How to find the right supply chain strategy? An analysis of contingency variables


Falkenhausen, Christian von ; Fleischmann, Moritz ; Bode, Christoph



DOI: https://doi.org/10.1111/deci.12355
URL: https://onlinelibrary.wiley.com/doi/abs/10.1111/de...
Weitere URL: https://www.researchgate.net/publication/330605509...
Dokumenttyp: Zeitschriftenartikel
Erscheinungsjahr: 2019
Titel einer Zeitschrift oder einer Reihe: Decision Sciences : DS
Band/Volume: 50
Heft/Issue: 4
Seitenbereich: 726-755
Ort der Veröffentlichung: Oxford
Verlag: Wiley-Blackwell
ISSN: 0011-7315 , 1540-5915
Sprache der Veröffentlichung: Englisch
Einrichtung: Fakultät für Betriebswirtschaftslehre > ABWL u. Logistik (Fleischmann 2009-)
Fachgebiet: 330 Wirtschaft
Abstract: Contingency variables are characteristics of the business environment that influence the competitive priorities supply chains should pursue for maximizing profits. But which contingency variables should managers focus on when developing a supply chain strategy? On the one hand, if important variables are omitted, the selected strategy may fail to fulfill the needs of the business environment. On the other hand, considering irrelevant variables unnecessarily complicates the strategy formation process, hence preventing well‐suited strategies from being found. As a first step toward resolving this trade‐off, our study analyzes the effects hypothesized to be underlying a set of frequently cited contingency variables referred to as “DWV3” (product lifecycle Duration, delivery time Window, demand Variability, demand Volume, product Variety) as well as contribution margins. We test the hypotheses on archival data from a leading chemical manufacturer using multilevel regression. Our findings indicate that demand variability, the delivery time window, and contribution margins are important for strategy development because they indicate to what extent companies should invest in market mediation. Volume, variety, and lifecycle duration are less important for this purpose, but may instead be used for analyzing the causes of demand variability.




Dieser Eintrag ist Teil der Universitätsbibliographie.




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