Kirjahaku

One of the most important tasks faced by decision-makers in business and government is that of selection. Selection problems are challenging in that they require the balancing of multiple, often conflicting, criteria. In recent years, a number of interesting decision aids have become available to assist in such decisions. The aim of this book is to provide a comparative survey of many of the decision aids currently available. The first chapters present general ideas which underpin the methodologies used to design these aids. Subsequent chapters then focus on specific decision aids and demonstrate some of the software which implement these ideas. A final chapter provides a comparative analysis of their strengths and weaknesses.

Enterprise Risk Management in Finance is a guide to measuring and managing Enterprise-wide risks in financial institutions. Financial institutions operate in a unique manner when compared to other businesses. They are, by the nature of their business, highly exposed to risk at every level, and indeed employ their own risk management functions to manage many of these risks. However, financial firms are also highly exposed at enterprise level. Traditional approaches and frameworks for ERM are flawed when applied to banks, asset managers or insurance houses, and a different approach is needed. This new book provides a comprehensive, technical guide to ERM for financial institutions. Split into three parts, it first sets the scene, putting ERM in the context of finance houses. It will examine the financial risks already inherent in banking, and then insurance operations, and how these need to be accounted for at a floor and enterprise level. The book then provides the necessary tools to implement ERM in these environments, including performance analysis, credit analysis and forecasting applications. Finally, the book provides real life cases of successful and not so successful ERM in financial institutions. Technical and rigorous, this book will be a welcome addition to the literature in this area, and will appeal to risk managers, actuaries, regulators and senior managers in banks and financial institutions.

One of the most important tasks faced by decision-makers in business and government is that of selection. Selection problems are challenging in that they require the balancing of multiple, often conflicting, criteria. In recent years, a number of interesting decision aids have become available to assist in such decisions. The aim of this book is to provide a comparative survey of many of the decision aids currently available. The first chapters present general ideas which underpin the methodologies used to design these aids. Subsequent chapters then focus on specific decision aids and demonstrate some of the software which implement these ideas. A final chapter provides a comparative analysis of their strengths and weaknesses.

Data mining has become the fastest growing topic of interest in business programs in the past decade. This book is intended to describe the benefits of data mining in business, the process and typical business applications, the workings of basic data mining models, and demonstrate each with widely available free software.

This book addresses project management in the context of general project management.An introductory chapter discusses project features in general. Part I of the book focuses attention on the important human element in project management. Part II discusses two processes involved in the initial project definition stage, as well as covering estimation. Part III involves planning and project risk and implementation.A feature of the book is an effort to tie content to that of the Project Management Body of Knowledge (PMBOK). Each chapter includes reference to how each chapter relates to the PMBOK structure, and relationship to the 2020 PMP Exam Outline.

Information Systems Project Management addresses project management in the context of information systems. It deals with general project management principles, with focus on the special characteristics of information systems. It is based on an earlier text, but shortened to focus on essential project management elements.This updated version presents various statistics indicating endemic problems in completing information system projects on time, within budget, at designed functionality. While successful completion of an information systems project is a challenge, there are some things that can be done to improve the probability of project success. This book reviews a number of project management tools, including, developing organizational ability to work on projects, better systems analysis and design, project estimation, and project control and termination.

This book addresses the use of quantitative tools to support general project management.Part I of the book deals with critical path modeling. Part II discusses risk modeling tools to include Program Evaluation and Review Technique (PERT), critical chain modeling, and agile/scrum approaches. Project control through earned value analysis is also covered. Part III is a Microsoft Project orientation. A feature of the book is an effort to tie content to that of the Project Management Body of Knowledge (PMBOK).Each chapter includes reference to how each chapter relates to the PMBOK structure and its relationship to the 2020 Project Management Professional (PMP) Exam Outline.

Data mining has become the fastest growing topic of interest in business programs in the past decade. This book is intended to describe the benefits of data mining in business, the process and typical business applications, the workings of basic data mining models, and demonstrate each with widely available free software. The book focuses on demonstrating common business data mining applications. It provides exposure to the data mining process, to include problem identification, data management, and available modeling tools. The book takes the approach of demonstrating typical business data sets with open source software. KNIME is a very easy-to-use tool, and is used as the primary means of demonstration. R is much more powerful and is a commercially viable data mining tool. We also demonstrate WEKA, which is a highly useful academic software, although it is difficult to manipulate test sets and new cases, making it problematic for commercial use.

This book addresses project management in the context of general project management.An introductory chapter discusses project features in general. Part I of the book focuses attention on the important human element in project management. Part II discusses two processes involved in the initial project definition stage, as well as covering estimation. Part III involves planning. Part III deals with project risk and implementation.A feature of the book is an effort to tie content to that of the Project Management Body of Knowledge (PMBOK). Each chapter includes reference to how each chapter relates to the PMBOK structure, and relationship to the 2020 PMP Exam Outline.

This book addresses the use of quantitative tools to support general project management. Part I of the book deals with critical path modeling. Part II discusses risk modeling tools to include Program Evaluation and Review Technique (PERT), critical chain modeling, and agile/scrum approaches. Project control through earned value analysis is also covered. Part III is a Microsoft Project orientation. A feature of the book is an effort to tie content to that of the Project Management Body of Knowledge (PMBOK).Each chapter includes reference to how each chapter relates to the PMBOK structure and its relationship to the 2020 Project Management Professional (PMP) Exam Outline.

This book offers an overview of knowledge management. It starts with an introduction to the subject, placing descriptive models in the context of the overall field as well as within the more specific field of data mining analysis. Chapter 2 covers data visualization, including directions for accessing R open source software (described through Rattle). Both R and Rattle are free to students. Chapter 3 then describes market basket analysis, comparing it with more advanced models, and addresses the concept of lift. Subsequently, Chapter 4 describes smarketing RFM models and compares it with more advanced predictive models. Next, Chapter 5 describes association rules, including the APriori algorithm and provides software support from R. Chapter 6 covers cluster analysis, including software support from R (Rattle), KNIME, and WEKA, all of which are open source. Chapter 7 goes on to describe link analysis, social network metrics, and open source NodeXL software, and demonstrates link analysis application using PolyAnalyst output. Chapter 8 concludes the monograph.Using business-related data to demonstrate models, this descriptive book explains how methods work with some citations, but without detailed references. The data sets and software selected are widely available and can easily be accessed.

This book is devoted to presenting models that have been applied in project management. There are a variety of project domains. We discuss engineering/construction projects, software development projects, massive projects to include governmental undertakings, and pharmaceutical product development. Chapter 1 gives an overview of projects, and discusses the difficulties in completing projects on time, within budget, and at designed functionality. While the successful completion of a project is a challenge, there are some things that can be done to improve the probability of a project’s success. The book reviews a number of project management concepts. These include developing organizational ability to work on projects, as discussed in Chapters 2 and 3. Sponsor expectations can be based on better information if a good job of project development, estimation and selection is conducted, as discussed in Chapters 4, 5 and 6. Project planning tools involving the critical path method are covered in Chapter 7. Tools to evaluate project risk are covered in Chapter 8. The critical chain method is covered in Chapter 9. Chapter 10 discusses means to rush projects when circumstances demand, to include project crashing as well as Agile and SCRUM approaches used in software engineering projects. Chapter 11 covers project implementation and control, including assessment of delay responsibility.

This book is devoted to presenting models that have been applied in project management. There are a variety of project domains. We discuss engineering/construction projects, software development projects, massive projects to include governmental undertakings, and pharmaceutical product development. Chapter 1 gives an overview of projects, and discusses the difficulties in completing projects on time, within budget, and at designed functionality. While the successful completion of a project is a challenge, there are some things that can be done to improve the probability of a project’s success. The book reviews a number of project management concepts. These include developing organizational ability to work on projects, as discussed in Chapters 2 and 3. Sponsor expectations can be based on better information if a good job of project development, estimation and selection is conducted, as discussed in Chapters 4, 5 and 6. Project planning tools involving the critical path method are covered in Chapter 7. Tools to evaluate project risk are covered in Chapter 8. The critical chain method is covered in Chapter 9. Chapter 10 discusses means to rush projects when circumstances demand, to include project crashing as well as Agile and SCRUM approaches used in software engineering projects. Chapter 11 covers project implementation and control, including assessment of delay responsibility.