PurposeExtant research has shown that workplace ostracism (WO) elicits counterproductive work behaviors, such as employee silence (ES), culminating in reduced job performance. However, lesser is known about the factors that buffer against this underlying linkage. With an emphasis on conservation of resource (COR) theory and social identity theory, this study investigates the hitherto unexplored moderating roles of moral identification (MI) and organizational identification (OI) in the relationship between WO and ES.Design/methodology/approachThe study employed a time-lagged design to collect multi-source data from 250 employees working in the service sector organizations in Pakistan. Data are analyzed in SMARTPLS (v 3.3.3) to assess the measurement model and the structural model.FindingsResults reveal that WO is positively correlated with ES and negatively correlated with job performance. At the same time, ES mediates the negative relationship between WO and job performance. In addition, MI and OI buffer against the positive connection between WO and ES. The positive association between WO and ES is less pronounced at high levels of MI and OI and vice versa.Practical implicationsThe findings indicate that there is potential value in developing MI and OI, for which several interventions are discussed.Originality/valueThis study is one of the few efforts to outstretch the boundary conditions of ES. Moreover, this is the first study to investigate the role of identity-based perspective in the relationship between WO and ES.
This research was aimed at investigating the environmentally responsible behavior of tourists and their satisfaction with a tourist destination. Moreover, this study examined the effects of employee service quality, perceived value, environmental commitment and tourist satisfaction with a destination on loyalty and environmentally responsible behavior. We used data from tourists (n = 640) who had previously visited the world’s longest natural sea beach (Cox’s Bazar, Bangladesh). A partial least square structural equation model (PLS-SEM) method was used in this study to evaluate the proposed model and hypotheses. The results suggest that the perceived value of the destination has a significantly positive impact on both tourist satisfaction and environmental commitment. Similarly, employee service quality significantly impacts perceived value, tourist satisfaction and environmental commitment. Thus, both perceived value and employee service quality also substantially affect the environmentally responsible behavior at the Cox’s Bazar tourist destination. The main contribution of this research involved an investigation of the mediating effects of environmental commitment and tourist satisfaction with a destination on loyalty and environmentally responsible behavior using a single model based on relationship quality theory. Tourist satisfaction was found to completely mediate the relationship between the perceived value of a destination and environmentally responsible behavior, as well as loyalty. In addition, the theoretical and managerial implications for the destination were discussed.
Education is the cultivation of people to promote and guarantee the development of society. Education reforms can play a vital role in the development of a country. However, it is crucial to continually monitor the educational model’s performance by forecasting the outcome’s progress. Machine learning-based models are currently a hot topic in improving the forecasting research area. Forecasting models can help to analyse the impact of future outcomes by showing yearly trends. For this study, we developed a hybrid, forecasting time-series model by long short-term memory (LSTM) network and self-attention mechanism (SAM) to monitor Morocco’s educational reform. We analysed six universities’ performance and provided a prediction model to evaluate the best-performing university’s performance after implementing the latest reform, i.e., from 2015–2030. We forecasted the six universities’ research outcomes and tested our proposed methodology’s accuracy against other time-series models. Results show that our model performs better for predicting research outcomes. The percentage increase in university performance after nine years is discussed to help predict the best-performing university. Our proposed algorithm accuracy and performance are better than other algorithms like LSTM and RNN.
The impacts of the avian influenza virus (AIV) on farmed poultry and wild birds affect human health, livelihoods, food security, and international trade. The movement patterns of turkey birds from farms to live bird markets (LBMs) and infection of AIV are poorly understood in Bangladesh. Thus, we conducted weekly longitudinal surveillance in LBMs to understand the trading patterns, temporal trends, and risk factors of AIV circulation in turkey birds. We sampled a total of 423 turkeys from two LBMs in Dhaka between May 2018 and September 2019. We tested the swab samples for the AIV matrix gene (M-gene) followed by H5, H7, and H9 subtypes using real-time reverse transcriptase-polymerase chain reaction (rRT-PCR). We used exploratory analysis to investigate trading patterns, annual cyclic trends of AIV and its subtypes, and a generalized estimating equation (GEE) logistic model to determine the factors that influence the infection of H5 and H9 in turkeys. Furthermore, we conducted an observational study and informal interviews with traders and vendors to record turkey trading patterns, demand, and supply and turkey handling practices in LBM. We found that all trade routes of turkey birds to northern Dhaka are unidirectional and originate from the northwestern and southern regions of Bangladesh. The number of trades from the source district to Dhaka depends on the turkey density. The median distance that turkey was traded from its source district to Dhaka was 188 km (Q1 = 165, Q3 = 210, IQR = 45.5). We observed seasonal variation in the median and average distance of turkey. The qualitative findings revealed that turkey farming initially became reasonably profitable in 2018 and at the beginning of 2019. However, the fall in demand and production in the middle of 2019 may be related to unstable market pricing, high feed costs, a shortfall of adequate marketing facilities, poor consumer knowledge, and a lack of advertising. The overall prevalence of AIV, H5, and H9 subtypes in turkeys was 31% (95% CI: 26.6–35.4), 16.3% (95% CI: 12.8–19.8), and 10.2% (95% CI: 7.3–13.1) respectively. None of the samples were positive for H7. The circulation of AIV and H9 across the annual cycle showed no seasonality, whereas the circulation of H5 showed significant seasonality. The GEE revealed that detection of AIV increases in retail vendor business (OR: 1.71; 95% CI: 1.12–2.62) and the bird’s health status is sick (OR: 10.77; 95% CI: 4.31–26.94) or dead (OR: 11.33; 95% CI: 4.30–29.89). We also observed that winter season (OR: 5.83; 95% CI: 2.80–12.14) than summer season, dead birds (OR: 61.71; 95% CI: 25.78–147.75) and sick birds (OR 8.33; 95% CI: 3.36–20.64) compared to healthy birds has a higher risk of H5 infection in turkeys. This study revealed that the turkeys movements vary by time and season from the farm to the LBM. This surveillance indicated year-round circulation of AIV with H5 and H9 subtypes in turkey birds in LBMs. The seasonality and health condition of birds influence H5 infection in birds. The trading pattern of turkey may play a role in the transmission of AIV viruses in the birds. The selling of sick turkeys infected with H5 and H9 highlights the possibility of virus transmission to other species of birds sold at LBMs and to people.
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