Abstract:
This paper presents an optimized diamond structured automobile supply chain network towards a robust Business Continuity Management model. The model is necessitated by the nature of the automobile supply chain. Companies in tier two are centralized and numerically limited and have to supply multiple tier one companies with goods and services. The challenge with this supply chain structure is the inherent risks in the supply chain. Once supply chain disruption takes place at tier 2 level, the whole supply chain network suffers huge loses. To address this challenge, the paper replaces Risk Analysis with Risk Ranking and it introduces Supply Chain Cooperation (SCC) to the traditional Business Continuity Plan (BCP) concept. The paper employed three statistical analysis techniques (correlation analysis, regression analysis and Smart PLS 3.0 calculations). In this study, correlation and regression analysis results on risk rankings, SCC and Business Impact Analysis were significant, ascertaining the value of the model. The multivariate data analysis calculations demonstrated that SCC has a positive total significant effect on risk rankings and BCM while BIA has strongest positive effects on all BCP factors. Finally, sensitivity analysis demonstrated that company size plays a role in BCM.
Machine summary:
"To address this insufficiency, we replace RA with Risk Ranking (RR) and introduce a new term Supply Chain Cooperation (SCC) to our BCP figure 3 Company size, Product type etc Business Impact Analysis Risk Analysis BCM Recovery Time Competitive Advantage Figure 2.
Company size, Product type etc Business Impact Analysis Man-mad e RR Natural RR BCM Recovery Time Competitive Advantage Supply Chain.
This definition relates very well with the American National Fire Protection Agency (NFPA) 1600 (2010), which defines BIA as an analysis which measures the effect of resource loss and escalating losses over time in order to provide the entity with reliable data upon which to base decisions concerning hazard mitigation, recovery strategies and continuity planning.
Hypothesis 4 [Partly Supported] As expected, big company size has positive effects on supply chain cooperation, it can also be observed that correlation and regression analysis did not establish the significance of this relationship, and as such, this hypothesis is not significant.
Hypotheses 10 and 11 [Supported] BIA has a positive and significant total effects on both recovery time (***) and competitive advantages (*), the same results were also calculated by the regression analysis in table 5 (continuation).
Hypothesis 18 and 19 [Not supported] Contrary to our expectations both natural and manmade risk ranking has negative total effects on recovery time, but a weak positive significance (*) from the regression analysis results, this positive significant relationship seems to have been lost during Smart PLS 3."