Decision Bias and Bullwhip Effect in Multiechelon Supply Chains: Risk Preference Models

损失厌恶 供应链 利润最大化 经济 微观经济学 前景理论 风险厌恶(心理学) 利润(经济学) 最大化 偏爱 牛鞭效应 期望效用假设 计量经济学 供应链管理 营销 业务 数理经济学
作者
Mehrdokht Pournader,Arunachalam Narayanan,Matthew F. Keblis,Dmitry Ivanov
出处
期刊:IEEE Transactions on Engineering Management [Institute of Electrical and Electronics Engineers]
卷期号:71: 9229-9243 被引量:2
标识
DOI:10.1109/tem.2023.3292348
摘要

In this article, we investigate whether risk aversion, risk seeking, loss aversion, or prospect theory could explain the ordering decisions in multiechelon supply chains. First, we develop analytical models based on various theories of risk preference to predict order quantities of decision-makers. Then, using controlled laboratory experiments with participants from universities in the U.S. and Australia, we assess if the models predict the ordering behavior of decision-makers in profit-maximization and loss-minimization settings. For the profit-maximization setting, two variations of the beer game are tested, namely, games with purchase cost and games without purchase cost. The results for games with no purchase cost are consistent with loss-averse and risk-averse preferences, while the results for games with purchase cost are partially consistent with risk-seeking preferences. For loss-minimization games, the results are consistent with loss-averse preferences. We examined our results using two different reference points, namely, wealth at the beginning of each period of the game and changes in payoffs between two consecutive periods. Furthermore, we find that, based on the Berlin numeracy test, decision-makers with greater comprehension of risk usually order with lower variation. Finally, we find that decision-makers in a supply chain increase their order quantities when the objective is to maximize profit and reduce their order quantities when the objective is to minimize loss. Therefore, if the profit margins are higher in the supply chain, then the likelihood of a bullwhip effect increases.
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
睡不醒的xx完成签到 ,获得积分10
1秒前
cc发布了新的文献求助10
1秒前
北走发布了新的文献求助30
2秒前
2秒前
余书文发布了新的文献求助10
3秒前
llll发布了新的文献求助10
3秒前
3秒前
人小鸭儿大完成签到 ,获得积分10
3秒前
4秒前
咕咕发布了新的文献求助10
4秒前
兔农糖发布了新的文献求助10
4秒前
buran完成签到,获得积分10
4秒前
顺利的富发布了新的文献求助10
4秒前
优雅的WAN完成签到,获得积分10
5秒前
5秒前
白开水完成签到,获得积分10
6秒前
6秒前
怕黑荠应助surain采纳,获得10
6秒前
yusheng发布了新的文献求助10
7秒前
麻麻薯完成签到 ,获得积分10
7秒前
爱笑秀发发布了新的文献求助10
7秒前
7秒前
LYM发布了新的文献求助10
8秒前
9秒前
HeyJocelyn发布了新的文献求助30
9秒前
XXF完成签到,获得积分10
9秒前
10秒前
自然盼柳完成签到,获得积分10
11秒前
容若完成签到,获得积分10
11秒前
圈圈圈关注了科研通微信公众号
12秒前
jinshijie完成签到 ,获得积分10
12秒前
drsxtang完成签到,获得积分10
12秒前
香蕉觅云应助123456采纳,获得10
13秒前
算命的完成签到,获得积分10
13秒前
天天快乐应助哈哈哈采纳,获得10
13秒前
山山而川发布了新的文献求助10
13秒前
13秒前
小二郎应助咕咕采纳,获得10
14秒前
psycan发布了新的文献求助10
14秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Mechanistic Modeling of Gas-Liquid Two-Phase Flow in Pipes 2500
Structural Load Modelling and Combination for Performance and Safety Evaluation 1000
Conference Record, IAS Annual Meeting 1977 710
電気学会論文誌D(産業応用部門誌), 141 巻, 11 号 510
Virulence Mechanisms of Plant-Pathogenic Bacteria 500
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 3563859
求助须知:如何正确求助?哪些是违规求助? 3137060
关于积分的说明 9420785
捐赠科研通 2837499
什么是DOI,文献DOI怎么找? 1559874
邀请新用户注册赠送积分活动 729212
科研通“疑难数据库(出版商)”最低求助积分说明 717187