دانلود مقاله ISI انگلیسی شماره 42329
ترجمه فارسی عنوان مقاله

ارزیابی روش های پیش بینی قطعی حالت هنر برای مدت زمان پروژه بر اساس مدیریت ارزش کسب شده

عنوان انگلیسی
Evaluation of deterministic state-of-the-art forecasting approaches for project duration based on earned value management
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
42329 2015 9 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : International Journal of Project Management, Volume 33, Issue 7, October 2015, Pages 1588–1596

ترجمه کلمات کلیدی
مدیریت پروژه - پیش بینی زمان - مدیریت ارزش کسب شده - به دست آورده مدیریت زمان - دوباره کاری - اقدامات حساسیت - پایگاه داده های تجربی - کنترل پروژه
کلمات کلیدی انگلیسی
Project management; Time forecasting; Earned value management; Earned duration management; Rework; Sensitivity measures; Empirical database; Project control
پیش نمایش مقاله
پیش نمایش مقاله  ارزیابی روش های پیش بینی قطعی حالت هنر برای مدت زمان پروژه بر اساس مدیریت ارزش کسب شده

چکیده انگلیسی

In recent years, a variety of novel approaches for fulfilling the important management task of accurately forecasting project duration have been proposed, with many of them based on the earned value management (EVM) methodology. However, these state-of-the-art approaches have often not been adequately tested on a large database, nor has their validity been empirically proven. Therefore, we evaluate the accuracy and timeliness of three promising deterministic techniques and their mutual combinations on a real-life project database. More specifically, two techniques respectively integrate rework and activity sensitivity in EVM time forecasting as extensions, while a third innovatively calculates schedule performance from time-based metrics and is appropriately called earned duration management or EDM(t). The results indicate that all three of the considered techniques are relevant. More concretely, the two EVM extensions exhibit accuracy-enhancing power for different applications, while EDM(t) performs very similar to the best EVM methods and shows potential to improve them.