The collaboration between the universities and industries is currently in the focus of attention globally. Governments, universities, and industries are interested in good and effective collaboration, which would be beneficial for all parties. To foster University-Industry Collaboration, and to help transfer the knowledge and technology between these two parties, academics, politicians and companies are paying attention to science and technology policies more than ever. In this study, the factors affecting the improvement of University-Industry Collaboration are identified and prioritized. In the first step, 20 factors are identified and 12 factors are selected using the Fuzzy Delphi method. Then, using the BWM method, prioritizing the extracted factors is determined for industry sponsorship of the university research. Finally, based on the results, the discussion is conducted and six major strategies are presented to improve this relationship.

Closed-loop supply chain management is an effective and efficient solution for a set of activities to retrieve a product from a customer and improve its value or to dispose it. Today, designing and planning a closed-loop chain is an inevitable but difficult task. In this research, a scenario-based modeling approach is presented by considering both forward and reverse flows as a closed-loop supply chains in steel industry. The proposed study also develops a multi-product and multi-period model based on a mixed integer linear programming (MILP) approach for profit maximization. The study also considers uncertainty in the amount of raw material, processing, storage and distribution of several products flow. Uncertainty is associated with the quantity and quality of the products in the reverse flow, which are directly affected by customers and sorting centers, respectively. Finally, the model is deployed in Steel industry with real data. The results show that by increasing the quality level of returned products the need for raw materials is reduced and the total profit of the supply chain is increased.

The lack of a proper communication link between supply chain operations and financial performance seems to be due to the difficulty of using the operational metrics of supply chain measurement to reach the financial goals. This study is an attempt to find the effect of supply chain management (SCM) implementation on the financial success of the firms. The study considers the effects of Revenue, Prime Cost, Cash-to-cash cycle period and Return on working capital on the financial performance of the selected firms listed in Istanbul stock exchange from 2012 to 2017. The study divides the sample size based on their financial growth into two groups and using some statistical test measures the difference between two groups, statistically. The results show that there was a significant difference between the mean of high-growth and low-growth companies in terms of SCM implementation. However, the effects of cost, cash cycle and working capital on financial performance were not confirmed.