درخت حوزه‌های تخصصی

The purpose of this study is to evaluate the rough analysis process to select the most effective functions of supply chain flexibility based on the propositions of integration of competitive values in the petrochemical industry. The methodology of this research is hybrid and to perform it from meta-synthesis analysis; Delphi and Rough collection used. The target population in the qualitative sector was similar research and academic experts in the field of industrial management. However, the target population was a small number of 23 managers with experience in petrochemical companies, which is acceptable from the statistical population due to the need to analyze the Rough process. In this study, based on the combined analysis of selected researches, 5 propositions of competitive value integration and 5 components of supply chain flexibility were determined, which entered the Rough collection analysis phase according to the confirmation of theoretical adequacy based on Delphi analysis. The results in this section identify the most effective propositions of integration of competitive values of companies operating in the petrochemical industry, three propositions of demand-based management propositions (P2); creating innovative values (P3) and reducing operating time (P5), which affects the flexibility of the supply chain and causes the flexibility of financing as the most effective component of the flexibility functions in the supply chain in the petrochemical industry.

Despite numerous upstream communications, there is still no comprehensive and reliable model for implementing these tasks; neither in the literature nor in oil & gas industry. Previously developed models focus more on the outsourcing process and it seems that there is no outsourcing model that has been developed with an eye to utilizing internal capabilities in a portfolio of alliances and be compatible with the unique characteristics of the Iran's oil and gas industry. In an attempt to validate the components of the "Model of development outsourcing physical assets in the oil and gas industry, with the approach of upgrading internal capacity" this study used a questionnaire in a Likert scale (very high, high, moderate, low, and very low). From the population, 102 people participated and a total of 100 completed questionnaires received. Using confirmatory factor analysis the validity of the variables and the questionnaire were examined. In this research, SPSS and Smart PLS softwares were used and the error probability level was considered α = 0.05. The results showed that the model has a good fit. According to the Geiser index, the fit of the model was medium to high and the goodness of fit criterion was equal to 461.0 and indicates the optimal fit of the model.