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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.

Considering rapid digitalization development, this study examines the impacts of digital technology innovation on social responsibility in platform enterprises.

The study applies the event study method and cross-sectional regression analysis, taking 168 digital technology innovations for social responsibility issued by 88 listed platform enterprises from 2011 to 2022 to study the impact of digital technology innovations for social responsibility announcements of different announcement content and platform attributes on the stock market value of platform enterprises.

The results show that, first, the positive stock market reaction is produced on the same day as the digital technology innovation announcement. Second, the announcement of the platform’s public social responsibility and the announcement of co-innovation and radical innovation bring more positive stock market reactions. In addition, the announcements mentioned above issued by trading platforms bring more positive stock market reactions. Finally, the social responsibility attribution characteristics of the announcement did not have a significant differentiated impact on the stock market reaction.

Most scholars have studied digital technology innovation for social responsibility through modeling rather than second-hand data to empirically examine. This study uses second-hand data with the instrumental stakeholder theory to provide a new research perspective on platform social responsibility. In addition, in order to explore the different impacts of digital technology innovation on social responsibility, this study has classified digital technology innovation for social responsibility according to its social responsibility and digital technology innovation characteristics.

Ensuring the safety of structures is important. However, when a structure possesses both an implicit performance function and an extremely small failure probability, traditional methods struggle to conduct a reliability analysis. Therefore, this paper proposes a reliability analysis method aimed at enhancing the efficiency of rare event analysis, using the widely recognized Relevant Vector Machine (RVM).

Drawing from the principles of importance sampling (IS), this paper employs Harris Hawks Optimization (HHO) to ascertain the optimal design point. This approach not only guarantees precision but also facilitates the RVM in approximating the limit state surface. When the U learning function, designed for Kriging, is applied to RVM, it results in sample clustering in the design of experiment (DoE). Therefore, this paper proposes a FU learning function, which is more suitable for RVM.

Three numerical examples and two engineering problem demonstrate the effectiveness of the proposed method.

By employing the HHO algorithm, this paper innovatively applies RVM in IS reliability analysis, proposing a novel method termed RVM-HIS. The RVM-HIS demonstrates exceptional computational efficiency, making it eminently suitable for rare events reliability analysis with implicit performance function. Moreover, the computational efficiency of RVM-HIS has been significantly enhanced through the improvement of the U learning function.

Islanding detection has become a serious concern due to the extensive integration of renewable energy sources. The non-detection zone (NDZ) and system-specific applicability, which are the two major issues with the islanding detection methods, are addressed here. The purpose of this paper is to devise an islanding detection method with zero NDZ and, which will be applicable to all types of renewable energy sources using the sequence components of the point of common coupling voltage.

Here, a parameter using the sequence components is derived to devise an islanding detection method. The parameter derived from the sequence components of point of common coupling voltage is analysed using wavelet transform. Various operating conditions, such as islanding and non-islanding, are considered for several test systems to evaluate the performance of the proposed method. All the simulations are carried out in Simulink/MATLAB environment.

The results showed that the proposed method has zero NDZ for both inverter- and synchronous generator-based renewable energy sources. In addition, the proposed method works satisfactorily as per the IEEE 1547 standards requirement.

Performance of the proposed method has been tested in several test systems and is found to be better than some conventional methods.

The primary objective of this research is to draw a comparative analysis between Turkey and Italy in terms of how festival events function as catalysts for the endorsement of regional culinary delicacies. The study endeavours to elucidate the role of these festivals in fortifying the regional gastronomic landscape of both nations.

Adopting a comprehensive comparative methodology, this study meticulously scrutinises the gastronomy festivals spanning diverse geographical locales in both Turkey and Italy. Consideration is given to the standout food and beverage items spotlighted at these events and the venues where they are hosted. The research design takes into account the extensive cultural and geographical spectrum that characterises Turkey and Italy. The primary research method comprises web content analysis techniques. This method involves analysing textual data from online sources pertaining to gastronomy festival events in both countries. Web content analysis is instrumental in evaluating how such festivals are deployed in promoting indigenous gastronomic products and exploring the intricate dynamics between brand identity and brand image.

The research outcomes underscore the pivotal role that festival events play in elevating regional gastronomic products' profile in Turkey and Italy. It highlights the top 10 festivals and the most popular local culinary items on digital platforms. Additionally, the study offers a side-by-side comparison of the most celebrated gastronomic products in Turkey versus those that receive prominence in Italy.

This study enriches academic understanding by dissecting the nuances of how festivals contribute to the promotion of local gastronomic treasures. By juxtaposing Turkey and Italy, this research provides valuable insights into the influence of festivals on regional culinary promotion across diverse cultural milieus. This study makes substantial contributions to the fields of gastronomy, tourism, and brand promotion.

Based on the cognition-affection personality system theory, this study constructs and tests a mediation model of leadership non-contingent punishment on bystander workplace deviance behavior through bystander affective rumination and bystander psychological contract violation, as well as a chain mediation effect of bystander affective rumination and bystander psychological contract violation, and explores the moderation role of bystander performance pressure in this model.

This study takes 454 employees and their colleagues from several Chinese enterprises as the research subjects and conducts a paired survey at three-time points using Mplus 7.4 to analyze the empirical data.

The research results are as follows: Bystander affective rumination and bystander psychological contract violation play a mediation role between leadership non-contingent punishment and bystander workplace deviance behavior, respectively. Bystander affective rumination and bystander psychological contract violation play a chain mediation role in the positive role of leadership non-contingent punishment on bystander workplace deviance behavior. Bystander performance pressure moderates the chain mediation path by enhancing the positive role of leadership non-contingent punishment on bystander affective rumination.

This study comprehensively explores the internal path of the impact of leadership non-contingent punishment on bystander workplace deviance behavior from the perspective of bystanders through dual paths of cognition and affection. It enriches the result variables of leadership non-contingent punishment, expands existing research on the mediation mechanism of leadership non-contingent punishment and deepens the understanding of the mechanism of leadership non-contingent punishment. At the same time, it has practical guidance significance to promote the suppression of leadership non-contingent punishment in organizations, reduce the occurrence of employee workplace deviance behavior, help employees better integrate into the organization and build a harmonious organizational environment.

Research on the effects of feedback frequency has reported mixed findings. To tackle this problem, the current study focuses on specific feedback signs (i.e. negative feedback). By integrating the face management theory and attribution theory, this study examined the mediating effect of trust in supervisors and the moderating effect of employee-attributed performance promotion motives for negative feedback.

A field study with 176 participants and two supplemental experiments with 143 and 100 participants, respectively, were conducted to test the theoretical model.

Results revealed that the frequency of supervisory negative feedback negatively influenced employees’ trust in supervisors, which in turn influenced employees’ perceptions of feedback utility and learning performance. These indirect effects can be alleviated when employees have high degrees of performance promotion attribution for supervisor motives.

This research extends feedback research by integrating feedback frequency with a specific sign of feedback and revealing a moderated mediation effect of the negative feedback frequency.

This study aims to investigate the negative interpersonal antecedents, emotional mediators and boundary conditions of knowledge sabotage behavior.

The authors collected data from 275 Chinese employees using convenience sampling and snowball sampling across three stages. Subsequently, the authors used both hierarchical regression and bootstrap methods to test the proposed hypotheses.

The results confirmed that workplace ostracism has positive effects on employee knowledge sabotage behavior both directly and via employee anger. In addition, the authors found that employee bottom-line mentality (BLM) moderates not only the direct effect of workplace ostracism on employee anger but also the indirect effect of employee anger in this context. Employee conscientiousness moderates only the direct effect of workplace ostracism on employee anger and does not moderate the indirect effect.

To the best of the authors’ knowledge, this study not only explores the influence of workplace ostracism on employee knowledge sabotage behavior for the first time but also elucidates the underlying emotional mechanisms (anger) and boundary conditions (employee BLM and conscientiousness) by which workplace ostracism influences employee knowledge sabotage behavior, thus deepening the understanding of how knowledge sabotage emerges in organizations.

This study explores the variance in investor responses to the corporate social responsibility (CSR) performance of firms, as influenced by information sources and investor types.

This study applies a short-term event study and cross-sectional analysis with unique CSR datasets obtained from newspaper articles and the Dow Jones Sustainability Index.

Investor reactions are significantly shaped by their sources of information. Individual investors are found to predominantly respond to accessible news announcements, whereas institutional investors show heightened sensitivity to adverse news from both scrutinized sources. Foreign investors, mirroring institutional investors' patterns, uniquely react positively to index additions.

Investors’ assessment of CSR activities varies due to the differing sources of information obtained; further, it is affected by the type of investor.

The findings guide public relation managers in strategizing CSR communication toward diverse investor types. This includes recommending targeted approaches for Japanese individual investors through newspapers and TV, exercising caution in disseminating adverse news to Japanese institutions, and promoting and justifying CSR actions to foreign investors. It underscores the need for a strategic investor relations frameworks that considers accessibility, literacy, and investors' interests.

This study examines the relationship between sources of information for CSR activities and investors’ responses, an area under-represented in the literature. The author uses CSR announcement data, collected from newspapers to make the results more accurate and relevant.

This study aims to investigate the adoption of the United Nations’ Sustainable Development Goals (SDGs) as the new performance perspective in cities. It also aims to understand how accounting for SDGs begins in city administrations by following Power’s (2015) fourfold development schema composed of policy object formation, object elaboration, activity orchestration and practice stabilization.

Focusing on a network of cities coordinated by the Finnish local government association, we analyzed the six largest cities in Finland employing a holistic multiple case study strategy. Our data consisted of Voluntary Local Reviews (VLRs), city strategies, budget plans, financial statements, as well as results of participant observations and semi-structured interviews with key individuals involved in accounting for SDGs.

We unveiled the SDG framework as an interpretive scheme through which cities glocalized sustainable development as a novel, simultaneously global and local, performance object. Integration of the new accounts in city management is necessary for these accounts to take life in steering the actions. By creating meaningful alignment and the ability to impact managerial practices, SDGs and VLRs have the potential to influence local actions. Our results indicate further institutionalization progress of sustainability as a performance object through SDG-focused work.

While prior research has focused mainly on general factors influencing the integration of the sustainability agenda, this study provides a novel perspective by capturing the process and demonstrating empirically how new accounts on SDGs are introduced and deployed in the strategic planning and management of local governments.