International Journal of Knowledge Processing Studies
Volume:3 Issue: 3, Summer 2023

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.

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.

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.

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.

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.

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.

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.