Erdiyansyah

This study aims to investigate the impact of social distancing policies on SMEs in Indonesia. It used a quantitative method with a survey design. Respondents were all SMEs in Indonesia that are affected by social distancing policies during the COVID-19 pandemic. It involved a total of 587 SME samples selected randomly. The data were collected through observations, questionnaires, and literature studies. The collected data were analyzed using descriptive statistics with SPSS software to determine the mean value. The result showed that social distancing policies affect SMEs during the COVID-19 pandemic. This is indicated by the decreasing income and demand for SMEs products, and even some have no income (mean values of 2.40) due to the social distancing policies. Besides, the policy’s impact is also shown in the increasing cost of raw materials and production costs due to supply chain problems (mean values of 4.79). The policy’s impact raises anxiety for SMEs to survive so that business actors change their plans by utilizing information technology (mean values of 4.81). This change is a strategy to survive due to the impact of the applied policies. Although social distancing policies affect SMEs’ survival during the pandemic, research findings show that SMEs in Indonesia did not terminate employment (mean values of 4.37) due to the presence of economic stimulus policies that helped SMEs survive and grow during the COVID-19 pandemic.

Both natural and non-natural disasters greatly affect human life, including business actors. The government is urgently required to solve the emerging problems caused by the disaster. This study aims to determine collaborative governance in handling natural and non-natural disasters that affect the business actors in Palu City. This study used a quantitative approach with a series of statistical tests. The sample of this study consisted of 207 respondents who are government and the business actors in Palu City affected by natural and non-natural disasters. Data were collected through observation, questionnaires, and documentation. Then, the data were analyzed with statistical testing including descriptive statistics and a T-Test (comparative test). The results showed a significant difference between collaborative governance during natural and non-natural disasters. Further, the differences in collaborative governance can be seen in the leadership and initial condition variables. When a natural disaster occurs, leadership is urgently required, while a non-natural disaster caused by the COVID-19 is highly determined by the initial conditions. It means that government decision-making to deal with non-natural disasters from the start is urgently required. The evidence can be seen from some countries and regions with slow response to the COVID-19 resulting in difficulty in controlling the spread of the virus.