درخت حوزه‌های تخصصی

Organizations face many challenges in the current unpredictable and changing business in which superiority in competition is one of their main goals. In this trend, the field of production has moved towards a paradigm called "Agile Production". If an organization wants to be agile, it must shorten the workflow of the process and provide the conditions for saving time. If a hospital is agile, it can respond when faced with internal and external changes and compete with other hospitals and provide appropriate and fast services to patients. Today, hospitals are currently trying to continuously evaluate their performance due to the increasing advancement of technology. A method in evaluating the performance of the organization is the Balanced Score Card (BSC) approach. In this, indicators measure the desired goals in the organization in four aspects of Internal process, Growth and Learning, Financial and Customer. In this approach, important aspects of sustainable development are ignored , therefore, the new method of Sustainable Balanced Score Card (SBSC) is used to evaluate the performance, which takes into account the environmental index. This study aimed to determine the factors that can be important for evaluating agility in the hospital and then classify them based on the perspectives of SBSC. In the next step, using a questionnaire and statistical hypothesis test, the effectiveness of these factors was confirmed. Then, the importance of each perspective in the field of agility was determined by hierarchical analysis, and this model was presented using the scoring method. Accordingly, the "Economic" index had the highest priority and the "Environmental" index had the lowest priority. Due to the high importance of the Economic index, suggestions were made, the most important of which is the use of long-term loans for the promotion and development of hospitals, effective cooperation, and the use of various insurance services of insurance organizations, considering inventory and tools. , Equipment, essential devices in the warehouse for greater efficiency. Regarding the innovation of this research, we can refer to the evaluation of agility from the perspective of the scorecard by considering the criterion of stability in the hospital.

This research aims to design an integrated model for digital marketing based on marketing intelligence and validate the model in the ISACO Company. The research uses a mixed-methods descriptive survey design. In the qualitative phase, the model and nine theoretical hypotheses were proposed using grounded theory and a semi-structured questionnaire. Fourteen academic experts and managers in the area of marketing and sales were interviewed until theoretical saturation was achieved. Then, the model and proposed hypotheses were validated using the quantitative method of structural equation modeling. A questionnaire rated by the Likert scale was distributed among 340 active employees in the relevant areas to the research topic with at least a Bachelor’s degree chosen by the convenience sampling method in the ISACO Company and affiliated companies. The structural model and hypotheses related to causal factors, core category, contextual factors, strategies, and consequences (except the moderating role of environmental factors) were validated by the research findings.

Voluntary deviation from self-control, commonly referred to as moral licensing, is a phenomenon in which an individual justifies his or her immoral and counterproductive behavior depending on various factors, especially past creditable behaviors and activities, without worrying about the loss of his or her reputation and esteem. Considering the undesirable consequences of this phenomenon for the individual, organization and society, this study attempts to find the reasons and factors that lead to the formation of moral licensing in addition to the individual's previous creditable behaviors and activities. The research philosophy was descriptive, the approach was qualitative, and the strategy was emergent-based grounded theory. The population under study consists of managers and employees of public administrations in northeastern Iran. 17 individuals were selected as purposive samples until theoretical saturation was reached. A semi-structured interview was used to collect data. Analysis of the interviews based on actual and theoretical coding shows that the causes of moral licensing are classified into six categories. Identifying these causes can provide solutions to prevent moral licensing in the organizations.

The Forex market is known as the strongest and richest financial market in the world that has been operating continuously. This market is formed based on the exchange rates of different countries, as well as the prices of oil and gold. The price of currency pairs in the Forex market as the largest market for financial transactions has always been of great importance. The purpose of this article is to study the Forex market based on chaos theory. Its statistical population includes three currency pairs Euro / Dollar, Pound / Dollar and Dollar / Yen. The period of prices of the surveyed currency pairs is from January 2017 to December 2021 and its time range includes daily prices. The results showed that after fitting the model and performing the BDS test, on the GARCH model residues in different dimensions and ε of all 6 groups, which are IID residues and there is no dependence on them. The results of Lyapunov's maximalism test showed that for all dimensions, and all time intervals (n), the value of Lyapunov's exponent is a positive and small number, indicating that the time series of the triple currency pair follows a chaotic process.

The issue of transportation, which today as a socio-political phenomenon plays a very sensitive and important role in the quality and socio-economic structure of a society, forms the basis of modern urban life and the needs of human movement. In this research, our goal is to design a system dynamics model in the form of combined transport system to try to reduce costs, time and increase customer satisfaction by taking into account the uncertainty in the combined transport system, especially uncertainty in demand. Considering the productivity required by both of passengers and urban management, the importance of the issue and its impact on other sectors, as well as the lack of sufficient research in this field, in this study, the design of intra-city transportation system will be studied. The purpose of this planning is to determine the location of stations for public transportation as well as to determine the best route to reach the next station. Initially, the IoT system is used to collect and analyze historical data. Then the effective parameters and input values of the mathematical programming model are determined. The implementation of the model determines the appropriate outcomes for the decision variables. In other words, this leads to determining the optimal stations and the appropriate route to transport passengers between stations so that travel time and cost are minimized. In addition to material profitability, this includes passenger satisfaction, increased willingness to use public transport, reduced traffic, and reduced environmental impact, increased reliability of public transport and more accurate forecast of vehicle arrival at the station.

Accurate stock market prediction can assist in an efficient portfolio and risk management. However, accurately predicting stock price trends still is an elusive goal, not only because the stock market is affected by policies, market environment, and market sentiment, but also because stock price data is inherently complex, noisy, and nonlinear. Recently, the rapid development of deep learning can make the classifiers more robust, which can be used to solve nonlinear problems. This study proposes a hybrid framework using Long Short-Term Memory, Autoencoder, and Deep Neural Networks (LSTM-AE-DNNs). Specifically, LSTM-AE is responsible for extracting relevant features, and in order to predict price movement, the features are fed into two deep learning models based on a recurrent neural network (RNN) and multilayer perceptron (MLP). The dataset used for this is Dow Jones daily stock for 2008-2018, which was used in this article. Besides, to further assess the prediction performance of the proposed model, original stock features are fed to the single RNN and MLP models. The results showed that the proposed model gives the more accurate and best results compared to another. In particular, LSTM-AE+RNN shows a better performance than the LSTM-AE+MLP. In addition, hybrid models show better performance compared to a single DNN fed with the all-stock features directly.