Strategic integration decision under supply chain competition in the presence of online channel

This study explores the pricing decisions of substitutable products for two competing supply chains in the presence of an online channel. Each supply chain consisting of a single manufacturer and an exclusive retailer and one of the manufacturers distributes products through the online channel. We examine optimal decisions under five scenarios to explore how the strategic cooperation between two manufacturers at the upstream horizontal level or with the retailer at the vertical level affects product pricing decisions and the performance of two supply chains? The results reveal that decisions for cooperation with competing manufacturers and opening an online channel are correlated. In the absence of an online channel, cooperation with their respective retailer can lead to a higher supply chain profit. However, if a manufacturer opens an online channel, then cooperation with competing manufacturers can lead to a higher supply chain profit. Under the vertical integration, total supply chain profit might be lower compared to a scenario where members in each supply chain remain independent. Consumers also need to pay more for products

The impact of stochastic lead times on the bullwhip effect–a theoretical insight

In this article, we analyze the models quantifying the bullwhip effect in supply chains with stochastic lead times and find advantages and disadvantages of their approaches to the bullwhip problem. Moreover, using computer simulation, we find interesting insights into the bullwhip behavior for a particular instance of a multi-echelon supply chain with constant customer demands and random lead times. We confirm the recent finding of Michna and Nielsen that under certain circumstances lead time signal processing is by itself a fundamental cause of bullwhip effect just like demand-signal processing is. The simulation also shows that in this supply chain the delay parameter of demand forecasting smooths the bullwhip effect at the manufacturer level much faster than the delay parameter of lead time forecasting. Additionally, in the supply chain with random demands, the reverse behavior is observed, that is, the delay parameter of lead time forecasting smooths bullwhip effect at the retailer stage much faster than the delay parameter of demand forecasting. At the manufacturer level, the delay parameter of demand forecasting and the delay parameter of lead time forecasting dampen the effect with a similar strength

Delivery-flow routing and scheduling subject to constraints imposed by vehicle flows in fractal-like networks

The problems of designing supply networks and traffic flow routing and scheduling are the subject of intensive research. The problems encompass the management of the supply of a variety of goods using multi-modal transportation. This research also takes into account the various constraints related to route topology, the parameters of the available fleet of vehicles, order values, delivery due dates, etc. Assuming that the structure of a supply network, constrained by a transport network topology that determines its behavior, we develop a declarative model which would enable the analysis of the relationships between the structure of a supply network and its potential behavior resulting in a set of desired delivery-flows. The problem in question can be reduced to determining sufficient conditions that ensure smooth flow in a transport network with a fractal structure. The proposed approach, which assumes a recursive, fractal network structure, enables the assessment of alternative delivery routes and associated schedules in polynomial time. An illustrative example showing the quantitative and qualitative relationships between the morphological characteristics of the investigated supply networks and the functional parameters of the assumed delivery-flows is provided

Reducing the Total Product Cost at the Product Design Stage

Currently used decision support systems allow decision-makers to evaluate the product performance, including a net present value analysis, in order to enable them to make a decision regarding whether or not to carry out a new product development project. However, these solutions are inadequate to provide simulations for verifying a possibility of reducing the total product cost through changes in the product design phase. The proposed approach provides a framework for identifying possible variants of changes in product design that can reduce the cost related to the production and after-sales phase. This paper is concerned with using business analytics to cost estimation and simulation regarding changes in product design. The cost of a new product is estimated using analogical and parametric models that base on artificial neural networks. Relationships identified by computational intelligence are used to prepare cost estimation and simulations. A model of product development, production process, and admissible resources is described in terms of a constraint satisfaction problem that is effectively solved using constraint programming techniques. The proposed method enables the selection of a more appropriate technique to cost estimation, the identification of a set of possible changes in product design towards reducing the total product cost, and it is the framework for developing a decision support system. In this aspect, it outperforms current methods dedicated for evaluating the potential of a new product