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This study investigates whether logistics and supply chain resilience strategies (SCREST) can help mitigate the negative impacts of disruptions on firm performance and logistics and supply chain (SC) activities of companies, using the COVID-19 pandemic as a case study.

The authors collected primary data on the implementation of different types of SCRESTs and measured the impact of COVID-19 in terms of firm performance and logistics and SC metrics through a survey of Japanese manufacturing companies in four sectors. The authors used these data to illustrate whether the companies benefitted from SCRESTs in mitigating the negative impacts of COVID-19. A questionnaire comprising structured and open-ended questions was sent to 8,000 companies all over Japan that met the selection criteria, using a combination of mail and web-based media. The respondents were logistics and SC professionals. A combination of qualitative and quantitative analysis was performed for data analysis and interpretation.

Research conducted within the case of the Japanese context revealed that findings varied depending on the methodology applied. The use of a direct analysis approach and qualitative analysis suggested that the implementation of SCRESTs is beneficial in addressing the negative impacts of COVID-19 on firm performance and logistics and SC activities, whereas the application of indirect analysis approach yielded mixed results. The analysis also indicated a shift in the preferred SCRESTs during COVID-19.

To the best of the authors’ knowledge, this is the first study to examine the benefits of implementing SCRESTs using primary data from the manufacturing sector of Japan. Furthermore, empirical research on this topic is generally lacking.

The purpose of this study is to compare revenue guarantee programs in a build-operation-transfer project (BOT). Two types of revenue guarantee programs are formulated: a payment-based annual revenue guarantee program and a period-extension-based cumulative revenue guarantee program.

Monte Carlo simulation is used to model the real option approach. This method is applied to a toll road project in the Philippines wherein the expected payoffs of the government and the concessionaire are simulated over an evaluation period that includes the concession period. The condition under which the expected government return in one program is equal to that in the other program is shown. These programs are then evaluated by incorporating a project risk factor into the project return.

The results show that the cumulative revenue guarantee program is preferred to the annual revenue guarantee program. However, the optimal solution depends on the government's return-risk preference.

The simulation was implemented with limited cases of discrete input with respect to the cost-sharing parameter, the annual guarantee rate, and the guaranteed cumulative revenue. A simulation with more input values should be performed to achieve results that are more general and sophisticated.

It is indicated that the simple reduction of risk does not necessarily mean that government expected payoff will increase.

It is expected that this method contributes to the proper decisions made by the governments with respect to the choice of a revenue guarantee mechanism in BOT projects.