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This study aims to research the large cross-section tunnel stability evaluation method corrected after considering the thickness-span ratio.

First, taking the Liuyuan Tunnel of Huanggang-Huangmei High-Speed Railway as an example and taking deflection of the third principal stress of the surrounding rock at a vault after tunnel excavation as the criterion, the critical buried depth of the large section tunnel was determined. Then, the strength reduction method was employed to calculate the tunnel safety factor under different rock classes and thickness-span ratios, and mathematical statistics was conducted to identify the relationships of the tunnel safety factor with the thickness-span ratio and the basic quality (BQ) index of the rock for different rock classes. Finally, the influences of thickness-span ratio, groundwater, initial stress of rock and structural attitude factors were considered to obtain the corrected BQ, based on which the stability of a large cross-section tunnel with a depth of more than 100 m during mechanized operation was analyzed. This evaluation method was then applied to Liuyuan Tunnel and Cimushan No. 2 Tunnel of Chongqing Urban Expressway for verification.

This study shows that under different rock classes, the tunnel safety factor is a strict power function of the thickness-span ratio, while a linear function of the BQ to some extent. It is more suitable to use the corrected BQ as a quantitative index to evaluate tunnel stability according to the actual conditions of the site.

The existing industry standards do not consider the influence of buried depth and span in the evaluation of tunnel stability. The stability evaluation method of large section tunnel considering the correction of overburden span ratio proposed in this paper achieves higher accuracy for the stability evaluation of surrounding rock in a full or large-section mechanized excavation of double line high-speed railway tunnels.

Despite recent organizational behavior studies have witnessed considerable progress in abusive supervision research; some demerits for both theory and methodology still remain in the past years. To clarify the current state of knowledge in the field, this study aims to analyze the current state of theories and methods on abusive supervision and provides a detailed future research agenda.

This paper conducted a literature review for both theory and methodology of the abusive supervision research using a content analysis of 134 publications.

For the theory part, this paper summarized the theories that had been applied to explain the relationship between abusive supervision and its consequences as well as antecedents. For the methodology part, this paper outlined some critical issues regarding country of origin, research design, measurement, analysis strategy and also summarized with a discussion of the relationship between methodological issues and article impact. Finally, this paper concluded by presenting an agenda for future abusive supervision research regarding both theory and methodology.

First, this paper summarizes the main theories, antecedents and consequences often used in abusive supervision research to allow scholars to carry out theoretically driven research investigating abusive supervision in the future. Second, through a content analysis of the methods sections of abusive supervision research in the samples (i.e. country of origin, research design, measurement and analytical procedures), this paper identified the potential reasons underlying the inconsistency in the conclusions of abusive supervision research and provide some guidance for future empirical studies. Third, based on the qualitative review, this paper provides an agenda for future research investigating abusive supervision by developing a content-specific theoretical framework to benchmark abusive supervision research against other research related to leadership and offers an accurate response to scholars’ criticisms of abusive supervision research.

For a better understanding of the preferences and differences of young consumers in emerging wine markets, this study aims to propose a clustering method to segment the super-new generation wine consumers based on their sensitivity to wine brand, origin and price and then conduct user profiles for segmented consumer groups from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences.

We first proposed a consumer clustering perspective based on their sensitivity to wine brand, origin and price and then conducted an adaptive density peak and label propagation layer-by-layer (ADPLP) clustering algorithm to segment consumers, which improved the issues of wrong centers' selection and inaccurate classification of remaining sample points for traditional DPC (DPeak clustering algorithm). Then, we built a consumer profile system from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences for segmented consumer groups.

In this study, 10 typical public datasets and 6 basic test algorithms are used to evaluate the proposed method, and the results showed that the ADPLP algorithm was optimal or suboptimal on 10 datasets with accuracy above 0.78. The average improvement in accuracy over the base DPC algorithm is 0.184. As an outcome of the wine consumer profiles, sensitive consumers prefer wines with medium prices of 100–400 CNY and more personalized brands and origins, while casual consumers are fond of popular brands, popular origins and low prices within 50 CNY. The wine sensory attributes preferred by super-new generation consumers are red, semi-dry, semi-sweet, still, fresh tasting, fruity, floral and low acid.

Young Chinese consumers are the main driver of wine consumption in the future. This paper provides a tool for decision-makers and marketers to identify the preferences of young consumers quickly which is meaningful and helpful for wine marketing.

In this study, the ADPLP algorithm was introduced for the first time. Subsequently, the user profile label system was constructed for segmented consumers to highlight their characteristics and demand partiality from three aspects: demographic characteristics, consumers' eating habits and consumers' preferences for wine attributes. Moreover, the ADPLP algorithm can be considered for user profiles on other alcoholic products.

Extant research has paid considerable attention to the effects of enterprise social media (ESM) on employees' work attitudes and outcomes, yet the authors know little about the influence of job demands arising from the implementation of ESM. Drawing on resource allocation theory, the purpose of this study is to unravel how ESM-related job demands influence employee outcomes.

This study conducts a two-wave time-lagged survey of 223 employees from 53 teams in 14 financial service firms in China to test the conceptual model.

The findings of this paper indicate that ESM-related job demands have indirect effects on employee outcomes (i.e. job satisfaction and work–family conflict), and emotional exhaustion plays an intermediary role in these relationships. Specifically, ESM-related job demands have a U-shaped effect on emotional exhaustion.

This study combines job demands with ESM research and clarifies the mechanism behind how ESM-related job demands at different intensity affect employee outcomes from a new perspective. Moreover, this study’s findings suggest several beneficial courses of action for managers to take advantage of ESM.

The purpose of this paper is to investigate the causal relationship between the prices of rice, crude oil, wheat, corn and soybean in China and estimate the long-run and short-run price relationships.

Using monthly price date over the period of January 1998-December 2013 in China, this paper employs an autoregressive distributed lag (ARDL) bounds test to explore the cointegration relationship among the price variables and estimate the ARDL long-run price relationship and the short-run error correction process (ARDL-EC).

The empirical results indicate that crude oil, as one of the forcing variables along with wheat, corn, and soybean prices, is effecting rice price in China. Both the long-run and short-run price transmission elasticity estimates suggest the importance of crude oil price on the formation of rice prices. Furthermore, the adjustment speed coefficient is found to be statistically significant, supporting the notion that there is an error correction mechanism for maintaining the long-run price relationship facing short-run shocks.

This paper adopts four types of commodity food prices to explore the relationships with crude oil price. The evidence of market integration, including the degree of price transmission and the speed of adjustment, remains a crucial step to proceed with the government intervention.

This paper analysed survey data of 715 rice-producing households in China to assess the determinants of adoption of five mutually exclusive soil conservation practices (SCPs) and their impact on rice yield and chemical fertiliser use.

The multinomial endogenous treatment effects model was used to account for selection bias and endogeneity arising from both observed and unobserved heterogeneity.

Farms that adopted SCPs as a package experienced an increase in rice yield and decrease in chemical fertiliser use. Adoption of SCPs as a package led to a 12.0% increase in yield and 15.2% decrease in chemical fertiliser use; these results have policy implications for the non-point source pollution control in the agricultural sector. In contrast, adoption of straw retention only significantly reduced yield by 4.9% and increased chemical fertiliser use by 18.1%.

The authors evaluate and compare multi-type of SCPs, such as straw retention, deep tillage and use of organic fertiliser, separately or in combination, and their impacts on smallholder farmers’ rice yield and chemical fertiliser usage.

According to the survey and measurement on rural housing in the Northeast severe cold regions of China, this paper analyzed the existing situation and problems of current rural housing in terms of integral development, functional layout, envelop structure, interior thermal environment, heating system and energy utilization etc.. Based on the climatic features of severe cold regions, as well as rural financial and technical conditions, living and production mode, residential construction characteristics and existing resource status etc., the feasible approaches of achieving building energy saving has been proposed, thus acting as a guidance for new rural housing design in severe cold regions.

The purpose of the paper is to investigate how cross-cultural elements such as cultural difference and stereotype are integrated into collaborative modes and actions and to explore their corresponding effectiveness.

The sample of the quantitative content analysis is drawn from the posts with the topic of China on Quora. A collaborative case, where two users have a question-and-answer interaction, is taken as the unit of analysis. The effectiveness of collaboration is operationalized as the extent to which a collaboratively produced answer is visited and favorably reviewed, using the feedback index (the number of upvotes*1,000/views). One of the sampled collaborative cases is further analyzed qualitatively to see how cultural differences, stereotypes and other factors are incorporated into users' interaction.

This content analysis reveals nine modes of collaborative production of knowledge on Quora: initial questioning, pointed answering, raising doubts, responding to others, agreeing with others, correcting mistakes, enriching content, further questioning and extending issues. Diversity of the cross-cultural acts of collaborative production, particularly two of often-used collaborative actions, correcting stereotypes and supplementing cultural differences, helps to enhance overall collaborative effectiveness.

This paper offers new perspectives and ideas for strategies to change socially problematic stereotypes, e.g. to correct stereotypes where necessary and use more convincing resources such as reliable images as collaborative actions to bridge cultural differences. It also calls on social Q&A website developers to create more international users-friendly design by providing various channels for users with diverse cultural backgrounds to interact with each other.

This study is one of the first to investigate online collaborative knowledge production within a broader cross-cultural context. Specifically, cultural factors and cross-cultural collaborative actions have been innovatively integrated into this research, enriching the dimensions that can be used for collaboration classification. It is helpful for users from different countries to actively adopting different strategies to overcome cultural differences, preconceptions and other negative factors that are not conducive to communication and knowledge acquisition.

Despite being an authentic carrier of various cultural practices, the human body is often underutilised to access the knowledge of human body. Digital inventions today have created new avenues to open up cultural data resources, yet mainly as apparatuses for well-annotated and object-based collections. Hence, there is a pressing need for empowering the representation of intangible expressions, particularly embodied knowledge within its cultural context. To address this issue, the authors propose to inspect the potential of machine learning methods to enhance archival knowledge interaction with intangible cultural heritage (ICH) materials.

This research adopts a novel approach by combining movement computing with knowledge-specific modelling to support retrieving through embodied cues, which is applied to a multimodal archive documenting the cultural heritage (CH) of Southern Chinese martial arts.

Through experimenting with a retrieval engine implemented using the Hong Kong Martial Arts Living Archive (HKMALA) datasets, this work validated the effectiveness of the developed approach in multimodal content retrieval and highlighted the potential for the multimodal's application in facilitating archival exploration and knowledge discoverability.

This work takes a knowledge-specific approach to invent an intelligent encoding approach through a deep-learning workflow. This article underlines that the convergence of algorithmic reckoning and content-centred design holds promise for transforming the paradigm of archival interaction, thereby augmenting knowledge transmission via more accessible CH materials.

Climatic changes caused by greenhouse gases (GHGs) emissions are an urgent challenge for all regions around the globe while the livestock sector is an important source of GHGs emissions. The adoption of low-carbon manure treatment technology (LMTT) by farmers is emerging as an effective remedy to neutralize the carbon emissions of livestock. This paper aims to incorporate environmental literacy and social norms into the analysis framework, with the aim of exploring the impact of environmental literacy and social norms on farmers' adoption of LMTT and finally reduce GHGs emission and climate effects.

This research survey is conducted in Hebei, Henan and Hubei provinces of China. First, this research measures environmental literacy from environmental cognition, skill and responsibility and describes social norms from descriptive and imperative social norms. Second, this paper explores the influence of environmental literacy and social norms on the adoption of LMTT by farmers using the logit model. Third, Logit model's instrumental approach, i.e. IV-Logit, is applied to address the simultaneous biases between environmental skill and farmers’ LMTT adoption. Finally, the research used a moderating model to analyze feasible paths of environmental literacy and social norms that impact the adoption of LMTT by farmers.

The results showed that environmental literacy and social norms significantly and positively affect the adoption of LMTT by farmers. In particular, the effects of environmental literacy on the adoption of LMTT by farmers are mainly contributed by environmental skill and responsibility. The enhancement of social norms on the adoption of LMTT by farmers is mainly due to the leading role of imperative social norms. Meanwhile, if the endogeneity caused by the reverse effect between environmental skill and farmers’ LMTT adoption is dealt with, the role of environmental skill will be weakened. Additionally, LMTT technologies consist of energy and resource technologies. Compared to energy technology, social norms have a more substantial moderating effect on environmental literacy, affecting the adoption of farmer resource technology.

To the best of the authors’ knowledge, a novel attempt is made to examine the effects of environmental literacy and social norms on the adoption of LMTT by farmers, with the objective of identifying more effective factors to increase the intensity of LMTT adoption by farmers.