In recent years, interest in big data has increased in the field of management. With digitalization, companies have started to receive data flow from many channels at the same time. Many sources such as the internet of things, connected sensors, cloud systems, social media, and daily operational records of companies have become an important source of big data for companies. In addition to encouraging companies to strengthen their technological infrastructure, the use of big data has also revealed important strategic and cultural adaptation problems. In this scope, the aim of the study is to examine the effect of big data analytics on the managerial capabilities and performance of companies. In this context, the studies in the literature on the subject have been examined. As a result of the literature review, issues related to big data that are thought to affect the managerial ability of the company have been discussed.
The purpose of this study is to determine major indicators of the Greek crisis that started in 2009 and the effects of which can still be observed. In this regard, 8 independent variables were applied so as to fulfill the objective. Besides, the annual data between the years 1984 and 2016 was analyzed with Probit model. As a consequence of this study, it was concluded that inflation and gross savings are the leading meters of Greek crisis based on probit method. On the other hand, according to the MARS results, 3 different variables are identified as the indicators of the debt crisis in Greece. It is concluded that there is a negative relation between financial crisis with saving ratio and current account balance. Additionally, it is also identified that high unemployment ratio leads to financial crisis. While comparisng the results of these two approaches, it is concluded that MARS is much more successful than the probit method to predict the debt crisis in Greece. It is strongly recommended that saving ratio should be increased in Greece. For this purpose, governments should take some actions in order to increase this ratio more than 15.5%. Within this framework, media channels can be used by the government to tell the people about the importance of the savings to have sustainable economic development.
Purpose- The purpose of the study is to show that multi-criteria decision-making methods can be used in the recruiting process of non-type rated pilots in the civil aviation sector.
Methodology-In this scope, the criteria taken into consideration by the HR departments in the recruitment process of non-type rated pilots to work in the civil aviation sector have been identified in the study. Then, with the AHP method, importance levels of the criteria have been determined by taking experts opinion. TOPSIS method has been used to select the right candidate for the business among the five candidates who applied as non-type rated pilots.
Findings- Finding of the study has proposed the most suitable candidate for the company.
Conclusion- The effective use of AHP and TOPSIS multi-criteria decision-making techniques in an integrated manner will facilitate HR managers and decision makers in the quantitative evaluation of subjective and objective criteria. The proposed method can also be used in selection processes in other areas of HRM.
Keywords: Human resource management, civil aviation, AHP, TOPSIS, non-type rated pilots
JEL Codes: M12, Y9, C35
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