Optimal pricing strategy in live streaming sales with blockchain traceability

Abstract

As live streaming transforms the automotive sector, sellers are adopting blockchain to ensure verifiable transparency and traceability with consumer data collection. In this process, each transaction generates consumer data with a monetizable unit value. In this study, we analyze how the interaction between live streaming and blockchain shapes supply chain profits and market demand. Three settings are considered: baseline, live only, and live plus blockchain, and the equilibrium is solved to compare outcomes. We examine stakeholder strategies and derive several findings by combining Stackelberg and Nash frameworks. First, as the per-transaction unit value of consumer interaction and transaction data rises, both demand and monetization increase in the basic and live streaming settings. However, only under live streaming do optimal retail prices fall with better matching, and profit allocation hinges on brand differentiation. Second, live streaming reshapes retailer economics. When brands are highly differentiated, higher data value compresses retail margins and lowers optimal service intensity, whereas when brands are similar, it raises retail profit and supports stronger live service inputs. Third, adding blockchain creates a data‑value threshold for pricing and profit leadership. In dual‑chain markets, gains tilt toward higher‑awareness products. Manufacturers of higher‑awareness goods often earn more under live plus blockchain, while platforms prefer pure live unless trust frictions dominate. Overall, as data value rises the equilibrium tilts toward higher brand awareness products, with wholesale prices and profits increasing for the leading brand and retail prices of both products declining under live settings. Managerially, align pricing, service intensity, and tech choice with the binding constraint of personalization versus trust.