• Energy Research
• 13. Climate action close
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The aim of this study is to simulate the self-organized evolution mechanism of inner innovation of large-scale construction enterprises (LSCE) under different contexts. Based on NK stochastic combinatorial optimization model with two parameters (N, K), this study proposes three modules—ambidexterity, punctuated equilibrium, and automation—to simulate the change behaviors of the inner innovation system. Furthermore, this study analyses the influence of factor correlation on inner innovation performance under discusses nine different combination situations. The research results show that (a) regardless of how the relationship strength changes, fitness increases with an increasing K value; and (b) the comparison of optimization modes show that the punctuated equilibrium mode can guarantee the long- and short-term inner innovation performance LSCE. This study therefore reveals the mutual effects of the factors in the inner innovation system in LSCE and provides an effective model for internal systems analyses in the construction industry and in other sectors.

The manufacturing industry has undergone numerous revolutions over the years, with a unanimous acceptance of the greater benefits of being sustainable. The present industrial wave—Industry 4.0—by using its enabling technologies and principles holds great potential to develop sustainable manufacturing paradigms which require balancing out the three fundamental elements —products, processes, and systems. Yet, numerous stakeholders, including industrial policy and decision makers, remain oblivious of such potential and requirements. Thus, this bibliometric study is aimed at presenting an overview of the broad field of research on the convergence of sustainable manufacturing and Industry 4.0 under the umbrella of “Sustainable Manufacturing 4.0”, which has yet to be developed. It includes the dissemination of original findings on pathways and practices of Industry 4.0 applied to the development of sustainable manufacturing, contributing a bibliometric structure of the literature on the aforementioned convergence to reveal how Industry 4.0 could be used to shift the manufacturing sector to a more sustainable-based state. An initial research agenda for this emerging area has accordingly been presented, which may pave the way for having a futuristic view on Sustainable Manufacturing 5.0 in the next industrial wave, i.e., Industry 5.0.

3D city models are a useful tool to analyze the solar potential of neighborhoods and cities. These models are built from buildings footprints and elevation measurements. Footprints are widely available, but elevation datasets remain expensive and time-consuming to acquire. Our hypothesis is that the GIS cadastral data can be used to build a 3D model automatically, so that generating complete cities 3D models can be done in a short time with already available data. We propose a method for the automatic construction of 3D models of cities and neighborhoods from 2D cadastral data and study their usefulness for solar analysis by comparing the results with those from a hand-built model. The results show that the accuracy in evaluating solar access on pedestrian areas and solar potential on rooftops with the automatic method is close to that from the hand-built model with slight differences of 3.4% and 2.2%, respectively. On the other hand, time saving with the automatic models is significant. A neighborhood of 400,000 m2 can be built up in 30 min, 50 times faster than by hand, and an entire city of 967 km2 can be built in 8.5 h.

Sustainable nitrogen (N) management in agriculture is one of the most important issues affecting the environmental performance of modern agriculture. It is actually well perceived that coordinated efforts and holistic approaches are required to regulate N use by farmers. The purpose of this study was to provide an initial examination of stakeholders’ views in Japan regarding N use in agriculture and challenges to increase its sustainability. The analysis was based on a questionnaire study of five types of stakeholders (farmers, advisors, researchers, suppliers, policy makers). By means of multivariate analysis techniques it was revealed that consensus was lacking either in the acknowledgment of the causes and effects of unsustainable N management or in the challenges that need to be addressed. N losses from farms and the effects of N use were perceived but not conceived equally by all stakeholders. Organic farming and mandatory measures were the most controversial challenges, while those involving awareness, training and advisory were the most popular. This study cannot provide safe conclusions that can be generalized in the Japanese context, but it indicates domains where further research is required and orientations for future policy design towards more sustainable N use.

This study deals with the flood-hazard assessment and mapping in the catchment of Megalo Rema (East Attica, Greece). Flood-hazard zones were identified utilizing Multi-Criteria Decision Analysis (MCDA) integrated with Geographic Information System (GIS). Five factors were considered as the most influential parameters for the water course when high storm-water runoff exceeds drainage system capacity and were taken into account. These factors include slope, elevation, distance from stream channels, geological formations in terms of their hydro-lithological behavior and land cover. To obtain the final weights for each factor, rules of the Analytic Hierarchy Process (AHP) were applied. The final flood-hazard assessment and mapping of the study area were produced through Weighted Linear Combination (WLC) procedures. The final map showed that approximately 26.3 km2, which corresponds to 22.7% of the total area of the catchment, belongs to the high flood risk zone, while approximately 25 km2, corresponding to ~15% of the catchment, is of very high flood risk. The highly and very highly prone to flooding areas are located mostly at the southern and western parts of the catchment. Furthermore, the areas on both sides of the channel along the lower reaches of the main stream are of high and very high risk. The highly and very highly prone to flooding areas are relatively low-lying, gently sloping and extensively urbanized, and host the densely populated settlements of Rafina-Pikermi, Penteli, Pallini, Peania, Spata, Glika Nera, Gerakas and Anthousa. The accuracy of the flood-hazard map was verified by correlating flood events of the last 30 years, the Hydrologic Engineering Center’s River Analysis System (HEC–RAS) simulation and quantitative geomorphological analysis with the flood-hazard level. The results of our approach provide decision makers with important information for land-use planning at a regional scale, determining safe and unsafe areas for urban development.

The present study provides an assessment of the climate variability at a subnational scale, focusing on the case of the Apulia region, in Southeastern Italy. The variables considered for the purpose of a trend analysis were the minimum, maximum, and mean temperatures, and reference evapotranspiration. These are very important in an urban–rural planning context. The study was based on 38 monitoring stations and consisted in the application of the nonparametric Mann–Kendall test and a progressive trend analysis, both used to detect the changes. The 1950–2003 period was investigated on seasonal and annual scales. The results generally showed a warming process and an acceleration of the atmospheric evaporative demand which took place especially since the mid-1970s. The latter had a significant positive trend, while the period before the break point of the 70s had a cooling effect. Finally, the warming effect was more pronounced for minimum temperatures.

Platform-based companies are rapidly emerging and occupy major positions in the global market. In addition, the business model that relies on digital technology makes platform-based companies sustainable. This paper empirically examines the impact of internationalization breadth on corporate performance and explores the moderating role of the platform enterprise network effect and innovation investment. Annual panel data from listed Chinese platform-based companies between 2012 to 2020 were used to also verify the scale of overseas companies’ association and social networks and the moderating effect of centrality and innovation research and development (R&D) investment on these two factors. The results indicate that the irregular internationalization rhythm of platform-based companies was negatively correlated with corporate performance, and the association network and the social network centrality of overseas companies had a positive moderating effect. Innovative R&D investment could help platform-based companies expand overseas to improve their corporate performance, and its moderating effect was more significant for platform companies in the early stages of internationalization. In terms of the internationalization pace, overseas network construction, and innovative R&D investment strategies, this paper provides valuable suggestions for platform-based companies to expand internationally and improve their corporate performance.