Roh Taeyeoun, Song Youngchul, Yoon Byungun
Department of Industrial & Systems Engineering, Dongguk University, Seoul 04620, Republic of Korea.
Foods. 2024 Dec 17;13(24):4065. doi: 10.3390/foods13244065.
Shared kitchens have a lower entry barrier than traditional kitchens, which generally require a significant initial investment, and have thus attracted attention as the most realistic new business model for restaurants in the sharing economy. The restaurant industry is founded on ensuring the safety of the food it serves in order to prevent the spread of foodborne diseases within the community, so strict quality control is essential. Existing food quality management typically employs continuous quality assistance, which is difficult to apply to the highly volatile shared kitchen environment and its various stakeholders. Therefore, in this study, a predictive model for managing food quality that can monitor volatility using quantitative indicators, especially microbial counts, is proposed. Stakeholder- and quality-related factors associated with shared kitchens are first defined, then a modified Gompertz growth curve and the transfer rate equation are used to quantify them. The proposed model, utilizing as a practical indicator for easily measuring changes in general environments, can be used to systematically manage food quality within the shared kitchen industry, thus supporting the establishment of this new business model.
共享厨房比传统厨房的进入门槛更低,传统厨房通常需要大量的初始投资,因此,作为共享经济中餐馆最现实的新商业模式,共享厨房已引起关注。餐饮行业的基础是确保所供应食品的安全,以防止食源性疾病在社区内传播,因此严格的质量控制至关重要。现有的食品质量管理通常采用持续质量协助,这很难应用于高度不稳定的共享厨房环境及其众多利益相关者。因此,在本研究中,提出了一种用于管理食品质量的预测模型,该模型可以使用定量指标(尤其是微生物数量)来监测波动性。首先定义与共享厨房相关的利益相关者和质量相关因素,然后使用修正的冈珀茨生长曲线和转移率方程对其进行量化。所提出的模型利用作为易于测量一般环境变化的实用指标,可用于系统地管理共享厨房行业内的食品质量,从而支持这种新商业模式的建立。