實驗相關文獻 in 管理科學 Management Science

http://maaw.info/ManagementJournals/ManagementScience.htm
有人整理了專門發表在 Management Science 的文章,哇,沒想到有這麼多…, 以下列出一些我較有興趣、近期的實驗相關文獻

Abdellaoui, M., E. Diecidue and A. Öncüler. 2011. Risk preferences at different time periods: An experimental investigation. Management Science (May): 975-987.

Abdellaoui, M., F. Vossmann and M. Weber. 2005. Choice-based elicitation and decomposition of decision weights for gains and losses under uncertainty. Management Science (September): 1384-1399. (JSTOR link).

Abedellaoui, M., O. L’Haridon and C. Paraschiv. 2011. Experience vs. described uncertainty: Do we need two prospect theory specifications? Management Science (October): 1879-1895.

Allon, G. and A. Bassamboo. 2011. Buying from the babbling retailer? The impact of availability information on customer behavior. Management Science (April): 713-726.

Amaldoss, W. and S. Jain. 2005. Conspicuous consumption and sophisticated thinking. Management Science (October): 1449-1466. (JSTOR link).

這篇是理論, 但也有 Laboratory test

Aral, S. and D. Walker. 2011. Creating social contagion through viral product design: A randomized trial of peer influence in networks. Management Science (September): 1623-1639.

Budescu, D. V. and B. Maciejovsky. 2005. The effect of payoff feedback and information pooling on reasoning errors: Evidence from experimental markets. Management Science (December): 1829-1843. (JSTOR link).

Cason, T. N., K. N. Kannan and R. Siebert. 2011. An experimental study of information revelation policies in sequential auctions. Management Science (April): 667-688.

Chen, H., S. H. Ham and N. Lim. 2011. Designing multiperson tournaments with asymmetric contestants: An experimental study. Management Science (May): 864-883.

Chen-Ritzo, C., T. P. Harrison, A. M. Kwasnica and D. J. Thomas. 2005. Better, faster, cheaper: An experimental analysis of a multiattribute reverse auction mechanism with restricted information feedback. Management Science (December): 1753-1762. (JSTOR link).

Ding, M., J. Eliashberg, J. Huber and R. Saini. 2005. Emotional bidders: An analytical and experimental examination of consumers’ behavior in a priceline-like reverse auction. Management Science (March): 352-364. (JSTOR link).

Harbaugh, R., J. W. Maxwell and B. Roussillon. 2011. Label confusion: The Groucho effect of uncertain standards. Management Science (September): 1512-1527.

Harbring, C. and B. Irlenbusch. 2011. Sabotage in tournaments: Evidence from a laboratory experiment. Management Science (April): 611-627.

Kalkanci, B., Y. Chen and F. Erhun. 2011. Contract complexity and performance under asymmetric demand information: An experimental evaluation. Management Science (April): 689-704.

Katok, E. and E. Siemsen. 2011. Why genius leads to adversity: Experimental evidence on the reputational effects of task difficulty choices. Management Science (June): 1042-1054.

Oiu, J. and E. Steiger. 2011. Understanding the tow components of risk attitudes: An experimental analysis. Management Science (January): 193-199.

Stecher, J., T. Shields and J. Dickhaut. 2011. Generating ambiguity in the laboratory. Management Science (April): 705-712.

廣告

Behavioral Causes of the Bullwhip Effect and the Observed Value of Inventory Information

Rachel Croson, Karen Donohue (2006) “Behavioral Causes of the Bullwhip Effect and the Observed Value of Inventory Information." MANAGEMENT SCIENCE, Vol. 52, No. 3, March 2006, pp. 323-336. DOI: 10.1287/mnsc.1050.0436. [linked PDF]

Keys related to Bullwhip Effects

低估 supply line 中 (即已訂, 但未收到) 的存貨
Sterman (1989a) provides evidence that the bullwhip effect exists and may be caused by participants’ tendency to underweight inventory in the supply line.
*統計上的衡量方式, 見以下的 Hypothesis 1

過去文獻已提出之解決方法:Common strategies include

  1. reducing order lead times,
  2. sharing consumer demand (e.g., POS data),and
  3. centralizing ordering decisions.

模型

image

I: 存貨
O: 訂貨
S: 出貨

Chain 成本:

image
image

Incentuve scheme:
每人 $5 + 有團隊獎金 (依下列公式) 每人得

image

Cg 是第 g 組的 Chain 成本 (成本愈低, bonus 獎金愈高)

實驗 & 主要結果

主要控制之實驗環境 Controlled variables:

  1. sharing knowledge of the retail demand distribution with all participants
  2. utilize an incentive scheme that avoids problems of collusion and reduced effort over time

有關 shipment delay 的設定:
the traditional beer distribution game setup 2期 between retailer, distributor, and wholesaler and 3 期 for producer.

…controls for three of the four operational causes of the bullwhip effect (p.4):

  1. inventory allocation (since there are no competing customers and manufacturing capacity is infinite),
  2. order batching (since setup times are zero), and
  3. price
    fluctuations (since prices are constant over time).

統計方法:
1. sign test
2. Mann-Whitney University test (Wilcoxon test)

第1個實驗:

受試者人數 = 4 roles x 11 group
Results from our first study confirm that decision makers still exhibit this bias (按: 係指underweighting the supply line) in a controlled setting where demand information is known and stationary (特別是 when traditional operational causes are removed and the demand distribution is known by all parties.)

image image

image

(以上每一個不同顏色為 1 組, 共11組)

Evidence of Underweighting the Supply Line

image
image

Hypothesis 1. The bullwhip effect will not occur when the demand distribution is known and stationary.
H01: a_
R = 1

Hypothesis 2. Participants will not underweight the supply line when demand is known and stationary.
H02: a_I =a_N =a_S = –1

underweighting behavior

If Sterman’s conjecture holds (i.e., participants are underweighting the supply line), then we should find:
a_N > a_I .
We found that the average value for a_N was −0.0302 compared to −0.2368 for a_I . …using a sign test (N = 44, x =0, p < 0.0001)

利用專業人員進行實驗驗證結果:
This result also holds for the professionals from CLM (see Appendix 2, 或以下的 Figure 5), implying that underweighting behavior is robust to professional experience.

image

第2個實驗 (information sharing):

…exposure to real time inventory information (inventory tracking systems) helps reduce the bullwhip effect but not in the manner expected.
(整體) 存貨資訊對下游訂貨變異影響很小, 但可減少上游訂貨變異

image

Hypothesis 3. Sharing dynamic inventory information across the supply chain will decrease the level of order oscillation.

… use a nonparametric twotailed Mann-Whitney University test (also called the Wilcoxon test)  to compare how the oscillation component of the bullwhip effect compares across the two treatments.
… known, compared with the control treatment (n = 44, m = 44, z = 1.92, p =0.028), providing support for the hypothesis.

Hypothesis 4. Sharing dynamic inventory information across the supply chain will decrease the amplification of order oscillation between each supply chain level.

結果是:  bullwhip effect 放大的成份有減少, 但是仍然存在
… the bullwhip effect still persists when inventory information is shown. Using the same sign test discussed in §3.2.1, we find that the variability of orders placed between each role increased 69% of the time (i.e., exhibited a 69% success rate) …. This is significantly different than the 50% success rate of the null hypothesis if no amplification existed (N =33, x = 10, p = 0.0107), but is significantly lower than the 82% rate of increase observed previously (p =0.0344).
This suggests that the amplification component of the bullwhip effect is reduced, but still present, …

Hypothesis 5. Sharing dynamic inventory information will cause participants to no longer underweight the supply line.

結果拒絶 Hypothesis 5。
The average inventory weight was −0.1939, while the average weight placed on the supply line was −0.0288. Forty-two out of 44 participants underweighted the supply line. … this pattern of results is significantly different than would be expected if the supply line were being weighted equally as inventory using a sign test (N = 44, x = 2, p < 0.0001).

Hypothesis 6a. Sharing dynamic inventory information across the supply chain will lead to a greater reduction in order oscillations for manufacturers and distributors than for retailers and wholesalers.

Hypothesis 6b. Sharing dynamic inventory information across the supply chain will lead to a lower reduction in order oscillations for manufacturers and distributors than for retailers and wholesalers.

… use a set of Mann-Whitney University tests. Grouping distributors and manufacturers together reveals that sharing inventory information leads to a significant reduction in the variance of orders at upstream sites (n = 22, m = 22, z = 1.82, p = 0.043). Grouping retailers and wholesalers together reveals an insignificant difference between the treatments (n=22, m=22, z=1.24,
p =0.110).

… these results suggest that members near the beginning of the chain exhibit a different impact from inventory information than those near the end. … Upstream members exhibit a significant reduction in order oscillations, while downstream members show
relatively little improvement.

image

==original Abstract==

The tendency of orders to increase in variability as one moves up a supply chain is commonly known as the bullwhip effect. We study this phenomenon from a behavioral perspective in the context of a simple, serial, supply chain subject to information lags and stochastic demand. We conduct two experiments on two different sets of participants. In the first, we find the bullwhip effect still exists when normal operational causes (e.g., batching, price fluctuations, demand estimation, etc.) are removed. The persistence of the bullwhip effect is explained to some extent by evidence that decision makers consistently underweight the supply line when making order decisions. In the second experiment, we find that the bullwhip, and the underlying tendency of underweighting, remains when information on inventory levels is shared. However, we observe that inventory information helps somewhat to alleviate the bullwhip effect by helping upstream chain members better anticipate and prepare for fluctuations in inventory needs downstream. These experimental results support the theoretically suggested notion that upstream chain members stand to gain the most from information-sharing initiatives.

Key Words: supply chain management; bullwhip effect; behavioral experiments; information sharing; dynamic decision making
History: Received: June 24, 1999;

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