“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.

The continuous development of the times and the application of artificial intelligence technology are more mature and common; as a new concept and way of thinking artificial intelligence technology plays an important role in brand marketing, brand marketing artificial intelligence era has truly arrived. Based on such a background, it is necessary to explore the value of artificial intelligence in brand marketing management and specific implementation strategies. With the help of artificial intelligence technology, we can realize the accurate capture of consumer demand, the accurate portrayal of consumer groups, and the high quality of brand marketing. The essence of strategic brand management is a brand management system based on brand value. With the help of the brand management system, all the company’s contents are integrated and used to guide all the company’s business actions. At the same time, the company’s brand plan and framework are properly adjusted to constantly improve the brand’s own value and promote the sustainable development of the brand and the company. In this paper, we briefly explain and analyze several brand marketing management modes and management countermeasures commonly used by modern enterprises and discuss the problems and optimization countermeasures in modern enterprise brand marketing management, hoping to enlighten the enhancement of enterprise brand marketing promotion effect and promote the sustainable development of enterprises.

With the increasing popularity of a large number of Internet-based services and a large number of services hosted on cloud platforms, a more powerful back-end storage system is needed to support these services. At present, it is very difficult or impossible to implement a distributed storage to meet all the above assumptions. Therefore, the focus of research is to limit different characteristics to design different distributed storage solutions to meet different usage scenarios. Economic big data should have the basic requirements of high storage efficiency and fast retrieval speed. The large number of small files and the diversity of file types make the storage and retrieval of economic big data face severe challenges. This paper is oriented to the application requirements of cross-modal analysis of economic big data. According to the source and characteristics of economic big data, the data types are analyzed and the database storage architecture and data storage structure of economic big data are designed. Taking into account the spatial, temporal, and semantic characteristics of economic big data, this paper proposes a unified coding method based on the spatiotemporal data multilevel division strategy combined with Geohash and Hilbert and spatiotemporal semantic constraints. A prototype system was constructed based on Mongo DB, and the performance of the multilevel partition algorithm proposed in this paper was verified by the prototype system based on the realization of data storage management functions. The Wiener distributed memory based on the principle of Wiener filter is used to store the workload of each workload distributed storage window in a distributed manner. For distributed storage workloads, this article adopts specific types of workloads. According to its periodicity, the workload is divided into distributed storage windows of specific duration. At the beginning of each distributed storage window, distributed storage is distributed to the next distributed storage window. Experiments and tests have verified the distributed storage strategy proposed in this article, which proves that the Wiener distributed storage solution can save platform resources and configuration costs while ensuring Service Level Agreement (SLA).