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Sharing co-owned information on social network platforms has become a common and inevitable phenomenon. However, due to the uniqueness of co-owned information, the privacy calculus theory based on a single information owner cannot explain co-owned information disclosure. Therefore, this study tries to investigate the underlying mechanism of users’ co-owned information disclosure from a collective privacy calculus perspective.

Through a survey of 740 participants, covariance-based structural equation modeling (CB-SEM) was used to verify the proposed model and hypotheses.

The results show that personal benefit, others’ benefit and relationship benefit promote users’ co-owned information disclosure by positively affecting personal distributive fairness and others’ distributive fairness perception. Meanwhile, personal privacy risk and others’ privacy risk prevent users’ co-owned information disclosure by negatively affecting personal distributive fairness and others’ distributive fairness perception. Besides, others’ information ownership perception enhances the positive effect of others’ distributive fairness perception on co-owned information disclosure intention. Furthermore, others’ information ownership strengthens the mediating role of others’ distributive fairness.

The findings of this study enrich the research scope of information disclosure and privacy calculus theory and help social network platform developers design collective privacy protection functions.

This study develops a collective privacy calculus model to understand users’ co-owned information disclosure on social network platforms, confirming the mediating role of collective distributive fairness and the moderating role of others’ information ownership perception in the process of collective privacy calculus.

This paper aims to explore the role of heuristics in the reassessment of relationship events and how it influences perceptions of commitment, fairness and relationship value. It answers the question of how heuristics interrelate with decision-makers’ evolving interpretations of commitment, fairness and relationship value in a specific buyer-supplier relationship.

This paper presents data from a longitudinal study of an evolving buyer–supplier relationship involving a multinational supplier of fast-moving consumer goods and a medium-sized and highly specialized supplier. It analyzes qualitative data about the use of heuristics in buyer–supplier relationships, and it is based on evidence collected from interviews, presentations, meetings and secondary data.

This paper shows that a buyer’s unexpected behavior can lead to a reassessment of commitment, fairness and relationship value. Heuristics can delay relationship reassessments, however. The case shows that heuristics have a preserving quality and that the effect of transformative events only slowly changes the perception of the value of the relationship. In this change process, the link between commitment, perceived fairness and heuristics is crucial.

This paper contributes to research on the relationship between buyer–supplier relationships and heuristics. In particular, the paper contributes to the understanding of how relational events in a buyer-supplier relationship change the commitment and perception of fairness, and how heuristics change accordingly. On a more overarching level, the study contributes to our understanding of business relationship dynamics.

The purpose of this study is to investigate possible drivers of loyalty amongst Islamic banking customers in Gauteng, South Africa. We ponder the relationships of service fairness (a secondorder reflective construct) with perceived value, satisfaction, and loyalty.

Data were obtained from Islamic banking customers in South Africa using interview-administered questionnaires. A total of 350 responses were perceived as being suitable for data analysis. The measurement and structural models were measured through structural equation modelling.

Service fairness and perceived value were found to be important drivers of loyalty within this context.

This study demonstrates that service fairness and perceived value are precursors to the future loyalty intentions of Islamic banking customers. As such, they should be nurtured as key elements of the relationship building process.

The study guides South African Islamic banks and South African banks with Islamic windows to better understand how service fairness (interactional, procedural and distributive) fosters satisfaction, perceived value and loyalty (attitudinal and behavioural).

Enhancing comprehension of the relationship between service fairness and customer loyalty, with satisfaction and perceived value playing intermediary roles, represents an unexplored avenue in academic research within the context of Islamic banking in an emerging African market.

Mental health problems are a grave concern in construction. Although the distinction between high job demands and low job resources, as reflected in the Job Demands-Resources (JD–R) model, has been used to examine the extent to which psychosocial hazards influence mental health for construction practitioners, limited research has reflected on the nature of these psychosocial hazards by exploring experiences of site-based construction practitioners.

This study adopted a phenomenological approach to examine people’ experiences and thoughts of the complex phenomena of psychosocial hazards and mental health in construction. In total, 33 semi-structured interviews were undertaken with site-based construction practitioners in Australia to unveil construction-focused psychosocial hazards and their effects on mental health. The data were analysed via content analysis, employing an interpretation-focused coding strategy to code text and an individual-based sorting strategy to cluster codes.

Eighteen psychosocial hazards were identified based on the JD–R model. Six of these represented a new contribution, describing salient characteristics inherent to the construction context (i.e. safety concerns, exposure to traumatic events, job insecurity, task interdependency, client demand and contract pressure). Of particular importance, a number of interrelationships among psychosocial hazards emerged.

The significance of this qualitative research lies in elucidating psychosocial hazards and their complex interrelatedness in the context of the mental health of construction practitioners, enriching the understanding of this central health and safety issue in the high-risk setting of construction work. The findings contribute to addressing mental health issues in the Australian construction industry by identifying higher order control measures, thereby creating a mentally healthy workplace.

The aim of this study is to empirically explore and analyze the concrete tasks of output measurement and the inherent challenges related to these tasks in a traditional and autonomous professional public work setting – the judicial system.

The analysis of the tasks is based on a categorization of general performance measurement motives (control-motivate-learn) and main stakeholder levels (society-organization-professionals). The analysis is exploratory and conducted as an empirical content analysis on materials and reports produced in two performance improvement projects conducted in European justice organizations.

The identified main tasks in the different categories are related to managing resources, controlling performance deviations, and encouraging improvement and development of performance. Based on the results, key improvement areas connected to output measurement in professional public organizations are connected to the improvement of objectivity and fairness in budgeting and work allocation practices, improvement of output measures' versatility and informativeness to highlight motivational and learning purposes, improvement of professional self-management in setting output targets and producing outputs, as well as improvement of organizational learning from the output measurement.

The paper presents empirically founded practical examples of challenges and improvement opportunities related to the tasks of output measurement in professional public organization.

This paper fulfils an identified need to study how general performance management motives realize as concrete tasks of output measurement in justice organizations.

The purpose of this paper is to assess the latest directives of the European Parliament and the Council – MiFID II and MiFIR – on markets in financial instruments in response to the growth of dark pools in European equity markets.

This paper examines the impact of the new regulatory packages on European equity markets by identifying areas where the legislation is effective and comparing these changes in EU legislation with US legislation on dark pools.

This paper find that the MiFID II and MiFIR directives, implemented by the European Securities and Markets Authority to address these concerns, have reduced information asymmetry between market participants, thereby increasing competition between regulated markets and alternative trading facilities.

Increased competition can improve market quality, which has practical implications for financial market regulation and policy formulation.

These findings are novel in the existing literature on high frequency trading through dark pools. They improve the understanding of dark trading and its impact on competition and market efficiency. In addition, this research can assist policymakers in designing effective financial market regulation. The economic analysis of legislation also helps regulators assess the impact of new legal provisions on the functioning of capital markets.

This chapter explores the nature of military law and IHL during the cold war period. It explores what treaties were completed, Additional Protocols I and II of the 1949 Geneva Conventions, the ad hoc international tribunals of the 1990s and 2000s, and examines the ICJ’s ruling of the legality of nuclear weapons.

Given continued debates on the potentials of newly emerging artificial intelligence (AI) like generative AI (GenAI), this study aims to contribute to corporal studies by investigating the efficacy of GenAI in improving students writing skills.

A mixed-methods research design with an experimental approach was used to elicit information from 70 undergraduate students studying at a private university. A writing course was designed and used to elicit information from the participants on the efficacy of using ChatGPT in their writing instruction.

After collecting data through experiments and interviews, the result indicates that although ChatGPT may assist students in providing ideas in writing lessons, it may not improve their overall writing skills.

This study provides empirical evidence limited to the scholarly literature on the role of ChatGPT in improving students’ writing skills. This study adds to scholarly discussions on the potential of ChatGPT which has recently sparked debates in academia.

The study aims to explore how integrating recent fundamental values (RFVs) from conventional accounting studies enhances the accuracy of a machine learning (ML) model for predicting stock return movement in Indonesia.

The study uses multilayer perceptron (MLP) analysis, a deep learning model subset of the ML method. The model utilizes findings from conventional accounting studies from 2019 to 2021 and samples from 10 firms in the Indonesian stock market from September 2018 to August 2019.

Incorporating RFVs improves predictive accuracy in the MLP model, especially in long reporting data ranges. The accuracy of the RFVs is also higher than that of raw data and common accounting ratio inputs.

The study uses Indonesian firms as its sample. We believe our findings apply to other emerging Asian markets and add to the existing ML literature on stock prediction. Nevertheless, expanding to different samples could strengthen the results of this study.

Governments can regulate RFV-based artificial intelligence (AI) applications for stock prediction to enhance decision-making about stock investment. Also, practitioners, analysts and investors can be inspired to develop RFV-based AI tools.

Studies in the literature on ML-based stock prediction find limited use for fundamental values and mainly apply technical indicators. However, this study demonstrates that including RFV in the ML model improves investors’ decision-making and minimizes unethical data use and artificial intelligence-based fraud.

This study examines the impact of inter-organisational justice (i.e. distributive, procedural and interactional) in the buyer–supplier relationship on supply risk and, in turn, on a firm’s marketing and financial performance.

A structured survey was administered both online and in-person to Jordan-based manufacturing companies. The 137 responses received were analysed using partial least structural equation modelling.

The study found that while establishing both procedural and interactional justice in the relationship has a negative impact on supply risk, promoting distributive justice, surprisingly, has no impact. Moreover, supply risk was found to be detrimental to the firm’s marketing and financial performance.

This study considers only the direct role of inter-organisational justice in reducing supply risk. Future research could enhance our understanding of this role by exploring the underlying mechanisms and conditions that could govern it.

Managers can alleviate supply risk by ensuring procedural and interactional justice in the relationship through involving suppliers in the decision-making processes, consistently adhering to established procedures and communicating transparent and ample information.

Addressing supply risk can help in maintaining community resilience and economic stability.

The study highlights inter-organisational justice as a new approach to mitigating supply risk. Moreover, by examining how supply risk can affect a firm’s marketing performance, it also highlights a new implication of supply risk. Furthermore, by exclusively examining the impact of supply risk on a firm’s financial performance, the study provides a more nuanced interpretation of the effect of supply risk and how it can be reduced.