subsidy

Governments use online platforms to keep track of transactions in the supply chain (SC) of subsidized foods to prevent fraud. Although regular checks of warehouses and documents were conducted, current platforms failed to resolve the issue. Blockchain technology (BT) provides governments with the ability to access transparent and real-time data to address these challenges. In this paper, we examine the key challenges influencing the implementation of a BT platform for managing subsidized food products in Iran. The barriers appear to be interconnected. We present a model that integrates the Best-Worst method (BWM) for obtaining independent weights and the Weighted Influence Non-Linear Gauge System (WINGS) using a rescaling scheme for considering the interrelatedness between the criteria. Expert opinions and literature reviews are used to identify critical factors. According to the findings, the costs of implementing and maintaining the system, as well as the regular restructuring of government rules regarding the data to be collected, are the two main challenges of implementing this new technology. Moreover, there are concerns about the cooperation with downstream entities of SC, cultural differences among partners, and their knowledge level, which may affect the complexity of downstream implementation. The results of sensitivity analysis show that WINGS gives greater weight to factors that have more impact on others. Conversely, the weight of factors that are interwoven with other factors and factors that aren't influenced by other factors is reduced as compared to the independent relative importance obtained from BWM.

For the valuation of the renewable energy investments, providing private investors with a financial incentive to accelerate their investment is a very significant issue. Financial subsidies are known by the majority of the people to be one of the most important drivers in renewable energy expansion and one of the main reasons which result in the development of any industry. In this paper, we present a new approach to compute the optimal subsidies over a specific time period by using the Binomial model for the Valuation of Real Options for Iranian renewable energy investments adjusted with Tax rate. We also apply linear regression method for predicting energy prices in order to allow an investor to exercise the relevant option over the timeline of the project at the optimal price. To evaluate our proposed approach, we apply it using predicted electricity prices for the next 16 years and electricity generation cost for Seid Abad, Damghan solar power plant. Our results in comparison of the base paper show that our proposed approach improves the error of subsidy’s computation by 1.57 percent since we used the predicted energy prices rather than the spot price as used before in real options’ valuation.

For the valuation of the renewable energy investments, providing private investors with a financial incentive to accelerate their investment is a very significant issue. Financial subsidies are known by the majority of the people to be one of the most important drivers in renewable energy expansion and one of the main reasons which result in the development of any industry. In this paper, we present a new approach to compute the optimal subsidies over a specific time period by using the Binomial model for the Valuation of Real Options for Iranian renewable energy investments adjusted with Tax rate. We also apply linear regression method for predicting energy prices in order to allow an investor to exercise the relevant option over the timeline of the project at the optimal price. To evaluate our proposed approach, we apply it using predicted electricity prices for the next 16 years and electricity generation cost for Seid Abad, Damghan solar power plant. Our results in comparison of the base paper show that our proposed approach improves the error of subsidy’s computation by 1.57 percent since we used the predicted energy prices rather than the spot price as used before in real options’ valuation.

This work considers cooperative advertising in a manufacturer–retailer supply chain. While the manufacturer is the Stackelberg leader, the retailer is the follower. Using Sethi model it models the dynamic effect of the manufacturer and retailer’s advertising efforts on sale. It uses optimal control technique and stochastic differential game theory to obtain the players’ advertising strategies and the long-run value of the awareness share. Further, it models the relationship between the payoffs of both players and the awareness share. The work shows that with the provision of subsidy the retail advertising effort increases while the manufacturer’s advertising effort reduces. It further shows that the total channel payoff is higher for subsidised retail advertising. However, the subsidy can only be possible if the rate of growth of the manufacturer’s payoff is twice higher than that of the retailer.