—Forecasting sales quantity and sales revenue is
very vital for a company to take action for the next period for
sustainable competition. It is especially important for growing
industries like grocery retailing industry. Turkey’s grocery
retailing industry is evolving rapidly. Due to increasing
importance; the aim of this study is to forecast the sales revenue
of grocery retailing industry in Turkey with the help of grocery
retailers marketing costs, gross profit, and its competitors’
gross profit by using artificial neural network. Artificial neural
networks are models which are used for forecasting because of
their capabilities of pattern recognition and machine learning.
ANN method is used to forecast the sales revenue of upcoming
period. According to results there are high similarities between
forecasted and actual data. Forecasted results of this study are
bigger or smaller than the actual data for only 10%. Because of
this high accuracy, companies at grocery retailing industry in
Turkey can use ANN as a forecasting tool.
—Sales revenue, forecasting sales revenue,
grocery retailing industry, artificial neural network.
The authors are with Adana Science and Technology University, Adana,
Turkey (e-mail: firstname.lastname@example.org, email@example.com).
Cite: Dilek Penpece and Orhan Emre Elma, "Predicting Sales Revenue by Using Artificial Neural Network in Grocery Retailing Industry: A Case Study in Turkey," International Journal of Trade, Economics and Finance vol.5, no.5, pp. 435-440, 2014.