Supply chain coordination with revenue-sharing contracts: strengths and limitations

Cachon, Gérard P., and Martin A. Lariviere. “Supply chain coordination with revenue-sharing contracts: strengths and limitations." Management science 51.1 (2005): 30-44. [[PDF] northwestern.edu] [[PDF] psu.edu];***

==abstract==

Under a revenue-sharing contract, a retailer pays a supplier a wholesale price for each unit purchased, plus a percentage of the revenue the retailer generates… We demonstrate that revenue sharing coordinates a supply chain with a single retailer (i.e., the retailer chooses optimal price and quantity) and arbitrarily allocates the supply chain’s profit….We find that revenue sharing is equivalent to buybacks in the newsvendor case and equivalent to price discounts in the price-setting newsvendor case. Revenue sharing also coordinates a supply chain with retailers competing in quantities, e.g., Cournot competitors or competing newsvendors with fixed prices. Additionally, revenue sharing does not coordinate a supply chain with demand that depends on costly retail effort.

Selling to the Newsvendor: An Analysis of Price-Only Contracts

Lariviere, Martin A., and Evan L. Porteus. “Selling to the newsvendor: An analysis of price-only contracts." Manufacturing & service operations management 3.4 (2001): 293-305.

http://pubsonline.informs.org/doi/abs/10.1287/msom.3.4.293.9971

*for 校內網路 PDF

==original Abstract==

We consider a simple supply-chain contract in which a manufacturer sells to a retailer facing a newsvendor problem and the lone contract parameter is a wholesale price. We develop a mild restriction satisfied by many common distributions that assures that the manufacturer’s problem is readily amenable to analysis. The manufacturer’s profit and sales quantity increase with market size, but the resulting wholesale price depends on how the market grows. For the cases we consider, we identify relative variability (i.e., the coefficient of variation) as key: As relative variability decreases, the retailer’s price sensitivity decreases, the wholesale price increases, the decentralized system becomes more efficient (i.e., captures a greater share of potential profit), and the manufacturer’s share of realized profit increases. Decreasing relative variability, however, may leave the retailer severely disadvantaged as the higher wholesale price reduces his profitability. We explore factors that may lead the manufacturer to set a wholesale price below that which would maximize her profit, concentrating on retailer participation in forecasting and retailer power. As these and other considerations can result in a wholesale price below what we initially suggest, our base model represents a worst-case analysis of supply-chain performance.

Licensing Strategies in the Presence of Patent Thickets

Lihui Lin (2011) “Licensing Strategies in the Presence of Patent Thickets."Journal of Product Innovation Management, Volume 28, Issue 5, pages 698–725, September 2011. DOI: 10.1111/j.1540-5885.2011.00835.x. link to Wiley;;;

Notes by yinung

本文之理論模型是以 2-stage, backward-induction 的方式來推理,其模型之數學形式,可供參考。

文獻上未討論不同 licensing contracts 對 patent thickets, royalty stacking, double marginalization 之影響。

賽局理論模型; 研究下游廠商向上游尋求 N 個 licenses 授權, 其討論 5 種 licensing contract 如下:

  • Quantity-Based Royalty Licenses

下游每單位 output 授權費 u

  • Downstream firm with no bargaining power
    上游完全決定 u (given 下游只能全盤接受, 在本文中稱之 researvation payoff = 0)
  • Downstream firm with any reservation payoff
    上游只要選一個 u 使下游的 payoffs >= reservation payoffs 即可;故下游 bargaining power 會大,則 u 會愈小
  • Revenue-Based Royalty Licenses (by Goldscheider, 1995)
上游向下游收取 r 比例之收入為授權費
  • Profit-Based Royalty Licenses

the price of the final product is independent of the royalty rate and the distribution of bargaining power.

  • Fixed-Fee Licenses

just like a profit-based royalty license, the price of the downstream product is not distorted by upstream costs.

  • Hybrid Licenses: Royalty plus Fixed Fee

some keywords:

patent thickets

royalty stacking

double marginalization

引文

the introduction of a new product or service often requires many complementary technologies

Abstract

Many key industries (e.g., biomedical, pharmaceuticals, telecommunications, and information technologies) are characterized by cumulative innovations, where the introduction of a new product or service often requires many complementary technologies. When these technologies are protected by intellectual property rights owned by many firms, patent thickets exist, which researchers have argued may hinder the development of cumulative innovations. Specifically, patent thickets may lead to excessive royalty burdens for potential licensees, which is called “royalty stacking,” and if such costs are passed on to consumers, prices of products based on cumulative technologies will be driven up, dubbed as “double marginalization.” The literature, however, does not address these issues under different forms of licensing contracts.

This article develops a game-theoretic model where a downstream firm seeks to license N patents that read on its product from upstream firms. It discusses a variety of licensing forms widely used in practice and attempts to discover whether royalty stacking and double marginalization occur under these forms of licenses. It also studies the impact of bargaining power between parties. It is found that when patent ownership becomes more fragmented, neither royalty stacking nor double marginalization occurs under profit-based royalty, fixed fee, and hybrid licenses. Such problems occur only under pure quantity-based or pure revenue-based royalty licenses when the downstream firm’s bargaining power is low. It is also shown that no matter how fragmented the ownership structure of patent is, hybrid licenses consisting of a fixed fee and a quantity- or revenue-based royalty rate lead to the same market outcomes as a fully integrated firm that owns all the patents and the downstream market.

This article has interesting implications for both research and practice. First, the results show that even under the same patent ownership structure, different forms of licenses lead to quite different market outcomes. Therefore, it is suggested that firms and policy makers pay more attention to contractual forms of licenses when trying to minimize the negative impact of patent thickets. Second, the extant literature has largely assumed that quantity-based royalties are used, where double marginalization is the most severe. In practice, revenue-based royalties are most common, under which double marginalization is much milder. Third, the results show that patent pools can be most effective in mitigating royalty stacking and double marginalization when quantity-based or revenue-based royalties are the sole or primary payment form, especially when downstream firms have low bargaining power.

References

  • Associated Press Financial Wire. 2007. Qualcomm announces record third quarter fiscal 2007 results. July 25.
  • Battersby, G. J., and C. W. Grimes. 2005. Licensing royalty rates. New York: Aspen Publishers.
  • Bessen, J., and R. Hunt. 2003. An empirical look at software patents. Working paper. Available at: http://www.researchoninnovation.org/swpat.pdf.
  • Bessen, J., and E. Maskin. 2009. Sequential innovation, patents, and imitation. Rand Journal of Economics 40 (4): 611–35.
  • Brunsvold, B. G., and D. P. O’Reilley. 2004. Drafting patent license agreements. Washington, DC: The Bureau of National Affairs.
  • Burns, S. 2007. Apple payment makes up 90 per cent of creative profit. ITnews, February 1. Available at: http://www.itnews.com.au/News/45179,apple-payment-makes-up-90-percent-of-creative-profit.aspx.
  • Cournot, A. 1838. Researches into the mathematical principles of the theory of wealth. Trans. N. Bacon. London: Macmillan.
  • Economides, N. 1996. The economics of networks. International Journal of Industrial Organization 16 (4): 673–99.
  • Foley Hoag LLP. 2007. Terms and trends in patent license agreements with universities and other research institutions. Available at: http://www.foleyhoag.com/NewsCenter/PressCenter/2007/05/Terms-and-Trends-050807.aspx.
  • Gans, J. S., D. H. Hsu, and S. Stern. 2002. When does start-up innovation spur the gale of creative destruction? Rand Journal of Economics 33 (4): 571–86.
  • Goldscheider, R. 1995. The negotiation of royalties and other sources of income from licensing. IDEA: The Journal of Law and Technology 36: 1–17.
  • Goldscheider, R., J. Jarosz, and C. Mulhem. 2005. Use of the 25% rule in valuing intellectual property. In Intellectual property: Valuation, exploitation, and infringement damages, ed. R. L.Parr, and G. V.Smith, 410–26. Hoboken, NJ: Wiley.
  • Goodman, D. J., and R. A. Myers. 2005. 3G cellular standards and patents. Proceedings of IEEE International Conference on Wireless Networks, Communications, and Mobile Computing. June 13.
  • Grindley, P. C., and D. J. Teece. 1997. Managing intellectual capital: Licensing and cross-licensing in semiconductors and electronics. California Management Review 39: 8–41.
  • Hall, B., and M. MacGarvie. 2006. The private value of software patents. NBER Working Paper No. 12195.
  • Heller, M. A., and R. S. Eisenberg. 1998. Can patents deter innovation? The anticommons in biomedical research. Science 280: 698–701.
  • Kamien, M. I. 1992. Patent licensing. In Handbook of game theory, vol. 1, ed. R. J.Aumann, and S.Hart, 332–54. Amsterdam: North-Holland.
  • Kamien, M. I., and Y. Tauman. 2002. Patent licensing: The inside story. Manchester School 70 (1): 7–15.
  • Kulatilaka, N., and L. Lin. 2006. Impact of licensing on investment and financing of technology development. Management Science 52 (12): 1824–37.
  • Lemley, M. A., and C. Shapiro. 2007. Patent holdup and royalty stacking. Texas Law Review 85: 1991–2049.
  • Lessig, L. 2001. The future of ideas: The fate of the commons in a connected world. New York: Random House.
  • Levine, A. 2009. Licensing and scale economies in the biotechnology pharmaceutical industry. Working paper, Stanford University.
  • Noguchi, Y. 2006. IPod patent dispute settled. Washington Post, August 24, p. D01. Available at: http://www.washingtonpost.com/wp-dyn/content/article/2006/08/23/AR2006082301702.html.
  • Port, K. L., J. Dratler, F. M. Hammersley, T. P. McElwee, C. R. McManis, and B. A. Wrigley. 2005. Licensing intellectual property in the information age (2nd ed.). Durham, NC: Carolina Academic Press.
  • Preston, R. 2005. Profit pending. Network Computing, December 8.
  • Qualcomm Inc. 2008. Qualcomm business model: A formula for innovation & choice. White paper. Available at: http://www.qualcomm.com/documents/files/qualcomm-business-model-formula-innovation-choice.pdf.
  • Ricadela, A. 2006. Microsoft IP: A $900 million patent deficit. InformationWeek, April 3.
  • Seget, S. 2005. Biotechnology licensing: How has the balance of power shifted? Spectrum: Pharmaceutical Industry Dynamics, Decision Resources, Inc. October 21.
  • Shapiro, C. 2001. Navigating the patent thicket: Cross-licenses, patent pools, and standard-setting. In Innovation policy and the economy, Vol. 1, ed. A.Jaffe, J.Lerner, and S.Stern. Cambridge, MA: National Bureau of Economic Research.
  • Slind-Flor, V. 2004. Goldscheider’s rule. IP Law & Business, August.
  • Stone, B. 2004. Nickels, dimes, billions: Big tech companies are raking in big bucks—a little at a time—by charging fees for use of their innovations. Newsweek (web exclusive), August 2. Available at: http://www.newsweek.com/2004/08/01/nickels-dimes-billions.html.
  • Via Licensing Corp. 2008. Via Licensing announces patent licensing terms for MPEG Surround. Press release. San Francisco, September 12. Available at: http://www.vialicensing.com/user-license-docs/newsreleasespdf/09_12_2008%20Via%20Licensing%20Announces%20Patent%20Licensing%20Terms%20for%20MPEG%20Surround.pdf.

Abuse of dominance and licensing of intellectual property

Patrick Rey and David Salant(2012) “Abuse of dominance and licensing of intellectual property." International Journal of Industrial Organization,Volume 30, Issue 6, November 2012, Pages 518–527. DOI. Other PDF.

==original abstract==

We examine the impact of the licensing policies of one or more upstream owners of essential intellectual property (IP hereafter) on the variety offered by a downstream industry, as well as on consumers and social welfare. When an upstream IP monopoly increases the number of licenses, it enhances product variety, adding to consumer value, but it also intensifies downstream competition, and thus dissipates profits. As a result, the upstream IP monopoly may want to provide too many or too few licenses relative to what maximizes consumer surplus or social welfare.

With multiple IP owners, royalty stacking increases aggregate licensing fees and thus tends to limit the number of licensees, which can also reduce downstream prices for consumers. We characterize the conditions under which these reductions in downstream prices and variety are beneficial to consumers or society.

Classroom Games in Economics : A Quantitative Assessment of the `Beer Game’

Noted by Yi-Nung

這篇文章提醒了實驗法用在課堂中的優缺點:

…the game tends to improve interest and motivation on average … (有助於提升學習動機…)

…the game is inferior where facts mastery or definitional learning is required … (對實務掌握和定義性學習不利…)

Date: 2011
By: McMahon, Michael (University of Warwick)
URL: http://d.repec.org/n?u=RePEc:wrk:warwec:964&r=net
Using an experiment, I compare the use of the `Beer Distribution’ classroom game with the more traditional `chalk and talk’ approach to teach students about inventories and the macroeconomy. My empirical results confirm and extend our understanding of the relative strengths and weaknesses of the use of classroom games : the game tends to improve interest and motivation on average, though some students dislike their use ; the game is e ective at driving home its key messages, but it may wrongly lead students to disregard other important factors ; the game is inferior where facts mastery or definitional learning is required. Rather than an endorsement or a criticism of classroom games, the conclusion is cautionary advice on how to best make use of games within an overall course. Key words: Classroom experiments and games ; motivation ; student learning outcomes JEL classification: A22 ; C90

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;

==References==

  1. Anderson, E., C. Fine. 1998. Business cycles and productivity in capital equipment supply chains. S. Tayur, Ganeshan, Magazine, eds. Quantitative Methods for Supply Chain Management, Chapter 13. Kluwer Academic Publishers.
  2. Anderson, E., D. Morrice. 2000. A simulation game for teaching service-oriented supply chain management: Does information sharing help managers with service capacity decisions? Production Oper. Management 9(1) 40–55.
  3. Bourland, K., S. Powell, D. Pyke. 1996. Exploiting timely demand information to reduce inventories. Eur. J. Oper. Res. 92 239–253.
  4. Cachon, G. 1999. Managing supply chain variability with scheduled ordering policies. Management Sci. 45 843–856.
  5. Cachon, G., M. Fisher. 2000. Supply chain inventory management and the value of shared information. Management Sci. 46, 1032–1048.
  6. Cachon, G., M. Lariviere. 1999. Capacity choice and allocation: Strategic behavior and supply chain performance. Management Sci. 45 1091–1108.
  7. Chen, F. 1998. Echelon reorder points, installation reorder points, and the value of centralized demand information. Management Sci. 44 S221–S234.
  8. Chen, F. 1999. Decentralized supply chains subject to information delays. Management Sci. 45 1016–1090.
  9. Chen, F., R. Samroengraja. 2000. The stationary beer game. Production Oper. Management 9 19–30.
  10. Chen, F., Z. Drezner, J. K. Ryan, D. Simchi-Levi. 1998. The bullwhip effect: Managerial insights on the impact of forecasting and information on variability in a supply chain. Tayur, Ganeshan, Magazine, eds. Quantitative Models for Supply Chain Management, Chapter 14. Kluwer Academic Publishers.
  11. Clark, A. J., H. E. Scarf. 1960. Optimal policies for a multi-echelon inventory problem. Management Sci. 6 475–490.
  12. Diehl, E., J. D. Sterman. 1995. Effects of feedback complexity in dynamic decision making. Organ. Behavior Human Decision Processes 62 198–215.
  13. Federgruen, A., P. Zipkin. 1984. Computational issues in an infinite horizon, multi-echelon inventory model. Oper. Res. 32 818–836.
  14. Forrester, J. 1958. Industrial dynamics: A major breakthrough for decision makers. Harvard Bus. Rev. 36 37–66.
  15. Gavirneni, S., R. Kapuscinski, S. Tayur. 1999. Value of information in capacitated supply chains. Management Sci. 45 16–24.
  16. Graves, S. C. 1999. A single-item inventory model for a nonstationary demand process. Manufacturing Service Oper. Management 1, 50–61.
  17. Hogarth, R. 1987. Judgment and Choice, 2nd ed. Wiley, New York.
  18. Hogarth, R., H. Einhorn. 1992. Order effects in belief updating: The belief-adjustment model. Cognitive Psych. 24 1–55. Kahneman, D., D. Lovallo. 1993. Timid choices and bold forecasts: A cognitive perspective on risk taking. Management Sci. 39 17–31.
  19. Kalidindi, V. S. 2001. The web based beer distribution game: An application. Unpublished Masters thesis, Department of Mechanical Engineering, University of Minnesota, MN.
  20. Kaminsky, P., D. Simchi-Levi. 1998. A new computerized beer distribution game: Teaching the value of integrated supply chain management. H. Lee, S. M. Ng, eds. Global Supply Chain and Technology Management, Vol. 1. The Production and Operations
    Management Society Series in Technology and Operations Management, 216–225.
  21. Lee, H., P. Padmanabhan, S. Whang. 1997a. Information distortion in supply chains. Sloan Management Rev. 38 93–102.
  22. Lee, H., P. Padmanabhan, S. Whang. 1997b. Information distortion in a supply chain: The bullwhip effect. Management Sci. 43 546–558.
  23. Lee, H., K. So, C. Tang. 2000. The value of information sharing in a two-level supply chain. Management Sci. 46 626–643.
  24. Paich, M., J. D. Sterman. 1993. Boom, bust, and failures to learn in experimental markets. Management Sci. 39 1439–1457.
  25. Scheck, S. 1998. Net tools could save automakers $1 billion. Electronic News 14(September) 104.
  26. Schotter, A., K. Weigelt. 1992. Behavioral consequences of corporate incentives and long-term bonuses: An experimental study. Management Sci. 38 1280–1298.
  27. Schweitzer, M., G. Cachon. 2000. Decision biases and learning in the newsvendor problem: Experimental evidence. Management Sci. 46 404–420.
  28. Seigel, S. 1965. Nonparametric Statistics for the Behavioral Sciences. Wiley, New York.
  29. Sengupta, K., T. Abdul-Hamid. 1993. Alternative conceptions of feedback in dynamic decision environments: An experimental investigation. Management Sci. 39 411–428.
  30. Sogomonian, A., C. Tang. 1993. A modeling framework for coordinating promotion and production decisions within a firm. Management Sci. 39 191–203.
  31. Steckel, J., S. Gupta, A. Banerji. 2004. Supply chain decision making: Will shorter cycle times and shared point-of-sale information necessarily help? Management Sci. 52(4) 458–464.
  32. Stein, T. 1998. SAP targets apparel. Information Week 140(May 4).
  33. Sterman, J. D. 1989a. Modeling managerial behavior: Misperceptions of feedback in a dynamic decision making experiment. Management Sci. 35 321–339.
  34. Sterman, J. D. 1989b. Misperceptions of feedback in dynamic decision making. Organ. Behavior Human Decision Processes 43 301–335.
  35. Sterman, J. D. 1989c. Deterministic chaos in an experimental economic system. J. Econom. Behavior Organ. 12 1–28.
  36. Sterman, J. D. 1992. Teaching takes off: Flight simulators for management education. OR/MS Today 19(5) 40–44.
  37. Sterman, J. D. 1994. Learning in and about complex systems. System Dynam. Rev. 10 291–330.