Business Statistics narrows the gap between theory and practice by focusing on relevant statistical methods, thus empowering business students to make good, data-driven decisions. Using the latest GAISE (Guidelines for Assessment and Instruction in Statistics Education) report, which included extensive revisions to reflect both the evolution of technology and new wisdom on statistics education, this edition brings a modern edge to teaching business statistics. This includes a focus on the report's key recommendations: teaching statistical thinking, focusing on conceptual understanding, integrating real data with a context and a purpose, fostering active learning, using technology to explore concepts and analyse data, and using assessments to improve and evaluate student learning. By presenting statistics in the context of real-world businesses and by emphasising analysis and understanding over computation, this book helps students be more analytical, prepares them to make better business decisions, and shows them how to effectively communicate results. Samples Preview the detailed table of contents Download a sample chapter from Business Statistics, Global Edition, 4th Edition

Throughout the world, artificial intelligence is reshaping businesses, trade interfaces, economic activities, and society as a whole. In recent years, scholarly research on artificial intelligence has emerged from a variety of empirical and applied domains of knowledge. Computer scientists have developed advanced deep learning algorithms to leverage its utility in a variety of fields such as medicine, energy, travel, education, banking, and business management. Although a growing body of literature is shedding light on artificial intelligence-enabled difficulties, there is still much to be gained by applying fresh theory-driven techniques to this vital topic. Revolutionizing Business Practices Through Artificial Intelligence and Data-Rich Environments provides a comprehensive understanding of the business systems, platforms, procedures, and mechanisms that underpin different stakeholders' experiences with reality-enhancing technologies and their transformative application in management. The book also identifies areas in various business processes where artificial intelligence intervention would not only transform the business but would also make the business more sustainable. Covering key topics such as blockchain, business automation, and manufacturing, this reference work is ideal for computer scientists, business owners, managers, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.

Current social, economic, and environmental challenges presented by the United Nations' Sustainable Development Goals may be partially attained by digitalization and sustainable practices diffusion. The antecedents, occurrences, and consequences of this process are currently under investigation, but the big challenge is to get a systemic view. This book attempts to bring such a view into focus. Digital and Sustainable Transformations in a Post-COVID World is dedicated to studying the consequences of the global crisis caused by the COVID-19 pandemic and the new needs and practices inherent in developing and disseminating digital and clean technologies.

For courses in business mathematics, personal finance, or small business management. Business Math Brief, Tenth Edition unlocks the world of math by showing how it is used in the business world. Written in a conversational style, the book covers essential topics such as banking, interest, insurance, taxes, depreciation, and inventory. It carefully explains common business practices such as markup, markdown, and cash discounts-showing students how these tools work in small business or personal finance. Authors encourage self-starters from the beginning, with the review of basic math, annotated examples, stop and check exercises, skill builders and application exercises. This edition includes updated problem sets, new trends and laws, and the one-of-a-kind MyMathLab website.

A balanced and holistic approach to business analytics Business Analytics teaches the fundamental concepts of modern business analytics and provides vital tools in understanding how data analysis works in today's organisations. Author James Evans takes a fair and comprehensive, approach, examining business analytics from both descriptive and predictive perspectives. Students learn how to apply basic principles, communicate with analytics professionals, and effectively use and interpret analytic models to make better business decisions. And included access to commercial grade analytics software gives students real-world experience and career-focused value. As such, the 3rd Edition has gone through an extensive revision and now relies solely on Excel, enhancing students' skills in the program and basic understanding of fundamental concepts.

The success of any organization is largely dependent on positive feedback and repeat business from patrons. By utilizing acquired marketing data, business professionals can more accurately assess practices, services, and products that their customers find appealing. The Handbook of Research on Intelligent Techniques and Modeling Applications in Marketing Analytics features innovative research and implementation practices of analytics in marketing research. Highlighting various techniques in acquiring and deciphering marketing data, this publication is a pivotal reference for professionals, managers, market researchers, and practitioners interested in the observation and utilization of data on marketing trends to promote positive business practices.

For any organization, analysis of performance and effectiveness through available data allows for informed decision making. Data envelopment analysis, or DEA, is a popular, effective method that can be used to measure productive efficiency in operations management assessment. Data Envelopment Analysis and Effective Performance Assessment addresses the myriad of practical uses and innovative developments of DEA. Emphasizing the importance of analyzing productivity by measuring inputs, goals, economic growth, and performance, this book covers a wide breadth of innovative knowledge. This book is essential reading for managers, business professionals, students of business and ICT, and computer engineers.

Over the past decade, platforms have spread through many industries and generated an increasing share of the global economy. Many of the world's most valuable companies have adopted a platform-based business model and today, we find that platforms pervade our everyday lives. So far, however, the existing management literature has failed to provide professionals and students with appropriate tools to understand the business models that make those platforms successful. This book offers rigorous analysis of the complexity of platforms, as well as practical strategic guidance and tools to help you deal with this complexity. Written in an accessible style and based on a comprehensive approach, Platform Strategies is self-contained and does not require the reader to have specific prior knowledge. The book is both academically rigorous and a pragmatic and efficient guide, incorporating path-breaking insights from academic research on platforms with real-world applications of concepts and tools. The book engages with case studies and highlights important take-aways that can be implemented in practice. You'll learn how to use new tools of strategic management and how to adapt well-established ones. This book is an invaluable resource for entrepreneurs (experienced or aspiring), managers of existing platforms and businesses, professionals, and students in business, management and economics.

Fuzzy cognitive maps (FCMs) have gained popularity in the scientific community due to their capabilities in modeling and decision making for complex problems.This book presents a novel algorithm called glassoFCM to enable automatic learning of FCM models from data. Specifically, glassoFCM is a combination of two methods, glasso (a technique originated from machine learning) for data modeling and FCM simulation for decision making. The book outlines that glassoFCM elaborates simple, accurate, and more stable models that are easy to interpret and offer meaningful decisions. The research results presented are based on an investigation related to a real-world business intelligence problem to evaluate characteristics that influence employee work readiness.Finally, this book provides readers with a step-by-step guide of the 'fcm' package to execute and visualize their policies and decisions through the FCM simulation process.

We are living in interesting times characterized by increasing digitalization of business enterprises in a global interconnected knowledge economy. With waning euphoria about the first wave of digital e-business enterprises and a sobering dot-com stock market, business model innovation is being recognized as the key enabler that can unleash value creation for new digital enterprises. In contrast to traditional factors of production, knowledge assets and intellectual capital are expected to play a dominant role in determining both valuation and value-creation capabilities of most new age enterprises. Not surprisingly, Knowledge Management for Business Model Innovation is anticipated to be the mantra for survival, competence and success of Net enterprises as well as traditional brick-and-mortar enterprises faced with the challenge of transforming their business models into and beyond click-and-mortar companies.

This book encompasses a systematic exploration of Cybersecurity Data Science (CSDS) as an emerging profession, focusing on current versus idealized practice. This book also analyzes challenges facing the emerging CSDS profession, diagnoses key gaps, and prescribes treatments to facilitate advancement. Grounded in the management of information systems (MIS) discipline, insights derive from literature analysis and interviews with 50 global CSDS practitioners. CSDS as a diagnostic process grounded in the scientific method is emphasized throughout Cybersecurity Data Science (CSDS) is a rapidly evolving discipline which applies data science methods to cybersecurity challenges. CSDS reflects the rising interest in applying data-focused statistical, analytical, and machine learning-driven methods to address growing security gaps. This book offers a systematic assessment of the developing domain. Advocacy is provided to strengthen professional rigor and best practices in the emerging CSDS profession. This book will be of interest to a range of professionals associated with cybersecurity and data science, spanning practitioner, commercial, public sector, and academic domains. Best practices framed will be of interest to CSDS practitioners, security professionals, risk management stewards, and institutional stakeholders. Organizational and industry perspectives will be of interest to cybersecurity analysts, managers, planners, strategists, and regulators. Research professionals and academics are presented with a systematic analysis of the CSDS field, including an overview of the state of the art, a structured evaluation of key challenges, recommended best practices, and an extensive bibliography.

Information modeling plays an important role in every level of the enterprise information system's architecture. Modeling allows organizations to adapt and become more efficient, helping top managers and engineers outline tactics to reach strategic objectives, understand organizational needs, and design information systems that are aligned with business goals. New Perspectives on Information Systems Modeling and Design is an essential reference source that discusses organizational adaptation through the integration of new information technologies into existing processes and underlying supporting applications. Featuring research on topics such as application integration, change management, and mobile process activities, this book is ideally designed for managers, researchers, system developers, entrepreneurs, graduate-level students, business professionals, information system engineers, and academicians seeking coverage on emerging technological developments and practical solutions for system modeling and design.

Operations management is a tool by which companies can effectively meet customers' needs using the least amount of resources necessary. With the emergence of sensors and smart metering, big data is becoming an intrinsic part of modern operations management. Applied Big Data Analytics in Operations Management enumerates the challenges and creative solutions and tools to apply when using big data in operations management. Outlining revolutionary concepts and applications that help businesses predict customer behavior along with applications of artificial neural networks, predictive analytics, and opinion mining on business management, this comprehensive publication is ideal for IT professionals, software engineers, business professionals, managers, and students of management.

The ultimate textbook in Business Information Systems for future Managers Business Information Systems: Technology, Development and Management for the Modern Business, 6th Edition by Bocij, Greasley, and Hickie is a leading text that will help you understand the relevance and impact of information systems in today's business environment. Written in a language that is easy to follow, this text does not assume any prior knowledge of IS or ICT and is ideal for students attending courses related to Business Information Systems and Management Information Systems at an Undergraduate or Postgraduate level. Starting from basic concepts this book provides a comprehensive and accessible guide to: understanding the technology of Business Information Systems choosing the right Information System for an organisation developing and managing an efficient Business Information System employing information systems strategically to achieve organisational goals Taking a problem-solving approach, this thoroughly revised edition defines new concepts and studies the theory of information systems according to the most recent business and technological advances, covering contemporary key topics such as: Big Data Analytics Cloud Computing Industry 4.0 Internet of Things With new business examples, case studies, and web links fully integrated throughout, this must-have guide will provide you with all the tools you need to understand the opportunities and benefits Information Systems bring to an organisation and successfully run a business.

While good data is an enterprise asset, bad data is an enterprise liability. Data governance enables you to effectively and proactively manage data assets throughout the enterprise by providing guidance in the form of policies, standards, processes and rules and defining roles and responsibilities outlining who will do what, with respect to data. While implementing data governance is not rocket science, it is not a simple exercise. There is a lot confusion around what data governance is, and a lot of challenges in the implementation of data governance. Data governance is not a project or a one-off exercise but a journey that involves a significant amount of effort, time and investment and cultural change and a number of factors to take into consideration to achieve and sustain data governance success. Data Governance Success: Growing and Sustaining Data Governance is the third and final book in the Data Governance series and discusses the following: * Data governance perceptions and challenges * Key considerations when implementing data governance to achieve and sustain success* Strategy and data governance* Different data governance maturity frameworks* Data governance - people and process elements* Data governance metrics This book shares the combined knowledge related to data and data governance that the author has gained over the years of working in different industrial and research programs and projects associated with data, processes, and technologies and unique perspectives of Thought Leaders and Data Experts through Interviews conducted. This book will be highly beneficial for IT students, academicians, information management and business professionals and researchers to enhance their knowledge to support and succeed in data governance implementations. This book is technology agnostic and contains a balance of concepts and examples and illustrations making it easy for the readers to understand and relate to their own specific data projects.

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.

Appropriate for one or two term courses in introductory Business Statistics. With Statistics for Management, Levin and Rubin have provided a non-intimidating business statistics textbook that students can easily read and understand. Like its predecessors, the Seventh Edition includes the absolute minimum of mathematical/statistical notation necessary to teach the material. Concepts are fully explained in simple, easy-to-understand language as they are presented, making the text an excellent source from which to learn and teach. After each discussion, readers are guided through real-world examples to show how textbook principles work in professional practice.

Business models are regarded as a main emerging topic in the management area for opportune science-driven practical conceptions and applications. They represent how organizations are proposed and planned, as well as how they establish a market and social relations, manage strategic resources, and make decisions. However, companies must produce new solutions for strategic sustainability, performance measurement, and overall managerial conditions for these business models to be implemented effectively. The Handbook of Research on Business Models in Modern Competitive Scenarios depicts how business models contribute to strategic competition in this new era of technological and social changes as well as how they are conceptualized, studied, designed, implemented, and in the end, how they can be improved. Featuring research on topics such as creating shared value, global scenarios, and organizational intelligence, this book provides pivotal information for scientific researchers, business decision makers, strategic planners, consultants, managers, and academicians.

This book provides conceptual understanding of machine learning algorithms though supervised, unsupervised, and advanced learning techniques. The book consists of four parts: foundation, supervised learning, unsupervised learning, and advanced learning. The first part provides the fundamental materials, background, and simple machine learning algorithms, as the preparation for studying machine learning algorithms. The second and the third parts provide understanding of the supervised learning algorithms and the unsupervised learning algorithms as the core parts. The last part provides advanced machine learning algorithms: ensemble learning, semi-supervised learning, temporal learning, and reinforced learning. Provides comprehensive coverage of both learning algorithms: supervised and unsupervised learning; Outlines the computation paradigm for solving classification, regression, and clustering; Features essential techniques for building the a new generation of machine learning.

This book projects a futuristic scenario that is more existent than they have been at any time earlier. To be conscious of the bursting prospective of IoT, it has to be amalgamated with AI technologies. Predictive and advanced analysis can be made based on the data collected, discovered and analyzed. To achieve all these compatibility, complexity, legal and ethical issues arise due to automation of connected components and gadgets of widespread companies across the globe. While these are a few examples of issues, the authors' intention in editing this book is to offer concepts of integrating AI with IoT in a precise and clear manner to the research community. In editing this book, the authors' attempt is to provide novel advances and applications to address the challenge of continually discovering patterns for IoT by covering various aspects of implementing AI techniques to make IoT solutions smarter. The only way to remain pace with this data generated by the IoT and acquire the concealed acquaintance it encloses is to employ AI as the eventual catalyst for IoT. IoT together with AI is more than an inclination or existence; it will develop into a paradigm. It helps those researchers who have an interest in this field to keep insight into different concepts and their importance for applications in real life. This has been done to make the edited book more flexible and to stimulate further interest in topics. All these motivated the authors toward integrating AI in achieving smarter IoT. The authors believe that their effort can make this collection interesting and highly attract the student pursuing pre-research, research and even master in multidisciplinary domain.

This book delves into the concept of data as a critical enterprise asset needed for informed decision making, compliance, regulatory reporting and insights into trends, behaviors, performance and patterns. With good data being key to staying ahead in a competitive market, enterprises capture and store exponential volumes of data. Considering the business impact of data, there needs to be adequate management around it to derive the best value. Data governance is one of the core data management related functions. However, it is often overlooked, misunderstood or confused with other terminologies and data management functions. Given the pervasiveness of data and the importance of data, this book provides comprehensive understanding of the business drivers for data governance and benefits of data governance, the interactions of data governance function with other data management functions and various components and aspects of data governance that can be facilitated by technology and tools, the distinction between data management tools and data governance tools, the readiness checks to perform before exploring the market to purchase a data governance tool, the different aspects that must be considered when comparing and selecting the appropriate data governance technologies and tools from large number of options available in the marketplace and the different market players that provide tools for supporting data governance. This book combines the data and data governance knowledge that the author has gained over years of working in different industrial and research programs and projects associated with data, processes and technologies with unique perspectives gained through interviews with thought leaders and data experts. This book is highly beneficial for IT students, academicians, information management and business professionals and researchers to enhance their knowledge and get guidance on implementing data governance in their own data initiatives.

In the past, practical applications motivated the development of mathematical theories, which then became the subject of study in pure mathematics where abstract concepts are studied for their own sake. The activity of applied mathematics is thus intimately connected with research in pure mathematics, which is also referred to as theoretical mathematics. Theoretical and Applied Mathematics in International Business is an essential research publication that explores the importance and implications of applied and theoretical mathematics within international business, including areas such as finance, general management, sales and marketing, and supply chain management. Highlighting topics such as data mining, global economics, and general management, this publication is ideal for scholars, specialists, managers, corporate professionals, researchers, and academicians.