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The development of technologies such as the Internet of Things has transformed traditional physical products into smart connected products (SCPs) that combine hardware, sensors, data storage, microprocessors, software, and connectivity in myriad ways. SCPs raise a new set of strategic choices for creating value and pricing products, how relationships with business partners such as channels are redefined, and what role companies should play as industry boundaries are expanded. This study develops an inventory model that considers optimal pricing, production, and intelligent policies for SCPs. In this model, customer demand is assumed to increase as the selling price decreases and the effort to improve product intelligence (i.e., intelligent effort) increases. In addition, a two-level trade credit is included in the SCPs supply chain channel. The manufacturer often receives a permissible delay-in-payment (trade credit) from the supplier while also offering a delayed payment to end customers to attract more sales. Trade credit is particularly important for SCPs as it can act as a payment plan to reduce the product's price barrier. This study aims to determine the optimal selling price, lot size, and level of intelligent effort while maximizing the manufacturer's profit under a two-level trade credit. The optimal solution is clarified, numerical examples are provided, and a sensitivity analysis is performed to illustrate the theoretical results and solution approach. The results reveal that considering the level of intelligent effort as a decision can benefit the manufacturer. Notably, as the intelligent effort coefficient increases by 55%, the total profit increases by 65.8%. [ABSTRACT FROM AUTHOR]

We explore the supply chain network design problem for a retailer selling perishable products when the supplier provides trade credit and the deterioration rate can be reduced by freshness-keeping effort. Using a continuous approximation model, we derive the total cost of the supply chain, including facility set up and operation cost, ordering cost, freshness keeping cost, transportation cost, inventory-holding cost, and interest cost of trade credit. We prove the convexity of the total cost functions and derive the closed-form solutions of the decision variables, including the service regions of distribution centers, the replenishment cycle time, and the fresh food freshness keeping effort. Finally, we conclude with some managerial insights from the numerical analysis. [ABSTRACT FROM AUTHOR]

We develop an economic production quantity model on the basis of radio frequency identification (RFID) adoption, trade credit, and reworking of imperfect products. We determine the optimal values of production cycle time and RFID investment levels for ordering, just-in-time, and operating efficiencies. On the basis of the relationship between the demand and reworking rates, we classify the model into two cases. Furthermore, on the basis of the relationship between production cycle time and credit period, we divide each case into four subcases. We derive the total manufacturing cost for the subcases and develop an algorithm to solve the four-branch piecewise nonlinear problem. Finally, we illustrate the solution approach and perform numerical analyses to discuss the influences of system parameters on decisions. [ABSTRACT FROM AUTHOR]