Search results

This study aims to uncover the black box of the influence mechanism between external stakeholder drivers and green public procurement practice, and meanwhile to explore the moderating role of administrative level in this process. Green public procurement (GPP) has been widely implemented. Existing literature has found that external stakeholder drivers can affect public sectors' GPP practice, however, the definition of its connotation is still unclear, and how external stakeholders affect GPP practice has remained a black box.

After defining the major external stakeholders, this study develops a multiple mediation theoretical model using survey data from 142 Chinese local public sectors. It aims to uncover the black box of the influence mechanism between external stakeholder drivers and GPP practice and meanwhile explore the moderating effect of administrative levels in this process.

The results show that external stakeholder drivers have a positive relationship with GPP practices. The knowledge of GPP implementation policies and the knowledge of GPP benefits can both mediate this relationship. This study also finds that the administrative level of public sectors can positively moderate the mediating effect produced by the knowledge of GPP implementation policies and negatively moderate the mediation effect produced by the knowledge of GPP benefits.

Local governments need to better encourage public sectors to implement GPP. Managers of public sectors need to pay attention to organizational learning to acquire relevant knowledge on GPP.

This study makes a theoretical contribution to a better understanding of the influence mechanism for GPP practice. This study also provides comparisons of GPP implementation policies between China and European Union.

The purpose of this paper is to provide managers with suitable strategic KPIs in decision-making processes, which aim to integrate the environmental dimension of sustainability at a business level in manufacturing organisations.

In view of the research proposal addressed, semi-structured interviews were conducted, based on theoretical milestones of the performance management system (PMS), with 48 managers that work in Italian manufacturing firms and specialise in green practices.

The authors developed a novel environmentally performed framework to adequately integrate environmental value drivers at a strategic level.

The resulting issues addressed in this paper, and their integration in the business strategy for managing environmental complexity, allows contributing, firstly, to the existing literature by suggesting the relevant key value drivers that need to be mostly studied from an accounting point of view. In addition, from these results, though their experience managers will have up-to-date key measures that could, in the future, help the integration process between the environmental aspect of the sustainability dimension and the PMS.

The results generate a robust roadmap for future analysis in this research field. Accordingly, the paper engenders a strategic alignment in the green transition process, providing scholars and practitioners with a clear view of the key sustainable drivers, metrics and potential solutions that have not been addressed to date.

The purpose of this paper is to investigate the effect of the Q‐switching parameters on the sintering behavior of laser micro sintering Cu‐based metal powder, using Q‐switched 1064 nm Nd‐YAG laser.

An experimental study has been performed. Metal powder mixture with Cu and Cu‐P alloy powders has been utilized. Q‐switching duration of 15 μs∼25 μs, rate of 25 kHz∼45 kHz have been used.

The results show that as the Q‐switching rate and duration increases, the peak laser power decreases and the densification enhances. However, an optimal peak laser power exists and if the peak laser power is too low, the density of the sample is also low. The densification regime of laser micro‐sintering is not only caused by the liquid phase filling the pores, but is also caused by the Cu powder migrating and by coalescence, e.g. including initial stage and intermediate stage of the traditional furnace liquid phase sintering. However, the degree of these stages depends on the peak power and input laser energy.

The effect of the Q‐switching parameters on sintering behavior of laser micro sintering Cu‐based metal powder using Q‐switched 1064 nm Nd‐YAG laser has been obtained. It is found that the densification behavior is Q‐switching parameters dependent, although the average laser power is same. The densification regime of laser micro‐sintering includes initial stage and intermediate stage of the traditional furnace liquid phase sintering, but the degree is Q‐switching parameters dependent.

Green consumption behaviour (GCB) has been advocated to mitigate the environmental consequences of traditional consumption patterns. Besides the current circumstances, Generation Z college students are a sizable consumer group who are likely to be concerned about the future. Thus, this study aims to examine the factors affecting the college students’ GCB and the moderating effect of government support to provide new evidence from college students in China.

In addition to environmental knowledge and social media influence as the variables, government support was used as a moderator to develop the extended theory of planned behaviour (TPB) model. Purposive sampling was used to obtain 328 valid responses from Chinese college students. The collected data were analysed using partial least squares structural equation modelling.

The findings indicated that subjective norms, perceived behavioural control, environmental knowledge and social media influence substantially affect students’ GCB. Notably, the moderation analysis suggested that government support greatly strengthens the relationship between subjective norms and social media influence on the GCB of Chinese college students.

The study provides several significant practical implications as the findings could be referred by stakeholders, such as government and businesses entities, in formulating policies and strategies to encourage the consumers’ GCB in mitigating ecological consequences.

The extended TPB model that integrated environmental knowledge and social media influence with the government support as the moderator contributes to the extant literature with the evidence derived from Generation Z in China.

The WeChat mini-program is a new channel for the delivery of online and mobile services, including electronic government services. Given the distinguishing characteristics and new business model of WeChat mini-programs, additional studies of mini-program-based government services are warranted. The purpose of this paper is to identify the factors that determine user adoption and usage of government WeChat mini-programs (GWMPs).

An empirical study was conducted through an online survey of Chinese GWMPs users. The proposed model was tested by analyzing the collected data using the covariance-based structural equation modeling approach.

The findings show that trust in government, trust in WeChat, trust in GWMPs and perceived convenience have significant effects on the usage of GWMPs.

This study contributes to the understanding of the GWMPs and mini-program-based government phenomenon. Theoretical implications for future e-government research as well as practical suggestions for GWMPs operators are also discussed.

The research on structure function recognition mainly concentrates on identifying a specific part of academic literature and its applicability in the multidiscipline perspective. A specific part of academic literature, such as sentences, paragraphs and chapter contents are also called a level of academic literature in this paper. There are a few comparative research works on the relationship between models, disciplines and levels in the process of structure function recognition. In view of this, comparative research on structure function recognition based on deep learning has been conducted in this paper.

An experimental corpus, including the academic literature of traditional Chinese medicine, library and information science, computer science, environmental science and phytology, was constructed. Meanwhile, deep learning models such as convolutional neural networks (CNN), long and short-term memory (LSTM) and bidirectional encoder representation from transformers (BERT) were used. The comparative experiments of structure function recognition were conducted with the help of the deep learning models from the multilevel perspective.

The experimental results showed that (1) the BERT model performed best, with F1 values of 78.02, 89.41 and 94.88%, respectively at the level of sentence, paragraph and chapter content. (2) The deep learning models performed better on the academic literature of traditional Chinese medicine than on other disciplines in most cases, e.g. F1 values of CNN, LSTM and BERT, respectively arrived at 71.14, 69.96 and 78.02% at the level of sentence. (3) The deep learning models performed better at the level of chapter content than other levels, the maximum F1 values of CNN, LSTM and BERT at 91.92, 74.90 and 94.88%, respectively. Furthermore, the confusion matrix of recognition results on the academic literature was introduced to find out the reason for misrecognition.

This paper may inspire other research on structure function recognition, and provide a valuable reference for the analysis of influencing factors.

The objectives of this study are to examine the impacts of CSR on purchase intentions either directly or indirectly and to investigate the moderating effects of consumer ethnocentrism on the relationship between CSR and purchase intentions.

This study utilized an online self-administered survey for data collection. All the measurement items were adopted or adapted from prior research concerning international marketing (Churchill, 1979). Concerning rating scales, the items of CSR, brand attitudes, and consumer ethnocentrism were measured from 1 (strongly disagree) to 7 (strongly agree), and the items of purchase intentions were measured from 1 (strongly disagree) to 5 (strongly agree).

The empirical findings suggest that CSR significantly influences purchase intentions directly and indirectly via brand attitudes. Besides, consumer ethnocentrism strengthens the positive effects of CSR on brand attitudes and purchase intentions.

This research sheds light on young Chinese consumers' purchase behaviors, which could facilitate Western brands implementing effective and efficient marketing strategies in the Chinese market.

This paper aims to study the initial trust of the owner to the contractor, establish the initial trust mechanism, explore the factors that affect the initial trust of the owner to the contractor and analyze its influence mechanism. Based on this, it is easy for the owners and contractors to take targeted measures to improve the initial trust, which is conducive to the sustainable development of the project.

On the basis of reading a large amount of literature, this paper constructs the occurrence mechanism of the owner's initial trust to the contractor from the five factors of trust propensity, trust belief, trustee’s characteristics, institution-based trust, trust motivation and from the perspective of the owner using the structural equation model for questionnaire survey and empirical analysis.

The results of this paper show that the institution-based trust, the trustee’s characteristics and the trust belief of the trustor clearly have a positive effect on trust motivation, and the trustee’s characteristics have the most significant effect on the trust motivation. The influence of trust propensity on trust motivation was not significant.

This paper studies the occurrence mechanism of the owner's initial trust in the contractor, discusses its influencing factors and analyzes the influence of these factors on the initial trust, which enriches the theoretical system of initial trust research. The results of this study can help owners and contractors to develop targeted measures to build good initial trust.

The purpose of this paper is to explore the Chinese microblog users’ psychological motivations and the association between users’ motivations and their offline civic and political engagement. Specifically, this study examines what the psychological impetuses of Weibo use are and how they promote the young citizens’ civic and political involvement.

The data were collected through the web-based survey with a total sample of 426 people. Principal components factor analysis, correlation analysis, and hierarchical multiple regressions were sequentially carried out to address the research questions.

The findings reveal that there are four major motives for using Weibo: information, socializing, recognition seeking and entertainment. Interestingly, seeking social needs is positively and significantly related to increasing young people’s civic participation, but not political participation.

Theoretically, the research demonstrates that the uses and gratifications is a suitable approach for analysis of psychological antecedents of Weibo use and subsequent outcomes. Practically, it will help understand the dynamics of how the new media technology may engender democratic development and change.

Although the growing significance of social media has drawn considerable attention, little research has been conducted to assess the political consequences of Weibo. The current study fills the void by investigating whether Weibo functions as an effective tool to facilitate democratic engagement in contemporary China. The obtained results may provide insight into the relationship between the gratification structures and engagement in other social settings.

In recent years, Chinese sentiment analysis has made great progress, but the characteristics of the language itself and downstream task requirements were not explored thoroughly. It is not practical to directly migrate achievements obtained in English sentiment analysis to the analysis of Chinese because of the huge difference between the two languages.

In view of the particularity of Chinese text and the requirement of sentiment analysis, a Chinese sentiment analysis model integrating multi-granularity semantic features is proposed in this paper. This model introduces the radical and part-of-speech features based on the character and word features, with the application of bidirectional long short-term memory, attention mechanism and recurrent convolutional neural network.

The comparative experiments showed that the F1 values of this model reaches 88.28 and 84.80 per cent on the man-made dataset and the NLPECC dataset, respectively. Meanwhile, an ablation experiment was conducted to verify the effectiveness of attention mechanism, part of speech, radical, character and word factors in Chinese sentiment analysis. The performance of the proposed model exceeds that of existing models to some extent.

The academic contribution of this paper is as follows: first, in view of the particularity of Chinese texts and the requirement of sentiment analysis, this paper focuses on solving the deficiency problem of Chinese sentiment analysis under the big data context. Second, this paper borrows ideas from multiple interdisciplinary frontier theories and methods, such as information science, linguistics and artificial intelligence, which makes it innovative and comprehensive. Finally, this paper deeply integrates multi-granularity semantic features such as character, word, radical and part of speech, which further complements the theoretical framework and method system of Chinese sentiment analysis.