Designing and testing the supply chain agility model in oil and gas industry with a mixed approach
الموضوعات :
Sajjad Shamsi Gooshki
1
(
Department of Business and Administrative Management, Faculty of Management and Accounting, University of Tehran, College of Farabi, Qom, Iran
)
Arsalan Nami
2
(
Technical and Vocational University (TVU), Bushehr, Iran
)
Mohammad Solgi
3
(
Department of Financial Management, Faculty of Management and Strategic Planning, University Of Imam Hossein, Tehran, Iran
)
الکلمات المفتاحية: Supply Chain, Agility, Oil and Gas Industry, Mixed approach,
ملخص المقالة :
Today, environmental change has become an integral part of businesses. One of the best ways to respond to these changes is supply chain agility. Therefore, the purpose of this study is to design and test the supply chain agility model in oil and gas industry. This research is conducted with a mixed approach. The statistical population was experts in the oil and gas industry. In the qualitative phase, a sample consisting of 8 experts are selected to extract the drivers, components and consequences of supply chain agility model and using the content analysis approach. In the quantitative phase, a sample of 64 experts are selected and the collected data are analyzed using a questionnaire tool through the structural equation modeling approach with Smart PLS software version 2. Qualitative findings represent that environmental drivers act as prerequisites and requirements of supply chain agility. Supply chain agility consists of the general categories of agile sensitivity, planning and production, which ultimately leads to the consequences of supply chain agility. Quantitative phase findings show that supply chain agility drivers have a significant and positive effect on agility sensitivity, agile planning and agile production. Also, agile planning and agile production have a significant and positive effect on the consequences of supply chain agility, but agile sensitivity has no significant effect on the consequences of supply chain agility. The results of fitting the research model also showed that this model has a good fit.
