TY - UNPB
T1 - Assessing Disruption Propagation Through Supply Networks
T2 - The Case of 737MAX and the Boeing-Airbus Duopoly
AU - Zhang, James
AU - de Koning, D.C.
AU - Dabadghao, Shaunak S.
AU - Udenio, Maximiliano
PY - 2023
Y1 - 2023
N2 - By utilizing Boeing 737MAX crashes and the subsequent announcements related to Boeing 737MAX production glitches during 2018-2019 time period, this paper investigates how these events impact shareholder values of publicly traded firms within supply chains of the Boeing-Airbus duopoly. We rely on 207 suppliers and 68 customers for Boeing, and 173 suppliers and 68 customers for Airbus to estimate this effect. For Event 1 (i.e., Lion Air Flight crash), we find that the negative effect of Boeing crash propagates to Boeing’s suppliers on event day. Event 2 (i.e., Ethiopian Airlines Flight crash) has more severe effects than Event 1. Overall, Boeing lost approximately 16% for this event, while Airbus seems to work well during this event. This event also propagates through Boeing’s suppliers and customers, with customers suffering more than suppliers. This effect also spillovers to suppliers and customers of Airbus. This effect is majorly due to common suppliers and customers of Boeing and Airbus. We also observe variations of regions and industries within suppliers of the duopoly. We have not found significant results for Boeing’s announcement of 737MAX production cut (i.e., Event 3). However, we do find some similar pattern for Event 4 (i.e., 737MAX production stop) as in Event 2 for suppliers in this duopoly. Our results have important implications for supply chain management and practice in an aircraft duopoly.
AB - By utilizing Boeing 737MAX crashes and the subsequent announcements related to Boeing 737MAX production glitches during 2018-2019 time period, this paper investigates how these events impact shareholder values of publicly traded firms within supply chains of the Boeing-Airbus duopoly. We rely on 207 suppliers and 68 customers for Boeing, and 173 suppliers and 68 customers for Airbus to estimate this effect. For Event 1 (i.e., Lion Air Flight crash), we find that the negative effect of Boeing crash propagates to Boeing’s suppliers on event day. Event 2 (i.e., Ethiopian Airlines Flight crash) has more severe effects than Event 1. Overall, Boeing lost approximately 16% for this event, while Airbus seems to work well during this event. This event also propagates through Boeing’s suppliers and customers, with customers suffering more than suppliers. This effect also spillovers to suppliers and customers of Airbus. This effect is majorly due to common suppliers and customers of Boeing and Airbus. We also observe variations of regions and industries within suppliers of the duopoly. We have not found significant results for Boeing’s announcement of 737MAX production cut (i.e., Event 3). However, we do find some similar pattern for Event 4 (i.e., 737MAX production stop) as in Event 2 for suppliers in this duopoly. Our results have important implications for supply chain management and practice in an aircraft duopoly.
U2 - 10.2139/ssrn.3950302
DO - 10.2139/ssrn.3950302
M3 - Working paper
SP - 1
EP - 39
BT - Assessing Disruption Propagation Through Supply Networks
PB - Social Science Research Network (SSRN)
ER -