Alternative Contracting Methods: Modeling and Assessing the Effects of Contract Type on Time-Cost-Change Performance

投标 激励 地铁列车时刻表 风险分析(工程) 运营管理 运筹学 不可预见费 计算机科学 精算学 环境经济学 业务 总成本 工程类 经济 相关成本 营销 会计 微观经济学 操作系统
作者
Kunhee Choi,Yangtian Yin,Darlene Goehl,H. David Jeong
出处
期刊:Journal of Management in Engineering [American Society of Civil Engineers]
卷期号:37 (1) 被引量:7
标识
DOI:10.1061/(asce)me.1943-5479.0000863
摘要

Although the use of alternative contracting methods (ACMs) has become increasingly common, little is known about their effects on a project’s time-cost-change performance. This study draws from 2,572 project datapoints, addressing this research gap by plotting, analyzing, and validating high confidence performance indicators. The effects of different ACMs on project time, cost, and change performance were all evaluated and time-cost performance prediction models developed and tested. The results reveal that the use of incentives/disincentives is preferable for reducing the duration of a project. Lump-sum contracting is an effective choice for onbudget project delivery, while cost-plus-time bidding is significantly less effective than incentives/disincentives and no-excuse bonus contracting. Notably, the results also convey that ACMs with large project sizes are more prone to schedule delays and cost overruns. The robustness of the predictive models was verified by a predicted error sum of squares validation. The findings of this study will help state transportation agencies make better-informed decisions by providing foresight regarding the pros and cons of ACMs for aspects of project time-cost-change performance. The use of the predictive models will also assist agencies in justifying the probable time-cost impact of project change orders, enabling them to conduct more reliable risk assessments and develop more realistic contingency plans in the project scoping phase.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
跳跃发布了新的文献求助10
2秒前
持卿应助宗磬采纳,获得20
2秒前
2秒前
花生油炒花生米完成签到 ,获得积分10
2秒前
Riki完成签到,获得积分10
4秒前
虚幻白玉发布了新的文献求助10
4秒前
德行天下完成签到,获得积分10
4秒前
Jenny应助lan采纳,获得10
5秒前
fztnh完成签到,获得积分10
5秒前
上官若男应助lyz666采纳,获得10
5秒前
顾念完成签到 ,获得积分10
5秒前
277发布了新的文献求助10
6秒前
小二郎应助GCD采纳,获得10
7秒前
hhhhhh完成签到 ,获得积分10
7秒前
甜味拾荒者完成签到,获得积分10
9秒前
小二郎应助BONBON采纳,获得10
9秒前
10秒前
charllie完成签到 ,获得积分10
10秒前
空禅yew完成签到,获得积分10
11秒前
坚强亦丝应助跳跃采纳,获得10
13秒前
英俊的铭应助cc采纳,获得10
13秒前
huangsan完成签到,获得积分10
13秒前
匹诺曹完成签到,获得积分10
13秒前
14秒前
华仔应助进取拼搏采纳,获得10
14秒前
15秒前
dingdong发布了新的文献求助10
15秒前
you完成签到 ,获得积分10
16秒前
qwf完成签到 ,获得积分10
16秒前
17秒前
万能图书馆应助一一采纳,获得10
17秒前
执着跳跳糖完成签到 ,获得积分10
18秒前
阳yang完成签到,获得积分10
18秒前
牛头人完成签到,获得积分10
18秒前
19秒前
Rrr发布了新的文献求助10
19秒前
20秒前
20秒前
serenity完成签到 ,获得积分10
20秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527961
求助须知:如何正确求助?哪些是违规求助? 3108159
关于积分的说明 9287825
捐赠科研通 2805882
什么是DOI,文献DOI怎么找? 1540070
邀请新用户注册赠送积分活动 716926
科研通“疑难数据库(出版商)”最低求助积分说明 709808