Factors influencing tier 2 supply chain risk data collection

Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Engineering Systems Division, 2015. === Cataloged from PDF version of thesis. === Includes bibliographical references (pages 50-52). === Natural disasters such as the earthquake and subsequent tsunami that hit Japan in 2011 can hav...

Full description

Bibliographic Details
Main Authors: Buscher, Stephanie Ann, Poyato Ayuso, Ángel
Other Authors: Bruce C. Arntzen.
Format: Others
Language:English
Published: Massachusetts Institute of Technology 2015
Subjects:
Online Access:http://hdl.handle.net/1721.1/99807
id ndltd-MIT-oai-dspace.mit.edu-1721.1-99807
record_format oai_dc
spelling ndltd-MIT-oai-dspace.mit.edu-1721.1-998072019-05-02T16:07:20Z Factors influencing tier 2 supply chain risk data collection Factors influencing tier two supply chain risk data collection Buscher, Stephanie Ann Poyato Ayuso, Ángel Bruce C. Arntzen. Massachusetts Institute of Technology. Engineering Systems Division. Massachusetts Institute of Technology. Engineering Systems Division. Engineering Systems Division. Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Engineering Systems Division, 2015. Cataloged from PDF version of thesis. Includes bibliographical references (pages 50-52). Natural disasters such as the earthquake and subsequent tsunami that hit Japan in 2011 can have catastrophic effects on businesses. This type of unexpected event can cause millions of dollars in damages, lost sales and can impact company stock performance. With 39% of supply disruptions occurring at indirect suppliers, companies can no longer ignore their supply networks when determining supply chain risk. Unlike measuring risk within a single company, measuring the risk of a network requires collaboration amongst all players. This research aims to mitigate the complexity of data collection through the understanding of the factors that influence supply chain risk data collection. Factors vary throughout different players in the networks. Internally, supply chain transparency must be indoctrinated in the culture of the executing company. Necessary parties must be well informed and incentivized to take part in this labor intensive exercise. By indoctrinating transparency into the culture, companies legitimize this initiative to both employees and suppliers. Through a series of conversations held with suppliers, the research conducted in this thesis identifies the internal and external factors that determine success in supply chain risk data collection. Keywords: Supply chain risk management, supply chain transparency, data collection, vendor collaboration. by Stephanie Ann Buscher and Angel Poyato Ayuso. M. Eng. in Logistics 2015-11-09T19:50:07Z 2015-11-09T19:50:07Z 2015 2015 Thesis http://hdl.handle.net/1721.1/99807 927169283 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 52 pages application/pdf Massachusetts Institute of Technology
collection NDLTD
language English
format Others
sources NDLTD
topic Engineering Systems Division.
spellingShingle Engineering Systems Division.
Buscher, Stephanie Ann
Poyato Ayuso, Ángel
Factors influencing tier 2 supply chain risk data collection
description Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Engineering Systems Division, 2015. === Cataloged from PDF version of thesis. === Includes bibliographical references (pages 50-52). === Natural disasters such as the earthquake and subsequent tsunami that hit Japan in 2011 can have catastrophic effects on businesses. This type of unexpected event can cause millions of dollars in damages, lost sales and can impact company stock performance. With 39% of supply disruptions occurring at indirect suppliers, companies can no longer ignore their supply networks when determining supply chain risk. Unlike measuring risk within a single company, measuring the risk of a network requires collaboration amongst all players. This research aims to mitigate the complexity of data collection through the understanding of the factors that influence supply chain risk data collection. Factors vary throughout different players in the networks. Internally, supply chain transparency must be indoctrinated in the culture of the executing company. Necessary parties must be well informed and incentivized to take part in this labor intensive exercise. By indoctrinating transparency into the culture, companies legitimize this initiative to both employees and suppliers. Through a series of conversations held with suppliers, the research conducted in this thesis identifies the internal and external factors that determine success in supply chain risk data collection. Keywords: Supply chain risk management, supply chain transparency, data collection, vendor collaboration. === by Stephanie Ann Buscher and Angel Poyato Ayuso. === M. Eng. in Logistics
author2 Bruce C. Arntzen.
author_facet Bruce C. Arntzen.
Buscher, Stephanie Ann
Poyato Ayuso, Ángel
author Buscher, Stephanie Ann
Poyato Ayuso, Ángel
author_sort Buscher, Stephanie Ann
title Factors influencing tier 2 supply chain risk data collection
title_short Factors influencing tier 2 supply chain risk data collection
title_full Factors influencing tier 2 supply chain risk data collection
title_fullStr Factors influencing tier 2 supply chain risk data collection
title_full_unstemmed Factors influencing tier 2 supply chain risk data collection
title_sort factors influencing tier 2 supply chain risk data collection
publisher Massachusetts Institute of Technology
publishDate 2015
url http://hdl.handle.net/1721.1/99807
work_keys_str_mv AT buscherstephanieann factorsinfluencingtier2supplychainriskdatacollection
AT poyatoayusoangel factorsinfluencingtier2supplychainriskdatacollection
AT buscherstephanieann factorsinfluencingtiertwosupplychainriskdatacollection
AT poyatoayusoangel factorsinfluencingtiertwosupplychainriskdatacollection
_version_ 1719035047708721152