جستجوی مقالات مرتبط با کلیدواژه « Tea » در نشریات گروه « علوم ترویج »

Consumer preferences regarding tea packaging are very important in the tea packaging industry and businesses. In this study, by combining symmetric analysis method with artificial neural network algorithm, buyerschr('39') preferences for tea packaging and factors affecting it have been used to identify. Tea packaging influences consumer preferences and marketing by conveying visual and textual information. The aim of this study was to investigate the effect of simultaneous tea packaging characteristics with price component on consumer preferences by symmetric analysis and artificial neural network based on symmetric analysis in Sari. The required data were collected in 1397 by completing 296 questionnaires. In this research, SPSS and Excel software have been used. Based on the results of the conjoint analysis of the four characteristics of the shape, Information, price and brand. the information on the package had the greatest impact on the consumer. Also, limited information is more preferable than complete information. Relatively newer brands are more preferable to long-term brands. Using the weight obtained from the results of conjoint analysis in the artificial neural network along with the entry of income, age and amount of tea consumption variables, the results showed that the effect of information on the total model of neural network is 25%, price is 50%, shape is 22% and brand is 19% in consumer selection. In the artificial neural network model, with the arrival of the variables income, age, and consumption of tea, choose according to the income and consumption of state of mind (desires) to the mode select consumer (close to the demand), the adjustment is that, in terms of properties of individual artificial neural network model leads to a realistic show the preferences of the  consumer in the model, artificial neural network has been؛ For example, the effect of tea price variable increased from 24% in conjoint analysis to 50% in synthetic neural network model based on conjoint analysis. According to the results of the research, entrepreneurs and business owners related to tea packaging should do the packaging in the form of a combination of minimal information (brand name, consumer price and production date and expiration) in the form of cylindrical cans and high price level.

Solving problems such as the system of small land ownership, land scatteredness, lack of optimal utilization of production resources and low yield is not feasible without reforming the system of operation and its institutionalization. Accordingly, in this research, operation systems in tea growing areas of Iran (peasant, common cooperative, and commercial) were investigated. The results of analyzing the data variance and comparing the averages and the Tukey tests of nine independent variables including age, education level, ownership, tea cultivated area, tea growing income, production cost, tea field topography, irrigation, and records of tea growing activity with tea production yields (as the dependent variable) in different operation systems as well as prioritization of these systems using five indexes including yield, employment generation, fertilizer consumption, machinery utilization, and satisfaction of tea growing activity based on screening approach showed that among the three systems identified in the tea growing areas, the common cooperative system had the highest yields and could be known as the most suitable operation system in tea growing areas of the country.