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This study aims to investigate the mechanism of the misinformation spread based on the elaboration likelihood model and the effects of four factors – emotion, topic, authority and richness – on the depth, breadth and structural virality of misinformation spread.

The authors collected 2,514 misinformation microblogs and 142,006 reposts from Weibo, used deep learning methods to identify the emotions and topics of misinformation and extracted the structural characteristics of the spreading network using the network analysis method.

Results show that misinformation has a smaller spread size and breadth than true news but has a similar spread depth and structural virality. The differential influence of emotions on the structural characteristics of misinformation propagation was found: sadness can promote the breadth of misinformation spread, anger can promote depth and disgust can promote depth and structural virality. In addition, the international topic, the number of followers, images and videos can significantly and positively influence the misinformation's spread size, depth, breadth and structural virality.

The influencing factors of the structural characteristics of misinformation propagation are clarified, which is helpful for the detection and management of misinformation.

The purpose of this paper is to identify global trends in the third-party logistics (3PL) industry, and with that to find out where the opportunities and challenges lie, what the critical success factors are, and how companies can position themselves well in China. As there is currently very limited knowledge about the 3PL industry in China, this study also intends to shed light in this area.

The study is conducted through focus group interviews with senior executives of leading 3PL companies in China followed by a survey with 70 logistics companies.

The key strengths of the logistics industry in China include numerous factors such as good connectivity and new infrastructure, while its main weaknesses are a shortage of qualified staff and slow adoption of technologies. There are a number of concerns and issues raised, such as lack of qualified staff, oversupply of warehousing space in China, competition from the influx of foreign 3PL companies to China, and regulations on free trade zones, seaports and airports, all of which may have policy implications.

As most of the logistics companies in the study are located and dominating in the Eastern and Southern China, it may be useful to conduct similar study in the new emerging western and central regions of China for comparison.

Managers and investors will appreciate the challenges and opportunities in logistics services in China and have a better insight into Chinese logistics development.

While China has been viewed as a cost effective place for manufacturing, the logistical costs in China are still very high as compared to other developed countries. This research will highlight the key reasons for the high logistical cost in China.

Crane plays a very important role in national economy with greatly reduced labor intensity, improved production efficiency and promoted social development as an indispensable auxiliary tool and process equipment. Therefore, its energy consumption becomes an unavoidable topic and in fact, energy consumption of crane is very huge. It has been proved to be the most cost-effective way for reducing energy consumption to establish and implement new energy efficiency standard. Thus, it is necessary to analyze and evaluate the energy efficiency for overhead crane so as to propose a new energy efficiency standard. The paper aims to discuss these issues.

In this paper, four kinds of energy consumption sources of overhead crane is considered, based on which, an energy efficiency grading model for overhead crane based on BP neural network is proposed. Second, DS evidential theory is analyzed and based on it, an energy efficiency evaluation model based on BP neural network and DS evidential theory is proposed. The evaluation procedure is discussed in detail. Then, a case is demonstrated how the evaluation is carried out.

If overhead cranes with different energy consumptions need to be graded according to energy efficiency, the criterions to establish the energy efficiency labels for overhead cranes is proposed in this paper.

The research results can provide energy efficiency standard proposal of overhead crane for relative departments to monitor the design, manufacturing and use of overhead crane.

An energy efficiency grading model for overhead crane based on BP neural network is proposed. An energy efficiency evaluation model based on BP neural network and DS evidential theory is proposed.

Adaptive slicing is a key step in three-dimensional (3D) printing as it is closely related to the building time and the surface quality. This study aims to develop a novel adaptive slicing method based on ameliorative area ratio and accurate cusp height for 3D printing using stereolithography (STL) models.

The proposed method consists of two stages. In the first stage, the STL model is sliced with constant layer thickness, where an improved algorithm for generating active triangular patches, the list is developed to preprocess the model faster. In the second stage, the model is first divided into several blocks according to the number of contours, then an axis-aligned bounding box-based contour matching algorithm and a polygons intersection algorithm are given to compare the geometric information between several successive layers, which will determine whether these layers can be merged to one.

Several benchmarks are applied to verify this new method. Developed method has also been compared with the uniform slicing method and two existing adaptive slicing methods to demonstrate its effectiveness in slicing.

Compared with other methods, the method leads to fewer layers whilst keeping the geometric error within a given threshold. It demonstrates that the proposed slicing method can reach a trade-off between the building time and the surface quality.

Megaproject knowledge innovation (MKI) is perceived as a critical strategy for engineering value co-creation and industrial chain upgrading. Ascertaining the impact mechanism of MKI is a crucial initial step towards improving management practices. Within the framework of complex systems in megaprojects, factors exhibit intricate interdependencies. However, the current domain of knowledge has either overlooked or oversimplified this relationship and therefore cannot propose pragmatic and efficacious strategies for enhancing MKI. To close this gap, this study develops a Bayesian network (BN) model aiming to investigate the interdependencies among MKI-related factors and their impact on MKI.

First, this study implements literature review, expert interview and field investigation to identify the influencing factor nodes for the network model development. Second, a Bayesian network was constructed by integrating the expert knowledge with Dempster-Shafer theory. Next, a MKI measurement model was established using 253 training samples. Finally, the factor significance and optimal MKI improvement strategies are identified from the sensitivity analysis and probabilistic reasoning within the BNs.

The results indicate that (1) the BN model exhibits significant reliability and holds promotion and application value in formulating MKI management strategies; (2) knowledge sharing, shared vision and leadership are the key influencing factors of MKI; and (3) simultaneously improving institutional pressure, leadership and knowledge sharing is the most optimal strategy to enhance MKI.

This study innovatively introduced the BN method into the domain of MKI management, providing an appropriate approach for modelling complex relationships among factors and investigate nonlinear influences. The developed model raises megaproject stakeholders’ awareness about factors influencing MKI and presents quantified strategies that increase the likelihood of maximising MKI levels. Its ease of generalisability positions it as a promising decision support tool, facilitating the implementation of sustainable MKI practices.

As a highly knowledge-intensive activity, digitalization is changing the construction industry landscape and is encouraging construction firms to explore the transformation. This study establishes a new theoretical model aimed at examining the impact of three types of intellectual capital (IC) on digitalization through the lens of knowledge-based view and explores how IC and digitalization influence sustainability performance from the triple bottom line principles.

A questionnaire survey was conducted to collect data from Chinese construction firms using convenience sampling. A total of 181 valid responses were obtained. Then, a partial least squares structural equation modelling (PLS-SEM) technique was executed through Smart PLS 3.0 software. The measurement model was assessed to ensure reliability and validity, and the structural model was analysed to test the proposed hypotheses.

The empirical results confirm the positive impact of IC on digitalization and digitalization on sustainability performance. Moreover, digitalization plays a significant mediating role in the relationship between IC and sustainability performance.

The results provide empirical evidence supporting the different roles of IC and digitalization in improving sustainability. The findings contribute to enhancing the understanding of digitalization practices from the perspective of IC and provide theoretical and managerial implications for sustainability issues in the context of the construction industry.

In order to study whether far-infrared fabrics can be used as a garment for breast cancer patients, or as an adjuvant rehabilitation underwear for breast cancer patients after postoperative radiotherapy and chemotherapy, to eliminate tissue edema. To explore the effect of different far-infrared fabrics on the proliferation and invasion of breast cancer cells as a basic in vitro study.

Six kinds of fabrics of the same specification with different far-infrared nanoparticles were selected. MCF7 and Bcap37 breast cancer cells were used to study the effect of far-infrared fabrics on cell proliferation and invasion. Six kinds of far-infrared fabrics were used to culture breast cancer cells and explore their effects on breast cancer cell growth and the difference between different far-infrared fabrics.

It is found that the far-infrared emissivity of six kinds of fabrics are different, among which tea carbon fabric is the highest, followed by volcanic fabric, graphene fabric and biomass graphene fabric are the lowest. The results show that the far-infrared fabrics can significantly inhibit the proliferation and invasion of breast cancer cells, the higher the far-infrared emissivity is, and the longer the time of far-infrared radiation, the more significant the inhibition effect is.

Far-infrared fabrics can inhibit proliferation and invasion of breast cancer cells in vitro. Therefore, far-infrared fabrics can be used for adjuvant rehabilitation of breast cancer patients. This conclusion provides a basis for the application of far-infrared functional fabrics in the medical field. This conclusion provides a basis for the application of far-infrared functional fabrics in medical field.

Since 2004, subsidies increased by 670 percent in the Chinese fertilizer industry to reduce the farmer's burden. The purpose of this paper is to assess whether subsidies benefit the target groups, the fertilizer subsidy distribution pattern and benefit allocation pattern among fertilizer producers and other sectors were investigated.

The Muth model is extended to evaluate the impacts of a subsidy on multi-stage markets.

It is found that the total benefits from the policy are about RMB 7.7 billion yuans. The fertilizer suppliers gain about RMB 51 billion yuans from the favorable policy with mean subsidy incidence 0.8 and capturing about 70 percent of total surplus.

The results suggest that transferring parts of subsidies to the non-fertilizer sectors could be considered an efficient way to redistribute welfare indifferent sectors.

This study first use the equilibrium displacement model to quantity the distribution of fertilizer subsidy in a vertical market in China.

Purpose – The net increase in China's urban population in the last 50 years equals the current total population of the European Union. The scale and speed of urbanization in China requires a sustainable solution to unprecedented energy demands and elevated carbon emissions. As low-carbon development emerges in urban China, it offers a unique vantage point to examine some fundamental theoretical questions of the environmental state. How do structural socioeconomic changes affect the environmental state? Does the rise of the environmental state offer a basis for regulatory reform on a broader scale?

Methodology/approach – Case study of five low-carbon cities in China provides the empirical evidence for the analysis. The five cities represent a continuum in their levels of postindustrialization. I compare low-carbon development strategies in postindustrial cities with those strategies in industrial cities. Evidence is collected primarily by way of interviews with planning bureau officials, urban design professionals, involved NGOs, academics, and private sector individuals familiar with the matter.

Findings – First, in cities where the level of postindustrialization is high, state resources support innovative low-carbon development strategies that attempt to achieve emission reductions in a variety of sectors. In industrial cities, however, the environmental state's regulative power is limited to one or two (sub)sectors. Second, and more importantly, a new pattern of governance is emerging in postindustrial cities. Low-carbon development in postindustrial cities is a much less centralized process, having local levels of governments as key players of low-carbon policy making. When the environmental state intersects with the postindustrial city, it gives birth to a new urbanism that has profound implications for political structuring in China.

Research limitations – The analysis in this chapter is based on evidence from a purposefully selected set of Chinese cities, which may render the results biased. Future studies should aim for a more systematic analysis of cities in order to establish more generalizable conclusions. In addition, given the increasing availability of quantitative data at the city level in China, future studies should also seek to incorporate quantitative analyses to better substantiate existing knowledge derived from qualitative sources of evidence.

Originality/value of chapter – First, this chapter challenges the Western bias in the existing literature on the environmental state. The role of the civil society is far from salient in the Chinese context, and yet the environmental state demonstrates a robust level of activity despite the weak civil society. It therefore seems that a general theory of the environmental state can be built from existing literature, but needs to be sensitive to non-Western social conditions that might falsify parts of the theoretical claims. Second, the environmental state literature can be consolidated and further developed when examined in conjunction with other literatures in the modernity tradition. I have demonstrated the connection between the environmental state and the postindustrial city. More studies are needed to examine other facets of the environmental state, as it intersects with a multitude of (post)modern conditions.

The increase in demand variability created by manufacturing enterprises presents new challenges for increasing resource usage and sharing flexibility. For this reason, it is of great importance to research manufacturing grids and their service modes. The purpose of this paper is to establish a systematic strategy and a system tool for manufacturing grid systems.

A manufacturing service oriented manufacturing grid (MSoMG) system is presented with open grid service architecture as the system architecture and GT3.9 as a development tool. A framework is proposed to support MSoMG by providing advisory tools and methods for uncertain information analysis and processing, multi-objective decision making of manufacturing grid service execution, manufacturing grid service performance prediction based on knowledge template, and flexible manufacturing grid service scheduling and solution. The methodology of the adopted rough set is discussed in detail. Finally, the design support strategies for MSoMG are investigated to guide the coordination of manufacturing activities.

Many conventional methods and models become very limited for manufacturing grid service with uncertain information. The processing of uncertain information and reasonable application flow can help to improve the completion rate and reliability of manufacturing grid services.

This research provides a solid foundation for manufacturing gird operations and can promote the use of a manufacturing grid mode.

A MSoMG system is presented. The manufacturing grid service with uncertain information is considered as well as design support strategies.