Does intangible assets affect the financial performance and policy of commercial banks' in the emerging market?

In a digital and knowledge based economy, intangible assets are predominant and their role along with age and knowledge has become key success factors for firms. However, a very little attention was given to the intangible assets in the banking sectors' in Ethiopia and the effect still not studied yet. Therefore, the aim of this study is to empirically examine the effect of intangible assets on the financial performance and policy of 17 commercial banks in Ethiopia from the year 2017 to 2020. Return on asset and equity were used to measure the financial performance and debt as a measure of financial policy. The intangible asset is used as the main explanatory variable and asset size and liquidity as control variables. Random effect estimation technique for panel data was used. The result revealed that intangible asset has positive effect on the financial performance measured both by ROA and ROE at 5% significance level while, negative effect on the financial policy of commercial banks in Ethiopia at 1% significance level. Moreover, the study found asset size has significant and positive effect on ROA and ROE at 1% and 5% significance level respectively. Liquidity ratio has also significant positive effect on the financial performance measured both by ROA and ROE at 5% significance level. Finally, the finding revealed asset size and liquidity ratio has significant positive effect on the financial policy of commercial banks in Ethiopia at 10% and 1% significance level respectively. Therefore, the study concludes that financial performance and policy is achieved not only by using physical assets but also using intangible assets. Thus, the boards and mangers of commercial banks' ought to plan and maintain the appropriate ratio of intangible assets to total assets for securing sustainable development in achieving the maximization of shareholders wealth and to have optimum debt.

Priority list of biodiversity metrics to observe from space.

Monitoring global biodiversity from space through remotely sensing geospatial patterns has high potential to add to our knowledge acquired by field observation. Although a framework of essential biodiversity variables (EBVs) is emerging for monitoring biodiversity, its poor alignment with remote sensing products hinders interpolation between field observations. This study compiles a comprehensive, prioritized list of remote sensing biodiversity products that can further improve the monitoring of geospatial biodiversity patterns, enhancing the EBV framework and its applicability. The ecosystem structure and ecosystem function EBV classes, which capture the biological effects of disturbance as well as habitat structure, are shown by an expert review process to be the most relevant, feasible, accurate and mature for direct monitoring of biodiversity from satellites. Biodiversity products that require satellite remote sensing of a finer resolution that is still under development are given lower priority (for example, for the EBV class species traits). Some EBVs are not directly measurable by remote sensing from space, specifically the EBV class genetic composition. Linking remote sensing products to EBVs will accelerate product generation, improving reporting on the state of biodiversity from local to global scales.