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The purpose of this study is to unpack the relationship between employees’ perceptions of organizational politics and their counterproductive work behaviour, by postulating a mediating role of organizational disidentification and a moderating role of perceived external crisis threats to work.

The empirical assessment of the hypotheses relies on survey data collected among employees who work in a large banking organization.

Perceptions that organizational decision-making is marked by self-serving behaviour increase the probability that employees seek to cause harm to their employer, because they feel embarrassed by their organizational membership. This mediating role of organizational disidentification is especially prominent when they ruminate about the negative impact of external crises on their work.

This study details an important danger for employees who feel upset with dysfunctional politics: They psychologically distance themselves from their employer, which then prompts them to formulate counterproductive responses that likely make it more difficult to take on the problem in a credible manner. This detrimental dynamic is particularly risky if an external crisis negatively interferes with their work functioning.

This study adds to prior research by detailing an unexplored but relevant mechanism (organizational disidentification) and moderator (external crisis threats) by which perceived organizational politics translates into enhanced counterproductive work behaviour.

The author develops a bilateral Nash bargaining model under value uncertainty and private/asymmetric information, combining ideas from axiomatic and strategic bargaining theory. The solution to the model leads organically to a two-tier stochastic frontier (2TSF) setup with intra-error dependence. The author presents two different statistical specifications to estimate the model, one that accounts for regressor endogeneity using copulas, the other able to identify separately the bargaining power from the private information effects at the individual level. An empirical application using a matched employer–employee data set (MEEDS) from Zambia and a second using another one from Ghana showcase the applied potential of the approach.

With the rapid development of Internet technology, cybersecurity threats such as security loopholes, data leaks, network fraud, and ransomware have become increasingly prominent, and organized and purposeful cyberattacks have increased, posing more challenges to cybersecurity protection. Therefore, reliable network risk assessment methods and effective network security protection schemes are urgently needed.

Based on the dynamic behavior patterns of attackers and defenders, a Bayesian network attack graph is constructed, and a multitarget risk dynamic assessment model is proposed based on network availability, network utilization impact and vulnerability attack possibility. Then, the self-organizing multiobjective evolutionary algorithm based on grey wolf optimization is proposed. And the authors use this algorithm to solve the multiobjective risk assessment model, and a variety of different attack strategies are obtained.

The experimental results demonstrate that the method yields 29 distinct attack strategies, and then attacker's preferences can be obtained according to these attack strategies. Furthermore, the method efficiently addresses the security assessment problem involving multiple decision variables, thereby providing constructive guidance for the construction of security network, security reinforcement and active defense.

A method for network risk assessment methods is given. And this study proposed a multiobjective risk dynamic assessment model based on network availability, network utilization impact and the possibility of vulnerability attacks. The example demonstrates the effectiveness of the method in addressing network security risks.

This study aims to identify and explore different risk typologies associated with consumer acceptance of purchase recommendations from voice assistants (VAs).

Drawing on components of perceived risk, consumer trust theory, and consumption value theory, a research model was proposed and tested using structural equation modeling (SEM) with data from 482 voice shoppers.

The results reveal that, unlike risks associated with physical harm, privacy breaches, and security threats, a variety of other concerns—including financial, psychological, social, performance-related risks, time loss, and the overall perceived risks—significantly influence consumers' willingness to accept VAs purchase recommendations. The effect is mediated by trust in VA purchase recommendations and their perceived value. Different types of risk affect various consumption values, with functional value being the most influential. The model explains 58.6% of the variance in purchase recommendation acceptance and significantly elucidates the variance in all consumption values.

This study contributes crucial knowledge to understanding consumer decision-making processes as they increasingly leverage AI-powered voice-based dialogue platforms for online purchasing. It emphasizes recognizing diverse risk typologies associated with VA purchase recommendations and their impact on consumer purchase behavior. The findings offer insights for marketing managers seeking to navigate the challenges posed by consumers' perceived risks while leveraging VAs as an integral component of modern shopping environments.

The study of shame has a long tradition in intra- and inter-personal psychology. This paper aims to investigate whether consumers can experience brand shame after self-relevant consumption incidents. Specifically, this research proposes that consumers follow a complex shame-inducing process in the aftermath of unpleasant experiences involving their favorite brand. The moderating role of relational tie strength between consumers and their favorite brand existing prior to symbolic failures is examined.

A scenario-based, online survey (n = 660) among consumers who have recently experienced a self-relevant failure with their favorite brand was conducted. Confirmatory factor analysis ensured the reliability and validity of the measurement model. For testing the conceptual model, data was analyzed by means of a moderated mediation analysis. The proposed model was tested against, among others, common method bias and alternative models. The findings were cross-validated with a scenario-based online experiment (n = 1,616).

Results show that brand shame is a key mediator between customer dissatisfaction and brand anger when self-relevant, symbolic failures happen. Moreover, strong consumer-brand identification triggers brand-detrimental effects. It is shown to influence the connection between consumers’ inward- (i.e. brand shame) and resulting outward-directed (i.e. brand anger) negative emotions on brands, which lead to consumer vengeance.

To the best of the authors’ knowledge, this research is the first to introduce the concept of situational brand shame to the literature on favorite brands. Furthermore, it shows that consumer-brand identification moderates the direct and indirect (via brand shame) unfavorable effects of failure-induced dissatisfaction on brand anger. This research adds insights to the investigation of the “love-becomes-hate” effect arising after self-relevant failures involving consumers’ most preferred brand.

This study aims to investigate how despotic leadership affects employee well-being through bullying behavior. The study further investigates emotional intelligence as a conditional variable on the association between bullying behavior and employee well-being.

The data from 257 nurses and their immediate supervisors (dyads) were collected on convenience basis using a cross-sectional design. Further, structural equation modeling was used to analyze the data.

The study noted that despotic leadership negatively affects employee well-being. Specifically, despotic leaders were noted to trigger employees’ bullying behavior that ultimately diminish their well-being. The study noted emotional intelligence as a conditional variable such that individuals with high emotional intelligence are more likely to buffer the negative association between bullying behavior and employee well-being.

This study highlights the importance of employee well-being and suggests the management focus on their leadership style. Further, the study suggests to Human Resource practitioners the importance of personality traits (emotional intelligence) at the time of recruitment, as it serves as a coping strategy to diminish employee well-being.

Drawing upon the conservation of resources, this study shed light on the mediating role of bullying behavior between negative leadership (despotic) and well-being. In addition, emotional intelligence has not been examined as a conditional variable between bullying behavior and employee well-being.

To estimate the volatility of exchange and stock markets and examine its spillover within and across the member countries of BRICS during COVID-19 and the conflict between Russia and Ukraine.

The study utilizes the “dynamic conditional correlation-generalized autoregressive conditional heteroskedasticity (DCC-GARCH)” approach of Gabauer (2020). The volatility of the markets is calculated following the approach of Parkinson (1980). The sample dataset comprises the daily volatility of the stock and exchange markets for 35 months, from November 2019 to September 2022.

The study confirms the existence of contagion effects among member countries. Volatility spillover between exchange and stock markets is low within the country but substantial across borders. Russian contribution increased significantly during the conflict with Ukraine, and other countries also witnessed a surge in the spillover index during the pandemic and war.

It adds to the body of literature by emphasizing the necessity of comprehending the economies' behavior and interdependence. Offers insightful information to decision-makers who must be more watchful regarding the financial crisis and its regional spillover.

The study is the first to explore the contagion of volatility among the BRICS countries during the two biggest crisis periods of the decade.

Working remotely in a COVID-19-induced lockdown has been challenging for both organisations and their employees; studies report that job demands changed, and teleworkers experienced increased burnout. This paper explores the negative employee outcomes that this work arrangement brings along and offers possible solutions to counter such negative outcomes since they could be detrimental to the much-touted future of work.

The study adopted a time-lagged longitudinal design and collected two-waved data from 403 quaternary sector employees. The data were analysed using structural equation modelling and model-21 in PROCESS macro for SPSS.

Findings affirm that employees experienced increased job demands during this crisis. Employees reported an increase in turnover intention because of burnout caused by increased job demands. However, increased task interdependence alone did not have any effect on turnover intention. The perceived organisational task support (POTS) was found to forestall the negative effect of job demands on burnout, and employee resilience (ER) buffered the burnout and turnover intention relationship.

Providing remote work task support and boosting resilience among employees will help in doing away with the negative effects of teleworking. However, managers shall prioritise reducing job demands for teleworkers.

The linkage between work factors and turnover intention is well established. Drawing on the event system theory and using the COVID-19 context, the present study added to the existing knowledge by studying the role of job demands (workload pressure and task interdependence) on turnover intention through the mediation of burnout. The study goes beyond the existing literature by accounting for POTS as a first-level moderator between job demands and burnout relationship, and ER as a second-level moderator between burnout and turnover intention relationship.

Building on the premise of conservation of resources theory (COR) that people protect their knowledge as a resource, the authors questioned whether the contextual nature of job resources buffers the counterintuitive positive relationship between evasive knowledge hiding (KH) and task performance.

Two multisource field survey studies were conducted to examine the moderating influence of task-job resources on the knowledge hiders' task performance. Hierarchical regression analyses tested the main effect of evasive KH on task performance. In addition, conditional process analyses were applied to examine two-way and three-way interactions of evasive KH, job autonomy and task variety.

The data analysis showed a positive relationship between evasive KH and task performance. Moreover, the authors found that employees receiving accumulative task-job resources continued to hide knowledge and used abundant resources to increase their task performance further. However, contrary to expectations, for employees—who received partial task-job resources—their task performance deteriorated when evasively hiding knowledge.

Managers and human resource practitioners should acknowledge that employees' evasive KH to co-workers is not always wrong and should not be treated like it is. Moreover, they are endorsed to pay attention and invest in job resources since job autonomy and task variety create a beneficial context for knowledge holders' task performance.

The authors provided novel theoretical (the gain-loss perspective of COR theory) and consistent empirical (confirmed by two field-study evidence) arguments for an important contextual role of an HRM practice of job design in shaping the underrepresented knowledge behavior–task performance relationship.

This paper aims to examine the dynamic conditional correlation (DCC) and hedging ratios between Dow Jones markets and oil, gold and bitcoin. Using daily data, including the COVID-19 pandemic and the Russia–Ukraine war. We employ the DCC-generalized autoregressive conditional heteroskedasticity (GARCH) and asymmetric DCC (ADCC)-GARCH models.

DCC-GARCH and ADCC-GARCH models.

The most of DCCs among market pairs are positive during COVID-19 period, implying the existence of volatility spillovers (Contagion-effects). This implies the lack of additional economic gains of diversification. So, COVID-19 represents a systematic risk that resists diversification. However, during the Russia–Ukraine war the DCCs are negative for most pairs that include Oil and Gold, implying investors may benefit from portfolio-diversification. Our hedging analysis carries significant implications for investors seeking higher returns while hedging their Dow Jones portfolios: keeping their portfolios unhedged is better than hedging them. This is because Islamic stocks have the ability to mitigate risks.

Our paper may make a valuable contribution to the existing literature by examining the hedging of financial assets, including both conventional and Islamic assets, during periods of stability and crisis, such as the COVID-19 pandemic and the Russia–Ukraine war.