000 | 03189nam a22004695i 4500 | ||
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001 | 978-1-4614-3043-8 | ||
003 | DE-He213 | ||
005 | 20140220083246.0 | ||
007 | cr nn 008mamaa | ||
008 | 120217s2012 xxu| s |||| 0|eng d | ||
020 |
_a9781461430438 _9978-1-4614-3043-8 |
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024 | 7 |
_a10.1007/978-1-4614-3043-8 _2doi |
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_aKJQ _2bicssc |
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_aBUS083000 _2bisacsh |
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_aCOM039000 _2bisacsh |
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082 | 0 | 4 |
_a650 _223 |
100 | 1 |
_aMohapatra, Sanjay. _eauthor. |
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245 | 1 | 0 |
_aInformation Theory and Best Practices in the IT Industry _h[electronic resource] / _cby Sanjay Mohapatra. |
264 | 1 |
_aBoston, MA : _bSpringer US, _c2012. |
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300 |
_aXV, 216p. 34 illus., 17 illus. in color. _bonline resource. |
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_atext _btxt _2rdacontent |
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_acomputer _bc _2rdamedia |
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_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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505 | 0 | _aIntroduction -- Literature Review -- Researchable Objectives, Hypotheses and Methodology -- Benchmarking Practices - Analysis and Assessment -- Testing of Hypotheses Validations Through Cases -- Case Studies -- Conclusions. Appendix I - Questionnaire -- Appendix II - Data Collected from Internal Benchmarking. | |
520 | _aThe importance of benchmarking in the service sector is well recognized as it helps in continuous improvement in products and work processes. Through benchmarking, companies have strived to implement best practices in order to remain competitive in the product- market in which they operate. However studies on benchmarking, particularly in the software development sector, have neglected using multiple variables and therefore have not been as comprehensive. Information Theory and Best Practices in the IT Industry fills this void by examining benchmarking in the business of software development and studying how it is affected by development process, application type, hardware platforms used, and many other variables. Information Theory and Best Practices in the IT Industry begins by examining practices of benchmarking productivity and critically appraises them. Next the book identifies different variables which affect productivity and variables that affect quality, developing useful equations that explaining their relationships. Finally these equations and findings are applied to case studies. Utilizing this book, practitioners can decide about what emphasis they should attach to different variables in their own companies, while seeking to optimize productivity and defect density. | ||
650 | 0 | _aEconomics. | |
650 | 0 | _aData structures (Computer science). | |
650 | 0 | _aManagement information systems. | |
650 | 1 | 4 | _aEconomics/Management Science. |
650 | 2 | 4 | _aBusiness Information Systems. |
650 | 2 | 4 | _aData Structures, Cryptology and Information Theory. |
650 | 2 | 4 | _aInnovation/Technology Management. |
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9781461430421 |
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-1-4614-3043-8 |
912 | _aZDB-2-SBE | ||
999 |
_c101291 _d101291 |