An evaluation framework for developing green infrastructure by using a new hybrid multiple attribute decision-making model for promoting environmental sustainability

With the expansion of urbanization caused by the growth of population and industrial activities, the urban/city and suburban areas are facing a variety of environmental threats. Although more research and urban policy has advocated and practiced the development of green infrastructure (GI) to support urban sustainable environment, the evaluation framework for the development of GI for promoting environmental sustainability is still insufficient. Moreover, the Analytic Hierarchy Process (AHP) commonly applied in published literature, makes an unrealistic assumption of independent relationships among dimensions/criteria in decision making for satisfying the real-world problem. Therefore, the purpose of this study is to construct the evaluation framework, including four dimensions and related ten criteria, using a new hybrid-modified multiple attribute decision-making (MADM) model for developing and improving the GI for promoting environmental sustainability. This MADM model is combined with three different methodologies of MADM, including the Decision-Making Trial and Evaluation Laboratory (DEMATEL) for constructing the influential network relation map (INRM) to explore the complex influential inter-relationships and DEMATEL based on Analytic Network Process (DANP) for determining the influential weights with the VIse Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) for evaluating and presenting improvement strategies for six different GIs. The empirical study indicates that DEMATEL and DANP Results suggest that decision-makers should pay more attention to the improvement of Design (D₄) and Materials (D₂) in terms of dimensions when utilizing the GI to promote environmental sustainability. Because these dimensions are enhanced, Species (D₁) and Energy (D₃) will be improved in synchronization. From the perspective of criteria, five are key core criteria and need to be focused on first: increasing the green coverage rate (B₉), utilizing sustainable materials (B₄), using ecological engineering (B₈), shaping species biodiversity (B₁), and reducing energy consumption (B₅). Modified VIKOR reveals that “grass swales” are a comparatively better choice among six GIs for promoting environmental sustainability toward achieving the aspiration level. Therefore, this MADM model is beneficial to provide a more convincing assessment framework and improvement strategies for the development of GI for promoting environmental sustainability. As a result, these modified MADM models can be shown more conveniently and reasonably than traditional methods such as traditional AHP or ANP method.     

Does parasocial interaction with weight loss vloggers affect compliance? The role of vlogger characteristics,consumer readiness,and health consciousness

Drawing on the notion of parasocial interaction (PSI) and the social comparison theory, this experimental research examines how nutritionist video bloggers (vloggers) influence consumer compliance intentions toward healthy, weight-loss diets. Drawing on two samples (Mexican Americans and White Caucasians) and using structural equation modeling and mediation analysis, this research highlights vloggers’ credibility and physical attractiveness, but not homophily, as salient source characteristics that influence PSI, which in turn reinforces compliance intention. Moreover, consumer readiness, consisting of role clarity, ability, and motivation, serves as a partial mediator of the PSI–compliance intention relationship. Lastly, consumer health consciousness emerged as a significant moderator of the PSI–compliance intention relationship among White Caucasians, but not among Mexican Americans. The findings and their implications are discussed.     

利用改进特征金字塔模型的SAR图像多目标船舶检测

深度学习模型中的特征金字塔网络（Feature Pyramid Network，FPN）常被用作合成孔径雷达（Synthetic Aperture Radar，SAR）图像中多目标船舶的检测。针对复杂场景下多目标船舶检测问题，提出了一种基于改进锚点框的FPN模型。首先将特征金字塔模型嵌入传统的RPN（Region Proposal Network）并映射成新的特征空间用于目标检测，然后利用基于形状相似度距离（Shape Similar Distance,SSD）度量的Kmeans聚类算法优化FPN的初始锚点框，并使用SAR船舶数据集测试。实验结果表明，所提算法目标检测精确率达到98.62%，在复杂场景下与YOLO、Faster RCNN、FPN based on VGG/ResNet等模型进行对比，模型准确率提高，整体性能更好。     

Beyond the boundaries: Challenges for business,policy and society

This editorial article introduces the papers presented at the ITS Seoul 2018 and seven papers selected for the special issue of ITS Seoul 2018. Specifically, this article provides the results of keyword networks, research agendas and coauthor networks of ITS Seoul 2018. A summary of the seven papers accepted for the special issue of ITS Seoul 2018 is also included. Finally, this article concludes by introducing another paper that empirically explores the value of special issues by analyzing the characteristics of special issues of Telecommunications Policy.     

Real estate prices and systemic banking crises

The collapse of real estate prices has historically jeopardized banking stability and triggered systemic banking crises. This paper studies risk contagion in a banking system in real estate price shock by adopting complex network theory. Modelling the real estate-related asset as a common exposure of banks to the real estate market, we propose a model that incorporates two main risk contagion channels, i.e., the financial network and asset fire sales, and reveal how the real estate price shock is transmitted and propagated across banks. We demonstrate that banking stability is highly sensitive to the real estate price shock. Moreover, due to the particularly low liquidity of the real estate market, the asset fire-sales of real estate assets overwhelms the financial network, playing the dominant role in risk contagion. Our model can be adopted by regulators to conduct stress testing and to forge effective risk management strategies.     

Using artificial neural network and multivariate analysis techniques to evaluate road operating conditions

Regional paved roads are low volume roads with a prevalence of heavy traffic. In the world, these roads concern about 80% of the total road network; however, the traffic that affects these roads is about 20%. Since regional roads are characterized by weak demand, budget for their management/maintenance is very low. This produces considerable difficulties in the choice of strategies for maintenance planning and scheduling. For this reason, the recurring topics of research in this field deal with typical roads issues and aim to develop low cost tools and methods. The study proposes a decision support system to evaluate regional paved roads operating condition in relation to the hydrogeological situation. In particular, the system allows to evaluate in a quick and easy manner, the operating conditions of the road, through low-cost tools (i.e. using low economic resources). This is very useful in the case of LVRs because administrations for these roads have a limited budget. The procedure is developed on a regional paved roads network based on more than 80 roads located in Southern Italy. Data is collected by direct surveys in the field and is integrated with cartography and information available in road agency records. From data analysis, obtained using two different techniques, an easy and quick use procedure is made. In particular, Model 1 is built through multivariate analysis and Model 2 using the artificial neural network (ANN) technique. The results show the validity of the two models in Regional paved roads operating conditions estimation in relation to hydrogeological situations of sites. Both models show good reliability. In particular, the first model (Model 1) is characterized by a high level of significance (p < 0.01) and by a coefficient of determination equal to 0.82. Comparative tests between the second model (Model 2) on which standard tests cannot be performed for obvious reasons, and the first model (Model 1). The results show that the ANN model (model 2), characterized by lower residual, simulates more accurately than the second (Model 1).     

The Internet of Things as an accelerator of advancement of broadband networks: A case of Thailand

The advanced development of broadband access is an inevitable step toward supportive daily lives and sustainable economic growth. However, the decisive outcome of the development relies heavily on the demand side. Consumer choice among advanced Internet broadband technologies will determine the achievement of the development. This study aims to illustrate that consumer decisions on choices of advanced Internet access are influenced by the emergence of the Internet of Things (IoT) applications. A bivariate probit model is applied to examine the effects of IoT, consumer's individual characteristics, and their current use of networks on their decision pertaining to the choice of advanced Internet access. Using Thailand as a case study, the result indicates that the emergence of IoT applications accelerates the adoption of both advanced mobile broadband (5G) and advanced fixed broadband (FTTH). This finding may help policy makers to optimize the future direction of the Internet infrastructure development in Thailand, and also countries in a similar stage.     

Virtual interlining within the European airport network: An airfare analysis

Virtual interlining, which covers the actively marketed or ‘non-hidden’ segment of all potential self-connecting flight itineraries, is often assumed to be a money-saving travel strategy. In this paper we assess the price difference between virtual interlined and ‘traditional’ flight itineraries within the intra-European airport network. We query Kiwi.com's recently developed Tequila platform, one of the few specialised online travel agencies (OTAs) offering both ‘traditional’ and virtual interlined flight itineraries, to obtain information on all available flights in the first week of August, October and December 2019. Using a series of sign tests, we investigate whether a statistically significant fare difference exists between the cheapest available (direct and/or indirect) ‘traditional’ and virtual interlined flight itineraries. Our results indicate a statistically significant fare difference between the cheapest indirect ‘traditional’ and the virtual interlined flight itineraries in favour of the latter. However, with regard to direct traditional flight itineraries the results are mixed. We explore the size and the scope of these patterns in more detail, and outline possible avenues for further research.     

Enhanced network effects and stochastic modelling in generation expansion planning: Insights from an insular power system

Electricity generation capacity expansion is driven by both economic and socio-political realities. Policy makers determine public infrastructural decisions, such as climate and renewable targets, and transmission infrastructure, and the optimal generation capacity expansion follows. Policy makers therefore require planning models that can determine the optimal generation capacity mix in the long run under various scenarios, including policy choices. This work presents a planning model based on linearised alternating current optimal power flow which determines optimal generation capacity expansion and operation, in a least-cost manner, given global and local technical constraints, as well as policy decisions. We apply the model to a test case of the island of Ireland, which has two weakly interconnected systems, high renewable generation targets and low storage and interconnection. We determine the optimal generation expansion and operation out to 2030 considering the effects of increased multi-area interconnection, existing fossil fuel generation phase-out and increased renewable generation targets and carbon prices. Our results find that costs and emissions are driven primarily by the decommissioning of old inefficient generation units. High renewable targets, on the other hand, render increased carbon prices relatively ineffective in reducing system emissions. Furthermore, high renewable generation targets crowd out low-carbon power generation options such as carbon capture and storage (CCS). The strategic north-south interconnection has little effect on renewable energy source installations required to achieve renewable power generation targets but does impact on security of supply and the congestion level across the island.