The analysis of bullwhip effect in a HMMS-type supply chain

The aim of the paper is to investigate the well-known bullwhip effect of supply chains. Control theoretic analysis of bullwhip effect is extensively analyzed in the literature with the Laplace transform. This paper tries to examine the effect for an extended Holt–Modigliani–Muth–Simon model. A two-stage supply chain (supplier–manufacturer) is studied with quadratic costs functional. It is assumed that both firms minimize the relevant costs. The order of the manufacturer is delayed with a known constant. Two cases are examined: supplier and manufacturer minimize the relevant costs decentralized, and a centralized decision rule. The question is answered, how to decrease the bullwhip effect.

The analysis of bullwhip effect in a HMMS-type supply chain

The aim of the paper is to investigate the well-known bullwhip effect of supply chains. Control theoretic analysis of bullwhip effect is extensively analyzed in the literature with Laplace transform. This paper tries to examine the effect for an extended Holt-Modigliani-Muth-Simon model. A two-stage supply chain (supplier-manufacturer) is studied with quadratic costs functional. It is assumed that both firms minimize the relevant costs. The order of the manufacturer is delayed with a known constant. Two cases are examined: supplier and manufacturer minimize the relevant costs decentralized, and a centralized decision rule. The question is answered, how to decrease the bullwhip effect.

Cross-country and inter-temporal analysis of Supply Chain Integration (SCI): China, Hungary and the Netherlands - changes in SCI from 1996 to 2008

Using plant level data from a global survey with multiple time frames, one begun in the late 1990s, this paper introduces measures of supply chain integration and discusses the dynamic relationship between the level of integration and a set of internal and external performance measurements. Specifically, data from Hungary, The Netherlands and The People’s Republic of China are used in the analyses. The time frames considered range from the late 1990s till 2009, encompassing major changes and transitions. Our results seem to indicate that SCI has an underlying structure of four sets of indicators, namely: (1) delivery frequency from the supplier or to the customer; (2) sharing internal processes with suppliers; (3) sharing internal processes with buyers and (4) joint facility location with partners. The differences between groups in terms of several performance measures proved to be small, being mostly statistically insignificant - but looking at the ANOVA table we can conclude that in this sample of companies those having joint location with their partners seem to outperform others.