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This study examines the effect of delegation of decision rights, moral justification (MJ), and ethical climate (EC) on managers’ misreporting in the financial services sector. We employed an online research panel called Qualtrics, to collect data based on a sample of 127 middle-level managers from various US financial services firms. We find that MJ mediates the relation between delegation and misreporting, suggesting delegation of decision rights increases employees’ misreporting indirectly by increasing MJ. We also find that EC significantly moderates the relationship between MJ and misreporting. Furthermore, our test of the moderated-mediation effect reveals that the indirect effect of the delegation of decision rights on misreporting through MJ is stronger when there is a higher level of instrumental climate (IC) and a lower level of principle climate (PC).

Management discretion in the decision to reduce payroll costs is an important but under-researched issue in management accounting. The authors leverage the experimental environment to test the role of organizational culture (close vs. distant) and managerial communion (concern for others) along with their interaction with sales decline persistence (one vs. two periods) on planned layoff decisions. The authors find that communal managers are hesitant to downsize employees and that a close organizational culture interacts with one period sales declines to reduce layoffs although the influence of culture is reduced with persistent sales declines. The authors also examine the influence of culture and communion on managers’ preference for pay cuts as an alternative to layoffs. The authors find that a close culture and higher communion are associated with decisions to choose pay cuts over layoffs; however, these costs interact such that managers low in communion in a distant culture express a higher preference for layoffs. These findings illustrate the combined influence of economic, organizational, and dispositional factors on manager decisions about the extent and form of labor cost reductions due to sales declines.

The purpose of this study is to use a lifetime income measure to evaluate the long-run housing affordability for an understudied cohort of households in the literature – the millennials. The authors do this in the context of Malaysia, measuring long-run affordability for four housing types across geographic locations and income distributions.

This study calculates a long-run housing affordability index (HAI) using data on house prices and household incomes. Essentially a ratio of predicted lifetime incomes to house prices, the HAI is computed for four common housing types in Malaysia from 2005 to 2016 and for six states in the country. The HAI is also compared across four income percentiles.

The analysis reveals varying patterns of housing affordability among different states in Malaysia. Housing affordability has declined since 2010, with most housing types being unaffordable for millennial-led households with the lowest income. Housing is most affordable for those in the highest income bracket, although even here, there are pockets of unaffordable housing as well.

Based on the findings, this study proposes three targeted interventions to improve housing affordability for Malaysian millennials.

This study fills a gap in the literature by examining the long-run housing affordability of Malaysian millennial-led households based on both geographic location and income distribution. The millennial population is understudied in the housing affordability literature, making this study a valuable contribution to the field.

This study aims to explore how science, technology, engineering, mathematics and medicine (STEMM) graduate students’ experiences with and conceptualizations of racism can more clearly expose the current racial climate across multiple academic institutions.

A mixed-method approach using a single online questionnaire consisting of open-ended and Likert scale questions about their perceptions of the racial climate in their department was completed by 34 graduate students of different races and STEMM disciplines.

Results from this study suggested that graduate students, regardless of race, consistently perceive STEMM as colorblind. The results also suggest that experiencing or witnessing racial discrimination is potentially predictive of perceptions of negative social support. Furthermore, multiracial and international graduate students often face different experiences of discrimination than do other graduate students.

By better understanding STEMM academic climates, higher education institutions can begin to reflect on the social barriers that may limit minoritized students from matriculating in academic STEMM spaces and affect retention.

Social movements are not monolithic entities. Activists and organizations disagree about the goals of the movement and the tactics to achieve these goals, including their framing tactics. Cultural sociologists have questioned the idea that tactical choice is rationally and strategically oriented, arguing that tactics are morally and emotionally grounded in the activists' lives. We follow this insight, though suggesting that activists make constant efforts to experience their action as rational, claiming a strategic status and a sense of efficacy for their lines of action. By studying framing resonance disputes in interactions between animal rights activists and mass media in south Brazil, we found that, to make their tactics accountable and justifiable, activists mobilize different folk theories on social transformation which allow their actions to be experienced as the best means to achieve the movement's ends.

This study addresses the ever-increasing cyber risks confronting the global banking sector, particularly in India, amid rapid technological advancements. The purpose of this study is to de velop an innovative cyber fraud (CF) response system that effectively controls cyber threats, prioritizes fraud, detects early warning signs (EWS) and suggests mitigation measures.

The methodology involves a detailed literature review on fraud identification, assessment methods, prevention techniques and a theoretical model for fraud prevention. Machine learning-based data analysis, using self-organizing maps, is used to assess the severity of CF dynamically and in real-time.

Findings reveal the multifaceted nature of CF, emphasizing the need for tailored control measures and a shift from reactive to proactive mitigation. The study introduces a paradigm shift by viewing each CF as a unique “fraud event,” incorporating EWS as a proactive intervention. This innovative approach distinguishes the study, allowing for the efficient prioritization of CFs.

The practical implications of such a study lie in its potential to enhance the banking sector’s resilience to cyber threats, safeguarding stability, reputation and overall risk management.

The originality stems from proposing a comprehensive framework that combines machine learning, EWS and a proactive mitigation model, addressing critical gaps in existing cyber security systems.