Today’s cities face numerous challenges due to climate change and urbanization. The concept of a smart city aims to help cities to address these challenges by adapting modern information and communication technology. Smart mobility and transportation form one important aspect of smart cities. Inefficient mobility in cities can lead to problems such as traffic congestion, which results in frustration for residents and a decrease in the quality of life. Against the backdrop of global warming, cities also strive to reduce CO₂ emissions, an attempt which requires sustainable and novel mobility concepts. Blockchain is a current technology, said to have huge potential, that is being investigated for application in many facets of smart cities. In the context of smart mobility, blockchain can be used for transactions relating to ridesharing and electric charging, handling of interactions of platoon members, or serving as a foundation for communication between vehicles. Although initial research about this topic exists, it is distributed among different use-cases and applications. This article conducts a systematic literature review to analyze blockchain’s role in mobility and transportation in smart cities, and its potential to increase efficiency in these areas. With this review, we aim to consolidate and summarize the current knowledge about this topic. As a first result, we present the findings from our literature review, which can be divided into five categories of use-cases. We also present a platform for further research about this emerging topic by identifying promising future research avenues. For this purpose, we derive a future research agenda based on our findings.

After cardiovascular diseases, cancer is responsible for the most deaths worldwide. Detecting a cancer disease early improves the chances for healing significantly. One group of technologies that is increasingly applied for detecting cancer is artificial intelligence. Artificial intelligence has great potential to support clinicians and medical practitioners as it allows for the early detection of carcinomas. During recent years, research on artificial intelligence for cancer detection grew a lot. Within this article, we conducted a bibliometric study of the existing research dealing with the application of artificial intelligence in cancer detection. We analyzed 6450 articles on that topic that were published between 1986 and 2022. By doing so, we were able to give an overview of this research field, including its key topics, relevant outlets, institutions, and articles. Based on our findings, we developed a future research agenda that can help to advance research on artificial intelligence for cancer detection. In summary, our study is intended to serve as a platform and foundation for researchers that are interested in the potential of artificial intelligence for detecting cancer.

Drug discovery is usually a rule-based process that is carefully carried out by pharmacists. However, a new trend is emerging in research and practice where artificial intelligence is being used for drug discovery to increase efficiency or to develop new drugs for previously untreatable diseases. Nevertheless, so far, no study takes a holistic view of AI-based drug discovery research. Given the importance and potential of AI for drug discovery, this lack of research is surprising. This study aimed to close this research gap by conducting a bibliometric analysis to identify all relevant studies and to analyze interrelationships among algorithms, institutions, countries, and funding sponsors. For this purpose, a sample of 3884 articles was examined bibliometrically, including studies from 1991 to 2022. We utilized various qualitative and quantitative methods, such as performance analysis, science mapping, and thematic analysis. Based on these findings, we furthermore developed a research agenda that aims to serve as a foundation for future researchers.

Urbanization is a global trend that continues to grow, leading to an increasing number of people to live in cities. This rapid expansion creates challenges such as traffic congestion, environmental pollution, and the need to ensure high living standards for all residents. To address these challenges, many cities adopt digital technologies to become smarter, more efficient, and more sustainable. Among these technologies, artificial intelligence (AI) has gained significant attention in recent years due to its transformative potential. In the context of smart cities, AI offers innovative solutions across various domains, including mobility, waste management, and energy optimization. Due to its multidisciplinary nature and rapid advancements, research on AI in smart cities has grown significantly. A comprehensive approach is needed to understand its role in urban transformation and identify key research gaps. This paper aims to synthesize existing knowledge on AI in smart cities, providing valuable insights for both researchers and practitioners. We define the scope of AI-related research by analyzing scientific literature and offer three main contributions. First, we provide a holistic overview of the field by conducting a bibliometric analysis to map the status and structure of existing knowledge. Second, we identify major research themes through co-citation clustering. Third, we outline a future research agenda by analyzing the most recent and influential journal articles. Our findings have both theoretical and practical implications for a wide range of disciplines, including computer science, energy, transportation, and security. Furthermore, our results can facilitate collaboration by identifying leading researchers and institutions, highlight critical research gaps, and foster discussions on the benefits and challenges of AI-driven smart city solutions.

Recent cases, such as Wirecard, Luckin Coffee, and Steinhoff, highlight the vulnerability of current accounting practices and question their suitability to prevent criminal behavior. Triple-entry accounting (TEA) is a possible answer against accounting fraud and financial manipulation that is increasingly discussed in research and practice. By being based on blockchain technology, TEA is tamper-proof and, thus, might be an effective instrument against manipulation in accounting. However, despite the potential of TEA, research on this topic is scattered and mostly isolated from each other. By conducting a systematic literature review, we synthesize and summarize current research on blockchain-based TEA. Hereby, we find that current research is almost entirely theoretical. Up to now, real-world implementations and their evaluation are still missing in both research and practice. To address these gaps, we develop guiding research questions for interested scholars to pave the way for TEA’s practical use. JEL Classifications: M40; M41.

Blockchain is a disruptive technology that is applied in many different areas (Atici, 2022). Non-fungible tokens (NFTs) are becoming increasingly popular and are already widely used in practice. New use cases for NFTs are emerging all the time. Due to the fact that they are unique, NFTs can prevent counterfeiting, as each token contains the digital signature of the owner (Rehman, Zainab, Imran, & Bawany, 2021). For the use of NFTs to advance in the institutional setting, the opportunities for using NFTs need to be clearly explored. Based on a systematic literature review (SLR), this paper describes and lists the most discussed use cases for NFTs in the scientific literature. The most discussed use cases are art and collectibles, video games, and applications in the metaverse. Another contribution of this article is a future research agenda that contains open questions in the field of NFTs. It aims to provide researchers with promising research avenues to stimulate future research. The results show that there are still challenges in the field of NFT that need to be further explored. In summary, our article aims to equip both researchers and practitioners with an initial overview and knowledge about NFTs, including their applications and challenges.