IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v215y2011i3p730-739.html
   My bibliography  Save this article

Optimizing referral reward programs under impression management considerations

Author

Listed:
  • Xiao, Ping
  • Tang, Christopher S.
  • Wirtz, Jochen

Abstract

We examine referral reward programs (RRP) that are intended for a service firm to encourage its current customers (inductors) to entice their friends (inductees) to purchase the firm's service. By considering the interplay among the firm, the inductor, and the inductee, we solve a "nested" Stackelberg game so as to determine the optimal RRP in equilibrium. We determine the conditions under which it is optimal for the firm to reward the inductor only, reward the inductee only, or reward both. Also, our results suggest that RRP dominates direct marketing when the firm's current market penetration or the inductor's referral effectiveness is sufficiently high. We then extend our model to incorporate certain key impression management factors: the inductor's intrinsic reward of making a positive impression by being seen as helping a friend, the inductor's concerns about creating a negative impression when making an incentivized referral, and the inductee's impression of the inductor's credibility when an incentive is involved. In the presence of these impression management factors, we show that the firm should reward the inductee more and the inductor less. Under certain conditions, it is optimal for the firm to reward neither the inductor nor the inductee so that the optimal RRP relies purely on unincentivized word of mouth.

Suggested Citation

  • Xiao, Ping & Tang, Christopher S. & Wirtz, Jochen, 2011. "Optimizing referral reward programs under impression management considerations," European Journal of Operational Research, Elsevier, vol. 215(3), pages 730-739, December.
  • Handle: RePEc:eee:ejores:v:215:y:2011:i:3:p:730-739
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377221711004905
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Eyal Biyalogorsky & Eitan Gerstner & Barak Libai, 2001. "Customer Referral Management: Optimal Reward Programs," Marketing Science, INFORMS, vol. 20(1), pages 82-95, August.
    2. Laura J. Kornish & Qiuping Li, 2010. "Optimal Referral Bonuses with Asymmetric Information: Firm-Offered and Interpersonal Incentives," Marketing Science, INFORMS, vol. 29(1), pages 108-121, 01-02.
    3. Amiya K. Basu & Rajiv Lal & V. Srinivasan & Richard Staelin, 1985. "Salesforce Compensation Plans: An Agency Theoretic Perspective," Marketing Science, INFORMS, vol. 4(4), pages 267-291.
    4. Ram C. Rao, 1990. "Compensating Heterogeneous Salesforces: Some Explicit Solutions," Marketing Science, INFORMS, vol. 9(4), pages 319-341.
    5. Fangruo Chen, 2000. "Sales-Force Incentives and Inventory Management," Manufacturing & Service Operations Management, INFORMS, vol. 2(2), pages 186-202, February.
    6. Brown, Jacqueline Johnson & Reingen, Peter H, 1987. "Social Ties and Word-of-Mouth Referral Behavior," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 14(3), pages 350-362, December.
    7. Fangruo Chen, 2005. "Salesforce Incentives, Market Information, and Production/Inventory Planning," Management Science, INFORMS, vol. 51(1), pages 60-75, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dan Zhou & Zhong Yao, 2015. "Optimal Referral Reward Considering Customer’s Budget Constraint," Future Internet, MDPI, vol. 7(4), pages 1-14, December.
    2. Kuester, Madlen & Benkenstein, Martin, 2014. "Turning dissatisfied into satisfied customers: How referral reward programs affect the referrer׳s attitude and loyalty toward the recommended service provider," Journal of Retailing and Consumer Services, Elsevier, vol. 21(6), pages 897-904.
    3. Heike M. Wolters & Christian Schulze & Karen Gedenk, 2020. "Referral Reward Size and New Customer Profitability," Marketing Science, INFORMS, vol. 39(6), pages 1166-1180, November.
    4. Berman, Barry, 2016. "Referral marketing: Harnessing the power of your customers," Business Horizons, Elsevier, vol. 59(1), pages 19-28.
    5. Lili Wang & Zoey Chen, 2022. "The effect of incentive structure on referral: the determining role of self-construal," Journal of the Academy of Marketing Science, Springer, vol. 50(5), pages 1091-1110, September.
    6. Li, Deng-Feng, 2012. "A fast approach to compute fuzzy values of matrix games with payoffs of triangular fuzzy numbers," European Journal of Operational Research, Elsevier, vol. 223(2), pages 421-429.
    7. East, Robert & Uncles, Mark D. & Romaniuk, Jenni & Hand, Chris, 2014. "The decay of positive and negative word of mouth after product experience," Australasian marketing journal, Elsevier, vol. 22(4), pages 350-355.
    8. Zhang, Xiaojing & Zhang, Yulin, 2024. "Content marketing in the social media platform: Examining the effect of content creation modes on the payoff of participants," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).
    9. Bazargan, Amirhossein & Karray, Salma & Zolfaghari, Saeed, 2018. "‘Buy n times, get one free’ loyalty cards: Are they profitable for competing firms? A game theoretic analysis," European Journal of Operational Research, Elsevier, vol. 265(2), pages 621-630.
    10. Wang, Ruibing & Wang, Qiao & Chiang, Wei-yu Kevin, 2024. "Optimal promotional mix and pricing when faced with uncertain product value," European Journal of Operational Research, Elsevier, vol. 313(2), pages 637-651.
    11. Söderlund, Magnus & Mattsson, Jan, 2015. "Merely asking the customer to recommend has an impact on word-of-mouth activity," Journal of Retailing and Consumer Services, Elsevier, vol. 27(C), pages 80-89.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lee, Chung-Yee & Yang, Ruina, 2013. "Compensation plan for competing salespersons under asymmetric information," European Journal of Operational Research, Elsevier, vol. 227(3), pages 570-580.
    2. Leon Yang Chu & Guoming Lai, 2013. "Salesforce Contracting Under Demand Censorship," Manufacturing & Service Operations Management, INFORMS, vol. 15(2), pages 320-334, May.
    3. Jian Chen & He Huang & Liming Liu & Hongyan Xu, 2021. "Price Delegation or Not? The Effect of Heterogeneous Sales Agents," Production and Operations Management, Production and Operations Management Society, vol. 30(5), pages 1350-1364, May.
    4. Panos Kouvelis & Duo Shi, 2020. "Who Should Compensate the Sales Agent in a Distribution Channel?," Production and Operations Management, Production and Operations Management Society, vol. 29(11), pages 2437-2460, November.
    5. Tinglong Dai & Kinshuk Jerath, 2013. "Salesforce Compensation with Inventory Considerations," Management Science, INFORMS, vol. 59(11), pages 2490-2501, November.
    6. Yang, Jian & Qi, Xiangtong, 2009. "On the design of coordinating contracts," International Journal of Production Economics, Elsevier, vol. 122(2), pages 581-594, December.
    7. Meyners, Jannik & Barrot, Christian & Becker, Jan U. & Bodapati, Anand V., 2017. "Reward-scrounging in customer referral programs," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 382-398.
    8. Wang, Ruibing & Wang, Qiao & Chiang, Wei-yu Kevin, 2024. "Optimal promotional mix and pricing when faced with uncertain product value," European Journal of Operational Research, Elsevier, vol. 313(2), pages 637-651.
    9. Lili Wang & Zoey Chen, 2022. "The effect of incentive structure on referral: the determining role of self-construal," Journal of the Academy of Marketing Science, Springer, vol. 50(5), pages 1091-1110, September.
    10. Terry A. Taylor, 2002. "Supply Chain Coordination Under Channel Rebates with Sales Effort Effects," Management Science, INFORMS, vol. 48(8), pages 992-1007, August.
    11. Long Gao, 2023. "Optimal Incentives for Salespeople with Learning Potential," Management Science, INFORMS, vol. 69(6), pages 3285-3296, June.
    12. Ariel BenYishay & A. Mushfiq Mobarak, 2014. "Social Learning and Communication," NBER Working Papers 20139, National Bureau of Economic Research, Inc.
    13. Inyoung Chae & Andrew T. Stephen & Yakov Bart & Dai Yao, 2017. "Spillover Effects in Seeded Word-of-Mouth Marketing Campaigns," Marketing Science, INFORMS, vol. 36(1), pages 89-104, January.
    14. Junhong Chu & Pradeep K. Chintagunta, 2009. "Quantifying the Economic Value of Warranties in the U.S. Server Market," Marketing Science, INFORMS, vol. 28(1), pages 99-121, 01-02.
    15. Dai, Yue & Chao, Xiuli, 2016. "Price delegation and salesforce contract design with asymmetric risk aversion coefficient of sales agents," International Journal of Production Economics, Elsevier, vol. 172(C), pages 31-42.
    16. Marty Stuebs & Li Sun, 2010. "Business Reputation and Labor Efficiency, Productivity, and Cost," Journal of Business Ethics, Springer, vol. 96(2), pages 265-283, October.
    17. Johannes Habel & Sascha Alavi & Nicolas Heinitz, 2023. "A theory of predictive sales analytics adoption," AMS Review, Springer;Academy of Marketing Science, vol. 13(1), pages 34-54, June.
    18. Williams, Martin & Buttle, Francis, 2011. "The Eight Pillars of WOM management: Lessons from a multiple case study," Australasian marketing journal, Elsevier, vol. 19(2), pages 85-92.
    19. Xiaoyang Long & Javad Nasiry, 2020. "Wage Transparency and Social Comparison in Sales Force Compensation," Management Science, INFORMS, vol. 66(11), pages 5290-5315, November.
    20. Yubo Chen & Jinhong Xie, 2008. "Online Consumer Review: Word-of-Mouth as a New Element of Marketing Communication Mix," Management Science, INFORMS, vol. 54(3), pages 477-491, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ejores:v:215:y:2011:i:3:p:730-739. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.