On-site maintenance (ONSM) is critical to ensuring the safety of equipment in the petrochemical industry. However, many accidents occur during ONSM processes because of unstable equipment, complicated work environment, and human error. To reduce congestion and exposure to hazards during on-site operations and thereby reduce the probability of accidents, off-site maintenance (OFSM) is proposed based on Energy Release Theory (ERT). The information requirements for OFSM are analyzed. A support system for OFSM, which makes use of visualization, information management, and localization capabilities, is developed. A case study utilizing OFSM and its support system for an oil-loading facility of a petrochemical company is conducted. The application results indicated that implementation of OFSM system can significantly reduce the operation risks and can improve the operation efficiency.

The popularization of the mobile internet has given rise to demand for flexible and convenient payment methods. For China, it is necessary to keep pace with or even lead the trend of innovation and development in the age of mobile payment. From the perspective of systems engineering, this paper introduces research and implementation of China UnionPay’s mobile payment project. The general requirements and core engineering problems of the mobile payment project are summarized based on analyses of the characteristics and engineering difficulties of this project. Integration of innovative technologies is introduced to resolve the contradiction between ease-of-use and security. A rapid iterative development process is adopted to improve the product release efficiency as well as the users' experience. The launch of the mobile payment project also opens the window to coordinating and upgrading the whole payment industry chains.

Construction equipment encompasses highly polluting machines adversely affecting the environment. Management tools are necessary for sustainability assessment of construction equipment fleets to allow contractors to reduce their emissions and comply with local or federal regulations. In addition to management tools, there is a need for a metrics that will allow companies to accurately assess the sustainability of their construction equipment fleets. The State of California USA is adopting innovative approaches to reduce adverse impact of humans on the environment. Once successfully implemented, the chances are that such practices attract other states to adopt similar approaches. This paper presents an evaluation of construction equipment fleets and data analysis. When measured and recorded, such results can be used along with decision-support tools for selection and utilization of construction equipment. The metrics for construction equipment evaluation as well as the tool for sustainable decision-making are developed based on readily available data from manufacturers or maintenance shops without a need for additional effort by contractors or government agencies for their adoption. The metrics developed and the decision support tool incorporate logical strategies of supply chain management for optimal selection of construction equipment for construction site while taking into account the availability, cost, and mobilization related constraints. The metrics and the model can benefit both the government agencies responsible for inspection of fleets and owners of construction companies in their decision-making processes related to environmental sustainability.

This paper aims to overview Building Information Modeling (BIM) implementation and problems of BIM implementation in Japan. First, BIM implementation guidelines and pilot projects are introduced. Then, some popular BIM software together with typical implementation cases are provided. BIM implementation in Japan is not always encouraged via a top-down consensus in architectural firms and general contractors, as the client and architects can reduce the project risk inherent in design and drawings by transferring these tasks to a general contractor. The paper finally discusses the problems in project management to present a strategy to develop a new version of BIM that will provide value to all of the stakeholders of a project.

Reverse auctions of PPP projects usually require the bid to specify several characteristics of quality and the concession period to be fulfilled. This paper sets up a summary function of generalized quality, which contributes to reducing the dimensions of information. Thus, the multidimensional reverse auction model of a PPP project can be replaced by a two-dimensional direct mechanism based on the concession period and the generalized quality. Based on the theory of the revelation principle, the feasibility conditions, equilibrium solution and generalized quality requirements of such a mechanism, considering the influence of a variable investment structure are described. Moreover, two feasible multidimensional reverse auctions for implementing such a direct mechanism: Adjusting the scoring function and establishing a special reverse auction rule are built. The analysis shows that in these types of reverse auctions, optimal allocation can be achieved, the social benefit under the incomplete information will be maximized, and the private sector with the highest integrated management level wins the bid. In such a direct mechanism, the investment and financial pressure of the public sector can be reduced.

The household sector consumes roughly 30% of Earth’s energy resources and emits approximately 17% of its carbon dioxide. As such, developing appropriate policies to reduce the CO₂ emissions, which are associated with the world’s rapidly growing urban population, is a high priority. This, in turn, will enable the creation of cities that respect the natural environment and the well-being of future generations. However, most of the existing expertise focuses on enhancing the thermal quality of buildings through building physics while few studies address the social and behavioral aspects. In fact, focusing on these aspects should be more prominent, as they cause between 4% and 30% of variation in domestic energy consumption. Premised on that, the aim of this study was to investigate the effect in the context of the UK of household transitions on household energy consumption patterns. To achieve this, we applied statistical procedures (e.g., logistic regression) to official panel survey data comprising more than 5500 households in the UK tracked annually over the course of 18 years. This helped in predicting future transition patterns for different household types for the next 10 to 15 years. Furthermore, it enabled us to study the relationship between the predicted patterns and the household energy usage for both gas and electricity. The findings indicate that the life cycle transitions of a household significantly influence its domestic energy usage. However, this effect is mostly positive in direction and weak in magnitude. Finally, we present our developed urban energy model “EvoEnergy” to demonstrate the importance of incorporating such a concept in energy forecasting for effective sustainable energy decision-making.

While in the EU alone 80 million citizens are suffering from excessive environmental noise, the conventional approach, i.e., reduction of ‘sound level’, does not always deliver the required improvements in quality of life. The growing field of ‘soundscape studies’ is addressing this gap by considering the sound environment as perceived, in context, with an interdisciplinary approach. However, soundscapes are hugely complex, and measuring them as a basis for environmental design requires a step change to the discipline. This paper explores the need for developing ‘soundscape indices’, in the movement from noise control to soundscape creation, adequately reflecting levels of human comfort, the impact of which will be reminiscent of that of the Decibel scale created by Bell Systems a century ago. By analysing the soundscape design of urban open public spaces, the coherent steps for achieving this are also discussed, including characterising soundscapes by capturing soundscapes and establishing a comprehensive database; determining key factors and their influence on soundscape quality based on the database; developing, testing and validating soundscape indices; and demonstrating the applicability of the soundscape indices in the management of our sound environment.

Universities are key drivers of sustainable development and are well-positioned to contribute to the sustainability agenda. Universities in the United Kingdom (UK) are themselves large and influential organisations, and because of their size, can have a significant impact on the environment. Their challenge, however, is to practice what they preach and to manage their own estates and procurement decisions to reduce their impact on the environment and meet carbon reduction targets. In the UK, higher education (HE) sector Scopes 1 and 2 carbon CO₂e emissions have, over recent years, been falling considerably short of the emission reduction targets set by the Higher Education Funding Council for England (HEFCE) in all but a few institutions. Setting sector specific targets, therefore, does not guarantee success in addressing climate change. However, in those institutions adopting the EcoCampus management system approach, Scopes 1 and 2 carbon CO₂e emissions have fallen by up to 5% over the latest reporting period (2013/2014–2014/2015). This contrasts with the increase in emissions from those institutions who currently do not have a certified management system and are currently at the bottom of the People and Planet University League Table. (This is an independent league table of UK universities ranked by environmental and ethical performance).

Environmental management systems (EMSs) are increasingly being used by organisations to improve their environmental performance. EMSs deliver many benefits such as reducing resource use and pollution, complying with relevant environmental legislation, managing risks, improving corporate reputation and saving costs.

The aim of this research was to assess the carbon management performance of universities in the UK and China and relate this to the level of uptake of EMSs in these universities. The results of this research informed the development of the EMS support and awards programme called EcoCampus. EcoCampus addresses the challenges faced by universities in reducing their carbon emissions by developing an EMS in simple stages with support in a variety of different forms. This self-financing programme has now been operating successfully for over ten years. During this time, EcoCampus has worked with over 60 universities and colleges in the UK. Eighteen participants have currently achieved the highest phase of EcoCampus and certification to the international EMS standard ISO14001. There are currently 40 universities, one research institute and three colleges enrolled on the various phases of the EcoCampus programme. There are five universities from the Russell Group including Cambridge University, Imperial College London, Nottingham University, Newcastle University and University College London. The EcoCampus programme is highly successful in the UK and there is growing interest from international universities wishing to join the programme. Seven of the top ten universities in the UK’s People and Planet University League Table are EcoCampus members. All the top ten universities in the League Table have shown a reduction in their carbon emissions. In contrast, the ten institutions at the bottom of the League don’t have a certified EMS and have increased their carbon emissions.

By identifying the benefits of an EMS, particularly in relation to carbon management, it is hoped that this paper will encourage organisations to develop, implement and operate an EMS. This should lead to a more sustainable sector able to lead by example.

This study explores the influence of social media on stock volatility and builds a feature model with an intelligence algorithm using social media data from Xueqiu.com in China, Sina Finance and Economics, Sina Microblog, and Oriental Fortune. We find that the effect of social factors, such as increased attention to a stock’s volatility, is more significant than public sentiment. A prediction model is introduced based on social factors and public sentiment to predict stock volatility. Our findings indicate that the influence of social media data on the next day’s volatility is more significant but declines over time.

Reverse auctions have been widely adopted for purchasing goods and services. This paper considers a novel winner determination problem in a multiple-object reverse auction in which the buyer involves loss-averse behavior due to uncertain attributes. A corresponding winner determination model based on cumulative prospect theory is proposed. Due to the NP-hard characteristic, a loaded route strategy is proposed to ensure the feasibility of the model. Then, an improved ant colony algorithm that consists of a dynamic transition strategy and a Max-Min pheromone strategy is designed. Numerical experiments are conducted to illustrate the effectiveness of the proposed model and algorithm. We find that under the loaded route strategy, the improved ant colony algorithm performs better than the basic ant colony algorithm. In addition, the proposed model can effectively characterize the buyer’s loss-averse behavior.

Using sudden cardiac deaths as an example and maximizing survival rate as the goal, this paper studies the influence of multi-stage medical logistics system optimization on the survival rate of sudden illness. A distribution model of survival is built, drone and ambulance arrival probability over time are discussed, a formula is proposed for maximum possible survival rate based on the probability of emergency medical logistics reaching the patient, and the results are analyzed using empirical data fitting distribution and numerical experiments performed with the model. The model is discussed as a reference point for management decision making by changing model parameters. Results show that compared to using current ambulance vehicles, ambulance drones delivering medical equipment for first aid on-site in emergencies can significantly increase survival rate, and the effect of collaborative multi-stage logistics optimization is better than that of any single stage logistics response optimization. Simulation results show that the medical rescue logistics service radius, speed, loading capacity and performance of ambulance drones impact the probability of survival, and there is an optimal service radius depending on the shape of probability distribution, which provides new information for management decisions.