How Do Fluctuations in Raw Material Prices Affect the Restaurant Industry? Can This Be Predicted Using AI Models?: Focusing on the Dining-out Price of Samgyeopsal

서지정보

· 발행기관 : 한국산업경영학회
· 수록지 정보 : 경영연구 / 39권 / 3호 / 109 ~ 124페이지
· 저자명 : 박종필, 정민수

초록

Despite the stabilization of the price index following the resolution of supply chain issues caused by Covid-19, consumers still perceive prices to be very high. The rise in dining-out prices, in particular, imposes a significant burden on the national economy. So, how much is the actual rise in food ingredient prices affecting the restaurant industry? And is the current price increase really reasonable? Additionally, if we can predict changes in dining prices through raw material costs, wouldn't consumers be able to make more informed decisions, and could this serve as a pricing indicator in the domestic restaurant industry? In this study, we adopt the aforementioned questions as our main research questions (RQs) and analyze how fluctuations in livestock prices impact the restaurant industry, focusing on dining prices. Additionally, we will develop an artificial intelligence (AI) model to predict these changes. Specifically, the study will identify and analyze factors in the distribution process that are expected to affect dining-out prices. Based on these results, it will ultimately analyze and predict dining-out prices. At this stage, fluctuations in livestock and dining-out prices will be analyzed separately for the Covid-19 period and the post-Covid-19 period. For this study, we have selected han-don (Korean pork), which is the most familiar food to our citizens, and specifically, we will use the dining-out price of the representative cut, samgyeopsal (pork belly). Specifically, the study will analyze the relationships between these variables and implement prediction models using techniques such as correlation analysis, OLS linear regression, ARIMA, and VAR, which are commonly used in time series data analysis. Additionally, deep learning prediction models will be developed using LSTM and GRU models. The study clarifies the relationship between the farm gate price of han-don (Korean pork) and the dining-out price of samgyeopsal (pork belly), and provides a clear analysis of the impact of Covid-19 on dining-out prices. Additionally, it implements significant prediction models. In conclusion, the models proposed in this study will enable small business owners to determine reasonable pricing points when making pricing decisions, and consumers can make informed purchases based on these decisions. Additionally, the government and public institutions can respond at a national level to price changes caused by trends and volatility in the prices of livestock raw materials. Ultimately, it is expected that utilizing this model can contribute to stabilizing the domestic restaurant industry and the national economy.

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