درخت حوزه‌های تخصصی

Managing supply chain operations in a reliable manner is a significant concern for decision-makers in competitive industries. In recent years consumers and legislation have been pushing companies to design their activities in such a way as to reduce negative environmental impacts more and more. It is therefore important to examine the optimization of total supply chain costs and environmental impacts together. However, because of the recycling of deteriorated products, the environmental impacts of deteriorating items are more significant than those of non-deteriorating ones. The subject of supply chain of deteriorating products, simultaneously considering costs and environment has gained attention in the academia and from the industry. Particularly for deteriorating and seasonal products, such as fresh produce, the issues of timely supply and disposal of the deteriorated products are of high concerns. The objective of this paper is to develop multi objective mathematical model and to propose a new replenishment policy in a centralized supply chain for deteriorating products. In this model, the manufacturer produces a new product and delivers it to a distant market, and then the distributor buys the product and sells it to the end consumers. This study presents a new mathematical model of the location-routing problem (LRP) of facilities in supply chain network (SCN) for deteriorating products through taking environmental considerations, cost, delivery time and customer satisfaction into account across the entire network and customer satisfaction. In order to solve the model, the combination of the two red deer algorithm (RDA) and annealing simulation (AS) was proposed. We then perform the network optimization in SCN and provide some managerial insights. Finally, more promising directions are suggested for future research.

People capability maturity model (PCMM) is a framework to help develop the level of maturity and improve the field of human resources of organizations. The present study is conducted with the aim of designing and validating an indigenous PCMM for managers among faculty members of the Islamic Azad University of Fars Province. First, the initial indicators are extracted through literature review, then the interview questions are designed and approved by 3 experts. After that, semi-structured interviews are conducted with 17 faculty members who, in addition to having executive records over 5 years, also are assistant professors and above. The sampling method is purposeful snowball. Data analysis is done based on Strauss and Corbin grounded theory model in 6 paradigms of causal conditions, main phenomenon, intervening conditions, context, strategies and consequences. The results of data analysis obtained during 3 open, axial and selective coding processes lead to the extraction of 29 indicators and 98 components. Then, using the obtained variables, a questionnaire is designed and distributed among faculty members, and data are collected and indicators are ranked using confirmatory factor analysis, based on which an indigenous model is presented. Validity and fitting of the model is measured through structural equations using PLS software. The results of validation show that the model has a high validity. According to the discussions and conclusions, one of the research suggestions in increasing the maturity and capability of faculty members can be holding perpetual training courses for managers, which should be implemented by teachers who have a brilliant record in human resource management.

As a vital practice in human resources management, workforce planning determines that the organization is needed how many workforces, when, and which position. Workforce planning is not formed in a vacuity, and job variables such as skill, ability, and knowledge affect the planning. This study examines workforce planning in the health sector concerning the workforce's flows such as recruitment, promotion, degradation, fired, retention, and termination of the contract according to the skill audit and the role of performance appraisal results in this program. For this purpose, a dynamic model has been applied that can provide optimal answers to the number of workforces required and the workforce's flows at any time during the planning periods. This model has been implemented in a hospital ward with two levels of hierarchy: nurses, supervisors, and nursing directors. The results show that the designed system can converge the existing values to the optimal values by noting delays by the optimal control model.

Planning for economic sections and industrial activities at a regional level requires a proper understanding of a region’s potentials. The present study applies product space theory, network science, and information on Iranian provincial production structure to outline a roadmap for industrial development of Kermanshah. Analysis of mean value added and population of Iranian provinces in 2014 to 2018 indicated that of the 32 activities examined, Kermanshah has a revealed comparative advantage in five areas (agriculture and horticulture, traditional husbandry, apiculture, sericulture, and hunting) and other agricultural areas, forestry, and chemicals, with latent comparative advantage in 11 areas, and no advantage in 16 areas. Next, greedy, majority, high degree, and low degree strategies were combined with Borda’s and Copeland’s approaches to identify 11 activities for activation prioritized as follows: poultry, fishing, food, base metal, machinery & equipment, wood industry, other non-metal minerals, pharmaceuticals, metals, appliances, and rubber and plastic products.

The arrangement of machines and how to move them is one of the most important issues in factories and production units, which always imposes a lot of costs on the collections. Although the arrangement of machines is done once over a long period of time, its effects are very widespread. Accordingly, it is necessary to pay more attention to the matter of arrangement. Today, cellular production is also one of the widespread production methods at the industrial level, which requires this precision. The current research aims to produce new arrangements by using artificial neural networks. The way of working is that by using the data related to the number of production parts, the production time of each part, and the group of parts under investigation, as well as the costs of the devices, this clustering is done in 3 modes of 4, 6, and 9. Performing this type of clustering has higher accuracy and speed than other methods, and the results may be somewhat different in each scenario and with each clustering time, which increases flexibility in selection.

Investing in stocks is fraught with long risks that make it tough to manage and predict the choices out there to the investor. Artificial Neural Network (ANN) is a popular method which also incorporates technical analysis for making predictions in financial markets. The purpose of this work is an applied study which is conducted using description based on testing as method. The discussion is established on analytical-computational methods. In this research, the documents and statistics of the Tehran Stock Exchange are used to obtain the desired variables. Descriptive statistics and inferential statistics, as well as Perceptron multi-layer neural networks are utilized to analyze the data of this research. The results of this research show the confirmation of the high prediction accuracy of the Tehran Stock Exchange index compared to other estimation methods by the presented model, which has the ability to predict the total index with less than 1.7% error.

The present study aimed to investigate the impact of organizational entrepreneurship on improving competitive advantage with the mediating role of innovation. The present study was applied in terms of aim, descriptive-survey in terms of data collection method, and quantitative in terms of type of data collected. The statistical population of the study included 75 executive managers of companies operating in the start-up digital industry. Using a convenience random sampling method and Cochran's formula, 63 people were considered as the sample size. Data were analyzed using Smart PLS software. The results obtained from path coefficients and significant coefficients showed that organizational entrepreneurship and competitive advantage have a significant and positive effect on the innovation of start-up digital industries. It was also concluded that organizational entrepreneurship has a positive and significant impact on competitive advantage. It was also found that competitive advantage could mediate the relationship between organizational entrepreneurship and innovation.