جستجوی مقالات مرتبط با کلیدواژه « کارایی » در نشریات گروه « مدیریت »

Organisational Citizenship Behaviour (OCB) is one of the important concepts that has been used as an effective factor in the success of organisations in recent years. Despite the proven effect of OCB on the effectiveness and efficiency of the organisation, the appropriate method to determine the extent of its effect is less known. OCB is a qualitative indicator as an output in performance evaluation. In this article, we measure the effect of the OCB quality index on the efficiency of institutions using the envelopment analysis method of ordinal data without compensatory properties.

Data coverage analysis is a powerful tool for assessing the performance of decision-making institutions based on a large number of input and output indicators, which can be quantitative or qualitative. Data coverage analysis models have compensatory properties, i.e. the weakness of one index is covered by the strength of another, and efficient institutions do not necessarily have a favourable quality level. This article presents a new method for performance evaluation that includes the quality index of OCB and a modification of the data envelopment analysis model without compensability. Another feature of the proposed model is the ability to separate qualitative and quantitative indicators in the evaluation. In the presented method for ranking institutions, the improvement of quality is considered simultaneously with the reduction of costs without compensability.

In this study, ten public and applied scientific institutions in three cities of the country were evaluated with the proposed model. Four quantitative indicators and one qualitative index of OCB were used in the evaluation.

Originality/Value: 

The OCB index was measured using 1024 questionnaires and the results show the efficiency of 7 institutions. Then, by using the proposed new method, the ranking of institutions with logical results in performance evaluation was achieved. To validate the method, the results of the proposed method were compared with the ranking results of the hierarchical process method.

A significant part of the the capital of the leading organizations has been attributed to the considering human resources in recent years. The knowledgeable and capable managers know that the more they provide the prerequisites for progress and promotion of human resources, the more they guarantee the success, efficiency and superiority of their organization before other organizations. The most efficient way for achieving high competitive advantage and the most important superiority index according to tremendous changes in the economic conditions is empowering and making efficient the human resources in organizations. Human resource is the most important capital of the organizations. The purpose of this research is to propose a model of efficiency of investment in human resources. The statistical population consisted of all companies listed in Tehran Stock Exchange. The research method is descriptive and survey. The statistical sample included 155 companies selected via available sampling method. The data were collected by author-made questionnaire based on Likert scale. Kolmogorov- Smirnov test was used for normality test and structural equations modeling was employed for hypotheses test. The results showed that the quality of financial disclosure, human capital disclosure, improvement of business environment have a positive and significant impact on human resources.

Since the healthcare system is one of the most important pillars of community health, and considering that providing healthcare services to the people is one of the elements of individual development in any country, attention and supervision of this sector can lead to development and social welfare. To ensure better and higher quality healthcare services, performance evaluation in the health sector plays a crucial role. In order to achieve this, proper and proportional use of existing facilities and assets is inevitable. In this study, by introducing an application in the field of healthcare systems, the educational hospitals of the country have been measured in terms of performance and their managerial ability has been calculated. Additionally, by identifying and introducing the impact of contextual variables on the performance of decision-making units, their efficiency has been assessed. For this purpose, data related to educational hospitals in 31 provinces of the country was collected, and then by identifying contextual variables and with the presence of undesirable factors, the efficiency was evaluated and the managerial ability of each was calculated. To reach this goal, in the first step, technical efficiency with the presence of undesirable factors was calculated using data envelopment analysis technique, and then the logarithm of technical efficiency obtained from the first stage was regressed on a set of contextual variables that affect hospital performance. In the next stage, managerial ability was extracted from the residual of the regression obtained from the previous stage. Finally, a unique ranking based on the managerial ability of each unit was provided. Ultimately, the results obtained were analyzed and examined in order to provide valuable suggestions for managers and more efficient management of the country's hospitals to maintain public health. According to the study, without considering contextual variables, 25 effective units were evaluated, but by applying the effect of contextual variables on the efficiency index, no unit becomes effective, proving the high impact of such indices on the performance of units. Additionally, in the ranking of units based on managerial ability, Lorestan province ranked first and Golestan province ranked last.

One of the important issues that has attracted the attention of economists over the past decades is the role of financial systems in the economic growth of countries. Insurance industry is one significant component of financial markets. Therefore, the stability and efficiency of insurance industry as a financial market sector is important for a country's economy. One of the most crucial changes in Iran's insurance industry is the regulations having been made in recent years. One main goal of regulation is to eliminate problems of market failure and improve efficiency. This research investigates the effect of these regulations on the efficiency of insurance companies in Iran.

The studied community is 27 insurance companies in the country and the relevant statistics were collected for the years 1385-1400 Persian Year (2005-2020). This study was conducted in two stages. In the first stage, the efficiency of insurance companies has been measured, using the method of data envelopment analysis (DEA) with the bootstrap approach. The implicit assumption of the traditional data envelopment analysis method is that the inputs and outputs are definite. But the output of an insurer is not necessarily certain. To solve this problem, we can use the bootstrap approach to obtain statistical characteristics for this technique. In the second stage, in order to investigate the effect of regulation on efficiency, according to the reviewed studies, the purpose of the present study, and the conditions of Iran's insurance industry, the effective factors on efficiency are determined and the regression model is defined. Then, the dynamic regression model was estimated using the generalized method of moments (GMM) and the related tests confirmed the validity of the results of the model. To calculate the efficiency and estimation of the model, MATLAB and Eviews software were used.

The most important finding of the research is the significant effect of regulation on efficiency. Also the coefficient of regulation, market share, and privateness of insurance companies are estimated as -0.066, 0.041 and 0.306 respectively.

The results of the research show that regulation had a negative effect on the efficiency of insurers and led to a decrease in their efficiency, but the market share and the privateness of insurance companies had a positive effect on the efficiency. In the end, suggestions for improving the efficiency of insurers have been presented.

One of the models that is used to measure the efficiency and decision support is DEA, but considering all the merits, it also has its own limitations, which has led to the idea of combining it with artificial neural networks. ANN is increasingly used in model and data-based approaches to enrich analytical and predictive capabilities and thus improve decision-making. The present research presents a model for evaluating the efficiency of units by integrating neural networks. The studied sector is the active pharmaceutical industry in the Tehran stock market. To create the model, the efficiency of 4 DEA models on a variable scale, including input-oriented and output-oriented BCC model, SBM model and RAM model during the years 2018 to 2022 was calculated in GAMS. The efficiency values of these four models were ANN'S education vector. Also cost, income and profit data from 2018 to 2022 was entered into MATLAB as ANN'S input. To generalize education, the data of 2023 was used. The results showed that the trained efficiency boundary shows a more comprehensive and accurate approximation of efficiency for the ranking of pharmaceutical companies. The results of this research will help pharmaceutical companies in the fields of investment, resource allocation, predicting the results of policies and planning.

This research is organized with the aim of designing a dynamic model to evaluate the effectiveness of social capital in the insurance industry using the method of content analysis, which in terms of purpose is practical and in terms of the method of collecting information, it is a part of qualitative research. The statistical population consists of insurance industry experts and managers of Iran's social security insurance branches in Tehran. For sampling in this research, the purposeful sampling method, which is non-probability sampling, was used. In addition, after collecting the information, the codes related to the written interviews were analyzed using thematic analysis method. The credibility of the research was obtained through the agreement of experts and validity with the help of consensus of opinions and face validity. Qualitative data analysis in this study was done with thematic analysis method. ATLAS TI software was used for qualitative content analysis. Also, by examining the data obtained from the text, 1 overarching theme, 5 organizing themes, and 21 basic themes were extracted. The results showed that all the themes identified from Expert opinions are relevant and there is favorable consensus about their importance.

Banks, as key participants in the financial market, play a crucial role in expediting production processes and driving economic growth. They achieve this by gathering savings and idle liquidity, and channeling these resources into vital economic sectors. Enhancing efficiency and performance is a primary management objective for these institutions, as it leads to improved productivity. However, given the multitude of indicators and criteria used to assess efficiency, it is essential to identify and employ appropriate indicators based on specific guidelines. This study adopts an analytical-descriptive approach, collecting data from 2014 to 2019 through documentary research and surveys. The goal is to identify the influential indicators for evaluating the efficiency of commercial banks in Iran, as determined by a panel of experts. These indicators are then prioritized using factor analysis and the Fuzzy Delphi method. The findings reveal the existence of 19 key factors that determine bank efficiency, categorized into 7 main groups. These factors encompass financial, human, environmental and geographical, structural and organizational, physical, technical, and financial ratios. Together, they account for 62.45% of the total variance and serve as the most significant inputs and outputs that explain and determine the efficiency of commercial banks in Iran.

Early models of data envelopment analysis are not suitable for evaluating two-stage structures due to the black box view and lack of attention to internal processes. In these structures, Deriving the efficiency frontier and fairly determining the optimal value of variables is the most important challenge. In many existing two-stage models, the efficiency frontier is not plotted or the optimal value of intermediate variables is determined by one of two steps. This leads to incorrect calculation of the efficiency of the next stage and the total efficiency. In fact, in these models, poor performance of one stage leads to reduced efficiency of the other stage. In this study, by keeping the intermediate variables constant at the current level and with an input-output oriented approach, radial and non-radial models were developed on a constant and variable returns to scale in terms of efficiency. Using mathematical relations, the validity of the models was proved and shown that in the proposed models, the performance of the units in steps is compared with a unit on the efficiency frontier, and the models make the whole structure efficient by bringing the steps to the efficiency frontier. The proposed models were used in an applied study to evaluate the sustainability of nine supply chains of tomato producers. Their performance results were expressed by four models as well as the optimal value of inefficient unit variables in each of these models.

Today, with the rapid spread of the Corona pandemic, problems have arisen for businesses, especially small and medium-sized businesses. On the other hand, marketing capabilities are considered essential in determining the heterogeneous evaluation of product quality for customers, which helps the strategic direction of small and medium-sized businesses in the critical conditions of the Corona pandemic. Hence, the purpose of the current research was to explain the effect of the Corona pandemic on efficiency considering the mediating role of marketing capabilities and strategic orientation. The direction of the research was applied and descriptive in terms of purpose. The statistical population of the research included 2200 managers and senior employees of small and medium-sized businesses in Tehran province, from among whom, a sample of 335 people was recruited using a stratified sampling procedure. A survey method was used for the data collection and PLS method was used for the data analysis. Based on the results, the effect of the Corona disease pandemic on efficiency, marketing capabilities and strategic orientation and the role of strategic orientation on efficiency were confirmed. Moreover, the indirect role of mediating variables of marketing capabilities and strategic orientation in the relationship between the Corona disease pandemic and efficiency was confirmed. However, the effect of marketing capabilities on performance was rejected. This research advises senior managers of small and medium-sized businesses to pay extra attention to strategic orientation and marketing capabilities in order to reduce threats and increase the possibility of survival and take advantage of future opportunities in the post-corona era.

This paper aims to evaluate the response of different countries against Covid-19 for three consecutive periods from January 2020 to October 2022. 16 countries have been chosen based on their differences in various demographic, cultural, and geographical characteristics.

Design/methodology/approach:

 Window Data Envelopment Analysis (DEA) model, Malmquist Productivity Index and DEA with non-controllable input variables have been used over three periods of 345 days to evaluate the efficiency of health systems of the countries. By the Window DEA and DEA with non-controllable input variables, the efficiency of the countries in several different periods has been compared. Also, the scores for the progress of countries' performance during successive periods have been computed by the Malmquist Productivity Index.

The performance scores calculated with the window DEA indicated that there is a difference in the countries' responses. Based on the obtained results, China had the most efficiency and Italy had the worst efficiency during the three periods. Based on the model of uncontrollable variables, Egypt had the best performance, although the model did not distinguish among most countries. The results of the Malmquist Productivity Index method also indicated that countries had different efficiencies and progress. Based on its results, Malaysia had the most progress, while Singapore had the least progress during the three periods. China despite its high-performance score from the window DEA, had not received a good score from the Malmquist Productivity Index and non-controllable input variables model, which implies the low growth and even retrogression of this country during the three periods. According to the results of the window DEA, Italy had progressed, but this growth has not been enough to make this country's performance efficient.

Research limitations/implications:

 The selection of different and more precise time intervals based on COVID-19 variants (alpha, delta and micron) and a wider selection of countries can be considered in future studies. Considering the amount of vaccination or the type of vaccine and observing its effects dynamically on the DEA model can be also a potential direction for future research. The development of window DEA and the Malmquist Productivity Index for uncontrollable variables and their application to the data of this paper are also suggested. Besides, the selection of input and output indicators based on other goals can be investigated in future studies.

Practical implications: 

To increase countries’ efficiency in dealing with epidemics such as COVID-19, different countries need to know as much as possible about their current situation. One of the ways to get this recognition is to compare them with other countries with the best performance. In such conditions, finding relative efficiency and trying to make the inefficient ones efficient is a solution to increase efficiency. It is possible to identify and extract coping strategies from successful countries with good performance in dealing with COVID-19, and suitable strategies can be implemented in Iran according to the required facilities and infrastructure.

Social implication:

 Appropriate reactions and successful strategies of health systems of countries in dealing with epidemic diseases such as COVID-19 can be very effective in controlling such diseases and reducing their negative social and economic impacts. The results of evaluating the efficiency of different countries along with the review of their strategies can be helpful in this direction.

Originality/value: 

An attempt has been made to present a new picture of countries' response to the COVID-19 pandemic by selecting a diverse range of countries, indicators, and relatively long periods using DEA. Windowed DEA, Malmquist productivity index and DEA with uncontrollable input variables in a period of almost three years were used for the first time to evaluate the efficiency of countries' health systems and their progress in dealing with COVID-19.

Recognizing the significance of decisions and decision-making by the Islamic Parliament and their impact on human societies, it is crucial to evaluate the efficiency of different parliamentary terms, identify strengths and weaknesses, and determine influential factors for enhancing future performance. The reformation of the decision-making process is essential as it will result in sound decisions and elevate the political and economic conditions of the country. Thus, the objective of this research is to propose a two-stage data envelopment analysis (DEA) model to evaluate the performance of various periods of the Islamic Parliament (from the third to the tenth period) in terms of legislation and supervision. In the proposed approach, each term of the Islamic Parliament is considered a two-stage decision-making unit (DMU), with legislation as the first stage and supervision as the second stage. The results suggest that, generally, 50% of the periods are efficient, while the remaining 50% are inefficient. Specifically, Periods C, D, G, and H are identified as efficient periods across both dimensions. However, Period B, in terms of overall performance and the supervision dimension, and Period A, within the legislative dimension, are pinpointed as the most inefficient periods. Additionally, an analysis of the average efficiency scores in legislation and supervision underscores that, overall, the Islamic Parliament has demonstrated superior performance in legislation compared to supervision during various periods. This disparity in performance between the supervisory and legislative aspects has led to higher inefficiencies among the periods characterized as inefficient.

Regarding the strategic role and importance of human resources in organizational valuation in modern business space, investment is highly important. Hence, the present study aimed to investigate the effective factors affecting the efficiency of human resources investment in Iranian capital market. This survey study had a descriptive design. The statistical population consisted of all firms listed in Tehran Stock Exchange. The statistical sample included 155 companies recruited through convinience sampling method. A researcher-made questionnaire based on Likert scale was used for collecting the data. Kolmogorov-Smirnov test was used to test the normality of the data and structural equation modeling was employed to test the hypotheses. The results showed that the quality of financial reporting, the quality of profit and financial stability, human capital disclosure, social responsibility reporting, motivational commitment of employees, conservatism in financial reporting, organizational atmosphere and improvement of business environment have a positive and significant effect on the efficiency of investment in human resources.

Cement production in Iran takes place across various geographical locations, each characterized by distinct weather conditions. The technology employed in cement production varies depending on the availability of raw materials, fuel sources, and essential resources like water. Consequently, diverse inputs and outputs assume significance in each production technology, resulting in non-homogeneity among cement factories. Despite these differences, all these facilities are engaged in cement production, warranting a comparative analysis of their efficiency. This study examines the operational processes of five different cement production technologies—dry, semi-dry, humid, semi-humid, and wet slurry—across four companies comprising a total of nine factories. The study evaluates their efficiency between 2017 and 2020 using network data envelopment analysis under non-homogeneous conditions across three modeling stages. An important aspect of this study is its focus on the entire supply chain, from raw materials to the final product. Although the raw materials employed vary among different cement production technologies, the end product remains largely consistent.IntroductionIn certain real-world scenarios, even with similar production technologies, the assumption of homogeneous decision-making units may not hold true. Practical applications often involve supply chain structures that differ significantly from others. For instance, some supply chains may, at certain stages, eject intermediate products to meet specific needs, a phenomenon not universal to all supply chains, resulting in non-homogeneous chains. The cement industry, including Iran, constitutes one of the pivotal economic sectors. Therefore, mitigating shortcomings, including resource and material waste reduction, can have a substantial impact on this industry and consequently on the broader economy. Due to varying climatic conditions, cement production employs diverse technologies, primarily categorized as dry or wet processes. This study investigates the operational processes of five different cement production methods—dry, semi-dry, humid, semi-humid, and wet slurry—across four companies with a total of nine factories. Their performance between 2017 and 2020 is evaluated using network DEA under non-homogeneous conditions, encompassing three modeling stages.Materials and MethodsIn novel approaches, DEA is utilized to assess the performance of network decision-making units. The models typically assume homogeneity among decision-making units, which may not always align with real-world conditions. Practical situations often violate assumptions of unit homogeneity and uniformity in input and output parameters. Consequently, it is imperative to present and employ methods and models capable of accommodating non-homogeneous units. This study employs a scientific library research approach and practical purposive data collection to gather relevant information. This information informs specific adjustments to operational processes. Consequently, the development of a robust system for evaluating supply chain performance becomes essential. The study utilizes common models to evaluate efficiency under non-homogeneous conditions. Classification of operational processes and related data, followed by modeling using Lingo software, is employed in this research.Discussion and This article consists of two parts. Initially, it introduces the fundamental performance evaluation model and subsequently delves into the three-stage model of data envelopment analysis (DEA) within the supply chain context. In the second part, the production processes of Portland cement are examined, covering dry, semi-dry, humid, semi-humid, and wet slurry processes. The proposed approach assesses the performance of four cement production companies over a four-year period. Efficiency calculations for nine factories are conducted in three stages:The first stage consists of three steps as follows:First step: Input and output parameters used across the entire production process are categorized based on the different production methods.Second step: Processes utilizing similar production steps, as determined in the first stage, are grouped into four categories.Third step: Efficiency assessments for factories sharing similar production stages from the previous step are conducted, resulting in the identification of nine categories.Second stage: The efficiency of each category, characterized by a common feature from the previous step, is calculated.Third stage: To determine the overall efficiency of each factory, the efficiencies of individual processes are multiplied.ConclusionsThe results indicate that the fourth cement production company exhibits the highest efficiency, while the first company has the lowest efficiency. Notably, the lowest efficiency for the years 2017 to 2020 was recorded by the first company in 2020, while the fourth company achieved the highest efficiency in the same year. Among the factories, the lowest efficiency was observed in 2017 for the first company's five semi-dry factories, the fourth company's four semi-humid factories in 2018, the fourth company's nine wet slurry factories in 2018, the third company's seven semi-humid factories in 2020, and the fourth company's four semi-humid factories in 2020, which recorded the highest efficiency. Further examination and identification of suitable solutions to enhance efficiency in cases with lower efficiency levels can follow this study.

DEA is one of the most applicable methods of performance evaluation. In traditional models of DEA, the unit's internal structure and time effects are not considered. Network DEA models survey internal structure, but they are static and do not calculate dynamic efficiency. On the other hand, dynamic models consider the unit as a black box in each period. So, network and dynamic models are not adequate for the evaluation alone. However, the dynamic network DEA models have the advantages of both dynamic and network models. In this study considering a comprehensive dynamic two-stage structure, a dynamic network DEA was presented in both input-oriented and output-oriented, to calculate the optimum weight of input, output, intermediate, and overtime variables. Then using the calculated weight, the method of calculating dynamic network efficiency in each stage, period, and the whole structure was stated. The suggested model for the condition of variables return to scale was also developed and the efficiency relations were explained. In the suggested models, a unit is overall efficient only if it is efficient in all stages and periods. Finally, for the description and potential performance of the suggested models, the data was used from central branches of Keshavarzi bank and the efficiency results were compared in two conditions of CRS and VRS.

Islamic banking is an emerging research in the field of banking studies. Studies can be further expanded due to the lack of extensive research in this area. A major part of this literature includes a comparative study of Islamic banking and its conventional counterparts based on their performance and the subject matter of their legislation. Islamic banking and finance have emerged as an attractive field in academic research over the past decade. Islamic countries are among the developing and less developed countries of the global economic community. With financial assets valued at approximately $ 1.8 trillion worldwide, Islamic banking and finance have led to friction between Islamic and non-Islamic financial markets over the past decade. The growing severity of the recurring financial crises seen in the recent financial crises of 2008-2007 has put a lot of pressure on the conventional financial system and put it back under the microscope. While some have turned their attention to methods and tools for resolving instability in an interest-based system, others are looking for alternative financial systems. In this regard, the Islamic financial system seems to offer a promising path to future financial resilience and stability. So far, however, this view has largely been published mainly in professional circles and has recently become the subject of academic research. Islamic financial institutions act as major hubs in about 75 countries, mainly in the Middle East, Southeast Asia, Bahrain and Malaysia. Islamic financial products have grown rapidly in recent decades in competition with the conventional financial industry in both Muslim and Muslim minority countries. As a non-competitive industry, the Islamic financial industry is becoming a market that can compete in many countries. The growth of Islamic financial services has attracted a great deal of attention from around the world, with nearly 25 percent of Islamic financial institutions operating in non-Muslim countries; At the same time, the conventional banking system has begun to open the windows of Islamic banking around the world, primarily in Europe and North America. In this study, an attempt is made to investigate the effect of capital adequacy index on the efficiency and risk-taking of Islamic and conventional banks for 51 Islamic and conventional banks in the period 2012-2017.

 The present article intends to evaluate the effect of capital adequacy on the efficiency and risk-taking of Islamic and conventional banks with an analytical-descriptive approach and examines the role of various indicators in this analysis. The method used in this The research is to provide a model of the quantum method and the software used by Eviews. This study also examined data related to 51 Islamic and conventional banks in 8 countries in the period 2012-2017.

The results of this study showed that in the conventional banking group, the capital adequacy index had a positive and significant effect on efficiency. According to other results, in the Islamic banking group, the capital adequacy index has a negative and significant effect on banking efficiency.

The results of this study show that in the group of conventional banks, efficiency also increases with increasing capital adequacy. The results of the studied quantiles also show that in high quantities (rates) of efficiency, the effect of capital adequacy on efficiency increases. In other words, with increasing the level of efficiency, the effect of capital adequacy on efficiency also increases. Also, the estimation results for the Islamic banking group show that the capital adequacy index has a negative and significant effect on banking efficiency, but at high efficiency rates, the negative impact of the capital adequacy index on banking efficiency has decreased. In other words, with the increase in the efficiency of Islamic banks, the negative effects of capital adequacy have decreased. Also, the results of estimating the risk model for Islamic banks show that the model has a width of origin with a positive sign; Banking variables including net loan to total assets ratio, capital adequacy and total assets, have a negative and significant relationship with the risk of Islamic banks and also the results of risk model estimation for conventional banks show that the model has a width of origin. With a positive sign; Banking variables including net loan to total assets ratio, capital adequacy and total assets, have a negative and significant relationship with the risk of Islamic banks.

By prioritizing the three functional dimensions of performance, customer satisfaction and relationship development, the present study has segmented organizations using the government electronic procurement system to adopt and utilize the system more. The research method of this research is quantitative and its nature is descriptive and correlational. A questionnaire was used to collect data related to variables based on previous studies. For this purpose, a sample of 148 purchasing and procurement managers of companies that have used the e-procurement system of the government were selected by simple random sampling method. By implementing the structural equation model with the partial least squares approach to test the hypotheses, it was found that the proposed model has a good fit. This study is the first research in Iran on the topic of user segmentation of e-government procurement system. The results of this study distinguish three groups of organizations: the first group of companies that are looking for more efficiency or efficiency is their first priority; the second group is the organizations whose customer satisfaction is their first priority; Third, there are companies looking to develop relationships with their business partners.

Using the input-oriented bootstrap data envelopment analysis approach, using the LSW algorithm, this study estimated the corrected bias efficiency values of the technical, managerial and scale efficiency of technology centers with an emphasis on science and technology parks in Iran. The central question of this article is what is the industrial capacity and regional innovation capacity in each province and what is the matrix of the relationship between the commercialization coefficient and the industrial and innovation coefficient of each region. The results obtained from this study indicate that the super-efficiency score in the technology centers of the country (variable return to scale) is 2.97, the efficiency score is 0.94, and the efficiency score using the bootstrap method is 0.85. Also, the findings of the research show that the most important factor in improving the technical efficiency of science and technology parks in the country is the improvement of managerial efficiency. According to the research findings, only 5 of the 15 science and technology parks with high commercialization efficiency have high innovation, three of them are located in industrial areas and the other two are located in semi-industrial areas. Among the reasons for their success, we can mention the existence of driving industries, the existence of effective communication between universities and research institutions with industry, networking related to innovation, and such things. On the other hand, looking at 4 non-innovative regions that have less commercial efficiency, it is clear that they are located in semi-industrial and weak regions, and among the most important obstacles to their innovation, we can mention the lack of knowledge clusters, emphasis on absolute theoretical skills, lack of necessary coordination between organizations He pointed out specialization and lack of emphasis on innovation.

The growth centers of technology units and science and technology parks can play a unique role in the commercialization of knowledge and the growth and development of the regional economy, and from the functional point of view, the parks cultivate and apply knowledge in a targeted manner and in creating knowledge-based employment, the rapid growth of the income of the local community. and creating wealth, increasing the level of specialized competition, creating influential business networks, creating the capacity to access other markets, improving the level of education and market-oriented skills, defending a cooperative and competitive knowledge business culture, and providing creative and innovative public services.
In Iran, like the member states of the European Union, various science and technology parks are active in different provinces of the country. Now the central question is how successful these parks have been in commercializing ideas? Also, another central question is what is the industrial capacity and regional innovation capacity in each province, and what is the matrix of the relationship between the commercialization coefficient and the industrial and innovation coefficient of each region? The answer to each of the above questions can help to examine the state of regional innovation and commercialization development or industrial lock-in and commercialization in each province.

Modified bias efficiency of technical, managerial and scale efficiency of technology centers with emphasis on science and technology parks in Iran.

In this research, the bootstrap approach has been used. First, he explained the general process of data generation and bootstrap, and then, in the second section, we introduced the method of evaluating the efficiency, i.e. data envelopment analysis, and finally, this section ends with the introduction of algorithms for estimating the data generation process (DGP) in the third part.

The Results of the research confirm that among the types of parks and according to the required infrastructure, it is possible to make the country's science and technology parks mission-oriented according to the coordinates of the advanced technology park, innovation and entrepreneurship park, university park, virtual park and business park. The central mission of the parks based on which model is defined requires a detailed analysis of the structure of human capital, the state of universities in each province, the evaluation of the local economy according to the structure of the macro economy, the business environment, analysis of the local, regional and extra-regional market, the structure of investment and sources of supply. Finance depends on the local economic cycle, local capabilities and talents, entrepreneurial infrastructure, and the state of technology in each province. In this article, the results and achievements of the commercialization of science and technology parks have been examined and quantified.

The regional science and technology park, as a market support institution, together with universities and industry, can create a regional innovation ecosystem. The regional science and technology park should balance local and extra-regional facilities and needs. By examining the institutional structure of science and technology parks in the world, it can be seen that the parks do not have the same structure and countries have adopted different goals and diverse operational models depending on the development goals and university structure and industrial and technology structure according to regional requirements; Therefore, developed and developing countries have followed different development patterns according to their needs.

In this research, the effect of individual ambidexterity on high level performance of the medical staff of Sahrekord University of Medical Sciences was investigated. High level performance of employees includes three main dimensions of team performance, efficiency and effectiveness of the department. The hidden dimensions of ambidexterity include exploration and exploitation. Past studies in the field of ambidexterity have mostly been conducted at organizational levels, but in the present study, there was an attempt to study the impact of ambidexterity at the level of individuals. In this research, we generally investigated the relationship between individual ambidexterity and employee performance, seeking to answer whether individual ambidexterity influences the performance, efficiency and effectiveness of organizational units. In order to answer the research questions, 260 questionnaires were sent to the medical staff of Shahrekord University of Medical Sciences. The data were gathered and analyzed using statistical methods and structural equation modeling based on the least squares method. It was found that individual ambidexterity had a positive influence on employee performance and that there was a significant relationship between individual ambidexterity and the efficiency and effectiveness of the department

Estimating the revenue efficiency of entities under evaluation is one of the most important evaluations that can give valuable information about organizations provided that the output prices are known . In this research, a new definition of optimal scale size ( OSS ) based on maximizing the average revenue efficiency (ARE) is presented . Also , the ARE is defined in both convex and non - convex sets, which is independent of returns to scale and the assumption that the vector of input-output prices of units is uniform . Next, due to the presence of uncertain data in many real applications, the introduced ARE model is extended to evaluate systems with random inputs and outputs , and approaches are provided to calculate it . Finally , the proposed method is used in an experimental example and the ARE is calculated for a data set of postal areas in Iran .

The electric power industry is one of the vital arteries contributing to the growth and development of countries and the electricity access index is one of the main components of assessing the industrial competitiveness in each country. Given the importance of this strategic industry, this study sought to develop an analytical-mathematical model for evaluating the efficiency of the power production, transmission, and distribution companies in the electric power industry of Iran.

In this study, the network data envelopment analysis (NDEA) approach with undesirable outputs was used. Additionally, a model was developed to evaluate the efficiency of the power production, transmission, and distribution companies in the electric power industry of Iran.

By solving the mathematical model used in this study, the efficiency of 43 governmental power plants, 16 regional electricity companies, and 39 power distribution companies in Iran were evaluated. The findings demonstrated that the average efficiency of the power production, transmission, and distribution companies in the Iranian electric power industry stands at 0.83, 0.6, and 0.71, respectively.

The results of this study indicated that the efficiency of the power transmission companies in the electric power industry of Iran is lower than those of the power production and distribution companies. The study also identified the main reason for the inefficiency of the power production, transmission, and distribution companies of Iran's electricity industry.