PurposeLivestreaming, as a relatively new online marketing model, has generated numerous business opportunities for e-commerce and social commerce. The purpose of this paper is to investigate to what degree livestreaming content impacts online users' cognitive and emotional reactions and whether their cognitive and emotional responses affect their purchase intention.Design/methodology/approachThrough the lens of regulatory focus theory (RFT) and stimulus–organism–response (S–O–R) theory, the authors empirically examine the influencing mechanisms of livestreaming on online consumers' purchase intentions. Structural equation models are used to analyze the relationships in the proposed research model.FindingsThe results of this study show that information-task fit positively affects consumers' perceived usefulness of livestreaming. Both visual effects and sociability positively affect consumers' perceived value and social presence. Furthermore, perceived usefulness and perceived joy positively affect consumers' purchase intentions in a livestreaming environment. This study’s results also demonstrate that the regulatory focus of consumers has a moderating effect on the influence of their perceived joy on shopping intentions.Originality/valueThis study contributes to the relevant literature by simultaneously examining the role of e-commerce platform characteristics and online consumer psychology in influencing behavioral intention. With a better understanding of their role, platform operators and sellers can refine their livestreaming marketing tools and strategies. Highlighting the interplays among external stimuli, user reactions and user motivational styles, this study contributes to mobile e-commerce literature and the broader literature on digital marketing and human–computer interaction.

PurposeA smart city is a potential solution to the problems caused by the unprecedented speed of urbanization. However, the increasing availability of big data is a challenge for transforming a city into a smart one. Conventional statistics and econometric methods may not work well with big data. One promising direction is to leverage advanced machine learning tools in analyzing big data about cities. In this paper, the authors propose a model to learn region embedding. The learned embedding can be used for more accurate prediction by representing discrete variables as continuous vectors that encode the meaning of a region.Design/methodology/approachThe authors use the random walk and skip-gram methods to learn embedding and update the preliminary embedding generated by graph convolutional network (GCN). The authors apply this model to a real-world dataset from Manhattan, New York, and use the learned embedding for crime event prediction.FindingsThis study’s results show that the proposed model can learn multi-dimensional city data more accurately. Thus, it facilitates cities to transform themselves into smarter ones that are more sustainable and efficient.Originality/valueThe authors propose an embedding model that can learn multi-dimensional city data for improving predictive analytics and urban operations. This model can learn more dimensions of city data, reduce the amount of computation and leverage distributed computing for smart city development and transformation.

PurposeThe space industry has experienced rapid development over the last few years. Activities such as building things in space, learning about our Earth and exploring outer space are satisfying people's fantasies and achieving humanity's ambitions. Such activities have also generated many issues that belong to several information systems (IS) research domains. In this article, the authors discuss the challenges and opportunities associated with the space economy.Design/methodology/approachThe authors discuss why the emerging space economy opens a new frontier of e-commerce and data analytics. Linking three important IS research areas (i.e. digital commerce, data analytics and information security) to the space economy, this study motivates scholars to pay close attention to this promising new frontier for IS research.FindingsThe authors identify new research opportunities within several IS research contexts (digital commerce, data analytics and information security). The authors highlight the potential for opening a robust, interdisciplinary field in the IS domain that could provide valuable insights for practitioners and academics.Originality/valueBecause of the unique characteristics of the space economy, this article presents some promising avenues, research opportunities and implications for several IS fields (digital commerce, data analytics, decision science, information sharing and information security and new business models). Indeed, many opportunities are interdisciplinary in scope, with overlaps occurring between IS and other disciplines.