3 resultados para latent growth curve modeling

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A cikk a magyarországi kis- és középvállalkozások logisztikai költségeit vizsgálja a nemzetközi kutatások tükrében és a 2009-es közel kétezer hazai KKV-re kiterjedő „Vállalkozások helyzetének felmérése” alapján. A hazai logisztikai költségeket leginkább a vállalatméret és az ágazat befolyásolja. A magyarországi kis- és középvállalkozások ki nem szervezett szállítási és raktározási tevékenységei a hazai fuvarozóknak és raktárszolgáltatóknak jelentős piacbővülést jelenthetnének. Ez azonban csak látens piacbővülés, mivel a hazai KKV-k nem tervezik, hogy szállítási és raktározási tevékenységeiket nagyobb arányban szervezzék ki. Ez részben azzal magyarázható, hogy a feldolgozóipari, mezőgazdasági és kereskedő kis- és középvállalkozások viszonylag nagy arányban tekintik a logisztikát alapvető képességnek. Nemzetközi viszonylatban a magyarországi KKV-k magas logisztikai költségszintekkel szembesülnek, melynek mérséklésével az adminisztrációs terhek csökkentéséhez hasonló megtakarítást lehetne elérni. ____ This article examines total logistics costs and its components of the Hungarian small- and medium-sized enterprises in the light of international researches. It shows that company-size and its sector are the most important drivers of logistics costs and its components according to „Survey of position of enterprises”, which covered nearly 2000 Hungarian SMEs in 2009. It also proves that transport and warehousing demand of the Hungarian SMEs means a significant market growth for national carriers and warehouse providers. It is only a latent growth, because the Hungarian SMEs do not plan to outsource their transport and warehouse activities in a greater extent. The relative high level of logistics as a core competence among processing industry, agriculture and trade SMEs can be a partial explanation to this. The Hungarian small- and medium-sized enterprises face with high logistics costs in international comparison. Its reduction may bring similar savings as reduction of administrative burdens.

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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.