Restaurant management

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Restaurant management is the profession of managing a restaurant. Associate, bachelor, and graduate degree programs are offered in restaurant management by community colleges, junior colleges, and some universities in the United States [1] and elsewhere. [2]

One hierarchical system for organizing a restaurant's kitchen staff is the brigade de cuisine system developed by Auguste Escoffier (1846–1935).

The management system of restaurants over the last years was more willing to implement data-based methods to become more efficient and make decisions [3] . Through the use of analytics, demand forecasting, staffing, and inventory control will lead to reduced wastage and maximized profitability [4] . The machine-learning systems and artificial intelligence are utilized in order to perform real-time assessment of service quality and customer experience [5] . The trend to sustainability and ethical sourcing becomes a part of the operational strategy nowadays and suits restaurants with the greater environmental goals [6] . Among the most significant ones is workforce development where both training and flexible-related scheduling have been effective in retention [7] . Comparative research indicates that restaurant and hotel management uses increasingly similar performance evaluation analytical models to achieve the greatest satisfaction of customers [8]

References

  1. United States Department of Labor (2004). Occupational Outlook Handbook, 2004-2005: Bulletin 2570. Claitor's Law Books and Publishing. p.  54. ISBN   1-57980-925-1.
  2. "Courses: Restaurant and Catering Establishment Managers and Proprietors". UCAS . Retrieved 3 March 2025.
  3. Roy, Debjit; Spiliotopoulou, Eirini; de Vries, Jelle (2022-10-01). "Restaurant analytics: Emerging practice and research opportunities". Production and Operations Management. 31 (10): 3687–3709. doi:10.1111/poms.13809. ISSN   1059-1478.
  4. Rejeb, Abderahman; Abdollahi, Alireza; Rejeb, Karim; Mostafa, Mohamed M. (2023). "Tracing knowledge evolution flows in scholarly restaurant research: a main path analysis". Quality & Quantity. 57 (3): 2183–2209. doi:10.1007/s11135-022-01440-7. ISSN   0033-5177. PMC   9214194 . PMID   35756090.
  5. Vargas-Calderón, Vladimir; Ochoa, Andreina Moros; Nieto, Gilmer Yovani Castro; Camargo, Jorge E. (2021-07-23), Machine learning for assessing quality of service in the hospitality sector based on customer reviews, arXiv, doi:10.48550/arXiv.2107.10328, arXiv:2107.10328, retrieved 2025-11-12
  6. Rejeb, Abderahman; Abdollahi, Alireza; Rejeb, Karim; Mostafa, Mohamed M. (2023). "Tracing knowledge evolution flows in scholarly restaurant research: a main path analysis". Quality & Quantity. 57 (3): 2183–2209. doi:10.1007/s11135-022-01440-7. ISSN   0033-5177. PMC   9214194 . PMID   35756090.
  7. Vargas-Calderón, Vladimir; Ochoa, Andreina Moros; Nieto, Gilmer Yovani Castro; Camargo, Jorge E. (2021-07-23), Machine learning for assessing quality of service in the hospitality sector based on customer reviews, arXiv, doi:10.48550/arXiv.2107.10328, arXiv:2107.10328, retrieved 2025-11-12
  8. Vargas-Calderón, Vladimir; Ochoa, Andreina Moros; Nieto, Gilmer Yovani Castro; Camargo, Jorge E. (2021-07-23), Machine learning for assessing quality of service in the hospitality sector based on customer reviews, arXiv, doi:10.48550/arXiv.2107.10328, arXiv:2107.10328, retrieved 2025-11-12

Further reading