Exploring the application of knowledge-enhanced large language models in automotive marketing education: A case study of ERNIE bot
With the rapid evolution of intelligent and electric vehicle technologies, the automotive industry faces significant transformation, especially in autonomous driving, connected systems, and global market integration. This shift has heightened the demand for skilled automotive marketing professionals...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Akademia Baru
2024
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/43494/ http://umpir.ump.edu.my/id/eprint/43494/1/J%202024%20ARFMT%20LuHK%20M.M.Noor%20Automotive%20Edu%20Case%20Study.pdf |
| _version_ | 1848826889309782016 |
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| author | Lu, Hong Kun Fei, Song Noor, M. M. Wu, Bingli |
| author_facet | Lu, Hong Kun Fei, Song Noor, M. M. Wu, Bingli |
| author_sort | Lu, Hong Kun |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | With the rapid evolution of intelligent and electric vehicle technologies, the automotive industry faces significant transformation, especially in autonomous driving, connected systems, and global market integration. This shift has heightened the demand for skilled automotive marketing professionals equipped with both practical expertise and cross-cultural competence. This study explores the application of Baidu's ERNIE Bot as a knowledge-enhanced large language model in automotive marketing education. Focusing on its capabilities to innovate teaching content, optimize instructional methods, expand virtual training, and enhance cross-cultural sensitivity, we investigate ERNIE Bot’s effectiveness in preparing students for global industry challenges. Case studies illustrate ERNIE Bot’s role in guiding students through culturally tailored virtual marketing scenarios, emphasizing the importance of cultural adaptation in customer engagement and international sales. The findings suggest that knowledgeenhanced language models not only enrich educational content but also improve students’ |
| first_indexed | 2025-11-15T03:51:59Z |
| format | Article |
| id | ump-43494 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:51:59Z |
| publishDate | 2024 |
| publisher | Akademia Baru |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-434942025-01-07T01:49:04Z http://umpir.ump.edu.my/id/eprint/43494/ Exploring the application of knowledge-enhanced large language models in automotive marketing education: A case study of ERNIE bot Lu, Hong Kun Fei, Song Noor, M. M. Wu, Bingli L Education (General) T Technology (General) TJ Mechanical engineering and machinery With the rapid evolution of intelligent and electric vehicle technologies, the automotive industry faces significant transformation, especially in autonomous driving, connected systems, and global market integration. This shift has heightened the demand for skilled automotive marketing professionals equipped with both practical expertise and cross-cultural competence. This study explores the application of Baidu's ERNIE Bot as a knowledge-enhanced large language model in automotive marketing education. Focusing on its capabilities to innovate teaching content, optimize instructional methods, expand virtual training, and enhance cross-cultural sensitivity, we investigate ERNIE Bot’s effectiveness in preparing students for global industry challenges. Case studies illustrate ERNIE Bot’s role in guiding students through culturally tailored virtual marketing scenarios, emphasizing the importance of cultural adaptation in customer engagement and international sales. The findings suggest that knowledgeenhanced language models not only enrich educational content but also improve students’ Akademia Baru 2024 Article PeerReviewed pdf en cc_by_nc_4 http://umpir.ump.edu.my/id/eprint/43494/1/J%202024%20ARFMT%20LuHK%20M.M.Noor%20Automotive%20Edu%20Case%20Study.pdf Lu, Hong Kun and Fei, Song and Noor, M. M. and Wu, Bingli (2024) Exploring the application of knowledge-enhanced large language models in automotive marketing education: A case study of ERNIE bot. Journal of Advanced Research in Technology and Innovation Management, 13 (1). pp. 1-12. ISSN 2811-4744. (Published) https://doi.org/10.37934/jartim.13.1.112 10.37934/jartim.13.1.112 |
| spellingShingle | L Education (General) T Technology (General) TJ Mechanical engineering and machinery Lu, Hong Kun Fei, Song Noor, M. M. Wu, Bingli Exploring the application of knowledge-enhanced large language models in automotive marketing education: A case study of ERNIE bot |
| title | Exploring the application of knowledge-enhanced large language models in automotive marketing education: A case study of ERNIE bot |
| title_full | Exploring the application of knowledge-enhanced large language models in automotive marketing education: A case study of ERNIE bot |
| title_fullStr | Exploring the application of knowledge-enhanced large language models in automotive marketing education: A case study of ERNIE bot |
| title_full_unstemmed | Exploring the application of knowledge-enhanced large language models in automotive marketing education: A case study of ERNIE bot |
| title_short | Exploring the application of knowledge-enhanced large language models in automotive marketing education: A case study of ERNIE bot |
| title_sort | exploring the application of knowledge-enhanced large language models in automotive marketing education: a case study of ernie bot |
| topic | L Education (General) T Technology (General) TJ Mechanical engineering and machinery |
| url | http://umpir.ump.edu.my/id/eprint/43494/ http://umpir.ump.edu.my/id/eprint/43494/ http://umpir.ump.edu.my/id/eprint/43494/ http://umpir.ump.edu.my/id/eprint/43494/1/J%202024%20ARFMT%20LuHK%20M.M.Noor%20Automotive%20Edu%20Case%20Study.pdf |