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Organizations working in high-hazard environments contribute significantly to modern society and the economy, not only for the valuable resources they hold but also for the indispensable products and services they provide, such as power generation, transportation and defense weapons. Therefore, the main purpose of this study is to develop a framework that outlines future research on systems safety and provides a better understanding of how organizations can effectively manage hazard events.

In this research, we developed the high hazard theory (HHT) and a theoretical framework based on the grounded theory method (GTM) and the integration of three established theoretical perspectives: normal accident theory (NAT), high reliability theory (HRT) and resilience engineering (RE) theory.

We focused on the temporal aspect of accidents to create a timeline showing the progression of hazard events and the factors contributing to safety and hazards in organizations. Given the limitations of the previous theories in providing a coherent explanation of hazard event escalation in high-hazard organizations (HHOs), we argue that the highlighted theories can be more complementary than contradictory regarding their standpoints on disasters and accident prevention.

A proper appreciation of the hazard nature of organizations can help reduce their susceptibility to failure, prevent outages and breakdowns of systems, identify areas for improvement and develop strategies to enhance performance.

By developing HHT, we contribute to systems safety research by developing a new, refined theory and enrich the theoretical debate. We also expand the understanding of scholars and practitioners about the characteristics of organizations working in high-hazard environments.

Given the scarcity of studies regarding religious food as a destination attraction and limited research on tourist halal food experience, this study aims to explore and compare halal food experience perceived by Muslim and non-Muslim tourists in a non-Islamic destination.

This study was carried out in a halal food street in Yuanjia Village, China. It used a qualitative approach and interviewed 16 Muslim tourists and 20 non-Muslim tourists.

Six themes and 18 attributes of halal food experience were identified. The findings revealed that Muslim tourists saw the reassuring options and religious value of halal food as important experiences. By contrast, the experiences of abundant choices, value for money, sensory pleasure and unique charm were frequently mentioned by non-Muslim tourists. The nature of halal food, the context of China (i.e. Chinese halal food culture) and the feature of research site (i.e. food operation of Yuanjia Village) work together to create such experiences.

To the best of the authors’ knowledge, this is one of the first studies to explore and compare halal food experiences of Muslim and non-Muslim tourists in a non-Islamic country (China). This study suggests that halal food could be an appealing destination attraction, even in non-Islamic destinations. Thus, this study contributes to a better understanding of the halal food experiences and assists destination marketers in promoting halal food.

This paper aims to prepare third-order nonlinear optical (NLO) organic materials with large nonlinear optimization value, high damage threshold and ultrafast response time.

A series of novel symmetric and asymmetric compounds possessing third-order NLO properties were synthesized using 1,3,5-tribromobenzene as the basis. The photophysical and electrochemical properties, as well as the click reactions, were characterized by means of UV–VIS–NIR absorption spectroscopy and cyclic voltammetry.

The donor–acceptor chromophores were inserted into compound, making the molecule to have a broader absorption in the near-infrared regions and a narrower optical and electrochemical band gap. It also formed an electron-delocalized organic system, which has larger effects on achieving a third-order NLO response. The third-order NLO phenomenon of benzene ring complexes was experimentally studied at 532 nm using Z-scan technology, and some compounds showed the expected NLO properties.

The click products exhibit more NLO phenomena by performing different click combinations to the side groups, opening new perspectives on using the system in a variety of photoelectric applications.

Virtual clothing presentation has a visual 3D effort and allows consumers to interact. Currently, most scholars make virtual clothing presentations as a whole or focus on one element to study its impact on consumers’ purchase intentions. This study disassembles the components of virtual clothing presentation in Taobao and explores how each component (virtual clothing, virtual model, presentation space, presentation technology and system quality) affects consumers’ purchase intention, which can provide clothing companies recommendations for developing it and help improve consumers’ online shopping experience.

This study created the parts of a virtual clothing presentation and took advantage of Taobao’s 3D interactive module to simulate a shopping scenario. Participants experienced a 3D interactive virtual clothing presentation in which they could change clothing colors, show actual clothing sizes, try different model poses, switch presentation backgrounds and unfold clothing structure through interactive buttons. Then they were randomly assigned to view two kinds of images and videos of experiment clothing (real images and videos vs virtual ones), respectively. Hypotheses were tested using SEM and applying SmartPLS 4.

The results demonstrated that five components of virtual clothing presentation have different degrees of influence on consumers’ purchase intention through different consumer perceptions (perceived usefulness, ease of use and enjoyment). It is necessary to consider the design of the virtual clothing presentation in those five dimensions for different needs. In addition, it is feasible to replace images and animated videos of real clothing with virtual ones in Taobao.

Different types of virtual clothing presentations can lead to various results in terms of diverse impacts. This study disassembles and researches each component of a virtual clothing presentation. Overall, this study could provide guidance and suggestions for clothing companies to develop and design or invest in virtual clothing presentations.

Drawing on the Service Robot Acceptance Model (sRAM) proposed by Wirtz et al. (2018), this study aims to examine how functional and social-emotional antecedents affect relational elements and the critical functions that trust and rapport play in robot acceptance in hotel services. Additionally, this study incorporates customer characteristics into the modified sRAM.

Consistent partial least squares (PLSc) was used to test the proposed model utilizing data collected from 456 Chinese customers.

The results indicated that effort expectancy and performance expectancy positively affect hotel guests’ trust toward and rapport with service robots. However, the effect of social influence on trust and rapport is insignificant. Additionally, perceived humanness and perceived social interactivity positively influence rapport, and perceived social presence positively affects both trust and rapport. Furthermore, trust and rapport positively influence hotel guests’ acceptance of service robots. The results also revealed the moderating role of age.

This study contributes to service robot literature by providing insights into how functional and social-emotional factors affect relational factors and the key role of relational factors in robot acceptance based on the sRAM. This study also advances this body of knowledge by highlighting the moderating effect of age.

基于Wirtz等人（2018）提出的服务机器人接受模型（sRAM）, 本研究旨在探讨功能性和社会-情感性前因如何影响关系元素, 以及信任和融洽在酒店服务中对机器人接受度的关键作用。此外, 本研究将顾客特征纳入修改后的 sRAM 中。

采用一致性偏最小二乘法（PLSc）对来自456名中国顾客的数据进行分析，以验证所提出的模型。

结果表明, 努力期望和绩效期望积极影响酒店客人对服务机器人的信任和融洽。然而, 社会影响对信任和融洽的影响不显著。此外, 感知人性化和感知社会互动积极影响融洽, 感知社会临场感积极影响信任和融洽。此外, 信任和融洽积极影响酒店客人对服务机器人的接受度。结果还揭示了年龄的调节作用。

本研究通过提供关于功能性和社会-情感性因素如何影响关系因素以及关系因素在机器人接受度中的关键作用的见解, 为服务机器人文献做出了贡献。本研究还通过强调年龄的调节效应, 推进了这一知识体系的发展。

Addressing the adverse effects of entrepreneurial failure stigma and establishing the subsequent entrepreneurship legitimacy of new ventures are crucial for reinvigorating entrepreneurial endeavors. This paper investigated the implementation of impression-management strategies for mitigating the adverse effects of the stigma associated with entrepreneurial failure on the legitimacy of subsequent entrepreneurial activities.

Drawing on impression-management theory and legitimacy theory, we conducted three experimental studies to explore the impact of impression-management strategies of entrepreneurial-failure stigma on the legitimacy of subsequent entrepreneurship. Additionally, the role of stakeholders’ forgiveness as a mediating factor and how the specific type of entrepreneurial failure stigma (attributable vs non-attributable) moderates these effects were analyzed.

The results from Studies 1 and 2 show that implementing impression-management strategies positively contributes to sustaining the legitimacy of subsequent entrepreneurial endeavors in failed new ventures. Assertive strategies demonstrate a more effective impact on enhancing the legitimacy of subsequent entrepreneurship than defensive impression management strategies. In addition, stakeholders’ forgiveness plays a mediating role in the relationship between impression-management strategies and subsequent entrepreneurship legitimacy. The results of Study 3 demonstrate that the type of stigma associated with entrepreneurial failure moderates the impact of impression-management strategies on the legitimacy of subsequent entrepreneurship. In situations where the stigma is attributable, implementing only assertive strategies is adequate to yield favorable results. However, in situations where the stigma is non-attributable, it is essential to implement both defensive and assertive strategies to effectively strengthen subsequent entrepreneurship legitimacy.

The findings make a valuable contribution to the existing literature on the recovery from entrepreneurial failure, and they also offer practical strategies for new ventures to adeptly handle the stigma of failure and resume their entrepreneurial endeavors.

Improving the diversity of recommendation information has become one of the latest research hotspots to solve information cocoons. Aiming to achieve both high accuracy and diversity of recommender system, a hybrid method has been proposed in this paper. This study aims to discuss the aforementioned method.

This paper integrates latent Dirichlet allocation (LDA) model and locality-sensitive hashing (LSH) algorithm to design topic recommendation system. To measure the effectiveness of the method, this paper builds three-level categories of journal paper abstracts on the Web of Science platform as experimental data.

(1) The results illustrate that the diversity of recommended items has been significantly enhanced by leveraging hashing function to overcome information cocoons. (2) Integrating topic model and hashing algorithm, the diversity of recommender systems could be achieved without losing the accuracy of recommender systems in a certain degree of refined topic levels.

The hybrid recommendation algorithm developed in this paper can overcome the dilemma of high accuracy and low diversity. The method could ameliorate the recommendation in business and service industries to address the problems of information overload and information cocoons.

Safety cognitive ability is a key factor influencing unsafe behavior. However, the existing achievements have not yet involved the division of the hierarchical relationship of factors influencing safety cognition and lack a quantitative evaluation system of safety cognitive ability. The purpose of this paper is to find out the deficiencies in the safety cognition of workers in high-risk construction positions and to provide practical suggestions for improving their safety cognitive ability and reducing unsafe behavior.

Based on the iceberg model, the factors influencing the safety cognitive ability of workers in high-risk construction positions and their hierarchical relationship were determined, and an evaluation index system consisting of four primary indicators and 20 secondary indicators was constructed. The game theory algorithm was used to optimize the subjective and objective weights of the indicators calculated by the sequential analysis method (G1) and the entropy weighting method (EWM) to obtain the optimal combination weight value. The Matlab software was used for cloud mapping and similarity calculation to determine the safety cognitive ability level of the object to be evaluated.

The research results indicate that the comprehensive level of safety cognitive ability of scaffolders in this construction project is at “Level III”, the fundamental factors and compliance factors are at “Level IV”, the auxiliary factors and driving factors are at “Level III”. This conclusion aligns with the situation learned from the previous field investigation, which validates the feasibility and scientificity of the proposed evaluation method.

Considering that the safety cognitive ability of construction workers is constantly changing, this study has not yet delved into the specific impacts of various influencing factors on the level of safety cognitive ability. Future research can utilize simulation software, such as MATLAB and Vensim, to construct dynamic simulation models that accurately simulate the changing rules of construction workers’ safety cognitive ability under the influence of different factors.

This research broadens the application scope of the iceberg model, enriches the analysis model of the factors influencing the safety cognitive ability of workers in high-risk construction positions and provides a novel perspective for similar research. The safety cognitive ability evaluation method proposed in this paper can not only accurately evaluate the safety cognitive ability level of workers in high-risk positions such as scaffolders but also provide practical suggestions for improving the safety cognitive ability of workers, which is of great significance to improve the safety management level and reduce unsafe behavior in the construction field.

This research fills the research gap of workers in high-risk construction positions and the quantification of safety cognitive ability. The iceberg model is used to realize the hierarchical division of the factors influencing safety cognitive ability. Additionally, an evaluation method for the safety cognitive ability of workers in high-risk construction positions based on the game theory combination weighting method and cloud model is proposed, which realizes the quantitative evaluation of safety cognitive ability.

The purpose of this paper is twofold: first, it explores the influencing factors of the government’s trust decision-making in the private sector; second, it explores how these influencing factors affect the government’s trust decisions.

A theoretical model was established, and a questionnaire survey was conducted among 152 professionals. The collected datas were analyzed by the structural equation modeling (SEM) method.

The study identified four critical factors that influence the government’s decision to trust the private sector in public-private-partnership (PPP) projects. All the four factors have a positively correlated impact on the government’s trust decision-making. The structural equation path analysis shows that the most important factor affecting the government’s trust decision-making is the trustee’s (private sector) trustworthy characteristics, and the path coefficient is 0.92. The path coefficients of risk perception and the trustor’s trust tendency are 0.83 and 0.74, respectively. The influence of the legal system environment on government trust decision-making is moderate, with a path coefficient of 0.68.

This paper contributes to the literature in two aspects. First, the factors influencing decision-making to government trust in the private sector in PPP projects have been identified. Second, a comprehensive view of the mechanism of government trust in the private sector in PPP projects has been theorized by the SEM method.

Trust is the glue that holds cooperative relationships together and often exists in an asymmetric manner. The purpose of this study is to explore how to mitigate the issue of losses or increased transaction costs caused by opportunistic behavior in a soft environment where trust asymmetry is quite common and difficult to avoid.

This study focuses on examining asymmetric trust between the government and the private sector in public-private partnership (PPP) projects. Drawing upon both project realities and relevant literature, the primary conditional variables influencing asymmetric trust are identified. These variables encompass power perception asymmetry, information asymmetry, interaction behavior, risk perception differences and government-side control. Subsequently, through the use of a survey questionnaire, binary-matched data from both the government and the private sector are collected. The study employs fuzzy-set qualitative comparative analysis (fsQCA) to conduct a configurational analysis, aiming to investigate the causal pathways that trigger asymmetric trust.

No single conditional variable is a necessary condition for the emergence of trust asymmetry. The pathways leading to a high degree of trust asymmetry can be categorized into two types: those dominated by power perception and those involving a combination of multiple factors. Differences in power perception play a crucial role in the occurrence of high trust asymmetry, yet the influence of other conditional variables in triggering trust asymmetry should not be overlooked.

The findings can contribute to advancing the study of trust relationships in the field of Chinese PPP projects. Furthermore, they hold practical value in facilitating the enhancement of trust relationships between the government and the private sector.