“Lucid waters and lush mountains are invaluable assets”. Green marketing and sustainable development have become crucial topics in economic and social development. During 2019–2023, there are nearly 952 publications on green marketing-related topics in the Web of Science core database, and a large number of scholars researched green marketing, but there is still a lack of comprehensive and systematic studies on the current status of green marketing research and hot trends. The main purpose of this study is to summarize and sort out the current status of green marketing research by reviewing the literature related to green marketing (enterprises vs. consumers). Meanwhile, using Cite Space 6.2 R2 software, the core literature of green marketing in the past five years was screened, the data were visualized and analyzed, and a knowledge map of the cooperative authors, institutions, countries, and keywords was drawn in an attempt to discover the research hotspots and major development trends of green marketing. The results show that the publications and citation frequency of green marketing-related literature showed an increasing trend from 2019 to 2023, and the highest citation frequency was reached in 2022. Green marketing literature appears more frequently in the USA, China, and England and has a higher influence. Green management, firm performance, green innovation, green strategy, green capability, sustainable development, green business, green market orientation, green supply chain management, green exploitation, green responsibility, ecosystem, green commitment, green perceptions, green competitive advantage, and corporate social responsibility reflect the hot topics and important themes of green marketing research. This study innovatively combines a green marketing literature review and bibliometric analysis, comprehensively and systematically discusses the current status of green marketing research and hot trends based on both textual and data perspectives, and puts forward the “individual-environment-economy-society” virtuous ecological cycle of green marketing from a macro perspective.

With the rapid increase of market competition pressure, enterprises’ collaborative innovation plays a more prominent role in competitive advantage. This paper aims to explore how the enterprise–science community can achieve sustainable collaborative value co-creation. Taking the Maoduoli Group as a sample, using the single case study method and grounded theory, a structural model of the enterprise–science community collaborative value co-creation mechanism is constructed. The proposed model is based on the value logic of “advocating value—creating value—delivering value—acquiring value”, which explains how the enterprise–scientific community collaborative value co-creation model is formed, how it is implemented, how it is delivered to customers, and the overall process of jointly harvesting value at last. The findings are as follows: First, government support, market demand, and entrepreneurial spirit are the internal and external factors for the enterprise–science community to develop collaborative value co-creation; secondly, the synergy mechanism of the enterprise–science community is to realize mutual activities such as joint research and development, a joint publication of papers, sharing of research results, joint research and development activities, and joint teaching practice through means of capital investment, concept support, and technical support. Third, the synergy mechanism of the enterprise–science community can realize the value of the economic and scientific research and the ecological and social benefits (narrow sense), and continuously feed back to further promote a deeper level of collaborative value co-creation of the enterprise–science community. This paper introduces the dimension of the scientific community, forms a special construct, and focuses on the collaborative value co-creation model of the enterprise–scientific community, which fills the gap in this research direction, and also provides theoretical support and practical guidance for the collaborative value co-creation model of the enterprise–scientific community.

Artificial intelligence (AI) has emerged as a transformative force in the marketing landscape, significantly altering consumer engagement, decision-making processes, and strategic management practices. However, despite the substantial expansion of research on AI in marketing, a comprehensive and systematic understanding of its underlying knowledge structure and the evolution of its thematic domains remains insufficient. Therefore, we synthesize qualitative insights with bibliometric science mapping by applying CiteSpace and latent Dirichlet allocation (LDA) topic modeling to 564 Web of Science Core Collection articles (2019–May 2025). The analysis yields three core findings. First, China and the USA anchor the field’s knowledge production, with the UK, Australia, and India as secondary hubs. Second, LDA reveals five topics: (1) Digitalization Transformation and Marketing Strategy, which explores the impact of digital technologies on reshaping traditional marketing approaches; (2) Consumer Behavior and Experience, focusing on how AI influences consumer decision-making and engagement; (3) Business Value and Innovation Research, examining how AI contributes to business value creation and the development of innovative marketing practices; (4) Machine Learning Algorithms and Technological Applications, addressing the technical foundations and practical implementations of AI in marketing; and (5) Generative AI Content and Applications, highlighting the emerging role of generative AI in content creation and personalization. Third, we develop an integrative value chain framework that explicates how AI permeates and transforms distinct stages of the marketing process, offering a holistic perspective on AI’s role in modern marketing practices. Building on these results, we advance a dual co-evolutionary framework—Consumer–Technology–Market and Technology–Economy–Society—that consolidates dispersed streams, clarifies the field’s intellectual structure. For managers, we map the AI–marketing technology landscape, identify high-yield opportunities in customer experience and service automation, and delineate risks involving data privacy, bias, and ethical guardrails, thereby informing effective and responsible adoption of AI in marketing strategy.