Modeling, evaluating, and predicting IT human resources performance:
Numerous methods exist to model and analyze the different roles, responsibilities, and process levels of information technology (IT) personnel. However, most methods neglect to account for the rigorous application and evaluation of human errors and their associated risks. This book fills that need....
Gespeichert in:
| Beteiligte Personen: | , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Boca Raton
Auerbach
2015
|
| Ausgabe: | 1st. |
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781482299939/?ar |
| Zusammenfassung: | Numerous methods exist to model and analyze the different roles, responsibilities, and process levels of information technology (IT) personnel. However, most methods neglect to account for the rigorous application and evaluation of human errors and their associated risks. This book fills that need. Modeling, Evaluating, and Predicting IT Human Resources Performance explains why it is essential to account for the human factor when determining the various risks in the software engineering process. The book presents an IT human resources evaluation approach that is rooted in existing research and describes how to enhance existing approaches through strict use of software measurement and statistical principles and criteria. Discussing IT human factors from a risk assessment point of view, the book identifies, analyzes, and evaluates the basics of IT human performance. It details the IT human factors required to achieve desired levels of human performance prediction. It also provides a rigorous investigation of existing human factors evaluation methods, including IT expertise and Big Five, in combination with powerful statistical methods, such as failure mode and effect analysis (FMEA) and design of experiment (DoE). Supplies an overview of existing methods of human risk evaluation Provides a detailed analysis of IT role-based human factors using the well-known Big Five method for software engineering Models the human factor as a risk factor in the software engineering process Summarizes emerging trends and future directions In addition to applying well-known human factors methods to software engineering, the book presents three models for analyzing psychological characteristics. It supplies profound analysis of human resources within the various software processes, including development, maintenance, and application under consideration of the Capability Maturity Model Integration (CMMI) process level five. |
| Beschreibung: | CIP data; item not viewed |
| Umfang: | 1 Online-Ressource Illustrationen (black and white) |
| ISBN: | 9781482299939 1482299933 |
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| 520 | |a Numerous methods exist to model and analyze the different roles, responsibilities, and process levels of information technology (IT) personnel. However, most methods neglect to account for the rigorous application and evaluation of human errors and their associated risks. This book fills that need. Modeling, Evaluating, and Predicting IT Human Resources Performance explains why it is essential to account for the human factor when determining the various risks in the software engineering process. The book presents an IT human resources evaluation approach that is rooted in existing research and describes how to enhance existing approaches through strict use of software measurement and statistical principles and criteria. Discussing IT human factors from a risk assessment point of view, the book identifies, analyzes, and evaluates the basics of IT human performance. It details the IT human factors required to achieve desired levels of human performance prediction. It also provides a rigorous investigation of existing human factors evaluation methods, including IT expertise and Big Five, in combination with powerful statistical methods, such as failure mode and effect analysis (FMEA) and design of experiment (DoE). Supplies an overview of existing methods of human risk evaluation Provides a detailed analysis of IT role-based human factors using the well-known Big Five method for software engineering Models the human factor as a risk factor in the software engineering process Summarizes emerging trends and future directions In addition to applying well-known human factors methods to software engineering, the book presents three models for analyzing psychological characteristics. It supplies profound analysis of human resources within the various software processes, including development, maintenance, and application under consideration of the Capability Maturity Model Integration (CMMI) process level five. | ||
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| spelling | Richter, Konstantina VerfasserIn aut Modeling, evaluating, and predicting IT human resources performance Konstantina Richter, Reiner R. Dumke 1st. Boca Raton Auerbach 2015 1 Online-Ressource Illustrationen (black and white) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier CIP data; item not viewed Numerous methods exist to model and analyze the different roles, responsibilities, and process levels of information technology (IT) personnel. However, most methods neglect to account for the rigorous application and evaluation of human errors and their associated risks. This book fills that need. Modeling, Evaluating, and Predicting IT Human Resources Performance explains why it is essential to account for the human factor when determining the various risks in the software engineering process. The book presents an IT human resources evaluation approach that is rooted in existing research and describes how to enhance existing approaches through strict use of software measurement and statistical principles and criteria. Discussing IT human factors from a risk assessment point of view, the book identifies, analyzes, and evaluates the basics of IT human performance. It details the IT human factors required to achieve desired levels of human performance prediction. It also provides a rigorous investigation of existing human factors evaluation methods, including IT expertise and Big Five, in combination with powerful statistical methods, such as failure mode and effect analysis (FMEA) and design of experiment (DoE). Supplies an overview of existing methods of human risk evaluation Provides a detailed analysis of IT role-based human factors using the well-known Big Five method for software engineering Models the human factor as a risk factor in the software engineering process Summarizes emerging trends and future directions In addition to applying well-known human factors methods to software engineering, the book presents three models for analyzing psychological characteristics. It supplies profound analysis of human resources within the various software processes, including development, maintenance, and application under consideration of the Capability Maturity Model Integration (CMMI) process level five. Computer industry Personnel management Computer industry Personnel management Mathematical models Informatique ; Industrie ; Personnel ; Direction Informatique ; Industrie ; Personnel ; Direction ; Modèles mathématiques Computer industry ; Personnel management Dumke, Reiner VerfasserIn aut 9781482299922 Erscheint auch als Druck-Ausgabe 9781482299922 |
| spellingShingle | Richter, Konstantina Dumke, Reiner Modeling, evaluating, and predicting IT human resources performance Computer industry Personnel management Computer industry Personnel management Mathematical models Informatique ; Industrie ; Personnel ; Direction Informatique ; Industrie ; Personnel ; Direction ; Modèles mathématiques Computer industry ; Personnel management |
| title | Modeling, evaluating, and predicting IT human resources performance |
| title_auth | Modeling, evaluating, and predicting IT human resources performance |
| title_exact_search | Modeling, evaluating, and predicting IT human resources performance |
| title_full | Modeling, evaluating, and predicting IT human resources performance Konstantina Richter, Reiner R. Dumke |
| title_fullStr | Modeling, evaluating, and predicting IT human resources performance Konstantina Richter, Reiner R. Dumke |
| title_full_unstemmed | Modeling, evaluating, and predicting IT human resources performance Konstantina Richter, Reiner R. Dumke |
| title_short | Modeling, evaluating, and predicting IT human resources performance |
| title_sort | modeling evaluating and predicting it human resources performance |
| topic | Computer industry Personnel management Computer industry Personnel management Mathematical models Informatique ; Industrie ; Personnel ; Direction Informatique ; Industrie ; Personnel ; Direction ; Modèles mathématiques Computer industry ; Personnel management |
| topic_facet | Computer industry Personnel management Computer industry Personnel management Mathematical models Informatique ; Industrie ; Personnel ; Direction Informatique ; Industrie ; Personnel ; Direction ; Modèles mathématiques Computer industry ; Personnel management |
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