Interactive signaling grouping strategies and long-tail effects in E-commerce platform contexts

Purpose This study aims to explore the complex driving mechanisms of bilateral platform interaction signals on consumer shopping behavior, reveal consumer response strategies to interaction signals, improve platform recommendation algorithms and service efficiency, expand merchant marketing strategies and enhance consumer information utility and satisfaction. Design/methodology/approach Based on the Elaboration Likelihood Model (ELM), the signal entities of a two-sided platform are categorized into merchants, consumers and the platform itself. A configuration strategy research model is constructed to guide consumer decision-making. First, using product exposure, click and transaction data from 64,184 users, a pre-experiment explores the interactive effects of price, review value and supplier certification to validate the existence of interactive signal configuration effects. Additionally, the Fuzzy-set Qualitative Comparative Analysis (fsQCA) method is employed to investigate the synergistic and long-tail effects of interactive signals on consumer browsing and purchasing behavior. Findings Exploratory research has found that multi-party interaction signals have substitution and complementary effects, and their configuration strategies exhibit asymmetry, equivalence and marginal characteristics. In addition, based on the screening of consumer groups with low browsing but high purchasing, this study proposes specific signal configuration strategies for long-tail groups. Originality/value This study constructs an integrated interpretive framework for interactive signal configurations, employing a mixed-method approach combining regression analysis to test interactive effects and fsQCA to analyze configuration patterns, thereby overcoming the limitations of studies focused on single signals or stages. Theoretically, this framework expands the application of signal theory in interactive scenarios, refines the signal mechanisms underlying two-stage decision-making under the ELM and connects curiosity-driven and cognitive load theories to explain long-tail group behavior. Practically, the proposed configuration strategies can reduce platform resource redundancy, provide new pathways for long-tail market operations and enhance marketing precision and decision-making efficiency.