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.
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.
