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There are many safety hazards in construction workplaces, and inattention to the hazards is the main reason why construction workers failed to identify the hazards. Reasonably allocating attention during hazard identification is critical for construction workers’ safety. However, adverse working environments in job sites may undermine workers’ attention. Previous studies failed to investigate the impacts of environmental factors on attention allocation, which hinders taking appropriate measures to eliminate safety incidents when encountering adverse working environments. This study aims to examine the effects of workplace noise and heat exposure on workers’ attention allocation during construction hazard identification to fill the research gap.

This study applied an experimental study where a within-subject experiment was designed. Fifteen construction workers were invited to perform hazard identification tasks in panoramic virtual reality. They were exposed to three noise levels (60, 85 and 100 dBA) in four thermal conditions (26°C, 50% RH; 33°C, 50% RH; 30°C, 70% RH; 33°C, 70% RH). Their eye movements were recorded to indicate their attention allocation under each condition.

The results show that noise exposure reduced workers’ attention to hazardous areas and the impacts increased with the noise level. Heat exposure also reduced the attention, but it did not increase with the heat stress but with subjects’ thermal discomfort. The attention was impacted more by noise than heat exposure. Noise exposure in the hot climate should be more noteworthy because lower levels of noise would lead to significant changes. These visual characteristics led to poorer identification accuracy.

This study could extend the understanding of the relationship between adverse environmental factors and construction safety. Understanding the intrinsic reasons for workers' failed identification may also provide insights for the industry to enhance construction safety under adverse environments.

The overload of user-generated content in online mental health community makes the focus and resonance tendencies of the participating groups less clear. Thus, the purpose of this paper is to build an early identification mechanism for users' high attention content to promote early intervention and effective dissemination of professional medical guidance.

We decouple the identification mechanism from two processes: early feature combing and algorithmic model construction. Firstly, based on the differentiated needs and concerns of the participant groups, the multiple features of “information content + source users” are refined. Secondly, a multi-level fusion model is constructed for features processing. Specifically, Bidirectional Encoder Representation from Transformers (BERT)-Bi-directional Long-Short Term Memory (BiLSTM)-Linear are used to refine the semantic features, while Graph Attention Networks (GAT) is used to capture the entity attributes and relation features. Finally, the Convolutional Neural Network (CNN) is used to optimize the multi-level fusion features.

The results show that the ACC of the multi-level fusion model is 84.42%, F1 is 79.43% and R is 76.71%. Compared with other baseline models and single feature elements, the ACC and F1 values are improved to different degrees.

The originality of this paper lies in analyzing multiple features based on early stages and constructing a new multi-level fusion model for processing. Further, the study is valuable for the orientation of psychological patients' needs and early guidance of professional medical care.

The purpose of this study is to examine the role of retail investors’ green attention in promoting corporate environmental investments (EIs) using a communication sample on “Hudongyi” from 2011 to 2022.

In this paper, Python is used to capture data and text analysis techniques to obtain green attention information. In the word-matching process, words are matched in the target document one by one based on the preset dictionary and vocabulary rules. In addition to employing fixed effects, this study also incorporates instrumental variables using two-stage least squares (2SLS) estimation and applies the Heckman two-step method to verify the regression results.

First, this paper empirically examines the positive influence of retail investors’ green attention on EIs. Second, the findings show that retail investors’ green attention promotes EIs through decreasing principal-agent costs and principal-principal costs. Third, the results show that retail investor’s supervision effect is strengthened under the following three circumstances: executives with stronger green conception, corporations with less information asymmetry and areas with higher level of investor protection.

Our findings broaden the scope of prior research by exploring the impact of retail investor activism on nonfinancial outcomes, contributing to understanding the “black box” of how investor attention fosters EIs. Moreover, by leveraging the power of technology, retail investors have evolved from being the “silent majority” to being actively engaged. The internet has empowered retail investors by providing them with access to information and enabling them to exercise “voice” rights by appealing companies to engage in pro-environmental activities. Our study can provide useful suggestions for the green development of listed companies in China, as well as in other emerging countries.

Unlike other studies that focus on the deterrent effect and corporate financial outcomes of retail investors, we focus on the supervisory effect of retail investors and verify its role in driving EIs. This fills the knowledge gap in prior studies and contributes new insights to explain EIs and extends the understanding of retail investor activism.

Football stadiums, traditionally linked to local landmarks, now see a shift as corporate brands engage in naming rights through sponsorship. However, limited scholarly attention has focused on the perception of stadium toponyms. This research initiative aims to gauge attention garnered by football stadiums in Europe and China based on various naming rights options.

Commencing with a well-known European stadium: Allianz Arena (Munich) and new constructed stadium in China, the original naming rights have been proffered as stimuli, in comparison with two major technology brands as well as Coca-Cola, the historical sponsor of sport mega-events. A sample of 100 participants was analyzed using the eye-tracking technique to compare the perceptions of European and Chinese youth.

The conclusion drawn from the study is that for stadiums with a history of sponsorship, unedited versions of the pictures attract the most attention. Compared with technology brand, Coca-cola is the brand with the greatest ability to attract the attention of young people in both historical stadiums or new constructed stadium, acting as an impulse to the activation of the naming rights strategy due to its historical character as a sponsor of mega sporting events.

The research makes dual contributions, both theoretically and practically. It enhances comprehension of audience visual attention patterns in the context of football stadium naming rights sponsorship, employing cognitive attention theory to substantiate empirical evidence. Furthermore, it advances the existing literature on football stadium naming rights research. Additionally, it proposes an optimization tool to assess the effectiveness of naming rights sponsorships, offering valuable insights for companies and brands seeking to enhance their marketing strategies.

Understanding the effect of assortment composition on attentional levels is an essential topic for academic researchers and practitioners. This work has important implications when analyzing the influence of shopping frame time and search effort on the relationship between the reaction to assortment composition and visual attention to stock-keeping units (SKUs) pricing.

Two experimental studies through gauze behavior analysis technology (using eye-tracking equipment) analyze the variable's large assortment, visual attention to SKU pricing, search effort and shopping frame time.

The results suggest that, although it increases the search effort, a large assortment decreases the visual attention to SKU pricing. Further, our results indicate a moderating effect associated with mitigating the negative effect by medium-low levels of search effort and a moderating impact of time in this relation.

Marketing professionals can carefully optimize the in-store experience by managing the assortment and variety and by influencing consumers' visual attention to SKU pricing along the journey as part of the experience. Assortment and SKU pricing strategies need to be aligned with consumer journey design.

Our findings contribute to assortment theory and management by detailing the relationship between consumers' reactions to assortment perception and visual attention to SKU pricing in time flow. We reinforce the importance of considering assortment strategies from the consumer perspective and giving reliable information about in-store behavior.

Based on the attention-based view (ABV), this study examines the mechanism of external pressure and internal managerial interpretation affecting the promotion of green entrepreneurial orientation (GEO) of agricultural enterprises.

Based on data collected from 208 agricultural enterprises in China, the conceptual model was tested by using hierarchical regression.

The results show that managerial interpretation can affect the promotion of GEO. Command and control regulation, market-based regulation and green market pressure are important external pressures that affect the promotion of GEO. In addition, managerial interpretation mediates the relationship between command and control regulation and GEO, market-based regulation and GEO, as well as green market pressure and GEO.

This study proposes a key path for promoting the adoption and implementation of GEO by agricultural enterprises. The research results provide experience for emerging and developing countries to promote the GEO of agricultural enterprises, which is helpful to alleviate the environmental problems caused by the development of agricultural enterprises.

For the first time, this study introduced the ABV into the research of GEO. The research results enrich the theoretical perspective of GEO and expand the research field of the ABV. In addition, this study fills the research gap that existing research has not paid enough attention to the internal driving factors of GEO and opens the black box between the external pressure and GEO.

As China's economy begins to transform into a high-quality development, and under the national “carbon peak and carbon neutral” target, all sectors of society and industries need to transform to green development to varying degrees, coupled with the catalyst of epidemics and other factors, new development requirements are put forward for enterprises to better fulfill their climate risk disclosure behaviors. Thus, it is clear that improving corporate climate risk disclosure is of far-reaching significance to both countries and enterprises.

This study incorporates management science, psychology and other related knowledge fields, based on stakeholder theory and media dependency theory, and aims to improve the level of corporate compliance with climate risk disclosure, suggesting the influence of entrepreneurs' visibility on corporate climate risk disclosure; on this basis, the role of entrepreneurs' visibility and media attention on corporate climate risk disclosure is verified through an empirical model; finally, targeted and effective response strategies are proposed to improve corporate climate risk disclosure, set reasonable media attention and increase the effectiveness of entrepreneurs' visibility.

This paper establishes a multiple regression model using A-share listed companies in China from 2016 to 2022 as the research sample, verifies the intrinsic association between entrepreneurial visibility and corporate climate risk climate disclosure through empirical analysis, and further examines the mediating role of media attention in the relationship between the two. The results show that entrepreneurs' visibility is positively related to the level of corporate climate risk disclosure, with media attention playing a part in mediating the relationship between the two. Increasing entrepreneurs' visibility is conducive to increasing the level of corporate climate risk disclosure. Therefore, it contributes to the dual incentive effect of reputation and compensation.

This study incorporates management science, psychology and other related knowledge fields, based on stakeholder theory and media dependency theory, and aims to improve the level of corporate compliance with climate risk disclosure, suggesting the influence of entrepreneurs' visibility on corporate climate risk disclosure; on this basis, the role of entrepreneurs' visibility and media attention on corporate climate risk disclosure is verified through an empirical model; finally, targeted and effective response strategies are proposed to improve corporate climate risk disclosure, set reasonable media attention and increase the effectiveness of entrepreneurs' visibility.

The anomaly detection task for oil and gas pipelines based on acoustic signals faces issues such as background noise coverage, lack of effective features, and small sample sizes, resulting in low fault identification accuracy and slow efficiency. The purpose of this paper is to study an accurate and efficient method of pipeline anomaly detection.

First, to address the impact of background noise on the accuracy of anomaly signals, the adaptive multi-threshold center frequency variational mode decomposition method(AMTCF-VMD) method is used to eliminate strong noise in pipeline signals. Secondly, to address the strong data dependency and loss of local features in the Swin Transformer network, a Hybrid Pyramid ConvNet network with an Agent Attention mechanism is proposed. This compensates for the limitations of CNN’s receptive field and enhances the Swin Transformer’s global contextual feature representation capabilities. Thirdly, to address the sparsity and imbalance of anomaly samples, the SpecAugment and Scaper methods are integrated to enhance the model’s generalization ability.

In the pipeline anomaly audio and environmental datasets such as ESC-50, the AMTCF-VMD method shows more significant denoising effects compared to wavelet packet decomposition and EMD methods. Additionally, the model achieved 98.7% accuracy on the preprocessed anomaly audio dataset and 99.0% on the ESC-50 dataset.

This paper innovatively proposes and combines the AMTCF-VMD preprocessing method with the Agent-SwinPyramidNet model, addressing noise interference and low accuracy issues in pipeline anomaly detection, and providing strong support for oil and gas pipeline anomaly recognition tasks in high-noise environments.

The author examined effects of endorser type and message framing on visual attention and ad effectiveness in health ads, including the moderator of involvement. This paper aims to discuss this issue.

An experiment was conducted with a 2 (celebrity vs. expert) × 2 (positive vs. negative framing) between-subject factorial design. Eye-tracking measured visual attention and a questionnaire measured ad effectiveness and product involvement.

Experimental data from 78 responses showed no vampire effect in the health advertisements. Celebrity endorsement with negative message framing received more attention and had less ad recall than that with positive message framing. Negative and positive message framing attracted the same amount of attention and ad recall in the expert endorsement condition. High involvement participants paid more attention to the ad message with the expert than that with the celebrity, but ad recall was not significantly increased. Low involvement participants exhibited the same attention to the ad message with the expert and with the celebrity, but had greater recall of the ad message with the expert. Visual attention to the endorser was associated with ad attitude but not with ad recall. Ad attitude impacted behavioral intention.

Studies examining influences of celebrity and message framing on ad effectiveness have focused on the response to advertising stimuli, not the information process. The author provides empirical evidence of the viewers' information processing of endorsers and health messages, and its relationship with ad effectiveness. The study contributes to the literature by combining endorser and message framing in health ads to promote public health communication from the information processing perspective.

Multiple topics often exist on social media platforms that compete for users' attention. To explore how users’ attention transfers in the context of multitopic competition can help us understand the development pattern of the public attention.

This study proposes the prediction model for the attention transfer behavior of social media users in the context of multitopic competition and reveals the important influencing factors of users' attention transfer. Microblogging features are selected from the dimensions of users, time, topics and competitiveness. The microblogging posts on eight topic categories from Sina Weibo, the most popular microblogging platform in China, are used for empirical analysis. A novel indicator named transfer tendency of a feature value is proposed to identify the important factors for attention transfer.

The accuracy of the prediction model based on Light GBM reaches 91%. It is found that user features are the most important for the attention transfer of microblogging users among all the features. The conditions of attention transfer in all aspects are also revealed.

The findings can help governments and enterprises understand the competition mechanism among multiple topics and improve their ability to cope with public opinions in the complex environment.