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A product strategy for daily deal campaigns utilizing demand expansion and consumer leakage

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  • Yao Tang

    (School of Business Administration, Zhongnan University of Economics and Law)

Abstract

Daily deal campaigns help local service merchants expand their market demand, which also result in consumer leakage concerns. This paper investigates how to exercise product strategies, i.e., price and quality decisions, for daily deal campaigns through a systematic exploration of demand expansion and consumer leakage. We consider a local service merchant who currently sells a product in his or her local market and who might contract with a platform to introduce daily deal campaigns. We document how the demand expansion and consumer leakage effects jointly affect a merchant’s product strategy. Particularly, we find it not always profitable to introduce daily deal campaigns amid relatively low levels of the demand expansion effect. Moreover, a merchant should adopt the product strategy of overlooking (inhibiting) consumer leakage amid relatively low (high) levels of the consumer leakage effect. In addition, we discuss the strategic role of a platform’s agency fees on leveraging a merchant’s product strategy. Based on this, we take a platform’s perspective to examine how to establish optimal agency fees amid various market conditions. Our results provide useful insights for firms in the daily deal business on how to carry out more intelligent marketing strategies. Our conclusions also cater to other businesses, wherein offline merchants could adopt online platforms to expand their demand while addressing the issue of consumer leakage.

Suggested Citation

  • Yao Tang, 2023. "A product strategy for daily deal campaigns utilizing demand expansion and consumer leakage," Electronic Commerce Research, Springer, vol. 23(3), pages 1861-1883, September.
  • Handle: RePEc:spr:elcore:v:23:y:2023:i:3:d:10.1007_s10660-021-09519-3
    DOI: 10.1007/s10660-021-09519-3
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    References listed on IDEAS

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    1. Upender Subramanian & Ram C. Rao, 2016. "Leveraging Experienced Consumers to Attract New Consumers: An Equilibrium Analysis of Displaying Deal Sales by Daily Deal Websites," Management Science, INFORMS, vol. 62(12), pages 3555-3575, December.
    2. Mantian (Mandy) Hu & Chu (Ivy) Dang & Pradeep K. Chintagunta, 2019. "Search and Learning at a Daily Deals Website," Marketing Science, INFORMS, vol. 38(4), pages 609-642, July.
    3. Kukar-Kinney, Monika & Xia, Lan, 2017. "The effectiveness of number of deals purchased in influencing consumers' response to daily deal promotions: A cue utilization approach," Journal of Business Research, Elsevier, vol. 79(C), pages 189-197.
    4. J. Miguel Villas-Boas, 2004. "Communication Strategies and Product Line Design," Marketing Science, INFORMS, vol. 23(3), pages 304-316, January.
    5. (Catherine) Zhang, Jie & Savage, Scott J. & Chen, Yongmin, 2015. "Consumer uncertainty and price discrimination through online coupons: An empirical study of restaurants in Shanghai," Information Economics and Policy, Elsevier, vol. 33(C), pages 43-55.
    6. Liang Guo & Juanjuan Zhang, 2012. "Consumer Deliberation and Product Line Design," Marketing Science, INFORMS, vol. 31(6), pages 995-1007, November.
    7. Kukar-Kinney, Monika & Scheinbaum, Angeline Close & Schaefers, Tobias, 2016. "Compulsive buying in online daily deal settings: An investigation of motivations and contextual elements," Journal of Business Research, Elsevier, vol. 69(2), pages 691-699.
    8. Mussa, Michael & Rosen, Sherwin, 1978. "Monopoly and product quality," Journal of Economic Theory, Elsevier, vol. 18(2), pages 301-317, August.
    9. Zike Cao & Kai-Lung Hui & Hong Xu, 2018. "When Discounts Hurt Sales: The Case of Daily-Deal Markets," Information Systems Research, INFORMS, vol. 29(3), pages 567-591, September.
    10. Ming Zhao & Yulan Wang & Xianghua Gan, 2016. "Signalling effect of daily deal promotion for a start-up service provider," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 67(2), pages 280-293, February.
    11. Chakravarthi Narasimhan, 1984. "A Price Discrimination Theory of Coupons," Marketing Science, INFORMS, vol. 3(2), pages 128-147.
    12. Serguei Netessine & Terry A. Taylor, 2007. "Product Line Design and Production Technology," Marketing Science, INFORMS, vol. 26(1), pages 101-117, 01-02.
    13. J. Miguel Villas-Boas, 1998. "Product Line Design for a Distribution Channel," Marketing Science, INFORMS, vol. 17(2), pages 156-169.
    14. Tang, Yao & Chen, Rachel R. & Guan, Xu, 2021. "Daily-deal market with consumer retention: Price discrimination or quality differentiation," Omega, Elsevier, vol. 102(C).
    15. Chenxu Ke & Bo Yan & Ruofan Xu, 2017. "A group-buying mechanism for considering strategic consumer behavior," Electronic Commerce Research, Springer, vol. 17(4), pages 721-752, December.
    16. Tong Che & Zeyu Peng & Zhongsheng Hua, 2016. "Characteristics of online group-buying website and consumers intention to revisit: the moderating effects of visit channels," Electronic Commerce Research, Springer, vol. 16(2), pages 171-188, June.
    17. Ming Hu & Xi Li & Mengze Shi, 2015. "Product and Pricing Decisions in Crowdfunding," Marketing Science, INFORMS, vol. 34(3), pages 331-345, May.
    18. Lingling Zhang & Doug J. Chung, 2020. "Price Bargaining and Competition in Online Platforms: An Empirical Analysis of the Daily Deal Market," Marketing Science, INFORMS, vol. 39(4), pages 687-706, July.
    19. K. Sridhar Moorthy, 1984. "Market Segmentation, Self-Selection, and Product Line Design," Marketing Science, INFORMS, vol. 3(4), pages 288-307.
    20. Song, Minjae & Park, Eunho & Yoo, Byungjoon & Jeon, Seongmin, 2016. "Is the Daily Deal Social Shopping?: An Empirical Analysis of Customer Panel Data," Journal of Interactive Marketing, Elsevier, vol. 33(C), pages 57-76.
    21. Simone Marinesi & Karan Girotra & Serguei Netessine, 2018. "The Operational Advantages of Threshold Discounting Offers," Management Science, INFORMS, vol. 64(6), pages 2690-2708, June.
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