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Climate change-induced weather changes are severe and frequent, making it difficult to predict apparel sales. The primary goal of this study was to assess consumers' responses to winter apparel searches when external stimuli, such as weather, calendars and promotions arise and to develop a decision-making tool that allows apparel retailers to establish sales strategies according to external stimuli.

The theoretical framework of this study was the effect of external stimuli, such as calendar, promotion and weather, on seasonal apparel search in a consumer's decision-making process. Using weather observation data and Google Trends over the past 12 years, from 2008 to 2020, consumers' responses to external stimuli were analyzed using a classification and regression tree to gain consumer insights into the decision process. The relative importance of the factors in the model was determined, a tree model was developed and the model was tested.

Winter apparel searches increased when the average, maximum and minimum temperatures, windchill, and the previous day's windchill decreased. The month of the year varies depending on weather factors, and promotional sales events do not increase search activities for seasonal apparel. However, sales events during the higher-than-normal temperature season triggered search activity for seasonal apparel.

Consumer responses to external stimuli were analyzed through classification and regression trees to discover consumer insights into the decision-making process to improve stock management because climate change-induced weather changes are unpredictable.

This study aims to examine process improvement strategy (PIS) (proxied by remote work, workforce training, and technological innovation), and employee productivity amid the COVID-19 pandemic among bank employees.

The study employed cross-sectional and descriptive design by applying multistage sampling techniques using convenience sampling to select the study organization and stratified and simple random sampling to select 900 respondents for the study. Data were collected by using validated measures of the study variables designed into a questionnaire. Pearson’s correlation and simple regression analysis were employed to establish relationships and causal effects among variables respectively.

Results showed significant relationships between the PIS (work-from-home, workplace training, and technological innovation) and the outcome variable (employee productivity); and predictive capabilities between the PIS and the outcome variables (employee productivity). The study revealed that remote work accounted for the highest variability (R2 = 0.775) in employee productivity, followed by workplace training (R2 = 0.499), and finally investment in technological innovation (R2 = 0.486)] and as such PIS fosters employee productivity and may, therefore, be applied when faced with a similar pandemic in the future.

The study was recognized for its significance in examining how PIS supports enhancing employee productivity in banks and, by extension, other organizations during a pandemic. The research has proven to be crucial in providing insights into bank management in emerging economies and other organizations worldwide that have previously gone unnoticed during a pandemic. It has aided in the extension of existing literature on PIS and employee productivity by carefully developing a framework, thus covering practical knowledge gaps.