سلیم کریمی تکلو

Management of sustainable hospital services, while giving importance to patient care, also considers economic and environmental issues. The aim of the current research is to identify, analyze the scenario and analyze the effective drivers of sustainable service management in the hospitals of Kerman

The present study is a quantitative study that was conducted in 1402. The statistical population of this research is all the experts of Kerman hospitals (including doctors, hospital managers, development and support assistants and administrative assistants) with at least 10 years of work experience and working experience as managers or consultants in Kerman hospitals. 10 experts were selected as samples by snowball method. Based on this, at first, according to the research literature and soliciting opinions from hospital experts, the drivers of sustainable service management in the health field were identified. Then, the data was analyzed with the method of fuzzy cognitive mapping, and then forward and backward scenarios were performed.

The results showed that there are 18 drivers in the management of sustainable services in the health field, the driver of reforming the organizational structure with a weight of 5.90 has high effectiveness and the driver of hospital waste management system with a weight of 2.40 has high effectiveness. Also, the forward scenario showed that reforming the organizational structure will lead to the perceived reputation of the hospital, and in the backward scenario, in order to achieve hospital waste management, first attention should be paid to the construction of the green hospital building.

According to the results of the research, it is suggested to pay special attention to the incentive to reform the organizational structure in hospitals. Because it provides stability in the supply chain and services of the hospital, and the result is creating a positive image of the hospital. Also, with the construction of the green hospital building, the hospital waste management system will be improved.

Green innovation provides a sustainable competitive advantage for hospitals and has been the focus of academics and managers in new business models. The purpose of this research is to identify and level the obstacles of green innovation in hospitals.

The present study is a descriptive-analytical type that was conducted with the participation of 18 experts from Rafsanjan hospitals in 1400. Experts were selected purposefully by snowball method. A structured questionnaire was used to collect data. Fuzzy Delphi method and interpretive structural modeling and Excel software were used for data analysis.

The results showed that there are 11 obstacles in the green innovation of hospitals, including managerial obstacles, customers, laws and regulations, organizational, green human capital, information, finance, supply chain partners, competitors, technology and weak research and development. Of these obstacles, laws and regulations, competitors and customers are the most effective obstacles in moving towards green innovation.

According to the results, organizational barriers, supply chain partners, laws and regulations, customers and competitors are independent barriers that affect other barriers and should be prioritized to be resolved. By removing the obstacles identified in this research in order of priority, managers can help to improve the state of green innovation in hospitals in order to reduce environmental risks and increase sustainability.

The perishable food supply chain is a critical system that includes the production, processing, distribution and consumption of food and ensures the availability and access to food for the population. Today, the complexities of the business environment, uncertainty and environmental fluctuations have made the supply chain vulnerable to various types of challenges. The aim of this research is to identify and prioritize the challenges of the perishable food supply chain and provide effective insights and solutions to reduce the impact of these challenges.The current research is Qualitative and Quantitative . Fuzzy Delphi method and Ordinal Priority Approach (OPA) were used for data analysis. At first, 18 challenges of the perishable food supply chain were extracted by reviewing the research literature in reliable scientific databases, then the final 13 challenges were selected using the fuzzy Delphi method. In the following, by preparing a questionnaire and experts' opinions, the challenge of the perishable food supply chain was ranked using the OPA method. The statistical population of the research is made up of academic experts, managers of the agricultural jihad and the food and drug organization of Kerman province. For this purpose, 10 people were selected as a sample using the purposeful sampling method. By prioritizing the challenges, the first to third place was awarded to "weak demand management", "lack of regulations and government support" and "lack of product quality control". The results of this research have been obtained based on scientific texts and the opinion of domestic experts. Therefore, it can be new and comprehensive insights for organizations, experts and researchers in this field.

At present, economic activities destroy the environment by excessive use of resources and transferring the waste of production and consumption activities to the environment. The purpose of this research is to evaluate the impact of environmental regulations on green productivity in Iran. For this purpose, while using the information related to capital, labor, gross domestic product, pollution and environmental regulations in 31 provinces during the period of 1400-1395 and using the "non-radial directional distance function", the effect of environmental regulations on green productivity, outputs and undesirable output would be evaluated. The research results indicate that environmental regulations promote green productivity in the provinces of Iran. In addition, environmental regulations have been less successful in controlling the undesirable outputs of economic activities. In addition, the results showed that the effect of GDP on green productivity is insignificant and the ratio of manufacturing added value  to GDP has a negative and significant effect on green productivity.

The Internet of Things (IoT) is considered a modern concept in the production industry, based on which the physical and digital worlds are connected using the potential of the Internet. Since this technology is new, its acceptance and implementation in the oil and gas industry are associated with barriers. Therefore, this study aims to identify and analyze such barriers.

This study has been performed with a mixed approach in two phases. The qualitative phase was conducted to identify the barriers to using the Internet of Things in the oil and gas industry, and the quantitative phase was conducted to model and analyze the scenario. To identify and extract the barriers to using IoT in the oil and gas industry, it is identified through a literature review and content analysis method. In this research, 58 articles were analyzed and 10 industrial and academic experts analysed extracted barriers by using the Fuzzy cognitive mapping method. To analyze the scenarios, two categories of backward and forward scenarios have been designed. FCMapper software has been used for scenario design.

The results of the content analysis showed 10 barriers, which are subcategories of four aspects. The barriers identified are "limited coordination and collaboration" "lack of automation in organizations", "insufficient leadership support", "weak staff knowledge and abilities", "limited scalability", "opposition to change", "lack of Certain rules and standards for the adoption of the IoT", "the cost of data storage and analysis", "the high cost of implementation and maintenance", "security and confidentiality issues". Finally, these barriers were categorized into four main subcategories: "Organizational", "Integration", "Economic" and "Technical". The results of the fuzzy cognitive mapping method indicate that the barrier "security and confidentiality issues" with a factor of 4.34 has the highest level of influence, and the barrier "high implementation and maintenance cost" with a factor of 4.95 has the highest level of influence, and the barrier "security and confidentiality issues" has the highest centrality with a coefficient of 6.45.

Like any other research, this research has been faced with limitations. Considering that the research was limited to a specific industry, its findings may be affected by the opinions and biases of experts involved in the process, and we cannot generalize the results to another industry. Another limitation of this research is the complexity and time-consuming methods used in it. The methods of content analysis and fuzzy cognitive map may be complex and require sufficient time and a high level of expertise to use them, which can limit their application in some fields.

Considering that the IOT is an emerging and new technology, the adoption of this concept in the oil and gas industry can have several operational advantages, such as reducing testing and calibration time, minimizing production downtime, improving performance, and predicting maintenance performance. One of the important barriers to the use of IoT in the oil and gas industry is "security and data confidentiality" issues in different parts, and this issue causes the unwillingness of stakeholders and decision-makers to use this technology. Conducting research in the field of raising and increasing the security of these systems and ways to increase the security of privacy will greatly help in solving this barrier.

The study offers valuable insights for researchers, managers, and policymakers in the oil and gas industry concerning the adoption of Internet of Things (IoT) technologies. To facilitate the adoption of IoT in the oil and gas industry, companies should invest in comprehensive training programs for managers and stakeholders to improve awareness and understanding of IoT technologies and their benefits.

Since several barriers have prevented the widespread adoption of the IOT in the oil and gas industry, in this research, the identification and extraction of these factors have been done comprehensively for the first time. Modelling and scenario analysis of these barriers with fuzzy cognitive mapping were also performed for the first time.

Today, one of the main components of the sustainable development of organizations and among the methods of overcoming economic and technological challenges is innovation. Evaluation of the innovation process is an important issue in knowledge-based companies. One of the innovation evaluation methods is two-stage DEA, which allows considering multiple inputs and outputs and the internal structure without any special assumption regarding the production function. In this research, the theory of cooperative games was used to determine the optimal value of intermediate variables. A non-linear cooperative model for a consecutive two-stage structure with surplus input and output and conditions to the variable scale of development and two calculation procedures of variable first stage efficiency and variable second stage efficiency were proposed to solve it. Considering the two stages of research and development and commercialization for the innovation process, the efficiency of the stages and the total of 9 knowledge-based information and communication technology companies was calculated. The results showed that only one company is efficient in both stages and research and development has a greater contribution to the ineffectiveness of innovation in companies compared to commercialization. The results give important insights to managers to identify the source of inefficiency and prioritize resource allocation.

The purpose of this research was to identify and analyze the drivers of the smart sustainable circular supply chain. Twelve samples were selected by the snowball method from among industry experts in the edible oil sector. Drivers were finalized with expert opinions and analyzed using the DEMATEL and AISM methods. The results showed that organizational competence and human resource competence are the most effective drivers, while economic sustainability and environmental sustainability drivers have the highest levels of effectiveness compared to other drivers. According to the results of the research, officials in the edible oil industry should pay special attention to organizational competence to advance towards a sustainable and smart circular supply chain, as this driver has the greatest impact compared to others.

Disruptive digital innovations are innovations that include the use of digital technologies in an innovative and new way and can affect the performance of hospitals. This research was conducted with the aim of analyzing the mutual effect of enablers of digital innovation in the field of health. The present study is analytical-descriptive and was conducted with the participation of 16 experts from Kerman hospitals. Experts were selected purposefully by snowball method. In order to collect and analyze data, structured interviews and structural analysis methods were used. Based on the research literature and expert opinions, 20 enablers related to disruptive digital innovation were identified. The results showed that the factors of management style and strategic orientation have a high impact on other enablers. By identifying the effective and efficient factors in destructive digital innovation, the officials of Kerman hospitals can, considering the effective factors, create a context for setting up clinical information systems, remote monitoring of the patient, management of medical imaging registration and conversion. and learning to create knowledge.

Digitalization has become a crucial factor driving innovation in companies, research centers, and governmental organizations. This study aimed to identify the drivers of digital innovation, map the relationships between them, and analyze the effective routes of these drivers within governmental hospitals in Rafsanjan.

This research is pragmatic in its purpose and employs a descriptive survey for data collection, conducted in 1402. The study's population comprised experts from governmental hospitals in Rafsanjan, with a sample of 12 experts selected through the snowball method. The data's validity was confirmed using the content validity ratio index. Data analysis was performed using the fuzzy cognitive mapping method, supported by Fcmapper, Pajek, and Excel software.

The study identified 12 key factors driving digital innovation in governmental hospitals. Fuzzy cognitive map analysis revealed that senior management support, with a coefficient of 1.57, exerted the most influence. Meanwhile, the organization's digital capacity, with a coefficient of 3.24, was found to have the greatest influence. Additionally, the organization's digital capacity, with a coefficient of 3.89, exhibited the highest centrality. This research contributes by identifying key digital innovation factors, establishing causal relationships among these factors, and determining the primary factors influencing others through various digital innovation scenarios within governmental hospitals.

Based on scenario analysis findings encompassing 12 drivers and understanding the causal relationships among them, it is recommended that hospital authorities prioritize the "needs of citizens" driver to foster digital innovation.

In recent years, the circular supply chain has attracted the attention of many researchers and experts as a new approach in response to the lack of resources and minimizing waste production, and it can be useful in achieving a sustainable society and economy. Many research studies consider the reason for the slow progress of circular supply chain implementation to be a set of obstacles that prevent its successful adoption. Despite the study of obstacles and challenges of circular supply chain implementation in different countries, due to the difference in laws, infrastructures and social and cultural conditions, it is necessary to examine these obstacles in Iran as well. Among different industries in Iran, the investigation of the obstacles of the rotating supply chain in the automotive industry has not been considered. Therefore, in order to address this research gap, the researchers assessed the obstacles of the revolving supply chain in Saipa Citroen Automobile Company. To implement this necessity, the multi-criteria group decision-making method and specifically the Ordinal Priority Approach have been used. The results showed that the barrier of lack of technology to design recyclable products with a weight of 0.106 is the most important compared to other barriers. The findings of this study provide a comprehensive list of obstacles for the adoption of the circular supply chain and help the managers and decision makers of the automotive industry to formulate strategies to eliminate or reduce the effect of the most effective ones.

The sustainable development in public organizations has become a principle in the framework of today's organizations. The purpose of this article is to present a causal model to investigate the antecedents of sustainable development of public organizations. The approach used for data analysis and conclusion is intuitive fuzzy cognitive map. In this article, in the first stage, an attempt was made to create a causal model for the antecedents extracted from the literature and interviews with 15 experts of public organizations in Kerman city. In the second stage, by creating a scenario for two external antecedents “attention of stakeholders” and “Expectations for greater transparency” were observed, which changes have significant effects on increasing investment for infrastructure development, paying attention to clients in providing services, approving and complying with regulations, and the requirement to minimize environmental impacts. On the other hand, in this article, it has been tried to determine which antecedent for sustainable development has the most and the least influence. Based on the results, “increasing social awareness” has the most influence and “company culture” as an antecedent that can be considered with It is the highest degree of centrality.

the purpose of this research is to investigate the causal relationship of the antecedents of disruptive innovation in the field of healthcare services in Kerman. This research is applied-developmental in terms of purpose. According to the purpose of the research, first, the antecedents of disruptive innovation in the field of medical services in Kerman were identified based on theoretical literature and soliciting opinions from experts, and then data analysis was performed using the opinions of 7 experts in the field of medical services and the fuzzy cognitive mapping. The results of the research showed that the antecedents of disruptive innovation include: social, strategic, network and ecosystem, market, entrepreneurship, economic and foundational, managerial, resources, technological and organizational antecedents , the results showed that managerial antecedents with a weight of 2.05 are the most effective, entrepreneurial antecedents with a weight of 1.67 are the most effective, and strategic antecedents with a weight of 2.60 are the most central. Disruptive innovation studies have generally been conducted in industrial organizations. In this research, effective and effective antecedents and drivers in disruptive innovation in medical service organizations were investigated, which can help the managers of the medical field in the direction ofdestructive innovation.

Blockchain as a distributed, secure, transparent and reliable database shared by a community can also affect sustainable supply chain networks. This research was conducted with the aim of determining the causal relationship of the factors related to the use of blockchain in the sustainable supply chain of the health sector.

The current research is descriptive and was conducted with the participation of 5 experts from Ali Ibn Abi Talib Hospital in Rafsanjan. The experts were selected as a snowball. In order to collect and analyze data, structured interview and fuzzy cognitive mapping method were used.

Based on the research literature and expert opinions, fifteen variables related to the use of blockchain in the sustainable health supply chain were identified. The results showed that the data encryption variable was the most effective with a factor of 2.03 and the scalability variable was the most effective with a factor of 2.20. Among the 15 factors, the variable of standardization and development of software platforms has the highest degree of centrality with a coefficient of 2.97.

By identifying the effective and efficient factors in the use of blockchain, the officials of Ali Ibn Abitaleb (AS) hospital can use the data encryption that provides a secure environment by implementing blockchain technology, and also an intelligent system for convenience. To make patients communicate with the hospital.Key words: sustainable supply chain, blockchain, service supply chain, health field

By identifying the effective and efficient factors in the use of blockchain, the officials of Aliebn Abitaleb Hospital will be able to prepare the ground for the application of the blockchain approach by investing in these variables.

Today, sustainable innovation is recognized as a way to gain a competitive advantage and solve social and environmental problems. The aim of this study was to developing a model of sustainable innovation in public hospitals in Tehran using Grounded Theory in public hospitals in Tehran. 

The present study is a qualitative study that was performed by Grounded Theory method. Experts of public hospitals in Tehran (physicians, hospital managers, deputy director of development and support and administrative assistants) were considered as the population of this study. A combination of targeted method and snowball was used to select the sample. The method of data collection was semi-structured interviews with 11 experts familiar with the topic of sustainability innovation. The validity of the instruments was determined by external audits and the reliability was determined by Holsti Test and the data were analyzed through open, axial and selective coding.

The model of sustainable innovation in hospitals was developed in 6 components, 25 subcomponents and 84 concepts. Subcomponents include: causal conditions such as political stability, economic stability, stability of laws and cultural stability, background conditions include internal environment dynamics, staff dynamics, vision and awareness dynamics, and infrastructure dynamics, intervention conditions include macro environment conditions, organizational conditions and capabilities, and infrastructure conditions, axial phenomena include environmental monitoring and management, social monitoring and management, economic monitoring and management, strategies include health-oriented, quality and up-to-date services, keeping pace with the Fourth Industrial Revolution, attention to design and architecture, crisis preparedness, bio-imitation and pollution management, outcomes were categorized into tangible community outcomes, intangible community outcomes, tangible hospital outcomes, and intangible hospital outcomes. 

The final model indicates that the 6 components, 25 subcomponents, can provide sustainable innovation in public hospitals. It is suggested that hospital officials, considering the model developed, provide a suitable platform for the development of sustainable innovation in hospitals.

Sustainable innovation is recognized as one of the influencing factors in the performance of the health sector because the dynamic and complex nature of the health care industry requires innovative methods and solutions to achieve sustainability. The aim of this study is to determine factors influenced by and influencing sustainable innovation in public hospitals in Tehran.

The present applied research was conducted in two stages according to mixed methods research (qualitative and quantitative). In the first stage, in order to extract the factors influencing sustainable innovation in public hospitals, 11 people were selected from among the experts of public hospitals in Tehran by the snowball sampling method, and in-depth interviews were conducted with them. In the second stage, through a questionnaire and the fuzzy dimatel method using Excel software, the internal relationship between these factors and the influenced and influencing factors was determined.

72 codes were extracted from the interviews and categorized into 17 factors. Out of 17 factors, 8 factors were influencing ones and 9 factors were influenced ones. According to the results of the research, the manager's familiarity with current knowledge was the most influencing factor and the observance of stability was the most influenced factor in all aspects of the hospital.

Considering the benefits of sustainable innovation, it is recommended that hospital officials should provide a suitable platform for the development of sustainable innovation in hospitals with practical and up-to-date training and human resource development and the use of systems that create transparency in hospitals.

Medical centers consume large amounts of electricity, water, food and building materials to provide high quality care. Among the medical centers, hospitals consume more energy and water than many industries and produce more waste. Medical centers should look for programs to reduce energy consumption, reduce environmental impact, and manage waste disposal and medical waste. Green innovation makes this possible for these centers. Green Innovation is a set of changes in production products and processes aimed at managing waste, environmentally friendly productivity, reducing greenhouse gas emissions, environmentally friendly design, and reducing environmental impact.In order to create a green innovation culture in the organization, in the first step, it is necessary to identify and prioritize the barriers to innovation in order to eliminate them.In this study, by examining the research literature and consulting experts, 15 sub-obstacles were identified in the form of 4 main management barriers, green suppliers, human and financial resources for medical centers.Then, using BWM method, their livelihood and ranking were considered according to 12 experts, and the results showed that managerial barriers and especially lack of management commitment are the most important obstacles for green innovation in medical centers. Therefore, first of all, this concept and its advantages and disadvantages should be explained to the managers, and then other obstacles should be removed.

This research aims to identify and model the factors affecting the adoption of environmental sustainability in information systems by healthcare centers. The statistical population of this study consists of two groups. The first group includes twelve experts whose ideas were used to determine the critical factors and their causal relationships. The second group includes 250 employees, nurses, head nurses, and supervisors of al-Zahra medical and educational center in Isfahan. According to the results obtained from the review of research literature and interview with academic experts and information technology areas of healthcare centers, a total of twenty-four factors were identified in five dimensions of legal requirements, environmental responsibility, environmental legitimacy, resource consumption, and environmental justice. The content validity and construct validity were used along with confirmatory factor analysis to examine the validity of the research questionnaire Also, the overall reliability of a questionnaire based on Cronbach's alpha was 0.888. After collecting the required data, the level of dimensions was first determined in three levels using interpretive structural modeling. The factor of environmental justice was placed at the highest level and the factors of legal requirements and environmental responsibility were placed at the lowest level. The analysis model of the research path was designed based on the research interpretive structural model and it was and implemented using AMOS software. The results from path analysis indicated that among the six paths identified in the interpretive structural model, it was only the path of a legal requirement to resource consumption path that is not meaningful. Moreover, resource consumption has the highest total standard effect on environmental responsibility.

Healthcare centers can achieve social sustainability through adoption of sustainable information systems (SIS). This study aimed to identify and model the factors played a role in affecting the adoption of health care centers with information systems.
The current study was a descriptive survey in the category of applied research. The statistical population of this study included two groups. The first group consisted of experts. The factors were identified and modeled by library studies, and through interviews with experts. The second group consisted of the staff, nurses, head nurses, and supervisors in Alzahra training and treatment center of Isfahan, Iran. The research questionnaire was distributed among the second statistical population. The identified factors were leveled through the interpretive structural modeling. The research hypotheses were then defined based on the model’s levels. The research hypotheses were tested using the analysis techniques of the study route.
The interpretive interpretive-structural model included three levels. The factor of staff along with society and shareholders was placed at the first level. The factor of business ethics was placed at the second level. The third level included factors of social responsibility and organizational responsibility. The research hypotheses were determined based on the model’s levels. The results obtained from model fitness indicated the confirmation of all research hypotheses.
Social responsibility and organizational responsibility are two fundamental and effective factors in adoption of health care centers with sustainable information system. The adoption of sustainable requires senior management support, strategy development, proper policies, and expansion of organizational knowledge storage.

Configuration of supply chain is considered as the highest level of decision-making, which is part of the strategic decision-making process. According to few studies on the service supply chain, the current study aimed at configuring the sustainable supply chain of health services using the fuzzy cognitive mapping method.
The current research was deigned based on mixed method (quantitative and quantitative). The qualitative statistical population of the study was the hospital experts of which 18 individuals were selected by the snowball sampling method for interviewing and extraction of effective concepts on the sustainable supply chain of hospitals. In a small part of all employees of hospitals in Kerman, Iran, 414 individuals were selected as the quantitative samples using random sampling method. The sustainable supply chain questionnaire in hospital was made by the author and exploratory factor analysis was used to identify the concepts of 15 main factors designed with fuzzy cognitive mapping method to quantitatively configure the sustainable supply chain. SPPS version 18, EXCEL, PAJEK, and FCMAPPER were employed in the current study.
The effective measure on the sustainable supply chain comprised of 60 concepts in the form of 15 main factors. Based on 15 concepts, the configuration of the sustainable supply chain was designed. The results showed that service delivery management with 4.19 degrees has the highest centrality and attention to the environment with 0.99 degrees has the lowest centrality among other factors.
Service delivery management has a high impact on sustainable supply chain in hospitals. Therefore, it is recommended that hospital officials focus on service delivery management factors and manage it to reach a more sustainable supply chain.

Despite the importance of the service sector and its contribution to the world economy, studies on the supply chain of the service sector in comparison with the industrial sector are very rare The purpose of this paper are: identify effective concepts on the sustainable supply chain of hospitals, and design a sustainable supply chain model for the hospital.
This study is an applied descriptive survey. its nature is a type of qualitative and Delphi methods. At first, using deep interviews, effective concepts on the sustainable supply chain of the hospital were extracted. Then, using the Delphi method, the concepts were placed in the form of 15 main concepts. then, using of Type-2 fuzzy cognitive mapping method a causal model of sustainable supply chain were desined.
Effective concepts on the sustainable supply chain include 68 concepts that are in the form of the 15 main concepts such as: demand management, resource and capacity management, customer relationship management, supplier relationship management, service management, information management, financial performance management, Attention to the environment, contamination, energy consumption, legal requirements, employees, community and stakeholders, social accountability and business ethics. Based 15 concepts, the mapping of the sustainable supply chain of the hospital was designed. The results indicate that service delivery management is highly central among other concepts.
By focusing on concepts such as service management and capacity and resources management that have a high level of focus, a sustained supply chain supply chain can be improved.

Open innovation is targeted from flow of knowledge for accelerate internal innovation and market expansion using external innovation. Todays, the necessity of applying open innovation to enhance competitiveness of companies in domestic and foreign markets is as a new topic. Science and technology Parks plays large role in the creation of a national innovation to cover knowledge based companies. Because Necessity of innovation in this type of companies, Parks have to provide a platform for innovation in the use of their Sections. One method to achieve success is the implementation of open innovation. Accordingly, this research seeks to develop a model of open innovation in Science and technology parks. For design of the model, firstly. By investigating the research literature and surveys of 126 researchers and experts in universities and Science and technology parks, Dimension of open innovation were identified. Then, through the validation by 45 people of Directors, Officers and Staff in companies of science and technology park the development model of open innovation was Confirmed. The model presented in this study includes four the role of facilitating: Facilitation role, Supportive role, regulation role and Cognitive-normative role for open innovation in science and technology parks and 19 sub role. finally In this study, mining models was confirmed using confirmatory factor analysis. It should be mentioned Calculations were performed using the software spss18 and lisrel8.8.

Stockholders for making proper investment decisions need information which assists them in making the best decision. Among available information، Information related to the per share forecasted earnings is the important ones in the user’s opinions. Beside، companies try to forecast the earnings per share with maximum accuracy to attract investors. Accordingly، the present study seeks to provide a model to improve earnings per share forecast of companies listed in Tehran Stock Exchange (TSE) using modern artificial neural networks approaches. For this purpose، first the factors affecting future earnings per share were inferred from internal and external research، then using the sample companies'' financial information in the years 2005-2012 and employing support vector machines and artificial neural networks methods، earnings per share forecasting was designed. Support vector machines model was able to forecast the sample companies’ next year’s earnings per share with an adequate error of 5%. This model introduces current year’s earnings per share with effective coefficient of 25% as most effective variable to forecast next year’s earnings per share. The results suggested that the support vector machines model has similar performance in comparison with artificial neural networks model.

One of the main issues in financial management is choosing the best way of utilizing investment. Investors would like to invest their capitals in a way to minimize their risks. Bankruptcy is one of the risk factors which affect the decision of investors. Prediction of bankruptcy can help investors to reduce the risks in the capital markets and recognize the best opportunities for alternative investment. This study aims to predict the bankruptcy of companies by using the technique of Artificial Neural Network (ANN). Moreover, discriminant Analysis and logestic regression techniques are employed to compare the results. The data used in this study covers the firms in the Kerman Province of Iran over the period 1975- 2007. The results show that ANN model perfom much better than the discriminant analysis and logestic regression techniques. Moreover, the results confirm that the accuracy of ANN model is higher than the discriminant analysis and logestic regression techniques for predicting of bankruptcy. The analysis also shows that none of the firms will bankrupt in the year after the period covered in this study.

One of the main important issues in financial management is choosing the best way for utilizing investment. Investors like to invest their capitals in a way to minimize its risks. Bankruptcy is one of the risk factors which affect the decision making for investment. Predicting bankruptcy can helps investors to reduce the risks in capital markets and to recognize the best opportunities for their capitals. To do this, the Artificial Neural Network technique can be used for bankruptcy of firms in the future. In this study, this method is applied for the firms in the Province of Kerman, Iran. The result shows that none of the firms will bankrupt in the year 2008.