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1. |
Record Nr. |
UNINA9910962930103321 |
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Autore |
Haselkorn Mark P |
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Titolo |
Strategic management of information and communication technology : the United States Air Force experience with Y2K / / Mark Haselkorn, principal investigator ; Policy and Global Affairs, Computer Science and Telecommunications Board Division on Engineering and Physical Sciences, National Research Council of the National Academies |
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Pubbl/distr/stampa |
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Washington, D.C., : National Academies Press, c2007 |
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ISBN |
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9786610969128 |
9780309179324 |
0309179327 |
9781280969126 |
1280969121 |
9780309111294 |
0309111293 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (xiii, 128 pages) |
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Disciplina |
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Soggetti |
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Year 2000 date conversion (Computer systems) - United States |
Software maintenance - United States |
Strategic planning - United States |
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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 (p. 117-121). |
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Nota di contenuto |
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""Front Matter""; ""PREFACE""; ""CONTENTS""; ""SUMMARY""; ""Chapter 1 Background""; ""Chapter 2 Managing ICT Complexity""; ""Chapter 3 Aligning Organizational and ICT Strategies""; ""Chapter 4 Managing ICT Risk""; ""Chapter 5 Technology Risk as a Socially Embedded Issue""; ""REFERENCES""; ""APPENDIX A: REFERENCES TO WORKSHOP DISCUSSIONS ANDINTERVIEWS""; ""APPENDIX B: ABBREVIATIONS AND ACRONYMS""; ""APPENDIX C: BIOGRAPHICAL INFORMATION ON THE PRINCIPAL INVESTIGATOR"" |
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Sommario/riassunto |
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Although Y2K did not result in major disruptions, the event is a rich source of critical lessons for strategic management of information and communication technology (ICT), many of which apply to large |
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organizations today. Using a case study approach, this report describes lessons learned from the response of the Air Force to Y2K and makes recommendations for managing ICT complexity, aligning organizational and ICT strategies, and minimizing risk. |
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2. |
Record Nr. |
UNINA9910969848103321 |
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Autore |
Moriyama Kenji |
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Titolo |
Forecasting Inflation in Sudan / / Kenji Moriyama, Abdul Naseer |
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Pubbl/distr/stampa |
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Washington, D.C. : , : International Monetary Fund, , 2009 |
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ISBN |
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9786612843464 |
9781462340637 |
1462340636 |
9781452738970 |
1452738971 |
9781451872798 |
1451872798 |
9781282843462 |
128284346X |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (27 p.) |
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Collana |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Inflation (Finance) - Sudan |
Economic forecasting - Sudan |
Agricultural prices |
Agriculture: Aggregate Supply and Demand Analysis |
Business cycles |
Cyclical indicators |
Deflation |
Economic Forecasting |
Economic forecasting |
Economic growth |
Forecasting and Other Model Applications |
Forecasting |
Inflation |
Macroeconomics |
Monetary base |
Monetary economics |
Monetary Policy, Central Banking, and the Supply of Money and Credit: General |
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Money and Monetary Policy |
Money supply |
Price Level |
Prices |
Prices, Business Fluctuations, and Cycles: General (includes Measurement and Data) |
Sudan |
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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. |
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Nota di contenuto |
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Contents; I. Introduction; II. Recent Developments; Figures; 1. Average and Standard Deviation of Inflation, 2000-08; 2. Monthly Inflation (12-Month) in Sudan, January 2000-October 2008; III. Methodology; A. Which Inflation Should Be Forecasted?; 3. Overall Inflation, 2000-08; B. Autoregressive Moving Average (ARMA) Model; 4. Cumulative Spectral Distribution of Inflation, 2000-08; C. Leading Indicators; 5. Currency Holding and Islamic Dummies, 2005-08; 6. Candidates of Leading Indicators; IV. Results; A. ARMA Model; 7. Actual and Projected Inflation Based on the Estimated ARMA Models |
B. Granger Causality Tests for Leading IndicatorsV. Implications-What Can be said from the Estimated Model and the Tests?; A. Can the Estimated Model Explain the Surge of Inflation in 2007 and 2008?; 8. Forecasted Inflation, July 2007-December 2008; 9. Forecast Errors of the Model and Bread Contribution to Inflation, July 2007-October 2008; B. Forecasting Inflation for 2009 and 2010; 10. Forecasted Inflation; 11. Inflation Forecast Based on ARMA (4,5), July 2008-December 2010; C. Leading Indicators (Private Sector Credit Growth and Wheat Price Inflation) |
12. Oil Price Projections, World Economic Outlook, 2000-1013. Wheat Price Projections, World Economic Outlook, 2000-10; VI. Conclusions; Tables; 1. Estimated ARMA Model of Inflation; 2. Main Statistics of Various ARMA Models, 2000-08; 3. Granger Causality Tests Between Inflation and Leading Indicators, 2000-08; Appendices; I. The Schwartz Information Criterion; II. Estimated ARMA Model for main Monetary Aggregates; Appendix Tables; A1. Estimated ARMA Model of Broad money, 2000-08; References |
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Sommario/riassunto |
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This paper forecasts inflation in Sudan following two methodologies: the Autoregressive Moving Average (ARMA) model and by looking at the leading indicators of inflation. The estimated ARMA model remarkably tracks the actual inflation during the sample period. The Granger causality test suggests that private sector credit and world wheat prices are the leading indicators explaining inflation in Sudan. Inflation forecasts based on both approaches suggest that inflationary pressures for 2009 and 2010 will be modest and that inflation will remain in single-digits, assuming that prudent macroeconomic policies are maintained. |
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