فصلنامه مطالعات مدیریت کسب و کار هوشمند
پیاپی 38 (زمستان 1400)

Social media, as an advancement in information technology is one of the most appealing topics to the public sector. Governments need to take measures to profit from this technology so that they can offer the most sought-for today's services. The COVID-19 pandemic and the necessity of providing virtual services have additionally highlighted social media technology in public sector. This study aims to propose a social media-based maturity model to deliver sustainable e-government services (e-government 2.0) in developing countries. The various dimensions of the model were identified by using the mixed research approach. For qualitative investigations, data were collected by literature review and semi-structured interviews and thematic analysis. For quantitative assessments, data were gathered through a researcher-made questionnaire and analyzed by a one-sample t-test and the two-way chi-square test. The dimensions of e-government 2.0 maturity model were initial phases (information transparency activities), managed phases (knowledge creation and management), defined phases (participation and collaboration), quantitatively managed phases (activities, real servicing, and transactions), and optimized phases (smartening up service delivery).

Today, in the age of digital developments, financial technologies (fintechs) have become an integral part of the banking industry. These technologies have challenged the future of the banking industry. So the purpose of this study is to identify the future scenarios of the banking industry and fintech startups in Iran, on 1404 horizon. The research is applied according to the type of purpose and exploratory from the methodological point of view. By using purposive sampling and theoretical saturation, 17 interviews were done with co-founders of fintech startups and managers and experts in banking and Fintech industry. In the first step, using interview analysis and background review, 38 drivers influencing the future of the banking and fintech industry were identified. Among the mentioned drivers, 4 key uncertainties were identified using a combination of the results of two methods structural analysis and instantaneous Delphi. By plotting two possible scenarios for each of them in the future, 16 possible scenarios were obtained. In the meantime, some scenarios were omitted due to similarity and incompatibility to other scenarios. Based on the morphological analysis, out of 16 possible scenarios, 5 scenarios remained and the other scenarios were eliminated. Thus five scenarios include; "The paradise of fintechs in the banking system", "migration of fintechs”, "crucified fintechs", "resistance fintechs" and "creeping fintechs" were identified, which according to the experts, the scenario paradise of fintechs In the banking system was introduced as a favorable scenario in the horizon of 1404.

The present study was conducted to design a content marketing model and seeks to obtain information that can be used to identify the effective factors in content marketing and to design a comprehensive model thereof.

This research was qualitative in terms of method and was conducted using a three-pronged model. By studying previous research, questions related to said interviews with experts were identified and organized, and subsequently, the data collected during in-depth interviews were opened and coded on the axis of summarizing and finally making hypotheses. The statistical sample interviewed was 10 experts who were selected by non-probability sampling and judgment. Their opinions on the factors affecting content marketing were collected in the form of researcher perceptual theory and the answers were coded and analyzed using MaxQDA software.

From the categorization of participants' opinions, a total of 63 open codes were obtained, which were categorized into three structural, contextual, and behavioral areas of content marketing with central coding. The results show that there is a high consensus based on 22 concepts in behavioral factors, 23 concepts in underlying factors, and 18 concepts acting as structural factors affecting content marketing. Underlying and therefore behavioral factors have the greatest impact on content marketing, and the structural factor is considered to have less of an effect than these two mentioned factors.

The growing trend of the world towards new technologies and the formation of smart cities, despite their capabilities and benefits, has raised serious concerns about cybersecurity threats and citizens' privacy challenges. Tehran is no exception to this rule in the transition to a smart city. The present paper, in a descriptive survey study, aims to provide a framework for managing cybersecurity and privacy challenges in the transition of Tehran to a smart city. In this research, these challenges are identified by in-depth library studies as well as the implementation of fuzzy Delphi method among a sample of organizational experts (including ten senior managers and relevant officials of the Ministry of Communication and Information Technology, Tehran Municipality Information and Communication Technology Organization, and cyber police). Moreover, the degree of importance (weight) of each challenge is determined by the Fuzzy Best-Worst method (FBWM). The findings of this study indicated the high capability of the proposed framework in identifying and accurately weighting these challenges under uncertainty.

Today, many countries are institutionalizing the concept of smart city and implementing IoT programs that support smart city components, relying on the extensive IT infrastructure to improve the sustainability and quality of life needed by their communities. But using the Internet of Things to develop a smart city faces several challenges. Accordingly, the purpose of this study is to identify the main challenges of the Internet of Things and to understand the relationship between these challenges to support the development of smart cities in Iran. Initially, 14 major challenges were extracted based on domestic and foreign literature. Then, using the SWARA technique, the challenges were prioritized based on summarizing the views of seven relevant experts in the field of smart cities in Iran. In the next step, the underlying interactions between the identification challenges and their importance were determined using interpretive structural modeling (ISM). Then, MICMAC method was used to confirm the results. According to the findings, the challenges in the interpretive structural method were leveled at six levels. Then, to test the results of this stage, MICMAC method was used.The results of this stage showed that the lack of policies, perspectives and regulatory guidelines, high training, operational and maintenance costs, inequality (social), lack of transparency and responsibility, lack of technical knowledge among Planners, lack of technology infrastructure and lack of intelligence were identified as influential and key variables of the study.

Recommendation systems are one of the most essential tools for e-commerce intelligence. These systems with different types of data filtering methods are able to offer the best recommendations from a multitude of selectable items. Collaborative Filtering is the most widely used method of filtering data to make recommendations. One of the advanced models for predicting ratings in the Collaborative Filtering is the Singular Value Decomposing (SVD). In this paper, an optimized model of the film recommending system based on the SVD method is developed, which while reducing the dimensions of the matrices and the volume of computations and memory, and with iteration replacement method, has appropriate accuracy compared with other methods. For this research, a set of 100k Movie Lens datasets and Python programming have been used. Evaluation of error rate with root mean square error (RMSE) and mean absolute error (MAE) value shows a good improvement over similar methods in other references.vv

One of the most important factors in understanding customer behavior is identifying their expectations. Therefore, this study in order to design customer expectations model for platform with agent-based model approach. At first, for finding customers and servants expectations was used of semi-structure interview and then was done automatic clustering with using meta-heuristic algorithms in order to find different factors. Then, with the factor-based simulation approach, the model was designed in Any Logic software. After designing the model, using design method of Taguchi experiments (Qualitek-4 software), scenarios for the growth and development of the platform based on effective factors (liquidity the quality of communication and trust) designed on four levels and finally simulation was performed and scenarios were examined in the simulation environment. the research results showed that the appropriate level of platform growth and development indicators in the fourth level of liquidity, the fourth level of communication quality and the fourth level of trust. In addition, after implementing the optimal scenario in the simulation environment was determined that the percentage of value created on the Instagram platform due to the implementation of the desired scenario is equal to 0.934.

The rapid depletion of natural resources and growing awareness of the environmental deterioration have made sustainability one of the key elements enabling contemporary businesses to thrive. Among the most crucial sustainable practices is the application of Green IT due to the wide use of IT in various business sectors to enhance the performance of businesses. Green Information Technology (IT) has emerged as a vital IT governance concern to promote environmentally-friendly IT use and ecologically responsible business processes. according to various researches in green information technology, this research aims to design a green information technology using Meta-synthesis method. In order to design and explain a comprehensive model, all factors of green information technology have been identified through systematic literature review using 189 papers and content analysis. Then the importance and priority of each proposed factor was determined using Shannon quantitative method. The results reveal cost reduction, data center layout, employee stewardship and participation are the major factors in green information technology. At the end the research results demonstrate a comprehensive framework for green information technology factors.

The purpose of paper is to present a conceptual model of the IOT-based online monitoring system to improve the distribution system‌ of pharmaceutical, using the agent-based modeling approach. First, by reviewing the research literature and interviewing industry experts, the basic concepts are extracted and using the grounded-theory method, the conceptual grounded-theory model is compiled; finally, using the obtained model and performing the agent-based modeling steps, the conceptual model of the agent-based is extracted. Based on the findings, data quality, information and communication technology infrastructure, automatic measurement and evaluation, and automatic action and evaluation are among the factors affecting the IoT-based online monitoring system. Also, the agents of the organization, customers, suppliers, governance and information technology infrastructure, interact with each other and with the environment. Based on the results, the IoT-based online monitoring system is an effective way to improve processes, and decision makers can make smarter decisions with this approach.

Clustering is a common method for analyzing various data that is used in many fields, including statistical pattern recognition, machine learning, data mining, image analysis, and bioinformatics. Clustering The process of grouping objects similar to different groups, or more precisely, partitioning and dividing a set of data, into separate subcategories, the main point of which is not to be specific. The number of classes is in clustering. One of its most widely used uses is in the field of data, the clustering of which is performed by experts in taste. Bank customer clustering has been a challenge from the beginning, and it has been difficult to find consensus among experts to select a feature for grouping.
This dissertation seeks to provide a solution for dynamic clustering of bank customers. This clustering will be based on a genetic algorithm and will decide on the number of categories, members of each category, and the similarity criteria used. The dynamics of the method are based on the improvement of the LRFM method using the genetic algorithm. In other words, the genetic algorithm will try to find different information fields about the bank's customers in the database; Put the right fields next to the features used in the LRFM method and get better results for clustering the bank's customers. This process leads to the determination of the criterion of similarity of one customer with another customer and the degree of similarity between them.

The development of E-government is one of the priorities of the managers of the tax affairs organization in recent years that despite the growth of investments in the field of information and communication technologies and the necessity of E-government development in this field, So far in the E-government literature, the effective dimensions in the development of E-government has not been identified and has been neglected. Therefore, the purpose of this study was to investigate the effective dimensions in the development of E-government in the tehran tax affairs organization. This research in terms of purpose applied and in terms of method, was a combination of qualitative and quantitative methods. The statistical population in the qualitative section 15 experts and specialists and in the quantitative section was 1097 employees of the tehran tax affairs organization that with using Cochran's formula, 285 people were selected as a sample. In the qualitative section, purposeful sampling method  and in the quantitative section, stratified random sampling method was used. In order to analyze the data and confirm the model structure, chi-square and friedman ranking tests were used. The results showed that the effective dimensions in the development of E-government in order of importance are: technological, political-legal, cultural-social, human capital, organizational-managerial and economic-financial.