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This work proposes a framework that attempts to explain the connection between the dimensions of consumer perceived corporate social responsibility (social, environmental, economic), firm trustworthiness and firm reputation, using market level of development as a moderating factor.

Mexico and Spain were selected as the emerging and developed markets; a cross-cultural study with 1173 consumers (521 from Mexico and 652 from Spain) was undertaken. In each country, participants evaluated one of two well-known companies (one making consumer products and one providing retail services). The hypotheses were tested through SEM.

The results showed that, in the emerging market, perceived environmental actions did not influence consumers' perceptions and, in the developed market, perceived social actions had no effect.

The study identifies two mechanisms through which consumers' perceptions of a company's CSR influence company reputation, offering evidence that the level of development of a country can have a moderating effect on how the mechanisms operate.

Across the USA, local municipalities and providers struggle to reliably supply water and electricity when faced with severe weather events induced by climate change. Previous research suggests those at higher risk for experiencing the detrimental effects of climate change have higher climate-related concerns. Additionally, research demonstrates variation in trust in institutions and perceptions of environmental justice along racial lines, which can influence concern for access to resources. Informed by this research, the authors ask two questions: how do Oklahomans’ trust in institutions, environmental justice perceptions and global climate change risk perceptions differ based on race, and how do these factors influence concern for water and electrical infrastructure? The purpose of this study is to better understand Oklahomans’ trust in information from institutions, environmental justice perceptions, global climate change risk perceptions and concern for water and electrical infrastructure.

This study uses a series of nested regression models to analyze the survey responses of 2,687 Oklahoman adults. The data were pulled from Wave 3 of the Oklahoma Meso-scale Integrated Socio-geographic Network survey, which is part of the National Science Foundation EPSCoR S3OK project.

The findings demonstrate the complex interplay of riskscapes – or risk landscapes – that encompass institutional trust, perceptions of environmental justice, climate change and infrastructure in Oklahoma. The authors find evidence that education and income are better predictors of institutional trust and environmental justice than race among our respondents. Political ideology emerges as a significant predictor across all hypotheses.

This study contributes to the understanding of complex dynamics involving race, perceptions of environmental justice, trust in information from institutions, risk perceptions of climate change and concerns for water and electrical infrastructure in Oklahoma.

The development of digital technology has provided technical support to various industries. Specifically, Internet-based freight platforms can ensure the high-quality development of the logistics industry. Online freight platforms can use cargo transportation insurance to improve their service capabilities, promote their differentiated development, create products with platform characteristics and increase their core competitiveness.

This study uses a generalised linear model to fit the claim probability and claim intensity data and analyses freight insurance pricing based on the freight insurance claim data of a freight platform in China.

Considering traditional pricing risk factors, this study adds two risk factors to fit the claim probability data, that is, the purchase behaviour of freight insurance customers and road density. The two variables can significantly influence the claim probability, and the model fitting outcomes obtained with the logit connection function are excellent. In addition, this study examines the model results under various distribution types for the fitting of the claim intensity data. The fitting outcomes under a gamma distribution are superior to those under the other distribution types, as measured by the Akaike information criterion.

With actual data from an online freight platform in China, this study empirically proves that a generalised linear model is superior to traditional pricing methods for freight insurance. This study constructs a generalised linear pricing model considering the unique features of the freight industry and determines that the transportation distance, cargo weight and road density have a significant influence on the claim probability and claim intensity.

To measure the dynamic features of compassion as an emotional and behavioral construct, the present research used a univariate latent growth modeling (LGM) approach within the structural equation modeling (SEM) framework. The aim was to trace the dynamic development of compassion longitudinally in accounting and business students during a three-credit English course at university.

The suggested method ensures the measurement invariance over time, deals with the first order latent variable, traces its growth and takes into account the measurement errors. This longitudinal analytical method was used to explore the initial state and the growth of compassion in four points of time during a language course. The data were collected from 60 adult accounting and business students in four time phases using Sprecher and Fehr's Compassionate Love Scale and were analyzed in Mplus 8.4 with univariate LGM.

The model fit was accepted and the invariance of the latent factor was confirmed over time. The negative covariance between intercept and slope (second-order latent variables) suggested that lower initial scores in L2 learners' compassion show a faster increase in compassion over time as the mean of slope is larger than that of the intercept. L2 learners who started off at a higher level of compassion showed a slower change in compassion over time. This can be at least partly explained by the teacher's motivating role or learners' compassion but needs to be further explored in complementary qualitative phases for deeper insights.

In the present research, awareness was raised of the developmental nature of compassion as an emotional and behavioral construct essential to the accounting and business profession. The great strength of this research lies in the dynamic approach to the compassion construct and the LGM used to capture the temporal growth of compassion and how it evolved through the L2 course.

The purpose of this paper is to draw on the agent-system model of (in)justice and negative norm of reciprocity of social exchange theory to examine the indirect impact of supervisory interactional injustice (i.e. interpersonal and informational) on employees’ target-specific extra-role work behaviours [counterproductive work behaviour directed at supervisor (CWB-S) and organisational citizenship behaviour directed at supervisor (OCB-S)] via distrust in supervisor.

The authors conducted a two-wave study, and participants (n = 401) were recruited via Amazon Mechanical Turk using a survey methodology. Bias-corrected confidence intervals (CIs) constructed in 20,000 bootstrap samples were used to test the mediation effects.

The findings indicated that interpersonal and informational injustice are positively related to employees’ distrust in supervisor. Furthermore, interpersonal and informational injustice indirectly affected CWB-S and OCB-S via distrust in supervisor.

Several limitations and future research should be discussed. First, the cross-sectional nature of this study prevented us from establishing the causal direction implied by the mediation models in this research. Second, the authors cannot rule out the potential for common method variance. These limitations can be addressed by collecting data from multiple sources (e.g. supervisor and coworkers) at different points in time or by experimental study design. Lastly, the authors did not consider contextual variables (e.g. formal policies, practices, ethical rules and cultural climate) that may influence the proposed relationships’ strengths and directions.

Even though perceptions of distributive and procedural injustice can affect employee deviant behaviours targeted at the organisation and organisational members, the present findings suggest that practitioners should be aware that perceptions of supervisory interactional injustice (i.e. interpersonal and informational) are likely be requited with employees’ extra-role work behaviours targeted at the supervisor. The present findings suggest that, via distrust in supervisor, employees are likely to engage in more CWB-S and fewer OCB-S as a result of supervisory interactional injustice. Considering the costs associated with high CWB-S and low OCB-S, supervisors should be trained in adhering to interactional justice rules. Additionally, supervisors should be mindful and practice caution when interacting with subordinates, to ensure that interactional justice norms are not violated. Lastly, supervisors can seek feedback from subordinates regarding their perceptions of supervisory interactional injustice, as these assessments will allow the supervisors to adapt their behaviours to impede subordinates’ deviant behaviours aimed towards them.

This study contributes to the literature on organisational injustice and workplace behaviour. First, most injustice research assumes that injustice is the opposite of justice; this study examines the effect of interactional injustice. Second, the authors develop a target-specific model focusing on the interactions between two key organisational stakeholders (i.e. supervisors and employees). The authors suggest that supervisor’s disrespect and untruthfulness towards the employee will eventually result in employee revenge (i.e. CWB-S) and lack of cooperation (i.e. OCB-S) towards supervisor. Finally, the authors examine the mechanism (i.e. distrust in supervisor) through which supervisory interactional injustice may ensue in employee extra-role behaviours directed at the supervisor.

Drawing on the work as calling theory, the purpose of this study is to explore how and when career calling promotes taking charge by focusing on the mediating effects of work meaningfulness and felt obligation and the moderating role of family-friendly human resource practice (FF-HRP).

The authors collected data from 293 supervisor–employee dyads at three time points in southeastern China. Path analysis and bootstrap method were used for hypothesis testing.

Employees' perceived career calling positively affected taking charge through work meaningfulness and felt obligation. The positive effects of career calling on work meaningfulness and felt obligation as well as the indirect effect of career calling on taking charge are stronger when employees perceive high levels of FF-HRP.

Organizational interventions should be designed to enhance employees' sense of calling, and the organization should inspire employees to take charge by awakening their perception of work meaningfulness and obligation. Moreover, FF-HRP should be implemented as a form of organizational support.

This research identifies work meaningfulness and felt obligation as mediators that link career calling to taking charge and reveals the role of FF-HRP in amplifying the positive impact of career calling.

This paper investigates the predictive impact of Financial Stress on hedging between the oil market and the GCC stock and bond markets from January 1, 2007, to December 31, 2020. The authors also compare the hedging performance of in-sample and out-of-sample analyses.

For the modeling purpose, the authors combine the GARCH-BEKK model with the machine learning approach to predict the transmission of shocks between the financial markets and the oil market. The authors also examine the hedging performance in order to obtain well-diversified portfolios under both Financial Stress cases, using a One-Dimensional Convolutional Neural Network (1D-CNN) model.

According to the results, the in-sample analysis shows that investors can use oil to hedge stock markets under positive Financial Stress. In addition, the authors prove that oil hedging is ineffective in reducing market risks for bond markets. The out-of-sample results demonstrate the ability of hedging effectiveness to minimize portfolio risk during the recent pandemic in both Financial Stress cases. Interestingly, hedgers will have a more efficient hedging performance in the stock and oil market in the case of positive (negative) Financial Stress. The findings seem to be confirmed by the Diebold-Mariano test, suggesting that including the negative (positive) Financial Stress in the hedging strategy displays better out-of-sample performance than the in-sample model.

This study improves the understanding of the whole sample and positive (negative) Financial Stress estimates and forecasts of hedge effectiveness for both the out-of-sample and in-sample estimates. A portfolio strategy based on transmission shock prediction provides diversification benefits.

Drawing on signaling theory and the “signal transmission–interpretation–feedback” framework, this study explores the effects of perceived distributive justice and respect from managers on nurses' work meaningfulness and work effort in public hospitals in China and examines the moderating role of work self-efficacy.

We collected 341 paired questionnaires for nurses and managers from four public hospitals in China. The data were analyzed by structural equation modeling and hierarchical regression analysis.

Distributive justice and managers' respect for employees are positively related to work meaningfulness. Additionally, work self-efficacy negatively moderates this relationship. Work meaningfulness is positively related to work effort and fully mediates the relationships between perceived distributive justice and respect from the manager and work effort.

This study provides useful insights for healthcare organizations to improve nurses' work meaningfulness from the perspectives of their material and emotional needs, according to their work self-efficacy characteristics, thus promoting their work effort. The findings offer important guidance for improving the effectiveness of grass-roots human resources to cope with unpredictable situations such as the COVID-19 pandemic.

This study focuses on the organization's environmental factors that affect the primary staff's work meaningfulness. Further, it analyzes the differences in signal interpretation among nurses with different work self-efficacy characteristics, thus providing new insights into work meaningfulness. Through manager–nurse pairing data, it reveals the important role of work meaningfulness in motivating work effort.

The purpose of this study is to investigate the complexity of how demands and stress are mitigated to enhance employee performance in remote working arrangements.

A time-lagged snowball sample of 223 full-time remote working adults in the United States participated in an online survey. Data were analyzed using R 4.0.2 and structural equation modeling.

Results suggest remote job resources involving organizational trust and work flexibility increase performance via serial mediation when considering information communication technology (ICT) demands and work–life interference (WLI). The findings provide insights into counterbalancing the negative aspects of specific demands and stress in remote work arrangements.

This study provides insights for managers to understand how basic job resources may shape perspectives on demands and WLI to impact performance. Specific to remote working arrangements, establishing trust with the employees and promoting accountability with their work flexibility can play an important part in people and their performance.

This study contributes theoretically to the literature by evidencing how components of the E-Work Life (EWL) scale can be used with greater versatility beyond the original composite measurement because of the job-demand resource (JD-R) framework and conservation of resources theory (COR). This study answers several calls by research to investigate how ICT demands and WLI play a complex role in work performance.

The purpose of this study is to revisit the measures of internal consistency for multi-item scales in hospitality research and compare the performance of Cronbach’s α, omega total (ω_Total), omega hierarchical (ω_H), Revelle’s omega total (ω_RT), Minimum Rank Factor Analysis (GLB_fa) and GLB algebraic (GLB_a).

A Monte Carlo simulation was conducted to compare the performance of the six reliability estimators under different conditions common in hospitality research. Second, this study analyzed a data set to complement the simulation study.

Overall, ω_Total was the best-performing estimator across all conditions, whereas ω_H performed the poorest. α performed well when factor loadings were high with low variability (high/low) and large sample sizes. Similarly, ω_RT, GLB_fa and GLB_a performed consistently well when loadings were high and less variable as well as the sample size and the number of scale items increased. Of the two GLB estimators, GLB_a consistently outperformed GLB_fa.

This study provides hospitality managers with a better understanding of what reliability is and the various reliability estimators. Using reliable instruments ensures that organizations draw accurate conclusions that help them move closer to realizing their visions.

Though popular in other fields, reliability discussions have not yet received substantial attention in hospitality. This study raises these discussions in the context of hospitality research to promote better practices for assessing the reliability of scales used within the hospitality domain.