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.

Aligning supplier evaluation with manufacturing competitive priorities. Results of an international survey in manufacturing and assembly industries

The aim of our research is to investigate a company’s purchasing and manufacturing competitive priorities jointly in order to uncover any relationships between them and also their effect on the supply chain tools implemented by the company. We assume that the supplier selection criteria of the companies reflect the true goals of the purchasing function and we take the purchasing function’s point of view to examine the aforementioned relationships. We use a multinational database for our empirical analysis which contains almost 700 companies from 20 countries and data that were acquired in 2009. We identified four different clusters which reflect a different level of supply chain tool implementation.