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PurposeThe purpose of this paper is to illustrate the outcomes of the RED (Routing on Empirical Data) Project, a three year cross‐jurisdictional collaborative undertaking in the State of California that significantly improved the efficiency of the State's wireless 9‐1‐1 emergency communications system.Design/methodology/approachThe Project's approach looked at historical wireless call data over a three‐year period and created accurate jurisdictional shapefiles to identify actual call origination and determine statistically which Public Safety Answering Point (PSAP) should receive wireless 9‐1‐1 calls routed to a particular wireless sector.FindingsThe findings or outcomes of the project were that busy signals previously in the 9‐1‐1 system were dramatically reduced to 2.3 per cent of total call volume in 2011 from 42.4 per cent of total call volume in 2007. This occurred with a concurrent 29 per cent increase in call volume over the same time period.Practical implicationsThe practical and social implications for improvement in public safety are significant given the improvements in emergency response time that the project's outcome provides. Exponential increases in wireless phone usage over the past decade makes review of emergency communication infrastructure essential to ensure expeditious delivery of emergency services to the 9‐1‐1 calling public. Whether fire, ambulance or law enforcement response is required, when delay is inserted into the process of answering 9‐1‐1 calls, a reduction in the likelihood of a positive outcome occurs.Originality/valueThe outcomes of the RED Project show that Local and State government collaboration using empirical data studies can ensure emergency communication systems are optimized and ready for Next Generation technologies.

Financial institutions are an important source of financial system functioning of a country and include banks, pension funds, insurance companies, microfinance institutions, and so on. While the risk of financial institutions presents their ability to lose, consequently the change of the actual cash flow from the planned one. Among the major risks facing financial institutions are credit risk, market risk, operational risk and liquidity risk.The purpose of this paper is to investigate the risk management in financial institutions by making a survey with the banking sector, which accounts for most of the financial activities. For this reason, eight financial indicators are used to calculate the financial performance of the eight commercial banks involved in the research, which operate in Kosovo, taking into account the last two years of their operation. From the data derived from these indicators, using the One-Way ANOVA analysis, differences between banks were investigated according to their performance. As a result, it has been found that there are significant differences between banks according to liquidity risk, credit risk, equity risk and profitability risk. In addition, a linear regression model was also performed, which shows that the change in the return on equity (ROE) depends almost entirely on the change in the other seven indicators included.
Key words: Commercial Banks,Risks, Liquidity, Credit, Equity, Profitability.

From November to December 2020, the third wave of COVID-19 cases in Korea is ongoing. The government increased Seoul's social distancing to the 2.5 level, and the number of confirmed cases is increasing daily. Due to a shortage of hospital beds, treatment is difficult. Furthermore, gatherings at the end of the year and the beginning of next year are expected to worsen the effects. The purpose of this paper is to emphasize the importance of prediction timing rather than prediction of the number of confirmed cases. Thus, in this study, five groups were set according to minimum, maximum, and high variability. Through empirical data analysis, the groups were subdivided into a total of 19 cases. The cumulative number of COVID-19 confirmed cases is predicted using the auto regressive integrated moving average (ARIMA) model and compared with the actual number of confirmed cases. Through group and case-by-case prediction, forecasts can accurately determine decreasing and increasing trends. To prevent further spread of COVID-19, urgent and strong government restrictions are needed. This study will help the government and the Korea Disease Control and Prevention Agency (KDCA) to respond systematically to a future surge in confirmed cases.