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JDR Vol.11 No.4 pp. 691-698
(2016)
doi: 10.20965/jdr.2016.p0691

Paper:

Modifying Business Continuity Plan (BCP) Towards an Effective Auto-Mobile Business Continuity Management (BCM): A Quantitative Approach

Abednico Lopang Montshiwa*,†, Akio Nagahira*, and Shuichi Ishida**

*Graduate School of Engineering, Tohoku University
661180 Aza-Aoba-ku, Sendai, Miyagi 980-8579, Japan

Corresponding author,

**Graduate School of Technology Management, Ritsumeikan University, Osaka, Japan

Received:
October 8, 2015
Accepted:
May 17, 2016
Published:
August 1, 2016
Keywords:
business continuity plan (BCP), business continuity management (BCM), supply chain cooperation, business impact analysis (BIA), risk ranking (RR)
Abstract
Traditionally BCP consists of two main aspects, being Business Impact Analysis (BIA) and Risk Assessment (RA) [3,,8]. However, this approach doesn’t seem to be sufficiently addressing the complex and elaborate nature of supply chain network in the automobile industry. To address this insufficiency, we replace RA with Risk Ranking (RR) and introduce a new term Supply Chain Cooperation (SCC) to our BCP. A quantitative study was carried on 75 automobile parts markers in disaster prone regions (Asia and North America) and the results were analyzed by adopting this modified BCP concept and using Smart PLS 2.0 as our statistical analysis tool. We realized that SCC has a positive total significant effect on manmade risk rankings, natural risk ranking and BCM. Though risk ranking affects BCM, recovery time and competitive advantages positively, the relationships were not significant. In this study, we realized that BIA is the single most important part of BCP as it had the strongest positive total effects on other BCP factors (SCC, manmade risk ranking and natural risk ranking), BCM and evaluation factors (competitive advantages and recovery time).
Cite this article as:
A. Montshiwa, A. Nagahira, and S. Ishida, “Modifying Business Continuity Plan (BCP) Towards an Effective Auto-Mobile Business Continuity Management (BCM): A Quantitative Approach,” J. Disaster Res., Vol.11 No.4, pp. 691-698, 2016.
Data files:
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