Long-term Development Patterns Research Articles

Nanotechnology and knowledge relatedness: how to identify optimal regional partners in EU innovation networks?

Abstract Research & Innovation (R&I) policy initiatives employed by the European Union (EU) across its regional economies are important instruments to ensure the scientific and technological progress along with the associated benefits. One relevant aspect in this regard is to encourage and enable collaboration between regional partners to enhance potential learning opportunities and to ensure cohesive long-term development patterns. Furthermore, frequently these initiatives are also targeted at specific technology sectors, such as the EU R&I policy actions towards nanotechnology. Based on an advance theoretical framework and data from the official EU project databases as well as regionalized European Patent Office data, the present study develops a methodological tool through which it is possible to identify effective collaboration settings, while providing policymakers and evaluators with a practical tool that will enable them to predict the possible outcomes of such critical EU-funded R&I projects from the onset.

Evaluation and Spatial Correlation Analysis of Green Economic Growth Efficiency in Yangtze River Delta Urban Agglomeration

The Yangtze River Delta urban agglomeration has an extremely important strategic location in the national regional development pattern, is the engine of China’s green economic development, and plays an important role in promoting the green transformation of the national economy. It is important to clarify the region’s current situation and the space–time characteristics of green economic growth. This study uses a super-efficiency dynamic Slacks-Based Measure (SBM) model to measure the green economic growth efficiency (GEGE) of 41 cities in the Yangtze River Delta urban agglomeration. Based on this, the exploratory spatial data analysis (ESDA) method is used to analyze the spatial correlation of the GEGE. Differently from previous studies, this paper evaluates the GEGE based on a dynamic perspective, considering the intertemporal role of capital. At the same time, the space–time analysis of regional systems (STARS) is used to explore the long-term development pattern and transition path of the GEGE in the Yangtze River Delta urban agglomeration. The results show the following: (1) The GEGE in the Yangtze River Delta urban agglomeration shows a fluctuating downward trend. The efficiency values of the Shanghai, Jiangsu, Zhejiang, and Anhui are significantly different, showing the distribution law of “high in the east and low in the west”. (2) The global spatial autocorrelation has weakened, but the characteristics of local agglomeration are obvious. (3) The space–time transitions show high spatial stability and path dependence. The findings highlight that the economic development of the Yangtze River Delta urban agglomeration is undergoing a difficult period of transition. Despite a decline in the GEGE, the overall regional linkage shows a positive trend. The conclusions can provide a reference for enhancing the green economic development of the Yangtze River Delta urban agglomeration. The implications of this research are important for the implementation of a regional integration strategy and the early achievement of the emission peak and carbon neutrality goals.

Factors Affecting the Long-Term Development of Specialized Agricultural Villages North and South of Huai River

Village-level agricultural specialization in China is becoming increasingly important for rural development. However, existing knowledge of specialized agricultural villages (SAVs) based on singular assessment criteria and data describing static time points becomes insufficient in addressing multifaceted developmental questions today. We examined the long-term development patterns of SAVs in Anhui, China, with attributes from multiple angles, and explored how local factors affected SAV development across space and time using random forest regression. We found that as time elapsed, economic rationality drove specialized farmers closer to sale dependency and made SAVs more susceptible to market and economic factors, which builds upon previous findings analyzing SAVs at specific time points and consolidates the importance of market factors in the long-term development of SAVs. However, this susceptibility manifests differently in these two geographically contrasting regions north and south of Huai River. The northern SAVs received increased influences from market and economic factors, while the southern SAVs were continuously controlled by market and location factors. The dynamic spatial and temporal patterns of the two regions point to different dependencies, which emphasized local sales in the north and distant sales in the south. We propose that policies and strategies regarding SAV development accommodate these dynamics and address appropriate influencing factors accordingly.

Two centuries of settlement and urban development in the United States.

Over the past 200 years, the population of the United States grew more than 40-fold. The resulting development of the built environment has had a profound impact on the regional economic, demographic, and environmental structure of North America. Unfortunately, constraints on data availability limit opportunities to study long-term development patterns and how population growth relates to land-use change. Using hundreds of millions of property records, we undertake the finest-resolution analysis to date, in space and time, of urbanization patterns from 1810 to 2015. Temporally consistent metrics reveal distinct long-term urban development patterns characterizing processes such as settlement expansion and densification at fine granularity. Furthermore, we demonstrate that these settlement measures are robust proxies for population throughout the record and thus potential surrogates for estimating population changes at fine scales. These new insights and data vastly expand opportunities to study land use, population change, and urbanization over the past two centuries.

Assessment of Air-Pollution Control Policy’s Impact on China’s PV Power: A System Dynamics Analysis

Recently, China has brought out several air-pollution control policies, which indicate the prominent position that PV power hold in improving atmosphere environment. Under this policy environment, the development of China’s PV power will be greatly affected. Firstly, after analyzing the influencing path of air-pollution control policies on PV power, this paper built a system dynamics model, which can be used as a platform for predicting China’s PV power development in every policy scenario during 2015–2025. Secondly, different model parameters are put into the SD model to simulate three scenarios of air-pollution control policies. Comparisons between the simulated results of different policy scenarios measure the air-pollution control policy’s impact on China’s PV power in the aspect of generation, installed capacity, power curtailment and so on. This paper points out the long-term development pattern of China’s PV power under latest incentive policies, and provides reference for the policymakers to increase the effect and efficiency of air-pollution control policies.

China's photovoltaic power development under policy incentives: A system dynamics analysis

Recently China has brought out several incentive policies to break high-cost limitation and stimulate investment in photovoltaic industry. Under this favorable policy environment, PV power is undoubtedly facing enormous development opportunities. Firstly, after analyzing current policy environment and interactions between involved variables, a simulation model of China's PV power development was built using system dynamics methodology considering both economic and technical factors. Secondly, sensitivity analyses are made to analyze the sensitivities of key variables and the effectiveness of relevant policies. The simulated results of generation, investment and capacity during 2012–2032 indicate the future developing trend, and evaluate the rationality and effect of incentive policies. The model allows an understanding of PV power's long-term development pattern under China's latest incentive policies, thus helping to provide reference for policy-making institutions.

Spatio-temporal trend analysis of long-term development patterns (1900–2030) in a Southern Appalachian County

Many mountainous areas in the U.S. have experienced significant changes in residential development patterns over the past century, in large part due to changing economies and in-migration from outsiders seeking the scenic resources of these areas. To evaluate changes in the Southern Appalachian mountain region, we reconstructed building and road locations in Macon County, North Carolina, since 1906 from historic maps, aerial photographs, county parcel records and emergency response program data. We used these data to analyze growth trends using spatio-temporal classification and quantile regression analysis. We also forecast future development patterns through 2030 using a multi-step model incorporating population growth projections, extrapolations of recent development density trends, and spatial logistic regression models. We characterize new development in the county as primarily rural from 1906 to 1960, exurban from 1960 to 1975 and increasingly suburban since 1975. While the rate of population growth and new building construction peaked in the 1980s, the total road length and rate of development in forested areas continued to increase from 1990 to 2009. We forecast that through 2030 approximately 75% of new buildings will be constructed at urban and suburban densities and that 67% of all new buildings will be constructed in forested areas. In addition to establishing the utility of using spatial analysis to draw together disparate data sources to understand urbanization over long time scales, this analysis identifies trends that have important implications for land-use planning, hydrology, forest management, and wildlife conservation.

The making of research funding in Austria: transition politics and institutional development, 1945–2005

In many cases, the long-term development patterns of research policy still remain blurred. However, historical insights may lead to a better understanding of what makes research funding work. A perspective of 60 years on the situation in Austria exemplifies a system run by a broad set of stakeholders. Consensus among those stakeholders is necessary for the implementation of new elements. Once agreed upon, such elements remain stable for a long time as any change requires a new consensus. Thus individual stakeholders tend to add bypass solutions, while existing principal-agent relationships develop lock-ins. The system needs sufficient pressure to be built up by those factors in order to trigger substantial change. Copyright , Beech Tree Publishing.

The Dynamics of Land Development in Resort Communities: A Multiagent Simulation of Growth Regimes and Housing Choice

Over the past thirty years, recreation communities in many parts of the globe have gone through cycles of diversification and integration into complex recreation regions. As resort communities mature, they face increasing pressures on scarce recreational resources, demands for economic diversification, and changing attitudes toward tourism on the part of local residents. A variety of land-use management practices and economic development initiatives has emerged in resort towns in response to resource congestion and other growth issues. In this paper we explore alternative growth strategies through a simulation of housing decisions by primary actors in resort land markets. We use a multiagent system to model the dynamics of growth regimes, assess the influence of recreational and town amenities, and evaluate the effect of alternative growth processes on long-term development patterns. Our case study area is Steamboat Springs and surrounding parts of Routt County, a four-season recreational region in northwestern Colorado.