Quantifying Success Factors for IT Projects-An Expert-Based Bayesian Model

Liv Gingnell; Ulrik Franke; Robert Lagerstroem; Evelina Ericsson; Joakim Lillieskoeld

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Quantifying Success Factors for IT Projects-An Expert-Based Bayesian Model

机译：量化IT项目的成功因素-基于专家的贝叶斯模型

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Large investments are made annually to develop and maintain IT systems. Successful outcome of IT projects is therefore crucial for the economy. Yet, many IT projects fail completely or are delayed or over budget, or they end up with less functionality than planned. This article describes a Bayesian decision-support model. The model is based on expert elicited data from 51 experts. Using this model, the effect management decisions have upon projects can be estimated beforehand, thus providing decision support for the improvement of IT project performance.

机译：每年都会投入大量资金来开发和维护IT系统。因此，IT项目的成功成果对经济至关重要。但是，许多IT项目完全失败，被延迟或超出预算，或者最终导致功能少于计划。本文介绍了贝叶斯决策支持模型。该模型基于来自51位专家的专家得出的数据。使用此模型，可以预先估计管理决策对项目的影响，从而为提高IT项目绩效提供决策支持。

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来源
《Information Systems Management》 |2014年第2期|21-36|共16页
作者
Liv Gingnell; Ulrik Franke; Robert Lagerstroem; Evelina Ericsson; Joakim Lillieskoeld;
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作者单位

Industrial Information and Control Systems, KTH Royal Institute of Technology, Stockholm, Sweden;

Swedish Defence Research Agency (FOI), Stockholm, Sweden;

Industrial Information and Control Systems, KTH Royal Institute of Technology, Stockholm, Sweden;

Industrial Information and Control Systems, KTH Royal Institute of Technology, Stockholm, Sweden;

Industrial Information and Control Systems, KTH Royal Institute of Technology, Stockholm, Sweden;

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原文格式 PDF
正文语种 eng
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关键词
IT project success factors; decision support; Bayesian networks; Noisy-OR; expert elicitation;

机译：IT项目成功的因素;决策支持;贝叶斯网络;噪声或专家启发;

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机译：量化IT项目的成功因素-基于专家的贝叶斯模型

Quantifying Success Factors for IT Projects-An Expert-Based Bayesian Model

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