درخت حوزه‌های تخصصی

Export is a crucial driver of economic growth in various countries and significantly contributes to a country's entry into global markets and enhances economic success. In developing countries such as Iran, economic and social development programs prioritize the expansion of exports, particularly high value added agricultural products. The growth in non-oil exports, such as dried fruits, and the entry of domestic producers into new global markets have led to an increased demand for Iran's export products. This has also resulted in higher production levels, increased employment opportunities, and higher value added in the related activities. To enhance export performance, which is a crucial measure of a company's success in utilizing its resources and capabilities in the international arena over a specific period of time, it is important to focus on improving marketing strategies and specialized knowledge. Therefore, this research aims to examine the impact of marketing mix and specialized marketing knowledge on the export performance of small and medium-sized enterprises (SMEs) involved in exporting dried fruits in Mashhad, Iran in 2022. A total of 80 questionnaires were distributed among senior managers, board members, and business managers of dried fruits SMEs using the available sampling method. Structural equation modeling was employed for data analysis and test of research hypotheses. The statistical data and structural equation modeling revealed that the joint impact of marketing mix and specialized marketing knowledge has a positive and significant influence on export performance. In order to improve the company's profitability, it is essential for senior managers and sales managers to recognize the significance of these two factors and undergo relevant training to acquire the necessary skills. Moreover, managers should make effective use of appropriate distribution channels to expand their exports. Simultaneously, they should consider adapting product quality and packaging to align with the preferences of foreign buyers.

The prices accepted by consumers in the market are influenced by the characteristics of the goods, based on consumer behavior. Each of these features contributes to the price agreed upon by both consumers and suppliers. The packaging of a product plays a crucial role in attracting consumers and protecting the product from damage. High-quality and visually appealing packaging can create a positive perception among consumers, potentially resulting in a higher price point. Additionally, specialized packaging techniques designed to preserve freshness and extend the shelf life of oil can also impact the price. This study investigates the impact of quality and packaging on the price of sunflower oil in Iran. The primary objective was accomplished using the hedonic pricing method. Given the qualitative and ordinal nature of the dependent variable, the ordinal logit model was employed. The sample size was determined through a two-stage cluster sampling approach, which involved collecting 350 questionnaires from consumers in Tehran city. Statistical analysis was conducted using Shazam and Stata software. Numerous factors influence the consumption of sunflower oil at various levels. However, in general, factors such as increasing age, higher income levels, the presence of diseases, and dietary considerations contribute to a decrease in its consumption. On the other hand, factors like improving product quality, enhancing the quality of oil packaging, increasing consumer loyalty towards edible oil, and rising online sales of this product contribute to an increase in its demand.

In recent years, the fluctuation in agricultural commodity prices in Iran is increased and thus, accurate forecasting of price change is necessary. In this article, a flexible combined method in modeling monthly prices of beef, lamb and chicken from April 2001 to March 2021, was proposed. In this new method, three different approaches namely simple averaging, discounted and shrinkage methods were effectively used to combine the forecasting outputs of three hybrid methods (MLPANN-GA, MLPANN-PSO and MLPANN-ICA) together. In implementation stage of hybrid methods, based on test and error method, the optimal MLPANN structure was found with 3/2/4–6–1 architectures and the controlling parameters are carefully assigned. The results obtained from three hybrid methods indicate that, based on the RMSE statistical index, the MLPANN-ICA method performs the best when forecasting prices for beef, lamb, and chicken. The outputs of three combination approaches show that the shrinkage method, with a parameter value of K=0.25, achieves the highest prediction accuracy when forecasting prices for these three meats. In summary, the proposed method outperforms the other three hybrid methods overall.