Sajjad Pashaie; Parisa Mahmodpour; Mohammad rasol Khodadadi
Abstract
vv The aim of this study was to evaluate the mediating role of the sport participation in explaining the relationship between the uses of communication tools of information technology (Mobile Phone, Internet, Instagram, Telegram) by reducing the depression of adolescents in the Maku Free Zone. The population ...
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vv The aim of this study was to evaluate the mediating role of the sport participation in explaining the relationship between the uses of communication tools of information technology (Mobile Phone, Internet, Instagram, Telegram) by reducing the depression of adolescents in the Maku Free Zone. The population of the study was selected in simple random way and 265 teenagers were selected from among those who were doing exercise three sessions per week. This study was a solidarity descriptive survey. A questionnaire was used to collect data. The validity (content, convergence, divergence) and reliability (factor loadings, reliability of supplies and alpha coefficient) questionnaires were well within acceptable limits (α= %94). Relations between variables were found by using AMOS20 structural equation modeling and were analyzed by using ordinary regression weights and were standardized by the maximum likelihood estimation method. The results showed that information and communication tools (Internet, Mobile and Virtual Networks) cause depression in teenagers, and sports participation as a mediator variable can reduce the negative impact of information and communication technology tools on teenagers’ depression. Therefore, the use of Internet, mobile and virtual networks causes loss of face to face communication because of the creation of false appeal to users and causes people to be introspective. Therefore, people will stay away from direct communication, and finally this will result in depression and loneliness.v
Maghsoud Amiri; Iman Raeesi Vanani; Seyed Hossein Razavi Hajiagha; Taranoush Jafari
Abstract
Proper management and optimal allocation of financial resources will increase gross national product and growth, create jobs and increase public welfare. The purpose of this study is to present an investment strategy that has tried to pave the way for the development of the investing company in the financial ...
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Proper management and optimal allocation of financial resources will increase gross national product and growth, create jobs and increase public welfare. The purpose of this study is to present an investment strategy that has tried to pave the way for the development of the investing company in the financial markets. Therefore, the forthcoming research can be considered as applied in terms of purpose. Also, considering that in the present research, mathematical modeling, modeling, artificial intelligence, etc. are used and the optimization of the investor company's portfolio is evaluated with the proposed model, so it is a quantitative and descriptive research. This study evaluated the performance of the proposed model in three modes: prudent, moderate and risky investor company. The results showed that for all three cases, the proposed strategy performs significantly better than the market index and other previous strategies. At the end of the investment period, the risky portfolio was more valuable than other portfolios. On the other hand, a prudent portfolio has achieved a more stable and stable return. These results revealed that the proposed fuzzy programming is able to reflect the characteristics and desires of the investor company in the portfolio composition.
Ehram Safari; Ali Asghar Ansari
Abstract
One of the most important issues in the development of artificial intelligence is the adoption of the use of artificial intelligence by the private and public sectors. In other words, in order for artificial intelligence to be used in a country or industry, it is necessary to identify and evaluate the ...
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One of the most important issues in the development of artificial intelligence is the adoption of the use of artificial intelligence by the private and public sectors. In other words, in order for artificial intelligence to be used in a country or industry, it is necessary to identify and evaluate the important factors of adoption. The purpose of this study is to identify and rank the factors affecting admission in the public and private sectors in Iran. For this purpose, first, a set of models and factors affecting the adoption of technology were extracted from the literature and opinions of experts and were classified into three categories: technological, organizational and environmental factors Then, the most important factors in each category were determined through a collection questionnaire, and using nonparametric Friedman test for each category with the most important and least important criteria. In order to weight and prioritize the factors, the quantitative approach and BWM technique have been used. The statistical population of the study included 37 experts in artificial intelligence in the public sector and 45 experts in the private sector. According to the obtained results, in the public sector, 3 important factors of admission are the support of senior managers, the existence of the required infrastructure for artificial intelligence and the existence of specialized and capable forces in the field of artificial intelligence. Efficiency and productivity with the use of artificial intelligence, cost savings with the use of artificial intelligence and ease of use and learning has been easy.
MohammadHossein Ronaghi
Abstract
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 ...
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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.
Management approaches in the field of smart
Sahar Masah Choolabi; Kambiz Shahroodi; Narges Delafrooz; Yalda Rahmati
Abstract
Today, virtual businesses need to innovate in order to have a better market performance. But the ability of companies to acquire innovation is one of the serious challenges of online stores; Based on this, the present research has been done with the aim of designing a model for innovation on the market ...
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Today, virtual businesses need to innovate in order to have a better market performance. But the ability of companies to acquire innovation is one of the serious challenges of online stores; Based on this, the present research has been done with the aim of designing a model for innovation on the market performance of online shopping websites with the approach of narrative analysis. This study has a qualitative approach. The statistical population included all narratives related to the dimensions of innovation and market performance of prominent online shopping websites in the country. With the help of judgmental sampling method, 69 narratives were examined. Narratives have been analyzed by searching websites and blogs and using the three-step open, central and selective coding method in the form of a topic network. The results indicated 7 organizing themes and 161 basic themes. The identified dimensions include the business model innovation dimension (the sub-dimension of business model type and revenue flow), the organizational innovation dimension (the structure innovation sub-dimension, strategic innovation and innovation culture), the marketing innovation dimension (the product innovation sub-dimension, price innovation, distribution innovation , promotion innovation, advertising innovation, customer segmentation innovation, value proposition innovation and customer relationship innovation), process innovation dimension (technology innovation sub-dimension and safety innovation), credibility innovation dimension (trust innovation sub-dimension and expertise innovation) and market performance dimension ( sub-dimensions of financial performance and non-financial performance) which were included under the overarching themes of innovation and performance of prominent online shopping websites in the country.
Introduction
Market performance is a critical factor for any organization as companies that perform well can generate value over time. In light of the current coronavirus crisis, it is particularly important for online shopping websites to operate efficiently and compete with each other. For these businesses to thrive, they must continuously innovate and adopt new technologies. However, the significant challenge faced by marketers is not merely understanding the constituents of innovation. While previous studies have proposed different models in this area, fewer studies have presented a comprehensive framework that analyzes how various aspects of innovation impact the market performance of online shopping websites. Thus, to address this research gap, the current study introduces a novel framework that views innovation from a fresh perspective. The present study aims to develop a model that examines the effects of innovation on the market performance of online shopping websites, using a narrative analysis approach. Accordingly, the research question that needs to be answered is: what are the different dimensions of innovation in online shopping websites?
Literature Review
2.1. Innovation and market performance of internet businesses
Although research has been conducted on the relationship between innovation and market performance in various industries, there have been relatively few studies specifically focused on the electronic business sector. For instance, Saifullahi and Hamidzadeh Arbabi (2021) conducted internal research at Tejarat Bank, Fallah et al. (2021) examined companies in the petrochemical industry, Malek Mahmoudi et al. (2021) investigated sports clubs, and Hosseinpour et al. (2020) studied food industry exporters, while Dehghani Soltani et al. (2019) explored the hotel industry. All of these studies were conducted on both public and private sector enterprises. In addition, there are foreign studies that have examined the relationship between innovation and market performance in different industries. For instance, Fatonah, S (2022) researched small and medium-sized companies, Lartey et al. (2020) studied telecommunication companies, and Efrata et al. (2020) investigated the clothing industry, while Thi Canh et al. (2019) explored manufacturing companies. However, these studies did not specifically focus on stores or electronic businesses.
2.2. Literature review
Fatonah’s (2022) research revealed a positive correlation between market orientation, product innovation, and competitive advantage. Similarly, Muharam, Andria & Tosida (2020) found that disruptive technology moderates the connection between process innovation and financial performance. However, it was observed that this technology does not have a moderating impact on the relationship between market innovation and financial performance. Moulai, Yazdani, and Kazemi (2022) found that organizational innovation positively impacts export performance and is also related to both radical technological innovation and technological innovation. Ultimately, both types of technological innovation were seen to have a positive impact on export performance. According to Hosseinpour et al. (2019), strategic innovation has a significant impact on the performance of small and medium-sized businesses. In highly competitive environments, where there is only a slight difference in market conditions, strategic innovation has a greater influence on innovative performance, indicating that the stronger the competition, the more significant the impact of strategic innovation on innovative performance.
Considering the theoretical foundations and literature review, it can be concluded that while previous studies have identified different dimensions of innovation, only a few have presented a framework that includes other significant aspects such as business model and credibility. Thus, there is a need to develop a comprehensive framework that encompasses all aspects of innovation.
Methodology
This study employed a qualitative approach with a practical objective and utilized narrative analysis as the research strategy. The target population comprised all narratives related to the dimensions of innovation and market performance of popular online shopping websites in the country, including Digikala, Mediseh, Zanbil, Digistyle, MoTenRo, Khanomi, Baneh.com, Okala, Mobit, Faradars, Dindengar, Uzdellamart, Shipour, Divar, Tasufan, Torob, Filimo, Pol Ticket, totaling 83 narratives. The sample size was determined using judgmental sampling logic. To achieve this goal, all stories published on the websites were examined to ensure that they had specific authors and editing dates. These websites were then categorized accordingly. Afterward, each website was evaluated based on several criteria such as the presence of a communication channel, accessibility to managers and audiences, author and date of text insertion, number of visits, and an electronic trust symbol. Sites that did not meet these criteria were excluded from the study, leaving only 69 narratives for analysis. The data for this study was collected from textual and written stories found on online shopping websites. These texts were analyzed using narrative analysis with the aid of theme analysis. The analysis involved manually coding the narratives using the three-step open, central, and selective coding method, which then formed a network of themes.
Results
Using a comprehensive approach, this study developed a model by analyzing narratives gathered from credible domestic websites and applying the open, central, and selective three-stage coding method. In response to the research question, seven organizing themes and 161 basic themes were identified. The identified dimensions of innovation and performance include business model innovation (with sub-dimensions of business model type and revenue flow), organizational innovation (with sub-dimensions of structure innovation, strategic innovation, and innovation culture), marketing innovation (with sub-dimensions of product innovation, price innovation, distribution innovation, promotion innovation, advertising innovation, customer segmentation innovation, value proposition innovation, and customer relationship innovation), process innovation (with sub-dimensions of technology innovation and safety innovation), credit innovation (with sub-dimensions of trust innovation and expertise innovation), and market performance (with sub-dimensions of financial performance and non-financial performance). These were categorized under the comprehensive themes of innovation and performance of popular online shopping websites in the country and presented in a theme network.
Discussion
According to the findings, business model innovation - specifically the type of business model and income flow sub-dimensions - can impact the market's performance (both financial and non-financial). These results align with previous research in this area. Additionally, organizational innovation was found to have an effect on performance similar to previous studies, but only when considering sub-dimensions such as structure innovation, strategic innovation, and innovation culture. Thus, the identification of various sub-dimensions can be viewed as a novel aspect of this study. The marketing innovation dimension, which includes product innovation, price innovation, distribution innovation, promotion innovation, advertising innovation, customer segmentation innovation, value proposition innovation, and customer relationship innovation sub-dimensions, aligns with prior research results. Meanwhile, process innovation was found to impact performance in a similar way to previous studies, but only when considering sub-dimensions such as technological innovation and safety innovation among other dimensions identified in this study that affect the performance of online shopping websites. Thus, the novelty of this study is emphasized from this perspective. Ultimately, it was found that the credit innovation dimension, which includes sub-dimensions such as trust innovation and expertise innovation, is one of the other dimensions identified in this study that impact the performance of online shopping websites. As previous research has not focused much on this dimension of innovation, it can be concluded that this study's innovation lies in this aspect.
Conclusion
Overall, the findings indicate that online shopping websites looking to enhance their performance can do so by implementing various dimensions of innovation. These include business model innovation, organizational innovation, marketing innovation, process innovation, and credit innovation.
Acknowledgments
We would like to express our gratitude to the professors, experts, and online shopping website managers who assisted us with data collection.
Keywords: Market Performance, Innovation, Website, Online Shopping, Online Stores.
Data, information and knowledge management in the field of smart business
Payam Faghihi; Mehrdad Kazerooni
Abstract
AbstractAccelerating the agility of production control systems in today's dynamic production environment is one of the challenges that many types of research have been conducted using multi-agent systems to improve it. The current models of these systems have shortcomings such as limited predictability, ...
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AbstractAccelerating the agility of production control systems in today's dynamic production environment is one of the challenges that many types of research have been conducted using multi-agent systems to improve it. The current models of these systems have shortcomings such as limited predictability, low reliability in the decision-making process, poor ability to understand and interpret the current state of the system, control with many limitations, and generally the existence of error-prone systems. In order to solve these problems, the current research presents a new methodology for multi-agent production control based on integration with ERP, which improves the capabilities of the system in the face of the above deficiencies. The research method employed in this study is qualitative, and developmental-applicative, aiming to enhance the integration of multi-agent production control systems with ERP. The objective is to improve the flow of material, production, and the quality of semi-finished products on the production line by considering the parameters that influence them. The key accomplishment of this research is the development of a reliable production control methodology that encompasses three components: a data exchange framework, tools, and implementation. These components are derived from existing ERP information systems that are functionally mature and designed based on best practices with a focus on maintenance, modification, and performance, aiming to minimize errors. The developed methodology offers a practical and agile solution for enhancing production control using an ERP system, with a lower implementation cost than the implementation of a commercial ERP system with a separate multi-agent system. IntroductionAccelerating the agility of production control systems in today's dynamic production environment is one of the challenges that many types of research have been conducted using multi-agent systems to improve it. The current models of these systems have shortcomings such as limited predictability, low reliability in the decision-making process, poor ability to understand and interpret the current state of the system, control with many limitations, and generally the existence of error-prone systems. In order to solve these problems, the presented research introduces a versatile methodology developed to enhance the efficiency of data and material flow control within a production system. The methodology emphasizes the role of data flow in regulating material flow, making it agile and autonomous.The innovation lies in elevating the role of ERP modules from process flow reporting to that of decision-making software agents, aligning with the common nature of both systems. Consequently, higher levels of data integration between the production system and the Multi-Agent Production Control System (MAPCS) integrated with ERP are achieved, leveraging agent technology and best practices from ERP modules.This approach enables real-time responsiveness to changes in the production system, establishing an agile production control methodology capable of managing material flow dynamics. Furthermore, it represents a step toward addressing current MAPCS limitations.Literature ReviewThe advent of affordable computer technology marks a pivotal moment in the adoption of advanced IT-based production control systems (Karrer, 2012). Leveraging technologies that continually monitor and gather information concerning the real-time status of production systems, such as machines equipped with sensors actively participating in the production process and offering virtual representations of the production system's state, enhances data integrity for improved decision-making in production control (Huang, 2022).Over the last decade of the 20th century, agent technology emerged, giving rise to agent-based production planning and control models and extensive research into technology development based on these principles (Bär, 2022; Groß et al., 2021).Agent-based systems represent the next generation of software, capable of dynamic adaptation to the evolving business environment and addressing a wide array of production system challenges (Mesbahi et al., 2014). However, they do present ongoing challenges, including limitations in system state comprehension, restricted control, reduced decision-making reliability, and a generally increased risk of errors in design and implementation (De la Prieta et al., 2019; Balaji & Srinivasan, 2010).Concurrently, Enterprise Resource Planning (ERP) systems emerged as IT-based solutions in the final decade of the 20th century, witnessing rapid expansion in research and implementation across various organizations (Scharf et al., 2022; De Brabander et al., 2022; Febrianto & Soediantono, 2022; Senaya et al., 2022).The integration of agents with ERP systems holds the promise of enhancing ERP intelligence, allowing them to autonomously interact with their environment and execute self-directed actions while collaborating with other systems (Faghihi & Kazerooni, 2023).This paper introduces a novel solution: the development of a Multi-Agent Production Control Methodology (MAPCM) integrated with ERP system that encompasses three components: data exchange framework, tools, and implementation.MethodologyIn this study, a developmental-applicative research method has been employed with the goal of building upon the findings of prior fundamental research. The objective is to enhance and refine various aspects, including behaviors, methods, tools, devices, structures, and patterns. This iterative process aims to address the practical needs of the society's industries.Additionally, to gather the desired data, a qualitative research method has been employed. This approach is particularly useful for tackling complex problems and deriving meaningful, easily comprehensible conclusions accessible to a wide audience.Results4.1. Data exchange frameworkThe development of the Final MAPCM integrated with ERP framework proceeded in a systematic four-layer approach. To enhance comprehension of the progress in each stage and the data exchange within these layers, we represent the first layer's data in black, while the data from the second and third layers are depicted in blue and red, respectively.4.1.1. Layer 1: A Framework for streamlining production control data exchangeFigure 1, illustrates an exemplary data-exchange framework for production control, which serves as the foundation for the proposed framework (Frazzon et al., 2018). This framework leverages a Manufacturing Execution System (MES) as the central data hub, facilitating seamless data exchange to bridge the physical manufacturing and production system with a multi-agent system.The data-exchange framework, depicted in Figure 2, emphasizes the implementation of real-time inventory distribution, dispatching limitations, and delivery constraints throughout the production process. Also, effectively addresses the dynamic handling of inventory distribution and delivery constraints in response to unplanned and unscheduled maintenance operations. This capability is achieved through the collaborative efforts of the inventory control and the maintenance modules of the ERP system. After upgrading the ERP quality control module to a software agent, it conducts three-phase quality checks utilizing data from both human and cyber-physical systems. (Figure 3):- Phase 1:This phase is dedicated to assessing the quality of raw materials and consists of two sections:The quality of incoming warehouse inventoryThe quality of warehouse inventory during storage periods- Phase 2:Semi-product quality control during the manufacturing process- Phase 3:Quality of finished productsFigure 3. MAPCM integrated with ERP – based on quality control framework 4.1.4. Layer 4: Final MAPCM integrated with ERP frameworkThe final MAPCM integrated with ERP framework (Figure 4) was developed through concurrent implementation and application of the preceding layers.Figure 4. Final MAPCM integrated with ERP framework 4.2. ToolsCyber-physical systems offer rich sensory data. A network of sensors continuously monitors the condition of machine tools on the shop floor and tracks the work-in-progress status in the production system.4.3. ImplementationWhile constructing complex software agents from the ground up using Agent-Oriented Programming (AOP) languages can be challenging due to the skills and knowledge required, readily accessible agent-building toolkits like JAFMAS, JATLite, ZEUS, and Sodabot provide valuable alternatives.DiscussionAgent-based approaches are essential for future production control systems due to their decentralized decision-making, flexibility, and complexity-reducing capabilities. Integrating ERP modules into software agents and enabling data exchange and direct interactions among these agents can enhance self-management and intelligence in production systems. This integration reduces implementation costs compared to using separate commercial ERP software and a multi-agent system. Furthermore, real-time soft sensors become more accessible and user-friendly due to the software-based nature of production control agents.ConclusionThe developed methodology offers a practical, cost-effective, and agile solution to enhance production control through ERP integration. By harnessing the synergistic capabilities of agents and ERP modules for monitoring, decision-making, and control, the limitations of traditional MAPCS models have been resolved. This transition results in autonomous production control systems that reduce reliance on human intervention. This methodology leverages well-established ERP information systems, following best practices to minimize errors, and enhance maintenance, modification, and performance, ultimately striving for error reduction.
Management approaches in the field of smart
alireza rezanezhad kookhdan; peyman ghafari ashtiani; Mohammad Hasan Maleki; Majid Zanjirdar
Abstract
Traditional banking needs new fintech innovations and technologies to improve its processes and services. Various factors affect the cooperation of banks and fintechs, some of which are related to banks and others to the banking environment.The purpose of this study is to identify and analyze the strategic ...
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Traditional banking needs new fintech innovations and technologies to improve its processes and services. Various factors affect the cooperation of banks and fintechs, some of which are related to banks and others to the banking environment.The purpose of this study is to identify and analyze the strategic factors affecting the cooperation of banks and fintechs in Bank.The present study is applied in terms of orientation and has a quantitative nature in terms of methodology. Two methods of fuzzy Delphi and fuzzy dematel were used to analyze the data. The fuzzy Delphi method was used to screen the strategic factors of the research and the fuzzy dematel technique was used to identify the most effective factors. Two tools of interview and questionnaire were used to collect data. The research questionnaires were:Fuzzy Screening Questionnaire and effect analysis Questionnaire. Initially, through literature review and interviews with experts, 28 strategic factors were identified.These factors were screened by fuzzy Delphi technique.10 internal factors and eight external factors had a defuzzy number greater than 0.7 and were selected for analysis with fuzzy dematel.Analysis of internal factors with fuzzy dematel showed that the factors of the nature of the needs of the bank's customers,the future thinking of the bank's senior managers, the culture of risk-taking between managers and senior experts and the agility of the bank's structure and processes have the most net effect In relation to external factors, the factors of intensity of competition between banks, effective factors on the cooperation between banks and fintechs. IntroductionThe relationship with banks is not only beneficial for them but also brings threats and challenges. So, banks have resorted to using different strategies to deal with the possible threats of FinTechs, the most important of which is the formation of strategic partnerships. A strategic partnership is a cooperative arrangement between organizations, contributing to the competitive advantage of the parties. Some advantages of the strategic partnership between the banking system and FinTech are efficiency in speed, agility, cost, and attracting new customers. Some of the challenges faced by traditional banks are having complex structures, high level of formality, increasing operating costs, providing expensive and time-consuming banking services, lack of service innovation, and failure to meet customer expectations (Soltani and Tahmasebi Aghbolaghi, 2020). Through strategic partnerships with FinTechs, banks can overcome many of their inefficiencies.Most of the studies on banks and FinTechs have investigated the effects of financial innovations on the operational variables of banks, such as costs and performance. The challenges and opportunities of bank and FinTech partnerships have been evaluated by some studies. Moreover, some studies have extracted the patterns of bank and FinTech partnerships from the point of view of bank and fintech managers. Factors affecting the partnership between banks and FinTechs have been examined by a few studies. They obtained limited factors from the perspective of a few stakeholders. The strategic partnership between banks and FinTechs is affected by various factors, some of which are intra-organizational and some are extra-organizational. Accordingly, the study questions are as follows:What are the strategic factors affecting the partnership between banks and FinTechs?Which strategic factors have the most impact on the partnership between banks and FinTechs? Literature ReviewBy providing customer-oriented services, using Internet-based technologies, and facilitating the use of financial services, FinTechs have competed with traditional financial services (Suryono et al., 2021). FiTtechs offer more innovative, faster, and cheaper services than banks. On the other hand, banks have slower structures and processes than FinTechs. Many traditional institutions, such as banks, do not have a positive view of Fintechs (Romānova & Kudinska, 2016; Temelkov, 2018). However, the trend towards bank-FinTech partnerships has increased significantly recently (Buchak et al., 2018; Iman, 2019; Ky et al., 2019; Cole et al., 2019; Ya, 2020; Cheng & Qu, 2020; Saphyra & Zahra, 2021; Hoang et al., 2021). Banks and their managers have two important approaches to FinTechs. The first approach does not have a positive view of FinTechs, arguing that the risk of partnering with and investing in them is very high and that partnering with them can lead to various threats such as security risks. The second approach suggests that partnering with them, especially in research and development, can lead to the agility of banking structures and processes. Partnerships between banks and FinTechs can have various reasons, the main of which are reducing costs, increasing profitability, growing revenues, developing market share, reducing each other's risks, and providing optimal and unique services (Tahmasebi Aghbolaghi et al., 2021). Many studies have investigated the effects of FinTechs on banking indicators. Th These studies, which form an important part of the literature, aim to explain the effects and functions of FinTechs and their innovations in the banking sector. This relationship is accompanied by challenges such as regulatory (Buchak et al., 2018; Omarova, 2020), customer management (Suryono et al., 2020), security (Lee & Shin, 2018), integration and partnership (Phan et al., 2020), fee system (Koshesh Kordsholi et al., 2019), receiving international licenses (Payandeh et al., 2014; Koshesh Kordsholi et al., 2019), authentication and validation systems (Suryono et al., 2020), wallets (Agarwal & Zhang, 2020), and low financial literacy of users (Suryono et al., 2020). One of the most important challenges faced by FinTechs is the lack of effective and supportive laws. The laws enacted are mainly for the benefit of traditional institutions. They are mostly ambiguous and unpredictable. Banks and large financial institutions are reluctant to partner with FinTechs due to the ambiguity of laws and regulations. Materials and MethodsThis study was conducted to provide a framework for identifying and analyzing strategic factors affecting the partnership between banks and FinTechs. For this purpose, fuzzy Delphi and fuzzy DEMATEL techniques were used. These are quantitative techniques and use quantitative data for analysis. The fuzzy Delphi technique was used to screen the strategic factors of partnership between banks and FinTechs and the fuzzy DEMATEL technique was used to analyze the effectiveness of these factors. Since these techniques are quantitative, the study has multiple quantitative methodologies. Moreover, it is an applied study because of the benefit of its findings for the banking industry and FinTechs.The study was conducted in three steps. In the first step, the factors affecting the partnership between banks and FinTechs were extracted through a literature review and interviews with FinTech experts. In the next step, these factors were screened using the fuzzy Delphi technique. In the third step, the effectiveness of the screened factors was determined through the fuzzy DEMATEL technique. ConclusionThis study was conducted to identify and analyze the strategic factors affecting the partnership between banks and FinTechs. 28 factors were extracted through a literature review and expert interviews. 14 of the extracted factors were intra-organizational and the rest were extra-organizational. They were screened using the fuzzy Delphi technique, and 10 factors were eliminated. The intra-organizational and extra-organizational strategic factors were then analyzed separately through the fuzzy DEMATEL technique. Among the intra-organizational strategic factors, the nature of the needs of the bank's customers, the forward-thinking of the bank's senior managers, the culture of risk-taking among managers and senior experts, and the agility of the bank's structure and processes were the most effective, respectively. Among the extra-organizational strategic factors, the intensity of competition between banks, the fee system, the performance of the regulator in legislation, and the risks and security considerations concerning FinTechs, had a greater effect on the partnership between banks and FinTechs, respectively.Keywords: Financial Technology, FinTech, Banking Industry, Banking FinTechs, Fuzzy Approach.Traditional banking needs new fintech innovations and technologies to improve its processes and services. Various factors affect the cooperation of banks and fintechs, some of which are related to banks and others to the banking environment.The purpose of this study is to identify and analyze the strategic factors affecting the cooperation of banks and fintechs in Bank.The present study is applied in terms of orientation and has a quantitative nature in terms of methodology. Two methods of fuzzy Delphi and fuzzy dematel were used to analyze the data. The fuzzy Delphi method was used to screen the strategic factors of the research and the fuzzy dematel technique was used to identify the most effective factors. Two tools of interview and questionnaire were used to collect data. The research questionnaires were:Fuzzy Screening Questionnaire and effect analysis Questionnaire. Initially, through literature review and interviews with experts, 28 strategic factors were identified.These factors were screened by fuzzy Delphi technique.10 internal factors and eight external factors had a defuzzy number greater than 0.7 and were selected for analysis with fuzzy dematel.Analysis of internal factors with fuzzy dematel showed that the factors of the nature of the needs of the bank's customers,the future thinking of the bank's senior managers, the culture of risk-taking between managers and senior experts and the agility of the bank's structure and processes have the most net effect In relation to external factors, the factors of intensity of competition between banks, effective factors on the cooperation between banks and fintechs. IntroductionThe relationship with banks is not only beneficial for them but also brings threats and challenges. So, banks have resorted to using different strategies to deal with the possible threats of FinTechs, the most important of which is the formation of strategic partnerships. A strategic partnership is a cooperative arrangement between organizations, contributing to the competitive advantage of the parties. Some advantages of the strategic partnership between the banking system and FinTech are efficiency in speed, agility, cost, and attracting new customers. Some of the challenges faced by traditional banks are having complex structures, high level of formality, increasing operating costs, providing expensive and time-consuming banking services, lack of service innovation, and failure to meet customer expectations (Soltani and Tahmasebi Aghbolaghi, 2020). Through strategic partnerships with FinTechs, banks can overcome many of their inefficiencies.Most of the studies on banks and FinTechs have investigated the effects of financial innovations on the operational variables of banks, such as costs and performance. The challenges and opportunities of bank and FinTech partnerships have been evaluated by some studies. Moreover, some studies have extracted the patterns of bank and FinTech partnerships from the point of view of bank and fintech managers. Factors affecting the partnership between banks and FinTechs have been examined by a few studies. They obtained limited factors from the perspective of a few stakeholders. The strategic partnership between banks and FinTechs is affected by various factors, some of which are intra-organizational and some are extra-organizational. Accordingly, the study questions are as follows:What are the strategic factors affecting the partnership between banks and FinTechs?Which strategic factors have the most impact on the partnership between banks and FinTechs? Literature ReviewBy providing customer-oriented services, using Internet-based technologies, and facilitating the use of financial services, FinTechs have competed with traditional financial services (Suryono et al., 2021). FiTtechs offer more innovative, faster, and cheaper services than banks. On the other hand, banks have slower structures and processes than FinTechs. Many traditional institutions, such as banks, do not have a positive view of Fintechs (Romānova & Kudinska, 2016; Temelkov, 2018). However, the trend towards bank-FinTech partnerships has increased significantly recently (Buchak et al., 2018; Iman, 2019; Ky et al., 2019; Cole et al., 2019; Ya, 2020; Cheng & Qu, 2020; Saphyra & Zahra, 2021; Hoang et al., 2021). Banks and their managers have two important approaches to FinTechs. The first approach does not have a positive view of FinTechs, arguing that the risk of partnering with and investing in them is very high and that partnering with them can lead to various threats such as security risks. The second approach suggests that partnering with them, especially in research and development, can lead to the agility of banking structures and processes. Partnerships between banks and FinTechs can have various reasons, the main of which are reducing costs, increasing profitability, growing revenues, developing market share, reducing each other's risks, and providing optimal and unique services (Tahmasebi Aghbolaghi et al., 2021). Many studies have investigated the effects of FinTechs on banking indicators. Th These studies, which form an important part of the literature, aim to explain the effects and functions of FinTechs and their innovations in the banking sector. This relationship is accompanied by challenges such as regulatory (Buchak et al., 2018; Omarova, 2020), customer management (Suryono et al., 2020), security (Lee & Shin, 2018), integration and partnership (Phan et al., 2020), fee system (Koshesh Kordsholi et al., 2019), receiving international licenses (Payandeh et al., 2014; Koshesh Kordsholi et al., 2019), authentication and validation systems (Suryono et al., 2020), wallets (Agarwal & Zhang, 2020), and low financial literacy of users (Suryono et al., 2020). One of the most important challenges faced by FinTechs is the lack of effective and supportive laws. The laws enacted are mainly for the benefit of traditional institutions. They are mostly ambiguous and unpredictable. Banks and large financial institutions are reluctant to partner with FinTechs due to the ambiguity of laws and regulations. Materials and MethodsThis study was conducted to provide a framework for identifying and analyzing strategic factors affecting the partnership between banks and FinTechs. For this purpose, fuzzy Delphi and fuzzy DEMATEL techniques were used. These are quantitative techniques and use quantitative data for analysis. The fuzzy Delphi technique was used to screen the strategic factors of partnership between banks and FinTechs and the fuzzy DEMATEL technique was used to analyze the effectiveness of these factors. Since these techniques are quantitative, the study has multiple quantitative methodologies. Moreover, it is an applied study because of the benefit of its findings for the banking industry and FinTechs.The study was conducted in three steps. In the first step, the factors affecting the partnership between banks and FinTechs were extracted through a literature review and interviews with FinTech experts. In the next step, these factors were screened using the fuzzy Delphi technique. In the third step, the effectiveness of the screened factors was determined through the fuzzy DEMATEL technique. ConclusionThis study was conducted to identify and analyze the strategic factors affecting the partnership between banks and FinTechs. 28 factors were extracted through a literature review and expert interviews. 14 of the extracted factors were intra-organizational and the rest were extra-organizational. They were screened using the fuzzy Delphi technique, and 10 factors were eliminated. The intra-organizational and extra-organizational strategic factors were then analyzed separately through the fuzzy DEMATEL technique. Among the intra-organizational strategic factors, the nature of the needs of the bank's customers, the forward-thinking of the bank's senior managers, the culture of risk-taking among managers and senior experts, and the agility of the bank's structure and processes were the most effective, respectively. Among the extra-organizational strategic factors, the intensity of competition between banks, the fee system, the performance of the regulator in legislation, and the risks and security considerations concerning FinTechs, had a greater effect on the partnership between banks and FinTechs, respectively.Keywords: Financial Technology, FinTech, Banking Industry, Banking FinTechs, Fuzzy Approach.
Data science, intelligence and future analysis
Mohammad Hasan Maleki; Seyed Morteza Mortazavi; Shahriar Shirooyehpour; Mohammad Javad Zare Bahnamiri
Abstract
AbstractThis research has been done with the aim of developing Iran's banking scenarios with an emphasis on big data. The current research is practical in terms of orientation and exploratory in terms of the goal. It is also mixed in terms of its philosophical, pragmatic and methodological foundations. ...
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AbstractThis research has been done with the aim of developing Iran's banking scenarios with an emphasis on big data. The current research is practical in terms of orientation and exploratory in terms of the goal. It is also mixed in terms of its philosophical, pragmatic and methodological foundations. To carry out the research in the first stage, 20 key drivers of the research were extracted through literature review and interviews with banking and technology experts. After screening with the fuzzy Delphi method, 8 factors were removed and the rest were evaluated with the Marcus decision making technique. The findings of the research show that the two factors of "technology regulation" and "technology transfer costs" were chosen as key uncertainties for developing research scenarios. Based on these two key uncertainties, four scenarios were developed based on interviews with the focus group with the titles of comprehensive banking, static banking, searching banking, wandering banking. In the comprehensive banking scenario, everything is in its optimal state; Technology transfer costs have decreased and regulators are supportive of the technologies. According to the findings of the research, considering drivers, key uncertainties and alternative scenarios by managers and decision makers can improve the performance and increase the competitive advantage of banks.IntroductionFinancial innovations has been challenged the banking sector and can improve it. They cover a variety of financial businesses such as online lending, asset management platforms, trading management, mobile payment platforms, etc. All these services generate a large amount of data every day (Hasan et al, 2020: 1). Analyzing this volume of data is difficult, giving rise to the concept of "big data" (Munawar et al, 2020: 2). Big data as one of the important fields of future technology has attracted the attention of various industries (Raguseo & Vitari, 2018: 5206). In general, big data refers to a large volume of structured or unstructured data that is generated and stored at a high speed (Dicuonzo et al, 2019: 41). Big data has found its position in the banking industry; Because of the useful data they have stored in recent years (Rakhman et al, 2019: 1632). Recent applications of big data in banking have been for improving customer relationship management, marketing, optimizing strategic management and human resources (Parmar, 2018: 33; Hassani et al, 2018: 2). Therefore, it can be said that nowadays big data plays a major role in providing financial and banking services, and the realization of its potential benefits in banking is more from technical aspects and affects the organizational structure of banking and mobilizes a large number of different actors (Diniz et al, 2018: 151- 152). With changes in customer expectations and increased competition, the banking industry is no longer able to ignore technological innovations in the banking sector. Due to the numerous applications and benefits of big data in various industries, including the banking industry, and it's becoming more widespread in the future, this technology is becoming a prominent research topic (Phan & Tran, 2022: 6.)Research Question(s)What are the plausible scenarios for banking in Iran with an emphasis on big data? Literature ReviewMany studies conducted in the field of banking and big data deal with the role of big data in improving the performance of the banking industry (for instance: Shakya & Smys, 2021; Gonsalves & Jadhav, 2020; Hung et al, 2020; Parmar, 2018). Also, another part of the studies conducted with a future research approach in the banking sector without focusing on innovative financial technologies and specifically big data (for instance: Baumgartner & Peter, 2022; Eskandari et al,2020). The focus on innovative banking and financial technologies with a Futures Studies approach has been weak (for instance: Maja & Letaba, 2022; Murinde et al, 2022; Hajiheydari et al, 2021; Broby, 2021; Harris & Wonglimpiyarat, 2019). And the role of big data in the Futures Studies of the banking industry has been seen to be very limited due to the relatively large amount of data available in banks and its effect on performance and gaining a competitive advantage (for instance: Valero et al, 2020). Therefore, despite the studies conducted in the field of banking and big data, some of these researches have paid attention to the present time, and the researches conducted in the future of the banking industry have also been without focusing on the role of big data. Now, the most important theoretical gap in research is the lack of studies on the future of banking in Iran with an emphasis on big data. MethodologyThe current research is pragmatism due to the use of qualitative and quantitative methods from the perspective of philosophical foundations. It is also exploratory in terms of purpose due to the identification of drivers and practical in terms of direction due to the application of the results in the analysis of the future of banking in Iran. In the current research, two methods of literature review and interviews with experts are used to identify drivers, both of which are qualitative methods. According to Popper, the interview tool is based on the expert dimension. The literature review is evidence-based and uses articles and scientific texts to identify factors. Fuzzy Delphi, which is semi-quantitative and evidence-based, is used to screen and determine key drivers that require great accuracy. Then, to determine the key uncertainties, the MARCOS technique is used based on the importance and uncertainty indicators of the Global Business Network (GBN) approach, which is a quantitative and evidence-based technique. Finally, interviews with focus groups are used to write the scenario, which is a qualitative method based on the expert dimension. The theoretical community of the research includes academic experts and managers of the banking sector and are aware of new banking and financial technologies (Fintechs) and specifically big data. The selection of the participants is based on their knowledge and nobility of the research topic and the importance of their presence in the research, and finally 15 people were selected by purposeful sampling using the snowball method. Experts have at least 10 years of relevant work experience and a master's degree. ConclusionThis research has clarified the situation of this area by identifying the shaping factors and drivers of the future of banking in Iran. Two factors of "technology regulation" and "technology transfer costs" were chosen as key uncertainties for developing research scenarios. Based on these two key uncertainties, four scenarios were developed based on interviews with the focus group with the titles of comprehensive banking, static banking, searching banking, wandering banking. In the comprehensive banking scenario, everything is in its optimal state; Technology transfer costs have decreased and regulators are supportive of the technologies. Considering drivers, key uncertainties and alternative scenarios by managers and decision makers can improve the performance and increase the competitive advantage of banks.Keywords: Futures Studies, Driver, Scenario Planning, Banking, Big Data.
yazdan shirmohammadi; Arash Bostan manesh
Abstract
Using artificial intelligence technology, smart stores transfer a lot of customer and product information (big data) including facial recognition, smart sensors, smart shelves, automatic payment and interactive displays at high speed based on the fifth generation (5G) internet. Since the spread of the ...
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Using artificial intelligence technology, smart stores transfer a lot of customer and product information (big data) including facial recognition, smart sensors, smart shelves, automatic payment and interactive displays at high speed based on the fifth generation (5G) internet. Since the spread of the corona virus has changed the way of life and business today, that's why marketers have used new strategies based on artificial intelligence to advance. This research analyzed the hedonic factors of customers' purchases based on the Hedonic Information Systems Acceptance Model (HISAM). The sampling method of this research was simple random and its number was 404 people. The measurement tool in this research is a questionnaire. Statistical analysis was done using structural equation method and using SPSS and Amos software. To determine the causal relationship between the variables using the structural equation model method and significance levels in order to test the hypotheses, a p_value smaller than 0. 05 was considered. The results of this research showed that the perceived ease of use, perceived benefit and perceived enjoyment have a positive and significant effect on the purchase intention due to the technology readiness of customers. Also, the results of the research indicated that the mediating variable of technology readiness was effective from optimism, innovation, discomfort and insecurity, and perceived ease of use, perceived enjoyment, and perceived benefit had a positive effect on customers' purchase intentions from smart stores in the era of Corona.
soraya bakhtiari bastaki; peyman ghafari ashtiani; Ali hamidizadeh; Rasoul Sanavi Fard
Abstract
The growing evolution of social networks with intensified role in the business world and consequently in the advertising in one hand, and the ease of deception in such emerging media on the other hand, have increased the prevalence of deceptive advertising and false claims in the communication and commercial ...
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The growing evolution of social networks with intensified role in the business world and consequently in the advertising in one hand, and the ease of deception in such emerging media on the other hand, have increased the prevalence of deceptive advertising and false claims in the communication and commercial media. In this way, it is difficult for the audiences of social media ads to distinguish between the truthful and deceptive advertising and this can lead to distrust to social media advertising and reduced sales. In this regard, the present research aimed at providing a model for the perceived deception of social media advertising using grounded theory. For the purpose, in-depth and semi-structured interviews were performed among 15 people who had past deception related experiences in their purchase from social networks. Data analysis was undertaken using open coding method and MAXQDA 2020 software. Finally, the research conceptual model was designed based on 8 main categories, 15 sub-categories, and 71 concepts, and it was revealed that social media perceived usefulness and social media ads characteristics as “causes”, and media characteristics as “covariance” were effective on perceived deception. In this regard, customer knowledge and perceived trust were considered as “contingencies”. Consumer attitude was recognized as “condition”, and consumer characteristics was presented as contextual factor for such a process resulting in the occurrence of consumer psychological damage known as individual consequence of social media ads perceived deception.
Kamelia Emami; Bahram Kheiri; Mandan Momeni
Abstract
The present study aimed to provide a model for holistic strategic marketing plan formulation in online businesses. In this study, with a qualitative approach based on contextual theory and through in-depth interviews with experts in the field of strategic marketing planning in the field of online businesses, ...
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The present study aimed to provide a model for holistic strategic marketing plan formulation in online businesses. In this study, with a qualitative approach based on contextual theory and through in-depth interviews with experts in the field of strategic marketing planning in the field of online businesses, the model of holistic strategic marketing plan in online businesses is presented. The participants were selected through purposive and snowball sampling at the same time and the interviews continued until theoretical saturation was reached and finally, 10 in-depth interviews were conducted. In order to analyze the data, the principles related to grounded theory (open and axial and selective coding) were used and concepts and categories were created. The results of data coding led to the identification of 130 basic concepts that were classified into 15 main categories. Finally, the conceptual model of the research includes 6 main parts of causal conditions (holistic marketing, customer relationship management, components of moving from offline to online planning, online marketing mix, data and information and the mental paradigm of managers), field conditions (prediction of future environmental changes and values), intervening conditions (online business characteristics and change), focal variable (online holistic strategic marketing plan), action and interaction (determination of operational plans and implementation of operational plans) and consequences (organizational performance and evaluation and control) were extracted. The results of the present research can be used in academic circles in order to create and store knowledge and for companies active in the field of online businesses and marketing managers.
Ra,min Kangarlou Haghighi; Abbas Toloie Eshlaghy; Mohammad Reza Motadel
Abstract
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 ...
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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.
Management approaches in the field of smart
Mahsa Akbari; mostafa bigdeli; Parvaneh Charestad
Abstract
AbstractGamification is a relatively new concept that has seen a significant increase in its use in recent years. Gamification involves the application of game elements in a non-gaming environment to create a gaming experience related to a product or service. The aim of this research is to investigate ...
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AbstractGamification is a relatively new concept that has seen a significant increase in its use in recent years. Gamification involves the application of game elements in a non-gaming environment to create a gaming experience related to a product or service. The aim of this research is to investigate the impact of different aspects of gamification (immersion, achievement, social) on customer engagement (emotional, cognitive, social) in the online store of Digikala. The research population consists of consumers and users of the Digikala website who have made at least one purchase on this site. In this regard, 222 questionnaires obtained from Digikala website users' data were analyzed. The research model was designed by reviewing the literature related to the research topic and previous studies, and it was analyzed using structural equation modeling. Finally, it was determined that the aspects of gamification have a positive and significant effect on customer engagement. The immersion aspects of gamification have a positive impact on emotional aspects of customer engagement, the achievement aspects affect the cognitive aspects of customer engagement, and the social aspects of gamification also have a stronger positive impact on the social aspects of customer engagement.IntroductionGamification has gained recognition as a powerful tool for establishing customer engagement in recent years, garnering significant attention both in industry and academia (Huotari, 2017), (Hamari et al., 2014), (Hamari et al., 2014b). This is because the inherent nature of play and the potential for possible achievement evoke positive emotions in people. In marketing, gamification is a means to elicit positive emotions in customers for the sale of a product or service. The use of gamification helps consumers spend more time on your website, increasing the likelihood of them making a purchase. In this context, gamification can be described as the use of game design in a non-gaming environment (Deterding et al., 2011). In other words, gamification seeks to replicate the effects of games, including motivation, excitement, and repetition, in a real-world context. Therefore, gamification technologies have the capability to manipulate social and individual factors to motivate customers and influence their intentions (Shang & Lin, 2013), (Jackson, 2009).As online games and social software continue to advance and become integrated into e-commerce businesses, they create new patterns that enhance user experiences and encourage active participation (Hsu & Chen, 2018).With the expansion of online businesses, the use of effective marketing techniques to attract customers has become crucial. In this regard, Digikala, the largest online retailer in Iran, has been no exception. Therefore, the use of gamification has great importance in branding and improving customer experiences.Literature ReviewGamification is an innovative concept that has not only impacted the gaming industry but has also opened avenues in management sciences to provide maximum effectiveness for organizations in competitive conditions. Initial studies on gamification were conducted in 2008 by Brett Terrill. However, its scientific popularity and extensive research began around 2010 (Alhamed & Morano, 2018).In terms of the effectiveness and the impact of gamification on marketing concepts, particularly in customer engagement, extensive research has not been conducted. However, most studies indicate a positive impact of gamification on customer engagement. In this regard, we will review some important research studies.In a study that examined the effects of gamification aspects on customer engagement dimensions and brand value among customers of Huawei and Xiaomi in social networks, it was found that gamification aspects have a significant impact on customer engagement dimensions and brand value (Xi & Hamari, 2019). In another study that investigated the impact of gamification on customer engagement and online sales, it was revealed that gamification aspects such as social interactions, goal orientation, and rewards lead to increased customer engagement and online sales (Eisingerich et al., 2019). In a study that focused on the impact of gamification on participation in online programs, the results indicated that gamification significantly affects participation (Looyestyn et al., 2017).MethodologyThis study is descriptive & applied in nature and employs a quantitative approach. Data collection was done through questionnaire. In this study, the statistical population consists of customers of the Digikala website who have made at least one purchase from this site. Since this website is the most well-known online shopping site in Iran, a structured questionnaire was distributed to 300 Digikala users using convenience sampling method. After filtering out incomplete and problematic questionnaires, a total of 222 questionnaires were gathered. Data analysis was conducted using Structural Equation Modeling (SEM) through the Lisrel Software.ResultsBased on the results obtained from the hypothetical model, we conclude that:The influence of immersion aspects of gamification on the emotional dimension of customer engagement was confirmed (Hypothesis 1).The influence of immersion aspects of gamification on the social and cognitive dimensions of customer engagement was not confirmed (Hypotheses 2 and 3).The influence of achievement aspects of gamification on the emotional and cognitive dimensions of customer engagement was confirmed (Hypotheses 4 and 5).The influence of achievement aspects of gamification on the social dimension of customer engagement was not confirmed (Hypothesis 6).The influence of achievement aspects of gamification on the emotional, cognitive, and social dimensions of customer engagement was confirmed (Hypotheses 7, 8, and 9).The immersion aspects of gamification have a stronger and more significant impact on the emotional dimension of customer engagement compared to other dimensions (Hypothesis 10).The achievement aspects of gamification have a stronger and more significant impact on the cognitive dimension of customer engagement compared to other dimensions (Hypothesis 11).The social aspects of gamification have a stronger and more significant impact on the social dimension of customer engagement compared to other dimensions (Hypothesis 12).Discussion & ConclusionIn general, the findings of the present research indicate that immersion aspects of gamification (such as creating avatars, customizing applications and web pages, storytelling, and narrative) have a greater impact on the emotional dimensions of customer engagement.When compared to immersion aspects, achievement aspects of gamification, such as giving prizes, medals, digital currency, coins, points, and gift cards, have a greater influence on the cognitive dimensions of customer engagement. They also affect the emotional aspect. Providing rewards and medals leads to customers forming a better rational and cognitive perception of our brand.Moreover, social aspects of gamification, like organizing competitions and teamwork activities and using social networks, have a more significant impact on the social dimension of customer engagement. However, they also have an effect on the emotional and cognitive dimensions.The findings of this research are consistent with the results of previous studies, including Madura (2015), Zhi and Hamari (2019), Harwood and Garry (2015), Yin et al. (2017), and Eisingerich et al. (2019).Based on the results obtained, it is recommended that online stores and smart businesses employ various gamification elements to increase customer engagement
Data science, intelligence and future analysis
Yaqub Ahmadlou; Alireza pourebrahimi; jafar tanha; Ali Rajabzadeh Ghatari
Abstract
Fraud cases have increased in recent years, especially in important and sensitive financial and insurance fields. Therefore, to deal with such frauds, there is a need for different measures than traditional inspection methods. Agricultural insurance is also not exempted from this threat due to its nature ...
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Fraud cases have increased in recent years, especially in important and sensitive financial and insurance fields. Therefore, to deal with such frauds, there is a need for different measures than traditional inspection methods. Agricultural insurance is also not exempted from this threat due to its nature and wide extent and every year a lot of money is spent on paying fake damages. This research was presented with the aim of providing a model to discover unrealistic damage claims in agricultural insurance by using data mining and machine learning techniques. It was used to build a deep learning model. The data used was obtained from the Agricultural Insurance Fund and related to wet and rainfed wheat insurance policies of Khuzestan province, for which compensation was paid in the 2018-2019 crop year. After preparing and preprocessing the data, using deep learning to discover unusual cases, the action and results were evaluated by the experts of the Agricultural Insurance Fund. After analyzing the results, it was found that 1% of the damages paid were related to unrealistic requests and more care should be taken in paying the damages. The accuracy of the model in detecting unusual cases for wet and dry wheat was 53.53 and 63.37 percent, respectively. In the review of the results, it was found that 5 categories of unusual behavior have led to the payment of unrealistic damages, and the behavior of not providing damage documentation was more frequent than the others.IntroductionInsurance fraud refers to the immoral act of committing a crime with the intention of abusing an insurance policy to obtain illegal profit from an insurance company; In general, insurance is made to protect the assets and business of individuals or organizations against financial loss and may occur at any stage of the insurance process by anyone such as customers or fraudulent agents (Al -Hashedi & Magalingam, 2021). Insurance fraud not only reduces the profit of the insurance company and leads to major losses, but also affects the pricing strategy of the insurance company and its socio-economic benefits in the long term (Yaram, 2016). Every year, significant sums of money are defrauded from the insurance industry, but not all of them are discovered. According to the statistics published by the Insurance Anti-Fraud Coalition, an amount of about eighty billion dollars is added to customers' expenses in the United States through fraud, and they must compensate for the amount of fraud by paying higher insurance premiums in the following year (Fraud statistics, 2020). In Iran, there is no accurate estimate of the amount of compensations paid to unreal damage claims or any other fraud, and one of the goals of this research is to estimate the amount of fraud in wheat crop insurance using deep learning. Research Question(s)This research seeks to find answers to these questions: In rainfed and irrigated wheat crop insurance, what percentage of the paid compensations are related to unrealistic and fictitious damage claims, and what is the accuracy of deep learning detection for this purpose?Literature ReviewGhahari et al. (2019) in their study investigated the use of deep learning in predicting agricultural performance in time and space with unstable weather conditions. They compared the performance of machine learning next to weather stations with conventional methods. Their findings showed that deep learning provides the highest prediction accuracy compared to other approaches. It can also be inferred from this result that the use of deep learning can play a role in reducing agricultural insurance costs by knowing the exact measures of crop yield (Newlands et al., 2019). Gomez et al. (2021) presented a new deep learning method to gain pragmatic insight into the behavior of an insured individual using the unsupervised effective variable. Their proposed method can be used in the fields of pension insurance, investment and other broader areas of the insurance industry. Their proposed method enables auto encoder and variable auto encoder to be used in semi-supervised/unsupervised effective variable analysis to identify cheating agents (Gomes et al., 2021). Xia et al. (2022) in their study proposed a deep learning model to detect car insurance fraud by combining convolutional neural network, long-term and short-term memory, and deep neural network. In their proposed method, more abstract features were extracted and helped the experts in the complex process of feature extraction which is very critical in traditional machine learning algorithms. The results of the experiments showed that their method can effectively improve the accuracy of car insurance fraud detection.MethodologyThe current research method is practical from the point of view of the objective and is data-oriented from the point of view of its nature. For machine learning modeling, the standard CRISP process has been used, which includes the stages of data collection, data preparation and preprocessing, modeling and model evaluation, and obtaining results. Figure 1 shows the general process of anomaly detection and analysis.Figure 1. Anomaly detection process framework In this research, the data related to one agricultural year of wet and dry wheat crop were obtained from the Agricultural Insurance Fund. The national code of the insurers has been removed from the data set to maintain confidentiality. The extracted data is related to the crop insurance policies of wet and rainfed wheat for the crop year 2018-2019 of Khuzestan province. In this crop year, compensation has been paid for these insurance policies according to the claim of the damage they had, in other words, the data set includes those insurance policies of wet and dry wheat whose product is damage Seen and compensated for them. The data were obtained from the comprehensive system of the insurance fund in the form of a csv report. The obtained data set had 23 features.ConclusionThe results of the research show that in wheat insurance, about 1% of the compensations paid are allocated to unrealistic claims, so they need to be further investigated by experts before payment. This amount of compensations paid to unrealistic claims was close to the prediction of insurance fund inspection experts who stated that about 1.5% of claims are unrealistic. Also, according to the results, 5 categories of behavior or methods were identified in the beneficiaries to receive compensation for unrealistic claims, which are mentioned below:Lack of sufficient documentation to prove the damage: This means that the necessary documents that should be uploaded in the system according to the implementation methods are not available or some of them have not been uploaded. Payment of compensation without the existence of documents indicating the occurrence of damage can be caused by the negligence or collusion of the appraiser or broker with the insured.The documents are not in accordance with the declared damage: the documents uploaded in the system according to the relevant instructions do not show the occurrence of the type of registered damage. For example, the speed of storm damage is mentioned as 50 km/h, but in meteorological documents it is 15 km/h.The damage documentation is not true: for example, in some documents, the risk factor is mentioned in the expert form of drought, but the picture sent shows flood damage. In this case, it is probably due to negligence. In another possibility, it is also possible to send the image of damaged agricultural land instead of healthy agricultural land. Non-observance of the damage notification period: According to the executive instructions of the insurance fund, the time limit for the declaration of damage until the time of payment of compensation is one month. Outside of that, it is against the instructions. Sometimes it was observed that the damage had been declared before the accident. The date of damage does not match with the time of its announcement: according to the executive instructions of the insurance fund, in the case of damage to agriculture, the visit must be done one week after the occurrence of the damage; before removing the damage, the type and amount of the damage should be carefully checked. In some cases, it was observed that the announcement date was recorded one month after the damage occurred. It is clear that after removing the effects of damage, the payment of compensation can seem suspicious because there may not have been any damage in the past.Keywords: Anomaly Detection, Crop Insurance, Deep Learning, Auto Encoder.
Data science, intelligence and future analysis
Mozhdeh Salari; Reza Radfar; Mahdi Faghihi
Abstract
AbstractThe purpose of this research is to investigate the effective factors in predicting the academic performance of undergraduate students in the classification of four classes. To achieve this goal, the study follows the CRISP data mining method. The data set was extracted from the NAD educational ...
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AbstractThe purpose of this research is to investigate the effective factors in predicting the academic performance of undergraduate students in the classification of four classes. To achieve this goal, the study follows the CRISP data mining method. The data set was extracted from the NAD educational system for the bachelor's degree in Shahed University for the entry of the years 2011 to 2021. 1468 records were used in data mining. First, the effective features on students' academic performance were extracted. Modeling was done using Rapidminer9.9 tool. To improve classification performance and satisfactory prediction accuracy, we use a combination of principal component analysis combined with machine learning algorithms and feature selection techniques and optimization algorithms. The performance of the prediction models is verified using 10-fold cross-validation. The results showed that the decision tree algorithm is the best algorithm in predicting students' performance with an accuracy of 84.71%. This algorithm correctly predicted the graduation of 77.88% of excellent students, 85.26% of good students, 84.69% of medium students, and 85.96% of weak students based on the final GPA. IntroductionThe main problem in this research is to identify the factors that are effective in predicting the academic performance of undergraduate students in Shahed University. Choosing the best machine learning algorithm in predicting academic performance among different modeling methods based on validation and evaluation of models is another issue in the present research. The purpose of this research is to investigate the effective factors in predicting the academic performance of undergraduate students in Shahed University using educational data mining based on classification models.Research questionsThe main question in this research is what factors affect the prediction of undergraduate students' performance and improving their performance?Sub questions1- Which modeling algorithms have better results in predicting student performance?2- What methods have been used to predict students' performance?3- What is the validity of the developed model for Shahed University students? 2- Research background1-2- Theoretical foundationsEducational data miningThe processing of educational data improves the prediction of student behavior and new approaches to educational policies (Capuano & Toti, 2019) (Viberg et al., 2018)Academic performanceAcademic performance of students means the extent to which they achieve educational goals (Banik & Kumar, 2019).2-2- review of past studiesThe highlighted cells in Table 1, based on past research, show the classification algorithms that have the most accuracy and effectiveness in predicting students' performance in the relevant research. The decision tree algorithm has been used the most in previous researches. The NB algorithm has been the most used in research after the decision tree. RF and ANN algorithms are next in use. After that, SVM and KNN algorithms have been used in researchTable 1. The results of research literature based on the use of classification algorithmsData mining algorithmDTRFNBKNNSVMANNLine RLLRAccuracy(Batool et al., 2023) * * (Marjan et al., 2023)****** (Abdelmagid & Qahmash, 2023) * ** * (Manoharan et al., 2023)** * * * (Alghamdi & Rahman, 2023)*** 99.34%(Alboaneen et al., 2022) * **** (Yağcı, 2022)* *** *70-75%(Dabhade et al., 2021)* * * 83.44%(Najafi & etal,2021)* 95%(Soltani & etal,2021)* ** (Cruz-Jesus et al., 2020) * ** *50-81%(Sokkhey & Okazaki, 2020)*** * (Rebai et al., 2020)** (Jayaprakash et al., 2020)*** (Zulfiker et al., 2020)** * (Musso et al., 2020) * (Waheed et al., 2020) * 85%(Salal & Abdullaev, 2019)* **** (Turabieh, 2019)* ** * (Xu et al., 2019)* ** (ghodoosi & etal,2019)* * (fadavi & etal,2019) * 95.84%(Ajibade et al., 2019)* *** 91.5%(Ahmad & Shahzadi, 2018) * 85%(Hasani & Bazrafshan, 2018)* * (Hussain et al., 2018)*** * (Umer et al., 2017)**** * (Khasanah, 2017)* * (Asif et al., 2017)* (Hoffait & Schyns, 2017) * * *92.34%(khosravi &etal,2017)* * (Mueen et al., 2016)* * * 86%(Amrieh et al., 2015)* ** (Yehuala, 2015)* * 92.34%(zahedi & etal,2015)* * * (Punlumjeak & Rachburee, 2015)* (Osmanbegović et al., 2014)** 71%(Shamloo & et al.,2014)* (Asadi & et al.,2013)* (Kabakchieva, 2013)* ** 60-75%(Oskouei & Askari, 2014)*** * 96%(Nghe et al., 2007)* * present research****** 94.17%3- MethodThis study follows the popular training data mining method CRISP. The data collection of Nad educational system for bachelor's degree in non-medical fields of Shahed University has been extracted from 2011 to 2021. We used the Label Encoder technique to encode the features. In this research, C4.5 and ID3 decision tree classification algorithms, random forest, Naïve Bayes, k-nearest neighbor and artificial neural network and gradient enhanced tree were used to analyze and classify students and predict the final GPA. Modeling was done using RapidMiner 9.9. To improve the classification performance and solve the misclassification problem, we use a combination of principal component analysis and feature selection techniques and optimization algorithms. In this research, prediction accuracy was evaluated using 10-fold cross-validation method for all algorithms. Also, different algorithms were compared using the analytical descriptive method and based on evaluation criteria, and the best prediction model was introduced in this research.4-Data analysis4-1 IntroductionThe best model is the model that has the best values for the selected performance measurement criteria(Lever et al., 2016). Figure 1 is a graph that compares the accuracy of the algorithms used in this research.Figure 1. Comparative chart of the accuracy of the algorithms According to Table 2, the DTC4.5 algorithm is able to predict the class of 1235 objects out of 1458, which gives it an accuracy value of 84.71%.Table 2. Confusion matrix of DT C4.5-GI&OSE research modelprecisionStudents with poor performanceStudents with average performanceStudents with good performanceStudents with excellent performance 78.64%002281Prediction 178.67%94929522Prediction 286.46%50498271Prediction 389.36%3614120Prediction 4 85.95%84.69%85.26%77.88%Recall4-2 important featuresThe prioritization of predictive variables based on their weight is as follows:Diploma GPA: 0.262Semester 1 GPA: 0.201Semester 2 GPA: 0.197Number of honors semesters: 0.122Conditional number: 0.114Year of entry: 0.1044-3 The results of the implementation of the student performance prediction modelThe results of the prediction model are shown in Table 3:Table 3. The results of the DT C4.5-GI&OSE model implementation 5- DiscussionIn the main method of research, namely DT C4.5-GI&OSE, in the classification mode of four classes, it is observed that the average of the diploma has the greatest effect on the process of predicting student performance. In response to the sub-question of a research, the best algorithm in the four-class mode is Decision Tree C4.5-GI&OSE with a prediction accuracy of 84.71. This model showed 84.17% accuracy, 83.42% sensitivity and 0.780 kappa. DT C4.5-GI&OSE technique correctly predicted the graduation of 77.88% of excellent students, 85.26% of good students, 84.69% of average students, and 85.96% of poor students.6-ConclusionThe obtained results show that there is a relationship between students' social and academic characteristics and their academic performance. DT C4.5-GI&OSE algorithm was the best algorithm for predicting the final GPA scores of students at the end of studies with a prediction accuracy of 84.71%. In this model, the average grade point average of the diploma has the greatest effect on the prediction process. Using machine learning models as a decision support tool improves the academic level of students and reduces the number of potential unsuccessful and dropout students. This study was carried out at the undergraduate level, which can be used in future research for the master's and doctoral level.Keywords: student performance prediction, data mining, machine learning, modeling, improving the quality of education
Mehregan Ghobakhloo; Ali Rajabzadeh Ghatari; Abbas Toloie Eshlaghy; Mahmood Alborzi
Abstract
Customer retention is an important issue for any organization, so finding a way to retain the customer is one of the critical needs of any organization. In this regard, the goal in the field of machine learning is focusing on the problem of accurate customer needs with a method based on extracting opinion ...
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Customer retention is an important issue for any organization, so finding a way to retain the customer is one of the critical needs of any organization. In this regard, the goal in the field of machine learning is focusing on the problem of accurate customer needs with a method based on extracting opinion and sentiment analysis and quantifying customers' emotional orientation.In the other words, the issue is designing a recommender system to provide appropriate services to customers, using their opinions and experiences. The proposed solution, by receiving and reviewing customers' opinions and experiences in the form of extracting variables such as user sentiment score for tweets, relation score, cosine similarity, and confidence factor, and considering groups of relevant features and registration ideas in the process of training and testing, the result is presented in the form of a banking service suitable offer. In order to provide a recommending solution, appropriate classification methods are used along with opinion mining methods and an appropriate validation approach, and the final designed system with a small error, in order to provide personalized services, will step in to help bank managers.Since currently there is no complete provision of banking services tailored to the situation of customers, so in this regard, this mentioned system will be very helpful.
Reyhaneh Forouzandeh Joonaghani; mirali Seyednaghavi; Vajhollah ghorbanizadeh; Mohammad Taghi Taghavifard
Abstract
In recent years, the application of artificial intelligence, especially machine learning, has grown significantly in the field of HRM, which is unknown to many managers and experts in the field of HR due to the newness of this field. A lot of data is being generated by users of organization in HRM domains ...
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In recent years, the application of artificial intelligence, especially machine learning, has grown significantly in the field of HRM, which is unknown to many managers and experts in the field of HR due to the newness of this field. A lot of data is being generated by users of organization in HRM domains and the related fields, which are difficult to analyze and use in HR activities. The capabilities of data science and machine learning have been able to make great contributions to the field of HRM and beyond to the management of the organization with descriptive, diagnostic, predictive and prescriptive reports and analyses. The purpose of the research is to examine the measures that have been taken so far in the field of HRM intelligence, and in this research, three main questions are answered. The first question is to identify HRM activities that can be made intelligent. In the second question, the application of various ML algorithms in HRMI has been identified. In the third question, based on the maturity levels of data analytics, the classification of "ML algorithms in intelligent HRM functions" has been made. In order to answer , a wide range of articles were extracted from reliable scientific databases and journals and analyzed based on a mixed method. In this method, qualitative and quantitative methods for data analysis were investigated at the same time. IN the quantitative part, text mining algorithms were used Python language, and in the qualitative part, thematic analysis was used MAXQDA2020 .
Mohammad Kazemi; Mohammad Ali Keramati; Mehrzad Minooie
Abstract
AbstractClustering 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 ...
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AbstractClustering 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.
Data, information and knowledge management in the field of smart business
Fatemeh Rezaimehr; Chitra Dadkhah
Abstract
AbstractRecently, the Internet has played a significant and substantial role in people's lives. However, the content available in the global web environment should align with users' daily needs, providing them with useful and up-to-date information tailored to their tastes. In this context, recommender ...
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AbstractRecently, the Internet has played a significant and substantial role in people's lives. However, the content available in the global web environment should align with users' daily needs, providing them with useful and up-to-date information tailored to their tastes. In this context, recommender systems assist users by suggesting items that closely match their preferences in less time. Today, with the exponential growth of data, the utilization of recommender systems has surged. Conversely, these systems encounter challenges such as evolving user preferences over time, cold start problem, sparsity within the user-item matrix, the infiltration of fake users in the systems, and their adverse impact on the recommendation lists. The objective of this paper is to propose a recommender system grounded in time and trust factors to enhance the efficiency and precision of system recommendations. Initially, the proposed system addresses the data sparsity dilemma by incorporating reliable implicit ratings into the user-item matrix. Subsequently, it constructs a weighted user-user network based on user rating timestamps and trust relationships among users, thereby mitigating the cold start problem and accounting for changing user preferences over time. The proposed recommender system employs a novel community detection algorithm introduced in this paper to identify the nearest neighbors of active users and recommends the top @k items based on the collaborative filtering approach. Evaluation results of the proposed system, tested on a film recommender system using the Epinions dataset, demonstrate its superior efficiency compared to basic systems.IntroductionToday, with the increasing tendency of users to use websites for obtaining information, online shopping, and using social networks for expressing personal opinions, the ways of obtaining information and establishing connections among users have undergone significant changes. Consequently, users are confronted with the big of data. Managing this data and selecting the appropriate options from this vast collection and presenting it to users is one of the main reasons for the development of information retrieval systems and search engines. In this regard, Recommendation Systems (RSs) help users choose the best options and recommend items that are closer to their preferences in the shortest possible time. Different models of RS such as collaborative filtering, content-based, knowledge-based, and newly developed context-aware RS, have been presented by researchers (Casillo et al., 2022). Each has its own advantages and disadvantages, which can be combined to create a hybrid RS. It should be noted that RS face challenges, including changes in user preferences over time, cold start for new users or items, sparsity of the user-item matrix, attack by fake users, and their negative impact on the recommendation list. In this paper, a time- and trust-based recommendation system is presented to enhance the performance and accuracy of recommendations. Our proposed system initially solves the data sparsity problem by adding reliable implicit ratings to the user-item rating matrix. It then generates a weighted user-user network based on the time of user feedback on items and trust relationships among users. This approach addresses the cold start problem and the change in user preferences over time. Our system is based on a novel community detection algorithm presented in this article, which identifies the nearest neighboring users with similar tastes to the active user and recommends the top-k items using the collaborative filtering method. The evaluation of the proposed system is performed on an Epinions dataset for a movie recommendation system. The evaluation uses metrics such as accuracy, recall, F1 score, mean absolute error, and root mean square error. The experimental results indicate the superior performance of the proposed system compared to similar systems.Literature ReviewIn the recent years, the researchers attempt to improve the accuracy of their recommendation for retaining the users and increasing the profit. Some of the papers has worked on optimizing the performance of their proposed RS using evolutionary algorithms (Tohidi & Dadkhah, 2020) and the others used the additional information such as time, location, etc. Trust-based RSs have been recently introduced to the community of computer science. Recent studies have shown that incorporating social factors or trust statements in RSs leads to the improvement of recommendation quality (P. Moradi & Ahmadian, 2015; S. Ahmadian, M. Meghdadi, & Afsharchi, 2018b). So far, several trust-based CF approaches have been proposed to overcome data sparsity and cold-start problems as well as to increase recommendable items (Ghavipour & Meybodi, 2016; Moradi, Ahmadian, & Akhlaghian, 2015; P. Massa & Avesani, 2007; Ranjbar Kermany & Alizadeh, 2017). Trust statements can be explicitly collected from users or can be implicitly inferred from users behaviors (S. Ahmadian, M. Meghdadi, & Afsharchi, 2018a; S. Ahmadian, P. Moradi, & Akhlaghian, 2014). Liu and Lee proposed a specific approach which does not directly use the trust information; instead they take into account the number of exchanged messages among the users of the system to construct the trust network (Liu & Lee, 2010). Alahmadi and Zeng presented a framework to apply short texts posted by users friends in microblogs as an additional data source to build the trust network (Alahmadi & Zeng, 2015). Since explicit trust statements are directly specified by the users, they are more accurate and reliable than implicit ones in determining social relationships among users (Cho, Kwon, & Park, 2009; Ingoo, Kyong, & Tae, 2003; Lathia, Hailes, & Capra, 2008; Manolopoulus, Nanopoulus, Papadopoulus, & Symeonidis, 2008).The research In (Abdul-Rahman & Hailes, 2000) has been shown that a user constructs his/her social connections with someone who has similar tastes. Massa and Avesani showed that adding social network data to traditional collaborative filtering improves the recommendation results (P. Massa & Avesani, 2007). Gharibshah and Jalili studied the relation between RSs and connectedness of users-items bipartite interaction network (Gharibshah & Jalili, 2014). Guo et al. proposed a method which merged the ratings of users trusted neighbors with the other information sources to identify their preferences (G. Guo, J. Zhang, & Thalmann, 2014). Yang et al. proposed a Bayesian inference based recommendation method for online social networks (X. Yang, Y. Guo, & Liu, 2013). In this method, the similarity value between each pair of users is measured using a set of conditional probabilities derived from their mutual ratings. Jiang et al. introduced a framework to incorporate interpersonal influences of users in social network with their individual preferences to improve the accuracy of social recommendation (Jiang, Cui, Wang, Zhu, & Yang, 2014).Purchase/rating time is one of the most important contextual information that can be used to design RSs with high precision (Xiong, Chen, Huang, Schneider, & Carbonell, 2010). The main motivation for time-aware RS is that in realistic scenarios users tastes might change over time.MethodologyWe propose a time and trust-aware RS using a graph-based community detection method consists of four steps: 1: developing a user-item rating matrix, 2: constructing a time weighted user-user network, 3: performing graph- based community detection, 4: recommending Top-N items. In the first step, the user-item rating matrix is developed by adding some implicit ratings and the quality of the implicit ratings is evaluated using a reliability measurement. In the second step, a time-weighted user-user network is constructed based on the combination of trust relationships and similarity between users. Moreover, the timestamps of user-item ratings are considered to calculate the similarity between users. In the third step, a graph-based community detection method classifies similar users into appropriate communities. Finally, in the fourth step, it predicts the rating for each unobserved item and top-N recommendations is generated for the target user.We proposed a new community detection method that consists of three phases. First, the initial centers of communities are obtained using a sparsest subgraph of weighted user-user network. It should be noted that the initial centers must have the maximum dissimilarities with each other based on the general concept of clustering and community detection algorithms. Then users can be assigned to their nearest communities. For each user proposed system calculated the fitness function. User has associated to community which has high value of fitness function. Then the centers of communities were updated in order to maximize a fitness function. This process is iteratively repeated until members of communities do not change and steady state is achieved. A set of communities are identified where the users are assigned to their corresponding communities. Some of the communities may have overlap and they can be merged. The final communities were used as the nearest neighbors set of the active user in the same community for the recommendation.ConclusionOur proposed algorithm solves the sparsity of rating matrix by adding the implicit rating and solved cold-start problem for new users by considering the trust between the users. We applied the proposed algorithm on extended Epinions dataset and compared its performance with similar algorithms. The experimental results showed that our proposed algorithm outperforms the other algorithms according to the accuracy and recommends the top@N items with high precision.
Management approaches in the field of smart
Javad Keshvari Kamran; Mohammad ali Keramati; Abbas Toloie Eshlaghy; Seyed Abdollah Amin Mousavi
Abstract
The aims of this study is to provide a conceptual model of hospital accreditation in Iran through qualitative research. The grounded theory model was compiled using the results of the analysis of the interviews. Then, with the help of the grounded theory model and the results of qualitative analysis, ...
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The aims of this study is to provide a conceptual model of hospital accreditation in Iran through qualitative research. The grounded theory model was compiled using the results of the analysis of the interviews. Then, with the help of the grounded theory model and the results of qualitative analysis, a state diagram was obtained. Using the state diagram, initial sampling, systematic review of sources and results of interviews, 9 conceptual agents "governance organizations, management and leadership, clinical personnel, support personnel, hospital infrastructure, assessor, standards, assessment method and service recipient" were identified. Finally, the conceptual model of agent-based, environment, behavioral rules of agents and their input and output interactions was presented. In future researches, reinforcement learning models can be designed according to the conceptual model of this study, so that by using it, software developers can develop a suitable framework for solving complex problems in the field of hospital accreditation. Because the field of hospital management systems is one of the desirable types of socio-technical systems that have high capacities.IntroductionThe ecosystem of hospital accreditation is a triangle with “standard, accreditation method, and accreditation assessors” sides (Mosadeghrad et al.,2017). Hospital accreditation in Iran has faced challenges, the most important of which are: “a large number of standards and measures, lack of transparency and ambiguity in the measures, incompleteness and defects in the standards and high emphasis on structure and documentation, lack of systemic thinking and following that, a lot of focus on the sectoral approach” (Mosadeghrad & Ghazanfari, 2020). The results of a systematic review of sources and documents indicate that as a result of the lack of new approaches to solving “social-technical” problems such as “use of agent-based systems”, the above-mentioned challenges have become more prominent and ultimately cause the credibility and ranking of hospitals to become unrealistic (Ghazanfari et al., 2021). This study aims to present new models such as the agent-based conceptual model in Iran's hospital accreditation system. This model will create a study foundation for the environmental simulation process and the creation of a multi-agent hospital accreditation system to provide useful guidelines to the relevant policymakers.Therefore, it seems that the result of the current research covers the research gap in this field to some extent. Also, this study aims to answer the main research question; “What are the rules, position, behavior, and relationships of each of the agents in the multi-agent hospital accreditation system and how are they formulated?” It has started working.Literature ReviewHospital accreditationHospital accreditation is the process of systematic evaluation and determination of hospital credit by an external organization using the desired structural, process, and outcome standards (Chehrzad et al., 2019).Figure 1. The main elements of the hospital accreditation system, Source: (Mosadeghrad & Ghazanfari, 2021) Figure 1 shows the main elements of the hospital accreditation system. The hospital accreditation system is a triangle that includes the sides of “standard, accreditation method, and accreditation assessors”. The governance element is the regulator and controller of the sides of this triangle.Agent-based systemsThe agent-based system can be used to solve problems that are difficult or impossible to solve for a “single agent” or an integrated system. Agent-based systems provide new methods for solving complex computing problems and implementing social-technical software projects (Dorri et al.., 2018). The elements of agent-based systems are: “environment, objects, a set of agents, a set of relationships, and a set of agent behaviors” (Bonabeau, 2002).Research backgroundTable 1 shows the summary report of the background of the most important research conducted in the fields of hospital accreditation and agent-based models.Table 1. Summary report of the background of the researchSummary of study resultsResearcherA comprehensive hospital accreditation model was developed and validated. Paying attention to structures, processes, outcomes, and systemic thinking during model development is one of the advantages of this study.(Mosadeghrad & Ghazanfari, 2021)The challenges of hospital accreditation standards were categorized into two groups: standards development process and standards content.(Ghazanfari et al., 2021)The identified agents describe the consumer's impulse buying behavior as an economic analysis based on the relationship between the customer and the product.(Abbasi Siar et al., 2022)The multi-agent model and process simulations provide useful information for generating strategies to reduce the risks of COVID-19 transmission inside the facility.(Cuevas, 2020)The results of the agent-based simulation show the advantages of the proposed model for reducing the response time to requests compared to the current maintenance system.(Yousefli et al., 2020)The proposed model of pre-hospital management operation was presented. The identified agents are: “Management Center, Ambulance, Traffic Station, Medical Service Provider, Patient, Counseling Center, National Medical Record System, and Service Quality Monitoring”.(Safdari et al., 2017)MethodologyTo collect data, library and field methods have been used. Using qualitative analysis and obtained results, conceptual models were created. Therefore, the approach of this research is of a hybrid type. Also, the snowball sampling method was used to collect the required information. By using primary sampling, agents, the environment, and their relationships were extracted. By conducting six interviews, theoretical saturation was achieved regarding the conceptual model. To collect the information needed to know the elements and processes, a systematic review of sources and semi-structured interviews were used. The interviewees were selected from among the professors, managers, and employees of the hospitals. Finally, the interviews were summarized using grounded-theory-based methods, approaches, and systematic approaches. To calculate the reliability of the interviews, the method of two inter-coder agreements was used. Finally, the fuzzy Delphi method with triangular fuzzy numbers was used to validate the extracted conceptual model. ResultsConceptual model of the agent-basedUsing the results obtained from qualitative data analysis and the grounded theory model, examples and independent agents of each agent group were identified. All the interactions of the agents are included in the final model in the form of input and output. Figure 2 shows the agent-based conceptual model of the hospital accreditation system.Figure 2. Conceptual model of the agent-based hospital accreditation system (source: findings of the present research) DiscussionThis study aimed to provide a conceptual model of the agent-based system in Iran's hospital accreditation system. Also, agents, the environment, general behavioral rules, and their interactions with the environment were obtained. Because, so far, a lot of research has been conducted to provide an optimal model in the hospital accreditation ecosystem, there have been no studies that have new methods such as agent-based design. Therefore, it seems that the findings of the current research have covered some research gaps in this field because agent-based design is one of the newest and most efficient solutions available for solving distributed problems and complex human processes and environments. The agent-based conceptual model of the current research can create a suitable study base for the environmental simulation process and the creation of a multi-agent hospital accreditation system. Also, future researchers are suggested to carry out relevant research in this field, considering the wide application of agent-based modeling in the field of social-technical hospital systems and the importance of using reinforcement learning algorithms in them.ConclusionThe background analysis of the research was done with the method of systematic review of sources. Using experts' opinions, broad and general questions were asked about the results of the research, and then their description and analysis were addressed through grounded theory-based tools (MAXQDA), and a conceptual model of the grounded theory was obtained. Then, to the main research question; “What are the rules, position, behavior, and relationships of each of the agents in the multi-agent hospital accreditation system and how are they formulated?” The appropriate answer was given so that by using qualitative analysis, the dimensions of the problem were fully understood and the obtained results were converted into the final conceptual model. Also, agents, the environment, and their relationships were obtained. Then their general rules of conduct were compiled. All interactions of the agents with the environment were included in the model as input and output.Keywords: Agent-Based Conceptual Model, Hospital Accreditation, Multi-Agent System, Simulation.The aims of this study is to provide a conceptual model of hospital accreditation in Iran through qualitative research. The grounded theory model was compiled using the results of the analysis of the interviews. Then, with the help of the grounded theory model and the results of qualitative analysis, a state diagram was obtained. Using the state diagram, initial sampling, systematic review of sources and results of interviews, 9 conceptual agents "governance organizations, management and leadership, clinical personnel, support personnel, hospital infrastructure, assessor, standards, assessment method and service recipient" were identified. Finally, the conceptual model of agent-based, environment, behavioral rules of agents and their input and output interactions was presented. In future researches, reinforcement learning models can be designed according to the conceptual model of this study, so that by using it, software developers can develop a suitable framework for solving complex problems in the field of hospital accreditation. Because the field of hospital management systems is one of the desirable types of socio-technical systems that have high capacities.IntroductionThe ecosystem of hospital accreditation is a triangle with “standard, accreditation method, and accreditation assessors” sides (Mosadeghrad et al.,2017). Hospital accreditation in Iran has faced challenges, the most important of which are: “a large number of standards and measures, lack of transparency and ambiguity in the measures, incompleteness and defects in the standards and high emphasis on structure and documentation, lack of systemic thinking and following that, a lot of focus on the sectoral approach” (Mosadeghrad & Ghazanfari, 2020). The results of a systematic review of sources and documents indicate that as a result of the lack of new approaches to solving “social-technical” problems such as “use of agent-based systems”, the above-mentioned challenges have become more prominent and ultimately cause the credibility and ranking of hospitals to become unrealistic (Ghazanfari et al., 2021). This study aims to present new models such as the agent-based conceptual model in Iran's hospital accreditation system. This model will create a study foundation for the environmental simulation process and the creation of a multi-agent hospital accreditation system to provide useful guidelines to the relevant policymakers.Therefore, it seems that the result of the current research covers the research gap in this field to some extent. Also, this study aims to answer the main research question; “What are the rules, position, behavior, and relationships of each of the agents in the multi-agent hospital accreditation system and how are they formulated?” It has started working.Literature ReviewHospital accreditationHospital accreditation is the process of systematic evaluation and determination of hospital credit by an external organization using the desired structural, process, and outcome standards (Chehrzad et al., 2019).Figure 1. The main elements of the hospital accreditation system, Source: (Mosadeghrad & Ghazanfari, 2021) Figure 1 shows the main elements of the hospital accreditation system. The hospital accreditation system is a triangle that includes the sides of “standard, accreditation method, and accreditation assessors”. The governance element is the regulator and controller of the sides of this triangle.Agent-based systemsThe agent-based system can be used to solve problems that are difficult or impossible to solve for a “single agent” or an integrated system. Agent-based systems provide new methods for solving complex computing problems and implementing social-technical software projects (Dorri et al.., 2018). The elements of agent-based systems are: “environment, objects, a set of agents, a set of relationships, and a set of agent behaviors” (Bonabeau, 2002).Research backgroundTable 1 shows the summary report of the background of the most important research conducted in the fields of hospital accreditation and agent-based models.Table 1. Summary report of the background of the researchSummary of study resultsResearcherA comprehensive hospital accreditation model was developed and validated. Paying attention to structures, processes, outcomes, and systemic thinking during model development is one of the advantages of this study.(Mosadeghrad & Ghazanfari, 2021)The challenges of hospital accreditation standards were categorized into two groups: standards development process and standards content.(Ghazanfari et al., 2021)The identified agents describe the consumer's impulse buying behavior as an economic analysis based on the relationship between the customer and the product.(Abbasi Siar et al., 2022)The multi-agent model and process simulations provide useful information for generating strategies to reduce the risks of COVID-19 transmission inside the facility.(Cuevas, 2020)The results of the agent-based simulation show the advantages of the proposed model for reducing the response time to requests compared to the current maintenance system.(Yousefli et al., 2020)The proposed model of pre-hospital management operation was presented. The identified agents are: “Management Center, Ambulance, Traffic Station, Medical Service Provider, Patient, Counseling Center, National Medical Record System, and Service Quality Monitoring”.(Safdari et al., 2017)MethodologyTo collect data, library and field methods have been used. Using qualitative analysis and obtained results, conceptual models were created. Therefore, the approach of this research is of a hybrid type. Also, the snowball sampling method was used to collect the required information. By using primary sampling, agents, the environment, and their relationships were extracted. By conducting six interviews, theoretical saturation was achieved regarding the conceptual model. To collect the information needed to know the elements and processes, a systematic review of sources and semi-structured interviews were used. The interviewees were selected from among the professors, managers, and employees of the hospitals. Finally, the interviews were summarized using grounded-theory-based methods, approaches, and systematic approaches. To calculate the reliability of the interviews, the method of two inter-coder agreements was used. Finally, the fuzzy Delphi method with triangular fuzzy numbers was used to validate the extracted conceptual model. ResultsConceptual model of the agent-basedUsing the results obtained from qualitative data analysis and the grounded theory model, examples and independent agents of each agent group were identified. All the interactions of the agents are included in the final model in the form of input and output. Figure 2 shows the agent-based conceptual model of the hospital accreditation system.Figure 2. Conceptual model of the agent-based hospital accreditation system (source: findings of the present research) DiscussionThis study aimed to provide a conceptual model of the agent-based system in Iran's hospital accreditation system. Also, agents, the environment, general behavioral rules, and their interactions with the environment were obtained. Because, so far, a lot of research has been conducted to provide an optimal model in the hospital accreditation ecosystem, there have been no studies that have new methods such as agent-based design. Therefore, it seems that the findings of the current research have covered some research gaps in this field because agent-based design is one of the newest and most efficient solutions available for solving distributed problems and complex human processes and environments. The agent-based conceptual model of the current research can create a suitable study base for the environmental simulation process and the creation of a multi-agent hospital accreditation system. Also, future researchers are suggested to carry out relevant research in this field, considering the wide application of agent-based modeling in the field of social-technical hospital systems and the importance of using reinforcement learning algorithms in them.ConclusionThe background analysis of the research was done with the method of systematic review of sources. Using experts' opinions, broad and general questions were asked about the results of the research, and then their description and analysis were addressed through grounded theory-based tools (MAXQDA), and a conceptual model of the grounded theory was obtained. Then, to the main research question; “What are the rules, position, behavior, and relationships of each of the agents in the multi-agent hospital accreditation system and how are they formulated?” The appropriate answer was given so that by using qualitative analysis, the dimensions of the problem were fully understood and the obtained results were converted into the final conceptual model. Also, agents, the environment, and their relationships were obtained. Then their general rules of conduct were compiled. All interactions of the agents with the environment were included in the model as input and output.Keywords: Agent-Based Conceptual Model, Hospital Accreditation, Multi-Agent System, Simulation.vv
Management approaches in the field of smart
Atieh Moghaddam Monfared; Abbas Toloie Eshlaghy; Reza Ehtesham Rasi
Abstract
AbstractConsidering that the users are the main focus of immersive journalism, any study in this field without understanding and recognizing them is incomplete. The quality of the VR news experience depends on many parameters, the most important of which are related to the cognitive and behavioral science ...
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AbstractConsidering that the users are the main focus of immersive journalism, any study in this field without understanding and recognizing them is incomplete. The quality of the VR news experience depends on many parameters, the most important of which are related to the cognitive and behavioral science of the users, apart from the technological factors that are prerequisites for making VR. In this regard, through interviews with experts in journalism and cognitive sciences, this research identified the categories that influence the depth of user’s immersion based on the Grounded Theory methodology and finally presented a conceptual model. The phenomenon of the model is “user involvement”. This category is affected by contextual factors such as "user’s demographic characteristics" and "type of news", as well as the intervening factors of "trauma" and "preventing factors of using virtual reality". In addition, the three categories of "cognition", "narrative" and "crafting pieces" provided the causal conditions that are the basis for the immersion in the news narrative. Finally, "focusing on user’s cognitive factors" in creating VR pieces is the interaction strategy that brought two consequences of "increasing immersion" and "changing norms and behaviors". IntroductionIn an era characterized by rapid technological advancement and digital transformation, journalism stands at the precipice of a profound evolution. The fusion of virtual reality (VR) with journalism has emerged as a pioneering innovation, propelling the field into a new dimension – the metaverse. This dynamic convergence is reshaping how news is both reported and consumed, presenting a paradigm shift that warrants a closer examination. Traditional journalism has long been the cornerstone of information dissemination, serving as society’s watchdog and providing a lens through which we view the world. However, with the advent of VR and its integration into news reporting, we find ourselves on the cusp of a revolution that promises to redefine the very essence of journalism. The immersive nature of VR enables audiences to step inside the stories they consume, transcending the limitations of two-dimensional screens and forging a connection that goes beyond words and images. At the heart of this transformation is the metaverse –a digital universe where virtual and real-world experiences coalesce seamlessly. Within this expansive virtual realm, the potential for immersive, interactive journalism knows no bounds (Uskali & Sirkkunen, 2020, P. 6).In an ever-evolving landscape of journalism, Virtual Reality (VR) journalism stands as a transformative force, not merely conveying information to audiences, but immersing them in the stories with a dynamic and active role. One of the intriguing aspects of this evolution is the dynamic role played by the audience, who, in the realm of Virtual Reality and the metaverse, are no longer passive news consumers but active participants in the storytelling process. Traditionally, audiences in journalism assumed the role of static observers and receivers of news (Shin, 2018, P. 65). However, with the emergence of Virtual Reality and its integration with the metaverse, audiences are no longer mere spectators; they become active participants deeply embedded in situations and places beyond their physical reality. This transcends the conventional viewing of news reports and empowers audiences to actively contribute to news production (McMahan, 2016, P. 68).Secondly, within the metaverse, audiences interact with characters and other audience members, express their opinions, and directly engage in news creation. These active interactions provide a powerful tool for fostering increased engagement and a deeper understanding of news topics (Shin, 2016, P. 141). In this article, we delve into the exploration of the dynamic role of audiences in Virtual Reality journalism and examine the impacts of this role on the reporting process and media communications. From shifting public opinions to experiencing active audience engagement in the metaverse, we delve deep into these transformations, highlighting the formation of a two-way and dynamic relationship between media outlets and their audiences.Research QuestionHow can we enhance audience immersion in virtual reality news content by strategically addressing their perceptual systems and cognitive factors? Literature ReviewVirtual reality (VR) in storytelling, exemplified by De la Peña et al.'s (2010) "Immersive Journalism," demonstrates its popularity. The study explores user participation in simulated news events, highlighting heightened presence through avatars and virtual scenario reconstruction. It advocates for a fundamental shift in journalism perspectives, aligning with embodied cognition theory. Immersive journalism aims to provide empathetic, simulated experiences, potentially influencing real-world actions. VR's impact on perceptual experiences is acknowledged, with powerful illusions forming the foundation of these experiences.It discusses the unique potential of virtual reality (VR) in journalism, emphasizing its ability for deep behavioral influence. Research, like that of Yee & Bailenson (2007), indicates that avatars in VR can alter user behavior. Recent studies focus on VR’s positive role in creating empathy. For example, Ma (2020) suggests immersive storytelling enhances social engagement. Breves (2021) explores how spatial presence in VR persuasively impacts cognitive processes. The text touches on the emergence of the metaverse and highlights the need for further research in the evolving field of VR journalism. MethodologyIn this article, the research process follows an inductive approach due to the absence of specific laws for identifying cognitive factors influencing the quality of user immersion in virtual reality (VR) experiences. The study aims to explore these cognitive factors affecting immersion by engaging targeted experts in journalism, VR, cognitive sciences, and VR content creators. Data collection involves document analysis and in-depth interviews using Skype. The data is analyzed using the Strauss and Corbin method with a focus on cognitive factors impacting user immersion in VR storytelling.The research participants were selected purposefully, and key themes in the interviews include defining cognition, main stimuli for cognitive factors, factors inducing immersion, cognitive factors affecting user engagement, and interaction with simulated environments. The research process spans over four years, and to enhance credibility, the researcher consulted participants and another expert coded four interviews for inter-coder reliability, yielding a reliability coefficient of 73.0%. The study’s reliability is confirmed as the coefficient is above 70%. ResultsIn the Grounded theory approach, interview texts underwent open coding, extracting initial codes that were then compared to identify related phenomena. Concepts like “attention” emerged, involving cognitive focus, intentional neglect of irrelevant details, and concentrating energy on essential information to avoid distractions and complete specific tasks.All concepts were extracted through this process. The identification of concepts and categories continued until the researcher did not discover any new concepts, essentially reaching saturation. In total, 100 codes, 29 concepts, and 14 categories were identified. Figure 1. Conceptual Model of cognitive factors affecting audience immersionCasual Conditions CognitionNarrativeCrafting the pieceCentral Phenomenon User Engagement and Immersive PerceptionStrategies Focusing on the user's cognitive factors in creating virtual reality news piecesOutcomes Increasing perceived immersionChanging norms and beliefs Intervening Conditions Demographic User FeaturesNature of News Contextual Conditions TraumaInhibiting Factors of Virtual Reality Usage Discussion5.1. Central phenomenonThis article focuses on “User Engagement and Immersive Perception,” highlighting the significance of “Interaction” as a cornerstone for user immersion. Seamless alignment of virtual events with user expectations fosters a profound sense of immersion. Quotes emphasize the impact of substituting real-world stimuli, physically adjusting viewpoints, and empowering users to explore beyond scripted narratives. The provided quotes shed light on identified codes:“The substitution of real-world stimuli with virtual counterparts elicits a profound sense of complete immersion.”“Empowering users to explore the environment beyond scripted narratives results in an unmistakable enhancement of immersion.”The concept of the “First-Person Experience” plays a crucial role in immersive journalism. The objective is to immerse users in a first-person perspective during events, allowing them to undergo news stories firsthand. Quotes highlight the experiential context of stepping into a story, encountering it through a first-person lens, and the critical role of three-dimensional graphics in creating an interactive first-person perspective. The immersive experience transforms into knowledge unattainable through traditional journalism, showcasing the potency of both conventional and immersive storytelling. The following quotes further underscore this concept:“In an experiential context, individuals step into a story, encountering it through a first-person lens, moving within and interacting realistically.” “These theoretical discussions share striking similarities, emphasizing the critical role of three-dimensional graphics in crafting the illusion of a fully interactive first-person perspective, transcending mere camera positions.”5.2. Casual conditionsFocusing on enhancing immersive quality, three pillars shape the experience: “Cognition”, “narrative” and “ crafting the piece”.Cognition:Schema: Users’ knowledge structures impact immersion. If experiences don’t align with existing schemas or create new ones, cognitive dissonance disrupts harmony.Orientatin: Recognizing individuals and self-awareness are vital for enjoyment and immersion.Past Experience: Similar past experiences significantly influence users’ perception and immersive depth.Narrative:Realism: Theplace illusion and plausibility in virtual environments are crucial for perceptual stability and creating a tangible experience.Interactive Scenario: Active user participation enhances the illusion of presence, blurring the line between observer and participant.Crafting the Piece:Audio Quality: Sound is the backbone of storytelling, playing a crucial role in immersive journalism.Visual Quality: Initial immersion relies on visual display, creating a sensation unique to immersive journalism.These elements converge to craft an engaging and immersive virtual reality journalism experience.5.3. Contextual conditionsThe categories of “Demographic User Features” and the “Nature of News” chosen for virtual reality creation acts as the linchpin determining the augmentation or hindrance of immersive quality. These elements, encompassing age, gender, education, and social standing, prove pivotal. Emotional variances, persuasiveness, age, and the overall well-being shaping users’ lives are initial influencers, possibly steering the audience’s propensity for virtual reality engagement and, on a broader scale, molding their conduct and viewpoint. Noteworthy quotes include:“Attitudes cultivated through profound cognitive engagement or transformative shifts compared to those grounded in superficial cognitive processes cultivate more enduring and favorable behaviors.”“The behavior and mindset of an individual hinge on their literacy and knowledge levels. Consequently, this can significantly impact the user’s ability to connect with the narrative.”Conversely, the selection of news types for virtual reality production holds significance. Not all news is inherently suitable for virtual reality journalism, with only specific themes demonstrating aptness for this platform. If the chosen news type is incongruous, it risks diminishing the level of immersive experience. Conversely, judicious selection of news types can yield superior outcomes in captivating the audience with the subject matter. Exemplary quotes comprise:“While immersed in crime journalism, theft, and media coverage of racism, gender discrimination, and the like, we navigate these realms. Yet, I contend that only select topics within this spectrum prove beneficial and practical for virtual reality journalism.”“News conducive to immersive journalism are those that enrich the user’s comprehension of the event, actively involving them in the unfolding narrative.”5.4. Intervening conditionsTwo significant factors, ‘Trauma’ related to users and ‘Inhibiting Factors of Virtual Reality Usage’ tied to technology, exert substantial negative influence, undermining the core subject’s quality. The combination of ‘Disorder’ and ‘Claustrophobia’ shapes the ‘Trauma’ issue, with virtual reality equipment intensifying anxiety and inducing discomfort, impacting the immersive experience. The narrative space acts as an amplifier, heightening anxiety, particularly for users with real-world trauma, posing risks for producers. Additionally, barriers like high costs and limited accessibility hinder widespread virtual reality adoption, creating a challenging landscape. Noteworthy quotes emphasize caution in deploying tools for trauma survivors and address potential medical or psychological consequences, highlighting the obstacles in virtual reality’s emerging technology adoption.5.5. StrategiesThe primary goal of immersive journalism is to foster empathy by enabling the audience to connect with narrated stories, placing themselves in similar situations. Immersion is achieved when the news storyline aligns with the audience’s cognitive factors, enhancing their inclination and motivation. Focusing on cognitive elements plays a significant role in immersing the audience in the virtual narrative.5.6. Outcomes The presented strategy of “increasing perceived immersion” among audiences leads to broader outcomes, such as “changing norms and beliefs.” Immersion involves concepts like “suspension of disbelief,” “acceptance,” and “transference,” emphasizing user interaction with news narratives and a more realistic understanding of the virtual world. Norman Holland suggests that when individuals engage with a narrative, their brains immerse in perception, delaying critical evaluation until disengagement. This immersion is crucial for empathy and unbiased judgment. Additionally, focusing on cognitive factors can intensify audience immersion.On the other hand, the shift in norms and beliefs is the second outcome of immersive journalism’s cognitive focus, encompassing “catharsis” and “creating new knowledge.” The virtual space enables individuals to explore events without real-world consequences, aiding emotional release and achieving catharsis. Moreover, immersive news, addressing issues like climate change, can evoke empathy and drive societal change. The impact extends to individual, social, and global levels, showcasing the potential of this industry to influence behavior and reshape global societal norms. Conclusionimmersive journalism, utilizing virtual reality (VR), transforms storytelling by immersing users in news events. Dolapena’s 2010 study emphasizes a shift in journalism perspectives, focusing on cognitive factors like perception and psychology. The proposed model, derived from expert interviews, identifies six key elements, emphasizing user engagement, environmental interaction, and immersion perception. Strategic attention to cognitive factors enhances user involvement, increasing empathy and immersion. The primary outcome is heightened user empathy, while the secondary outcome positively impacts global norms and beliefs. Challenges in VR storytelling revolve around the dynamic relationship between immersion and user cognition, emphasizing the pivotal role of individual characteristics.Keywords: Virtual Reality, Immersion, Narrative, Immersive Journalism, Cognition.
Roghyeh Nouri; Mohammadreza Motadel
Abstract
Dashboards are an important tool for monitoring the performance of the organization and the decisions of managers, so their proper design in an integrated and orderly manner, taking into account the needs of customers and users and in accordance with organizational goals, is essential. The purpose of ...
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Dashboards are an important tool for monitoring the performance of the organization and the decisions of managers, so their proper design in an integrated and orderly manner, taking into account the needs of customers and users and in accordance with organizational goals, is essential. The purpose of this study is to provide a framework for designing management dashboards with QFD approach. For this purpose, after in-depth study in literature review, a conceptual research model was proposed, then using a mixed exploratory research Approach, management dashboard design framework, was presented. The statistical population of the qualitative section included 40 articles out of 452 articles related to the period 2005 to 2020 and related to dashboard topics and its design, which was done by Meta-Synthesizing method. Also, in quantitative part of the research, in order to validate the proposed framework and screen the indicators, fuzzy Delphi technique was used. The statistical population at this stage was 18 managers in different fields and 12 IT specialists and thus the framework. The design of management dashboards consisted of 4 dimensions, 11 components and 102 final indicators.
jamalodin ebrahimi; Mohammad Azizi; Katayoun Pourmehdi
Abstract
In today's world, technological advances and the complexity of the environment have created a highly competitive environment in which companies are constantly faced with dramatic market changes and the emergence of a variety of business opportunities. In such an environment, adapting to innovations and ...
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In today's world, technological advances and the complexity of the environment have created a highly competitive environment in which companies are constantly faced with dramatic market changes and the emergence of a variety of business opportunities. In such an environment, adapting to innovations and changes is essential for companies to achieve sustainable business success. International corporate entrepreneurship activities can increase the company's ability to recognize and take advantage of international market opportunities ahead of its competitors. This research is applied in terms of purpose and exploratory mixed method (qualitative-quantitative). The statistical population includes 17 people in the qualitative section by snowball method and 389 people in the quantitative section by random sampling. Data collection tools in the qualitative part are interviews and in the quantitative part are questionnaires. The method of data analysis in the qualitative part includes coding in the initial coding step, open coding and axial coding, and in the quantitative part is confirmatory factor analysis and structural equations using SPSS and Amos software. The research findings in the qualitative section show that five categories of factors affect the entrepreneurship of an international company, which are international factors, national factors, individual, organizational and industry characteristics. The results of the quantitative section show that these factors affect 74% of the achievements of international corporate entrepreneurship and organizational, international, individual and national factors and industry characteristics have the most to the least impact on international corporate entrepreneurship, respectively.
Kobra Khoram; Esmaeil Asadi; Sahar Dorniani
Abstract
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 ...
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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.
Ahmad Rahmani; Majid Sorouri; Reza Radfar; Mahmood Alborzi
Abstract
Technological innovation in the financial industry created the financial technology ecosystem. With the advent of artificial intelligence, the technology and financial worlds are intertwined to allow smarter financial processes to enable managers to make smarter decisions. It is not a fixed method of ...
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Technological innovation in the financial industry created the financial technology ecosystem. With the advent of artificial intelligence, the technology and financial worlds are intertwined to allow smarter financial processes to enable managers to make smarter decisions. It is not a fixed method of using the machine and accurate prediction of the test results using the machine algorithms is challenging. Much research has been done on the specific management of the customer experience, but research on financial technology in the artificial intelligence and machine industry in the sense of constructing a theory that can create a customer experience is a subject that pays less attention to. . This article, by reviewing 75 articles and summarizing it in 41 research articles, has examined the subject of the present study. In order to predict the presentation of theory, research method is a fundamental theory. The purpose of this article is to cover the gap of studies through which a research path is studied and the field of financial technology and artificial intelligence is examined. Findings show that what is done in extraordinary networks can be divided into five main parts of innovation. The findings provide a good way to address some of the issues in financial and artificial technology research for knowledge management experience through the possibility of providing a customer performance model.
