Impacts of demand uncertainty on retailer's dominance and manufacturer-retailer supply chain cooperation

Recent studies in marketing and distribution channels have shown that the balance of power between manufacturers and retailers is shifting. Based on this observation, we investigate a two-echelon supply chain with a manufacturer and a retailer in this paper. We first develop retailer-dominant non-cooperative game models by introducing a sensitivity of retailer's order quantity to manufacturer's wholesale price; then we analyze two cooperative scenarios, in which the Nash bargaining model is utilized to implement profit sharing between the manufacturer and the retailer. Under the assumption that the manufacturer and the retailer are risk-neutral, we find that the manufacturer and the retailer can bargain to cooperate at any level of retail-market demand uncertainty with exogenous retail price. However, the cooperation is conditional on retail-market demand uncertainty with endogenous retail price: it can be implemented if the fluctuation of retail-market demand is relatively small, and the measure of retail-market demand uncertainty does not exceed an upper bound. Theoretical and numerical analyses show that the retailer's dominance over the manufacturer increases with the increase in the sensitivity of retailer's order quantity to manufacturer's wholesale price under a limitation of retail-market demand uncertainty. Numerical analyses also show that the retailer's dominance decreases with the increase in retail-market demand uncertainty.     

Production quantity allocation for order fulfilment in the supply chain: a neural network based approach

In the current global business environment, it is very important to know how to allocate products from the producer to buyers (or distributors). If products are not appropriately distributed due to absence of an effective allocation policy, the producer and buyers cannot expect to increase customer satisfaction and financial profit. Sometimes some buyers can order more than the actual demand due to inappropriately forecasting customer orders. This is the big obstacle to the effective allocation of products. If the producer can become aware of buyers’ actual demands, it is possible to realise high-level order fulfilment through the effective allocation of products. In this study, new allocation policies are proposed considering buyers’ demands. The back propagation algorithm, one of the learning algorithms in neural network theory, is used to recognise actual demands from the previous buyers’ orders. After excluding surplus demands included in buyers’ demands, products are allocated to buyers according to one of the existing allocation policies depending on the company's decision. In the numerical examples, new allocation policies reducing buyers’ surplus demands outperform previous allocation policies with respect to average amount of backorder.     

Two-period pricing and ordering policy for the dominant retailer in a two-echelon supply chain with demand uncertainty

Retailing channels are increasingly being dominated by ‘power’ retailers who are in a position to dictate prices and ordering schedules to manufacturers and suppliers. A dominant retailer, such as Wal-Mart, has the ‘power’ to decide retail prices of products because there are so many manufacturers who are keen to sell their products through or to such a large and powerful retailer. Several products, such as electronic products, can be sold in the market for some periods during their lifecycles before they retreat, except when they are not popular with consumers after been introduced. Therefore, in case of such products, the retailer should not just consider a single-period pricing and ordering policy. It should make dynamic pricing and ordering decisions based on market demand forecast, in order to obtain maximum cumulative profit from the product during its lifecycle. In this study, we consider this scenario and construct a two-period model to discuss pricing and ordering problems for a dominant retailer with demand uncertainty in a declining price environment. We show that the maximum expected profit function is continuous concave, so the optimal solution to pricing and ordering policy exists and it is the one and only. We also analyze sensitivity of retailer's expected profit to the effects of parameters of price-discount sharing scheme and market demand.     

Impacts of demand and supply factors on the capacity scheduling performance of logistics service supply chain with mass customisation service modes: an empirical study from China

This paper studies the influence of the demand–supply environment on the capacity scheduling performance of the logistics service supply chain. According to the key characteristics of the demand–supply environment, the cases of five Chinese companies were introduced and cross-analysed, then research hypotheses were developed. After receiving 154 valid questionnaires and testing our hypotheses, some key conclusions were obtained. From the aspect of demand, there is a positive correlation between the customised levels of demand and the scheduling cost of logistics service integrators but a negative correlation between the customised levels of demand and the scheduling flexibility; From the aspect of supply, a higher self-support ratio of logistics source and a higher sourcing integrity of logistics service integrators will lead to a higher scheduling cost and a lower scheduling flexibility; a whole-process performance evaluation is a moderator, which will positively improve the impact of the whole process scheduling performance.