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While the main purpose of reporting – e.g. reporting for taxes – is to gauge the economic state of a company, the fact that reporting is done at pre-determined dates distorts the reporting results. For example, to create a larger impression of their productivity, companies fire temporary workers before the reporting date and re-hire then right away. The purpose of this study is to decide how to avoid such distortion.

This study aims to come up with a solution which is applicable for all possible reasonable optimality criteria. Thus, a general formalism for describing and analyzing all such criteria is used.

This study shows that most distortion problems will disappear if the fixed pre-determined reporting dates are replaced with individualized random reporting dates. This study also shows that for all reasonable optimality criteria, the optimal way to assign reporting dates is to do it uniformly.

This study shows that for all reasonable optimality criteria, the optimal way to assign reporting dates is to do it uniformly.

It is found that the individualized random tax reporting dates would be beneficial for economy.

It is found that the individualized random tax reporting dates would be beneficial for society as a whole.

This study proposes a new idea of replacing the fixed pre-determining reporting dates with randomized ones. On the informal level, this idea may have been proposed earlier, but what is completely new is our analysis of which randomization of reporting dates is the best for economy: it turns out that under all reasonable optimality criteria, uniform randomization works the best.

We present an approach for pricing American put options with a regime-switching volatility. Our method reveals that the option price can be expressed as the sum of two components: the price of a European put option and the premium associated with the early exercise privilege. Our analysis demonstrates that, under these conditions, the perpetual put option consistently commands a higher price during periods of high volatility compared to those of low volatility. Moreover, we establish that the optimal exercise boundary is lower in high-volatility regimes than in low-volatility regimes. Additionally, we develop an analytical framework to describe American puts with an Erlang-distributed random-time horizon, which allows us to propose a numerical technique for approximating the value of American puts with finite expiry. We also show that a combined approach involving randomization and Richardson extrapolation can be a robust numerical algorithm for estimating American put prices with finite expiry.

The purpose of this study is to examine the sociocultural implications of caring for persons with COVID-19 in a developing country context.

In total, 156 nurses participated in the study. Stratified random sampling methodology was used. Data were collected via online self-administered questionnaire. Descriptive and inferential statistics, including ANOVA tests were done.

Nurses experienced stigmatization, discrimination and reduced income. Nurses functioned on the frontline during the COVID-19 pandemic and encountered negative sociocultural experiences from a personal, social and professional perspective. ANOVA showed statistically significant relationships between the conflicts between their work role, family commitments and level of physical interactions with a number of variables.

Data were collected from one Regional Health Authority and may not be representative of the national population of nurses. Further, as the researchers depended on gatekeepers to access participants, the recruitment process may not have been entirely based on randomization as originally agreed.

The findings from this study can be used as a framework to develop context specific programmes and policies to support health professionals, including nurses.

Pandemics, while not new, contribute to serious sociocultural challenges for individuals and families, as well as nurses, as part of their professional roles. In this regard, maintaining effective social networks must be central to effective functioning in crisis situations, such as pandemics.

Nurses have played a key role, working both to identify, isolate and manage those with COVID-19 and supporting those who have non-COVID-19 related health needs. While nurses have been at the forefront delivering care in these uncertain times, doing so puts them at great risk, for not only contracting COVID-19 but also for experiencing negative psychosocial effects that may be due to the nature of their jobs.

This study aims to explore the spillover effects of data breaches from a consumer perspective in the e-commerce context. Specifically, we investigate how an online retailer’s data breach affects consumers’ privacy risk perceptions of competing firms, and further how it affects shopping intention for the competitors. We also examine how the privacy risk contagion effect varies depending on the characteristics of competitors and their competitive responses.

We conducted two scenario-based experiments with surveys. To assess the spillover effects and the moderating effects, we employed an analysis of covariance. We also performed bootstrapping-based mediation analyses using the PROCESS macro.

We find evidence for the privacy risk contagion effect and demonstrate that it negatively influences consumers’ shopping intention for a competing firm. We also find that a competitor’s cybersecurity message is effective in avoiding the privacy risk contagion effect and the competitor even benefits from it.

While previous studies have examined the impacts of data breaches on customer perceptions of the breached firm, our study focuses on customer perceptions of the non-breached firms. To the best of the authors’ knowledge, this study is one of the first to provide empirical evidence for the negative spillover effects of a data breach from a consumer perspective. More importantly, this study empirically demonstrates that the non-breached competitor’s competitive response is effective in preventing unintended negative spillover in the context of the data breach.

This paper aims to reflect on the outcomes of a community-based video-conferencing intervention for depression, predating the COVID-19 pandemic. The study investigates the potential implications of its findings for enhancing adherence to digital mental health interventions. The primary objective is to present considerations for researchers aimed at minimising the intention-behaviour gap frequently encountered in digital mental health interventions.

A randomised control feasibility trial design was used to implement a telehealth model adapted from an established face-to-face community-based intervention for individuals clinically diagnosed with depression. In total, 60 participants were initially recruited in association with a local mental health charity offering traditional talking-based therapies with only eight opting to continue through all phases of the project. Modifications aligning with technological advancements were introduced.

However, the study faced challenges, with low uptake observed after an initial surge in recruitment interest. The behaviour-intention gap highlighted technology as a barrier to service accessibility, exacerbated by participant age. Furthermore, the clinical diagnosis of depression, characterised by low mood and reduced interest in activities, emerged as a potential influencing factor.

The limitations of the research include its pre-pandemic execution, during a nascent stage of technological mental health interventions when participants were less familiar with online developments.

Despite these limitations, this study's reflections offer valuable insights for researchers aiming to design and implement telehealth services. Addressing the intention-behaviour gap necessitates a nuanced understanding of participant demographics, diagnosis and technological familiarity.

The study's relevance extends to post-pandemic society, urging researchers to reassess assumptions about technology availability to ensure engagement. This paper contributes to the mental health research landscape by raising awareness of critical considerations in the design and implementation of digital mental health interventions.

Reflections from a pre-pandemic intervention in line with the developments of a post-pandemic society will allow for research to consider that because the technology is available does not necessarily result in engagement.

To propose the use of indirect survey protocols, in general and the item count technique (ICT), in particular, that ensure participant anonymity in organizations to explore the effect of employee perceived abusive supervision on job performance.

We apply ICT to a sample of 363 employees (52.6% female) from Greek organizations. Utilizing multivariate statistical techniques, we investigated how employees assess the impact of their personal encounters with abusive supervision on job performance. This approach allowed us to explore the percentage of employees perceiving negative effects on job performance, distinguishing our study from previous studies that primarily focus on quantifying the extent or magnitude of abusive supervision in organizational settings. Also, we investigated how employee socio-demographic characteristics, human capital characteristics and affective traits relate to the evaluation of experienced abusive supervision as a negative factor for their job performance.

We found that approximately 62% of the respondents evaluated personal experience of abusive supervision as negatively affecting their job performance. We also found that the likelihood of employees evaluating personal experience of abusive supervision as having a negative impact on their job performance is: (1) higher for female employees, (2) does not depend on employee age, job tenure and education; (3) is lower for employees with managerial roles and (4) increases with employee trait negative affectivity.

The study is a response to the call for researchers to use innovative methods for advancing abusive supervision research. The study highlights the significance of taking a proactive stance towards addressing abusive supervision in the workplace, by using indirect survey methods that ensures employee anonymity. The results have implications for organizational strategies aimed at increasing awareness of abusive supervision and its impact on employee performance.

Financial services industry is increasingly showing interest in automated financial advisors, or robo-advisors, with the aim of democratizing access to financial advice and stimulating investment behavior among populations that were previously less active and less served. However, the extent to which consumers trust this technology influences the adoption of rob-advisors. The resemblance to a human, or anthropomorphism, can provide a sense of social presence and increase trust.

In this paper, we conduct an experiment (N = 223) to test the effect of anthropomorphism (low vs medium vs high) and gender (male vs female) of the robo-advisor on social presence. This perception, in turn, enables consumers to evaluate personality characteristics of the robo-advisor, such as competence, warmth, and persuasiveness, all of which are related to trust in the robo-advisor. We separately conduct an experimental study (N = 206) testing the effect of gender neutrality on consumer responses to robo-advisory anthropomorphism.

Our results show that consumers prefer human-alike robo-advisors over machinelike or humanoid robo-advisors. This preference is only observed for male robo-advisors and is explained by perceived competence and perceived persuasiveness. Furthermore, highlighting gender neutrality undermines the positive effect of robo-advisor anthropomorphism on trust.

We contribute to the body of knowledge on robo-advisor design by showing the effect of robot’s anthropomorphism and gender on consumer perceptions and trust. Consequently, we offer insightful recommendations to promote the adoption of robo-advisory services in the financial sector.

Corporations are confronted with growing demands to take a stand on socio-political issues, i.e. corporate social advocacy (CSA), which affects their reputation in the public. Companies use different CSA message strategies, including calling the public to support and act on the issue they advocate. Using reactance theory, the authors investigate the impact of CSA messages with a call to action on corporate reputation in the case of a company's gender equality initiative.

A one-factorial (CSA message with or without a call to action) between-subjects experiment was conducted by surveying 172 individuals living in Switzerland. The CSA messages were created in the context of gender equality.

The authors' study indicates that CSA messages with a call to action compared to those without overall harmed corporate reputation due to individuals' reactance, which is higher for CSA messages with a call to action, negatively affecting corporate reputation. The impact of the CSA message strategy with a call to action on corporate reputation remains significant after controlling for issue alignment and political leaning.

Communicating about socio-political issues, especially taking a stand, is a significant challenge for corporations in an increasingly polarized society and has often led to backlash, boycotts and damage to corporate reputation. This study shows that the possible adverse effects of advocating for socio-political issues can be related to reactance. It emphasizes that companies advocating for contested issues must be more cautious about the message strategy than the issue itself.

This paper aims to investigate the influence of sustainable enterprise resource planning (S-ERPs) systems implementation on sustainability performance.

A 1 × 2 experiment was conducted, involving a sample of 72 professional accountants enrolled in MPA, MBA and DBA programs at two prominent Egyptian universities. Simple linear regression was used to analyze the data.

The results reveal positive relationships between the implementation of S-ERPs and economic, environmental and social sustainability performance.

Considering the research methodology used, which relies on a laboratory experiment design; nevertheless, empirical data derived from a quasi-experiment conducted in a real-world context would offer valuable insights into the existing literature.

For manufacturing sector managers, the results offer value as organizations can benefit from S-ERP adoption in the internal and external integration of sustainability functions. The findings also provide decision-makers in the manufacturing context, particularly in emerging countries, with tangible reasons to consider S-ERP adoption for holistic sustainability benefits including waste management, resource consumption reduction and management of sustainable supply chain complexities. Further, the findings provide valuable insights for ERP vendors on how they can develop their ERP packages to align with software sustainability criteria.

This study is among the few that experimentally investigates the influence of S-ERPs implementation on sustainability performance within the manufacturing sector, especially in an emerging context such as Egypt. This unique contribution provides valuable insights into the complex connection between technology adoption and sustainability outcomes.