Closed-loop supply chains have attracted more attention by researchers and practitioners due to strong government regulations, environmental issues, social responsibilities and natural resource constraints over past few years. This paper presents a mixed-integer linear programming model to design a closed-loop supply chain network and optimizing pricing policies under random disruption. Reusing the returned products is applied as a resilience strategy to cope with the waste of energy and improving supply efficiency. Moreover, it is necessary to find the optimal prices for both final and returned products. Therefore, the model is formulated based on demand function and it maximizes total supply chain’s profit. Finally, its application is explored through using the real data of an industrial company in glass industry.
PurposeThis work examines the joint pricing and ordering (JPO) decisions for a loss-averse retailer with quantity-oriented reference point (RP) effect under demand uncertainty.Design/methodology/approachThe demand is assumed to be uncertain with the mean and variance as the only known information. The prospect theory is used to model the retailer's expected utility. An expected utility maximization model in the distribution-free approach (DFA) is then developed. Using duality theory, the expected utility under the worst-case distribution is transformed into tractable piece-wise functions. To examine the effectiveness of the DFA in coping with the demand uncertainty, a stochastic programming model is developed and its solutions are used as benchmarks.FindingsThe proposed model and solution approach can effectively hedge against the demand uncertainty. The JPO decisions are significantly influenced by the LA coefficient and the reference level. The LA has a stronger influence than the reference level does on the expected utility. An excessive LA is detrimental while an appropriate reference level is beneficial to the retailer.Practical implicationsThe results of this work are applicable to loss-averse retailers with the quantity-oriented RP when making JPO decisions with difficulty in predicting the demands.Originality/valueThe demand is assumed to be uncertain in this work, but a certain demand distribution is usually assumed in the existing literature. The DFA is used to study JPO decisions for the loss-averse retailer with quantity-oriented RP effect under the uncertain demand.
Objectives: This paper constructs an analytic model for optimal pricing in which the interrelationship between the tobacco equipment and the optional value-added service supplied by tobacco equipment manufacturers are effectively depicted, and derives the closed-form solutions of
the optimal prices, which has previously been considered analytically intractable in the bundling problem of pricing two goods. The research reveals that when the marginal cost of the optional value-added service is 0 and the valuation of the service for tobacco manufacturing enterprises is
relatively low, it is advisable to adopt pure bundling pricing strategy; when the marginal cost of the service is 0 but the valuation of the service is relatively high, it is advisable to adopt separate pricing strategy; when the marginal cost of the service is greater than 0, separate pricing
strategy is always optimal. And it is interesting that, under separate pricing strategy, the higher valuation of the tobacco equipment leads to lower price for the service; the higher marginal cost of the service leads to higher price for the service, but lower price for the tobacco equipment.
This paper also proves that there are only two basic pricing strategies for tobacco equipment manufacturers: pure bundling pricing and separate pricing of the tobacco equipment and service.
PurposeThis paper investigates a dual-channel supply chain in which a manufacturer offers coupons in the online channel and the retailer in the offline channel. The optimal pricing and coupon promotion policies are explored, and the brand image under different promotion scenarios is studied.Design/methodology/approachThree differential game models, namely no coupon is offered, coupons offered by the manufacturer and coupons offered by the retailer, are constructed.FindingsThe results show that the manufacturer and retailer intend to conduct coupon promotions under a large coupon redemption rate. Coupon promotion derives a higher price and profit for the issuers, and the manufacturer can free-ride on the retailer's coupon promotion. The retailer's profit in the retailer-promotion scenario may be lower than that in the manufacturer-promotion scenario in some special conditions. Besides, price, coupon face value, brand image and profit increase over time. After multiple cycles game, the operational strategy evolves to an optimal equilibrium status.Originality/valueThis paper provides guidance and advice for dual-channel supply enterprises to implement joint pricing and coupon promotion strategies under multiple sales seasons.
This paper aims to develop a new bi-level game model for joint pricing and inventory decisions in a competitive supply chain consisting of a dominant manufacturer, who produces single perishable product from deteriorating raw materials, and two follower retailers who face nonlinear price-dependent demand and operate under Cournot assumptions. Three levels of warehousing including raw material warehouse, final product warehouse, and retail warehouses with exponential deterioration rates are considered to explore the joint impact of deterioration rate and price elasticity on the equilibrium inventory decisions. A Stackelberg-Nash-Cournot model is developed to seek the equilibrium prices, quantities, and replenishment cycles and is solved through an exact methodology. A numerical example is presented to validate the proposed model and comprehensive sensitivity analyses are carried out to measure the impact of the model’s key parameters including the deterioration rate in the producer’s and the retailers’ warehouses, the retail and competitor price elasticity, and the market scale on the equilibrium.
A joint pricing and network design model for a closed-loop supply chain under disruption (Glass Industry)
