Dynamic treatment regimes (DTRs) are sequences of decision rules that recommend treatments based on patients’ time-varying clinical conditions. The sequential multiple assignment randomized trial (SMART) is an experimental design that can provide high-quality evidence for constructing optimal DTRs. In a SMART, participants are randomized to available treatments at multiple stages, typically following a fixed and balanced randomization procedure. Despite its relative simplicity of implementation and desirable performance in comparing embedded DTRs, the SMART with balanced randomization (SMART-BR) is faced with inevitable ethical issues including assigning many participants to the observed inferior treatment or the treatment they dislike, which might slow down the recruitment procedure and lead to higher attrition rates. In this context, we propose a SMART under the Experiment-as-Market framework (SMART-EXAM), a novel SMART design that holds the potential to improve patient welfare by incorporating participants’ preferences and predicted treatment effects into the randomization procedure. We describe the procedure of conducting a SMART-EXAM and evaluate its theoretical and empirical statistical properties compared with other competing SMART designs. The results indicate that the SMART-EXAM design can improve the welfare of participants enrolled in the trial, while also achieving a comparable ability to construct an optimal DTR. We finally illustrate the practical potential of the SMART-EXAM design using data from a SMART for children with attention-deficit/hyperactivity disorder (ADHD).