فهرست مطالب سید محمد باقر جعفری

Organizational misbehaviors are one of the organizational weaknesses and problems that researchers have always considered due to their importance and impact on organizational performance. This study aims to provide a Pattern of organizational misbehavior extracted from the research literature using the  meta-synthesis method. The statistical population includes articles published between 1995 and 2021. After screening, 60  articles were selected for final analysis. Data analysis was performed using a deductive approach to thematic analysis with MAXQDA 2020; from the analysis of articles, 281 codes were extracted and classified into 57 categories and five main themes. The main identified themes include the causes and context of the organizational misbehavior, moderating variables, mediating variables, the nature of the organizational misbehavior, the purpose of the organizational misbehavior, types of the organizational misbehavior, and its consequences. Extracting the present pattern to identify gaps in organizational misbehavior research can be useful in clarifying the direction of future research and managing them in the organization.

The Asian Productivity Organization (APO) reports a one percent increase in Iran's Total Factor Productivity (TFP) index when compared to the majority of Asian countries and some reference countries in the long-term horizon of 50 years. In fact, the growth of labor productivity between 2010 and 2019 was less than all Asian countries. The present study was conducted with the aim of presenting a productivity pattern based on social capital.  Using the meta-synthesis approach and MaxQDA software, and after selecting 79 studies from among 580 previous studies, the dimensions, components and indicators of the model were extracted and identified. Based on the research findings, 9 dimensions, 24 main categories and 163 sub-categories (code)were identified. The nine dimensions are trust building, communication management, learning and growth, cultural factors, facilitator strategies, organizational factors, human resources, achieving sustainable development and profitability. The results of the emphasis of the previous research on each of the main categories using Shannon entropy technique and Excel software showed that growth and maturity and economic programs are the most important and the least important categories among the 24 categories, respectively. It is suggested that all managers update the human capital management process in accordance with the social capital based productivity pattern by hiring expert consultants and creating a special office for productivity management. Then, while periodically evaluating productivity based on the proposed pattern, all payments, bonuses and promotions of employees and managers should be base on the amount of their effort and participation in order to increase social capital and productivity.

Despite the paramount importance of fostering a spirit of cooperation within educational systems and recognizing the pivotal role of teachers in enhancing the quality of the teaching and learning process, there remain notable deficiencies and limitations in achieving this objective. Identifying these shortcomings and devising strategies for improvement and assurance has become an imperative necessity. In light of this, the present study was undertaken with the primary goal of conducting a qualitative exploration of a model aimed at enhancing the collaborative spirit among teachers. The research methodology employed in this study was qualitative, utilizing a grounded theory approach. The research sample comprised 19 individuals who were closely connected to the research subject, selected through purposeful sampling. Data collection was facilitated through semi-structured interviews. In the initial open coding phase, a total of over 195 preliminary codes were identified. After further refinement and consolidation of similar codes during the axial coding stage, 77 distinct codes were delineated. Subsequently, during the selective coding stage, these concepts were organized into a model designed to enhance group cooperation among school teachers, consisting of 12 components, 21 indicators, and 77 codes following further refinement. In summary, the resulting model highlights the central phenomenon of elevating the spirit of cooperation among teachers. Within this model, strategic factors encompass managerial and behavioral components, while causal conditions encompass social, personal, and educational components. Intervening conditions involve entrepreneurial and legal components, and the outcomes comprise components related to teachers' voice and communication. Contextual conditions encompass economic, environmental, and cultural components. These findings offer valuable insights for planning and designing interventions aimed at fostering a cooperative spirit among teachers.

Nowadays, social networks are an essential part of daily life, and it's safe to say that the majority of the world's population uses at least one social media platform. With the advancement of technology and the prevalence of the Internet, social networks have become an integral tool for communication and information sharing. As more citizens turn to web 2.0 services and social media platforms, governments are increasingly considering using them as a channel for service delivery. In this research, we aim to identify the factors that impact the government's use of social media for service provision. By doing so, governments can gain a better understanding of the factors that influence their decision to enter this field and take more informed steps in this regard.
Research Question(s)
In this article, we aim to address two key questions: if the government intends to provide services through social media tools, which set of influential factors will be at play, and which of these factors will be driving versus prevented? Identifying these factors is critical for the government to better understand the factors that influence its decision to enter this field and take more informed steps in this regard.
Literature Review
According to Mergel's study in 2016, the adoption of social media in the American government requires careful consideration of two key activities: strategic alignment and routinization. Strategic alignment involves ensuring that the use of social media is in line with the government's overall objectives and priorities, while routinization involves establishing clear processes and procedures for using social media, as well as ensuring that it becomes ingrained in the daily routines of government employees and citizens alike. By taking these factors into account, governments can better ensure that the use of social media for service provision is sustainable and effective.
Gregory (2016) examined the relationship between public sector social media usage and citizens' trust in e-government websites. Using a sample of 1100 citizens in Seoul, South Korea, the study found that increased use of e-government websites is negatively correlated with citizens' satisfaction and trust. On the other hand, the findings suggested that the use of social media by the government can lead to higher levels of trust and satisfaction among citizens. While the study was limited to a single city in South Korea, it provides valuable insights into the relationship between government social media usage and public trust.
Wukick and Mergel (2016) investigated the repurposing of social media information in American public sector institutions. The study highlighted that government organizations often default to trusted sources of social media information rather than seeking out new sources, and that private institutions may utilize social media to communicate their messages directly to citizens. These findings indicate that the use of social media may be limiting the range of information available to the public and introducing a degree of bias into public discourse.
Reddick et al.'s (2017) research studied the utilization of social media, particularly Facebook, in providing government services. The study utilized a double-loop learning theory approach to evaluate the relationship between the government and citizens. The findings showed that the government uses Facebook to modify citizens' behavior toward organizations and promote greater support. Additionally, the study found that social media is effective in monitoring citizens' needs and prioritizing them based on different categories. Overall, this study suggests that social media can be a powerful tool in delivering government services and enhancing communication between the public sector and citizens.
Aizhan et al.'s (2017) study examined the utilization of social media in the e-government sector for the public health sector. The research was conducted as a systematic review, in which studies related to the topic were examined. Out of 2441 related studies, 22 were fully examined. The findings of the study suggested that transparency, accountability, public participation, and cooperation were prominent characteristics of using social media in the government service sector. The study aimed at providing insights into the potential benefits of social media for public health services and highlighting the need for further research in this area.
Medaglia and Zhu (2017) investigated the use of social media by Chinese government agencies. This study analyzed data from Weibo, a Chinese social media platform, and aimed to understand the public's opinion on government social media accounts. The study used a sample of 417 users and found that there was a lack of engagement and interaction on government social media, leading to a decrease in creative ideas. Additionally, users had a lower evaluation of government social media compared to other platforms. These findings suggest that government agencies may need to reevaluate their strategies for effectively using social media for public outreach.
Rodriguez et al.'s (2018) study investigated the strategies employed by different governments to utilize social media for providing services to their citizens. The research was conducted on Latin American local governments and assessed the impact of differing social media strategies on citizen participation in governmental decisions. The findings showed that the use of various social media platforms by local governments can lead to increased engagement from citizens and enhance their participation in decision-making processes.
Eom et al. (2018) addressed the issue of "Can social media increase government accountability?" This study was conducted in South Korea. The results of the study showed that the mayor of Seoul plays the most important role in Twitter networks. Especially, the mayor acts as a bridge between different categories of citizens and government officials and follows up on citizens' communications.

In order to investigate the drivers and preventers of social media usage for government service delivery in a meta-composite research framework, Sandelowski and Barroso's 7-step meta-Analysis method was utilized. This approach enabled the identification of a suitable number of articles that met the inclusion criteria. After applying the Glynn tool to evaluate the quality of the articles, 39 publications were deemed suitable for inclusion in the final review. A meta-combination method was subsequently used to determine the drivers and preventers of government social media usage for service delivery. The analysis revealed four factors - managerial, organizational, human, and infrastructural - that influenced the effectiveness of social media usage for service delivery. The final decision on the type of effect (propelling or preventive) of each of the factors was made based on a comprehensive review of the literature and an assessment of the existing limitations in the country from this perspective.

In this research, we sought to find a set of requirements that governments can identify before using social media tools to provide their services to the beneficiaries, and increase their chances of success in managing the service delivery process.
As a result, the 4 factors affecting the government's use of social media for service delivery were identified - managerial, organizational, human, and infrastructural. A decision on the type of effect of each factor (propelling or preventive) was made based on the information provided in the research and the limitations that exist in the country with regard to this perspective.
The management factors affecting the government's use of social media for service delivery include 4 sub-factors: transparency, enforcement, manager training, and capital budgeting. The study aimed to identify these requirements to increase the chances of success in managing the service delivery process.
Managerial factors:1-Transparency sub-factor: preventive
2-Executive sub-factor: preventive
3-The sub-factor of Manager training: preventive
4-Sub-factor of Capital budgeting: preventive
Based on the research findings, it is clear that the government needs to pay attention to the management factors, including transparency, enforcement, manager training, and capital budgeting, when using social media to deliver services. If these factors are not adequately addressed, they may serve as obstacles to the effective use of social media for service delivery. Therefore, it is recommended that the government take into consideration these factors and implement appropriate measures to maximize the benefits of social media-driven service delivery.
 The organizational factors affecting the government's use of social media for the purpose of providing services include 3 sub-factors of organizational policies, organizational structure and communication, and organizational processes.
Organizational factors:1-Sub-factor of organizational policies: preventive
2-Organizational structure and communication sub-factor: Preventive
3-Sub factor of organizational processes: preventive
It is imperative to consider the organizational factors, including organizational policies, organizational structure and communication, and organizational processes, when using social media to deliver services. Failure to pay attention to these sub-factors will act as hurdles in the effective use of social media for service delivery.
The human factors affecting the government's use of social media for the purpose of providing services can be broken down into four sub-factors: user education, user resistance, usability of the social media platform, and citizens' experience.
Human factors:1-User training sub-factor: preventive
2-User resistance sub-factor: preventive
3-Functionality sub-factor: preventive
4-Citizen experience sub-factor: motivator
After examining the findings, it is clear that human factors must be taken into account in order for the government to effectively use social media. Specifically, the factors that affect success include: user education, resistance to changing behavior, usability of the social media platform, and citizen's experience. If these factors are not addressed, they can act as obstacles to the effective use of social media. However, the factor of citizen's experience - established and early habituation to using social media - can act as a driving force to encourage the government to adopt social media.
The infrastructural factors affecting the government's use of social media for the purpose of providing services include 5 sub-factors of technical infrastructure, financial infrastructure, legal infrastructure, specialized infrastructure and cultural infrastructure.
Infrastructural factors:1-Technical infrastructure sub-factor: motivator
2-Sub-factor of financial infrastructure: preventive
3-Legal infrastructure sub-factor: preventive
4-Specialized infrastructure sub-factor: preventive
5-Cultural infrastructure sub-factor: preventive
It has been determined that infrastructural factors, including financial, legal, specialized, and cultural infrastructures, affect the government's use of social media for service delivery. Without these necessary components, the effectiveness of social media for this purpose may decrease. However, since the required technical infrastructure exists in the country and most regions, the infrastructure factor may serve as a driving force for successful implementation. 

 The government must be motivated to use social media to serve its beneficiaries. In order for this to happen, it is essential for the government to have the necessary will to provide its services via social media. To achieve this, it is important to identify the set of factors, including advantages (motivators) and obstacles (preventives), which will affect the government's use of social media. These factors should be used to create a positive influence on the government's performance.
With the help of motivators and stimulators, governments can increase the speed of their action. By understanding the obstacles that they may face on this path, governments can either independently or through the use of available resources, reduce or eliminate these obstacles, and streamline their actions.

Considering the current changes and conditions, greater attention should be given to promoting the spirit of cooperation among human resources working in schools in order to achieve organizational goals. With this in mind, the present study aimed to validate a model for improving group cooperation among school teachers. The research employed a descriptive-correlational design. The statistical population consisted of managers and teachers in the field of educational sciences in Qom City in 2021. A sample of 129 participants was selected through accessible sampling method and Cochran's formula. Data was collected using a researcher-made questionnaire consisting of 39 statements. To validate the proposed model, structural equation modeling was performed using PLS software. The findings indicated that the tool designed to test the proposed model had adequate validity and reliability. Additionally, the overall fit of the research model was appropriate and approved. The validation of the identified components showed that all paths had a critical value higher than the critical value (1.96) at the 95% confidence level, indicating the significance of the paths, the appropriateness of the structural model, and the confirmation of all the identified components. In conclusion, the proposed model was approved, and the designed questionnaire can be used to measure the spirit of group cooperation among school teachers.

Crowdfunding has become a modern and favorite financing channel worldwide. Crowdfunding is a new financing method that helps entrepreneurs acquire the financial resources needed for their projects. This study aimed to investigate the factors affecting individuals' interest in participating and investing in social crowdfunding projects. Using the Structural Equation Modeling (SEM) technique, the developed model was tested with the help of Amos software via the data obtained from 318 individuals. This paper examined the direct and indirect contextual variables: awareness of need, altruism, reputation, psychological benefits, efficacy, funder’s trust, and institution-based trust in the investment intention. Finally, it was observed that awareness of need, altruism, values, reputation, psychological benefits, efficacy, funder’s trust, and institution-based trust were the factors influencing people's intention to invest in social crowdfunding projects.

Despite the significance of mobile payments, research in this domain is still in its early stages. The objective of this study is to develop a framework for implementing mobile payment in Iran, using a behavioral approach. This qualitative research employed grounded theory methodology. Data was collected through interviews with 19 experts from the first mobile company in Tehran. The validity and reliability of the data collection tool (interview protocol) were assessed using formal and content validity approaches, as well as inter-coder agreement evaluation. Data analysis followed the procedures of grounded theory, including open, axial, and selective coding stages. The study results not only identify the stakeholders of the payment system but also provide a clearer conceptualization and outline various strategic aspects for its establishment. Moreover, the study identifies functions and subsequent consequences of implementing a mobile payment system within the macro environment, suggesting activities such as cultural context development, enhancing user experience, improving revenue models (fees), and personalizing services to strengthen the deployment framework. Overall, these findings offer researchers a basis for investigating more detailed and specific models within a macro and dispersed framework. Furthermore, it enables market participants to consider the diverse steps involved in establishing such systems in their respective fields and estimate potential outcomes.

The lack of correct mechanisms of assessment and evaluation of education in e-learning has caused managers to implement fleeting strategies and programs with additional costs. This is the result of the lack of proper identification of evaluation components in e-learning and training, and the digital formative evaluation process helps e-learning and training management systems to adopt appropriate strategies and apply the digital formative evaluation process to meet the main objective of learning, despite various models and frameworks in the field of e-learning and training so far no comprehensive model has been presented. It is necessary to consider the multiple dimensions of academic assessment and evaluation as an integrated one for achieving the same truly evaluation for learning. In this paper, in order to explain a comprehensive model, by systematic review of literature and using meta-classical qualitative research method, all dimensions of digital formative evaluation have been identified, then the level of importance and firstly, The nature of each of the effective factors has been determined based on the method of content analysis using Shannon's quantitative entropy method, so that this research has innovation in both methodology and results.

The concept of national innovation system has attracted a lot of attention during the last three decades. Modern theories describe the national innovation system as a set of organizations and institutions in the process of creating, distributing, and using knowledge and technologies with the aim of achieving strategic goals such as the sustainable development of the economic system and helping to increase the competitiveness of its subjects including governments at the international level interact. The purpose of the current research is to present the framework of the national innovation system based on the knowledge functions and the knowledge role of the actors of this system and to achieve this framework, the approach of systematic research synthesis has been used. Based on this, by studying and examining in depth 180 study sources in the form of articles, books, reports and other documents, six main knowledge functions including "creation, acquisition, dissemination, development, exploitation, and commercialization of knowledge" and four support functions including "support and foundation, financing", mediation and policy-making and regulation" and seven main actors "government, research organizations, financial institution - financial institutions, universities, and higher education centers, industry, intermediaries, society and supporters, and enablers" were defined. Based on main and supporting functions, related roles were extracted and actors were categorized based on roles. The final result of the research is the framework of the national innovation system with a focus on knowledge functions and a new category of actors identified in 5 related layers, including the main knowledge function as the most central layer, layers of supporting knowledge functions, knowledge roles and actors as the next layers and Finally, it presents the classification of the subsystems of the national innovation system based on the helix cycle and as the outermost layer.

ObjectiveIn the era of social networks, it can be said that people are heavily influenced by the experiences shared by others and have the desire to share experiences that may be impactful for others in this environment (Dedeoğlu et al., 2020). Sharing travel experiences on social media platforms is highly popular (Kock et al., 2020; Oliveira et al., 2020). Tourists have a strong motivation to explore suggestions and opinions shared by others to reduce their own risks and uncertainties (Su, Cheng, et al., 2020), as travel activities cannot be physically demonstrated or pre-evaluated unless the individual personally experiences them (Su et al., 2019). The nature of travel activities allows individuals to transcend the boundaries of their everyday lives (Wong et al., 2019) and offers a significantly different experience from their daily routines (Filep & Laing, 2018; Xu & Zhang, 2021). Sharing travel experiences plays a crucial role in the tourism industry and has an undeniable impact (Kirilenko et al., 2021; Su, Tang, et al., 2020; Wong et al., 2019; Zauberman et al., 2009).Given that numerous explicit and implicit factors strongly influence tourists' motivation to use social networks during their travels, with Instagram being one of the most extensively utilized platforms for obtaining and sharing travel information and experiences (Boley et al., 2018; Daxböck et al., 2021), this domain still requires further research. Considering the potential of social networks in enhancing tourism, this study aims to establish an interdisciplinary connection between social psychology, motivational theories, and social networks in the context of tourism. Sharing experiences in the online space by tourists is one of the primary sources for acquiring valuable information about various travel destinations. Therefore, identifying the factors that influence tourists' behavior and inclination to share these experiences holds significant importance. By identifying these factors, it becomes feasible to plan strategies for reinforcing such behavior. Consequently, based on suggestions from previous researchers regarding the need for further studies in this field, as well as examining internationally published articles and library studies, the researcher has chosen this topic for their research. In this regard, the main objective of this study is to identify the influential factors on tourists' sharing of travel experiences in online environments.Research MethodologyThe present study employed a developmental-applied research design with a correlation-based approach. The data collection method was a descriptive survey, and the study was conducted over a specific time period. The target population consisted of individuals who had traveled to various parts of Iran in the past decade and expressed a willingness to share their travel experiences online. Convenience sampling was used, and a sample size of 206 individuals was determined using the Cochran formula. The questionnaire used in the study included 78 researcher-developed questions, examining the impact of 26 identified factors on the inclination to share travel experiences. The Kolmogorov-Smirnov test was used to check the normality assumption of the data, and nonparametric tests were employed for analysis due to the non-normal distribution of the variables. The structural equation modeling (SEM) approach, specifically the Partial Least Squares (PLS) method, was used to test the research hypotheses. SEM is a powerful statistical tool for developing and validating frameworks, allowing for the examination of direct and indirect effects and model fit evaluation. SMART-PLS software facilitated the analysis and interpretation of the results.FindingsTo analyze the inferential findings of this study, the Kolmogorov-Smirnov test was used to examine the normality assumption of the data. The test indicated that the variables in this study did not follow a normal distribution, suggesting the use of nonparametric tests for analysis. The next step involved testing the research hypotheses using the structural equation modeling (SEM) approach in the Smart PLS software. The SEM analysis facilitated the examination of the relationships between variables and provided both statistical and graphical results. In the SEM analysis, the model fit was evaluated through various indices, including Cronbach's alpha coefficient, composite reliability, average variance extracted, and cross-loading. The validity of the measurement model was confirmed when these indices exceeded certain thresholds.The absolute T-values and path coefficients (beta) were examined to determine the significance and direction of the relationships between variables. T-values higher than 1.96 at a significance level of 0.05 indicated the confirmation of the hypotheses. Additionally, T-values of 2.58 and 3.64 at a significance level of 0.01 and 0.001, respectively, were also considered significant. Based on the data and the results, six factors, including gaining respect, openness to new experiences, suitable platforms for sharing, technological knowledge, perceived security, and the desire for positive feedback from other online users, significantly influenced the inclination to share travel experiences online. On the other hand, factors such as entertainment, self-expression, helping others, positive attitude towards sharing, high self-esteem, progress orientation, knowledge and awareness, friendship, gaining reputation, belief in content honesty, perceived ease, financial benefits, social interaction, and technological infrastructure did not have a significant impact on the inclination to share experiences online.Discussion & ConclusionTo examine the factors influencing experience sharing in the online space, 25 factors were identified from previous studies and investigated. The findings indicated that among these factors, gaining respect, openness to new experiences, suitable platforms for sharing, technological knowledge, perceived security, and the desire for positive feedback from other online users significantly influenced the inclination to share experiences online. The study confirmed six hypotheses, providing valuable insights for online businesses in the tourism and non-tourism sectors to better understand their audience's needs and tailor their content accordingly. It is suggested that further research should focus on foreign tourists visiting Iran, examining their inclination to share travel experiences on specific social media platforms to enhance their understanding of this field. The study was conducted with limitations such as reduced traveler willingness to travel due to various diseases, economic difficulties, and limited access to research resources due to high costs and internet restrictions.

Despite the enormous volume of data and the benefits it can bring to marketing activities, it is unclear how to use it in the literature, and very few studies have been conducted in this field. In this regard, this study uses dynamic capabilities view to identify the dynamic capabilities of data-driven marketing to focus on data in the development of marketing strategies, make effective decisions, and improve efficiency in marketing processes and operations. This research has been carried out in a qualitative method utilizing the content analysis strategy and interviews with specialists. The subjects were 18 professionals in the field of data analytics and marketing. They were selected by the purposeful sampling method. This study provides data-driven marketing dynamic capabilities, including; Ability to absorb marketing data, aggregate and analyze marketing data, the ability to data-driven decision-making, the ability to improve the data-driven experience with the customer, data-driven innovation, networking, agility, and data-driven transformation. The results of this study can be a step towards developing the theory of dynamic capabilities in the field of marketing with a data-driven approach. Therefore, it can be used in training and creating new organizational capabilities to use big data in the marketing activities of organizations, to develop and improve data-driven products and services, and improve the customer experience

Despite the importance of social media marketing in many organizations, including small and medium enterprises (SMEs), scattered and limited studies have been done to evaluate its performance. Therefore, the present study attempts to develop a comprehensive framework for evaluating the performance of social media marketing in SMEs using the well-known management of the balanced scorecard (BSC). This study is an applied-development study in terms of purpose and mixed-methods in terms of data collection. In order to achieve the research goal, in the first step, the qualitative method via interviewing with experts as well as a comprehensive literature review was applied and the indicators of the proposed framework were extracted. In the second step, a questionnaire was developed for the validation and weighting of dimensions and indicators. Besides, an evaluation of academic experts, experienced marketing managers in the field of social media marketing, and senior managers of small and medium enterprises was done. The findings of the study showed that the financial dimension with a weight of 0.257 was the first priority. The customer dimension with a weight of 0.255 was the second priority. The learning and growth dimension with a weight of 0.250 was the third priority, and then the internal business processes dimension with a weight of 0.236 was the last priority. The developed framework can be used as a tool to measure the strengths and weaknesses of social media marketing performance projects in organizations, especially SMEs.

With the expansion of cyberspace and the emergence of social media, the use of media space has been recognized as a common experience for corporate communication with customers and the exchange of information. In the past decade, social media has had tremendous success. Nowadays, implementing some form of online marketing through social media is very important for all businesses. Despite the importance of social media marketing in many organizations, including small and medium enterprises (SMEs), scattered and limited studies have been done to evaluate its performance. Therefore, the present study attempts to develop a comprehensive framework for evaluating the performance of social media marketing in SMEs using the well-known management of the balanced scorecard (BSC).

This research has been conducted using a mixed-methods approach in three phases as below:
In the first phase, a comprehensive literature review was conducted among the past studies on this field to identify the indicators and dimensions that were mentioned in the previous studies for assessing the performance evaluation of social media marketing.
In the second phase, through a qualitative approach, interviews were conducted with ten experts to identify and extract the indicators and dimensions of social media marketing performance evaluation in SMEs. Judgment sampling was applied for sample selection.
In the third phase, the research approach was quantitative, and a questionnaire based on the indicators and dimensions extracted from the earlier phases was used. The Likert scale was utilized to collect the perception of the respondents on the questionnaire items. For this phase, about 39 samples were collected.

In this study, interviews were conducted using a semi-structured exploratory approach to collect the data. Two criteria of credibility and reliability were used to validate the present study. To achieve these two criteria, the following steps were followed:
Credibility: for this purpose, the participant feedback method was employed, in which six interviewees were asked to provide feedback on the interviews conducted and the analyses obtained. This helped to obtain the agreement of the interviewees.
Reliability: to do this, all details of the interviews were recorded, and notes at every step of the research were taken. Voice recording and oral data writing were performed in all interviews. In order to calculate the interview reliability, the two coders (evaluators) agreement method was used.

The researcher, along with the research fellow, coded the three interviews. The percentage of agreement within the results as a measure of reliability was 0.8, which is more than the acceptable level of 0.6.
Also, to determine the reliability of the questionnaire, Cronbach’s alpha coefficient was calculated by SPSS software. The alpha coefficients of the studied variables were higher than the threshold value of 0.7. Therefore, it can be said that the questionnaire was valid. To analyze the data obtained from interviews, the content analysis method, which is the most common approach for analyzing data in the social sciences, was utilized in this research. The data gathered via questionnaires were analyzed using the sign test to confirm or reject the research indices, and the weighted average method was used to measure and rank the research indices via SPSS software.

After the code and indicators were identified for each interviewee in the first step, 65 indicators were extracted. It was found that 7 indicators are related to the financial dimension. Twenty-six indicators are related to the customer dimension, and 17 indicators are related to the internal business processes dimension. In addition, 15 indicators are related to the dimension of learning and growth. Also, with the results of the indicators obtained during the research, it was found that many indicators have been extracted from the study and review of the content of other studies by citing sources, and some indicators are just the result of interviews with experts in the field of social media in the executive and academic field. This part of the indicators, in turn, refers to the innovative aspect of the current research.

The top indicators identified in this study are as follows: the financial dimension (0.257), the customer dimension (0.255), the learning and growth dimension (0.250), and the internal business processes dimension (0.236). Also, with the results of the indicators calculated during the research, it was found that many indicators have been extracted from the study and a review of the literature content of other studies by mentioning the sources. And some indicators are just the result of interviews with experts in the domain of social media in executive and academic fields. This type of indicators, in turn, refers to the innovative aspect of the current research. The developed framework can be used as a tool to measure the strengths and weaknesses of social media marketing performance projects in organizations, especially SMEs.
This research has some limitations. First, the proposed framework is presented at the theoretical level and has not been used in practice. It is suggested to use the case study method to evaluate the selected company in terms of social media marketing performance. The second limitation of this research is that the mutual effects of the identified dimensions have not been considered in the framework. Therefore, it is suggested to investigate the mutual effects of dimensions and indicators using quantitative modeling methods such as DEMATEL in future studies. Third, the proposed framework generally provides a performance evaluation framework regardless of the media type. Therefore, it is suggested that future researchers identify social media marketing performance evaluation indicators according to the type of media used by the company.

Education, as one of the scientific, cultural and educational structures, despite having a huge human force, including caring and educated teachers and gifted and creative students, has been somewhat involved with the difficulties of research, which does not have a clear strategy for research, and this has caused It cannot define and institutionalize the place of research and researcher and their role in the progress and development and excellence of the society, and it only causes a large part of scholars to stay away from research, but it also reduces the motivation to study and creates the ground for depression and job burnout. In order to solve their problem, higher education institutions and research centers, but also education, should adjust to the necessity of reforming and changing the research structure and mechanisms and techniques and research management methods, and seek to increase the productivity of research, including effective measures in this field of the program. He pointed out the strategic planning of the existence of structures, methods, guidelines, organization of the use of technological equipment and human resources, and culture building, so that problems and weaknesses can be identified and solved with appropriate solutions, and the ground is prepared for the scientific and research dynamism of cultural workers. The realization of this important matter requires the determination of the authorities. and the custodians of education in order to be able to take a step in updating science and knowledge and cultural workers. In this direction, in order to realize the research goals of education and culture, examining the extent of cultural researchers' adherence to research ethics has been an inevitable thing, and knowing it in order to promote The qualitative and quantitative level of research and increasing the research efficiency of educators is very necessary. Therefore, in this article, the level of adherence to research ethics among the cultural researchers of Arak education is analyzed in order to provide a suitable model for promoting adherence to research ethics among educators.

Although with the increasing use of social media, the impact of user-generated content on customer decision-making has increased, no comprehensive research has been done to evaluate the quality of user-generated content on social media so far. Therefore, the purpose of this study is to provide a framework for evaluating the quality of user-generated content on social media. In the first stage of the research, the dimensions and indicators of the quality of user-generated content have been identified and extracted using the meta-synthesis method. The statistical population includes a collection of articles in the related fields collected by a library survey through the Internet. In the second stage, Shannon’s entropy-based approach has been used to prioritize the dimensions and indices extracted, based on the frequency of the obtained codes. According to the results from meta-synthesis, six main categories, 13 dimensions and 207 indicators have been presented as the final framework, which include the following: “content” (including textual and audio-visual dimensions), “validity” (including user credentials and information source credentials), “presentation” (including structure and form dimensions), “integrity” (including accuracy and security dimensions), “background” (including time and demographic dimensions) and “performance” (including usefulness, cognitive and socio-emotional dimensions). This study tries to inform managers and those active in the field of e-commerce, of how to create effective content so that it can benefit them from the new technology of social commerce.

In Iran, despite the increase in the number of international students, our knowledge of the factors that lead to the satisfaction of international students is very limited, therefore, this study was conducted to identify and rank the factors affecting the satisfaction of international students in Iranian universities.

The research is applied in terms of purpose. The factors affecting the satisfaction of international students were extracted from literature and classified into 7 categories and provided to students as a questionnaire. During a quarter in 2021, 532 international students from 30 different universities and 12 different nationalities answered to this questionnaire. The data were analyzed by using t-test, analysis of variance and Friedman

According to the obtained results, among the seven dimensions investigated in this study, the dimensions of technology and information technology, management and organizational programs, financial and economic costs and educational services have the greatest impact in the satisfaction of international students in Iran.

The factors affecting the satisfaction of international students in Iran in order of importance include: information technology, management and organizational programs of the university, financial and economic conditions, provision of educational services, scientific support, welfare facilities and social relations. Except for the factor of satisfaction with financial and economic conditions, there is no significant difference between the average level in the two gender groups of men and women. The importance of the factors are the same among different levels of education. Also, except for welfare facilities and social relations, the importance of factors was different among different age groups of international students.

Social media as an effective tool in small and medium businesses will create a wide range of valuable opportunities and significantly reduce costs. Today, the strategy of companies to interact with customers and build relationships and cooperation with other market elements has changed with the advent of social media. Is. Over the past two decades, business-related social media research has grown exponentially, but so far no comprehensive study has been conducted on the social values ​​of social media in small and medium-sized businesses and their prioritization. Therefore, the present study, by systematically reviewing the studies in the period from 2012 to 2019, 57 articles were selected and reviewed using the meta-combined method of selected articles and the commercial values ​​mentioned in them were coded. The identified values ​​were then prioritized using Shannon entropy method so that the five main categories of business value including operational value, financial value, strategic value, customer value and finally knowledge / information value were ranked first to fifth, respectively. The present study is innovative both in terms of findings and methodology in the field of using social media in small and medium enterprises.

The application of artificial intelligence (AI) in online marketing has created a revolution in this field, which has attracted the attention of many investors and marketing managers in this field. AI marketing uses artificial intelligence technologies to make automated decisions based on data collection, data analysis, and additional observations of audience or economic trends that may impact marketing efforts. AI is often used in marketing efforts where speed is essential. Since little research has been done on this issue, and the purpose of this research is to identify the applications of artificial intelligence in various aspects of online marketing and prioritize these applications. The present research is thematically one of the first studies that applies artificial intelligence in online marketing. There has been no comprehensive and continuous view of the entire chain of attraction, persuasion, sales, and after-sales services. Thus, this research provides a comprehensive view of its audience by examining all the members of it. This research was been conducted using a mixed method. In the qualitative stage, there were ten semi-structured interviews with experts in online marketing, artificial intelligence, and e-marketing. With the content analysis method, forty applications of artificial intelligence in online marketing were enumerated in four sections. They were categorized based on the marketing mix. The marketing mix refers to the set of actions or tactics that a company uses to promote its brand or product in the market. a typical marketing mix of price, roduct, Promotion, and Place. In the quantitative stage, using a questionnaire and the best-worst analysis method, the applications identified in the qualitative stage have been prioritized using the opinions of industry experts and the students of prominent Iranian universities familiar with artificial intelligence and online marketing. Best Worst Method (BWM) is a multi-criteria decision-making (MCDM) based on a systematic pairwise comparison of the decision criteria used to evaluate a set of alternatives with respect to a set of decision criteria. The salient feature of the BWM is that it uses a structured way to generate pairwise comparisons, which leads to reliable results. Product design and value creation, pricing and cost design, advertising and customer information, and product distribution were identified as four general areas in which 40 applications were classified and prioritized. Finally, nine applications were identified in the field of product design and value creation, nine applications in the field of pricing and cost design, and 16 applications in the field of advertising and customer information. In the field of sales place and product supply method, six applications were identified and ranked. Making advertisements in accordance with the previous behavior of users and customers' feelings in relation to advertisements had the highest priority. Also, the distribution of forces in distribution branches in accordance with the forecast of work pressure in each branch had the lowest priority. This study suggests that, in order to use artificial intelligence in online marketing, various types of artificial intelligence should be applied in the marketing mix matrix. A comprehensive review of the most appropriate solutions for the organization is needed to maximize the effectiveness and efficiency of the solutions in the organization.Considering the prioritization of different parts of the marketing mix, it should be noted that businesses should pay special attention to the use of artificial intelligence applications in online marketing in the field of advertising and customer information. Then, a focus should be placed on product design and value proposition, which leads to market knowledge and user interaction. After these two areas, pricing and cost design have almost the same weight as product design and value proposition, which shows their equal importance in this sector. The developed framework provides a comprehensive view of artificial intelligence in online marketing and helps organizations comprehensively identify solutions and prioritize them. Therefore, using the methods found here can solve a large percentage of marketing problems and guide businesses to achieve their marketing goals.This research can also be used as a tool to comprehensively evaluate the performance of organizations in using artificial intelligence in online marketing. By designing a scoring model based on the weights obtained in this study, it is easy to determine the status of companies in different industries and with different conditions in the use of artificial intelligence in online marketing and in accordance with the priorities. This approach will also help many traditional companies that have some online marketing techniques to design and optimize their marketing system as optimally as possible.

Nowadays, the importance of nobility has cumulatively grown among increasing competition between corporations and myriad of researchers and managers gravitate towards business model innovation as the guarantor of profitability and persistence. In spite of various models and frameworks related to business model innovation, no comprehensive model has been proposed so far to recognize and priority characteristics of business model innovation. In order to proposed a framework by systematic literature review of articles indexed in WOS and SCOPUS have been collected and 42 selected articles have been examined, interpreted and eventually combined by means of meta-synthesis method. It was found that the characteristics of business model innovation can be categorized as the overall four frames of innovation in content (including 2 macro-definitions of 1.value chain activities, 2.intra-organizational activities), innovation in structure, innovation in governance and innovation in value capture. Then the importance and priority of characteristics was determined using Shanon method. Eventually, requisite suggestions according to the findings of research have been presented.

 Redesigning the business model is a prerequisite for the development and survival of organizations in the digital age. Accordingly, instead of relying on static models, every organization should update its business logic in line with environmental changes and customer expectations by utilizing the capabilities of technologies. The purpose of this study is provide a systematic approach to business model innovation based on using digital technologies.

 In the first phase, business model innovation components were extracted from 42 selected articles. Then, by survey method and by non-random and purposeful sampling of technology experts and fuzzy analysis of the received questionnaires, the application of digital technologies in the innovation components of the business model extracted in the first phase was presented.

 In the first phase, the components of the model were identified in the five categories, innovation in value network macro-activities, innovation in intra- organizational macro-activities, innovation in structure, innovation in governance and innovation in financial affairs and themes. Then, by extracting the views of experts in the field of technology regarding the application of digital technologies, including seven groups of platform, connectivity, Actor-based product, sensor-based data collection, analytical insight generation, analytical interaction and augmented interaction, the business model innovation framework is presented.

 The findings indicate in response to environmental dynamics and changes, innovation in what dimensions and components of the business model and using which group of digital technologies should be considered.

Due to the widespread use of information systems, a large amount of data has been stored in organizations, and the analysis of this data is a valuable resource to help organizations making better decisions. This concept is known as business intelligence (BI) and is one of the most important factors for the success of organizations in the contemporary world. Given the importance of BI, it is necessary to systematically review the research conducted in Iran on it. The purpose of this research is to identify the topics researched in selected journals, analyze the dispersion and frequency of studies, identify research methods, the purpose of articles, the level of analysis of BI research and finally identify research gaps and provide the future research suggestions. The research was conducted by analyzing secondary data and systematically mapping the existing knowledge of BI in 6 selected databases. For this purpose, 2108 articles were reviewed and in the initial review, 1274 articles were selected and 91 articles were approved by studying the abstracts. Finally, considering the exclusion criteria, 81 final articles were selected and analyzed. The results show that the most thematic coverage of BI in these journals was the specific topic of knowledge management and general topic was BI tools with 44.45%. The most used research method was descriptive-survey with 34.57%, the most purpose was practical with 82.71% and the highest level of analysis used was community analysis with 66.66%. Finally, research gaps were presented in the form of future research suggestions.

Nowadays, tourism destination markeing professionals and managers have to seek a kind of attachment and blondness in the tourists toward tourism destinations by which tourism destination satisfaction and loyalty can be increased. considering the experiences which tourist have in their travel is important. The reason is that such a factor lead to tourism destination revisit intention and its recommendation to others. Unfortunately, past studies have focused on this issue rarely. This is why the present study aims to present a model for explain the effective factors on the tourism destination revisit intention and its recommendation to others. In the model, tourist involvement, tourist experience quality, and tourism destination satisfaction have been considered as the effective factors on the tourism destination revisit intention and its recommendation to others. The statistical population of this study includes inbound tourists who traveled to the holy city of Ghom in the second season of 2016. A sample of 200 tourists was selected randomly. The research data, which were collected by using a questionnaire, were analyzed through path analysis in the Lisrel. The findings showed that tourist involvement, tourist experience quality, and tourism destination satisfaction affect tourism destination revisit intention and its recommendation to others significantly.

In recent years, knowledge management has become a fundamental principle in the field of management. Since the introduction of knowledge management, many institutions have tried to measure the benefits of using this concept. Success in implementing knowledge management and continuing its usage largely depends on measuring knowledge management benefits. However, few studies were conducted on this issue. This study, by using the adaptive neural fuzzy inference method (ANFIS) via Matlab 2017 software, tried to provide a predictive model to measure the benefits of knowledge management in the organization. The study population consists of scientists and experts working in 15 branches of the Social Security Organization, with a minimum of five years of experience in knowledge management related tasks. Based on the results, the degree of compatibility of the estimates with the actual results and the predictability and accuracy of the results were discussed, and at the end, based on the results, guidelines were provided to the studied organization.

By using big data, companies can be accurately informed about future market trends and customer preferences. Accordingly, innovate in marketing activities. However, to take advantage of this new technology in marketing, elements and factors are needed. In this regard, the current study has identified the necessary Prerequisites for using big data to innovate in marketing activities. the methodology of current research is a qualitative method by getting interviews and using content analysis. The subjects were 18 experts in the fields of data science that were selected by purposeful sampling method. By analyzing the interviews, 6 main concepts and 17 sub-concepts were identified. The results showed that antecedents for using big data in marketing activities are data-driven culture, data-driven skills, data-driven systems creation, dynamic resources provision, data-driven marketing capabilities, and support and perception CEOs. The results of this study can be used to assess the readiness to use big data in the marketing activities of organizations to develop and improve products and services and better experience for their customers.

Seeding is the introduction of a new product to a portion of consumers (seeds) before it is widely introduced to the market, and is one of the most important drivers in the design of marketing campaigns and effective word-of-mouth advertising. This research aims to identify different dimensions of seeding through meta-synthesis. For this purpose, 68 articles that had studied the subject of seeding were selected and coded on the concepts extracted from them. In the analysis of chosen researches, from 189 primary codes, 90 indicators (selective code), 18 components (sub-dimension), and five dimensions (main component) were identified. For the first time in this paper, different dimensions of seeding were investigated by the meta-synthesis method. According to the reviewed articles, the concepts extracted from the literature are: 1) Factors affecting seeding with 33 indicators and seven components that are target community characteristics, target community homogeneity, message nature, environmental conditions, internal conditions, marketing tools, and implementation strategies; 2) Characteristics of seeding target market with 21 indicators and three components that are consumer characteristics, customer nature and characteristics of individuals; 3) Communication and networking of seeding with 15 indicators and three components that are a big picture of seeding, position of seeding and nature of social network; 4) Seeding and growth and development with 12 indicators and three components that are value creation, market growth and development and product growth and development; And finally 5) Seeding and marketing with nine indicators and two components that are marketing tools strengthen and customer experience strengthen.