maryam shoar

A major disruption in the supply chain causes a shutdown or reduction in capacity. A disruption at any point in the supply chain spreads as a ripple effect to other members, causes a reduction or interruption in production and makes distributors unable to respond to customers with a lack of inventory or affects the lead time. The present research introduces and quantitatively shows the ripple effect of the disruption of the supply chain. To describe supply chain recovery and vulnerability, we integrated a discrete-time Markov chain with a Bayesian network model for simulating the propagation behaviour of supply chain interruptions. After that, we provided a set of standards for estimating the knock-on effects of a supply disruption on the supplier,manufacturer and distributor in terms of delivery lead time and revenue loss. We made a comparison between the results of the manufacturer disruption and the supplier disruption. Results indicate that this model can show the result of disruption and high-risk paths in the supply chain so that we can estimate the supply chain vulnerability before disruption. If a disruption occurs at one point in the supply chain, other members will be subject to disruption, and each member closer to the disruption point will receive a larger blast wave. The novelty of the present study is the quantitative estimation of the risk of a long-time disruption ripple effect based on the lead time and lost sales for a three-tier supply chain and compared the ripple effect of the manufacturer disruption with the ripple effect of the supplier disruption.

Objective (s): 

The Health Transformation Plan, initiated in 2014 in Iran and sought to protect public assets, promote equitable access to healthcare services, and enhance service quality. This study evaluated the performance indicators of hospitals affiliated with a medical university before and after the implementation of the plan.

This cross-sectional study encompassed 15 teaching medical centers affiliated with Shahid Beheshti University of Medical Sciences in Tehran province, Iran from 2009 to 2019, consisting of five years prior to the implementation of the plan (pre-2014) and five years following its implementation. Seven key performance indicators, including bed occupancy rate, length of stay, admission ratio, number of hospitalized patients, number of hospitalized referrals, number of surgeries, and number of cesarean sections, were investigated as primary variables.

The majority of performance indicators exhibited significant increase after the implementation of the Health Transformation Plan, with the exception of the number of cesarean sections and median length of hospital stay. Individual hospital analysis revealed a decrease in median length of stay in most hospitals post-implementation, while the median values of other performance indicators generally showed an increase across different hospitals. Notably, Imam Hossein, Taleghani, and Loghman Hakim hospitals had the highest number of registered beds.

The implementation of the Health Transformation Plan demonstrated a relatively positive impact on the performance indicators of hospitals, resulting in favorable changes in trends and medians of these indicators from 2015 to 2019.

e automotive industry is widely recognized as one of the most productive sectors in many countries and has consistently garnered the attention of governments worldwide. In recent times, environmental concerns and the potential risks to the natural world and human health have gained global prominence. Given the inherent environmental impact of the automotive industry, considerable efforts are underway to mitigate its adverse effects. This research aimed to present a model for analyzing the enablers of the green supply chain in the Iranian automotive industry. A structural-interpretive modeling approach was employed to determine the relationships between enablers. The study focused on active companies in the automobile and automotive parts manufacturing sectors. The statistical population of this research consisted of supply chain operations experts in automotive companies, and a sample of 16 managers from the mentioned companies was selected. MATLAB software was utilized for calculations and model presentation in this research. Based on the results derived from the structural-interpretive modeling approach, several significant components were identified at different levels of the model. At the initial level, the analysis focused on components related to the organization's social and environmental responsibilities, as well as its efforts in recycling and reuse. Moving to the seventh and final level of the model, the research emphasized the critical role of supplier relationship management

The growing trend electromagnetic waves such as mobile phones, which causes more people to be exposed to electromagnetic fields; It doubles the necessity of research regarding the possible effects of these waves on the health of citizens. Therefore, the present study was conducted using the soft systems methodology (SSM) and the problem-solving structure with the aim of measuring the actual radiation level of the base station transmitter (BTS). Also, effective solutions were presented to reduce human risks in the face of waves. Methodology In this study, 10 high-risk spots were selected from the metropolis of Ahvaz in cooperation with the regulator, the Regulatory and Radio Communications Organization of the Southwest Region. Then, with the related equipment and the NARDA device, the radiation level of the transmitter base station was measured. For each point, measurements were made at 3 different heights (100, 150 and 170 cm from the ground) with different distances (20, 30 and 100 meters from the antenna (BTS). Also, the duration of the measurement in each. The height was determined by 6 minutes according to the relevant standards. Finally, the maximum amount of radiation level obtained as a result was recorded for each point. Despite choosing the highest value obtained for each point, after comparing the extracted results with the threshold limit set by the Atomic Energy Organization of Iran, it was determined that all the points in question met the threshold limit and there was a huge difference with the minimum They had a threshold. Therefore, it can be concluded that the level of radiation in these places is not worrisome and this result can be generalized to larger scales. At the same time, considering that the concerns regarding the long-term effects of exposing people to radio frequency radiation are ongoing; Effective solutions were presented to reduce the presence of people exposed to electromagnetic fields.

The risks5 of buyer-supplier relationships cause the decreased performance and disruption in supply, but they can be managed by providing a suitable strategy. Despite the importance of these risks, a risk management model that determines the appropriate strategy for each supplier has not been developed so far. The purpose of this research is to provide a model for determining the strategy of buyer-supplier relationships risks for oil rotary equipment manufactures.

In the first stage, relationship risks and strategies were identified based on the research literature, and then experts' opinions about risks were collected to determine relationship risks in the studied industry. In the second stage, using the interpretive structural modeling method developed with fuzzy logic, the relationships between risks and those levels were examined and the most effective risks were determined by MICMAC analysis. The third stage is determined strategies by experts' opinions. Then fuzzy risk matrix with the dimensions of probability and intensity of impact is designed. Based on the risk priority (based on risk position in the matrix and its level based on interpretive structural model), a suitable strategy was determined for each supplier. In the last step, this model was validated by calculating the percentage of agreement.

The most effective risks of buyer-supplier relationships in this research include loss of objectivity, lack of trust and confidence, supplier's unwillingness to cooperate, Limited number of suppliers, supplier's opportunism, collusion and conflict of goals, which Their priority and relationships have been determined. Based on the priority of risk for each supplier, strategies for risk management have been determined.

The results of comparing the output of the model and the opinions of experts show the validity of the designed model and this model can be used for all industrial equipment manufacturer companies.

The disruption caused by natural, economic and political crises, piracy, and disturbance in information systems and human agents (low probability factors with high impact intensity) travel like a wave from the upstream of the supply chain, i.e. from the suppliers to its downstream. The ripple effect is the phenomenon of disruption in the supply chain with serious impacts on the performance of the supply chain. It can influence sales, on-time delivery, and profits. It has more serious consequences in reducing short-term performance, which leads to market share reduction. This disruption affects the entire supply chain. It destroys the capacity or inventory of the chain, disrupts its facilities, and causes material loss and production reduction in the next stages of the supply chain. Since disruptions are inevitable in supply chains, it is necessary to address this issue and evaluate the impact of disruption risk and its distribution on the supply chain. The purpose of the present study is to provide a simulation model for the behavior of disruption propagation in a three-stage supply chain. It tries to take into account both the vulnerability and recovery capabilities of the disrupted supplier and to determine a criterion for quantitatively predicting the ripple effect of the supplier disruption on the distributor. As the disruption in suppliers prolongs deliveries to customers, and any increase in lead time will decrease sales, the current study seeks to present the quantitative estimation of the ripple effect of supplier disruption on the distributor in terms of lead time and lost sales.
First, using a discrete-time Markov chain, a recovery and vulnerability model was proposed for long-term disrupted suppliers with three states of operational, semi-operational, and fully disrupted. The model was integrated with a Bayesian network to show the way the supplier disruption spreads to the manufacturer and distributor by dynamic Bayesian modeling. Then, in order to quantitatively show the ripple effect of the supplier disruption on the distributor, a criterion was established in terms of the lead time for the delivery of goods and lost sales based on the decision tree and the data of the dynamic Bayesian simulation model.
The model was presented through figures, definitions, and mathematical relations. Its capability was shown by an example based on the status of suppliers, manufacturers, and distributors in the production of a voltage-increasing electronic component. The obtained results showed that when a disturbance occurs in upstream of a supply chain, it spreads as a ripple to its downstream and affects its performance.
The proposed model by this study can quantitatively show the spread and impact of disruption along the supply chain. It can reveal the hidden risk paths and the role of each entity in the chain at the time of disruption. By quantitatively estimating the vulnerability caused by any disruption in the supply chain, the proposed model can help managers identify deviations or the risk of deviations in the chain in time. It can also help them with analyzing and performing control measures to restore the operation and process of the chain and prioritize possible policies and recovery. It is also useful for the selection of suppliers and inventory plans and making the right decisions to reduce the vulnerability of the supply chain sectors quickly with minimal cost.

Rapid development toward globalization, a competitive market, significant technological advances, and high customer expectations have encouraged companies to reduce costs and increase their competitive advantage. One of the things that can help companies achieve a competitive advantage is supply chain management. Information acts as an intermediary between all activities and operations within the supply chain. The innovation of this research can be shown in two aspects of application and modeling. In terms of application, with a review of the literature and investigating the application of multi-stage and network data development analysis in the supply chain, it was revealed that so far, the efficiency of financial and physical flows in the literature has been evaluated more and the indicators are mostly related to two financial and physical flows in the supply chain, therefore there is more research opportunity to evaluate the efficiency of information flow within the supply chain. Measuring the efficiency of information flow should be an integral part of supply chain management. Therefore, this research aimed to present a model to evaluate the efficiency of information flow in the supply chain. In terms of mathematical modeling, research innovation is considering the model of the network and reversible relationship in the supply chain. With a review of the literature, the indicators are investigated to evaluate the efficiency of information flow in the supply chain, and the validity of indicators is examined by the fuzzy Delphi method. Then the decision making unit and inputs and outputs of the model are introduced. In this research, the fuzzy network data envelopment analysis is used. In order to implement the models, we used the GAMS software.

Subject and purpose of the article:

 Deciding on the capital structure is one of the most challenging and difficult issues facing the companies. The present study examines the effect of determining the type of capital structure on the performance of the company. And determining that there is an optimal capital structure?

 At first, the present research has examined and reviewed the existing theories in the field of capital structure. Considering that the determination of capital structure is a dynamic process, in this research, from the approach of system dynamics and using Vensim software, the relationship between the structure The capital and accounting standards of performance evaluation (ROE, ROA) of Iran Telecommunication Company have been discussed.

The results of model simulation with real data from 1395 to 1400 ensure the correctness of the behavior of the model. And the results indicate that financing through debt in the company's capital structure has a significant effect on the debt cost rate and the capital cost rate and has an effect on the asset return and equity return ratios (performance evaluation accounting criteria). There is no punishment.

Conclusion, originality and its addition to knowledge: 

the findings of the research showed that the company's capital structure does not affect the company's ROA, ROE evaluation criteria. Also, the sensitivity analysis shows that the increase in the level of debt, despite the effect on the cost of debt and the cost of capital, does not lead to a significant change in, ROA, ROE.

In the present era, technology has changed tremendously, yet the successful adaption of technology is quite challenging. Due to the rapid emergence of new communication and information technology tools and increased rates of investments in telecommunication and expertise, society's dependency on these services is apparent. With regards to innovation in the ICT industry and the complexity of competition among stakeholders, it is demanding to promote an efficient and appropriate "regulatory" governing organization system in the ICT that provides constant access to the services. While few researchers have addressed the issue, the main problem still remains intractable. This study provides a comprehensive ICT regulatory sustainable business model for structuring an organization's governmental regulations using Peter Checkland's SSM approach in the real world. It was conducted using a problem-solving approach, investigating many scientific articles and related books, conducting inclusive and semi-structured interviews with experts, followed by extraction of the relevant parameters of the regulator model. Later, through analysis of performance indicators, the situation was assessed. After interviewing the experts and participants in this study, the regulatory model's key factors and components were analyzed and determined.Based on findings, this research was able to propose a proper model for regulating the critical beneficiaries. Moreover, this study presented a novel and efficient approach for developing a sustainable regulatory business model in the regulatory communication system. In the execution stage, the model's strengths and weaknesses were verified and modified to achieve an efficient improved resilient model that could support the main stakeholders in this field.

The purpose of this study is modeling of Electronic Word of Mouth Marketing with Emphasis on Customer Behavior and Business Improvement, In this regard, to identify and investigate the impact of various factors on the results of e-mouth marketing and Also examining the effects of successful implementation of this type of marketing on customer behaveor and Improving Electronic business. The research method is descriptive-survey, is of correlational type. In the conceptual model of the research, the independent variables of customer interaction, Electronic Word of Mouth marketing channel, Message quality and brand image With their components based on literature review Identification and research hypotheses have been developed. in order to Investigating the effectiveness of the identified components On the success of word of mouth marketing and the validity of the conceptual model of the research, Questionnaire tools and comments of users of internet sales sites in Iran have been used.The statistical sample to the unlimited statistical population it was estimated according to Cochran's formula 384, In order to review and present the final model from the structural equations approach with SmartPLS software was used. Statistical analysis of the collected data and research results show it customer interaction, Electronic Word of Mouth marketing channel, Message quality and brand image will have a positive and significant impact on the results of this type of marketing that will change of customer behavior and business improvement.

Business and organization environments need using numerous processing, saving and software resources for achieving their determined goals. Genesis of Cloud Computing, transform method of access to the information processing and saving resource. Having easy accessing features through network communication standard mechanism and Automatic increasing resource mechanism, cause great interest in organizations to use Cloud services. However, choosing suitable service despite increasing variety of services in terms of price, place and quality of service parameters, make the cloud services selection process so complex. One of the requirements for choosing the right cloud service is Identify the factors influencing the selection and estimation of the importance of them. This research has tried to follow a mixed approach and use systematic literature review and fuzzy Delphi method in the form of an exploratory plan, Identifies the effective factors in choosing the organizations cloud service and rank these factors with the help of the best-worst method. In the first step, by systematically reviewing the literature in this field and also comparatively reviewing the three industrial standards of cloud service level agreements, 24 elements affecting cloud service selection were identified, in order to expand the existing body of knowledge, validate and refine the factors affecting the choice of cloud service, Fuzzy Delphi method was used. Based on the consensus of experts, 20 factors affecting the choice of organizations cloud service were approved and finalized in the form of 4 main components. At the end, the factors confirmed from the previous stage were weighted and ranked by the best-worst method. The results showed that performance, security, environmental and organizational components are the most important in choosing a cloud service. Of the 20 factors influencing cloud service selection, availability factors weighing 0.137, reliability weighing 0.134, response time/delay weighing 0.122, governance weighing 0.096, and capacity weighing 0.072 have the highest weight, respectively.

The emergence of the Quid 19 global epidemic crisis has increasingly increased the users of e-learning systems. One of the important challenges of these systems is to provide the appropriate hardware and software infrastructure to respond to its growing users and maintain efficiency. The advent of cloud computing has revolutionized the way data storage and access resources are accessed. Easy access through standard network communication mechanisms and automatic resource allocation has made cloud computing an ideal infrastructure for e-learning systems. However, due to the multiplicity of cloud suppliers and the diversity of their services, as well as the various quality of these services components, the issue of choosing infrastructure as a service is a serious challenge for educational institutions. The purpose of this study is to design a conceptual framework for selecting the appropriate cloud service for e-learning systems.

The present study has tried to follow a mixed approach and use the methods of systematic literature review, fuzzy Delphi and prioritization of the fuzzy best worst in the form of an exploratory plan, a coherent and comprehensive view of "factors influencing cloud service selection for e-learning" Provide. In the first step, using the method of SLR and meta-combination of findings of 105 scientific sources in the field of cloud service selection, the concepts and categories of the initial framework were extracted. The initial research framework has been used as the input of the fuzzy Delphi study and based on the opinions of experts, the initial framework has been developed, refined and approved. In the final step, with the help of the fuzzy best worst method, the weight of each of the specific dimensions and elements and the conceptual framework of the research have been compiled and explained.

The framework for selecting the appropriate cloud service for e-learning systems consists of 259 conceptual elements organized in 5 dimensions and 27 components. Functional dimensions (7 components) 34.8%, security (6 components) 22.1%, organizational and environmental (7 components) 20.3%, personal data protection (5 components) 16.1% and data management (3 components) 6.7%, respectively Cloud services are effective. The results show that in choosing a cloud service, respectively, the components of availability, reliability, governance, virtual machine hardware features (such as throughput, memory, etc.), total cost (sum of rent cost, ISP cost and data transfer cost) and the geographical location of the data storage are most important.

Today, one of the important frameworks in understanding and recognizing digital transformation in all activities is the digital transformation maturity model. Understanding the dimensions and stages of maturity is important for transportation decision makers because in this way they can make appropriate management decisions by understanding the position of their organization in the maturity of digital transformation. The main purpose of this study is to present the maturity model of digital transformation capability, determine its stages, and investigate the use of Intelligent Transportation Systems and the maturity of transportation-related activities. In this paper, meta-synthesis is used to study the different models and stages of digital transformation maturity in various scientific databases on the Internet and provide a comprehensive summary of the dimensions and stages of maturity. After evaluation, 30 transportation companies in Tehran and their main activities were selected. By analysing the dimensions and stages of maturity in previous papers, the maturity model presented in this paper includes five stages and 10 dimensions in transportation area. These dimensions include digital management, information technology, manpower, operations and processes, culture, organizational structure, innovation and change, new strategies, intelligent products and services and customer orientation. Therefore, the maturity of 14 transportation activities was measured. The results showed that most transportation activities are at level three of the maturity model. Also, dimensions that scored the most are, respectively, digital process and operations of transportation, digital innovation in transportation, structure and governance, and digital management in transportation.

Buyers must identify and assess the risks of buyer-supplier relationship to reduce risks and dissatisfaction. The purpose of this study is to propose a risk assessment model for buyer-supplier relationships based on social capital, because in additions to benefits, social capital has risks that can reduce the company’s performance. However, no risk assessment model has been proposed for it so far. The method used in this study included three stages. In the first stage, the risk factors and their classification were identified based on library research. Then, after consulting with experts, questionnaires whose validity and reliability had been confirmed were distributed to collect expert opinions through the Delphi method in order to achieve a consensus on the risk factors of social capital in the industrial equipment manufacturing industry. The second step involved determining the importance of risk factors through the risk matrix and then assessing the risk based on the fuzzy expert system using MATLAB software. The output of the risk matrix was ​​entered into the fuzzy expert system and the risk of relationship was calculated by the system so that the decision-making team could make decisions for suppliers whose relationship risk was at an unacceptable level. In the third stage of the research, the model was validated. Comparing the output of the model with the experts' opinions showed that they were similar. Then, we propose that it is possible to assess the risk of relationships based on social capital in the buyer organization without experts and to decide about continuing cooperation with suppliers.

The importance of IT services in the life of businesses has led organizations to seek continuous evaluation of the quality of their IT services. In this regard, IT service management best practices such as Information Technology Infrastructure Library (ITIL), have introduced several processes for management of IT services and defined different KPIs for evaluation of each process, so that organizations can evaluate and analyze the quality of their IT services through these KPIs. Despite this fact that evaluation of each ITIL process using mentioned KPIs requires considerable time and money, organizations are looking for solutions to invest on the most effective KPIs to improve their ITSM processes in pursuit of their business requirements. Although there are some researches over process evaluation methods in different areas, there is no scientific research in ITSM process evaluation. This study proposes the unique method for ITSM evaluation using ITIL KPIs based on defined critical success factors (CSF). In addition to that, Simultaneous Evaluation of Criteria and Alternatives (SECA) model as one of the newest MCDM methods has been used for KPI prioritization. Based on the results, we recommended the order of KPIs in ITSM process performance evaluation. This research helps organizations to improve their ITSM processes by investment on the most effective KPIs.

In todaychr('39')s high-traffic world, where humans are constantly confronted with various dangers around the world, a proper response system with the proper functioning of pre-hospital medical emergencies is of paramount importance. A major challenge for emergency services worldwide is dispatching ambulances to patients appropriately in terms of limited resources and patient safety.

The mathematical model was first introduced based on the ambulance distribution process in East Tehran Emergency Area and solved using GAMS software based on Epsilon constraint technique and Pareto model analysis. The objective functions are to maximize coverage and minimize costs. To deal with the uncertainties of the parameters, a robust optimization approach was used and the Epsilon method was used for two purposes of modeling. To clarify the model and illustrate the application of the above mathematical model in the real world, a case study was conducted in the eastern region.

Based on the proposed model, the number of stations in East Tehran can be reduced from 39 to 19, but the number of ambulances in each station is almost twice as high as the average of 4 or 5 ambulances per station.

Reducing the number of bases can have a significant impact on the cost of stationary station equipment, personnel amenities, the cost of time consumed and the property used to build the station, thus saving more stations to reduce time. Responding to demands established increased productivity.

The introduction of cloud computing techniques revolutionized the current of information processing and storing. Cloud computing as a competitive edge provides easy and automated access to the vast ocean of resources through standard network mechanisms to businesses and organizations. Due to the vast diversity of service providers and their respective variety of available services with different qualities, top managements often face difficulty for choosing the best available option. So, considering the growing significance of the mentioned issue, this study aims to identify and rank contributing factors in selection of cloud service providers. In that attempt, this research approaches its goal by going through three major phases. Firstly, in phase one, prior studies are reviewed for extracting related elements of selection. Secondly, by employing Fuzzy Delphi method and obtaining results by interviewing experts in this field such as IT managers and technicians, this study tries to finalize the list of contributing factors. Lastly, by utilizing Fuzzy best-worst multi-criteria decision-making method, which is one of the most recent techniques employed to statistically rank variables, this research introduces a list of vital factors for cloud service selection. Based on the findings of this study, there are five major categories involved in the selection process which are: performance, security, data management, personal data protection and environmental-organizational. The finalized result of ranking shows that, performance related factors such as accessibility, response time and capacity are the first priority. The runner-up is security with reliability and governance. Environmental-organizational variables lands in the third place by considering rental and network costs.

Nowadays organizations are compelled to use and implement digital transformation in their organization in order not to retreat from competitors in a competitive environment and to be able to respond to customers' needs. But one of the most important ambiguities in this area is the understanding of the concept of digital transformation in the organization. Digital transformation maturity model is one of the important frameworks to understand digital transformation in an organization the digital transformation model. A maturity model consists the dimensions and the phases of the digital transformation. Understanding the important dimensions and phases of maturity is important for decision makers because they can make good decisions based on understanding their organization's place in the digital transformation mature. Given that the first step in implementing the digital transformation is to evaluate digital transformation maturity, the objectives of this study are this study is to develop a maturity model for digital transformation and to determine its phases. This paper presents a comprehensive overview of different maturity models and their phases. For this purpose, the Meta-synthesis method is used to conduct this study. This method has been used to search and select appropriate articles related to the subject of research in various scientific databases on the Internet and extract the necessary information from them. A total of 228 original articles are obtained after the evaluations and finally 28 papers are selected. By analysing and interpreting the dimensions and phases of maturity models presented in previous articles, the maturity model presented in this study consists of five phases and 10 dimensions. These dimensions are as follows: Leadership, Information Technology, Employees, Operations and Processes, Culture, Organizational Structure, Innovation and Change, Strategy, Intelligent Products and Services, and Customer. Finally, the maturity level of 20 pharmaceutical companies is measured by using the maturity model presented in the current study and the results showed that most of the pharmaceutical companies include level 2 to level 3 of the maturity model.

The main purpose of this study is to use Falcon's artificial neural networks and fuzzy inference system to designing an IOT-based business model in telemedicine at the National Institute of Medical Research Development of Iran. In fact, the research fatigue of NIMAD decision makers and physicians can be explained by the combining different ways of designing an IOT-based business model in telemedicine. In addition the need to use the T-MEDICINE+IOT.F-ANFIS system to increase confidence and reliability in Decision making, as well as the issue of the need for multiple expertise through the simultaneous using multi-disciplinary knowledge of different areas to solve the problem of internet of things-based business model. In this study, the Matlab R2017b programming environment was applied to design an Expert system based on Falcon neural networks. Finally, using the T-MEDICINE+IOT.F-ANFIS system outputs, the status of "IOT-based business model in telemedicine" can be analyzed based on variables such as following items: Using IOT in telemedicine; the ability to managing devices; The IOT networks position; IOT security; the degree of familiarity with the analyzing IOT applications. In fact, the final difference between the analyzing the outputs of the Expert system based on Falcon neuro-fuzzy system of this study, and the average views of Telemedicine physicians and IOT-based business model specialists, It is not significant and it equals to 0.065.

Given the high volume of web information, more attention has been paid to the automatic data extraction systems. One of the most important methods of data extraction is clustering. Today, many clustering methods are provided which are mostly based on vector models. In these models, each document is treated like a set of words, and the sequence of words in the sentence is ignored. Since the meanings in the natural language are completely dependent on the sequence of words, a great deal of shortcomings is observed in these methods. To overcome these shortcomings, this paper presents a new method for clustering HTML documents in which STC algorithm is considered for clustering snippets. This method, called clustering based on KS_STC key sentences, provides a weighted vector for each document and using this vector, the key sentences of each text are extracted from the document. Finally, these key sentences are given for clustering to the STC algorithm.