Demand forecasting is a scientific and methodical assessment of future demand for a critical product.The effective Demand Forecast Model (DFM) enables pharmaceutical companies to be successful in the global market. The purpose of this research paper is to validate various shallow and deep neural network methods for demand forecasting, with the aim of recommending sales and marketing strategies based on the trend/seasonal effects of eight different groups of pharmaceutical products with different characteristics. The root mean squared error (RMSE) is used as the predictive accuracy of DFMs. This study also found that the mean RMSE value of the shallow neural network-based DFMs was 6.27 for all drug categories, which was lower than deep neural network models. According to the findings, DFMs based on shallow neural networks can effectively estimate future demand for pharmaceutical products.

This paper attempts to gauge the satisfaction of agripreneurs and seeks to explore the effect of demographics and emporographics on the agripreneurs’ satisfaction. This study proposes a seven-dimension survey instrument, called AprenSAT, for measuring agripreneurs’ satisfaction. Responses from 784 agripreneurs are analyzed by applying exploratory and confirmatory factor analysis and multiple linear regression. The extraction of seven factors confirms that agripreneurs’ satisfaction is influenced by material availability, government support, farm growth, farm income, market performance, cultivation & production and perceived farm image. The linear regression result delineates that demographic factors such as age, education level and farming experience significantly influence the agripreneurs’ satisfaction. Similarly, variables of emporographics such as farm age, farm size, annual income, land ownership, sources of funds, and intercropping have a substantial influence on agripreneurs’ satisfaction. We recommend information dissemination, hands-on training, the creation of adequate infrastructure and technology adoption to enhance agripreneurs’ satisfaction and rural development.

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