This study examines how multichannel digital information environments shape user decision-making in disposition-prone contexts within China's T+1 market. Grounded in coping theory and dual-system theory, we specify how channel attributes—issuer disclosures, third-party analyses, social networks, and artificial intelligence (AI)-based tools—affect decision quality through problem- and emotion-focused coping.
We adopt an exploratory sequential mixed-methods design. Study 1 develops the framework through grounded theory interviews with experienced Chinese investors who use digital trading platforms. Study 2 tests the dual-path model with a survey (N = 713) analyzed using partial least squares structural equation modeling (PLS-SEM) to evaluate how information quality, information overload, and channel-specific cues transmit effects to decision quality through the two coping routes.
Information quality strengthens both coping routes, while information overload weakens them. In social channels, perceived infollution reduces emotion regulation, whereas informational influence enhances analytic engagement. In AI channels, social influence and perceived technology acceptability reinforce both routes, while perceived algorithmic bias is nonsignificant. Mediation analyses confirm that problem- and emotion-focused coping jointly transmit channel effects to decision quality in a regulated, time-lagged market.
This paper integrates coping theory with information systems research by articulating a process-level, dual-path mechanism linking multichannel digital information and decision quality in T+1 setting. It advances technostress/information-behavior work by separating channel attributes (quality, load, social and AI cues) from coping responses. Furthermore, it extends prior single-channel studies by situating dual coping in an emerging digital market.
