Mila Malekolkalami; Mohammad Hassanzadeh; Atefeh Sharif; Mansour Rezghi
Abstract
This study aims to conduct a bibliometric analysis of knowledge extraction to examine its grassroots and interdisciplinary interactions based on papers in the Scopus database between 1980 and 2022. The study uses Biblimetrix, performance analysis, and science mapping techniques using 307 articles extracted ...
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This study aims to conduct a bibliometric analysis of knowledge extraction to examine its grassroots and interdisciplinary interactions based on papers in the Scopus database between 1980 and 2022. The study uses Biblimetrix, performance analysis, and science mapping techniques using 307 articles extracted from the Scopus database. The study used Biblimetrix (R package) and VOSviewer as a tool to carry out the performance analysis and science mapping analysis. The results show that the number of publications has significantly increased in the past decade, 1.53% of authors contribute at least a single article, and 98.46% of authors published multi-authored. China, the USA, and Japan were the most prolific countries in terms of the total number of citations and foreign collaborations. Expert Systems with Applications and the Journal of Knowledge Management are the top journals for knowledge extraction; Advances in Intelligent Systems and Computing (book series), and Lecture Notes in Computer Science are the top conference proceedings series in this field. Implications of knowledge extraction as an emerging discipline have been discussed based on the evidence and trends. The bibliometrics analysis can be helpful for professionals, scholars, and academics interested in bibliometric studies. it also provides essential information for making decisions on the vitality of disciplines.
Knowledge management
Farshid Bigdeli; Mohammadreza Dalvi Esfahan; Saeed Aghasi
Abstract
The purpose of this research is to model supply chain performance management based on information dashboards in private banks. The data was derived from in-depth and semi-structured interviews with 12 managers of five private banks in the country, which were based on purposeful sampling and continued ...
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The purpose of this research is to model supply chain performance management based on information dashboards in private banks. The data was derived from in-depth and semi-structured interviews with 12 managers of five private banks in the country, which were based on purposeful sampling and continued until reaching theoretical saturation. The validity of the research data was checked and confirmed by going back to the participants and external auditors. Data analysis was done based on the Strauss and Corbin model in the form of open, axial, and selective coding in the Atlas TI8 software. Modeling of supply chain performance management based on information dashboard in private banks including causal factors (intensification of competition, supply chain inefficiency, banking system challenges), intervening (appropriate corrective measures, organizational strategies, banking service challenges), platforms (quality management services, facilitating elements, and action management), strategies (development strategy, partnership strategy, discovery strategy, and focus strategy) and consequences (correction of performance evaluation system, financial-administrative function, performance improvement and innovation and supply chain development). To succeed in developing and changing their business model, they must correctly recognize factors affecting the supply chain of banking services in the fourth industrial revolution and digital revolution and successfully transition to the new technological era. A supply chain refers to the flow of materials, information, funds received from customers, and services from suppliers of raw materials through factories and warehouses to final customers, and includes organizations and processes that create goods, information, and services and deliver them to intended consumers.
Knowledge Extraction
Elham Samadi; Hasanali Bakhtiyar Nasrabadi; Zohreh Saadatmand
Abstract
This research aims to analyze the intellectual education of Avicenna (Ibn Sina) and discover practical knowledge. The purpose of text mining in historical records is to identify relationships within existing data and extract knowledge from them. When the existing data are structured, it is easy to use ...
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This research aims to analyze the intellectual education of Avicenna (Ibn Sina) and discover practical knowledge. The purpose of text mining in historical records is to identify relationships within existing data and extract knowledge from them. When the existing data are structured, it is easy to use data mining methods to extract knowledge from them. In relation to the research topic, the method employed in this study is text mining analysis, making this research exploratory. The TF-IDF weighting method is used in this research. Considering the high dimensionality of the data, where the number of features is much greater than the number of vulnerable samples, linear Support Vector Machine (SVM) is a more suitable choice for these tests. Various implementations of this algorithm are available. In this research, LibLinear SVM, which is one of the most suitable implementations, has been used. First, the conceptual texts of Ibn Sina's thought were analyzed by understanding the contexts of existence, knowledge, man, and values. Subsequently, a list of educational requirements was deduced using concepts and categories. Finally, models for the construction of cognitive perception and an educational model were proposed. It can be said that the ideal human being, according to the teachings of Sinai, is someone who, through their scientific perspective related to their existence, knowledge, and values, can attain proper intellectual development and happiness derived from understanding the truths of the universe. This individual can acquire intellectual knowledge, enhance their power of critical thinking and reasoning, and ultimately achieve perfection.
Intelligent agents
Marco Scialdone; Maria Vittoria La Rosa
Volume 3, Issue 3 , July 2023
Abstract
The development and use of artificial intelligence (AI) systems are raising concerns among experts and intellectuals, including Elon Musk, Steve Wozniak, and Yuval Noah Harari. In a letter signed by multiple individuals from various fields, they call for a halt to the development of advanced AI systems, ...
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The development and use of artificial intelligence (AI) systems are raising concerns among experts and intellectuals, including Elon Musk, Steve Wozniak, and Yuval Noah Harari. In a letter signed by multiple individuals from various fields, they call for a halt to the development of advanced AI systems, citing the risks of propaganda and untruths flooding information channels, the automation of jobs, the development of non-human minds that could replace humans, and the danger of losing control of civilization. These concerns have resulted in calls for regulatory measures and investigations into companies like OpenAI. However, addressing the challenges posed by AI requires not just legal and regulatory instruments but also stronger cultural and critical education.
Knowledge management
Noorolla Majidian Dehkordi; Mohammadreza Dalvi Esfahan; Sayyed Rasool Aghadavood
Abstract
This fundamental-applied research aims to design and test the organizational embeddedness model based on the knowledge application with a mixed approach using grounded theory (GT). In the qualitative section, data is derived from in-depth interviews conducted with 25 high-ranking and experienced managers ...
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This fundamental-applied research aims to design and test the organizational embeddedness model based on the knowledge application with a mixed approach using grounded theory (GT). In the qualitative section, data is derived from in-depth interviews conducted with 25 high-ranking and experienced managers of the Central Bank, who were selected based on snowball sampling. In the quantitative section, according to Cochran's formula, 346 out of 3500 people were selected by stratified random method. Qualitative data analysis was done using the grounded theory analysis method and quantitative data was analyzed by confirmatory factor analysis method with AMOS and SPSS software. The results showed that the dimensions and components of organizational embeddedness in the Central Bank can be classified into 24 main dimensions and 51 components, which include 6 main groups: causal conditions, core category, strategies, consequences, contextual conditions, and intervening conditions. Each group has 4 dimensions: individuals, group, organizational and environmental. The results indicated that paying attention to the financial needs of employees in order to create motivation, maintain their job position, and encourage families can be considered as a general solution.
Data mining
Ali Esmaili; Hoshang Taghizadeh; Naser Faqhi Farhamand
Abstract
This research aims to study the data-driven model of gas consumption management, with a focus on addressing unauthorized use through the analysis of information systems. Research was conducted using a metasynthesis approach and technique in the field of gas consumption management and mathematical programming ...
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This research aims to study the data-driven model of gas consumption management, with a focus on addressing unauthorized use through the analysis of information systems. Research was conducted using a metasynthesis approach and technique in the field of gas consumption management and mathematical programming with genetic algorithms. ATLAS.ti software was used for analysis. The influencing factors related to a specific period of time were examined and searched for in this research. Internal and external sources from the years 2006 to 2023 were analyzed. 27 studies were selected based on the Critical Appraisal Skills Programme (CASP) technique. In the continuation of mathematical modeling using MATLAB software, the simulation was conducted to compare the performance of three proposed algorithms. Based on the results obtained from the meta-combination technique, the main categories include the use of renewable energy, gas consumption management, shortcomings, obstacles, data-driven solutions, consequences of gas consumption management, and economic growth. All three models also demonstrated the basis for optimal gas consumption and the reduction of unauthorized consumption. The utilization of data analysis can enhance system efficiency, pinpoint weaknesses and losses, boost productivity, and optimize the utilization of gas energy. Based on the analysis, it was shown that data mining can be very useful in managing gas energy consumption and identifying unauthorized breaches. Overall, simulating gas energy consumption management using a genetic algorithm can provide efficient and effective solutions, handle complex and dynamic scenarios, and offer insights into optimizing gas consumption and energy efficiency.
Data mining
Taimour Jafarian Dehkordi; Mohammadreza Dalvi Esfahan; Saeed Aghasi
Abstract
Purpose: The current research was conducted by designing the knowledge-based organizational satisfaction modeling with a data-driven approach using a qualitative and quantitative method of grounded theory and data mining techniques.methods: The data was taken from in-depth and semi-structured interviews ...
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Purpose: The current research was conducted by designing the knowledge-based organizational satisfaction modeling with a data-driven approach using a qualitative and quantitative method of grounded theory and data mining techniques.methods: The data was taken from in-depth and semi-structured interviews with 25 general managers of social security insurance departments in the provinces of the country, based on purposeful sampling. The validity of the research data was checked and confirmed by going back to the participants and external auditors. In the data mining section, registered data and the organization's database were used. Using the data recorded in the Clementine software, the happiness and unhappiness of the employees in the organization were categorized.Findings: The results showed that the model of organizational happiness in the social security organization was identified at three levels, group, individual and organization, including causal factors, intervenors, platforms, strategies and finally consequences. Also, the status of employees was determined based on the proposed model of happiness according to the collected data. Finally, the data mining model showed classification with 66% accuracy for happy and unhappy employees.Conclusion: The human resource management approach based on organizational data leads to correct decision making in organizational performance. The more transparent the collected data is, the more accurately the state of the organization can be predicted. Also, based on the proposed model and implementation in the form of data mining, it is possible to estimate the number of happy employees.
Hasan Asali; Sayyed Mohammad Reza Davoodi; Sayyed Hamid Reza Mirtavousi
Abstract
This research aims to present a knowledge development model for future managers based on talent management with a grounded theory approach in the Iranian Social Security Organization (headquarters). This research is applied in terms of purpose and exploratory in terms of method. It uses a mixed methods ...
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This research aims to present a knowledge development model for future managers based on talent management with a grounded theory approach in the Iranian Social Security Organization (headquarters). This research is applied in terms of purpose and exploratory in terms of method. It uses a mixed methods approach for data collection and analysis, qualitative and quantitative data analysis techniques- grounded theory and structural equation. The research tool in the qualitative part was a semi-structured interview. In the qualitative part, using the grounded theory method, data obtained from the interviews with 12 elites and qualified specialists of the Social Security Organization, which were analyzed manually and by using Atlas TI 8 software during three stages of open, central, and selective coding that resulted in generation of 19 categories. The results were presented in the form of a paradigm model that includes causal conditions (individual factors, organizational factors, lack of proper selection and knowledge and skills of employees), central phenomenon (future managers based on talent management and personality types), underlying conditions (organizational platform, selection of talents, use of talent) Intervening conditions (psychological factors, individual factors, managerial factors) and strategies (talent sourcing, empowering managers and employees, job and employee fit, succession planning, foresight, and cognitive strategy) and outcomes (organizational results, public satisfaction, futurization). In the quantitative part, the data obtained from the structural equation analysis questionnaire were analyzed using AMOS statistical software. Based on the outputs, the factor loadings of all the items of the standard model were higher than 0.3, and all the significant coefficients of the model were higher than 1.96.
Big data
Mona Abrofarakh; Kambiz Shahroodi; Narges Delafrooz
Abstract
This research aims to design a data-driven value-creation model for insurance policyholders. It uses a mixed methodology (qualitative-quantitative). The statistical population was university professors in insurance and marketing and senior managers of Iran's insurance industry, including Asia Insurance, ...
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This research aims to design a data-driven value-creation model for insurance policyholders. It uses a mixed methodology (qualitative-quantitative). The statistical population was university professors in insurance and marketing and senior managers of Iran's insurance industry, including Asia Insurance, and Alborz Insurance. The saturation was reached with 12 university professors. To identify the influential factors in the data-driven value creation model for insurance policyholders, the Delphi technique was used in the form of theoretical consensus. The interpretative structural method was used for modeling. The studied structures to design and explain the value creation model for insurance policyholders in Iran's insurance industry include factors related to employees, policyholders, training, organization, management, and branding. Based on structural-interpretive modeling calculations, it was determined that the factors related to employees are external independent variables unaffected by any variable in the model. The factors related to employees and training are endogenous independent variables, and the factors related to the brand are dependent. Also, the factors related to insurance policyholders plays a mediating role. Researchers believe that the more organizations can gain a better understanding of customer needs, as well as the activities of competitors and factors affecting market conditions and distributing information at all levels of the organization, the more ability they will have to survive in the competitive market.
Big data
Sadegh Tayebi; Alaedin Etemad Ahari; Fariba Hanifi
Abstract
The research aims to apply big data in providing an effective model of education in serving the knowledge workers of the municipality. The research method was integrated research (quantitative and qualitative). The components and dimensions of the subject were examined in the form of documentary studies ...
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The research aims to apply big data in providing an effective model of education in serving the knowledge workers of the municipality. The research method was integrated research (quantitative and qualitative). The components and dimensions of the subject were examined in the form of documentary studies and interviews and identified in the form of educational content with thematic analysis technique. To analyze the qualitative data, the theme analysis method was used using ATLAS TI software, and genetic algorithm and meta-heuristic methods were used in MINITAB software. The research tool (data collection) was the qualitative part of a semi-structured interview with 12 elites, experts, and qualified specialists of Karaj municipality. The sampling method in the qualitative part was non-probability and non-homogeneous purposeful type dependent on the criterion and in the quantitative part, it was simply random. Finally, the proposed model of in-service training for employees was designed and validated. 6 comprehensive themes (planning (comprehensive implementation), learner, teachers, content, educational environment, and infrastructure) were identified in the form of a paradigm model. The results showed that the VIS algorithm had the best performance. Algorithms CNSGA-II and MISA are almost ranked second and have shown almost similar performances. NSGA-II algorithm is ranked next. The NNIA algorithm is in the next position in terms of performance, and the worst performance is assigned to the NRGA algorithm. Organizational innovation based on big data and organizational training improves the performance of knowledge workers and creativity.
Mahshid Pourhossein; Mehdi Sabokro; Saeid Saeida Ardekani; Masood Charifi
Abstract
This study aims to develop a comprehensive bibliometric overview of the publications on knowledge workers from the Web of Science database (WOS). The current research is of an applied type and has been carried out using scientometric methods and co-authorship and synonym analysis techniques. In this ...
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This study aims to develop a comprehensive bibliometric overview of the publications on knowledge workers from the Web of Science database (WOS). The current research is of an applied type and has been carried out using scientometric methods and co-authorship and synonym analysis techniques. In this regard, 1609 scientific papers on knowledge workers were bibliometric analyzed in a descriptive-analytical study. A graphical mapping of the bibliometric material by using the visualization of similarities (VOS) viewer software has been developed in this work. The retrieved papers cover the years from 1938 to 2021. The results indicate an upward trend in the publication in the last ten years. This research demonstrated that keywords changed over time from focusing on key differences between knowledge workers and others to psychological factors related to employees and motivational factors. This study is one of the first attempts to summarize knowledge workers and suggests future research directions.
Data mining
Hojat Mahammadi Torkamani; Mohammad Pasban; Yaghoub Alavi Matin; Hakimeh Niki Esfahlan
Abstract
This research aims to design an intelligent model of digital consumer behavior knowledge based on big data. This research was conducted using a qualitative approach. First, the qualitative method of thematic analysis was used, followed by the application of big data analysis techniques. The statistical ...
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This research aims to design an intelligent model of digital consumer behavior knowledge based on big data. This research was conducted using a qualitative approach. First, the qualitative method of thematic analysis was used, followed by the application of big data analysis techniques. The statistical population includes experts in the field of marketing who specialize in qualitative analysis. The sample size was determined to be 10 people using the snowball method and theoretical saturation. The data collection tool includes interviews with experts, which were analyzed using the thematic analysis technique in MAXQDA. In the following, the customer's behavioral trend has been studied based on the Big Data technique model, using the data available in the Digikala company. Coding in MATLAB is done based on specific formulas. The results showed seven components and 48 indicators that were identified and approved by experts in designing consumer behavior patterns using a digital marketing approach. These components include 1. Marketing Practices. 2- Innovation, 3- Digital marketing strategy, 4- Dynamic digital marketing, 5- Customer management, 6- Consumer cooperative behavior, and 7- Consequences of consumer response. The business management has finally decided to expand the intelligent system for consumer behavior. The main evaluation index is relatively unique and cannot effectively stimulate the acquisition of new customers. The only evaluation comes from consumers who have a recorded history of financial behavior on the digital platform. The value network model relies on digital technology because it facilitates interaction between end consumers as a relational medium.
Data mining
Seyed Rohollah Abbasi; Abdul Khalegh Gholami Chenaristan Alia; Foad Makvandi
Abstract
This study aimed to design a data-driven decision-making model for managers in the direction of empowering human resources in the police headquarter of Kohgiluyeh and Boyer-Ahmad province. Increasing amount of information and rapid changes in the environment and the need to create continuous communication ...
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This study aimed to design a data-driven decision-making model for managers in the direction of empowering human resources in the police headquarter of Kohgiluyeh and Boyer-Ahmad province. Increasing amount of information and rapid changes in the environment and the need to create continuous communication with the complex and dynamic environment requires management, acquisition and distribution of knowledge as well as, proper organizing and analysis of information. The present research uses a qualitative approach. The statistical population included experts in the police force, 19 people were selected through purposive sampling and interviewed. The identified indicators of the data-driven decision-making model of managers in empowering employees were extracted in the form of 3 main categories, 17 sub-categories, and 69 concepts. The identified model was also tested based on the AdaBoost regression algorithm in Rapidminer software which led to development of the intelligence of the managers' decision-making model compared to the traditional model. The findings showed structural factors (including strategic orientations, organizational structure dynamics, performance management system, training and improvement, knowledge management system, job design system, and information technology system) behavioral factors (including management orientations, leadership style, development of psychological characteristics of employees), development of decision-making skills and competences of employees, human relations system, job attitudes, and organizational culture) and environmental factors (including legal factors, political factors, and economic factors). Based on the proposed model, the accuracy of data-driven decision-making of managers was tested and the results indicated the significance of intelligence and information in the organization.
Knowledge Extraction
Mohammad Hossein Rahmati; Farshid Namamian; Seyed Reza Hasani; Afshin Baghfalaki
Abstract
Brand resilience knowledge helps companies maintain customer trust and strengthen relationships through proper planning and strategies. This research was conducted to model brand resilience in Iran's handwoven carpet industry using background knowledge and data mining in critical conditions. In brand ...
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Brand resilience knowledge helps companies maintain customer trust and strengthen relationships through proper planning and strategies. This research was conducted to model brand resilience in Iran's handwoven carpet industry using background knowledge and data mining in critical conditions. In brand resilience, knowledge analysis is considered highly significant for identifying key factors and effective patterns. This mixed research has been done based on qualitative data techniques in NVIVO software and quantitative data mining method in MATLAB software. 12 people were selected purposefully from carpet industry experts. Interviews were analyzed, coded, according to Strauss and Corbin method, and compared with the data mining method of the trained model and the MLP method. Based on the proposed model, 6 categories, 15 core codes, and 41 primary codes were identified. The proposed model could predict 98% brand resilience in crisis conditions. This model can help brands to maintain their business interests and implement appropriate strategies for active development, internal resistance, creative support, and production under sanctions. Furthermore, this model can help brands strengthen their capabilities and brand value, and identity in critical situations.
Knowledge management
Seyed Mohammad Hadi Hosseini Hesamabadi; Nader Shahamat; Reza Zarei; Moslem Salehi
Abstract
The current research aimed to design and fit the knowledge-enhancing model of effective teaching. knowledge-enhancing in teaching, as a condition of "life, durability and survival", displays the dynamic spirit of education and is created in three pyramid heads (students, parents, and teachers). The research ...
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The current research aimed to design and fit the knowledge-enhancing model of effective teaching. knowledge-enhancing in teaching, as a condition of "life, durability and survival", displays the dynamic spirit of education and is created in three pyramid heads (students, parents, and teachers). The research method is mixed and practical in nature. The statistical population includes all teachers working in the education ministry in Fars province. The sample size of 18 people sample selection was determined in the qualitative section by the purposeful sampling method. Quantitative sampling was obtained according to Cochran's formula of 376 people. The data collection tool, in the qualitative part, included two parts, a semi-structured interview and review of upstream documents, and in the quantitative part, a researcher-made questionnaire tool. Data analysis in the qualitative section was based on thematic analysis in ATLAS TI software. Structural equation modeling was used in SMARTPLS software to fit the model. The obtained findings led to the identification of 3 dimensions, 10 components, and 176 indicators, and finally, the research model was presented. The results showed that each of the dimensions, respectively: teaching and evaluation, scientific-educational (/66), and individual (/57) affected effective teaching in elementary school. Students learn by connecting new knowledge with existing knowledge and concepts, constructing new meanings. Knowledge-based education emphasizes primary education on deep and powerful teaching and learning from shared knowledge.
Taimour JafarianDehkordi; Mohammadreza Dalvi Esfahan; Saeed Aghasi
Abstract
The purpose of this research was to present an organizational vitality model based on information management and human resource data. Human resource information management is a process that seeks to increase organizational capability through the organization's employees, which is considered one of the ...
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The purpose of this research was to present an organizational vitality model based on information management and human resource data. Human resource information management is a process that seeks to increase organizational capability through the organization's employees, which is considered one of the most important success factors. The research was designed in a mixed qualitative and quantitative method and benefited from the foundation's data strategy. In the qualitative part, the data obtained from in-depth interviews with 25 general managers of social security of the provinces of the selected country were based on purposeful sampling. In the quantitative part, 376 people from the lower-level employees of this organization were selected in different regions of the country by stratified random method and answered the questions of the researcher-made questionnaire. Qualitative data were analyzed using the Grounded Theory and the quantitative data were analyzed through confirmatory factor analysis using SPSS and AMOS software. The results obtained from the qualitative phase of the research led to the design of a proposed conceptual model of organizational vitality in the social security organization, and in the quantitative phase, using path analysis, validity of the conceptual model was. evaluated. From the practical point of view, the proposed model can be implemented by social security organization managers to create vitality among employees in order to reduce depression and boost productivity.
Knowledge Extraction
sahar kousari; Alireza Yari
Abstract
Innovation and economic growth is mainly formed by a unique combination of the companies that are interconnected in the field of knowledge and process. Such connections can be based on different goals among the service provider companies while two common methods for this objective include the cluster ...
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Innovation and economic growth is mainly formed by a unique combination of the companies that are interconnected in the field of knowledge and process. Such connections can be based on different goals among the service provider companies while two common methods for this objective include the cluster and ecosystem. The main objective of this article is to develop the cluster ecosystem of Iranian native search engine. In the ecosystem, relationship between the actors are formed based on the function-oriented complementary relationship of cluster of Iranian native search engine. This article aims at understanding the relating concepts of high-tech clusters and business ecosystems. Thus, while studying the existing literature, identified the different functions of native search engine clusters and different types of the actors and stakeholders of ecosystem by related experts. Then considering the role of each actor in the general functions of the native search engine, we tried to identify the relationships and interactions among those actors. Finally, the cluster ecosystem development model for the Iranian native search engine was designed based on the value network among the actors of Iranian native search engine. The findings of this research included: 1. identifying the ecosystem actors of native search engine, 2. developing the cluster of search engine functions, 3. designing the value network of the mentioned ecosystem.Originality/ value: the proposed model, makes it possible for the actors to begin the interaction and value flow based on their roles in the cluster.
Knowledge management
Alireza Mandegari; Sina Nematizadeh; Abbas Heidari
Abstract
Due to the increasing exchange of information and data through the use of cell phones, this research aims to design a data-driven model of mobile marketing in Iran. The focus is on decision-making information related to purchasing behavior. By studying customers' decision-making information, businesses ...
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Due to the increasing exchange of information and data through the use of cell phones, this research aims to design a data-driven model of mobile marketing in Iran. The focus is on decision-making information related to purchasing behavior. By studying customers' decision-making information, businesses can collectively form antecedents that enable them to predict customers' behaviors and reactions. A mixed exploratory methodology (qualitative-quantitative) was used to collect and analyze the research data. For this purpose, the qualitative phase utilized the theme analysis method, while the quantitative phase employed the fuzzy Delphi and fuzzy hierarchical analysis methods.Therefore, it was determined that the mobile marketing model, based on decision-making information on purchasing behavior, includes 98 indicators, 18 components, and four general categories (dimensions) of influencing factors. These categories are decision-making styles, individual factors, social factors, and technical factors.The results of the quantitative phase showed that the most important factors in decision-making, from the customer's perspective, were sensitivity to the price and value of goods, social pressures, user concerns and worries, and utilitarian factors related to the message. Mobile marketing can be effective among Iranian users and consumers when it aligns with the various aspects of consumer purchasing behavior decision-making information and enhances perceptions. It instilled a desire in people to prioritize safety and usefulness in their field.
Knowledge Extraction
Ali Zare Abarghouei; Mohammad Reza Dalvi; Zahra Dashtlaali
Abstract
The current research was conducted to apply knowledge extraction in the classification of jobs to identify the key role players using a mixed method (qualitative and sufficient data). The application of expert systems or decision support systems based on organizational data is increasing in the selection ...
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The current research was conducted to apply knowledge extraction in the classification of jobs to identify the key role players using a mixed method (qualitative and sufficient data). The application of expert systems or decision support systems based on organizational data is increasing in the selection and hiring of personnel. The data was derived from in-depth and semi-structured interviews with 17 subject experts in bank human resources, who were selected based on purposeful sampling.Data analysis was done based on the Strauss and Corbin model in the form of open, axial, and selective coding in the Atlas TI8 software. The results showed that the classification of jobs for the key role players in public and private banks includes causal conditions (requirement of talent substitution, human resource management developments, and organizational challenges), intervening conditions (organizational limitations and fear and resistance), and contextual conditions (strengthens and drivers) strategies (developmental, supportive and creating) and short-term and long-term consequences are among the components of the job classification model for the key role players in public and private banks. Next, based on the database with the CART method, the data mining of job classification was done. Regarding the performance of the model, it showed variance values of 311.92 and a risk value of 288.19. The predictions in the model explained 28.9% of the differences observed in the variable "employment status of A employees' category".
Hasan Najafi; Muslim Qabadian; Ebrahim Pour Hosseini
Abstract
This research aims to provide a knowledge dissemination system for the development of the professional skills of managers. This research was a mixed strategy of sequential exploratory type. The research method was a case study in the qualitative part and a descriptive survey in the quantitative part. ...
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This research aims to provide a knowledge dissemination system for the development of the professional skills of managers. This research was a mixed strategy of sequential exploratory type. The research method was a case study in the qualitative part and a descriptive survey in the quantitative part. The statistical population included all secondary school principals of different educational units in Tehran, totaling 1171 people. The sample (20 people) was selected by a purposeful sampling method and resource-oriented technique in the qualitative section. Quantitative part sampling was done by multi-stage cluster sampling and the sample size was 181 people according to Cochran's formula. In the qualitative part, the data collection tool consisted of two parts, a semi-structured interview and a single-question questionnaire, in the quantitative part, a researcher-made questionnaire tool was used to collect data. Data analysis was done in the qualitative section based on thematic analysis in ATLASTI software. Also, in the quantitative part, confirmatory factor analysis was used to analyze the data and structural equation modeling was used to determine the fit of the model. Spss-23 and Lisrel-8 software were used in the quantitative section. The obtained results led to the identification of 29 sub-components and 6 main components and finally, the research model was presented. The dimensions include the educational dimension (0.78), research dimension (0.70), service dimension (0.64), moral dimension (0.61), cultural dimension (0.57), and executive dimension (0.50). Bentler-Bonett's Normed fit index, relative fit, incremental fit, and adaptive model indices showed that the designed structural model had a good fit.
Knowledge Extraction
Zahra Sadat Hadj Seyed Hossein Khani Taher Kermani; Neda Fatehi Rad; Valeh Jalali
Abstract
Research in second language learning has identified the absence of metacognition awareness among learners as one of the major problems contributing to students' inability to develop reading skills. This mixed-method study sought to investigate the impact of metacognitive awareness raising via explicit ...
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Research in second language learning has identified the absence of metacognition awareness among learners as one of the major problems contributing to students' inability to develop reading skills. This mixed-method study sought to investigate the impact of metacognitive awareness raising via explicit reading strategy instruction in a flipped instructional environment on Iranian EFL learners' reading skills. To this end, a sample of 56 EFL learners at the pre-intermediate level (28 in the treatment group and 28 in the control group) who were selected based on convenient sampling from one of the private language institutes in Kerman, Iran, participated in the study. Data werecollected using the Oxford placement test, a reading pre-test, a post-test, and a semi-structured interview. The findings revealed that EFL learners in the treatment group outperformed the control group in reading comprehension from the pre-test to the post-test. The results of the semi-structured interview confirmed the results of the t-test, and it was concluded that the learners were satisfied with the treatment due to its cooperative, fun, and informative nature. The participants, even though they mentioned some negative points such as the unavailability of the instructor and wasting time on both methods and unimportant details, reported on the effective role of both flipped context and the strategy itself. In sum, the results confirmed that integrating flipped classrooms with metacognitive development increased EFL learners' reading comprehension.
Knowledge management
Abdolhamid Sharafi; Malike Beheshtifar; Mohamad Ziaaddini
Abstract
The main purpose of this study is to develop a model of strategic unlearning of sharing knowledge in Iranian state-owned banks. This qualitative study is developmental in terms of purpose. In the first part of this research, the content related to the concepts of unlearning and strategy were extracted ...
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The main purpose of this study is to develop a model of strategic unlearning of sharing knowledge in Iranian state-owned banks. This qualitative study is developmental in terms of purpose. In the first part of this research, the content related to the concepts of unlearning and strategy were extracted from library sources. The second part refers to the interview process with 21 managers, executives, and experts conducted in the winter of 2021. The statistical population of the research includes experts from the university department who have published at least two articles in the field of unlearning and related research plans. Furthermore, the executive team comprises individuals with a university degree and a minimum of 4 years of work experience in the field of banking education. Judgmental sampling was implemented based on the opinions of professors and experts in this field and continued until theoretical saturation was achieved. The interviews were then analyzed using Atlas.ti 8 software. Findings identified 11 components, 18 indicators, and 76 selected codes. The results also indicated that some components, such as employee development, management, economics, knowledge management, education, organizational structure, legal aspects, marketing strategies, cultural factors, consolidation, rigidity, and unlearning, are essential in the strategic unlearning process of Iranian state-owned banks.
Data mining
Nasim Bakhshaei; Mohammad Reza Bagherzadeh; Yusuf Gholipourkanani; Mohammad Reza Dalvi
Abstract
This research aims to develop a data-based model for fifth-generation universities. Creating a data-driven model in a university environment is essential in education. The primary mission of higher education is to address the specific educational needs of individuals, as well as the needs of society ...
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This research aims to develop a data-based model for fifth-generation universities. Creating a data-driven model in a university environment is essential in education. The primary mission of higher education is to address the specific educational needs of individuals, as well as the needs of society and its economic development. The study was conducted in both qualitative and quantitative sections. The grounded theory is conducted based on the perspectives of the chancellors of Islamic Azad University. 21 people were selected using snowball sampling techniques. In the following, a six-category model is provided. Analysis was done using NVIVO software. The statistical population in the quantitative section consisted of all professors from Islamic Azad University nationwide. A sample size of 381 professors was selected using the Cochran sampling formula. The research tool was a questionnaire created by the researcher. Then, using the model presented and the suggested pattern fit, the performance of the model is predicted based on the K-Mean method in Weka and RapidMiner software. According to the results, the proposed model was approved by experts. The analysis of structural equations was also confirmed. According to the Waode algorithm model, the highest accuracy was 81%.
Sakineh Bakhtiari; Shahram Ranjdoost; Ghafar Tari
Abstract
This research aims to process knowledge in educational organizations based on the jihadi management approach. Knowledge is a common subject in management, organization science, and economics, which is given special importance in Jihadi economic and managerial subjects. In the research, a mixed method ...
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This research aims to process knowledge in educational organizations based on the jihadi management approach. Knowledge is a common subject in management, organization science, and economics, which is given special importance in Jihadi economic and managerial subjects. In the research, a mixed method (quantitative-qualitative) has been used to advance the research objectives. The snowball technique was used for sampling in this research. In total, interviews were conducted with 11 experts in the field of education. In this combined research, the thematic analysis method has been performed. In the following, to fit the proposed model, the confirmatory factor analysis model has been used in AMOS software. The population studied in the quantitative analysis were the managers of the educational centers, and due to the unlimited number of people, 384 people were considered as a sample based on Morgan's table. Based on the findings of this research, 4 central categories were identified in the field of jihadi management, which provided the means for knowledge processing in educational organizations based on the jihadi management approach. From the findings of this research, it is concluded that an important step that must be taken to improve the productivity and performance of managers in organizations is to move from organizational information to knowledge processing; In fact, knowledge is obtained from understanding information, and if we apply our knowledge, skill is obtained, and when we combine our skill with other skills, expertise is obtained, and finally, we have mastered our expertise.
Knowledge Extraction
Ali Asghar Rajabi; Asadollah Mehrara; Mehrdad Matani
Abstract
This research aimed to provide a model for evaluating human resources management in the automotive industry. This applied research was conducted with an exploratory and mixed nature (qualitative-quantitative) using the seven-step hybrid method of Sandelowski and Barroso (2007). Furthermore, to enrich ...
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This research aimed to provide a model for evaluating human resources management in the automotive industry. This applied research was conducted with an exploratory and mixed nature (qualitative-quantitative) using the seven-step hybrid method of Sandelowski and Barroso (2007). Furthermore, to enrich the collected data, the opinions of experts in the automotive industry were used in the framework of focus groups. In the end, the importance and priority of each of the extracted dimensions, criteria, and concepts were determined using the multi-criteria decision-making approach and the hierarchical AHP method.The designed model included 3 main dimensions and 12 criteria coded as:Human resources leadership, The role of human resources manager, Strategic management of human resources and its design in the organization, Information, and knowledge system of human resources, Risk management in the field of human resources, Supply and adaptation, Development of human resources, Use of human resources, Maintenance of human resources and results, Results of human resources perception, Functional results of human resources, Organizational results are affected by the field of human resources. Furthermore, the reliability was calculated using the Kappa index. One of the advantages of this model is the emphasis on creating vertical and horizontal coordination and balance between human resources processes by examining and establishing the relationship between drivers, systems, and results simultaneously.