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This systematic literature review aims to investigate the application and integration of Industry 4.0 (I4.0) technologies in transportation infrastructure construction projects focusing on sustainability pillars.

The study employs a systematic literature review approach, combining qualitative review and quantitative analysis of 142 academic articles published between 2011 and March 2023.

The findings reveal the dominance of Building Information Modelling (BIM) as a central tool for sustainability assessment, while other technologies such as blockchain and autonomous robotics have received limited attention. The adoption of I4.0 technologies, including Internet of Things (IoT) sensors, Augmented Reality (AR), and Big Data, has been prevalent for data-driven analyses, while Unmanned Aerial Vehicle (UAVs) and 3D printing are mainly being integrated either with BIM or in synergy with Artificial Intelligence (AI). We pinpoint critical challenges including high adoption costs, technical barriers, lack of interoperability, and the absence of standardized sustainability benchmarks.

This research distinguishes itself by not only mapping the current integration of I4.0 technologies but also by advocating for standardization and a synergistic human-technology collaborative approach. It offers tailored strategic pathways for diverse types of transportation infrastructure and different project phases, aiming to significantly enhance operational efficiency and sustainability. The study sets a new agenda for leveraging cutting-edge technologies to meet ambitious future sustainability and efficiency goals, making a compelling case for rethinking how these technologies are applied in the construction sector.

This chapter presents an empirical effort for the theoretical applicability of sport diplomacy to sport for development (SFD) research by examining how sport played a role in pursuing South Korea's development at given four historical stages: (1) A prelude to Korean SFD before 1945, (2) sport for a new Korea between 1945 and 1960, (3) sport for developmental state between 1961 and 1979, and (4) sport for coming-out parties of the 1980s. This chapter supports current scholarly attempts to situate the 21st century sport for development (SFD) within the history of sport for social good, as well as approaches integrating the role of sport in the 19th century colonization and/or in the modern version of development during the post-war era. By adding an Asian case (South Korea), this chapter contributes to existing SFD literature mostly focusing on Western countries and their former colonies in Africa and South/Central America. It also contributes to the understanding of soft power's dualistic characteristics that direct domestic and international audiences with a new insight into the sport-development nexus in the history of South Korea.

Rural development programs are widely used policy instruments mitigating rural-urban economic disparities. Yet, little research has examined their effect on rural labor. This study fills this knowledge gap by quantifying the causal impact of such programs on the labor allocation of farm households in Taiwan.

A theoretical framework based on the agricultural household model is constructed to guide the empirical specification. A unique dataset compiles administrative data on the program’s subsidies with farm household surveys across seven years. To cope with endogeneity bias, an instrumental variables model is applied. The eligibility rule for a township to participate in the program is used as the instrument.

We find that the program increases the labor supply of farm household members. These effects are more pronounced for off-farm work, particularly non-heads of farm households. The program’s subsidies supporting culture and promotion-related activities have larger effects. Finally, females benefited more from the program.

We focus on farm households since this group is the target of place-based rural development programs. In addition, we identify the causal impact of place-based development programs on rural labor. Finally, this study is relevant to the literature on intra-household models by demonstrating that place-based rural development programs can affect the labor supply of farm household members.

The Chinese housing market has witnessed rapid growth during the past decade and the significance of housing price forecasting has undoubtedly elevated, becoming an important issue to investors and policymakers. This study aims to examine neural networks (NNs) for office property price index forecasting from 10 major Chinese cities for July 2005–April 2021.

The authors aim at building simple and accurate NNs to contribute to pure technical forecasts of the Chinese office property market. To facilitate the analysis, the authors explore different model settings over algorithms, delays, hidden neurons and data-spitting ratios.

The authors reach a simple NN with three delays and three hidden neurons, which leads to stable performance of about 1.45% average relative root mean square error across the 10 cities for the training, validation and testing phases.

The results could be used on a standalone basis or combined with fundamental forecasts to form perspectives of office property price trends and conduct policy analysis.

With the global economic slowdown in 2023, most universities in the central and western regions of China may face the problem of shortage of government financial funding, which is directly related to the development of science and technology of the universities. With the support of the local government, most of the ordinary universities have shifted attention to the transfer and transformation of intellectual property based on school-enterprise cooperation, hoping to seek more commercialization income as an extra source of income. Therefore, this paper aimed to study the current situation of university intellectual property, i.e. the reserve and distribution of transferable patents, discipline distribution of patents, and regional cooperation of university patents.

A patent database of 10 key universities in Henan Province of China from 2012 to 2021 was established. The evaluation indicator model by the Entropy method was conducted to reveal the interaction mechanism between quantity indicators, quality indicators, and value indicators. Based on the data analysis, the development direction of the discipline construction and school-enterprise cooperation for local universities was clear.

The findings indicated that the number of patent applications from ten key universities in Henan Province has been increasing rapidly over the years. The trend for authorized invention patents has remained relatively stable. Compared with the patent applications and authorizations, the growth of transferable patents was notably slow. The significance of strategic layout of dominant disciplines and related high-value patents was not appreciated enough by Chinese government and universities. There was a large difference of dominant disciplines between 10 key universities, and the patent level of each university was directly proportional to the number of dominant disciplines. The university patent level heavily relied on the researchers' contributions and the distribution mechanism of scientific research resources within the university. Guangdong Province and the Yangtze River Delta of China, being economically developed regions, exhibited the most active engagement in patent technology cooperation. Conversely, the central and western regions displayed relatively lower participation in high-value patent research and development.

This study can provide a unique perspective to understand and solve the financial bottleneck problem of ordinary universities in the central and western regions of China. The discipline construction and school-enterprise cooperation are just one of the existing schemes, but it still cannot solve the financial problems faced by local universities in China towards the government.

The findings of this study can serve as a foundation for further investigation into policies aimed at improving the financial problems of ordinary universities in the central and western regions of China.

As an important attempt, the study tried to focus the financial problem of universities in the central and western regions of China based on the evaluation of the current situation of university intellectual property. This research findings are of great value in finding optimal layout between university patents, disciplines and school-enterprise cooperation.

Urban green spaces support people to approach active, healthy ageing, especially in high-density cities where they compensate for limited private living spaces. This research paper aims to examine how urban green spaces support active, healthy ageing by exploring correlations between behaviour, physical setting and gender difference among older people in a highly populated urban context.

Urban parks in older neighbourhoods of Macau were selected for data collection. Photographic documentation was used to collect data, with 1,201 older people photographed identified as valid samples. Each was coded according to labels of behaviour, physical setting and gender. Chi-squared tests were conducted to assess correlations between behaviours and features of physical settings, and differences between genders in behaviours and physical settings. Logistic regression analysis was conducted to further examine associations between older people's behaviours and features of physical settings by gender.

The research reveals types and frequency of behaviours displayed, preferred environmental features for different behaviours and gender differences in behaviours and preferred environmental features. Design principles targeting active, healthy ageing should consider particular amenities and street furniture, the arrangement of trees and landscapes and the integration of open and secluded places.

Previous studies address older people's behaviour from the perspective of either environmental influence or gender difference, but there have been few studies on gendered behavioural differences among older people in urban green spaces. Analysing the behaviour–physical setting–gender relationship provides more evidence in the field of built environment studies.

The Chinese housing market has gone through rapid growth during the past decade, and house price forecasting has evolved to be a significant issue that draws enormous attention from investors, policy makers and researchers. This study investigates neural networks for composite property price index forecasting from ten major Chinese cities for the period of July 2005–April 2021.

The goal is to build simple and accurate neural network models that contribute to pure technical forecasts of composite property prices. To facilitate the analysis, the authors consider different model settings across algorithms, delays, hidden neurons and data spitting ratios.

The authors arrive at a pretty simple neural network with six delays and three hidden neurons, which generates rather stable performance of average relative root mean square errors across the ten cities below 1% for the training, validation and testing phases.

Results here could be utilized on a standalone basis or combined with fundamental forecasts to help form perspectives of composite property price trends and conduct policy analysis.

This paper aims to investigate whether the establishment of commodity futures can effectively hedge systemic risk in the spot network, given the context of financialization in the commodity futures market.

Utilizing industry association data from the Chinese commodity market, the authors identify systemically important commodities based on their importance in the production process using multiple graph analysis methods. Then the authors analyze the effect of listing futures on the systemic risk in the spot market with the staggered difference-in-differences (DID) method.

The findings suggest that futures contracts help reduce systemic risks in the underlying spot network. Systemic risk for a commodity will decrease by approximately 5.7% with the introduction of each corresponding futures contract, since the hedging function of futures reduces the timing behavior of firms in the spot market. Establishing futures contracts for upstream commodities lowers systemic risks for downstream commodities. Energy commodities, such as crude oil and coal, have higher systemic importance, with the energy sector dominating systemic importance, while some chemical commodities also have considerable systemic importance. Meanwhile, the shortest transmission path for risk propagation is composed of the energy industry, chemical industry, agriculture/metal industry and final products.

The paper provides the following policy insights: (1) The role of futures contracts is still positive, and future contracts should be established upstream and at more systemically important nodes in the spot production chain. (2) More attention should be paid to the chemical industry chain, as some chemical commodities are systemically important but do not have corresponding futures contracts. (3) The risk source of the commodity spot market network is the energy industry, and therefore, energy-related commodities should continue to be closely monitored.

This study examines network coopetition strategies to promote the spatial distribution of tourists and their importance for Destination Management Organisations (DMOs). Geotagged photos from the municipality of Porto, Portugal (n = 152,312) uploaded to the Flickr social network between 2010 and 2022 were utilised, and thematic maps were produced using geographic information systems (GISs). Residents and visitors were identified and separated, employing a heuristic approach with a five-day threshold between the first and last photo of each user. The findings indicate an uneven distribution of tourists within the destination, with a notable concentration of accommodation, attractions and visitors in the historic centre. The establishment of a coopetition network could contribute to the dispersion of activity.

Based on the conservation of resource (COR) theory, this study explores employees’ learning agility (ELA) as an antecedent of knowledge sharing behaviour, specifically in the supply chain environment. However, such discretionary behaviour can be negatively affected by the prevalence of psychological contract breaches. According to COR theory, employees' resources (knowledge, ability and skills) act as motivational factors that employees strive to protect, retain and at the same time invest in favour of obtaining more resources. On the other hand, when resource loss weighs more than resource gain, an individual agitated with resource depletion will minimise resource loss by decreasing their effort for future displays of resources. A random sample of 418 participants from the public sector in the Fiji Islands yielded a sample of 418 participants. The proposed model was analysed through structural equation modeling (SEM) to determine its fit. The analysis supports the proposed theoretical framework, providing a new dimension for ELA as an unexplored phenomenon for knowledge sharing behaviour (KSB) in the supply chain. The study specifically draws the attention of policymakers on industry, innovation and infrastructure (SDG09), where immediate actions are needed to create resilient supply chain management through ELA. Research shows that agile employees can easily adapt to unexpected changes, actively participate in discussions and quickly contribute to innovative and creative solutions. KSB can be further developed through a culture of learning and sharing, rewards for KSB, psychological support and upholding its promised obligations through regular communication, establishing a more resilient supply chain management.