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The purpose of this study is to reveal important insights by examining the relationships of two different field managers’ monitoring styles with performance through salespersons’ engagement.

Data was collected from 318 salespersons’ from 20 pharmaceutical firms. Given the performance-driven nature of the pharmaceutical sales profession, field managers seek to adopt the best monitoring style, which can optimize individual’s performance while providing a healthy work environment.

The results from multivariate analysis show the evidence of positive relationship between interactional monitoring and salespersons’ engagement. The results also confirm that engagement partially mediates the proposed relationships.

Authors assimilate and extend research and theory on field managers’ monitoring, salespersons’ performance and salespersons’ engagement to advance a model of salespersons’ reactions to different monitoring styles based on self-determination theory. Perhaps in no other field, the salespersons-field managers’ relationship is as important as in the field of pharmaceutical selling. The study offers insights about the important consequence of two different monitoring styles; also the study is one of the exceptional efforts to provide evidence regarding the role of engagement in the relationship between two different monitoring styles and salespersons’ performance.

The study aims to investigate the presence of herding behavior in the stock market of UK with a special emphasis on news sentiment regarding the economy. The authors focus on the news sentiment because in the current digital era, investors take their decision making on the basis of current trends projected by news and media platforms.

For empirical modeling, the authors use machine learning models to investigate the presence of herding behavior in UK stock market for the period starting from 2006 to 2021. The authors use support vector regression, single layer neural network and multilayer neural network models to predict the herding behavior in the stock market of the UK. The authors estimate the herding coefficients using all the models and compare the findings with the linear regression model.

The results show a strong evidence of herding behavior in the stock market of the UK during different time regimes. Furthermore, when the authors incorporate the economic uncertainty news sentiment in the model, the results show a significant improvement. The results of support vector regression, single layer perceptron and multilayer perceptron model show the evidence of herding behavior in UK stock market during global financial crises of 2007–08 and COVID’19 period. In addition, the authors compare the findings with the linear regression which provides no evidence of herding behavior in all the regimes except COVID’19. The results also provide deep insights for both individual investors and policy makers to construct efficient portfolios and avoid market crashes, respectively.

In the existing literature of herding behavior, news sentiment regarding economic uncertainty has not been used before. However, in the present era this parameter is quite critical in context of market anomalies hence and needs to be investigated. In addition, the literature exhibits varying results about the existence of herding behavior when different methodologies are used. In this context, the use of machine learning models is quite rare in the herding literature. The machine learning models are quite robust and provide accurate results. Therefore, this research study uses three different models, i.e. single layer perceptron model, multilayer perceptron model and support vector regression model to investigate the herding behavior in the stock market of the UK. A comparative analysis is also presented among the results of all the models. The study sheds light on the importance of economic uncertainty news sentiment to predict the herding behavior.

This paper investigates the role of psychological contract violation (PCV) as the antecedent of employee turnover intention. It also explores the role of job dissatisfaction and work disengagement as the sequential underlying mechanism of a positive effect of PCV on employee turnover intention.

Drawing on social exchange theory (SET), the authors postulate that PCV triggers negative reciprocity behaviour in employees, which leads to job dissatisfaction and work disengagement, which in turn develop into turnover intentions. The authors tested the research model on time-lagged data from 200 managers working in the banking sector of Pakistan.

The findings confirmed the hypothesis that employees experiencing PCV raise their turnover intentions because of a feeling of organisational betrayal which makes them dissatisfied and detached from their work.

This research advances the body of knowledge in the area of psychological contracts by identifying the mechanisms through which PCVs translate into employee turnover intentions.