areas of Data Science and Business Analytics, which has been categorized into five sections, namely: i) Marketing and Supply Chain Analytics; ii) Logistics and Operations Analytics; iii) Financial Analytics. iv) Predictive Modeling and Data Analytics; v) Communications and Information Systems Analytics. The readers shall not only receive the theoretical knowledge about this upcoming area but also cutting edge applications of this domains.

Enterprise Information Systems (EIS), as business management systems, seek to combine all aspects of an organization. EIS facilitate enterprise-wide integrated information systems (IS) covering all functional areas of the organization and performing core business activities. In today s uncertain and complex business environment, EIS are critical to organizations. Managing Adaptability, Intervention, and People in Enterprise Information Systems highlights ongoing issues in three areas having implications for EIS: adaptability, intervention, and people. This book discusses the role of change management, conversion management, readiness management, knowledge management, e-business management, people management, and stakeholder management for a competitive advantage in EIS. Ongoing research on EIS is vital to provide insights into the challenges, issues, and solutions related to management of various aspects of EIS in our ever changing world.

Healthcare practices have been enhanced through the use of information technologies and analytical methods. A cross between computer science, healthcare, and information science is needed for the optimization of data resources and information systems within the healthcare industry. Healthcare Informatics and Analytics: Emerging Issues and Trends introduces the latest research concerning the innovative implementation of information technology and data analysis in the healthcare field. Highlighting current concerns and recent advances in patient care and healthcare delivery, this book is a comprehensive reference source for academics, researchers, medical students, and healthcare practitioners interested in the application of information science within the health sector.

This book reports on the proceeding of the 5th International Conference on Intelligent, Interactive Systems and Applications (IISA 2020), held in Shanghai, China, on September 25-27, 2020. The IISA proceedings, with the latest scientific findings, and methods for solving intriguing problems, are a reference for state-of-the-art works on intelligent and interactive systems. This book covers nine interesting and current topics on different systems' orientations, including Analytical Systems, Database Management Systems, Electronics Systems, Energy Systems, Intelligent Systems, Network Systems, Optimization Systems, and Pattern Recognition Systems and Applications. The chapters included in this book cover significant recent developments in the field, both in terms of theoretical foundations and their practical application. An important characteristic of the works included here is the novelty of the solution approaches to the most interesting applications of intelligent and interactive systems.

This book discusses an emerging field of decision science that focuses on business processes and systems used to extract knowledge from large volumes of data to provide significant insights for crucial decisions in critical situations. It presents studies employing computing techniques like machine learning, which explore decision-making for cross-platforms that contain heterogeneous data associated with complex assets, leadership, and team coordination. It also reveals the advantages of using decision sciences with management-oriented problems. The book includes a selection of the best papers presented at the 2nd International Conference on Decision Science and Management (ICDSM 2019), held at Hunan International Economics University, China, on 20-21 September 2019.

This edited book is based on the research papers presented at the 4th International Conference on Intelligent, Interactive Systems and Applications (IISA2019), held on June 28-30, 2019 in Bangkok, Thailand. Interactive intelligent systems (IIS) are systems that interact with human beings, media or virtual agents in intelligent computing environments. This book explores how novel interactive systems can intelligently address various challenges and also limitations previously encountered by human beings using different machine learning algorithms, and analyzes recent trends. The book includes contributions from diverse areas of IIS, here categorized into seven sections, namely i) Intelligent Systems; ii) Autonomous Systems; iii) Pattern Recognition and Computer Vision; iv) E-Enabled Systems; v) Internet & Cloud Computing; vi) Mobile & Wireless Communication; and vii) Various Applications. It not only presents theoretical knowledge on the intelligent and interactive systems but also discusses various applications pertaining to different domains.

This book discusses an emerging area in computer science, IT and management, i.e., decision sciences and management. It includes studies that employ various computing techniques like machine learning to generate insights from huge amounts of available data; and which explore decision-making for cross-platforms that contain heterogeneous data associated with complex assets; leadership; and team coordination. It also reveals the advantages of using decision sciences with management-oriented problems. The book includes a selection of the best papers presented at the International Conference on Decision Science and Management 2018 (ICDSM 2018), held at the Interscience Institute of Management and Technology (IIMT), Bhubaneswar, India.

This edited volume is brought out from the contributions of the research papers presented in the International Conference on Data Science and Business Analytics (ICDSBA- 2017), which was held during September 23-25 2017 in ChangSha, China. As we all know, the field of data science and business analytics is emerging at the intersection of the fields of mathematics, statistics, operations research, information systems, computer science and engineering. Data science and business analytics is an interdisciplinary field about processes and systems to extract knowledge or insights from data. Data science and business analytics employ techniques and theories drawn from many fields including signal processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition, visualization, descriptive analytics, predictive analytics, prescriptive analytics, uncertainty modeling, big data, data warehousing, data compression, computer programming, business intelligence, computational intelligence, and high performance computing among others. The volume contains 55 contributions from diverse areas of Data Science and Business Analytics, which has been categorized into five sections, namely: i) Marketing and Supply Chain Analytics; ii) Logistics and Operations Analytics; iii) Financial Analytics. iv) Predictive Modeling and Data Analytics; v) Communications and Information Systems Analytics. The readers shall not only receive the theoretical knowledge about this upcoming area but also cutting edge applications of this domains.

This book presents the proceedings of the International Conference on Intelligent, Interactive Systems and Applications (IISA2018), held in Hong Kong, China on June 29-30, 2018. It consists of contributions from diverse areas of intelligent interactive systems (IIS), such as: autonomous systems; pattern recognition and vision systems; e-enabled systems; mobile computing and intelligent networking; Internet & cloud computing; intelligent systems and applications. The book covers the latest ideas and innovations from both the industrial and academic worlds, and shares the best practices in the fields of computer science, communication engineering and latest applications of IOT and its use in industry. It also discusses key research outputs, providing readers with a wealth of new ideas and food for thought.

Providing a central organisation for shared information, large businesses continue to rely on enterprise information systems to offer quality service when deadline with large volumes of data. Competition, Strategy, and Modern Enterprise Information Systems provides extensive coverage on the organisational, managerial and technologies concerns of enterprise information systems and its executive competitiveness. This collection of original research aims to bring together a discussion for innovative ideas and developments in the EIS field.

The intensity of global competition and ever-increasing economic uncertainties has led organizations to search for more efficient and effective ways to manage their business operations. Data envelopment analysis (DEA) has been widely used as a conceptually simple yet powerful tool for evaluating organizational productivity and performance. Fuzzy DEA (FDEA) is a promising extension of the conventional DEA proposed for dealing with imprecise and ambiguous data in performance measurement problems. This book is the first volume in the literature to present the state-of-the-art developments and applications of FDEA. It is designed for students, educators, researchers, consultants and practicing managers in business, industry, and government with a basic understanding of the DEA and fuzzy logic concepts.

This book discusses an emerging area in computer science, IT, and management, i.e., decision sciences and management. It includes studies that employ various computing techniques like machine learning to generate insights from huge amounts of available data; and which explore decision making for cross-platforms that contain heterogeneous data associated with complex assets; leadership; and team coordination. It also reveals the advantages of using decision sciences with management-oriented problems. The book includes a selection of the best papers presented at the Third International Conference on Decision Science and Management 2021 (ICDSM 2021), held at Hang Seng University of Hong Kong in China.

This edited book presents contributions from three different areas: cloud computing, digital mess and business algorithms on a single platform, i.e. Digital Business. The book is divided into four sections: (i) Digital Business Transformation, (ii) Cloud Computing, (iii) IOT & Mobility, and (iv) Information Management & Social Media, which are part of a holistic approach to information management and connecting the value chains of businesses to derive more throughput in the entire business ecosystem. Digital business is a niche area of computer science and business management, and its dimension is vast - it includes technologies such as cloud computing, Internet of Things, mobile platforms, big data applied in areas like ERP, data mining and business intelligence. Digital technologies have also challenged existing business models and will continue to do so. One of the key driving forces is the capacity of innovation and the commercialization of information and communication technologies. Providing insights into the new paradigm of digital business, the book is a valuable resource for research scholars, academics and professionals.