درخت حوزه‌های تخصصی

People's work and personal life are not two separate categories, but a concept and should be considered together; because considering them separately causes us to have an incomplete understanding of both. Accordingly, the purpose of this study is to design a model for work-life balance of employees of the National Iranian Gas Company. The present research is applied in terms of orientation, descriptive in terms of purpose and survey in terms of strategy. In this study, using Delphi technique, the opinions of 15 experts on the factors affecting the balance of family work were identified based on the roadmap programs for reforming the administrative system of the country and 33 indicators. The sample size was 219 official employees and 61 contract employees of the official and contract employees of the National Iranian Gas Company (main company). Using confirmatory factor analysis, the mentioned dimensions were evaluated and tested. From the results of DEMETEL technique, it was observed that the factors related to monitoring, evaluation and development of organizational culture had the most relationship with other factors. The index of organizational culture development has the most impact and the factor of human capital has the least impact. The role and structure engineering index is the most influential in the next degree. Also, the criterion of factors related to management factors and technologies is very influential. The criterion of organizational culture development is also the least affected by other criteria. Engineering criteria role and structure have the highest impact and impact with other criteria studied. The criterion of human capital factors has the least impact with other variables. In this model, the criteria of engineering role and structure, development of organizational culture and monitoring and evaluation of the variable are causal and the rest are disabled.

One of the essential factors that lead to severe disruptions in financial markets is price bubbles and subsequent crashes. Numerous models for detecting bubbles have been developed, one of which (LPPLS) has lately attracted considerable interest. This study aims to utilize this model to detect price bubbles in Tehran Stock Exchange's index (TEDPIX). Confidence multi-scale indicators for this model are presented by fitting the LPPLS model to the data of the TSE index from 2009 through 2020. The bubble is detected when the number of fits that are in our filter conditions increases which means the growth of the indicator's value. By applying this method on TSE data two significant crashes in 2013 and 2020 are detected. The proposed technique can be useful for market participants to detect financial crashes and bubbles.