Ellátási lánc kapcsolatok modellezése = Modeling of supply chain relationships

A dolgozatban az ellátási láncokban meglévő diadikus kapcsolatok minőségét állítjuk a vizsgálatok középpontjába. Az irodalomban számtalan megközelítés ismert az ellátási lánc kapcsolatok fejlődésének leírására. Ezen fejlődési elméletek inkább elméleti szinten írják le a diadikus kapcsolatok változását, annak empirikus tesztelhetőségét nem vizsgálják. Dolgozatunkban kísérletet teszünk az ellátási lánc kapcsolatok fejlődésének empirikus vizsgálatára. Arra próbálunk választ találni, hogy az életciklus hipotézis az üzleti kapcsolatok időbeli fejlődésére alkalmazható-e. = Our paper combines two approaches using data of an internet based questionnaire and applying quantitative analysis it tests the hypothesis business relationship development in time can be described with the concept of life cycle. The concept of life cycle is widely used in business research. Among others the diffusion of innovation is described using this concept, or the concept of product life cycle just to name a few. All of these researches analyze the life cycle along a specific variable (for example the volume of sales or revenue in case of the product life cycle) which (except the last stage of the cycle, the decline) has a cumulative character resulting in the widely known specific shape of a life cycle. Consequently testing a life cycle hypothesis inevitably means the acceptance of some type cumulativity in the development.

Simulation modeling of phytoplankton dynamics in a large eutrophic river, Hungary – Danubian Phytoplankton Growth Model (DPGM)

Ecological models have often been used in order to answer questions that are in the limelight of recent researches such as the possible effects of climate change. The methodology of tactical models is a very useful tool comparison to those complex models requiring relatively large set of input parameters. In this study, a theoretical strategic model (TEGM ) was adapted to the field data on the basis of a 24-year long monitoring database of phytoplankton in the Danube River at the station of G¨od, Hungary (at 1669 river kilometer – hereafter referred to as “rkm”). The Danubian Phytoplankton Growth Model (DPGM) is able to describe the seasonal dynamics of phytoplankton biomass (mg L−1) based on daily temperature, but takes the availability of light into consideration as well. In order to improve fitting, the 24-year long database was split in two parts in accordance with environmental sustainability. The period of 1979–1990 has a higher level of nutrient excess compared with that of the 1991–2002. The authors assume that, in the above-mentioned periods, phytoplankton responded to temperature in two different ways, thus two submodels were developed, DPGM-sA and DPGMsB. Observed and simulated data correlated quite well. Findings suggest that linear temperature rise brings drastic change to phytoplankton only in case of high nutrient load and it is mostly realized through the increase of yearly total biomass.