April  2017, 13(2): 873-899. doi: 10.3934/jimo.2016051

Salesforce contract design, joint pricing and production planning with asymmetric overconfidence sales agent

1. 

School of Management, China University of Mining and Technology, Xuzhou, China

2. 

College of Information Science and Engineering, State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, China

3. 

Advanced Modeling and Applied Computing Laboratory, Department of Mathematics, The University of Hong Kong, Pokfulam Road, Hong Kong, China

* Corresponding author: Xinyu Wang

Received  September 2015 Revised  June 2016 Published  August 2016

We study a supply chain in which a rational manufacturer relies on an overconfident sales agent to sell the products. The actual sales outcome is determined by the sales agent's selling effort, the product price and a random market condition, and the sales agent is overconfident in their estimation of sales outcome. Apart from them, both of the sales agent's degree of overconfidence and selling effort are his private information. We consider the salesforce incentive to motivate the sales agent and screen his real degree of overconfidence using a principle-agent method under dual information asymmetry, then the manufacturer uses the information to realize her joint decision on pricing and production. Furthermore, we derive the optimal compensation contract as well as the optimal pricing and production, and compare it to the symmetric overconfidence scenario. Finally, some interesting insights are found: when the manufacturer is uncertain about the sales agent's the degree of overconfidence, her expected profit decreases while the sales agent with private information exerts less effort but obtains higher income, which implies the value of information; the manufacturer should hire a more overconfident sales agent, while a higher commission rate is not guaranteed. These results suggest that the manufacturer should not only focus on hiring the overconfident sales agent but also on disclosing the degree of overconfidence.

Citation: Kegui Chen, Xinyu Wang, Min Huang, Wai-Ki Ching. Salesforce contract design, joint pricing and production planning with asymmetric overconfidence sales agent. Journal of Industrial & Management Optimization, 2017, 13 (2) : 873-899. doi: 10.3934/jimo.2016051
References:
[1]

A. BasuR. LalV. Srinivasan and R. Staelin, Salesforce-compensation plans: An agency theoretic perspective, Marketing Science, 4 (1985), 267-291. doi: 10.1287/mksc.4.4.267. Google Scholar

[2]

E. BendolyR. CrosonP. Goncalves and K. Schultz, Bodies of knowledge for research in behavioral operations, Production and Operations Management, 19 (2010), 434-452. doi: 10.1111/j.1937-5956.2009.01108.x. Google Scholar

[3]

L. W. Busenitz and J. B. Barney, Differences between entrepreneurs and managers in large organizations: Biases and heuristics in strategic decision-making, Journal of Business Venturing, 12 (1997), 9-30. Google Scholar

[4]

O. Caliskan-DemiragY. F. Chen and J. B. Li, Channel coordination under fairness concerns and nonlinear demand, European Journal of Operational Research, 207 (2010), 1321-1326. doi: 10.1016/j.ejor.2010.07.017. Google Scholar

[5]

E. CaoY. MaC. Wan and M. Lai, Contracting with asymmetric cost information in a dual-channel supply chain, Operations Research Letters, 41 (2013), 410-414. doi: 10.1016/j.orl.2013.04.013. Google Scholar

[6]

X. ChaoB. Yang and Y. Xu, Dynamic inventory and pricing policy in a capacitated stochastic inventory system with fixed ordering cost, Operations Research Letters, 40 (2010), 99-107. doi: 10.1016/j.orl.2011.12.002. Google Scholar

[7]

F. Chen, Salesforce incentives, market information and production/inventory planning, Management Science, 51 (2005), 60-75. doi: 10.1287/mnsc.1040.0217. Google Scholar

[8]

Y. J. ChenS. Shum and W. Q. Xiao, Should an OEM retain component procurement when the CM produces competing products, Production and Operations Management, 21 (2012), 907-922. doi: 10.1111/j.1937-5956.2012.01325.x. Google Scholar

[9]

C. H. ChiuT. M. Choi and C. S. Tang, Price, rebate, and returns supply contracts for coordinating supply chains with price dependent demand, Production and Operations Management, 20 (2011), 81-91. doi: 10.1111/j.1937-5956.2010.01159.x. Google Scholar

[10]

P. S. ChowY. WangT. M. Choi and B. Shen, An experimental study on the effects of minimum profit share on supply chains with markdown contracts: risk and profit analysis, Omega, 57 (2015), 85-97. doi: 10.1016/j.omega.2013.11.007. Google Scholar

[11]

A. T. Coughlan, Salesforce Compensation: A Review of MS/OR Advances, In: Eliashberg, J., G. L. Lilien (eds.), Handbook in Operations Research and Management Science, 1993.Google Scholar

[12]

T. H. CuiJ. S. Raju and Z. J. Zhang, Fairness and channel coordination, Management Science, 53 (2007), 1303-1314. Google Scholar

[13]

Y. Dai and X. L. Chao, Salesforce contract design and inventory planning with asymmetric risk-averse sales agents, Operations Research Letters, 41 (2013), 86-91. doi: 10.1016/j.orl.2012.11.010. Google Scholar

[14]

F. Englmaier and A. Wambach A, Optimal incentive contracts under inequity aversion, Games and Economic Behavior, 69 (2010), 312-328. doi: 10.1016/j.geb.2009.12.007. Google Scholar

[15]

B. FernandoJ. Song and X. Zheng, Free riding in a multi-channel supply chain, Naval Research Logistics, 56 (2009), 745-765. doi: 10.1002/nav.20379. Google Scholar

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D. GarciaF. Sangiorgi and B. Urosevic, Overconfidence and market efficiency with heterogeneous agents, Economic Theory, 30 (2007), 313-336. doi: 10.1007/s00199-005-0048-4. Google Scholar

[17]

J. Gonik, The salesmen's bonuses to their forecasts, Harvard Business Review, 56 (1978), 116-123. Google Scholar

[18]

A. Hung and C. Plott, Information cascades: Replication and an extension to majority rule and conformity rewarding institutions, American Economic Review, 91 (2001), 1508-1520. doi: 10.1257/aer.91.5.1508. Google Scholar

[19]

T. H. HoX. Su and Y. Wu, Distributional and peer-induced fairness in supply chain contract design, Historical Journal of Film Radio & Television, 23 (2014), 161-175. Google Scholar

[20]

D. Kahneman and A. Tversky, Prospect theory: An analysis of decision under risk, Econometrica, 47 (1979), 263-291. Google Scholar

[21]

E. Katok and V. Pavlov, Fairness in supply chain contracts: A laboratory study, Journal of Operations Management, 31 (2013), 129-137. doi: 10.1016/j.jom.2013.01.001. Google Scholar

[22]

M. Kaya and O. Ozer, Quality risk in outsourcing: Noncontractible product quality and private quality cost information, Naval Research Logistics, 56 (2009), 669-685. doi: 10.1002/nav.20372. Google Scholar

[23]

K. L. Keiber, Managerial Compensation Contracts and Overconfidence, Working paper, WHU Otto Beisheim Graduate School of Management, Vallendar, 2002. doi: 10.2139/ssrn.302416. Google Scholar

[24]

L. C. Kung and Y. J. Chen, Monitoring the market or the salesperson? The value of information in a multilayer supply chain, Naval Research Logistics, 58 (2011), 743-762. doi: 10.1002/nav.20480. Google Scholar

[25]

C. Y. Lee and R. Yang, Compensation plan for competing salespersons under asymmetric information, European Journal of Operational Research, 227 (2013), 570-580. doi: 10.1016/j.ejor.2013.01.007. Google Scholar

[26]

C. Y. Lee and R. Yang, Supply chain contracting with competing suppliers under asymmetric information, IIE Transactions, 45 (2013), 25-52. doi: 10.1080/0740817X.2012.662308. Google Scholar

[27]

Y. LiM. Shan and M. Z. F. Li, Advance selling decisions with overconfident consumers, Journal of Industrial & Management Optimization, 12 (2016), 891-905. doi: 10.3934/jimo.2016.12.891. Google Scholar

[28]

B. LiuR. Zhang and M. D. Xiao, Joint decision on production and pricing for online dual channel supply chain system, Applied Mathematical Modelling, 34 (2010), 4208-4218. doi: 10.1016/j.apm.2010.04.018. Google Scholar

[29] C. H. Loch, Behavioral Operations Management, Now Publishers Inc, Hanover, 2007. doi: 10.1561/0200000009. Google Scholar
[30]

S. LudwigP. C. Wichardt and H. Wickhorst, Overconfidence can improve an agent's relative and absolute performance in contests, Economics Letters, 110 (2011), 193-196. doi: 10.1016/j.econlet.2010.11.040. Google Scholar

[31]

U. Malmendier and G. Tate, CEO Overconfidence and Corporate Investment, Harvard University, 2002.Google Scholar

[32]

D. A. Moore and P. J. Healy, The trouble with overconfidence, Psychological review, 115 (2008), 502-517. doi: 10.1037/0033-295X.115.2.502. Google Scholar

[33]

S. OhK. Sourirajan and M. Ettl, Joint pricing and production decisions in an assemble-to-order system, Manufacturing & Service Operations Management, 16 (2014), 529-543. doi: 10.1287/msom.2014.0492. Google Scholar

[34]

S. Oskamp, Overconfidence in case study judgment, Journal of Consulting Psychology, 29 (1965), 261-265. Google Scholar

[35]

O. Ozer and G. Raz, Supply chain sourcing under asymmetric information, Production and Operations Management, 20 (2011), 92-115. Google Scholar

[36]

S. PalS. S. Sana and K. Chaudhuri, Joint pricing and ordering policy for two echelon imperfect production inventory model with two cycles, International Journal of Production Economics, 155 (2014), 229-238. doi: 10.1016/j.ijpe.2013.11.027. Google Scholar

[37]

V. Pavlov and E. Katok, Fairness and Coordination Failures in Supply Chain Contracts, Working paper, Smeal College of Business, Pennsylvania State University, Pennsylvania, 2009. doi: 10.2139/ssrn.2623821. Google Scholar

[38]

Y. QinJ. Wang and C. Wei, Joint pricing and inventory control for fresh produce and foods with quality and physical quantity deteriorating simultaneously, International Journal of Production Economics, 152 (2014), 42-48. doi: 10.1016/j.ijpe.2014.01.005. Google Scholar

[39]

L. E. De la Rosa, Overconfidence and moral hazard, Games and Economic Behavior, 73 (2011), 429-451. doi: 10.1016/j.geb.2011.04.001. Google Scholar

[40]

Y. Ren and R. Croson, Overconfidence in newsvendor orders: An experimental study, Management Science, 59 (2013), 2502-2517. doi: 10.1287/mnsc.2013.1715. Google Scholar

[41]

J. E. Russo and P. J. H. Schoemaker, Managing Overconfidence, Sloan Management Review, 33 (1992), 7-17. Google Scholar

[42]

S. Saghafian and X. Chao, The impact of operational decisions on the design of salesforce incentives, Naval Research Logistics, 61 (2014), 320-340. doi: 10.1002/nav.21585. Google Scholar

[43]

A. Sandroni and F. Squintani, Overconfidence and asymmetric information: The case of insurance, Journal of Economic Behavior & Organization, 90 (2013), 149-165. Google Scholar

[44]

T. Steenburgh and M. Ahearne, Motivating salespeople: what really works, Harvard Business Review, 90 (2012), 70-75. Google Scholar

[45]

T. A. Taylor, Supply chain coordination under channel rebates with sales effort effects, Management Science, 48 (2002), 992-1007. doi: 10.1287/mnsc.48.8.992.168. Google Scholar

[46]

T. A. Taylor, Sale Timing in a supply chain: When to sell to the retailer, Manufacturing & Service Operations Management, 8 (2006), 23-42. doi: 10.1287/msom.1050.0089. Google Scholar

[47]

H. XuN. ShiS. Ma and K. K. Lai, Contracting with an urgent supplier under cost information asymmetry, European Journal of Operational Research, 206 (2010), 374-383. doi: 10.1016/j.ejor.2010.03.012. Google Scholar

[48]

J. WeiK. GovindanY. Li and J. Zhao, Pricing and collecting decisions in a closed-loop supply chain with symmetric and asymmetric information, Computers & Operations Research, 54 (2015), 257-265. doi: 10.1016/j.cor.2013.11.021. Google Scholar

[49]

P. ZhangY. XiongZ. Xiong and W. Yan, Designing contracts for a closed-loop supply chain under information asymmetry, Operations Research Letters, 42 (2014), 150-155. doi: 10.1016/j.orl.2014.01.004. Google Scholar

[50]

A. A. ZoltnersP. Sinha and S. E. Lorimer, Sales force effectiveness: A framework for researchers and practitioners, Journal of Personal Selling & Sales Management, 28 (2008), 115-131. doi: 10.2753/PSS0885-3134280201. Google Scholar

show all references

References:
[1]

A. BasuR. LalV. Srinivasan and R. Staelin, Salesforce-compensation plans: An agency theoretic perspective, Marketing Science, 4 (1985), 267-291. doi: 10.1287/mksc.4.4.267. Google Scholar

[2]

E. BendolyR. CrosonP. Goncalves and K. Schultz, Bodies of knowledge for research in behavioral operations, Production and Operations Management, 19 (2010), 434-452. doi: 10.1111/j.1937-5956.2009.01108.x. Google Scholar

[3]

L. W. Busenitz and J. B. Barney, Differences between entrepreneurs and managers in large organizations: Biases and heuristics in strategic decision-making, Journal of Business Venturing, 12 (1997), 9-30. Google Scholar

[4]

O. Caliskan-DemiragY. F. Chen and J. B. Li, Channel coordination under fairness concerns and nonlinear demand, European Journal of Operational Research, 207 (2010), 1321-1326. doi: 10.1016/j.ejor.2010.07.017. Google Scholar

[5]

E. CaoY. MaC. Wan and M. Lai, Contracting with asymmetric cost information in a dual-channel supply chain, Operations Research Letters, 41 (2013), 410-414. doi: 10.1016/j.orl.2013.04.013. Google Scholar

[6]

X. ChaoB. Yang and Y. Xu, Dynamic inventory and pricing policy in a capacitated stochastic inventory system with fixed ordering cost, Operations Research Letters, 40 (2010), 99-107. doi: 10.1016/j.orl.2011.12.002. Google Scholar

[7]

F. Chen, Salesforce incentives, market information and production/inventory planning, Management Science, 51 (2005), 60-75. doi: 10.1287/mnsc.1040.0217. Google Scholar

[8]

Y. J. ChenS. Shum and W. Q. Xiao, Should an OEM retain component procurement when the CM produces competing products, Production and Operations Management, 21 (2012), 907-922. doi: 10.1111/j.1937-5956.2012.01325.x. Google Scholar

[9]

C. H. ChiuT. M. Choi and C. S. Tang, Price, rebate, and returns supply contracts for coordinating supply chains with price dependent demand, Production and Operations Management, 20 (2011), 81-91. doi: 10.1111/j.1937-5956.2010.01159.x. Google Scholar

[10]

P. S. ChowY. WangT. M. Choi and B. Shen, An experimental study on the effects of minimum profit share on supply chains with markdown contracts: risk and profit analysis, Omega, 57 (2015), 85-97. doi: 10.1016/j.omega.2013.11.007. Google Scholar

[11]

A. T. Coughlan, Salesforce Compensation: A Review of MS/OR Advances, In: Eliashberg, J., G. L. Lilien (eds.), Handbook in Operations Research and Management Science, 1993.Google Scholar

[12]

T. H. CuiJ. S. Raju and Z. J. Zhang, Fairness and channel coordination, Management Science, 53 (2007), 1303-1314. Google Scholar

[13]

Y. Dai and X. L. Chao, Salesforce contract design and inventory planning with asymmetric risk-averse sales agents, Operations Research Letters, 41 (2013), 86-91. doi: 10.1016/j.orl.2012.11.010. Google Scholar

[14]

F. Englmaier and A. Wambach A, Optimal incentive contracts under inequity aversion, Games and Economic Behavior, 69 (2010), 312-328. doi: 10.1016/j.geb.2009.12.007. Google Scholar

[15]

B. FernandoJ. Song and X. Zheng, Free riding in a multi-channel supply chain, Naval Research Logistics, 56 (2009), 745-765. doi: 10.1002/nav.20379. Google Scholar

[16]

D. GarciaF. Sangiorgi and B. Urosevic, Overconfidence and market efficiency with heterogeneous agents, Economic Theory, 30 (2007), 313-336. doi: 10.1007/s00199-005-0048-4. Google Scholar

[17]

J. Gonik, The salesmen's bonuses to their forecasts, Harvard Business Review, 56 (1978), 116-123. Google Scholar

[18]

A. Hung and C. Plott, Information cascades: Replication and an extension to majority rule and conformity rewarding institutions, American Economic Review, 91 (2001), 1508-1520. doi: 10.1257/aer.91.5.1508. Google Scholar

[19]

T. H. HoX. Su and Y. Wu, Distributional and peer-induced fairness in supply chain contract design, Historical Journal of Film Radio & Television, 23 (2014), 161-175. Google Scholar

[20]

D. Kahneman and A. Tversky, Prospect theory: An analysis of decision under risk, Econometrica, 47 (1979), 263-291. Google Scholar

[21]

E. Katok and V. Pavlov, Fairness in supply chain contracts: A laboratory study, Journal of Operations Management, 31 (2013), 129-137. doi: 10.1016/j.jom.2013.01.001. Google Scholar

[22]

M. Kaya and O. Ozer, Quality risk in outsourcing: Noncontractible product quality and private quality cost information, Naval Research Logistics, 56 (2009), 669-685. doi: 10.1002/nav.20372. Google Scholar

[23]

K. L. Keiber, Managerial Compensation Contracts and Overconfidence, Working paper, WHU Otto Beisheim Graduate School of Management, Vallendar, 2002. doi: 10.2139/ssrn.302416. Google Scholar

[24]

L. C. Kung and Y. J. Chen, Monitoring the market or the salesperson? The value of information in a multilayer supply chain, Naval Research Logistics, 58 (2011), 743-762. doi: 10.1002/nav.20480. Google Scholar

[25]

C. Y. Lee and R. Yang, Compensation plan for competing salespersons under asymmetric information, European Journal of Operational Research, 227 (2013), 570-580. doi: 10.1016/j.ejor.2013.01.007. Google Scholar

[26]

C. Y. Lee and R. Yang, Supply chain contracting with competing suppliers under asymmetric information, IIE Transactions, 45 (2013), 25-52. doi: 10.1080/0740817X.2012.662308. Google Scholar

[27]

Y. LiM. Shan and M. Z. F. Li, Advance selling decisions with overconfident consumers, Journal of Industrial & Management Optimization, 12 (2016), 891-905. doi: 10.3934/jimo.2016.12.891. Google Scholar

[28]

B. LiuR. Zhang and M. D. Xiao, Joint decision on production and pricing for online dual channel supply chain system, Applied Mathematical Modelling, 34 (2010), 4208-4218. doi: 10.1016/j.apm.2010.04.018. Google Scholar

[29] C. H. Loch, Behavioral Operations Management, Now Publishers Inc, Hanover, 2007. doi: 10.1561/0200000009. Google Scholar
[30]

S. LudwigP. C. Wichardt and H. Wickhorst, Overconfidence can improve an agent's relative and absolute performance in contests, Economics Letters, 110 (2011), 193-196. doi: 10.1016/j.econlet.2010.11.040. Google Scholar

[31]

U. Malmendier and G. Tate, CEO Overconfidence and Corporate Investment, Harvard University, 2002.Google Scholar

[32]

D. A. Moore and P. J. Healy, The trouble with overconfidence, Psychological review, 115 (2008), 502-517. doi: 10.1037/0033-295X.115.2.502. Google Scholar

[33]

S. OhK. Sourirajan and M. Ettl, Joint pricing and production decisions in an assemble-to-order system, Manufacturing & Service Operations Management, 16 (2014), 529-543. doi: 10.1287/msom.2014.0492. Google Scholar

[34]

S. Oskamp, Overconfidence in case study judgment, Journal of Consulting Psychology, 29 (1965), 261-265. Google Scholar

[35]

O. Ozer and G. Raz, Supply chain sourcing under asymmetric information, Production and Operations Management, 20 (2011), 92-115. Google Scholar

[36]

S. PalS. S. Sana and K. Chaudhuri, Joint pricing and ordering policy for two echelon imperfect production inventory model with two cycles, International Journal of Production Economics, 155 (2014), 229-238. doi: 10.1016/j.ijpe.2013.11.027. Google Scholar

[37]

V. Pavlov and E. Katok, Fairness and Coordination Failures in Supply Chain Contracts, Working paper, Smeal College of Business, Pennsylvania State University, Pennsylvania, 2009. doi: 10.2139/ssrn.2623821. Google Scholar

[38]

Y. QinJ. Wang and C. Wei, Joint pricing and inventory control for fresh produce and foods with quality and physical quantity deteriorating simultaneously, International Journal of Production Economics, 152 (2014), 42-48. doi: 10.1016/j.ijpe.2014.01.005. Google Scholar

[39]

L. E. De la Rosa, Overconfidence and moral hazard, Games and Economic Behavior, 73 (2011), 429-451. doi: 10.1016/j.geb.2011.04.001. Google Scholar

[40]

Y. Ren and R. Croson, Overconfidence in newsvendor orders: An experimental study, Management Science, 59 (2013), 2502-2517. doi: 10.1287/mnsc.2013.1715. Google Scholar

[41]

J. E. Russo and P. J. H. Schoemaker, Managing Overconfidence, Sloan Management Review, 33 (1992), 7-17. Google Scholar

[42]

S. Saghafian and X. Chao, The impact of operational decisions on the design of salesforce incentives, Naval Research Logistics, 61 (2014), 320-340. doi: 10.1002/nav.21585. Google Scholar

[43]

A. Sandroni and F. Squintani, Overconfidence and asymmetric information: The case of insurance, Journal of Economic Behavior & Organization, 90 (2013), 149-165. Google Scholar

[44]

T. Steenburgh and M. Ahearne, Motivating salespeople: what really works, Harvard Business Review, 90 (2012), 70-75. Google Scholar

[45]

T. A. Taylor, Supply chain coordination under channel rebates with sales effort effects, Management Science, 48 (2002), 992-1007. doi: 10.1287/mnsc.48.8.992.168. Google Scholar

[46]

T. A. Taylor, Sale Timing in a supply chain: When to sell to the retailer, Manufacturing & Service Operations Management, 8 (2006), 23-42. doi: 10.1287/msom.1050.0089. Google Scholar

[47]

H. XuN. ShiS. Ma and K. K. Lai, Contracting with an urgent supplier under cost information asymmetry, European Journal of Operational Research, 206 (2010), 374-383. doi: 10.1016/j.ejor.2010.03.012. Google Scholar

[48]

J. WeiK. GovindanY. Li and J. Zhao, Pricing and collecting decisions in a closed-loop supply chain with symmetric and asymmetric information, Computers & Operations Research, 54 (2015), 257-265. doi: 10.1016/j.cor.2013.11.021. Google Scholar

[49]

P. ZhangY. XiongZ. Xiong and W. Yan, Designing contracts for a closed-loop supply chain under information asymmetry, Operations Research Letters, 42 (2014), 150-155. doi: 10.1016/j.orl.2014.01.004. Google Scholar

[50]

A. A. ZoltnersP. Sinha and S. E. Lorimer, Sales force effectiveness: A framework for researchers and practitioners, Journal of Personal Selling & Sales Management, 28 (2008), 115-131. doi: 10.2753/PSS0885-3134280201. Google Scholar

Figure 1.  The impact of the sales agent's degree of overconfidence on his optimal effort
Figure 2.  The impact of the sales agent's degree of overconfidence on the commission rate
Figure 3.  The impact of the sales agent's degree of overconfidence on the price
Figure 4.  The impact of the sales agent's degree of overconfidence on the production quantity
Figure 5.  The impact of the sales agent's degree of overconfidence on the manufacturer's expected profits
Figure 6.  The impact of the sales agent's degree of overconfidence on her expected profits
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