Brojeswar Pal

Purpose: The purpose of this study is to investigate the integration of additive manufacturing (AM) with traditional manufacturing (TM) in supply chains (SCNs), aiming to meet diverse customer needs, optimize production time and cost and enhance competitiveness in uncertain market environments. Design/methodology/approach: The authors develop a game-theoretic SCN model under uncertainty, focusing on two substitute products – one produced through TM and the other through AM. Customer demand depends on product quality and sales effort. They analyze centralized and decentralized decision-making across three scenarios: (1) production through TM only, (2) production through AM only, and (3) production through both TM and AM. The model is validated through numerical examples, and sensitivity analysis is conducted to examine the effects of key parameters on SCN profit. Findings: Results show that integrating AM with TM enhances operational efficiency and overall SCN profitability. While AM reduces unit production cost compared to TM, its installation cost may reduce profitability if it exceeds a critical threshold. Improved product quality and increased sales effort significantly boost profits, and accounting for demand uncertainty enables better alignment with customer preferences, leading to mutual gains for SCN members. Originality/value: This research is among the first to examine SCN decision-making by combining AM and TM under demand uncertainty using a game-theoretic framework. It offers theoretical insights into the conditions under which AM adoption is profitable and provides practical guidance for managers seeking to balance investment in AM with traditional practices for improved competitiveness and sustainability.

Purpose: This study investigates how financing structure and sustainability investment jointly influence pricing, service, and green decision-making in a dual-channel supply chain under demand uncertainty. It particularly examines how bank financing and trade credit shape firms' ability to improve environmental performance, strengthen channel competitiveness, and enhance customer value. Design/methodology/approach: A Stackelberg game-theoretic model is developed involving a manufacturer and a retailer who operate through both online and offline channels. The manufacturer invests in green innovation financed through bank borrowing, while the retailer chooses between bank financing with a wholesale price discount or trade credit with deferred payment. Demand is uncertain and influenced by green investment and retail service. A distribution-free approach is employed to derive robust equilibrium strategies without assuming a specific demand distribution. Findings: Results show that financing choices critically shape sustainability-oriented decisions and channel coordination. Trade credit encourages higher green investment and retail service when financing costs are high, whereas bank financing is more effective under lower borrowing rates and stronger discount incentives. Demand uncertainty substantially affects inventory and profitability, particularly under high-variance settings. The distribution-free framework enhances decision robustness under uncertain market environments. Originality/value: This study develops an integrated dual-channel supply chain framework combining green innovation, retail service, dual financing, and distribution-free demand modeling within a single analytical structure. It contributes to marketing intelligence by illustrating how financial structures and uncertainty jointly drive sustainable strategy formation and channel coordination. The findings provide actionable insights for managers seeking to align green innovation, retail service, and financing decisions to build competitive and sustainable supply chains.

Purpose: This study addresses critical challenges in inventory management, demand responsiveness and sustainability within modern supply chains. It investigates how lot-for-lot inventory policies, trade credit and cost-sharing can be integrated into a green closed-loop supply chain to enhance coordination, reduce costs and strengthen market responsiveness. The model explicitly links operational and financial strategies with marketing perspectives by incorporating consumer heterogeneity in green willingness-to-pay, retailer promotional tactics under trade credit and market segmentation effects, thereby connecting supply chain decisions to marketing intelligence, branding strategy and managerial practice. Design/methodology/approach: A two-echelon green closed-loop supply chain, comprising a manufacturer and retailer, is modeled. The manufacturer follows a continuous production process, and the retailer faces deterministic demand based on price and greening level. Returned products are screened and either remanufactured or disposed of. Three models are developed: a basic model, one with trade credit and another combining trade credit with cost sharing. These models are analyzed under centralized, Stackelberg and Nash scenarios, utilizing numerical simulations and sensitivity analysis to evaluate the outcomes. Findings: The results show that improving recycling efficiency enhances both environmental outcomes and profitability. Strategic trade credit terms improve cash flow coordination, while shipment frequency optimization reduces logistics and inventory costs. Cost-sharing mechanisms encourage greening efforts and demand, particularly in decentralized systems. Aligning sustainability initiatives with financial incentives fosters a balanced and competitive supply chain. Originality/value: This research uniquely integrates environmental, financial and strategic dimensions in a lot-for-lot green closed-loop supply chain. It offers practical insights into how coordination mechanisms influence sustainability and profitability in competitive supply chain environments. By explicitly connecting green investment, trade credit and cost-sharing strategies to marketing outcomes such as segmentation, positioning and brand value, the study advances interdisciplinary understanding at the interface of operations management and marketing intelligence.

The study investigates a dual-channel closed-loop supply chain with a product exchange offer, considering environmental awareness efforts. The manufacturer produces new and refurbished products using recycled used products. The forward channel considers price-sensitive competitive linear demands, and the reverse channel considers a sensitive collection rate, which includes buy-back prices and environmental awareness initiatives. The goal is to determine optimal environmental and economic decisions under centralized, manufacturer-Stackelberg, retailer-Stackelberg, and Nash game scenarios. A wholesale price-sharing contract is also introduced to explore channel coordination. The study’s findings provide practical insights into the optimal decisions and their implications for channel coordination. The study’s findings demonstrate that higher buy-back prices and increased environmental awareness levels have a positive impact on product recovery, benefiting the entire supply chain. The retailer-Stackelberg model emerges as the one with the highest demand for refurbished products, while the retailer achieves the highest individual profit in the wholesale price sharing contract model. The study also uncovers that the recovery rate of products from the retailer’s end remains consistent across all decentralized models. Furthermore, the study suggests that managing the cost associated with environmental awareness provision is crucial for maintaining optimal supply chain network efficiency.