• Previous Article
    Utility maximization with habit formation of interaction
  • JIMO Home
  • This Issue
  • Next Article
    Simulated annealing and genetic algorithm based method for a bi-level seru loading problem with worker assignment in seru production systems
doi: 10.3934/jimo.2020017

Fit revelation strategy in a supply chain with two types of consumers

School of Economics & Management, Shanghai Maritime University, 1550 Haigang Ave, Shanghai 201306, China

* Corresponding author: Jing Shi

Received  February 2019 Revised  August 2019 Published  January 2020

Fund Project: The author is supported in part by (ⅰ) the National Natural Science Foundation of China under Grants 71601111 and 71774109. (ⅱ)the Natural Science Foundation of Shanghai under Grant 18ZR1416900. (ⅲ) the Shanghai Key Basic Research Program under Grant 15590501800. (ⅳ) the Ministry of Education of Humanities and Social Science project under Grant 17YJCZH054.

This paper develops a game theoretical model for a supply chain consisting of one manufacturer and one retailer who chooses one of two strategies: implementing fit revelation or not implementing fit revelation. Firstly, the fit revelation strategy of the retailer in the decentralized supply chain is analyzed. When the market scale is medium, the fit revelation strategy is implementing fit revelation and only good-fit consumer will buy the product; otherwise, it is not implementing fit revelation. The results are counterintuitive because people may believe that it would be better to let consumers know more information about the product when the market scale is low. Implementing fit revelation is not always beneficial for consumers. When the market scale is sufficiently low, good-fit and bad-fit consumers both prefer not implementing fit revelation. Secondly, the paper also considers the case in which the manufacturer decides whether to implement fit revelation. Sometimes, the retailer and the manufacturer prefer themselves to facilitate fit revelation. Thirdly, the effect of decentralization is investigated. Numerical examples show that the interval in which implementing fit revelation is optimal is larger under the centralized setting than that under the decentralized setting. The decentralization decreases the probability to implement fit revelation.

Citation: Jing Shi. Fit revelation strategy in a supply chain with two types of consumers. Journal of Industrial & Management Optimization, doi: 10.3934/jimo.2020017
References:
[1]

H. Bar-IssacG. Caruana and V. Cuñat, Information gathering and marketing, Journal of Economics & Management Strategy, 19 (2010), 375-401.  doi: 10.2139/ssrn.1120858.  Google Scholar

[2]

Y. B. Chen and J. H. Xie, Online consumer review: Word-of-mouth as a new element of marketing communication mix, Management Science, 54 (2008), 477-491.  doi: 10.1287/mnsc.1070.0810.  Google Scholar

[3]

W. Y. K. ChiangD. Chhajed and J. D. Hess, Direct marketing, indirect profits: A strategic analysis of dual-channel supply-chain design, Management Science, 49 (2003), 1-20.  doi: 10.1287/mnsc.49.1.1.12749.  Google Scholar

[4]

L. Y. Chu and H. Zhang, Optimal preorder strategy with endogenous information control, Management Science, 57 (2011), 1055-1077.  doi: 10.1287/mnsc.1110.1335.  Google Scholar

[5]

L. DengJ. G. Zheng and R. J. Zhao, Manufacturer's quality disclosure strategy in a dual-channel supply chain considering the impact of information acquisition, Industrial Engineering and Management, 23 (2018), 1007-5429.   Google Scholar

[6]

C. DingK. H. Wang and S. Y. Lai, Channel coordination mechanism with retailers having fairness preference: An improved quantity discount mechanism, Journal of Industrial and Management Optimization, 9 (2013), 967-982.  doi: 10.3934/jimo.2013.9.967.  Google Scholar

[7]

S. J. Grossman, The informational role of warranties and private disclosure about product quality, Journal of Law and Economics, 24 (1981), 461-483.  doi: 10.1086/466995.  Google Scholar

[8]

Z. Y. Gu and Y. Xie, Facilitating fit revelation in the competitive market, Management Science, 59 (2013), 1196-1212.  doi: 10.1287/mnsc.1120.1594.  Google Scholar

[9]

L. Guo and Y. Zhao, Voluntary quality Disclosure and market interaction, Marketing Science, 28 (2009), 488-501.  doi: 10.2139/ssrn.1100956.  Google Scholar

[10]

V. J. Hotz and M. Xiao, Strategic information disclosure: The case of multiattribute products with heterogeneous consumers, Economic Inquiry, 51 (2013), 865-881.  doi: 10.1111/j.1465-7295.2010.00340.x.  Google Scholar

[11]

J. Johnson and D. P. Myatt, On the simple economics of advertising, marketing, and product design, The American Economic Review, 96 (2006), 756-784.  doi: 10.2139/ssrn.503182.  Google Scholar

[12]

D. Kuksov and Y. Lin, Information provision in a vertically differentiated competitive marketplace, Marketing Science, 29 (2010), 1-198.  doi: 10.1287/mksc.1090.0486.  Google Scholar

[13]

X. LiY. J. Li and X. Q. Cai, Double marginalization and coordination in the supply chain with uncertain supply, European Journal of Operational Research, 226 (2013), 228-236.  doi: 10.1016/j.ejor.2012.10.047.  Google Scholar

[14]

O. Loginova and C. R. Taylor, Price experimentation with strategic buyers, Review of Economic Design, 12 (2008), 165-187.  doi: 10.1007/s10058-008-0048-5.  Google Scholar

[15]

M. L. Luo and G. Li, Cross-channel consumers return in a multi-channel supply chain, Operations Research and Management Science, 28 (2019), 16-22.   Google Scholar

[16]

P. R. Milgrom, Good news and bad news: Representation theorems and applications, The Bell Journal of Economics, 12 (1981), 380-391.  doi: 10.2307/3003562.  Google Scholar

[17]

S. Moorthy and S. A. Hawkins, Advertising repetition and quality perception, Journal of Business Research, 58 (2005), 354-360.  doi: 10.1016/S0148-2963(03)00108-5.  Google Scholar

[18]

J. Noll, Comparing quality signals as tools of consumer protection: Are warranties always better than advertisements to promote higher product quality?, International Review of Law and Economics, 24 (2004), 227-239.  doi: 10.1016/j.irle.2004.08.007.  Google Scholar

[19]

E. OfekZ. Katona and M. Sarvary, Bricks and clicks: The impact of product returns on the strategies of multi channel retailers, Marketing Science, 30 (2011), 1-194.  doi: 10.1287/mksc.1100.0588.  Google Scholar

[20]

D. Purohit and J. Srivastava, Effect of manufacturer reputation, retailer reputation, and product warranty on consumer judgments of product quality: A cue diagnosticity framework, Journal of Consumer Psychology, 10 (2001), 123-134.  doi: 10.1207/s15327663jcp1003_1.  Google Scholar

[21]

E. Schmidbauer and A. Stock, Quality signaling via strikethrough prices, International Journal of Research in Marketing, 35 (2018), 524-532.  doi: 10.1016/j.ijresmar.2018.03.005.  Google Scholar

[22]

J. Shi and T. J. Xiao, Service investment and consumer returns policy in a vendor-managed inventory supply chain, Journal of Industrial and Management Optimization, 11 (2015), 439-459.  doi: 10.3934/jimo.2015.11.439.  Google Scholar

[23]

J. StockT. Spek and H. Shear, Managing product returns for competitive advantage, MIT Sloan Management Review, 48 (2006), 57-62.   Google Scholar

[24]

M. Sun, Disclosing multiple product attributes, Journal of Economics & Management Strategy, 20 (2011), 195-224.  doi: 10.1111/j.1530-9134.2010.00287.x.  Google Scholar

[25]

T. J. XiaoT.-M. Choi and T. C. E. Cheng, Product variety and channel structure strategy for a retailer-Stackelberg supply chain, European Journal of Operational Research, 233 (2014), 114-124.  doi: 10.1016/j.ejor.2013.08.038.  Google Scholar

[26]

T. ZhangG. LiK. K. Lai and J. W. K. Leung, Information disclosure strategies for the intermediary and competitive sellers, European Journal of Operational Research, 271 (2018), 1156-1173.  doi: 10.1016/j.ejor.2018.06.037.  Google Scholar

[27]

X. M. Zhang and L. Jin, Pricing and contract design of supply chain under money-back guarantees offered by the online retailer, Forcasting, 37 (2018), 74-80.   Google Scholar

show all references

References:
[1]

H. Bar-IssacG. Caruana and V. Cuñat, Information gathering and marketing, Journal of Economics & Management Strategy, 19 (2010), 375-401.  doi: 10.2139/ssrn.1120858.  Google Scholar

[2]

Y. B. Chen and J. H. Xie, Online consumer review: Word-of-mouth as a new element of marketing communication mix, Management Science, 54 (2008), 477-491.  doi: 10.1287/mnsc.1070.0810.  Google Scholar

[3]

W. Y. K. ChiangD. Chhajed and J. D. Hess, Direct marketing, indirect profits: A strategic analysis of dual-channel supply-chain design, Management Science, 49 (2003), 1-20.  doi: 10.1287/mnsc.49.1.1.12749.  Google Scholar

[4]

L. Y. Chu and H. Zhang, Optimal preorder strategy with endogenous information control, Management Science, 57 (2011), 1055-1077.  doi: 10.1287/mnsc.1110.1335.  Google Scholar

[5]

L. DengJ. G. Zheng and R. J. Zhao, Manufacturer's quality disclosure strategy in a dual-channel supply chain considering the impact of information acquisition, Industrial Engineering and Management, 23 (2018), 1007-5429.   Google Scholar

[6]

C. DingK. H. Wang and S. Y. Lai, Channel coordination mechanism with retailers having fairness preference: An improved quantity discount mechanism, Journal of Industrial and Management Optimization, 9 (2013), 967-982.  doi: 10.3934/jimo.2013.9.967.  Google Scholar

[7]

S. J. Grossman, The informational role of warranties and private disclosure about product quality, Journal of Law and Economics, 24 (1981), 461-483.  doi: 10.1086/466995.  Google Scholar

[8]

Z. Y. Gu and Y. Xie, Facilitating fit revelation in the competitive market, Management Science, 59 (2013), 1196-1212.  doi: 10.1287/mnsc.1120.1594.  Google Scholar

[9]

L. Guo and Y. Zhao, Voluntary quality Disclosure and market interaction, Marketing Science, 28 (2009), 488-501.  doi: 10.2139/ssrn.1100956.  Google Scholar

[10]

V. J. Hotz and M. Xiao, Strategic information disclosure: The case of multiattribute products with heterogeneous consumers, Economic Inquiry, 51 (2013), 865-881.  doi: 10.1111/j.1465-7295.2010.00340.x.  Google Scholar

[11]

J. Johnson and D. P. Myatt, On the simple economics of advertising, marketing, and product design, The American Economic Review, 96 (2006), 756-784.  doi: 10.2139/ssrn.503182.  Google Scholar

[12]

D. Kuksov and Y. Lin, Information provision in a vertically differentiated competitive marketplace, Marketing Science, 29 (2010), 1-198.  doi: 10.1287/mksc.1090.0486.  Google Scholar

[13]

X. LiY. J. Li and X. Q. Cai, Double marginalization and coordination in the supply chain with uncertain supply, European Journal of Operational Research, 226 (2013), 228-236.  doi: 10.1016/j.ejor.2012.10.047.  Google Scholar

[14]

O. Loginova and C. R. Taylor, Price experimentation with strategic buyers, Review of Economic Design, 12 (2008), 165-187.  doi: 10.1007/s10058-008-0048-5.  Google Scholar

[15]

M. L. Luo and G. Li, Cross-channel consumers return in a multi-channel supply chain, Operations Research and Management Science, 28 (2019), 16-22.   Google Scholar

[16]

P. R. Milgrom, Good news and bad news: Representation theorems and applications, The Bell Journal of Economics, 12 (1981), 380-391.  doi: 10.2307/3003562.  Google Scholar

[17]

S. Moorthy and S. A. Hawkins, Advertising repetition and quality perception, Journal of Business Research, 58 (2005), 354-360.  doi: 10.1016/S0148-2963(03)00108-5.  Google Scholar

[18]

J. Noll, Comparing quality signals as tools of consumer protection: Are warranties always better than advertisements to promote higher product quality?, International Review of Law and Economics, 24 (2004), 227-239.  doi: 10.1016/j.irle.2004.08.007.  Google Scholar

[19]

E. OfekZ. Katona and M. Sarvary, Bricks and clicks: The impact of product returns on the strategies of multi channel retailers, Marketing Science, 30 (2011), 1-194.  doi: 10.1287/mksc.1100.0588.  Google Scholar

[20]

D. Purohit and J. Srivastava, Effect of manufacturer reputation, retailer reputation, and product warranty on consumer judgments of product quality: A cue diagnosticity framework, Journal of Consumer Psychology, 10 (2001), 123-134.  doi: 10.1207/s15327663jcp1003_1.  Google Scholar

[21]

E. Schmidbauer and A. Stock, Quality signaling via strikethrough prices, International Journal of Research in Marketing, 35 (2018), 524-532.  doi: 10.1016/j.ijresmar.2018.03.005.  Google Scholar

[22]

J. Shi and T. J. Xiao, Service investment and consumer returns policy in a vendor-managed inventory supply chain, Journal of Industrial and Management Optimization, 11 (2015), 439-459.  doi: 10.3934/jimo.2015.11.439.  Google Scholar

[23]

J. StockT. Spek and H. Shear, Managing product returns for competitive advantage, MIT Sloan Management Review, 48 (2006), 57-62.   Google Scholar

[24]

M. Sun, Disclosing multiple product attributes, Journal of Economics & Management Strategy, 20 (2011), 195-224.  doi: 10.1111/j.1530-9134.2010.00287.x.  Google Scholar

[25]

T. J. XiaoT.-M. Choi and T. C. E. Cheng, Product variety and channel structure strategy for a retailer-Stackelberg supply chain, European Journal of Operational Research, 233 (2014), 114-124.  doi: 10.1016/j.ejor.2013.08.038.  Google Scholar

[26]

T. ZhangG. LiK. K. Lai and J. W. K. Leung, Information disclosure strategies for the intermediary and competitive sellers, European Journal of Operational Research, 271 (2018), 1156-1173.  doi: 10.1016/j.ejor.2018.06.037.  Google Scholar

[27]

X. M. Zhang and L. Jin, Pricing and contract design of supply chain under money-back guarantees offered by the online retailer, Forcasting, 37 (2018), 74-80.   Google Scholar

Figure 1.  The profit of each member when different members facilitate fit revelation
Figure 2.  The upper bound and lower bound versus the proportion of bad-fit consumer
Figure 3.  The upper bound and lower bound versus the loss of bad-fit consumer
[1]

Tinggui Chen, Yanhui Jiang. Research on operating mechanism for creative products supply chain based on game theory. Discrete & Continuous Dynamical Systems - S, 2015, 8 (6) : 1103-1112. doi: 10.3934/dcdss.2015.8.1103

[2]

Yeong-Cheng Liou, Siegfried Schaible, Jen-Chih Yao. Supply chain inventory management via a Stackelberg equilibrium. Journal of Industrial & Management Optimization, 2006, 2 (1) : 81-94. doi: 10.3934/jimo.2006.2.81

[3]

Amin Aalaei, Hamid Davoudpour. Two bounds for integrating the virtual dynamic cellular manufacturing problem into supply chain management. Journal of Industrial & Management Optimization, 2016, 12 (3) : 907-930. doi: 10.3934/jimo.2016.12.907

[4]

Jun Li, Hairong Feng, Kun-Jen Chung. Using the algebraic approach to determine the replenishment optimal policy with defective products, backlog and delay of payments in the supply chain management. Journal of Industrial & Management Optimization, 2012, 8 (1) : 263-269. doi: 10.3934/jimo.2012.8.263

[5]

Ali Naimi Sadigh, S. Kamal Chaharsooghi, Majid Sheikhmohammady. A game theoretic approach to coordination of pricing, advertising, and inventory decisions in a competitive supply chain. Journal of Industrial & Management Optimization, 2016, 12 (1) : 337-355. doi: 10.3934/jimo.2016.12.337

[6]

Jiuping Xu, Pei Wei. Production-distribution planning of construction supply chain management under fuzzy random environment for large-scale construction projects. Journal of Industrial & Management Optimization, 2013, 9 (1) : 31-56. doi: 10.3934/jimo.2013.9.31

[7]

Lianju Sun, Ziyou Gao, Yiju Wang. A Stackelberg game management model of the urban public transport. Journal of Industrial & Management Optimization, 2012, 8 (2) : 507-520. doi: 10.3934/jimo.2012.8.507

[8]

David W. K. Yeung, Yingxuan Zhang, Hongtao Bai, Sardar M. N. Islam. Collaborative environmental management for transboundary air pollution problems: A differential levies game. Journal of Industrial & Management Optimization, 2019  doi: 10.3934/jimo.2019121

[9]

Juliang Zhang, Jian Chen. Information sharing in a make-to-stock supply chain. Journal of Industrial & Management Optimization, 2014, 10 (4) : 1169-1189. doi: 10.3934/jimo.2014.10.1169

[10]

Juliang Zhang. Coordination of supply chain with buyer's promotion. Journal of Industrial & Management Optimization, 2007, 3 (4) : 715-726. doi: 10.3934/jimo.2007.3.715

[11]

Feimin Zhong, Wei Zeng, Zhongbao Zhou. Mechanism design in a supply chain with ambiguity in private information. Journal of Industrial & Management Optimization, 2020, 16 (1) : 261-287. doi: 10.3934/jimo.2018151

[12]

Na Song, Ximin Huang, Yue Xie, Wai-Ki Ching, Tak-Kuen Siu. Impact of reorder option in supply chain coordination. Journal of Industrial & Management Optimization, 2017, 13 (1) : 449-475. doi: 10.3934/jimo.2016026

[13]

Liping Zhang. A nonlinear complementarity model for supply chain network equilibrium. Journal of Industrial & Management Optimization, 2007, 3 (4) : 727-737. doi: 10.3934/jimo.2007.3.727

[14]

Joseph Geunes, Panos M. Pardalos. Introduction to the Special Issue on Supply Chain Optimization. Journal of Industrial & Management Optimization, 2007, 3 (1) : i-ii. doi: 10.3934/jimo.2007.3.1i

[15]

Jia Shu, Jie Sun. Designing the distribution network for an integrated supply chain. Journal of Industrial & Management Optimization, 2006, 2 (3) : 339-349. doi: 10.3934/jimo.2006.2.339

[16]

Jun Pei, Panos M. Pardalos, Xinbao Liu, Wenjuan Fan, Shanlin Yang, Ling Wang. Coordination of production and transportation in supply chain scheduling. Journal of Industrial & Management Optimization, 2015, 11 (2) : 399-419. doi: 10.3934/jimo.2015.11.399

[17]

Eduardo Espinosa-Avila, Pablo Padilla Longoria, Francisco Hernández-Quiroz. Game theory and dynamic programming in alternate games. Journal of Dynamics & Games, 2017, 4 (3) : 205-216. doi: 10.3934/jdg.2017013

[18]

Astridh Boccabella, Roberto Natalini, Lorenzo Pareschi. On a continuous mixed strategies model for evolutionary game theory. Kinetic & Related Models, 2011, 4 (1) : 187-213. doi: 10.3934/krm.2011.4.187

[19]

Anna Lisa Amadori, Astridh Boccabella, Roberto Natalini. A hyperbolic model of spatial evolutionary game theory. Communications on Pure & Applied Analysis, 2012, 11 (3) : 981-1002. doi: 10.3934/cpaa.2012.11.981

[20]

K. F. C. Yiu, L. L. Xie, K. L. Mak. Analysis of bullwhip effect in supply chains with heterogeneous decision models. Journal of Industrial & Management Optimization, 2009, 5 (1) : 81-94. doi: 10.3934/jimo.2009.5.81

2019 Impact Factor: 1.366

Metrics

  • PDF downloads (75)
  • HTML views (292)
  • Cited by (0)

Other articles
by authors

[Back to Top]