نوع مقاله : مقاله پژوهشی
نویسندگان
1 استادیار، گروه مدیریت، دانشگاه پیامنور، تهران، ایران
2 گروه مدیریت، دانشگاه پیام نور، تهران، ایران
چکیده
کلیدواژهها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Purpose: The aim of this study is to present an analytical model to examine the relationship between language barriers (translation barriers, linguistic complexity, and cultural adaptation barriers) and knowledge processing in organizations, with a focus on the mediating role of artificial intelligence (AI) in the export storage units of Shazand Mahshahr Petrochemical Company. The study addresses the growing importance of knowledge management and the application of emerging AI technologies in multicultural and multilingual environments.
Method: This applied research employs a descriptive–survey design and is causal (ex post facto) in nature. The statistical population included all employees of the export storage units of Shazand Mahshahr Petrochemical Company (N=70), selected through a census method. Data were collected using three standardized questionnaires measuring language barriers including three dimensions, 21 items, knowledge processing including two dimensions, 7 items, and AI including five dimensions and 22 items. Validity was confirmed by expert review, and reliability was supported by Cronbach’s alpha coefficients above 0.7. Data analysis was conducted through confirmatory factor analysis and structural equation modeling using the PLS approach
Findings: The results indicated that all dimensions of language barriers (translation barriers, linguistic complexity, and cultural adaptation barriers) have a positive and significant effect on knowledge processing in the organization. Moreover, AI plays a mediating role in these relationships, with the strongest mediation observed between translation barriers and knowledge processing (path coefficient = 0.991). This suggests that part of the impact of language barriers on knowledge processing is transmitted through AI, which can mitigate the negative effects of these barriers.
Conclusion: The findings highlight the importance of accurate translation, the use of plain language, culturally adaptive content, and AI adoption in enhancing knowledge processing in organizations. AI can facilitate the knowledge transfer process, especially in specialized and multilingual settings, by reducing the adverse effects of language barriers. Therefore, managers should focus not only on overcoming language barriers but also on developing the necessary infrastructure for AI adoption and providing staff training to effectively utilize this technology.
Purpose: The aim of this study is to present an analytical model to examine the relationship between language barriers (translation barriers, linguistic complexity, and cultural adaptation barriers) and knowledge processing in organizations, with a focus on the mediating role of artificial intelligence (AI) in the export storage units of Shazand Mahshahr Petrochemical Company. The study addresses the growing importance of knowledge management and the application of emerging AI technologies in multicultural and multilingual environments.
Method: This applied research employs a descriptive–survey design and is causal (ex post facto) in nature. The statistical population included all employees of the export storage units of Shazand Mahshahr Petrochemical Company (N=70), selected through a census method. Data were collected using three standardized questionnaires measuring language barriers including three dimensions, 21 items, knowledge processing including two dimensions, 7 items, and AI including five dimensions and 22 items. Validity was confirmed by expert review, and reliability was supported by Cronbach’s alpha coefficients above 0.7. Data analysis was conducted through confirmatory factor analysis and structural equation modeling using the PLS approach
Findings: The results indicated that all dimensions of language barriers (translation barriers, linguistic complexity, and cultural adaptation barriers) have a positive and significant effect on knowledge processing in the organization. Moreover, AI plays a mediating role in these relationships, with the strongest mediation observed between translation barriers and knowledge processing (path coefficient = 0.991). This suggests that part of the impact of language barriers on knowledge processing is transmitted through AI, which can mitigate the negative effects of these barriers.
Conclusion: The findings highlight the importance of accurate translation, the use of plain language, culturally adaptive content, and AI adoption in enhancing knowledge processing in organizations. AI can facilitate the knowledge transfer process, especially in specialized and multilingual settings, by reducing the adverse effects of language barriers. Therefore, managers should focus not only on overcoming language barriers but also on developing the necessary infrastructure for AI adoption and providing staff training to effectively utilize this technology.
کلیدواژهها [English]
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