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This study, based on social exchange theory, aims to explore the association between appreciative leadership and employees' helping behaviors by investigating the mediation role of emotional reactions (pride, anxiety), and choosing organizational trust as a boundary condition between appreciative leadership and helping behaviors.

A total sample of 285 reliable questionnaires were collected in three time lags from employees working in the Pakistani education and banking sectors. PROCESS macro using SPSS and AMOS are employed for data analyses of the proposed model.

The findings reveal that appreciative leadership has positive impacts on employees' helping behaviors and emotional reactions (pride, anxiety) mediate the relationship of appreciative leadership and employees' helping behaviors. In addition, the results show that high organizational trust strengthens the positive relationship between appreciative leadership and employees' helping behaviors.

This research has provided empirical proof between the relationship of appreciative leadership and helping behaviors and the findings are of great significance for managers, employees, and organizations. The study proposes that leaders should have appreciative behavior while treating their subordinates. Moreover, it is revealed that the role of organizational trust should be given more attention and importance because it is a factor moderating the employees' helping behaviors.

The present study, among the first empirical efforts investigating the relationship between appreciative leadership and helping behaviors, organizational trust as a moderator, enriches the existing academic literature of and provides worthy insight into the research on appreciative leadership and helping behaviors.

Forecasting demand of emergency supplies under major epidemics plays a vital role in improving rescue efficiency. Few studies have combined intuitionistic fuzzy set with grey-Markov method and applied it to the prediction of emergency supplies demand. Therefore, this article aims to establish a novel method for emergency supplies demand forecasting under major epidemics.

Emergency supplies demand is correlated with the number of infected cases in need of relief services. First, a novel method called the Intuitionistic Fuzzy TPGM(1,1)-Markov Method (IFTPGMM) is proposed, and it is utilized for the purpose of forecasting the number of people. Then, the prediction of demand for emergency supplies is calculated using a method based on the safety inventory theory, according to numbers predicted by IFTPGMM. Finally, to demonstrate the effectiveness of the proposed method, a comparative analysis is conducted between IFTPGMM and four other methods.

The results show that IFTPGMM demonstrates superior predictive performance compared to four other methods. The integration of the grey method and intuitionistic fuzzy set has been shown to effectively handle uncertain information and enhance the accuracy of predictions.

The main contribution of this article is to propose a novel method for emergency supplies demand forecasting under major epidemics. The benefits of utilizing the grey method for handling small sample sizes and intuitionistic fuzzy set for handling uncertain information are considered in this proposed method. This method not only enhances existing grey method but also expands the methodologies used for forecasting demand for emergency supplies.

1. An intuitionistic fuzzy TPGM(1,1)-Markov method (IFTPGMM) is proposed.

2. The safety inventory theory is combined with IFTPGMM to construct a prediction method.

3. Asymptomatic infected cases are taken to forecast the demand for emergency supplies.

An intuitionistic fuzzy TPGM(1,1)-Markov method (IFTPGMM) is proposed.

The safety inventory theory is combined with IFTPGMM to construct a prediction method.

Asymptomatic infected cases are taken to forecast the demand for emergency supplies.