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Since the theory of planned behavior (TPB) was proposed by Ajzen in 1985, it has attracted extensive interest and been widely applied worldwide. Although an increasing number of studies have employed the TPB in the domain of environmental science, there have been no attempts to retrospectively analyze existing articles. The current study aimed to holistically understand the application status of the TPB in environmental science from a knowledge domain visualization perspective. A total of 531 journal articles were obtained through the Scopus database to perform a bibliometric analysis and content analysis. The results showed that waste management, green consumption, climate and environment, saving and conservation, and sustainable transportation are the primary research topics; the United States (U.S.), Mainland China, the United Kingdom (UK), and Malaysia are the most productive countries/regions. Moreover, the cross-disciplinary situations, main source journals, and key articles were revealed. Furthermore, the extended factors, integrated theories, major methods, specific groups, and control variables of environmental science research using the TPB were elaborated and integrated into a comprehensive application framework. Constructive criticisms were ultimately discussed. The findings contribute in several ways to help relevant researchers learn about the application of TPB to environmental science and provide new insights and holistic references for further research on environment-related behavior.

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As an essential part of a city, community is significant to the sustainable development of the city. At present, research on community sustainability assessment systems is relatively scarce. The existing community sustainability assessment systems often lack integrated consideration of community sustainability. For example, these systems especially place emphasis on the ecological and environmental aspects, but the economic and social aspects of sustainability are partially ignored. In order to comprehensively evaluate the sustainability of a community, this paper draws on the "participatory philosophy" and constructs an integrated assessment indicator system that includes five dimensions: environment; economy; society; institution; and culture. On this basis, a new hybrid evaluation method based on analytical hierarchy process (AHP)-entropy weight and the cloud model is proposed to evaluate community sustainability. This method combines AHP and the entropy weight method to determine index weight, thus making full use of their respective advantages. At the same time, it makes use of the superiority of the cloud model to transform qualitative remarks into quantitative representations and to reflect fuzziness and randomness. To verify the feasibility of this method, a case study is carried out on the "Minxinjiayuan" public rental housing community in Chongqing, China. The results show that the overall sustainability of the community lies between the "middle" and "good" level, and closer to the "middle" level. The level of the economic and social sustainability is higher than that of the environmental, institutional and cultural sustainability.

A common perception is that there are two competing visions for the future evolution of the Web: the Semantic Web and Web 2.0. In fact, Semantic Web technologies must integrate with Web 2.0 services for both to leverage each other's strengths. This paper illustrates how Semantic Web technologies can support information integration and make it easy to create semantic mashups. An intelligent recommendation system for tourism is presented to show the efficiency of our method. Through the ontology of tourism, the system allows the integration of heterogeneous online travel information. An integrated knowledge process is developed to guarantee the whole engineering procedure. Based on the Bayesian network technique, the system recommends tourist attractions to a user by taking into account the travel behavior both of the user and of other users.

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Cloud computing has become a scalable services consumption and delivery platform in the field of computer science. As more and more consumers delegate their tasks to cloud providers, service level agreements (SLAs) between consumers and providers emerge as a key aspect. Because of the dynamic nature of the cloud, continuous monitoring on quality‐of‐service attributes is necessary to enforce SLAs. In this paper, we propose a trust mechanism‐based task scheduling model for cloud computing. Referring to the trust relationship models of social persons, trust relationship is built among computing nodes, and the trustworthiness of nodes is evaluated by utilizing the Bayesian cognitive method. Integrating the trustworthiness of nodes into a dynamic level scheduling algorithm, the trust dynamic level scheduling algorithm for cloud computing is proposed. Theoretical analysis and simulations prove that the proposed algorithm can efficiently meet the requirement of cloud computing workloads in trust, sacrificing fewer time costs, and assuring the execution of tasks in a secure way in cloud environment. Copyright © 2011 John Wiley & Sons, Ltd.