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The surging market demand for green construction materials has brought opportunities for construction materials enterprises' greenwashing behavior (GWB). This study aims to establish the causal relationship among the influencing factors of GWB and reveal the key influencing factors from the perspective of Chinese construction materials enterprises under multi-agent interactions.

This study is based on stakeholder theory, resource-based theory and the green development behavior and performance of industrial enterprises (GDBP-IE). First, with the literature analysis, an index framework of the influencing factors of enterprises' GWB was constructed from five dimensions (including 15 factors): environmental regulation, public scrutiny, market environment, corporate resources and corporate green development (GD) performance. Second, the interactive relationship among influencing factors was obtained by a questionnaire survey. Finally, the data are processed and analyzed with the grey-DEMATEL (Decision-making Trial and Evaluation Laboratory) method.

Among the factors, corporate information transparency has the greatest impact on the other factors, and consumer green preferences are most influenced by others. The most critical and important factor is the corporate social performance factor. In China, corporate social performance, corporate information transparency, corporate size and media supervision are the key factors influencing the GWB of construction materials enterprises.

This study provides a new perspective on the literature related to GWB by considering multi-agent interactions and extends the evidence from the construction materials industry for research on the drivers or influencing factors of enterprises' bad environmental behavior. Furthermore, it adds insights from China for further research on the governance strategies of GWB in other countries.

This paper aims to investigate whether a complementary effect exists between government R&D subsidies (GRSs) and intellectual property rights (IPR) protection on innovation performance in the pharmaceutical manufacturing industry in China. This paper also attempts to understand whether this complementary effect is significantly different across China’s eastern, central and western regions.

The study sample comprised 28 provinces involved in the pharmaceutical manufacturing industry in China from 2003 to 2014. Ordinary least squares was used to test the complementary effects of GRSs and IPR protection on innovation performance. The seemingly unrelated estimation test was also applied to ascertain whether differences existed between the eastern and western regions.

A complementary effect between GRSs and IPR protection in terms of improving the innovation of pharmaceutical manufacturers was found to exist only in eastern and western regions. There was no significant difference in the complementary effect between GRSs and IPR protection in terms of improving innovation among the three regions. Without considering the interaction effect of GRSs and IPR protection, the GRSs were negatively associated with innovation in the eastern region, but positively related to the innovation in central region.

This study contributes to the literature on government policies and innovation by incorporating the interaction effect of GRSs and IPR protection on innovation in the context of a high-tech industry (pharmaceutical manufacturing) in an emerging economy (China). It also explores the internal differences in the influence of this complementary effect on innovation in an emerging economy, enriching the institution-based view.

Open government data (OGD) is a comparatively new field in e-government and the factors influencing its continuance use by citizens have not been extensively explored. A better understanding of these factors can help the government to articulate strategies and policies that can advance the acceptance and use of OGD technologies. Thus, this paper aims to empirically determine the predictors influencing the continuance usage intention of OGD technologies.

Following an empirical investigation among 370 respondents in Bangladesh, a developing country, the paper applied path analysis using the structural equation modeling approach. The unified theory of acceptance and use of the technology model is integrated with the information system continuance model to investigate the continuance usage intention of OGD technologies.

The outcomes of this study reveal that performance expectancy, effort expectancy, social influence and facilitating conditions (FC) directly affect users’ satisfaction (SAT). In addition, SAT and FC were found statistically significant toward continuance usage intention of OGD technologies.

The findings of this study suggest policymaker and OGD providers to formulate or modify their strategies to retain the existing OGD users and stimulate persistence usage.

Facilitating long-term use by citizens would increase their engagement and they might derive value from the OGD platforms. Concurrently, the government’s objective of ensuring increased future use of OGD technologies would be better realized.

The novelty of this study lies in the fact that it addresses a previously overlooked area of open data research, namely, the acceptance and use of open data technologies and ways to stimulate it. This study has contributed to the existing but limited literature on continuance usage intention of OGD technologies in the context of a developing country.

Because of the inconvenience and inflexibility of the laser controller, the applied range of optogenetics is limited. This paper aims to present the design of a portable remote-controlled laser controller system, including the remote-controlled system and the laser stimulator.

The remote-controlled system is handheld, which can wirelessly adjust the power and the emitting frequency of the laser by utilizing the ZigBee module.

The laser stimulator can be mounted on the animal as it is light weight (35 g) and small in size (40 × 40 × 20 mm), and its power and frequency can be appropriately adjusted by changing the current amplitude and duty radio. In the end, the experiments verify the reliability and effectiveness of the laser controller.

In virtue of the modular design of the driven circuit and the reasonable layout, the whole system has the advantages of small volume, convenient control and high stability, which provide the convenience for the development of portable optogenetics animal robot experiment and has broad market prospects.

This study examined the factors influencing willingness-to-repurchase for each class of airline service, and integrate the constructs of service quality, satisfaction and willingness-to-repurchase which were rooted on Engel-Kollat-Blackwell (EKB) model. The study focuses on the domestic and international arrival of passengers at Murtala Muhammed International Airport in Lagos and Nnamdi Azikwe International Airport in Abuja. Information was gathered from domestic and foreign passengers who had post-purchase experience and had used the airline's services more than once. The survey data were obtained concurrently from arrival passengers at two major international airports using an electronic questionnaire through random and purposive sampling techniques. The data was analysed using the ordinal logit model and structural equation model. From the 606 respondents, 524 responses were received but 489 responses were valid for data analysis and reporting and were obtained mostly from economy and business class passengers. The study found that the quality of seat pitch, allowance of 30 kg luggage permission, availability of online check-in 24 hours before the departing flight, quality of space for legroom between seats, and the quality of seats that can be converted into a fully flatbed are the major service factors influencing willingness-to-repurchase economy and business class tickets. Also, it was found that passengers' willingness to repurchase is influenced majorly by service quality, but not necessarily influenced by satisfaction. These results reflect the passengers' consciousness of COVID-19 because the study was conducted during the heat of COVID-19 pandemic. Recommendations were suggested for airline management based on each class.

Entrepreneurial boundaries and activities have changed with the widespread use of digital technologies. However, few studies have examined DTA’s effect on opportunity recognition, leading to a vague understanding of this relationship.

Building on the digital entrepreneurship perspective, we explore the underlying mediating mechanism and contextual conditions in the relationship between digital technology application (DTA) and opportunity recognition using data from Chinese entrepreneurial firms.

DTA positively affects opportunity recognition and network strategy mediates the relationship between DTA and opportunity recognition. Environmental uncertainty positively moderates DTA’s indirect effect on opportunity recognition through network strategies.

Our findings contribute to digital entrepreneurship literature by explaining how DTA promotes entrepreneurial firms’ opportunity recognition through network strategies.

This study aims to detect consumer sarcasm through inconsistencies in sentiment features between text and images of hotel reviews.

This paper proposes a model for sarcasm detection based on multimodal deep learning using reviews of three hotel brands collected from two travel platforms, which can identify emotional inconsistencies within a modality and across modalities. Text-image interaction information is explored using graph neural networks (GNN) to detect essential clues in sarcasm sentiment.

The research results show that the multimodal deep learning model outperforms other baseline models, which can help to understand hotel service evaluation and provide hotel managers with decision-making opinions.

This research can help hoteliers in two ways: detecting service quality and formulating strategies. By selecting reference hotel brands, hoteliers can better assess their level of service quality (optimal resource allocation ensues); therefore, sarcasm detection research is not only beneficial for hotel managers seeking to improve service quality. The multimodal deep learning method introduced in the present study can be replicated in other industries to help travel platforms optimize their products and services.

本研究通过分析酒店评论文本和图像之间情感特征的不一致性来检测消费者的讽刺。

本文提出了一种基于多模态深度学习的讽刺检测模型, 使用从两个旅行平台收集的三个酒店品牌的评论, 该模型能够识别模态内部和模态之间的情感不一致性。利用图神经网络（GNN）探索文本-图像交互信息, 以检测讽刺情感中的关键线索。

研究结果显示, 多模态深度学习模型优于其他基线模型, 这有助于理解酒店服务评估, 并为酒店经理提供决策建议。

该研究可以在两方面帮助酒店业者：检测服务质量和制定策略。通过选择参考酒店品牌, 酒店业者可以更好地评估其服务质量水平（随之而来的是最佳资源分配）, 因此, 讽刺检测研究不仅有助于寻求提高服务质量的酒店经理。本研究介绍的多模态深度学习方法可以在其他行业复制, 帮助旅行平台优化其产品和服务。

This study aimed to investigate associations between the organisational and cultural contexts in which Chinese teachers work, the influence of these on their understandings of professionalism, and relationships between these and their perceived willingness and commitment to be effective in teaching to their best.

The research was part of a two-country collaboration between the universities of Beijing and Sydney into Australian and Chinese teachers' perceptions of influences on their professionalism in which research protocols were jointly developed and implemented. This paper focusses mainly upon the Chinese research but also refers to key differences between Australian and Chinese teachers' perspectives. Seventeen teachers in early, middle and later career phases were recruited from a convenience sample of primary and secondary schools in Beijing. Qualitative data analyses of individual interviews, and cross case comparative analyses were conducted.

The analyses of the data from Beijing indicated that almost all teachers emphasised their strong moral purposes and commitment to teach to their best, despite identifying the challenges of workload, school contexts and cultures and personal circumstances, which tested their resolve. In contrast, concerns about teacher autonomy and agency, which were common in the Australian study and other published research literature, were not highly visible in the Chinese data.

The authors acknowledge that this study was small scale and data were collected from a narrow sample from one urban region of China, and we should be cautious with the generalisability of findings to other regions and schools of China since there are significant discrepancies between developed coastal areas and large cities and the remote rural areas in China. Furthermore, interview data were only collected once, restricting insight to a snapshot in time. This research may be seen as an encouragement to researchers from other regions and countries to further explore the impact of socially situated understandings of teacher professionalism on practice. Future research could also benefit from utilising multiple data sources, longitudinal design and cross-cultural collaborations to further explore the challenge of defining teachers' understandings of professionalism locally while engaging with global perspectives.

The practical implications relate to (1) expanding conceptualisations of teacher professionalism by developing locally nuanced understandings of perceptions and enactments of professionalism in different contexts across the profession, which take account of the unique roles of national and local cultural contexts; (2) designing initial teacher education and continuing professional development programmes so that they take account of the influences on the professions' ideals and individual teacher identities, of the ideological and practical interplay in the workplace of structures such as mandated standards, and different socio-economic geographical settings (e.g. rural and urban); (3) designing leadership development programmes that take account of research on associations between school leaders' values, qualities and practices on school cultures and their effects on teachers' well-being, and capacities and capabilities to fulfil their understandings of being professionals and teach to their best.

The social implications relate to (1) further research on the associations between the effects of external policy demands on teachers' work and work–life tensions, teachers' sustained commitment and quality; and (2) further research on the impact of the collective influences of national cultures, broad-based policy conditions, personal values and the demands of particular schools, parents and students that influence teachers' experience, perceptions and enactments of professionalism in order to provide further insights into understanding the complexity of teachers' lives and promoting teachers' sustained enactments of professionalism in broad contexts.

The research findings, though tentative, revealed that the altruistic nature of their mission to serve students and the parental community was the dominant marker of professionalism for teachers in China, regardless of school structures, cultures, academic achievement imperatives and personal circumstance; and that their professionalism was informed by the socio-cultural formation of individual and collective moral responsibility, reinforced through national educational policies. These findings differed from the concerns reported by the teachers in the Australian study, which aligned with literature that suggests that teacher professionalism is being eroded through neo-liberal government policies, excessive workloads and performance-oriented cultures. Though the comparative data set is small, these findings suggest that whilst there are increasing policy convergences across nations, which seek to define teacher professionalism through their abilities to make improvements in students' measurable academic achievement, how teachers in different countries and cultures define themselves as professionals may differ.

Ensuring quality is one of the most significant challenges in microtask crowdsourcing tasks. Aggregation of the collected data from the crowd is one of the important steps to infer the correct answer, but the existing study seems to be limited to the single-step task. This study aims to look at multiple-step classification tasks and understand aggregation in such cases; hence, it is useful for assessing the classification quality.

The authors present a model to capture the information of the workflow, questions and answers for both single- and multiple-question classification tasks. They propose an adapted approach on top of the classic approach so that the model can handle tasks with several multiple-choice questions in general instead of a specific domain or any specific hierarchical classifications. They evaluate their approach with three representative tasks from existing citizen science projects in which they have the gold standard created by experts.

The results show that the approach can provide significant improvements to the overall classification accuracy. The authors’ analysis also demonstrates that all algorithms can achieve higher accuracy for the volunteer- versus paid-generated data sets for the same task. Furthermore, the authors observed interesting patterns in the relationship between the performance of different algorithms and workflow-specific factors including the number of steps and the number of available options in each step.

Due to the nature of crowdsourcing, aggregating the collected data is an important process to understand the quality of crowdsourcing results. Different inference algorithms have been studied for simple microtasks consisting of single questions with two or more answers. However, as classification tasks typically contain many questions, the proposed method can be applied to a wide range of tasks including both single- and multiple-question classification tasks.

Researchers have noticed that in efficiency assessment, some attributes exhibit specializations including non-discretionary, non-controllable or undesirable. This paper aims to focus on other special factors which have target levels to achieve, i.e. the inputs (outputs) are no longer the-less-the-better (the-more-the-better).

In this paper, the authors further study the target variables when some attributes have multiple levels of targets. Such a situation can be found in many operational efficiency evaluations with various targets or bounded scale in inputs or outputs. They suppose that decision-making units (DMUs), reaching any target level, are identical efficient. To some extent, it is mitigation between common targets and individual targets. Using the closest target rule, the authors propose a target-level-oriented method to evaluate DMUs locally.

First, the authors found that some factors have multiple levels of targets to improve its efficiency in real world practice. Second, the proposed technique is able to deal with the multiple-levels-targets problems in data envelopment analysis (DEA) framework. Third, the decision-maker can select the improvement directions more freely than that in the traditional setting.

First, this is the first paper to discuss the multiple-levels-targets problems in DEA framework. Second, the proposed technique can help the decision-maker to select the best improvement strategies. Third, the technique developed in this paper can be used in many areas. For example, it can support the environmental efficiency evaluation with different standards of pollution emission.