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The privacy calculus based on a single stakeholder failed to explain users' co-owned information disclosure owing to the uniqueness of co-owned information. Drawing on collective privacy calculus theory and impression management theory, this study attempts to explore the co-owned information disclosure of social network platform users from a collective perspective rather than an individual perspective.

Drawing on collective privacy calculus theory and impression management theory, this study explores the co-owned information disclosure of social network platform users from a collective perspective rather than an individual perspective based on a survey of 740 respondents.

This study finds that self-presentation and others presentation directly positively affect users' co-owned information disclosure. Also, self-presentation, others presentation and relationship presentation indirectly positively affect users' co-owned information disclosure via relationship support. Furthermore, personal privacy concern, others' privacy concern and relationship privacy concern indirectly negatively affect users' co-owned information disclosure via relationship risk.

The findings develop the theory of collective privacy calculus and impression management, which offer insights into the design of the collective privacy protection function of social network platform service providers.

This study aims to investigate whether and how public air environmental concern (PAEC) affects corporate environmental, social and governance (ESG) performance in emerging markets.

This study measured PAEC using the Baidu index search keyword “雾霾 (PM2.5)” and assessed its impact on corporate ESG among Chinese A-share listed companies from 2011 to 2020 through regression analysis.

The empirical results indicate a positive relationship between PAEC and corporate ESG. Moreover, PAEC facilitates enhanced corporate ESG performance by mediating through corporate reputation and government environmental regulations. Heterogeneity analysis shows that the promotion effect of PAEC on ESG is more pronounced in the subgroups of companies with an excellent green image, low perceived uncertainty, strong management political connections, low short-termism, high industry technological levels and low pollution levels.

The practical implications of this study underscore the importance for policymakers, investors and companies to prioritize PAEC and its influence on corporate ESG performance.

This study contributes to ESG literature by highlighting the positive impact of external oversight, such as PAEC.

The purpose of this paper is to explore the effect of ZnO on the structure and properties of micro-arc oxidation (MAO) coating on rare earth magnesium alloy under large concentration gradient.

The macroscopic and microscopic morphology, thickness, surface roughness, chemical composition and structure of the coating were characterized by different characterization methods. The corrosion resistance of the film was studied by electrochemical and scanning Kelvin probe force microscopy. The results show that the addition of ZnO can significantly improve the compactness and corrosion resistance of the MAO coating, but the high concentration of ZnO will cause microcracks, which will reduce the corrosion resistance to a certain extent.

When the concentration of zinc oxide is 8 g/L, the compactness and corrosion resistance of the coating are the best, and the thickness of the coating is positively correlated with the concentration of ZnO.

Too high concentration of ZnO reduces the performance of MAO coating.

The MAO coating prepared by adding ZnO has good corrosion resistance. Combined with organic coatings, it can be applied in corrosive marine environments, such as ship parts and hulls. To a certain extent, it can reduce the economic loss caused by corrosion.

The effect of ZnO on the corrosion resistance of MAO coating in electrolyte solution was studied systematically, and the conclusion was new to the common knowledge.

Increasing incidents of privacy invasion on social networking sites (SNS) are intensifying the concerns among stakeholders about the misuse of personal data. However, there seems to be limited research on exploring the impact of specific privacy concerns on users’ intention to engage in various privacy protection behaviors. This study aims to examine the role of social privacy concerns, institutional privacy concerns and privacy self-efficacy as antecedents of privacy protection–related control activities intention among young adults active on SNS.

Data collected from 284 young adults active on SNS was analyzed through partial least squares structural equation modeling using Smart PLS.

The results indicate that institutional privacy concerns, social privacy concerns and privacy self-efficacy positively influence the control activities intention of SNS users. The extent of privacy self-efficacy and privacy protection-related control activities intention differs among users based on gender.

This study is limited to a population of young adults in the age group of 18–25 years.

The findings of this study form the basis for specific recommendations addressing the different types of privacy concerns experienced by social media users, promoting responsible privacy control behaviors on online platforms and discouraging the possible misuse of information by third parties.

This study validates a theoretical framework that can contribute to future investigations concerning the use of SNS. The study findings form the basis for a set of practical recommendations for policymakers, SNS platforms and users.

The interest in corporate social responsibility (CSR) has become burgeoning in the construction industry as firms are under constant pressure from socially conscious stakeholders to demonstrate their efforts to address various CSR issues. This study aims to unveil the key practices and impact factors (KPIFs) of CSR implementation in construction firms and the interrelationships among different key impact factors toward attaining CSR practices.

Mobilizing the integrated institutional, stakeholder and self-determination theories, a theoretical framework was first developed to elaborate the potential inter-relationships among the key impact factors toward CSR implementation. Data were collected from extra-grade contractors through an online questionnaire survey and was then analyzed by the partial least square structural equation modeling method.

The results show that construction firms' CSR practices could be classified into eight distinct key dimensions, e.g. shareholders' interests, government commitment and environment preservation. It is found that three groups of key impact factors – external institutional factors (especially coercive-normative factors), intrinsic factors (especially strategic business direction and organizational culture) and identified factors (i.e. the perceived importance of CSR practices) – have statistically significant positive impacts on most key dimensions of CSR practices.

The research findings have implications for top management to better understand CSR implementation, thereby helping them secure legitimacy to survive and advance in the competitive construction businesses.

The findings contribute to the theoretical body of knowledge in CSR by modeling and empirically demonstrating the influence mechanism of CSR implementation in construction within an integrated model.

This study aims to evaluate the potential of using the components of the quadruple helix and quintuple helix models, which are extensions of the triple helix university-private sector-public sector cooperation model. Thus, the triple helix model shaped by university-private-public sector cooperation has transformed into a quadruple helix innovation model with the inclusion of the media and culture-oriented public helix. In this context, while the triple helix emphasizes tripartite networks and hybrid organizations, the quadruple helix system focuses on intertwined collaborations, coevolution, and specialization within the framework of firms, institutions, and stakeholders. In the quadruple helix innovation system, the coevolution of art and innovation has assumed a central role in knowledge generation and innovation. In the quintuple helix innovation model, the natural environment of society is added to the quadruple helix. This study consists of three parts. In the first part, the literature on triple helix, quadruple helix, and quintuple helix models is reviewed. In the second part, digital transformation and technological innovations from Industrial Revolution 1.0 to Industry 5.0 are analyzed. In the third section, the contribution of the quintuple helix model to Industry 5.0 and Society 5.0 is explained.

To contribute to achieving the Sustainable Development Goals, this study aims to explore how to encourage innovative green behaviors among college students and the mechanisms behind the formation of green innovation behavior. Specifically, this study examines the influences of schools, mentors and college students themselves.

A multilevel, multisource study involving 261 students from 51 groups generally supported this study’s predictions.

Proenvironmental and responsible mentors significantly predicted innovative green behavior among college students. In addition, creative motivation mediated the logical chain among green intellectual capital, emotional intelligence and green innovation behavior.

The study findings offer new insights into the conditions required for college students to engage in green innovation. In addition, they provide practical implications for cultivating green innovation among college students.

The authors proposed and tested a multilevel theory based on the ability–motivation–opportunity framework. In this model, proenvironmental and responsible mentors, green intellectual capital and emotional intelligence triggered innovative green behavior among college students through creative motivation.

Natural disasters profoundly influence agricultural trade sustainability. This study investigates the effects of natural disasters on agricultural production imports in China within 2002 and 2018. This exploration estimates the mediating role of transportation infrastructure and agriculture value-added and the moderating role of government effectiveness and diplomatic relations.

This investigation uses Probit, Logit, Cloglog and Ordinary Least Squares (OLS) models.

The results confirm the mediating role of transportation infrastructure and agriculture value-added and the moderating role of government effectiveness and diplomatic relations in China. According to the findings, natural disasters in trading partners heighten the risk to the agricultural imports. This risk raises, if disasters damage overall agricultural yield or transportation infrastructure. Moreover, governments’ effective response or diplomatic ties with China mitigate the risk. Finally, the effect of disasters varies by the developmental status of the country involved, with events in developed nations posing a greater risk to China’s imports than those in developing nations.

China should devise an early warning system to protect its agricultural imports by using advanced technologies such as data analytics, remote sensing and artificial intelligence. In addition, it can leverage this system by improving its collaboration with trading partners, involvement in international forums and agreement for mutual support in crisis.

This study aims to investigate tourists’ attitudes and intentions regarding the usage of Chat Generative Pre-trained Transformer (ChatGPT) for accessing tourism information. Furthermore, by integrating the perceived risks associated with ChatGPT and the theory of planned behavior (TPB), this research examines the impact of three types of perceived risks, such as privacy risk, accuracy risk and overreliance risk, on tourists’ behavioral intention.

Data were gathered for this study by using two online survey platforms, thus resulting in a sample of 536 respondents. The online survey questionnaire assessed tourists’ perceived risks, attitude, subjective norm, perceived behavioral control, behavioral intention and demographic information related to their usage of ChatGPT.

The structural equation modeling analysis revealed that tourists express concerns about the associated risks of using ChatGPT to search for tourism information, specifically privacy risk, accuracy risk and overreliance risk. It was found that perceived risks significantly influence tourists’ attitude and intention toward the usage of ChatGPT, which is consistent with the hypotheses proposed in previous literature regarding tourists’ perceived risks of ChatGPT.

This work is a preliminary empirical study that assesses tourists’ behavioral intention toward the use of ChatGPT in the field of tourism. Previous research has remained at the hypothetical level, speculating about the impact of ChatGPT on the tourism industry. This study investigates the behavioral intention of tourists who have used ChatGPT to search for travel information. Furthermore, this study provides evidence based on the outcome of this research and offers theoretical foundations for the sustainable development of generative AI in the tourism domain. This study has limitations in that it primarily focused on exploring the risks associated with ChatGPT and did not extensively investigate its range of benefits.

First, to address privacy concerns that pose significant challenges for chatbots various measures, such as data encryption, secure storage and obtaining user consent, are crucial. Second, despite concerns and uncertainties, the introduction of ChatGPT holds promising prospects for the tourism industry. By offering personalized recommendations and enhancing operational efficiency, ChatGPT has the potential to revolutionize travel experiences. Finally, recognizing the potential of ChatGPT in enhancing customer service and operational efficiency is crucial for tourism enterprises.

Recognizing the potential of ChatGPT in enhancing customer service and operational efficiency is crucial for tourism enterprises. As their interest in adopting ChatGPT grows, increased investments and resources will be dedicated to developing and implementing ChatGPT solutions. This enhancement may involve creating customized ChatGPT solutions and actively engaging in training and development programs to empower employees in effectively using ChatGPT’s capabilities. Such initiatives can contribute to improved customer service and overall operations within the tourism industry.

This study integrates TPB with perceived risks in ChatGPT, thus providing empirical evidence. It highlights the importance of considering perceived risks in tourists’ intentions and contributes to the sustainable development of generative AI in tourism. As such, it provides valuable insights for practitioners and policymakers.

本研究旨在调查游客对使用ChatGPT获取旅游信息的态度和意向。此外, 通过将与ChatGPT相关的感知风险与计划行为理论（TPB）相结合, 本研究探讨了三种感知风险（隐私风险、准确性风险和过度依赖风险）对游客行为意向的影响。

本研究通过两个在线调查平台收集了536名受访者的数据。在线调查问卷评估了游客对ChatGPT使用的感知风险、态度、主观规范、感知行为控制、行为意向以及与其使用ChatGPT相关的人口统计信息。

结构方程建模分析显示, 游客对使用ChatGPT搜索旅游信息的相关风险表示关切, 特别是隐私风险、准确性风险和过度依赖风险。发现感知风险显著影响游客对使用ChatGPT的态度和意向, 与先前有关游客对ChatGPT感知风险的文献中提出的假设一致。

本研究将TPB与ChatGPT中的感知风险相结合, 提供了实证证据。它强调了在考虑游客意向时考虑感知风险的重要性, 并为旅游中生成AI的可持续发展提供了贡献。因此, 它为从业者和政策制定者提供了宝贵的见解。

The primary objective of this study is characterizing the anisotropic mechanical properties of corrugated cardboard and simultaneously simulating its drop cushioning dynamic effects under various drop conditions.

Static and dynamic tests were conducted on corrugated cardboard to obtain adequate experimental data in different directions. An effective anisotropic constitutive model is introduced by developing the honeycomb materials model in ANSYS LS-Dyna, and an effective approach is established toward effectively determining the material parameters from the test data obtained. The model is validated by comparing simulation results with experimental data from five drop conditions, including bottom drop, front drop, side drop, 30° side drop and edge drop. Additionally, simulations are conducted to study the cushioning performance of the packaging by dropping the corrugated cardboard at different heights.

The study establishes a fast and effective approach to simulating the drop cushioning performance of corrugated cardboard under various drop conditions, which demonstrates good agreement with experimental data.

This approach is of value for packaging protection and provides guidance for stacking of packaging during transportation.