Blockchain Architecture for Demand Visibility: An Agent-Based Modeling Approach to Bullwhip Effect Reduction

The bullwhip effect—where demand variability amplifies upstream—continues to undermine supply chain coordination despite extensive research. Prior studies established that sharing customer demand information among all SC partners optimally mitigates the bullwhip effect, addressing the "what" and "with whom" factors of information sharing. However, the "how" factor—the technological mechanisms enabling information sharing—remains insufficiently explored. This study addresses this gap by proposing a permissioned blockchain architecture that enables end-to-end demand visibility through authenticated, immutable, and real-time demand sharing across SC echelons. Using agent-based modeling, we simulate a four-echelon serial SC under normally distributed customer demand N (100, 20) across 1,000 periods. Two scenarios are compared: (i) a conventional SC with no information sharing (NIS), where each echelon forecasts from downstream orders with compounding information lead time, and (ii) a BCT-enabled SC with complete demand information sharing (CDIS-BCT), where all echelons access verified CDI via a permissioned ledger with near-zero consensus delay. Results indicate that BCT-enabled demand visibility substantially reduces order variability, with the order variance ratio decreasing by 22% at the retailer, 75% at the distributor, and 89% at the producer. The retailer's reduction reflects the modeled lead time adjustment rather than expanded demand visibility. These findings advance the information sharing framework for the bullwhip effect mitigation by addressing the "how to share" factor, complementing established knowledge on optimal information type and partner configuration, and offer practical guidance for implementing permissioned blockchain architectures in multi-echelon SC coordination.