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This article is an investigation of the entrepreneurial network and its strategic implications in a Chinese sociocultural context. It identifies four separate but highly interrelated network dimensions (relationship, governance, structure, and dynamic); it also highlights an important research gap. Entrepreneurs of 12 small Chinese high-technology firms in Beijing and Shenzhen were interviewed. The interview scripts were analyzed by data reduction. Concepts related to entrepreneurial network strategies of small Chinese high-technology firms were gradually condensed. Categorical principal component analysis (CATPCA) in SPSS for Windows 12.0 software was applied to group the cases, which in turn confirmed the qualitative data analysis results. A tentative schema is proposed, illustrating four types of entrepreneurial networkers according to network adaptation and external resource dependence. Network adaptation is based on the differentiation of the entrepreneurial efforts in network construction and change: integrative adaptation, cooperation, and coordination. External resource dependence indicates to what extent the entrepreneur relies on external resources-that is, placing emphasis on using external resources or maintaining a balance between internal and external resources. The reliance on external resources is highly related to two factors: the nature of relationship and the extent of commitment. In a transaction-based, relationship-dominated network, if the entrepreneur decides to develop his or her own resource competitiveness he or she will rely less on external resources. In a collaboration-based, relationship-dominated network, if the entrepreneur tends to have a low commitment to maintaining the relationship, he or she will depend little on external resources. Customer-oriented networkers value interpersonal relations and strive to establish long-term customer relationships. Partnership networkers form strategic alliance with suppliers, manufacturers, and subcontractors to access external resources. Value-oriented networkers have a holistic view of networks and play an active role in network construction and development. Prospecting networkers make a strong commitment to network actors to exploit external resources and to make proactive moves to adapt to environmental changes.

To evaluate the road safety development in Europe over the last decade, this study presents a new way for measuring the road safety performance change over time, which is to use the technique of data envelopment analysis (DEA) and the Malmquist productivity index. In doing so, we can not only focus on the evolution of road safety final outcomes within a given period, but also take the changes of exposure in the same period into account. In the application, the DEA-based Malmquist productivity index (DEA-MI) has proven valuable as a benchmarking tool for measuring the extent to which the EU countries have improved their road safety performance over the period 2001-2010, and it has derived more objective and insightful results than the ones based on the traditional indicator which only measures the percentage change in road fatalities. The results show considerable road safety progress in most of the Member States during these ten years, and the fatality risk on Europe's roads instead of the number of road fatalities has actually been reduced by approximately half. However, the situation differed considerably from country to country. The decomposition of the DEA-MI into efficiency change and technical change further reveals that the bulk of the improvement during the last decade was attained through the adoption of productivity-enhancing new technologies throughout the road transport sector in Europe, rather than through the relatively underperforming countries catching up with those best-performing ones.

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The road traffic crashes and consequent injuries and fatalities, traditionally regarded as random, unavoidable 'accidents', have been more and more recognized as a preventable public health problem. Given the fact that more and more countries are taking steps to improve their road safety situation, there is a growing need for these countries to work together more closely, because there are quite a number of common problems that can be identified in close cooperation, and improvement can be expected by learning lessons from existing best practices in other countries. As a consequence, comparison between a range of countries in terms of their road safety performance and development or − using state-of-theart terminology − inter-national benchmarking of road safety, is currently widely advocated by most countries and international bodies. However, performing a successful road safety benchmarking practice is by no means easy. Challenges exist from the definition of benchmarking framework at the very beginning to the final decisions in terms of identification of best practices and establishment of a continuous process of mutual learning. In this paper, based on a brief review of the concept of benchmarking, a benchmarking cycle for road safety is proposed. Moreover, as a valuable benchmarking tool, the development of a road safety index is highlighted, a number of recent studies are presented, and some theoretical and practical issues are discussed.

Given the importance of considering the serious injuries in addition to the fatalities for international benchmarking of road safety, the proposed model (i.e., the DEA-RS model with weight restrictions) turned out to be effective in deriving reasonable results. We are thereby also inspired to apply this kind of model to a more complete road safety benchmarking practice in the future when the data on, for example, the number of slight injuries, the degree of property damage, and the number of crashes are ready (i.e., comparable) to use.

Nowadays, considerable attention has been paid to the activity-based approach for transportation planning and forecasting by both researchers and practitioners. However, one of the practical limitations of applying most of the currently available activity-based models is their computation time, especially when large amount of population and detailed geographical unit level are taken into account. In this research, we investigated the possibility of restraining the size of the study area in order to reduce the computation time when applying an activity-based model, as it is often the case that only a small territory rather than the whole region is the focus of a specific study. By introducing an accuracy level of the model, we proposed in this research an iteration approach to determine the minimum size of the study area required for a target territory. In the application, we investigated the required minimum size of the study area surrounding each of the 327 municipalities in Flanders, Belgium, with regard to two different transport modes, that is, car as driver and public transport. Afterwards, a validation analysis and a case study were conducted. All the experiments were carried out by using the FEATHERS, an activity-based microsimulation modeling framework currently implemented for the Flanders region of Belgium.

Activity‐based travel demand modeling is the approach with most relation and need for intelligent solutions as it directly aims at reproducing human decision making in daily life. Therefore, the way to implement the selected intelligent solution plays an important role in the successful application of the models. FEATHERS (the Forecasting 16 Evolutionary Activity‐Travel of Households and their Environmental RepercussionS) is an activity‐based microsimulation modeling framework used for transport demand forecasting. Currently, this framework is implemented for the Flanders region of Belgium and the most detailed travel demand data can be obtained at the Subzone level, which consists of 2,386 virtual units with an average area of 5.8 km2. For the sake of more detailed travel demand forecasting, we investigated in this study the extension of the FEATHERS framework from the Subzone zoning system to a more disaggregated zoning system, i.e., Building block (BB), which is the most detailed geographical level currently applicable in Belgium consisting of 10,521 units with an average area of 1.3 km2. In this paper, we elaborated the data processing procedure to implement the FEATHERS framework under the BB zoning system. The observed as well as the predicted travel demand in Flanders based on the two zoning systems was compared. The extended modeling system was further applied to investigate the potential impact of light rail initiatives on travel demand at a local network in Flanders.