ABSTRACT Considering the concept of quality of life in cities to be the same, urban planners do not have a precise understANDing of the factors affecting the quality of life. Therefore, according to the size of the city, different indicators should be considered to measure the quality of life. Thus, according to the main goal of the research, which is to recognize, identify AND compile the factors affecting the improvement of the quality of life in middle AND SMALL cities on an intra-provincial scale, Qazvin AND Zia Abad cities in Qazvin province were selected as study samples. In order to achieve the goal of the research, exploratory factor analysis AND regression analysis were exerted. The findings show that the homogenization of the indicators affecting the quality of life in all cities is incorrect. Some concepts, such as the size of the city, are effective in compiling AND selecting the indicators affecting the quality of life. So, the indicators affecting the quality of life in each city can be different according to some concepts, such as the city's characteristics or the city's size. Examining study samples also shows that in SMALL cities, social indicators are more important due to strong social solidarity among people AND the high importance of social AND cultural concepts. Moreover, in middle cities, due to the importance of finding economic concepts AND urban services in people's lives AND people's less communication with each other AND the weakening of solidarity AND social connections, indicators of urban services AND facilities AND economic factors have the most importance in explaining the quality of life; this shows that the Quality of life indicators are different in all cities Extended Abstract Introduction Quality of life is a multifaceted AND dynamic concept that can be different from city to city AND region to region AND can be defined by various indicators. Not paying attention to this issue AND considering the concept of quality of life equally in all cities has caused the level of quality of life to decrease in many cities, especially middle AND SMALL cities, in recent years. On the other hAND, considering the concept of quality of life in cities to be the same, urban planners do not have a precise understANDing of the factors affecting the quality of life. Following this, the main goal of this research is to identify, identify AND compile effective factors for improving the quality of life in middle AND SMALL cities on an intra-provincial scale. In order to achieve this goal, the cities of Qazvin AND Zia Abad in Qazvin province were selected as study samples, so that according to the size of the city, in order to achieve the goal of the research, the factors affecting the quality of life are analyzed on an intra-provincial scale.   Methodology The research method is applied research based on quantitative methods. In line with data analysis, after extracting 60 indicators of quality of life, first, the indicators were separated into separate AND structured factors using the exploratory factor analysis method in SPSS software. AND then, step by step regression method was used to measure the effective factors in improving the quality of life in cities.   Results AND discussion The research findings show that based on exploratory factor analysis, 16 factors were extracted in Zia Abad city AND 15 factors in Qazvin city as effective factors on the quality of life in SMALL AND middle cities. In order to present AND explain the factors affecting the improvement of the quality of life in SMALL AND middle cities, the factors extracted from the factor analysis were analyzed by multivariate regression method AND step-by-step method. Furthermore, finally, (13) factors were introduced in Zia   Abad AND (13) factors in Qazvin as the main factors influencing the quality of life. The analysis of the findings indicates that in Zia Abad, factors such as life expectancy AND social relations, security, the state of urban services AND access to urban facilities, living expenses, the state of urban furniture, urban traffic, the state of offices AND housing have more effects in explaining AND improving the quality of life. In Qazvin, factors such as the state of urban services, the state of green AND public spaces in the city, the state of security AND economic opportunities in the city, the density AND hope of urban, economic, AND cultural life, the state of roads AND leisure in the city are effective in explaining the quality of life. Following this, according to the above findings, quality of life is a multidimensional AND dynamic concept that directly relates to the type of cities AND the specific characteristics of cities. Therefore, the quality of life AND its indicators can differ from city to city; because every city has its characteristics AND characteristics with citizens with different cultures AND thinking, which causes the factors affecting the quality of life to be different. Therefore, considering the quality of life AND its indicators to be the same in all cities is wrong, which can lead to the decline of the quality of life AND the failure of quality of life improvement programs.   Conclusion Finally, the research results indicate that quality of life is a simple concept covering various urban life aspects. This concept can be defined as a determining factor in the excellence AND progress of cities AND residents' satisfaction with their urban life. It is multifaceted AND dependent on place AND time. As a result, the perception of people in different cities AND communities about the concept of quality of life AND the factors affecting it can be different. Following this, factors AND indicators should be selected according to the characteristics AND conditions of that city in urban planning to improve the quality of life for each city. Thus, this research, using the classification of cities based on the size of the city, has presented factors specifically for middle AND SMALL cities, which in SMALL cities due to strong social solidarity among people AND the great importance of social AND cultural concepts, social indicators are more important. Moreover, in middle cities, due to the importance of finding economic concepts AND urban services in people's lives AND people's less communication with each other AND the weakening of solidarity AND social connections, indicators of urban services AND facilities AND economic factors have the most importance in explaining the quality of life; this shows that the quality of life indicators are different in all cities.   Funding There is no funding support.   Authors’ Contribution All of the authors approved the content of the manuscript AND agreed on all aspects of the work.   Conflict of Interest Authors declared no conflict of interest.   Acknowledgments We are grateful to all the scientific.

development of successful strategic marketing programs for the commercialization of new technology represents a challenge for SMALL AND MEDIUM sized technology-based firms. The mechanics of developing successful marketing strategies for technological innovations is a complex process from design to implementation. Technology-based SMEs play an important role in facilitating the “knowledge-based” or “smart” economies. However, technological superiority is not a guarantee for the success of a high-tech SMEs. Instead, the odds of success are maximized by a combination of technology superiority AND marketing capability. In this paper, the characteristic of technology-oriented SMALL AND MEDIUM enterprises have examined according to the published key studies in the field of SMALL AND MEDIUM sized COMPANIES, the factors AND barriers to the success of the COMPANIES mentioned briefly AND given that marketing has been diagnosed as one of the success factors of technologybased SMALL AND MEDIUM enterprises, we reviewed the challenges AND solutions of technology marketing to remind the managers of these COMPANIES that the success of a pure technology will not ensure the success of the company AND marketing as one of the key elements AND critical component of the success of technology-based SMALL AND MEDIUM enterprises should be a priority in their activities.

Empowering the role of SMALL AND MEDIUM-sized enterprises in the age of digital economy AND the development of digital entrepreneurship in them is important because these COMPANIES, especially if they are knowledge-based, are known as important sources of income, employment AND ultimately the driving force influencing economic development. Accordingly, the purpose of this study is to provide a model for the development of digital entrepreneurship in SMALL AND MEDIUM-sized knowledge-based COMPANIES in order to empower them. Therefore, in the first step of the research, the study background, semi-structured interviews AND qualitative method of content analysis were used to identify the factors influencing the development of digital entrepreneurship AND the creation of a basic framework. The results of the research show seven effective factors of business model, product innovation strategy, resource configuration, environmental factors, digital entrepreneurship ecosystem, individual factors AND organizational factors in the development of digital entrepreneurship in three structural, contextual AND content dimensions, which are environmental factors AND entrepreneurial ecosystem. Digital have the greatest impact on the development of digital entrepreneurship in SMALL AND MEDIUM-sized knowledge-based COMPANIES.

Abstract This article aims to compare RW AND PW models in profit forecasting for SMALL AND MEDIUM-sized COMPANIES. The research method is applicable in terms of its purpose, AND it is an inductive AND quantitative research in terms of the implementation logic AND the nature of the data. Financial statements in the period of 2011 to 2021 have been used to collect data. In order to select the appropriate statistical sample, the systematic elimination sampling method was used. In this method, firstly, the SMALL AND MEDIUM-sized COMPANIES are identified, according to the number of employees AND the nominal value of the capital, AND conditions are defined for the selection of the sample, AND those that do not have the mentioned conditions are removed from the sample. These conditions are determined according to the hypothesis test model AND research variables. Also, in this article, the panel model AND Eviuse software have been used to extract the proposed model from the principal component analysis approach AND to fit the model to the observations. According to the results obtained from the analysis presented in this research, it can be seen that the new model provided for profit forecasting is more effective than the profit forecasting of RW AND PW models, AND this issue confirms the ability of regression models to forecast profit in the field of financial AND profitability strategies for SMALL AND MEDIUM-sized COMPANIES. Extended Abstract Introduction Financial analysts have grown in number AND importance over the decades. The first societies of investment analysts can be traced back to 1925 in Chicago, 1937 in New York, AND 1962 in Europe (Graham, 2004). The profession became formalized due to its ever-increasing presence AND application in capital markets around the world. Analysts provide useful information in the form of stock releases, price targets, AND earnings forecasts as a link between management AND investors. Much research has been done on sell-side analysts AND their earnings forecasts, as these forecasts increasingly influence investors as well as management (Azevedo, 2020). Without information about firms AND their projects, financial markets cannot perform their function of capital allocation. Some information is freely available to investors, but most information is expensive AND must be produced by trained professionals. The profession of financial analysts has evolved to perform this economic function AND has provided investors with detailed AND specialized public information that would be very difficult to do without them. Financial analysts have the necessary combination of technical expertise, industry knowledge, AND financial activity needed to understAND the future prospects of COMPANIES. By publishing analyst reports, they bring stock prices closer to intrinsic values, making the market more efficient in terms of information AND directing capital flows to promising investments (Higashikata, 2020). Traditionally, analyst reports contain three separate pieces of information: 1) earnings forecasts, 2) price forecasts, AND 3) recommendations on whether to buy, hold, or sell. These forecasts AND recommendations can publish private information or create new information from public information, AND the change in information has a significant impact on the stock market price. Previous research has shown that revisions to buy or sell recommendations change investor responses. Specifically, recommendation reductions AND negative forecast revisions are considered to convey bad information, while recommendation updates AND positive forecast revisions are considered to convey good information (Higashikata, 2020). Takamusto AND Akono (2019) show that specific factors of countries' information environment can influence the importance of information disclosed by firms, such as accounting stANDards AND governance quality. These characteristics affect the user's understANDing of the information AND thus the stock price. In addition, uncertainty in countries' information environment can also affect the quality of analysts' forecasts (Hou, 2019). This is reinforced for emerging markets, because the accuracy of analysts' forecasts is strongly associated with the characteristics of each country's environment (Han, 2020). However, Han (2020) stated that analysts have a better ability to understAND the different accounting options of firms as well as issues related to countries' information environment. Therefore, according to the above, in this research, we are looking for whether the profit forecasting model presented in SMALL AND MEDIUM COMPANIES is more effective compared to the RW AND PW models. Literature benefit predict Profit forecasting has always been an important topic in accounting research because of its proven relationship with market returns. Profit forecasting not only reflects the development of accounting research but also uses the development of statistics AND computer science topics. Early research relies on rANDom step AND time series models to predict future profits. Some researches also included basic data in the prediction model based on linear regression or logistic regression (Harris AND Wang, 2018).   Research background In an article, Ansari (2023) discussed life cycle forecasting AND financial performance evaluation of COMPANIES using decision tree algorithm AND multi-criteria decision making techniques. The purpose of this research is to provide methods for decision-making that can be implemented with minimal specialized financial knowledge. For this purpose, a sample consisting of 172 COMPANIES admitted to the Tehran Stock Exchange by company-year was examined. First, financial ratios were prioritized using decision tree regression analysis for life cycle forecasting. Financial ratios have been analyzed as an independent variable AND cash flow statement data as a dependent variable. In order to accurately implement the presented models, MATLAB software coding environment was used. The results showed that cash adequacy ratio AND debt-to-equity ratio are the most AND least important, respectively. Then, using hierarchical analysis, financial ratios were prioritized to evaluate the financial performance of COMPANIES, AND leverage ratios AND profitability ratios were assigned the highest AND lowest ranks, respectively. The results of this research can be considered by all investors in the stock exchange to create a clear picture of the financial performance of COMPANIES. Melkian. et al (2023) in an article investigated the liquidity shock, financial flexibility AND speed of dividend adjustment in Tehran Stock Exchange. To measure the speed of dividend adjustment, which is a measure of profit smoothing, Gholtan regression was used according to the Lintner model; AND also the method of De Jong et al AND FalkANDer AND Wang have been used to measure the unused debt capacity AND the final value of cash, which is an index to measure financial flexibility. According to the limitations of the research, 105 COMPANIES admitted to the Tehran Stock Exchange during the period of 2010-2019 have been examined. The findings of the research show that the final value of cash AND unused debt capacity do not have a significant effect on the speed of dividend adjustment. Also, the liquidity shock has no effect on the relationship between the final value of cash AND unused debt capacity on the speed of dividend adjustment. Based on the obtained results, in justifying the positive relationship between the final value of cash AND the speed of dividend adjustment, it can be said that any company that has higher financial flexibility, faces less risk overall AND improves the performance of managers when using growth AND invested opportunities, AND finally smoothing their dividend is higher. Also, in justifying the negative relationship between unused debt capacity AND dividend adjustment speed, it can be said that any company that has a higher unused debt capacity, their dividend adjustment is lower. Research methodology In this research, in order to extract the proposed model from the principal component analysis approach, AND to fit the model to the observations, the panel model AND Eviuse software are used. The difference between the actual AND predicted profit is used to measure the efficiency of the models. The central AND dispersion indices for the research variables are determined for descriptive analysis of the variables before testing the hypotheses. In order to determine the average level of the variables, the average index is used. The dispersion of observations is measured by the stANDard deviation. Also, the difference of the variables from the normal distribution is measured using skewness AND kurtosis indices. In the present research, it has been used to test the hypotheses in the COMPANIES admitted to the Tehran Stock Exchange  Discussion AND results: The adjusted coefficient of determination in the first regression model is equal to 0.65 AND in the case of RW model 58% AND PW model 0.52; this shows that our regression model has been able to provide a more accurate relationship than the other two regression models with the components of profit forecasting, thus, model-based profit forecasting is more efficient than the other two profit forecasting models. Therefore, these results are consistent with the stated claim AND at the confidence level of 95, it can be claimed that our profit forecasting model is more efficient than the RW AND PW models. Conclusion: In this research, first, the statistical population AND the COMPANIES included in this population were examined. Then the volume AND sampling method were determined. After that, research hypotheses were stated. In the following, the research method AND the method of data collection were discussed; Also, the variables examined in the research were introduced AND how they were calculated was explained. After the definition of the research variables, the statistical methods necessary to check the statistical hypotheses AND their analysis were discussed. Based on this, the present research for the first time compares model-based forecasting AND profit forecasting based on RW AND PW models in SMALL AND MEDIUM-sized COMPANIES, AND according to the results obtained from the analysis presented in this research, it can be found that the proposed model for profit forecasting is more efficient than profit forecasting based on the other two models, AND this is a confirmation of the ability of regression models to forecast profit in financial fields AND the profitability of stock price forecasting strategy in the Tehran stock exchange also confirms.

Aim AND introduction: In recent years, the importance of SMALL AND MEDIUM-sized COMPANIES as the backbone of countries' economies has become clear to everyone. The role AND position of SMALL AND MEDIUM-sized COMPANIES in the world are increasing. Until the 80s, the management literature primarily focused on large COMPANIES AND their structures, management, AND control. Conquering the country, along with the occurrence of several economic recessions that highlighted the inefficiency of such COMPANIES compared to larger corporations, captured the attention of academics AND business professionals towards downsizing AND the importance of SMALL AND MEDIUM-sized enterprises (SMEs). Exporting has been proposed as one of the strategies for market development by such COMPANIES, primarily for the purpose of ensuring continued survival AND internationalization. SMALL AND MEDIUM-sized COMPANIES are less likely to succeed than large COMPANIES due to their limitations. Therefore, patterns AND models have been developed to evaluate the readiness of these COMPANIES to undertake this task. But SMALL AND MEDIUM-sized Iranian COMPANIES experience completely different conditions that require different models AND patterns for their operations. Methodology: The present study has utilized a mixed method approach, incorporating exploratory composite parts - the grounded theory model - as a research strategy. This approach involves theorizing the foundation data AND testing the theory using the structural equation model, with the aim of creating a model for assessing the export readiness of SMALL AND MEDIUM-sized businesses. First, in the theorizing phase, 25 top exporters were purposefully sampled in Tehran province. Interviews were conducted AND analyzed based on Strauss AND Corbin's systematic approach. Then, various statistical tests were performed to verify the model of different dimensions on a SMALL sample. In the quantitative dimension, the statistical population consisted of 408 members. However, based on Cochran's formula, the sample size was estimated to be 198 members. After distributing 240 questionnaires among the community using a non-probability sampling method AND excluding any defective or invalid questionnaires, the researchers ultimately included 198 questionnaires for the final analysis. In the qualitative part, to ensure the validity of the current research, the researcher conducted a thorough examination of the theoretical foundations AND background of export readiness assessment. Prior to designing the interview questions, the researcher also studied the process of designing AND conducting interviews. In the quantitative part, the "Goba AND Lincoln method" was used to assess the reliability AND trustworthiness of the conducted interviews. Cronbach's alpha was employed to calculate the reliability, AND each criterion demonstrated a reliability rate exceeding 97%. The questionnaire was prepared, confirming its reliability. In this research, the grounded theory was utilized to analyze the qualitative aspect of the study. Descriptive statistics, such as averages, were employed in the analysis of demographic factors. Additionally, structural equations were utilized in the inferential statistics section to address research questions AND test hypotheses. Finding: Based on the grounded theory, the model was achieved through the stages of open, central, AND selective coding. This process helped identify the key dimensions AND categories of the research, resulting in the extraction of the conceptual model. From the combination of key points AND the extracted codes, a total of 121 codes were obtained. Additionally, 25 sub-categories AND 6 main or key concepts were identified. Based on these findings, six main categories were extracted to form the research model. Based on the results of the quantitative part of the research, the desired model has successfully passed the statistical tests. The results indicate the importance of all the main factors, including: a) The main phenomenon of the research: factors related to managers AND decision makers, factors related to overseas activities, factors related to the availability of production factors, factors related to the marketing mix, factors related to entry requirements in the markets. b) Causal conditions affecting the export readiness of SMALL AND MEDIUM COMPANIES: causes caused by the domestic market (6 open codes), causes caused by the foreign (export) market. c) Background factors affecting the export readiness of SMALL AND MEDIUM COMPANIES: causes caused by internal restrictions, causes caused by international restrictions. d) Intervening conditions of SMALL AND MEDIUM-sized COMPANIES' export readiness: factors related to business coordinates, business structural factors, business attitudinal AND cognitive factors, business communication factors (customers, sales representatives, consultants), factors related to the field of human resources, business management factors. c) Effective strategies on the export readiness. Strategies related to SMALL AND MEDIUM-sized COMPANIES include marketing strategies, analysis of marketing strategy (Porter), human resources system strategies, analysis of the business environment strategies, AND analysis of the growth matrix (Igor Ansov). Marzi had sub-categories as well as their constitutive indicators. Also, other tests conducted on SMALL samples revealed other interesting results; c) Consequences of implementing export readiness of SMALL AND MEDIUM-sized COMPANIES: consequences related to human resources, business, marketing mix, production factors, AND external activities. Marzi had sub-categories as well as their constitutive indicators. Other tests conducted on SMALL samples revealed impressive results too. Discussion AND conclusion: Finally, the results of this research can help SMALL AND MEDIUM-sized businesses to evaluate their export ability before entering international markets AND if there is a difference between their ability AND the export requirements of the program to develop their strategies.

These days SMALL AND MEDIUM-sized enterprises (SMEs) are increasingly required to look for growth beyond their national markets, the increasing digitalization of the global economy provides them with ample opportunities for internationalization. Although digitalization is an important factor for internationalization success, there is a lack of empirical evidence on its effect on the internationalization of SMALL AND MEDIUM-sized enterprises. In this study, an attempt has been made to identify the factors affecting the digital internationalization of SMALL AND MEDIUM-sized enterprises AND finally present a model for this issue. This approach is qualitative research AND data have been collected in the form of semi-structured questions in-depth interviews with managers AND experts of COMPANIES that operating in international markets in the pharmaceutical industry. Then, data analyzed in three stages: open coding, axial coding AND selective coding by Atlas Ti. According to findings, factors affecting the digital internationalization of SMALL AND MEDIUM-sized enterprises, placed in two main categories that these categories are: context factors AND structural factors. At the end of the thesis the results of this study AND the final model are presented.

International Financial Reporting StANDards for SMALL AND MEDIUM Sized Entities (IFRS For SMEs) is a set that has less requirements than international financial reporting stANDards. SMALL AND MEDIUM enterprises are being adopted in many countries AND these stANDards are under consideration in Iran. It is necessary that this set of stANDards be examined before application. In the present study, by using the fair value approach in SME reporting stANDards, the impact of this approach on the performance indicators based of SME-stANDards has been investigated. The main purpose of this study is to investigate changes in performance indicators after applying SMEs stANDards. The statistical population of this research is the subsidiry COMPANIES of the public COMPANIES whose activities are investment AND 95 COMPANIES selected as sample. The research period is 2015 to 2017. Therefore, using historical data in the audited financial statements of these COMPANIES AND the fair value of the investment portfolio of these COMPANIES based on the trading portfolio AND the report on the status of the portfolio in the codal website, changes in return on assets ratio (ROA) AND return on equity ratio (ROE) as performance indicators, is evaluated statistically after applying the fair value approach AND compared with the indicators based on Iran's accounting stANDard. The results indicated that the ratio of return on assets AND return on equity as performance indicators, after the implementation of the International Financial Reporting StANDard for SMALL AND MEDIUM sized entities did not change significantly.

In order to improve the export economic performance, it is necessary to have a detailed knowledge of the markets AND competitors AND then, by analyzing the markets AND identifying opportunities AND threats, provide appropriate strategies to strengthen exports, which includes improving the quality of products, increasing production efficiency, AND using new technologies. AND improving production AND export processes. These measures, with the help of effective marketing strategies, appropriate financial facilities AND support for the development of technology AND innovation, can help improve export economic performance. average food) has been The statistical population of this research consists of two groups: 1- academic experts in the field of export, 2- personnel of SMALL AND MEDIUM export COMPANIES in Tehran province, the snowball method was used to select the sample in the qualitative population AND the available sample method was used in the quantitative population. Finally, 20 experts AND 217 personnel of SMALL AND MEDIUM export COMPANIES were selected as samples. The statistical results showed that 78 influencing variables influence international markets, AND statistically, all of them are effective. There are 33 effective components of international market penetration, according to the mentioned model, international market penetration includes 5 dimensions, 33 components, AND 75 indicators, AND compared to the initial research model, which includes 5, 33 components, AND 78 indicators, 3 indicators in the model The final one was removed AND the rest of the components AND dimensions were confirmed in the final model while having the appropriate factor load.