By reviewing US state-level panel data on infrastructure spending and on per capita income inequality from 1950 to 2010, this paper sets out to test whether an empirical link exists between infrastructure and inequality. Panel regressions with fixed effects show that an increase in the growth rate of spending on highways and higher education in a given decade correlates negatively with Gini indices at the end of the decade, thus suggesting a causal effect from growth in infrastructure spending to a reduction in inequality through better access to education and opportunities for employment. More significantly, this relationship is more pronounced with inequality at the bottom 40 percent of the income distribution. In addition, infrastructure expenditures on highways are shown to be more effective at reducing inequality. By carrying out a counterfactual experiment, the results show that those US states with a significantly higher bottom Gini coefficient in 2010 had underinvested in infrastructure during the previous decade. From a policy-making perspective, new innovations in finance for infrastructure investments are developed, for the US, other industrially advanced countries and also for developing economies.

To achieve the electrification of private vehicles, it is urgent to develop public charging infrastructure. However, choosing the most beneficial type of public charging infrastructure for the development of a country or region remains challenging. The municipal decision’s implementation requires considering various perspectives. An important aspect of energy development involves effectively integrating and evaluating public charging infrastructure. While car charging facilities have been thoroughly studied, motorcycle charging facilities have been neglected despite motorcycles being a vital mode of transportation in many countries. The study created a hybrid decision-making model to evaluate electric motorcycle charging infrastructure. Firstly, a framework for evaluating electric motorcycle charging infrastructure was effectively constructed through a literature survey and expert experience. Secondly, decision-makers’ opinions were gathered and integrated using Bayesian BWM to reach a group consensus. Thirdly, the performance of the alternative solutions was evaluated by exploring the gaps between them and the aspiration level through modified VIKOR. An empirical analysis was conducted using examples of regions/countries with very high rates of motorcycle ownership worldwide. Finally, comparative and sensitivity analyses were conducted to demonstrate the practicality of the proposed model. The study’s findings will aid in addressing municipal issues and achieving low-carbon development objectives in the area.

The rapid shift to online learning during COVID-19 posed challenges for students. This investigation explored these hurdles and suggested effective solutions using mixed methods. By combining a literature review, interviews, surveys, and the analytic hierarchy process (AHP), the study identified five key challenges: lack of practical experience, disruptions in learning environments, condensed assessments, technology and financial constraints, and health and mental well-being concerns. Notably, it found differences in priorities among students across academic years. Freshmen struggled with the absence of hands-on courses, sophomores with workload demands, and upperclassmen with mental health challenges. The research also discussed preferred strategies for resolution, emphasizing independent learning methods, managing distractions, and adjusting assessments. By providing tailored insights, this study aimed to enhance online learning. Governments and universities should support practical work, prioritize student well-being, improve digital infrastructure, adapt assessments, foster innovation, and ensure resilience.

This research examines the influence of virtual community platform attributes on luxury consumers’ purchase intentions, with a specific focus on the role of policy innovation in digital infrastructure. The study aims to 1) identify key factors affecting purchase intentions toward luxury products in virtual environments; 2) develop and validate a structural equation model to analyze these intentions; and 3) provide actionable insights for luxury goods marketers to refine their strategies within these platforms. Utilizing a structural equation model, the study investigates the interactions among various determinants of consumer behavior in virtual communities, highlighting the impact of policy innovation. Data was collected through purposive sampling from 1142 respondents in China’s top 10 high-spending cities on luxury goods, ensuring data relevance. The findings emphasize the significance of knowledge sharing, interactive communication, and leaders’ opinions in virtual communities in building consumer trust and shaping perceptions of online reviews. These elements influence purchase intentions directly and indirectly, with consumer trust serving as a crucial mediator. The study reveals the substantial impact of virtual community attributes on fostering consumer trust and shaping buying decisions for luxury items, underlining the contribution of social development processes. Moreover, the role of policy innovation is found to be significant in enhancing these virtual community dynamics, suggesting that regulatory changes can positively influence consumer engagement and trust. The conclusions offer valuable implications for marketers, proposing strategies to boost consumer engagement and drive sales in virtual settings. This research contributes to the theoretical understanding of digital consumer behavior and provides practical strategies for innovation and growth within the luxury goods sector, emphasizing the critical role of policy innovation in shaping these dynamics.

Against the backdrop of anti-globalization rhetoric, this paper summarizes our joint book entitled Going Beyond Aid (Lin and Wang, 2017a) and discusses the prospects for development finance in the broad context of Belt and Road Initiative (BRI). Based on the New Structural Economics (Lin, 2010; 2011), here we focus on China’s demonstrated comparative advantages in infrastructure, e.g. in hydropower and high-speed railways (HSR). In addition, long-term orientation (LTO) and patient capital are latent comparative advantages that many Asian economies possess, and are critical for the Belt and Road Initiative. Only if these comparative advantages are utilized can these economies cooperate to potentially achieve win-win.

This paper investigates the transformative role of Artificial Intelligence (AI) in enhancing infrastructure governance and economic outcomes. Through a bibliometric analysis spanning more than two decades of research from 2000 to 2024, the study examines global trends in AI applications within infrastructure projects. The analysis reveals significant research themes across diverse sectors, including urban development, healthcare, and environmental management, highlighting the broad relevance of AI technologies. In urban development, the integration of AI and Internet of Things (IoT) technologies is advancing smart city initiatives by improving infrastructure systems through enhanced data-driven decision-making. In healthcare, AI is revolutionizing patient care, improving diagnostic accuracy, and optimizing treatment strategies. Environmental management is benefiting from AI’s potential to monitor and conserve natural resources, contributing to sustainability and crisis management efforts. The study also explores the synergy between AI and blockchain technology, emphasizing its role in ensuring data security, transparency, and efficiency in various applications. The findings underscore the importance of a multidisciplinary approach in AI research and implementation, advocating for ethical considerations and strong governance frameworks to harness AI’s full potential responsibly.