- Volume:1 Issue:3, 2018
- تاریخ انتشار: 1397/09/05
- تعداد عناوین: 5
The creation of small manufacturing enterprises is considered by many governments and donor agencies, as the key to economic and social development in countries regardless of development level. Furthermore, review of the literature show evidence that SMEs are understood as a source of technology development. At the same time they are vulnerable to a number of restrictions such as access to finances, skilled labor, public support and suffer from survival rate problems. First, this research aims to shed lights on the role that small manufacturing enterprises play in the process of industrial and economic development across provinces of Iran. Second, the status of industrial infrastructure is investigated. The data is used to estimate parametrically and non-parametrically a number of composite infrastructure indices to investigate the capacity, resource, education, credit and capital assets components. Finally based on the findings, lessons and conclusion, guidelines for policy formulation will be suggested. For our study, use of sub-indices and a new composite of Development Infrastructure Index (DII) can help provinces to evaluate their status of industrial infrastructure.Keywords: Small manufacturing enterprises, Development infrastructure Index, Iranian Provinces, Principal Components Analysis
Evaluating the effects of energy and economic growth on Carbon dioxide emission (using spatial panel data)Pages 27-42
Energy is one of the most important inputs in production. Energy usage and energy diffusion of fossil fuels in process of production cause greenhouse gases (CO2) emission and destruction of environment. According to the importance of issues like energy usage and economic growth, this paper, concerning the effects of proximity, evaluates the effects of energy usage and economic growth on emission of Carbon dioxide (CO2) in MENA Zone countries during the period of 1994-2013. In every country, greenhouse gases (CO2) emission is the function of not only domestic factors but also economic activities of neighboring countries.
The results of the model estimation indicate that proximity effect is verified in the model studying on. Also, the results show that log variable of energy usage has positive and significant effect on CO2 emission. Log variable of income per capita affects CO2 emission positively and significantly, and square log variable of per capita income has negative and significant effect on dependent variable. So environmental Kuznets hypothesis is rejected in MENA Zone.Keywords: Energy Usage, Economic Growth, Carbon dioxide emission, spatial panel data
The competitive market and declined economy have increased the relevant importance of making supply chain network efficient. This has created many motivations to reduce the cost of services, and simultaneously, to increase the quality of them. The network as a tri-echelon one consists of Suppliers, Warehouses or Distribution Centers (DCs), and Retailer nodes. To bring the problem closer to reality, the majority of the parameters in this network consist of retailer demands, lead-time, warehouses holding and shipment costs, and also suppliers procuring and stocking costs all are assumed to be stochastic. The aim is to determine the optimum service level so that total cost could be minimized. Reaching to such issues passes through determining which suppliers nodes, and which DCs nodes in network should be active to satisfy the retailers' needs, the matter that is a network optimization problem per se. Proposed supply chain network for this paper is formulated as a mixed integer nonlinear programming, and to solve this complicated problem, since the literature for related benchmark is poor, three ones of GA-based algorithms called Non-dominated Sorting Genetic Algorithm (NSGA-II), Non-dominated Ranking Genetic Algorithm (NRGA), and Pareto Envelope-based Selection Algorithm (PESA-II) are applied and compared to validate the obtained results.Keywords: Supply Chain Management, Tri-Echelon Network, Mixed-Integer Nonlinear Programming, NRGA, NSGA-II, PESA-II
Relationship between Job Satisfaction, Job Performance and Team Identity: An investigation of the Mediating Role of the Corporate IdentityPages 73-87
This study examined the role of team identity on job satisfaction and job performance regarding the mediating role of the organizational identity. This paper is a correlation type using descriptive methods with applied goals. Our statistical population included all 420 male and female staffs of the telecommunication department in Eastern Azerbaijan province, Iran in 2014.Using stratified random sampling, a sample size of 180 people was achieved. Data was gathered through a standard questionnaire of job satisfaction by Brifield and Roots, job performance by Paterson, team identity, and organizational identity by Vandick et al. For evaluating the correlation of latent and observed variables in conceptual pattern, structural equations were used. The results showed that the team identity and organizational identity and job satisfaction and performance hade had positive and significant correlation. Also, there was no significant correlation between team identity and job satisfaction and performance. The correlation between team identity and job satisfaction and performance was also mediated by the organizational identity. Based on the results, the team identity improved the organizational identity. As the organizational identity improved, job satisfaction and performance of the staffs of the telecommunication department increase.Keywords: Team identity, organizational identity, job satisfaction, job performance.
Fundamental and technical analyses are two common methods for predicting the future behavior of the stock. Fundamental analysis focuses on the economic forces of supply and demand which cause stock prices change. On the other hand, technical analysis examines historical data relating to changes in the price and trading volume by using graphs and indicators as a primary tool to predict future price movements.
In this paper a model has been provided for selecting the right portfolio in stock exchange. Financial industries ranking and companies ranking have been applied for the selection of the right stock in this model. These rankings have been done through the PROMETHEE decision making method. Technical Analysis has been done for determining the right time to buy and to sell the superior stocks. A survey has been done for determining the effective criteria over industry and company evaluation. The developed model has been applied in Tehran Stock Exchange (TSE) as a real case and a real problem has been solved.
It is concluded that by using both Fundamental and Technical Analysis, an investor can get higher return on stocks instead of using just one individual analysis. In other words, while fundamental analysis distinguishes which stocks to buy, technical Analysis shows when to buy the superior stocks. Finally, some important and most commonly used indicators have been extracted. These indicators can be used by investors to consistently and correctly predict the future stocks prices.Keywords: fundamental analysis, technical analysis, stocks ranking, stocks trading, multi- criteria decision making, PROMETHEE method