Sector In Iran Research Articles

A robust LINMAP for EFQM self assessment

Article history: Received 30 July 2010 Received in revised form 14 November 2010 Accepted 16 November 2010 Available online 22 November 2010 During the past two decades, there have been tremendous efforts on developing efficient business excellence models to improve the quality of organizations. A typical business excellence model proposes several alternatives with different budget and the primary objective is to use the best ones. In this paper, we present a robust LINMAP method for measuring the relative importance of various alternatives in an EFQM self assessment. The presented robust model is capable of handling uncertainty as part of the problem formulation. The proposed model of this paper is implemented for a case-study of energy sector in Iran with various alternatives. The orderings of the alternatives are measured using data from multiple experts through applying the proposed model of this paper. © 2011 Growing Science Ltd. All rights reserved.

The Impact of Human Resource Information System on Strategic Decisions in Iran

Purpose – The purpose of this paper is to examine the impact of Human resource information system (HRIS) on strategic decisions. Design/methodology/approach – The papers develops a research model based on current literature and then test this model in Mellat and Parsian banks selected from 19 banks with 18000 branches, public and private sectors in Iran. Statistics society consists of 172 persons include assistant of general managers in both personnel affairs and welfare and domestic payments department in Mellat bank, and also professionals, managers and deputy of personnel affair and department of organisation and methods in Parsian bank. The sample size provided based on Cohan- Morgan- Korjsay is 108 persons which has been determined with descriptive methods. For data analyzing we used Chi- square test, Binomial test, and Kendall's tau- b test. Findings – The results indicate that, on average, few differences exist between Mellat and Parsian banks. Moreover, we found that the HRIS is effective on strategic decisions in both banks. Research limitations/implications – This study could benefit from a large sample, from public and private banks and replication in more branches. Practical implications – The paper offers practical suggestions to the banking industry and management in general on how to manage the HRIS effects on strategic decisions. Originality/value – This paper has tried to provide an inclusive understanding about the HRIS effects on strategic decisions in the banking industry. Since there was a lack of such research in an Iranian context, this paper can provide theoretical basis for future researches as well as practical implications for managers and the human resource (HR) professionals.

Investigating the effects of targeting subsidies on macroeconomics variables of agricultural sector in Iran

The aim of this study is simulating the results of targeting subsidies on macroeconomics variables of agricultural sector in Iran. In order to achieving the objectives of this study, a multi-sector computable general equilibrium model with five quintiles of rural and urban households is developed to analyze the results of elimination and redistribution of subsidies according to the law of targeting subsidies in Iran. The results show that during targeting, high income and average income groups lose. Income rising (in the case of quintiles which their income rise) causes to increasing demand of agricultural products, food products and services in both urban and rural households. The level of factor demand in agricultural and food industrial sectors increases. Income of unskilled labours increase more than income of skilled labours. The produced commodities of petroleum, industrial and mineral sectors will be expensive and the other commodities will be cheap. The level of production in agricultural and food industrial sectors increase and in the other sectors decrease. Agricultural, food industrial and services exports rise and petroleum, industrial and mineral exports reduce. Agricultural imports increase and the level of imports in other sectors decrease. Key words: Targeting subsidy, computable general equilibrium, agriculture, Iran.

The adoption of new and innovative knowledge by small and medium enterprises of Iran: Opportunities and constraints for growth

The purpose of this article was to explore the capacity of Small and Medium Enterprises (SMEs) in absorbing and managing knowledge as a prior condition to innovations and entrepreneurial growth. Drawing the findings from more than 1,500 SME owners/ managers of the ICT sector in Iran, across regular quarterly Small Enterprise Research (SER) team surveys and from other large scale studies, this article examined the effects of experiential and formal knowledge on the development of SMEs absorptive capacity. The mixed method (explanatory type) was used as the research method. There were significant effects, such as age, education and size (of what) influence SME acquisition and assimilation of knowledge. Primarily, it was the small firms with 15 employees or less that had the capacity to absorb and use new knowledge, especially those with higher educational levels and cleared growth objectives. These firms were not startups, but tend to be younger firms with younger founders. Given the main policy aim, of what, was the development of clusters and knowledge-based firms, policy makers should focus on SMEs that are recently started by graduates or people with technical qualifications. As such, educators need to develop technology and innovation management programmes for these firms. This article made an important contribution to the identification of priorities for public SME development support and areas where business schools and enterprise trainers could maximize their economic and developmental impact. Key words: Innovation, entrepreneurialism, knowledge management, small enterprises research paper.

Opportunities of GHGs emission minimization through processes improvement in Iranian oil industries

Abstract Iran is located in dry and arid region. This country faces to shortage of water resources for drinking and agriculture. Increasing of earth temperature causes direct and negative effects in different economical sectors in Iran. Therefore department of environment (DOE) is established some programs for GHGs emission reduction. According to these programs GHGs emission in Iranian energy sector must be reduced about 30 percent. Now, GHGs emission per GDP (kg equal CO2 per GDP) index in Iran (3.07 kg CO2/2000US$) is more than world average (0.73 kg CO2/2000US$) and Asia average (1.26 kg CO2/2000US$). Also emission factor of CO2 in Iranian oil refineries is about 3.5 times more than European ones, like England. Hence, the main goal for GHGs reduction in Iran is achievement to Asia average level. Since, potential of GHGs emission reduction is estimated about 67 million tones equal CO2 at 2025 in oil sector. The major part of this reduction is related to petrochemical complexes. It should be considered that the most of these industries are old and worn out, so there are several effective techniques for their GHGs emission reductions. Also cost of tone CO2 reduction in Iranian oil sector is very lower than same industries with new technologies. For this purpose, Naphtha hydrotreating unit of Abadan oil refinery and wastewater treatment plant and waste incineration furnace of Tondgouyan petrochemical complex are selected as case studies. Gained results showed that by process changing in Naphtha hydrotreating unit from once-through system to recycle system, the gas burning will reduce to 10.6 million kg per year. Also injection of produced methane (from anaerobic reactors of wastewater treatment plant) to waste incineration furnace, about 1.75 million cubic meter will saved due to prevention of gas sending to flare. All mentioned results reveals that GHGs reduction is possible via detection of energy losses and process problems in all units of refineries and petrochemical complexes. Obviously, expanding of economical relationships with developed countries and application of some mechanisms such as CDM can be very important and effective.

Effect of nuclear power on CO2 emission from power plant sector in Iran

It is predicted that demand for electricity in Islamic Republic of Iran will continue to increase dramatically in the future due to the rapid pace of economic development leading to construction of new power plants. At the present time, most of electricity is generated by burning fossil fuels which result in emission of great deal of pollutants and greenhouse gases (GHG) such as SO₂, NOx, and CO₂. The power industry is the largest contributor to these emissions. Due to minimal emission of GHG by renewable and nuclear power plants, they are most suitable replacements for the fossil-fueled power plants. However, the nuclear power plants are more suitable than renewable power plants in providing baseload electricity. The Bushehr Nuclear Power Plant, the only nuclear power plant of Iran, is expected to start operation in 2010. This paper attempts to interpret the role of Bushehr nuclear power plant (BNPP) in CO₂ emission trend of power plant sector in Iran. In order to calculate CO₂ emissions from power plants, National CO₂ coefficients have been used. The National CO₂ emission coefficients are according to different fuels (natural gas, fuels gas, fuel oil). By operating Bushehr Nuclear Power Plant in 2010, nominal capacity of electricity generation in Iran will increase by about 1,000 MW, which increases the electricity generation by almost 7,000 MWh/year (it is calculated according to availability factor and nominal capacity of BNPP). Bushehr Nuclear Power Plant will decrease the CO₂ emission in Iran power sector, by about 3% in 2010.

A system dynamic model for production and consumption policy in Iran oil and gas sector

A system dynamic model is presented, which considers the feedback between supply and demand and oil revenue of the existing system in Iran considering different sectors of the economy. Also the export of the oil surplus and the injection of the gas surplus into the oil reservoirs are seen in the model by establishing a balance between supply and demand. In this model the counter-effects and existing system feedbacks between supply and demand and oil revenue can be seen considering different sectors of the economy. As a result, the effects of oil and gas policies in different scenarios for different sectors of Iran’s economy together with the counter-effects of energy consumption and oil revenue are examined. Three scenarios, which show the worst, base and ideal cases, are considered to find future trends of major variables such as seasonal gas consumption in power plants, seasonal injected gas in oil reservoirs, economic growth in the industrial sector, oil consumption in the transportation sector, industrial gas consumption and exported gas. For example, it is shown that the exported gas will reach between 500 and 620 million cubic-meter per day in different scenarios and export revenues can reach up to $500 billion by 2025.

To Determine the Challenges in Commercialization of Nanotechnology in Agricultural Sector of Iran

To Determine the Challenges in Commercialization of Nanotechnology in Agricultural Sector of Iran

Prediction of added value of agricultural subsections using artificial neural networks: Box-Jenkins and Holt-Winters methods

Added value of agricultural sub sectors is affected by many factors such as quantity production per agricultural sub sectors and selling price of producers and is related to some factors such as government investment and monetary and financial policies. This study examines the performance of artificial neural network, Box-Jenkins and Holt-Winters-no-seasonal models in forecasting added value of agricultural sub sectors in Iran. It compares error criterions for determining the best model. Results showed that Box-Jenkins and artificial neural network are appropriate and artificial neural network indicated good result relatively in learn stage, but Box-Jenkins model gave better results in forecasting of unseen data. Holt-Winters model had the lowest mean absolute percent error in both of model fitting and model validation stages. Key words: Artificial neural network, Box-Jenkins, Holt-Winters, added value of agricultural sub sectors.

Efficiency Measurement of Housing Sector in Iran

The present research provides a critical review of the housing industry efficiency and its future in Iran. Data Envelopment Analysis (DEA) is used to evaluate housing industry performance in different states based on the relevant data collected from Statistical Centres of Iran during 2006-2009. The research found that only 30 percent of the states operate as technically efficient and the average efficiency score obtained by all states is 0.90. Most of the technically efficient states have the opportunity to employ illegally migrated workers of neighboring countries in building construction activities using the advantages of lower level of payments and less commitment to the worker's insurance regulations in the country. Providing subsidy assistance to disadvantaged states and stimulating legal employment of building workers will supplement the government in finding a solution to the current housing problem.

Lisrel Analysis of Factors for Empowering Producers to Abolish Livelihood Poverty through Optimizing Agricultural Water Resources Management

Problem Statement: Most of the projected increase in global population will take place in third world countries that already suffer from water, food, and health problems. Irrigation in developing countries tends to be stereotyped as equity reducing, in competition with other uses for scarce water resources. Agricultural intensification through the practice of irrigation as a strategy for poverty reduction is examined. Water users were surveyed in order to explore their perception about the factors influencing the optimizing water consumption in agricultural sectors in Iran. This study looks into water-poverty interfaces as well as into approaches to and tools of, managing water in such a manner that water sector activities can contribute to alleviation of poverty. In addition, this study aims to empower water users with information on agricultural wastewater. Approach: The methodology used in this study involved a combination of descriptive and quantitative research. The total population was 350 producers in six provinces in Iran. Results: Based on the perception of the respondents and ordinal factor analysis, the factors were categorized into four group’s namely technical and practical, recognition and managing water equipment and constructive ordered by the magnitude of their impact. The total variance explained by these 4 factors is 54.27% as effective mechanisms in optimizing agricultural water resources management. Structural equation model is expected to be useful for designing targeted optimizing agricultural water resources management and poverty alleviation strategies that also enhance agricultural-productivity growth. Conclusion/Recommendations: Where there is equity in resource distribution, the impact of improved water management on agricultural productivity growth has been more poverty reducing. Using water better means improving the productivity of agricultural water in both irrigated and rainfed systems, through multiple-use water system, integrated water resources planning, and targeted research.

The Impact of Improvement in Iran Iron and Steel Production Technology on Environment Pollution

Iron and steel industry is the most energy intensive sector in Iran's economy. In recent years this industry has experienced a high rate of growth. So it is expected that the growth of energy consumption in this industry and its environmental pollution will increase quickly in future. Thus, the estimation of long run energy consumption in iron and steel energy intensive industry and its environmental pollution, specifying the potentialities of energy saving as a result of technological progress in this industry, and analyzing of the impact of improvement in production technology in iron and steel industry on environment; seem to be considerably crucial. These subjects are analyzed in this paper using a techno - economy model. The finding of executing Model for Energy Demand Evaluation (MEDEE), reveals that through utilization of improved production technology in iron and steel industry, the level of energy consumption in this industry reduce about 13.5 and 45.8 MBOE in 2015 and 2025 respectively. So, the environmental pollution as the result of this reduction in energy consumption in iron and steel industry, is very considerable.

An analysis of the sources of technical change in the agricultural sector of Iran

A differential structural equation system including latent variables was applied for analyzing the sources of technical change in the agricultural sector of Iran, 1971–2005. The findings indicated that international knowledge spillover, human capital, and internal research and development expenditures have a significant role in technical progress in the agricultural sector of Iran. The findings showed that international knowledge spillover has been a more effective factor on the technical progress related to internal R&D. The technical progress was found out to be Hicks-neutral.

Financial Markets Barriers’ in Agricultural Sector: Empirical Evidence of Iran

This paper aims to examine the relationship between financial market development and agricultural sector in Iran. The study attempts to answer these questions empirically and try to shed some light on the roles of financial development as well as other conditional variables in agricultural sector. The results of this study shows that the financial market in agricultural sector, however there is some weakness still. The authors come to conclusion that for improving this vital sector in Iran the weakness should be removed or at least reduced as early as possible.

Modeling and estimation of the natural gas consumption for residential and commercial sectors in Iran

In this paper, a logistic based approach is used to forecast the natural gas consumption for residential as well as commercial sectors in Iran. This approach is relatively simple compared with other forecasting approaches. To make this approach even simpler, two different methods are proposed to estimate the logistic parameters. The first method is based on the concept of the nonlinear programming (NLP) and the second one is based on genetic algorithm (GA). The forecast implemented in this paper is based on yearly and seasonal consumptions. In some unusual situations, such as abnormal temperature changes, the forecasting error is as high as 8.76%. Although this error might seem high, one does not need to be deeply concerned about the overall results since these unusual situations could be filtered out to yield more reliable predictions. In general, the overall results obtained using NLP and GA approaches are as well as or even in some cases better than the results obtained using some older approaches such as Cavallini’s. These two approaches along with the gas consumption data in Iran for the previous 10 years are used to predict the consumption for the 11th, 12th, and 13th years. It is shown that the logistic approach with the use of NLP and GA yields very promising results.

Regional Dimensions of Economic Development in Iran - A New Economic Geography Approach

This paper presents a spatial analysis of the regional dimensions of poverty and economic development across provinces of Iran. It offers one of the few estimations made in developing countries using this strand of New Economic Geography (NEG) models and provides a comparison of the results for Iran with those in previously studied developed countries. The goal of this study is to offer an analysis of the effects of agglomeration and dispersion economies on the patterns of regional economic development in Iran based on the empirical estimation of two of the NEG models. First, it presents an estimation of a Market Potential Function (MPF), in which wages are associated with proximity to consumer markets. Second, it estimates an augmented MPF derived from the Krugman model of economic geography that estimates the importance of transportation costs and economies of scale. The estimation results suggest that Iran shows a generally good fit to both models, satisfying their specifications. Compared to similar studies of developed countries, Iran shows smaller returns to scale. This might be a result of the nature of the technologies used in the non-farm private sector in Iran, which is less industrial and more traditional. Dispersion and decentralization of industries to achieve lower income inequality between provinces would create a level of loss, but less losses than they would be in Western countries. The paper also found a significantly and consistently greater effect of market potential on wages in comparison to the effect estimated in similar analyses of other countries. This might be a result of the country relying on an underdeveloped transportation system between provinces in Iran. It is also a highly mountainous and geographically diverse country. The overall result of this study corroborates the notion of centralization in the Iranian economy. The large wage variations explained by economic geography could cause significant internal migration, beyond that seen in western countries. Indeed, significant internal migration has been observed in Iran in past years.

The economic impacts of drought on the economy of Iran: An integration of linear programming and macroeconometric modelling approaches

In this paper, we provide economy-wide estimates of the costs of drought in the cropping sector of the Iranian economy, using a linear programming model to estimate the direct costs on agriculture, and a macroeconometric model to trace the indirect impacts on the rest of the economy. The results indicate that a severe drought such as the one that occurred in the crop year 1999–2000 imposes a direct cost of 1605 million USD, equivalent to 30.3% of the total value added of the cropping sector in Iran. This, in turn, leads to a 12.7% reduction in the value added of other agricultural sub-sectors (livestock, fisheries and forestry). In the rest of the economy, the manufacturing and service sectors experience value added declines of 7.8 and 3.7%, respectively. In addition, there is a substantial decrease in investment in the agricultural, manufacturing and service sectors. Thus, such a drought reduces overall GDP by about 4.4%, and it would also result in decreased non-oil exports, increased food imports, and a rise in inflation. The results of some drought mitigation simulations are reported in brief. Such estimates strengthen the case for increased attention to drought strategies and management in agriculture in Iran and elsewhere.

A novel fuzzy linear regression model based on a non-equality possibility index and optimum uncertainty

Various kinds of fuzzy regression models are introduced in the literature and many different methods are proposed to estimate fuzzy parameters of the models. In this study, a new approach is introduced to find the parameters of a linear fuzzy regression, with fuzzy outputs, the input data of which is measured by crisp numbers. Based on a non-equality possibility index, a new objective function is designed and solved, by which a minimum degree of acceptable uncertainty (the h-level or h-cut) is found. Four numerical examples are presented to compare the proposed approach with some other methods. Results show superiority of the new approach based on the criterion used by Kim and Bishu in the cases studied here. A realistic application of the proposed method is also presented, by which the total energy consumption of the Residential-Commercial sector in Iran is modeled using three variables of the GDP, number of the Households and an Energy Price index as inputs (exogenous variables) to the model.

Oil demand in transportation sector in Iran: an efficiency and income asymmetric modelling approach

AbstractThe transportation sector in Iran consumed about 52 per cent of oil demand in 2005. This high consumption rate of oil in the sector is fuelled by many factors including fiscal policies structural, as well as infrastructural factors. The vehicle ownership (intensity), efficiency of vehicles, public transportation, transport infrastructure, per capita income, cost of vehicle use, and fuel prices are among the factors which are shaping the trend of oil demand in this very important sector. Energy in Iran is heavily subsidized and in the transportation sector, the subsidy amounted to $3.59 billion in 1996, rising to $12.43 billion in 2005.Logistic model of vehicle ownership is estimated as a function of real per capita income, length of roads and other explanatory variables. Per capita income is a cumulative non‐declining variable incorporating the idea of income asymmetric. Oil demand is estimated as a function of fuel efficiency, age of car fleet, per capita income and vehicle ownership per 1,000 inhabitants. Oil demand elasticities of vehicle ownership and fuel efficiency are 1.29 and 1.11, respectively, confirming that these variables have major impacts on oil demand in the transportation sector. It is concluded that rationing of fuel or upward price adjustment merely cannot curb the fast growth of oil demand in the sector. A policy package including mandatory fuel efficiency standards, scraping of old vehicles, upward fuel price, and development of public transportation could lead to better management of fuel consumption in this sector.

Trade, industrialization and the firm in Iran: the impact of government policy on business

This book seeks to find out how government interventions affect the performance of an economy. It develops notions on trade, industrial sector, and firms and examines them for the case of Iran. The analyses suggest that the excessive interventions of the Iranian government in trade and industrial sectors resulted in small benefits at high costs. Government interventions, for example, reduced the incentives of firms to undertake technological investments. They rather invested to increase their political competencies and aimed at short-term profits. Low technological investment is argued to have been one of the major reasons behind the poor performance of industrial sector in Iran.