Researchers from Temple University, Tsinghua University, and Fudan University published a new paper in the Journal of Marketing that explores the business impact of PPI on buyers’ purchase behaviors and sellers’ sales activities.
The study, forthcoming in the Journal of Marketing, is titled “The Impact of Platform Protection Insurance on Buyers and Sellers in the Sharing Economy: A Natural Experiment” and is authored by Xueming Luo, Siliang Tong, Zhijie Lin, and Cheng Zhang. The research: (1) quantifies the impact of PPI in the sharing economy; (2) reveals buyer-side and seller-side responses to PPI; and (3) describes the role of the prior experiences of buyers and sellers.
The rise of the sharing economy has dramatically reshaped marketing thought and practice. The projected revenue from sharing accommodations and transportation alone will surpass $335 billion in 2025. The recent initial public offerings of Uber and Lyft exemplify this remarkable growth.
However, consumers continue to face high transaction uncertainty and purchase risks on sharing platforms, which host unbranded individual sellers offering products of mixed quality. Although most sharing platforms have review-based reputation systems, these systems are insufficient to fully eliminate consumer risks due to review bias, inflation, and manipulation on the platform. Therefore, major sharing economy players have adopted platform-level buyer protection insurance (PPI), which refers to a blanket safeguard program that provides buyers with insurance protection against product-quality failures caused by sellers on the platform.
Luo says, “We find that PPI significantly increases buyer spending and seller revenues, affirming the benefits of this service in the sharing economy. We also uncover multifaceted buyer-side and seller-side responses that enable such benefits.” PPI boosts buyer spending by increasing product orders and variety-seeking behavior among buyers. PPI boosts seller revenues by increasing customer retention and acquisition. Additional preliminary findings show that PPI does not increase adverse selection among buyers (i.e., buyers did not purchase more items from lower-quality sellers) or opportunistic behaviors among sellers (i.e., sellers did not raise their prices or receive more consumer complaints) in the short run. Further, the insurance benefits are amplified for buyers with worse prior experiences and sellers with shorter tenure on the platform, suggesting that PPI acts as a reputable quality signal to reduce transaction uncertainty and purchase risks on the sharing platform.
Tong adds that “Our research also offers useful and actionable implications for platform managers. Managers can use PPI to affect buyer and seller behaviors and subsequent business performance. Our findings suggest that PPI may nurture trust among consumers and boost sales transactions for sellers, which will improve the business performance of sharing platforms. Results on whether and how PPI affects the efficacy of sharing platforms also enable platform managers to better communicate and build a trusted relationship with external stakeholders to gain more institutional legitimacy from public-policymakers, raise funding from venture capital and stock markets, and boost platform reputation in news channel and social media.”
Furthermore, platform managers may craft more targeted communication strategies across different user segments to earn higher returns on PPI. For example, PPI has a stronger beneficial impact for buyers with worse prior experiences and for sellers with less experience on the platform. Thus, for more vulnerable customers with dire needs of protection in the marketplace, a targeted marketing message that emphasizes the risk-reduction benefit of PPI might offer a more effective signal to boost their purchase confidence on the sharing platform.
To justify sharing platforms’ investment on PPI, platform managers are often challenged to scientifically quantify the causal impact because randomized field experiments that protect some buyers through insurance but exclude others are unethical in the real world. Lin explains that “Our DID modelling with two-way fixed effects based on a natural experiment provides managers with a viable solution or toolbox to scientifically gauge the causal impact of insurance and other platform governance policies in the sharing economy.”
Full article and author contact information available at: https://doi.org/10.1177%2F0022242920962510
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