درخت حوزه‌های تخصصی

This article aims to provide a model to explain the role of green human resource management in the resilience economy of small and medium-sized companies. The method of this research is a developmental-applied type of mixed research (qualitative-quantitative), which was used in the qualitative part of the Foundation (emerging) data method to identify components and indicators, and in the quantitative part, the descriptive-survey method was used. The statistical population in the qualitative part included experts (university faculty members) in the fields of human resource management, environment, and economics, after 28 interviews, the research reached theoretical saturation, and in a small part of the Cochran formula, there were 229 employees of the company. Industrial companies of Eshtehard town were selected. In the qualitative section, 13 codes were identified in process factors, 14 codes in prefixes, and 10 codes in suffixes. For the resistance economy, a researcher-made questionnaire with 31 indicators was used. The validity of the questionnaire was confirmed by the CVR method. Cronbach's alpha of the green human resources management questionnaire was equal to 0.761 and the resistance economy questionnaire was equal to 0.870. Two types of internal and external validity were used to validate the model. The results of the analysis of factor loadings of research components showed that there is a positive and significant linear relationship between each dimension of green human resource management. The results of the research model, it showed that among the identified factors, the antecedent dimension with a coefficient of 0.819, process factors with a coefficient of 0.797 and suffixes with a coefficient of 0.713, and finally, the coefficient of the impact of green human resources management on the resistance economy was obtained as 0.914, which shows the impact of 91 A percentage of aspects of green human resource management had resistance on the economy.

The purpose of this study is a new understanding behaviour and net cash flow forecasting. The data of this research contains the daily trial balance for one year, which has been received from 48 bank branches. For this purpose, the optimal model out of 4 models; Geometric Brownie, Arithmetic Brownie, Vasicek and Modified Square Root at three levels of microscopic, mesoscopic and macroscopic have been investigated and the Geometric Brownie model has been approved as the optimal model in microscopic level . The results show that Geometric Brownian Motion model can simulate the net cash flow highly accurate in accordance with the criteria of mean absolute percentage error. also forecasting net cash flow for each under study time series has been done in various forecasting horizons involved 7, 14, 21, 30, 60, 90 and 180 day time period accordance with the criteria of mean absolute percentage error. Also The other results obtained from this study is that according to 8 different prediction accuracy criteria, By increasing the forecast hori-zon, ability of the GBM model in simulation and forecasting the net cash flow de-creases.

The rapid emergence and evolution of technology have greatly impacted the way people live their lives. The internet has become a vital part of our daily lives. E-commerce is a type of technology development that enables customers to buy and sell products online. It is a unique form of transaction that connects people from all around the world. Today, many consumers shop for products online and present their products along with their specifications. This is becoming more prevalent. This increases the number of consumers online, which can result in a drop in growth. This is one of the main factors that a company uses to measure its success. Growing business success is revealed with retained customers. Satisfied consumers are the assets for a growing business. The study investigates the factors that influence people's decisions when it comes to buying items online. It shows that the experiences they have while shopping online can affect their decisions. The following statistical tools were applied for this study: percentage analysis, mean score with rank correlation, and t-Test. The results reveal that the factors quality, cost, product variety, uniqueness, and safety payments were highlighted as important indicators of performance and that the companies that do online businesses had to take care of their main goal as per the proposal.

The Analytic visualization suggests representing knowledge during a visual type that may be charts, graphs, lists, or maps. The COVID 19 detection and analysis of spreading is very important for countries. Database management with respect to virus deep analysis is a critical task to the researcher through conventional algorithms. The RNA, DNA, and biological data are helping to the bio-inspired algorithm but its implementation can be complex by software tools. Therefore, an effective technique is required to cross over the above limitations. So that covid 19 pandemic data analysis is performed through FCNN (Fully conventional Neural Network) pre-training network. The dataset is collected from social media, Kaggle, and GitHub databases. At 1st stage, the auto stack encoding process is applied later same data is processed with FCNN deep learning classifier. In this research work, covid-pandemic affects parameters like infected persons, deaths, active cases, and recovering cases. The FCNN is take care of feature extraction, training, testing, and classification. Finally using a confusion matrix accuracy of 98.34%, sensitivity 97.63%, Recall 98.26%, and F measure 98.83% had been estimated.

investors and managers are always faced with uncertainty in the information environment, which uncertainty can be due to factors such as the synchronization of stock returns, extraordinary fluctuations in stock returns and the number of equations. The purpose of this study is to investigate the political uncertainty caused by the size of the firm under the influence of risky information environment, the irregular behavior of accruals anomaly and the anomaly behavior of the cost of normal stock equity of companies. For this purpose, the data of 99 companies listed on the Tehran Stock Exchange and Iran TSETMC during the years 2009 to 2019 were examined and tested through combined data. The results showed that the political uncertainty caused by the firm size affected the concurrency stock returns with the optional accrual anomaly behavior and the cost of normal stock equity behavior of companies has a positive and signification relationship. The results also showed that the political uncertainty caused by the firm size is affected by the extraordinary fluctuation of stock returns with the optional accrual anomaly behavior and the cost of normal stock equity behavior of companies has a positive and signification relationship. In addition, the political uncertainty caused by the firm size is affected by the number of equations with the optional accrual anomaly behavior and the cost of normal stock equity behavior of companies has a positive and signification relationship.