Performance implications of supply chain risk and risk management

Westerburg, Michael

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URL:	https://madoc.bib.uni-mannheim.de/49590
URN:	urn:nbn:de:bsz:180-madoc-495902
Document Type:	Doctoral dissertation
Year of publication:	2019
Place of publication:	Mannheim
University:	Universität Mannheim
Evaluator:	Bode, Christoph
Date of oral examination:	23 November 2018
Publication language:	English
Institution:	Business School > Stiftungslehrstuhl für Procurement (Bode 2014-)
License:
Subject:	330 Economics 650 Management
Subject headings (SWD):	Supply Chain Management , Einkauf , Textanalyse , Operationelles Risiko , Risikomanagement
Keywords (English):	10-k reports , supply chain management , supply chain risk , text analysis
Abstract:	Firms operate in a complex world characterized by interdependencies among various factors which are difficult to anticipate and can pose a risk to a firm’s operations. On the one hand, prior research has identified major categories of supply chain risk. On the other, it has established that supply chain disruptions do indeed negatively affect a firm’s performance once they materialize. However, prior research has not explained which external uncertainties actually turn into what type of risk exposure. Moreover, such research has not yet explained under what conditions external events are extraordinarily harmful, and whether firms should have managed these potential risks. In order to fill in this lack of knowledge, this dissertation has developed a new measurement of a firm’s exposure to risk. To this end, it scrutinizes a firm’s 10-K reports and transforms the unstructured textual data into quantitative information. The resulting novel data set is augmented by financial and other publicly available secondary data. The results suggest that the industry is an important moderator of how external threats affect a firm’s performance. Furthermore, external threats always increase a firm’s exposure to risk, while internal strategies partly increase and partly decrease such an exposure. Finally, a firm must carefully analyze the type of risk to which it is exposed, because the efficiency of the mitigation strategy employed depends on the type of risk exposure. In sum, this dissertation suggests exploiting a firm’s self-disclosed textual information by means of linguistic computer analysis. As a result, it provides new answers to new research questions and hence extends the existing knowledge in the field of supply chain risk management.