This paper uses a new cross-country cross-industry dataset on investment in tangible and intangible assets for 18 European countries and the US.  We set out a framework for measuring intangible investment and capital stocks and their effect on output, inputs and total factor productivity. The analysis provides evidence on the diffusion of intangible investment across Europe and the US over the years 2000-2013 and offers growth accounting evidence before and after the Great Recession in 2008-2009. Our major findings are the following. First, tangible investment fell massively during the Great Recession and has hardly recovered, whereas intangible investment has been relatively resilient and recovered fast in the US but lagged behind in the EU. Second, the sources of growth analysis including only national account intangibles (software, R&D, mineral exploration and artistic originals), suggest that capital deepening is the main driver of growth, with tangibles and intangibles accounting for 80% and 20% in the EU while both account for 50% in the US, over 2000-2013. Extending the asset boundary to the intangible assets not included in the national accounts (Corrado, Hulten and Sichel (2005)) makes capital deepening increase. The contribution of tangibles is reduced both in the EU and the US (60% and 40% respectively) while intangibles account for a larger share (40% in EU and 60% in the US). Then, our analysis shows that since the Great Recession, the slowdown in labour productivity growth has been driven by a decline in TFP growth with relatively a minor role for tangible and intangible capital. Finally, we document a significant correlation between stricter employment protection rules and less government investment in R&D, and a lower ratio of intangible to tangible investment.

The whole world is in a fuel crisis nearly approaching exhaustion, with climate change knocking at our doorsteps. In the fight against global warming, one of the principle components that demands technocratic attention is Transportation, not just as a significant contributor to atmospheric emissions but from a much broader perspective of environmental sustainability. 

From the traditional technocratic aspect of transport planning, our epiphany comes in the form of Land Use integrated sustainable transport policy in which Singapore has been a pioneer, and has led the way for both developed and developing nations in terms of mobility management. We intend to investigate Singapore’s Transport policy timeline delving into the past, present and future, with a case by case analysis for varying dimensions in the present scenario through selective benchmarking against contemporary cities like Hong Kong, London and New York. The discussions will include themes of modal split, land use policy, vehicular ownership, emission policy, parking policy, safety and road traffic management to name a few. A visualization of Singapore’s future in transportation particularly from the perspective of automated vehicles in conjunction with last mile solutions is also detailed. 

With modern society and the ever-increasing consumption of polymeric materials, the way we look at products has changed, and one of the main questions we have is about the negative impacts caused to the environment in the most diverse stages of the life cycle of these materials, whether in the acquisition of raw materials, in manufacturing, distribution, use or even in their final disposal. The main methodology currently used to assess the environmental impacts of products from their origin to their final disposal is known as Life Cycle Assessment (LCA). Thus, the objective of this work is to evaluate how much the biodegradable polymer contributes to the environment in relation to the conventional polymer considering the application of LCA in the production mode. This analysis is configured through the Systematic Literature Review (SLR) method. In this review, 28 studies were selected for evaluation, whose approaches encompass knowledge on LCA, green biopolymer (from a renewable but non-biodegradable source), conventional polymer (from a non-renewable source) and, mainly, the benefits of using biodegradable polymers produced from renewable sources, such as: corn, sugarcane, cellulose, chitin and others. Based on the surveys, a comparative analysis of LCA applications was made, whose studies considered evaluating quantitative results in the application of LCA, in biodegradable and conventional polymers. The results, based on comparisons between extraction and production of biodegradable polymers in relation to conventional polymers, indicate greater environmental benefits related to the use of biodegradable polymers.

Given the increasing demand for sustainable energy sources and the challenges associated with the limited efficiency of solar cells, this review focuses on the application of gold quantum dots (AuQDs) in enhancing solar cell performance. Gold quantum dots, with their unique properties such as the ability to absorb ultraviolet light and convert it into visible light expand the utilization of the solar spectrum in solar cells. Additionally, these quantum dots, through plasmonic effects and the enhancement of localized electric fields, improve light absorption, charge carrier generation (electrons and holes), and their transfer. This study investigates the integration of quantum dots with gold plasmonic nanoparticles into the structure of solar cells. Experimental results demonstrate that using green quantum dots and gold plasmonic nanoparticles as intermediate layers leads to an increase in power conversion efficiency. This improvement highlights the significant impact of this technology on solar cell performance. Furthermore, the reduction in charge transfer resistance and the increase in short-circuit current are additional advantages of utilizing this technology. The findings of this research emphasize the high potential of gold quantum dots in advancing next-generation solar cell technology.

The use of geotechnologies combined with remote sensing has become increasingly essential and important for efficiently and economically understanding land use and land cover in specific regions. The objective of this study was to observe changes in agricultural activities, particularly agriculture/livestock farming, in the North Forest Zone of Pernambuco (Mata Norte), a political-administrative region where sugarcane cultivation has historically been the backbone of the local economy. The region’s sugarcane biomass also contributes to land use and land cover observations through remote sensing techniques applied to digital satellite images, such as those from Landsat-8, which was used in this study. This study was conducted through digital image processing, allowing the calculation of the Normalized Difference Vegetation Index (NDVI), the Soil-Adjusted Vegetation Index (SAVI), and the Leaf Area Index (LAI) to assess vegetation cover dynamics. The results revealed that sugarcane cultivation is the predominant agricultural and vegetation activity in Mata Norte. Livestock farming areas experienced a significant reduction over the observed decade, which, in turn, led to an increase in agricultural and forested areas. The most dynamic spatiotemporal behavior was observed in the expansion and reduction of livestock areas, a more significant change compared to sugarcane areas. Therefore, land use and land cover in this region are more closely tied to sugarcane cultivation than any other agricultural activity.

Artificial intelligence chatbots can be used to conduct research effectively and efficiently in the fifth industrial revolution. Artificial intelligence chatbots are software applications that utilize artificial intelligence technologies to assist researchers in various aspects of the research process. These chatbots are specifically designed to understand researchers’ inquiries, provide relevant information, and perform tasks related to data collection, analysis, literature review, collaboration, and more. The purpose of this study is to investigate the use of artificial intelligence chatbots for conducting research in the fifth industrial revolution. This qualitative study adopts content analysis as its research methodology, which is grounded in literature review incorporating insights from the researchers’ experiences with utilizing artificial intelligence. The findings reveal that researchers can use artificial intelligence chatbots to produce quality research. Researchers are exposed to various types of artificial intelligence chatbots that can be used to conduct research. Examples are information chatbots, question and answer chatbots, survey chatbots, conversational agents, peer review chatbots, personalised learning chatbots and language translation chatbots. Artificial intelligence chatbots can be used to perform functions such as literature review, data collection, writing assistance and peer review assistance. However, artificial intelligence chatbots can be biased, lack data privacy and security, limited in creativity and critical thinking. Researchers must be transparent and take in consideration issues of informed content and data privacy and security when using artificial intelligence chatbots. The study recommends a framework on artificial intelligence chatbots researchers can use to conduct research in the fifth industrial revolution.