Supply Chain Optimization Using Buy-Now-Pay-Later

With the increasing adoption of Buy Now, Pay Later (BNPL) payment systems, customer demand has risen significantly, particularly among younger customers. However, other key players in the supply chain, such as retailers and BNPL providers, face challenges in offering this payment option. Retailers suffer losses as a result of supplementary fees, and BNPL providers face the risk of customer default. To address these issues, this research develops a pricing model to optimize the selling price, maximizing retailer profit and BNPL provider revenue. The model incorporates key variables, including sales and service fees, transaction fees, and production costs, while factoring in demand rate, selling price, and the customer's maximum capacity to pay. Utilizing non-linear optimization through Mathematica and generating trend graphs with Python, we identify the optimal solution and provide managerial insights. The finding reveals that retailers and BNPL providers can achieve higher profitability with BNPL payments compared to general payment methods by strategically setting higher prices to support BNPL transactions. Retailers absorb the initial fees for customers choosing BNPL, allowing them to benefit from increased sales. Meanwhile, BNPL providers can further increase their revenue by adjusting interest rates or fees, setting their effective selling price slightly higher than retailers to account for the risk of covering product costs during the installment period. Moreover, progressively aligning the selling price closer to optimal values amplifies profitability for both players under BNPL. Finally, by addressing the needs of young customers with declining capacity to pay, retailers and BNPL providers offer more spending options and develop pricing strategies, delivering benefits across the entire supply chain.