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Record Nr. |
UNINA9910821738803321 |
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Autore |
Allitt Malcolm |
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Titolo |
Creating financial value : a guide for senior executives with no finance background / / Malcolm Allitt |
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Pubbl/distr/stampa |
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London, England : , : Bloomsbury Information, , 2016 |
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©2016 |
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ISBN |
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Descrizione fisica |
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1 online resource (248 p.) |
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Disciplina |
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Soggetti |
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Executives - Finance, Personal |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Cover ; Contents; Acknowledgements; Preface; 1 Measures of success; 1.1 The business world from an investor's perspective; 1.2 Measuring value; 1.3 Where should business leaders focus their attention?; 1.4 Quiz; 1.5 Summary and implications for managers and leaders; 2 Using the financial statements to improve company performance; 2.1 Introduction to the financial statements; 2.2 Assessing historical performance; 2.3 Using accounting information to guide efficiency improvements; 2.4 Quiz; 2.5 Summary and implications for managers and leaders |
3 Customer markets: How value is created by specialization3.1 Normal profits and economic profits; 3.2 Why do transactions happen?; 3.3 The value to the buyer; 3.4 Competition and market development; 3.5 What is an industry?; 3.6 Industries - the attractive and the unattractive; 3.7 Quiz; 3.8 Summary and implications for managers and leaders; 4 Getting the most from your resources; 4.1 Pricing; 4.2 Cost structure, pricing decisions and profitability; 4.3 Full costing: the budgeting system used by many companies; 4.4 Quiz; 4.5 Summary and implications for managers and leaders |
5 The value of your assets and the value of your company5.1 What is the value of this machine?; 5.2 How the value of a company relates to its assets and capabilities; 5.3 How value is created through projects; 5.4 Net present value; 5.5 The total value of a company; 5.6 Quiz; 5.7 Summary and implications for managers and leaders; 6 Creating value |
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through projects; 6.1 Evaluating proposed projects - taking account of uncertainties; 6.2 How accurately does NPV reflect the true value of a proposed project?; 6.3 The 'make or buy' decision; 6.4 Can you create value through acquisitions? |
6.5 Other investment appraisal methods you might encounter6.6 Quiz; 6.7 Summary and implications for managers and leaders; 7 Financing decisions and other factors which have impact on the value of the firm; 7.1 Where does funding come from?; 7.2 Cash surpluses; 7.3 Doing business internationally; 7.4 Other ways of using financial management to reduce cost and risk; 7.5 Ethics; 7.6 Financial distress; 7.7 Quiz; 7.8 Summary - this book's implications for leaders of twenty-first-century businesses; Glossary of terms; Bibliography and references; Index |
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2. |
Record Nr. |
UNINA9911009174903321 |
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Autore |
Hinsen Konrad |
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Titolo |
Computation in science : from concepts to practice / / Konrad Hinsen |
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Pubbl/distr/stampa |
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Bristol [England] (Temple Circus, Temple Way, Bristol BS1 6HG, UK) : , : IOP Publishing, , [2020] |
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ISBN |
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9780750332866 |
0750332867 |
9780750332873 |
0750332875 |
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Edizione |
[Second edition.] |
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Descrizione fisica |
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1 online resource (various pagings) : illustrations (some color) |
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Collana |
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Disciplina |
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Soggetti |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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"Version: 20200901"--Title page verso. |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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1. What is computation? -- 1.1. Defining computation -- 1.2. The roles of computation in scientific research -- 1.3. Analog computing -- 1.4. Further reading |
2. Computation in science -- 2.1. Traditional science : celestial mechanics -- 2.2. Scientific models and computation -- 2.3. Computation at the interface between observations and models -- 2.4. Computation for developing insight -- 2.5. The impact of computing on science -- 2.6. Further reading |
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3. Formalizing computation -- 3.1. From manual computation to rewriting rules -- 3.2. From computing machines to automata theory -- 3.3. Computability -- 3.4. Restricted models of computation -- 3.5. Computational complexity -- 3.6. Computing with numbers -- 3.7. Further reading |
4. Automating computation -- 4.1. Computer architectures -- 4.2. Programming languages -- 4.3. Observing program execution -- 4.4. Software engineering -- 4.5. Further reading |
5. Taming complexity -- 5.1. Chaos and complexity in computation -- 5.2. Verification, validation, and testing -- 5.3. Abstraction -- 5.4. Managing state -- 5.5. Incidental complexity and technical debt -- 5.6. Further reading |
6. Computational reproducibility -- 6.1. Reproducibility : a core value of science -- 6.2. Repeating, reproducing, replicating -- 6.3. The role of computation in the reproducibility crisis -- 6.4. Non-reproducible determinism -- 6.5. Staged computation -- 6.6. Replicability, robustness, and reuse -- 6.7. Managing software evolution -- 6.8. Best practices for reproducible and replicable computational science -- 6.9. Further reading |
7. Outlook : scientific knowledge in the digital age -- 7.1. The scientific record goes digital -- 7.2. Procedural knowledge turns into software -- 7.3. Machine learning : the fusion of factual and procedural knowledge -- 7.4. The time scales of scientific progress and computing -- 7.5. The industrialization of science -- 7.6. Preparing the future -- 7.7. Further reading. |
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Sommario/riassunto |
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In the course of only a few decades computers have revolutionized scientific research and more and more scientists are writing computer programs for doing their work. In spite of the ubiquitous use of computers in science, few researchers in the natural sciences have any schooling in computer science, software engineering, or numerical analysis. They usually acquire their computing knowledge 'on the job' and often feel overwhelmed by the amount of computing knowledge they must absorb. Computation in Science provides a background in computation for scientists who use computational methods. The book explains how computing is used in the natural sciences and provides a high-level overview of relevant aspects of computer science and software engineering with a focus on concepts, results, and applications. The goal of this book is to explain these basic principles, and to show how they relate to the tasks of a scientist's daily work in a language familiar to them. Its unique feature is in connecting the dots between computational science, the theory of computation and information, and software engineering. It will compensate for the general lack of any formal training in computer science and information theory allowing readers to better understand how they use computers in their work, and how computers work. Readers will learn to use computers with more confidence, and to see computing technologies in a different light, evaluating them based on how they contribute to doing science. This new edition has been significantly updated and extended to reflect developments in scientific computing, including new examples and references. It also includes a new chapter on reproducibility which reflects the importance that computational reproducibility plays. Accompanied by a website maintained by the author which hosts companion code and supplementary material, it is intended for both graduate students and experienced scientists. Some hands-on experience with computing is highly desirable, but no competence in any specific computing technology is expected. |
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