no. 5
Dynamic market share through advertising and loyalty reward programs: A case study of Ofo versus Mobike
RAIRO. Operations Research, Tome 56 (2022) no. 5, pp. 3545-3560

The emerging business models have impelled firms’ competition in a brand-new and fast-growing market. This study examines such a competition for market share through advertising and loyalty reward programs. Two stages can be distinguished based on the transformation of the competition strategies. These stages can be formulated as a dynamic differential game model and a static Hotelling game model. The operation strategies and performances of two firms are determined and compared via analytical studies and case analyses toward a bicycle-sharing program, i.e., Ofo versus Mobike. Historical data are used to fit the curve of the market size and to estimate the parameter values of these models. The results show that during the first stage, the difference in market share between these firms gradually decreases (increases) when the advertising response constant is low (high). Meanwhile, in the second stage, these firms offer converse reward strategies.

DOI : 10.1051/ro/2022166
Classification : 90B60, 90B90
Keywords: Dynamic market share, loyalty reward programs, advertising, bicycle-sharing program, case study 
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     title = {Dynamic market share through advertising and loyalty reward programs: {A} case study of {Ofo} versus {Mobike}},
     journal = {RAIRO. Operations Research},
     pages = {3545--3560},
     year = {2022},
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Wang, Jun; Li, Yu; Jiang, Wenwen; Wang, Yufang; Zhang, Shuhua. Dynamic market share through advertising and loyalty reward programs: A case study of Ofo versus Mobike. RAIRO. Operations Research, Tome 56 (2022) no. 5, pp. 3545-3560. doi: 10.1051/ro/2022166

[1] B. Niu, H. Yue, H. Luo and W. Shang, Pricing for newly-launched experience products: Free trial or not? Transp. Res. Part E Logist. Transp. Rev. 126 (2019) 149–176. | DOI

[2] D. Liu and V. Mookerjee, Advertising competition on the internet: Operational and strategic considerations. Prod. Oper. Manag. 27 (2018) 884–901. | DOI

[3] J. Huang, M. Leng and L. Liang, Recent developments in dynamic advertising research. Eur. J. Oper. Res. 220 (2012) 591–609. | MR | Zbl | DOI

[4] M. Nerlove and K. J. Arrow, Optimal advertising policy under dynamic conditions. Economica 29 (1962) 129–142. | DOI

[5] B. Viscolani and G. Zaccour, Advertising strategies in a differential game with negative competitor’s interference. J. Optim. Theory App. 140 (2009) 153–170. | MR | Zbl | DOI

[6] A. Nair, R. Narasimhan, Dynamics of competing with quality- and advertising-based goodwill. Eur. J. Oper. Res. 175 (2006) 462–474. | Zbl | DOI

[7] G. Bertuzzi and L. Lambertini, Existence of equilibrium in a differential game of spatial competition with advertising. Reg. Sci. Urban Econ. 40 (2010) 155–160. | DOI

[8] J. Pang and K. H. Tan, Supply chain quality and pricing decisions under multi-manufacturer competition. Ind. Manag. Data Syst. 118 (2018) 164–187. | DOI

[9] M. L. Vidale and H. B. Wolfe, An operations-research study of sales response to advertising. Oper. Res. 5 (1957) 370–381. | MR | Zbl | DOI

[10] Y. J. Chen and J.-B. Sheu, Environmental-regulation pricing strategies for green supply chain management. Transp. Res. Part E Logist. Transp. Rev. 45 (2009) 667–677. | DOI

[11] A. Prasad and S. P. Sethi, Competitive advertising under uncertainty: a stochastic differential game approach. J. Optim. Theory App. 123 (2004) 163–185. | MR | Zbl | DOI

[12] G. E. Kimball, Some industrial applications of military operations research methods. Oper. Res. 5 (1957) 201. | MR | Zbl | DOI

[13] M. Chalikias and M. Skordoulis, Implementation of F.W. Lanchester’s combat model in a supply chain in duopoly: the case of Coca-Cola and Pepsi in Greece. Oper. Res. 17 (2017) 737–745.

[14] R. Jarrar, G. Martín-Herrán and G. Zaccour, Markov perfect equilibrium advertising strategies of Lanchester duopoly model: A technical note. Manag. Sci. 50 (2004) 995–1000. | Zbl | DOI

[15] H. N. Zhou, X. G. Gu and L. Li, The dynamic investment strategy of online advertising based on spillover effect in duopoly competition market. Computing 100 (2018) 881–905. | MR | Zbl | DOI

[16] F. Rossi, Lower price or higher reward? Measuring the effect of consumers’ preferences on reward programs. Manag. Sci. 64 (2017) 4451–4470. | DOI

[17] B.-D. Kim, M. Shi and K. Srinivasan, Reward programs and tacit collusion. Mark. Sci. 20 (2001) 99–120. | DOI

[18] S. S. Singh, D. C. Jain and T. V. Krishnan, Research note—Customer loyalty programs: Are they profitable? Manag. Sci. 54 (2008) 1205–1211. | DOI

[19] A. Gandomi and S. Zolfaghari, A stochastic model on the profitability of loyalty programs. Comput. Ind. Eng. 61 (2011) 482–488. | DOI

[20] J. Zhang and M. Wedel, The effectiveness of customized promotions in online and offline stores. J. Mark. Res. 46 (2009) 190–206. | DOI

[21] S. Lim and B. Lee, Loyalty programs and dynamic consumer preference in online markets. Decis. Support Syst. 78 (2015) 104–112. | DOI

[22] A. Bazargan, S. Karray and S. Zolfaghari, Modeling reward expiry for loyalty programs in a competitive market. Int. J. Prod. Econ. 193 (2017) 352–364. | DOI

[23] A. Nastasoiu and M. Vandenbosch, Competing with loyalty: How to design successful customer loyalty reward programs. Bus. Horiz. 62 (2019) 207–214. | DOI

[24] P. K. Chintagunta and D. Jain, A dynamic model of channel member strategies for marketing expenditures. Mark. Sci. 11 (1992) 168–188. | DOI

[25] J. Zhang, L. Lei, S. Zhang and L. Song, Dynamic vs. static pricing in a supply chain with advertising. Comput. Ind. Eng. 109 (2017) 266–279. | DOI

[26] S. P. Sethi, Deterministic and stochastic optimization of a dynamic advertising model. Optim. Control Appl. Methods 4 (1983) 179–184. | Zbl | DOI

[27] E. De Haan, P. C. Verhoef and T. Wiesel, The predictive ability of different customer feedback metrics for retention. Int. J. Res. Mark. 32 (2015) 195–206. | DOI

[28] O. S. Vaidya and S. Kumar, Analytic hierarchy process: An overview of applications. Eur. J. Oper. Res. 169 (2006) 1–29. | MR | Zbl | DOI

[29] V. Kumar, A. Lahiri and O. B. Dogan, A strategic framework for a profitable business model in the sharing economy. Ind. Mark. Manag. 69 (2018) 147–160. | DOI

[30] X. He, A. Krishnamoorthy, A. Prasad and S. P. Sethi, Retail competition and cooperative advertising. Oper. Res. Lett. 39 (2011) 11–16. | MR | Zbl | DOI

[31] X. He, A. Krishnamoorthy, A. Prasad and S. Sethi, Co-op advertising in dynamic retail oligopolies. Decis. Sci. 43 (2012) 71–103.

[32] R. W. Buell, D. Campbell and F. X. Frei, How do customers respond to increased service quality competition? Manuf. Serv. Oper. Manag. 18 (2016) 585–607. | DOI

[33] S. R. Balseiro and O. Candogan, Optimal contracts for intermediaries in online advertising. Oper. Res. 65 (2017) 878–896. | MR | Zbl | DOI

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