The main focus of this paper is to propose a method for prioritizing knowledge and technology factor of firms towards sustainable competitive advantage. The data has been gathered and analyzed from two high tech start-ups in which technology and knowledge play major role in company’s success. The analytical hierarchy model (AHP) is used to determine competitive priorities of the firms. Then knowledge and technology part of sense and respond questionnaire is used to calculate the variability coefficient i.e. the uncertainty caused by technology and knowledge factor. The proposed model is tested in terms of two start-ups. Based on the initial calculation of uncertainties, some improvement plan is proposed and the method is applied again to see if the uncertainty of knowledge and technology decreases. In both cases, the proposed model helped to have a clear and precise improvement plan and led in reduction of uncertainty.
The objectives of this study were to develop a framework of the collaboration network, operational performance, and reverse logistics determinants on the performance outcomes of the auto parts industry, and to study the direct, indirect, and overall effects of the factors that influence the performance outcomes of the auto parts industry. This quantitative research utilized a questionnaire as the tool for data collection, which was completed by the managers in the auto parts industry from 320 companies. According to the analysis with the Structural Equation Modeling (SEM), it was found that the collaboration networks, operational performance, and reverse logistics positively affect the performance outcomes; whereas, the collaboration networks mainly affect the development of organizations by causing performance outcomes to continue growing unceasingly, including the enhancement of sustainable competitive capacity and the operational results of the auto parts industry.