Author(s)

ZhaoXia Xue, Wei Li^*

Affiliation(s)

College of Applied Sciences, Beijing Union University, Beijing 100101, China.

Corresponding Author

Wei Li

ABSTRACT

Against the dual backdrop of China’s “carbon peaking–carbon neutrality” strategy and the accelerating global net-zero transition, green marketing has shifted from a peripheral competitive instrument to a core mechanism for value creation and sustainable transformation. This shift calls for a new type of “green + intelligent” talent in vocational education—graduates who combine ecological literacy with data-driven and AI-enabled marketing capabilities. Drawing on competency-based education (CBE), ecological literacy, and AI-empowered education, this study reviews relevant international and domestic research and policy practices and maps them onto authentic job tasks and situational demands in green marketing roles. We develop a three-tier, five-dimensional competency framework (foundational–intelligent–innovative) and propose an end-to-end development pathway in which AI is embedded across curriculum design, practice-based training, assessment, and employment alignment. The framework comprises five dimensions: (1) green cognition and ecological literacy, (2) industry fundamentals and market adaptability, (3) AI/digital technology application, (4) cross-boundary collaboration and communication, and (5) innovative practice and sustainable development. It positions ecological literacy as the value foundation, AI as the technical engine, and lifelong learning as the growth trajectory, forming a closed loop of “task scenarios–competency progression–assessment feedback.” For implementation, the paper proposes an integrated scheme consisting of curriculum restructuring and interdisciplinary projects, intelligent learning and virtual simulation-based training, industry–education collaboration and job alignment, whole-process intelligent assessment and digital portfolios, and continuous learning with governance optimization. The proposed framework and pathway provide actionable guidance for vocational colleges in curriculum development, training-base construction, industry–education integration, and competency assessment, thereby supporting the supply and quality improvement of green marketing talent for the net-zero transition.

KEYWORDS

Net-zero transition; Green marketing talent; AI empowerment; Competency framework; Talent development pathway

CITE THIS PAPER

ZhaoXia Xue, Wei Li. Cultivating green marketing talent in vocational colleges for the net-zero transition: an AI-enabled competency framework and development pathway. World Journal of Educational Studies. 2026, 4(2): 8-16. DOI: https://doi.org/10.61784/wjes3134.

REFERENCES

[1] Kotler P. Reinventing marketing to manage the environmental imperative. Journal of marketing, 2011, 75(4): 132-135.

[2] Wiek A, Withycombe L, Redman C L. Key competencies in sustainability: a reference framework for academic program development. Sustainability science, 2011, 6(2): 203-218.

[3] Leonidou C N, Katsikeas C S, Morgan N A. “Greening” the marketing mix: Do firms do it and does it pay off?. Journal of the academy of marketing science, 2013, 41(2): 151-170.

[4] Meinrenken C J, Chen D, Esparza R A, et al. The Carbon Catalogue, carbon footprints of 866 commercial products from 8 industry sectors and 5 continents. Scientific Data, 2022, 9(1): 87.

[5] Benzidia S, Makaoui N, Bentahar O. The impact of big data analytics and artificial intelligence on green supply chain process integration and hospital environmental performance. Technological forecasting and social change, 2021, 165: 120557.

[6] Tian T, Zhang Y, Mei Y. Intelligent analysis of precision marketing of green agricultural products based on big data and GIS. Earth science informatics, 2022, 15(3): 1395-1406.

[7] Khan S I, Rahman M S, Ashik A A M, et al. Big Data and Business Intelligence for Supply Chain Sustainability: Risk Mitigation and Green Optimization in the Digital Era. European Journal of Management, Economics and Business, 2024, 1(3): 262-276.

[8] Geissdoerfer M, Savaget P, Bocken N M P, et al. The Circular Economy–A new sustainability paradigm?. Journal of cleaner production, 2017, 143: 757-768.

[9] Klemow K M, Cid C R, Jablonski L M, et al. How a multidimensional ecology education approach can enhance college curricula to implement the United Nations sustainable development goals. Sustainable Earth Reviews, 2024, 7(1): 12.

[10] Ma W, Adesope O O, Nesbit J C, et al. Intelligent tutoring systems and learning outcomes: A meta-analysis. Journal of educational psychology, 2014, 106(4): 901-918.

[11] Kochmar E, Vu D D, Belfer R, et al. Automated data-driven generation of personalized pedagogical interventions in intelligent tutoring systems. International Journal of Artificial Intelligence in Education, 2022, 32(2): 323-349.

[12] Taskin M. Artificial intelligence in personalized education: enhancing learning outcomes through adaptive technologies and data-driven insights. Human Computer Interaction, 2025, 8(1): 173.

[13] Makransky G, Terkildsen T S, Mayer R E. Adding immersive virtual reality to a science lab simulation causes more presence but less learning. Learning and instruction, 2019, 60: 225-236.

[14] Shankar V. How artificial intelligence (AI) is reshaping retailing. Journal of retailing, 2018, 94(4): vi-xi.

[15] Padovano A, Cardamone M. Towards human-AI collaboration in the competency-based curriculum development process: The case of industrial engineering and management education. Computers and Education Artificial Intelligence, 2024, 7.

[16] Papadas K K, Avlonitis G J, Carrigan M. Green marketing orientation: Conceptualization, scale development and validation. Journal of Business Research, 2017, 80: 236-246.

[17] Delmas M A, Burbano V C. The drivers of greenwashing. California management review, 2011, 54(1): 64-87.

[18] Mulder M. Competence-based education and training. The Journal of Agricultural Education and Extension, 2012, 18(3): 305-314.

[19] Campion M A, Fink A A, Ruggeberg B J, et al. Doing competencies well: Best practices in competency modeling. Personnel psychology, 2011, 64(1).

[20] Martinez-Marroquin E, Male S. Micro-credentials for recognition of workplace learning: Provocation. Journal of Teaching and Learning for Graduate Employability, 2021, 12(1): 52-57.

[21] Gamage K A A, Dehideniya S C P. Unlocking Career Potential: How Micro-Credentials Are Revolutionising Higher Education and Lifelong Learning. Education Sciences, 2025, 15(5): 525.

[22] Jobin A, Ienca M, Vayena E. The global landscape of AI ethics guidelines. Nature machine intelligence, 2019, 1(9): 389-399.

[23] Archambault S G, Ramachandran S, Acosta E, et al. Ethical dimensions of algorithmic literacy for college students: Case studies and cross-disciplinary connections. The Journal of Academic Librarianship, 2024, 50(3): 102865.

[24] Sajja R, Sermet Y, Cwiertny D, et al. Integrating AI and learning analytics for data-driven pedagogical decisions and personalized interventions in education. Technology, knowledge and learning, 2025: 1-31.

[25] Ha C, Huang G, Zhang J, et al. Assessing ecological literacy and its application based on linguistic ecology: a case study of Guiyang City, China. Environmental Science and Pollution Research, 2022, 29(13): 18741-18754.

[26] Maurer M, Bogner F X. Modelling environmental literacy with environmental knowledge, values and (reported) behaviour. Studies in Educational Evaluation, 2020, 65: 100863.

[27] Redman A, Wiek A. Competencies for advancing transformations towards sustainability. Frontiers in Education. Frontiers Media SA, 2021, 6: 785163.

[28] Leong W Y. Artificial intelligence, automation, and technical and vocational education and training: Transforming vocational training in digital era. Engineering Proceedings, 2025, 103(1): 9.

[29] Kovalchuk V, Reva S, Volch I, et al. Artificial intelligence as an effective tool for personalized learning in modern education. Environment Technology Resources. Proceedings of the International Scientific and Practical Conference. 2025, 3: 187-194.

[30] Zawacki-Richter O, Marín V I, Bond M, et al. Systematic review of research on artificial intelligence applications in higher education–where are the educators?. International journal of educational technology in higher education, 2019, 16(1): 1-27.

[31] Gligorea I, Cioca M, Oancea R, et al. Adaptive learning using artificial intelligence in e-learning: A literature review. Education Sciences, 2023, 13(12): 1216.

[32] Yoo Y, Cho Y H, Choi J. A systematic review on the competences of human-AI collaboration. 31st International Conference on Computers in Education, ICCE 2023. Asia-Pacific Society for Computers in Education, 2023: 1071-1074.

[33] Zirar A, Ali S I, Islam N. Worker and workplace Artificial Intelligence (AI) coexistence: Emerging themes and research agenda. Technovation, 2023, 124: 102747.