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In this paper, we have considered that ranked set sampling is able to estimate the parameters of exponentiated Pareto distribution. The method with which the maximum likelihood estimators for the parameters of exponentiated Pareto distribution is studied is numerical since there is no presence or possibility of a closed-form at the hands of estimators or any other intellectual. The numerical approach is a well-suited one for this study as there has been struggles in achieving it with any other technique. In order to compare the different sampling methods, simulation studies are performed as the main technique. As for the illustrative purposes, analysis of a simulated dataset is desired for the objective of the presentation. The conclusion that we can reach based on these is that the estimators based on the ranked set sample have far better efficiency than the simple random sample at the same sample size.

This publication analyzes the situation of businesses in the context of global pandemics. Business is an integral part of everyday life, facing risks and challenges daily, and in rare cases, such as pandemics and quarantine. Therefore, it is necessary for companies to have a contingency plan in place to deal with unexpected or expected challenges, i.e. what activities it would be possible to reorient to, how to perform activities by working remotely etc. Both the public sector and the private sector are closely interlinked. And every new environmental factor, be it state regulation, technological development, or the changing needs of humanity, and in this case, pandemic and quarantine, affects business in one way or another and leads to the success of some, the failure of others. At present, the coronavirus Covid-19, which is spreading all over the world, and the quarantine introduced in many countries are of great importance to business. This paper also presents a small-scale qualitative research data showing the impact on different types of businesses in Lithuania. The main scope of this paper is measuring the level of impact of the pandemic COVID-19 for businesses in Lithuania. Methods were used as follows: i) analysis, comparison and interpretation of scientific literature and documents; ii) qualitative approach applying structured interview with selected leaders/managers of the companies in Lithuania.

Today’s intensely competitive business is undergoing significant shifts, which render it a challenging environment to compete in. Production processes are evolving as customer demands change, which leads to greater variability. Firms must respond to changing environmental conditions to remain sustainable. Companies today look for ways to overcome their problems not only on their own but also with their supply chains. Reduced cost and improved performance are two significant benefits of supply chain management. Because companies can work together in the face of challenging market conditions throughout their supply chains, it makes sense for them to collaborate. When companies work together, they can collaborate to produce better-designed products and more efficient manufacturing processes. Learning, supply chain integration, and flexibility throughout the supply chain are critical to successful supply chain management. In this study, the effect of supply chain learning on supply chain integration and production flexibility has been investigated. The mediating role of supply chain integration on the impact of supply-chain learning on production flexibility has been tested. For this purpose, survey data was collected from the 144 companies selected out of Turkey's largest exporting companies. The data were analyzed via structural equation modeling and process macro methods. As a result of the structural equation model analysis, it was found that supply chain learning significantly affects the chain’s integration and its production flexibility. As a result of the intermediation test, it was determined that the integration of the supply chain has a vital intermediary role regarding the effect of supply chain learning on the flexibility of production.