In the process of global economy, in the face of increasing business competition, it is more difficult than ever for brands to approach consumers and persuade them to consume. In the commercial environment, the competition between enterprises is essentially the competition of brands, and the competition of brands must first carry out the competition of brand image. Brand image carries the mission of information dissemination and value creation and plays an important role in business behavior. How to improve customer purchase intention by optimizing brand image and greatly promote the development of business through brand image is the purpose of this study. The construction and application of brand image not only covers all the characteristics of the brand, but also the focus of consumers’ attention when choosing brands and products. This paper comprehensively uses the systematic theories and methods of art design, marketing and consumer psychology and behavior as support, and adopts research methods such as literature data to explore and study the field of brand image. This study finds that customer perception of brand image directly affects customer purchase intention. At present, there are relatively few researches on how brand image can empower business. Through the study of “optimizing brand image to improve customer purchase intention”, this paper focuses on the direction of brand image empowering business, broadens the research breadth and depth in the field of brand image, and enrichis the research achievements in the field of brand image.

Business model innovation (BMI) has garnered substantial academic and corporate attention in recent decades. Researchers have not yet agreed on the most complicated BMI practices in the high-tech startups (HTS). Despite being the second-biggest economy in the world today, China has done little research on the practice of business model innovation in China’s high-tech startups. This study addresses the factors that impact the business model innovation of high-tech startups in China. Our study aims to fill the research gap by visualising and analysing, using systematic literature review (SLR) analyses and reviewing 36 in-depth articles, from 688 academic literature sources. Relevant publications from Scopus, Springer, ScienceDirect, Web of Science, IEEE Xplore, and the JDM e-library expose the current research status from 2013 to December 2023 without bias. We conducted a literature-based investigation to identify essential insights on the BMI factors in the literature and derived a high-tech startup’s BMI critical factor. Our study shows that three main factors affect the innovation of business models in high-tech startups in China. The findings raise managers’, entrepreneurs’, and executives’ knowledge of corporate resource bricolage and cognitive style constraints in business model innovation and their pros and cons. The findings will help Chinese academics understand enterprises’ institutional environment and resource bricolage as final suggestions and proposals for corporates, regulators, and policymakers are presented.

Rapid urban expansion gives rise to smart cities which pose immense logistical and supply chain challenges. The COVID-19 pandemic transformed the holistic system identified by Zhao et al. in 2021. The system encompasses logistics and supply chain integral to the concept of smart cities, with a focus on sustainability. This transformation requires an in-depth study on challenges of a common framework of policies for smart cities in countries comprising the Organisation for Economic Cooperation and Development (OECD). The study employs an extensive literature analysis for the period 2020–2022. an approach which contextualizes the model. The model identifies the causes, impact, and spillovers of new trends in logistics and supply, including the sustainability of adopted technologies. The study includes the variables involved, and barriers to creating a shared model. The results reveal that the two elements affecting the supply chain and transport in smart cities are Industry 4.0 and 5.0 technologies supporting specific sectors. The resilience of small and medium-sized enterprises positively impacts the sustainability of large urban centres. The study presents both factors that help and hinder the adoption of environmental, social, and economic sustainability technologies.

The economy, unemployment, and job creation of South Africa heavily depend on the growth of the agricultural sector. With a growing population of 60 million, there are approximately 4 million small-scale farmers (SSF) number, and about 36,000 commercial farmers which serve South Africa. The agricultural sector in South Africa faces challenges such as climate change, lack of access to infrastructure and training, high labour costs, limited access to modern technology, and resource constraints. Precision agriculture (PA) using AI can address many of these issues for small-scale farmers by improving access to technology, reducing production costs, enhancing skills and training, improving data management, and providing better irrigation infrastructure and transport access. However, there is a dearth of research on the application of precision agriculture using artificial intelligence (AI) by small scale farmers (SSF) in South Africa and Africa at large. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) and Bibliometric analysis guidelines were used to investigate the adoption of precision agriculture and its socio-economic implications for small-scale farmers in South Africa or the systematic literature review (SLR) compared various challenges and the use of PA and AI for small-scale farmers. The incorporation of AI-driven PA offers a significant increase in productivity and efficiency. Through a detailed systematic review of existing literature from inception to date, this study examines 182 articles synthesized from two major databases (Scopus and Web of Science). The systematic review was conducted using the machine learning tool R Studio. The study analyzed the literature review articled identified, challenges, and potential societal impact of AI-driven precision agriculture.

With the economic development and the carbon emissions cluster rise, this study uses CiteSpace, VOSviewer, and R-based Bibliometrix software to visualize and analyze the relevant literature on carbon emissions retrieved from the Web of Science database from 2014 to 2023. Through the analysis of the trend of publication volume, author co-citation analysis, institutional co-citation analysis, country co-citation analysis, literature co-citation analysis, thematic analysis of research, research evolution, and other related contents, it reveals the main academic forces, hot research areas, thematic focus changes and cutting-edge trends of international carbon emission research. The results of the study found that the themes of international carbon emissions research focus on carbon emissions, the drivers of carbon neutrality, and the impacts of climate change. An in-depth study of these aspects can help formulate more effective climate policies and emission reduction strategies to achieve global carbon neutrality and combat climate change.