• Previous Article
    Impact of reorder option in supply chain coordination
  • JIMO Home
  • This Issue
  • Next Article
    Multiple-stage multiple-machine capacitated lot-sizing and scheduling with sequence-dependent setup: A case study in the wheel industry
January  2017, 13(1): 429-447. doi: 10.3934/jimo.2016025

Dynamic pricing of network goods in duopoly markets with boundedly rational consumers

1. 

Business School of Central South University, Changsha, Hunan 410083, China

2. 

School of Accountancy, Hunan University of Finance and Economics, Changsha, Hunan 410205, China

3. 

Department of Mathematics and Statistics, Curtin University, Australia

1 Corresponding Author Email:beenjoy@126.com

Received  April 2015 Published  January 2016

Fund Project: This work is supported by NSFC NO.91646115?71371191,71210003,712221061, PSFC NO.2015JJ2194 and 2015CX010.

In this paper, we present a dynamic pricing model for two firms selling products displaying network effects for which consumers are with bounded rationality. We formulate this model in the form of differential games and derive the open-loop equilibrium prices for the firms. Then, we show the existence and uniqueness of such open-loop equilibrium prices. The model is further extended to the case with heterogeneous network effects. Their steady-state prices obtained are compared. A numerical example is solved and the results obtained are used to analyze how the steady-state prices and market shares of both firms are influenced by the cost, price sensitivity and the network effects of the products.

Citation: Haiying Liu, Xinxing Luo, Wenjie Bi, Yueming Man, Kok Lay Teo. Dynamic pricing of network goods in duopoly markets with boundedly rational consumers. Journal of Industrial & Management Optimization, 2017, 13 (1) : 429-447. doi: 10.3934/jimo.2016025
References:
[1]

S. P. Anderson and A. D. Palma, Multiproduct firms: A nested logit approach, The Journal of Industrial Economics, 40 (1992), 261-276.  doi: 10.2307/2950539.  Google Scholar

[2]

S. P. Anderson, A. D. Palma and J. F. Thisse, Discrete Choice Theory of Product Differentiation, MIT press, 1992.  Google Scholar

[3]

M. E. Ben-Akiva and S. R. Lerman, Discrete Choice Analysis: Theory and Application to Travel Demand, MIT press, 1985. Google Scholar

[4]

B. Bensaid and J. P. Lesne, Dynamic monopoly pricing with network externalities, International Journal of Industrial Organization, 14 (1996), 837-855.  doi: 10.1016/0167-7187(95)01000-9.  Google Scholar

[5]

F. Bloch and N. Quérou, Pricing in social networks, Games and economic behavior, 80 (2013), 243-261.  doi: 10.1016/j.geb.2013.03.006.  Google Scholar

[6]

L. Cabral, Dynamic price competition with network effects, The Review of Economic Studies, 78 (2011), 83-111.  doi: 10.1093/restud/rdq007.  Google Scholar

[7]

L. CabralD. J. Salant and G. A. Woroch, Monopoly pricing with network externalities, International Journal of Industrial Organization, 17 (1999), 199-214.   Google Scholar

[8]

O. CandoganK. Bimpikis and A. Ozdaglar, Optimal pricing in networks with externalities, Operations Research, 60 (2012), 883-905.  doi: 10.1287/opre.1120.1066.  Google Scholar

[9]

A. Caplin and B. Nalebuff, Aggregation and imperfect competition: On the existence of equilibrium, The Econometric Society, 59 (1991), 25-59.  doi: 10.2307/2938239.  Google Scholar

[10]

P. K. Chintagunta and V. R. Rao, Pricing strategies in a dynamic duopoly: A differential game model, Management Science, 42 (1996), 1501-1514.  doi: 10.1287/mnsc.42.11.1501.  Google Scholar

[11]

E. Damiano and L. Hao, Competing matchmaking, Journal of the European Economic Association, 6 (2008), 789-818.  doi: 10.1162/JEEA.2008.6.4.789.  Google Scholar

[12]

A. Dhebar and S. S. Oren, Optimal dynamic pricing for expanding networks, Marketing Science, 4 (1985), 336-351.  doi: 10.1287/mksc.4.4.336.  Google Scholar

[13]

T. Doganoglu, Dynamic price competition with consumption externalities, Netnomics, 5 (2003), 43-69.   Google Scholar

[14]

C. Du, W. L. Cooper and Z. Wang, Optimal Pricing for a Multinomial Logit Choice Model with Network Effects, 2014. Available at SSRN 2477548: http://ssrn.com/abstract=2477548. Google Scholar

[15]

N. Economides, The economics of networks, International journal of industrial organization, 14 (1996), 673-699.   Google Scholar

[16]

G. Ellison and D. Fudenberg, Knife-edge or plateau: When do market models tip?, The Quarterly Journal of Economics, 118 (2003), 1249-1278.   Google Scholar

[17]

G. EllisonD. Fudenberg and M. Möbius, Competing auctions, Journal of the European Economic Association, 2 (2004), 30-66.   Google Scholar

[18]

W. Elmaghraby and P. Keskinocak, Dynamic pricing in the presence of inventory considerations: Research overview, current practices, and future directions, Management Science, 49 (2003), 1287-1309.   Google Scholar

[19]

J. Farrell and G. Saloner, Standardization, compatibility, and innovation, The RAND Journal of Economics, 16 (1985), 70-83.   Google Scholar

[20]

X. Gabaix, A sparsity-based model of bounded rationality, The Quarterly Journal of Economics, 129 (2014), 1661-1710.   Google Scholar

[21]

X. Gabaix, Sparse dynamic programming and aggregate fluctuations, manuscript, 2013. Google Scholar

[22]

A. Herbon, Dynamic pricing vs. acquiring information on consumers' heterogeneous sensitivity to product freshness, International Journal of Production Research, 52 (2014), 918-933.  doi: 10.1080/00207543.2013.843800.  Google Scholar

[23]

E. Hopkins, Adaptive learning models of consumer behavior, Journal of economic behavior & organization, 64 (2007), 348-368.  doi: 10.1016/j.jebo.2006.02.010.  Google Scholar

[24]

M. L. Katz and C. Shapiro, Network externalities, competition, and compatibility, The American economic review, 75 (2014), 424-440.   Google Scholar

[25]

M. J. Khouja, Optimal ordering, discounting, and pricing in the single-period problem, International Journal of Production Economics, 65 (2000), 201-216.  doi: 10.1016/S0925-5273(99)00027-4.  Google Scholar

[26]

D. Laussel and J. Resende, Dynamic price competition in aftermarkets with network effects, Journal of Mathematical Economics, 50 (2014), 106-118.  doi: 10.1016/j.jmateco.2013.10.002.  Google Scholar

[27]

Y. LevinJ. McGill and M. Nediak, Dynamic pricing in the presence of strategic consumers and oligopolistic competition, Management Science, 55 (2008), 32-46.  doi: 10.1287/mnsc.1080.0936.  Google Scholar

[28]

M. F. Mitchell and A. Skrzypacz, Network externalities and long-run market shares, Economic Theory, 29 (2006), 621-648.  doi: 10.1007/s00199-005-0031-0.  Google Scholar

[29]

R. RadnerA. Radunskaya and A. Sundararajan, Dynamic pricing of network goods with boundedly rational consumers, Proceedings of the National Academy of Sciences, 111 (2014), 99-104.  doi: 10.1073/pnas.1319543110.  Google Scholar

[30]

X. Vives, Oligopoly Pricing: Old Ideas and New Tools, MIT press, 2001. Google Scholar

[31]

X. L. Xu and X. Q. Cai, Price and delivery-time competition of perishable products: Existence and uniqueness of Nash equilibrium, Journal of Industrial and Management Optimization, 4 (2008), 843-859.  doi: 10.3934/jimo.2008.4.843.  Google Scholar

[32]

J. X. ZhangZ. Y. Bai and W. S. Tang, Optimal pricing policy for deteriorating items with preservation technology investment, Journal of Industrial and Management Optimization, 10 (2014), 1261-1277.  doi: 10.3934/jimo.2014.10.1261.  Google Scholar

show all references

References:
[1]

S. P. Anderson and A. D. Palma, Multiproduct firms: A nested logit approach, The Journal of Industrial Economics, 40 (1992), 261-276.  doi: 10.2307/2950539.  Google Scholar

[2]

S. P. Anderson, A. D. Palma and J. F. Thisse, Discrete Choice Theory of Product Differentiation, MIT press, 1992.  Google Scholar

[3]

M. E. Ben-Akiva and S. R. Lerman, Discrete Choice Analysis: Theory and Application to Travel Demand, MIT press, 1985. Google Scholar

[4]

B. Bensaid and J. P. Lesne, Dynamic monopoly pricing with network externalities, International Journal of Industrial Organization, 14 (1996), 837-855.  doi: 10.1016/0167-7187(95)01000-9.  Google Scholar

[5]

F. Bloch and N. Quérou, Pricing in social networks, Games and economic behavior, 80 (2013), 243-261.  doi: 10.1016/j.geb.2013.03.006.  Google Scholar

[6]

L. Cabral, Dynamic price competition with network effects, The Review of Economic Studies, 78 (2011), 83-111.  doi: 10.1093/restud/rdq007.  Google Scholar

[7]

L. CabralD. J. Salant and G. A. Woroch, Monopoly pricing with network externalities, International Journal of Industrial Organization, 17 (1999), 199-214.   Google Scholar

[8]

O. CandoganK. Bimpikis and A. Ozdaglar, Optimal pricing in networks with externalities, Operations Research, 60 (2012), 883-905.  doi: 10.1287/opre.1120.1066.  Google Scholar

[9]

A. Caplin and B. Nalebuff, Aggregation and imperfect competition: On the existence of equilibrium, The Econometric Society, 59 (1991), 25-59.  doi: 10.2307/2938239.  Google Scholar

[10]

P. K. Chintagunta and V. R. Rao, Pricing strategies in a dynamic duopoly: A differential game model, Management Science, 42 (1996), 1501-1514.  doi: 10.1287/mnsc.42.11.1501.  Google Scholar

[11]

E. Damiano and L. Hao, Competing matchmaking, Journal of the European Economic Association, 6 (2008), 789-818.  doi: 10.1162/JEEA.2008.6.4.789.  Google Scholar

[12]

A. Dhebar and S. S. Oren, Optimal dynamic pricing for expanding networks, Marketing Science, 4 (1985), 336-351.  doi: 10.1287/mksc.4.4.336.  Google Scholar

[13]

T. Doganoglu, Dynamic price competition with consumption externalities, Netnomics, 5 (2003), 43-69.   Google Scholar

[14]

C. Du, W. L. Cooper and Z. Wang, Optimal Pricing for a Multinomial Logit Choice Model with Network Effects, 2014. Available at SSRN 2477548: http://ssrn.com/abstract=2477548. Google Scholar

[15]

N. Economides, The economics of networks, International journal of industrial organization, 14 (1996), 673-699.   Google Scholar

[16]

G. Ellison and D. Fudenberg, Knife-edge or plateau: When do market models tip?, The Quarterly Journal of Economics, 118 (2003), 1249-1278.   Google Scholar

[17]

G. EllisonD. Fudenberg and M. Möbius, Competing auctions, Journal of the European Economic Association, 2 (2004), 30-66.   Google Scholar

[18]

W. Elmaghraby and P. Keskinocak, Dynamic pricing in the presence of inventory considerations: Research overview, current practices, and future directions, Management Science, 49 (2003), 1287-1309.   Google Scholar

[19]

J. Farrell and G. Saloner, Standardization, compatibility, and innovation, The RAND Journal of Economics, 16 (1985), 70-83.   Google Scholar

[20]

X. Gabaix, A sparsity-based model of bounded rationality, The Quarterly Journal of Economics, 129 (2014), 1661-1710.   Google Scholar

[21]

X. Gabaix, Sparse dynamic programming and aggregate fluctuations, manuscript, 2013. Google Scholar

[22]

A. Herbon, Dynamic pricing vs. acquiring information on consumers' heterogeneous sensitivity to product freshness, International Journal of Production Research, 52 (2014), 918-933.  doi: 10.1080/00207543.2013.843800.  Google Scholar

[23]

E. Hopkins, Adaptive learning models of consumer behavior, Journal of economic behavior & organization, 64 (2007), 348-368.  doi: 10.1016/j.jebo.2006.02.010.  Google Scholar

[24]

M. L. Katz and C. Shapiro, Network externalities, competition, and compatibility, The American economic review, 75 (2014), 424-440.   Google Scholar

[25]

M. J. Khouja, Optimal ordering, discounting, and pricing in the single-period problem, International Journal of Production Economics, 65 (2000), 201-216.  doi: 10.1016/S0925-5273(99)00027-4.  Google Scholar

[26]

D. Laussel and J. Resende, Dynamic price competition in aftermarkets with network effects, Journal of Mathematical Economics, 50 (2014), 106-118.  doi: 10.1016/j.jmateco.2013.10.002.  Google Scholar

[27]

Y. LevinJ. McGill and M. Nediak, Dynamic pricing in the presence of strategic consumers and oligopolistic competition, Management Science, 55 (2008), 32-46.  doi: 10.1287/mnsc.1080.0936.  Google Scholar

[28]

M. F. Mitchell and A. Skrzypacz, Network externalities and long-run market shares, Economic Theory, 29 (2006), 621-648.  doi: 10.1007/s00199-005-0031-0.  Google Scholar

[29]

R. RadnerA. Radunskaya and A. Sundararajan, Dynamic pricing of network goods with boundedly rational consumers, Proceedings of the National Academy of Sciences, 111 (2014), 99-104.  doi: 10.1073/pnas.1319543110.  Google Scholar

[30]

X. Vives, Oligopoly Pricing: Old Ideas and New Tools, MIT press, 2001. Google Scholar

[31]

X. L. Xu and X. Q. Cai, Price and delivery-time competition of perishable products: Existence and uniqueness of Nash equilibrium, Journal of Industrial and Management Optimization, 4 (2008), 843-859.  doi: 10.3934/jimo.2008.4.843.  Google Scholar

[32]

J. X. ZhangZ. Y. Bai and W. S. Tang, Optimal pricing policy for deteriorating items with preservation technology investment, Journal of Industrial and Management Optimization, 10 (2014), 1261-1277.  doi: 10.3934/jimo.2014.10.1261.  Google Scholar

Figure 1.  The relationship between $p^*_i$ and $\alpha_1$ when $ \alpha_2=0.95 $
Figure 2.  The relationship between $q^*_i$ and $\alpha_1$ when $ \alpha_2=0.95 $
Figure 3.  The relationship between $p^*_i$ and $c_1$ when $ c_2=1 $
Figure 4.  The relationship between $q^*_i$ and $c_1$ when $ c_2=1 $
Figure 5.  The relationship between $p^*_i$ and $\beta_1$ when $ \beta_2=0.9 $
Figure 6.  The relationship between $q^*_i$ and $\beta_1$ when $ \beta_2=0.9 $
Figure 7.  The relationship between $p^*_i$ with $\gamma_1$ when $ \gamma_2=0.8 $
Figure 8.  The relationship between $q^*_i$ with $\gamma_1$ when $ \gamma_2=0.8 $
Figure 9.  The relationship between $J^*_i$ and $\alpha_1$ when $ \alpha_2=0.95 $
Figure 10.  The relationship between $J^*_i$ and $c_1$ when $ c_2=1 $
Figure 11.  The relationship between $J^*_i$ and $\beta_1$ when $ \beta_2=0.9 $
Figure 12.  The relationship between $J^*_i$ and $\gamma_1$ when $ \gamma_2=0.8 $
Figure 13.  Comparison between the $p^*_1$ and $p^m_1$
Figure 14.  Comparison between the $p^*_i$ and $p^W_i$
Table1 
$ p_i(t) $the price of Firm $i's$ product at time $ t $
$ q_i(t) $the probability of a consumer purchases Firm $ i's $ product
$ \xi_i(t) $consumer's time-varying preference for Firm $ i's $ product
$ \beta_i$the coefficient of the time-varying preference for Firm $ i's $ product
$ \gamma_i$the price sensitivity parameter for Firm $ i's $ product
$ x_i(t)$market's total demand of Firm $ i's $ product at time $ t $
$ \alpha_i$the network effects sensitivity parameter for Firm $ i's $ product
$ \dot{\xi}_{is}(t)$the rate of change of $ \xi_{i}(t) $ with respect to time $ t $
$ \varepsilon_i(t)$the stochastic utility gained by the consumer for purchasing Firm $i's$ product at time $ t $
$ \varPsi_s$the fraction of consumers in segment $ s $
$ q_{is}(t)$the probability of purchasing Firm $ i's $ product for consumers in segment $ s $
$ \xi_{is}(t)$the time varying preference of Firm $ i's $ product for consumers in segment $ s $
$ p_i(t) $the price of Firm $i's$ product at time $ t $
$ q_i(t) $the probability of a consumer purchases Firm $ i's $ product
$ \xi_i(t) $consumer's time-varying preference for Firm $ i's $ product
$ \beta_i$the coefficient of the time-varying preference for Firm $ i's $ product
$ \gamma_i$the price sensitivity parameter for Firm $ i's $ product
$ x_i(t)$market's total demand of Firm $ i's $ product at time $ t $
$ \alpha_i$the network effects sensitivity parameter for Firm $ i's $ product
$ \dot{\xi}_{is}(t)$the rate of change of $ \xi_{i}(t) $ with respect to time $ t $
$ \varepsilon_i(t)$the stochastic utility gained by the consumer for purchasing Firm $i's$ product at time $ t $
$ \varPsi_s$the fraction of consumers in segment $ s $
$ q_{is}(t)$the probability of purchasing Firm $ i's $ product for consumers in segment $ s $
$ \xi_{is}(t)$the time varying preference of Firm $ i's $ product for consumers in segment $ s $
[1]

Junichi Minagawa. On the uniqueness of Nash equilibrium in strategic-form games. Journal of Dynamics & Games, 2020, 7 (2) : 97-104. doi: 10.3934/jdg.2020006

[2]

Rui Hu, Yuan Yuan. Stability, bifurcation analysis in a neural network model with delay and diffusion. Conference Publications, 2009, 2009 (Special) : 367-376. doi: 10.3934/proc.2009.2009.367

[3]

Alexandr Mikhaylov, Victor Mikhaylov. Dynamic inverse problem for Jacobi matrices. Inverse Problems & Imaging, 2019, 13 (3) : 431-447. doi: 10.3934/ipi.2019021

[4]

Juan Manuel Pastor, Javier García-Algarra, Javier Galeano, José María Iriondo, José J. Ramasco. A simple and bounded model of population dynamics for mutualistic networks. Networks & Heterogeneous Media, 2015, 10 (1) : 53-70. doi: 10.3934/nhm.2015.10.53

[5]

Simone Cacace, Maurizio Falcone. A dynamic domain decomposition for the eikonal-diffusion equation. Discrete & Continuous Dynamical Systems - S, 2016, 9 (1) : 109-123. doi: 10.3934/dcdss.2016.9.109

[6]

Jaume Llibre, Luci Any Roberto. On the periodic solutions of a class of Duffing differential equations. Discrete & Continuous Dynamical Systems - A, 2013, 33 (1) : 277-282. doi: 10.3934/dcds.2013.33.277

[7]

Xianchao Xiu, Ying Yang, Wanquan Liu, Lingchen Kong, Meijuan Shang. An improved total variation regularized RPCA for moving object detection with dynamic background. Journal of Industrial & Management Optimization, 2020, 16 (4) : 1685-1698. doi: 10.3934/jimo.2019024

[8]

Yuncherl Choi, Taeyoung Ha, Jongmin Han, Sewoong Kim, Doo Seok Lee. Turing instability and dynamic phase transition for the Brusselator model with multiple critical eigenvalues. Discrete & Continuous Dynamical Systems - A, 2021  doi: 10.3934/dcds.2021035

[9]

Guido De Philippis, Antonio De Rosa, Jonas Hirsch. The area blow up set for bounded mean curvature submanifolds with respect to elliptic surface energy functionals. Discrete & Continuous Dynamical Systems - A, 2019, 39 (12) : 7031-7056. doi: 10.3934/dcds.2019243

[10]

Wolf-Jüergen Beyn, Janosch Rieger. The implicit Euler scheme for one-sided Lipschitz differential inclusions. Discrete & Continuous Dynamical Systems - B, 2010, 14 (2) : 409-428. doi: 10.3934/dcdsb.2010.14.409

[11]

Luigi C. Berselli, Jishan Fan. Logarithmic and improved regularity criteria for the 3D nematic liquid crystals models, Boussinesq system, and MHD equations in a bounded domain. Communications on Pure & Applied Analysis, 2015, 14 (2) : 637-655. doi: 10.3934/cpaa.2015.14.637

[12]

Nhu N. Nguyen, George Yin. Stochastic partial differential equation models for spatially dependent predator-prey equations. Discrete & Continuous Dynamical Systems - B, 2020, 25 (1) : 117-139. doi: 10.3934/dcdsb.2019175

[13]

Bin Pei, Yong Xu, Yuzhen Bai. Convergence of p-th mean in an averaging principle for stochastic partial differential equations driven by fractional Brownian motion. Discrete & Continuous Dynamical Systems - B, 2020, 25 (3) : 1141-1158. doi: 10.3934/dcdsb.2019213

[14]

Xiaoming Wang. Quasi-periodic solutions for a class of second order differential equations with a nonlinear damping term. Discrete & Continuous Dynamical Systems - S, 2017, 10 (3) : 543-556. doi: 10.3934/dcdss.2017027

[15]

Zhiming Guo, Zhi-Chun Yang, Xingfu Zou. Existence and uniqueness of positive solution to a non-local differential equation with homogeneous Dirichlet boundary condition---A non-monotone case. Communications on Pure & Applied Analysis, 2012, 11 (5) : 1825-1838. doi: 10.3934/cpaa.2012.11.1825

2019 Impact Factor: 1.366

Metrics

  • PDF downloads (134)
  • HTML views (392)
  • Cited by (0)

[Back to Top]