Application of Multi-Criteria Decision Making Methods for Menu Selection

Year 2024, Volume: 7 Issue: 1, 21 - 30, 15.01.2024

Semih Latif İpek , Dilek Göktürk

https://doi.org/10.34248/bsengineering.1358895

Abstract

Nutritional information on menus can assist customers in making healthier eating choices. One technique being utilized to tackle the rise of overweight and obesity is the use of nutritional information on menus. Menu engineering strategies can be used to improve sales of generally healthier and higher margin items. For today's food and beverage companies, menu engineering has become essential. Companies must continually evaluate their menus in order to keep up with changing customer demands and the conditions of the competitive market. Menu engineering's core involves comparing the effectiveness of each menu. At this point, correct decision-making under numerous factors is thought to be a very challenging procedure. To evaluate alternatives according to many features, several Multi-Criteria Decision-Making (MCDM) approaches have been created. The main novelty of this paper is that four MCDM methods, including Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), Fuzzy TOPSIS, VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), and Fuzzy VIKOR, are employed to evaluate menu options. Comparative analysis of MCDM methods is another contribution of this study. The process of evaluating and selecting healthier menu alternatives can become challenging and time-consuming. This study pointed out how crucial it is to conduct comparative analysis using various MCDA methods and to carefully determine the right ones when addressing the issue of selecting the best menu, taking into account the values of the criterion in fuzzy numbers.

Keywords

Menu engineering, Menu selection, Multi-criteria, Decision-making approaches

References

• Alexander E, Rutkow L, Gudzune KA, Cohen JE, McGinty EE. 2021. Sodium menu labelling: priorities for research and policy. Public Health Nutr, 24(6): 1542-1551.
• Alonso S, Tan M, Wang C, Kent S, Cobiac L, MacGregor GA, He FJ, Mihaylova B. 2021. Impact of the 2003 to 2018 population salt intake reduction program in England: a modeling study. Hypertension, 77(4): 1086-1094.
• Alpay S, Iphar M. 2018. Equipment selection based on two different fuzzy multi criteria decision making methods: Fuzzy TOPSIS and fuzzy VIKOR. Open Geosci, 10(1): 661-677.
• Alsalem MA, Zaidan AA, Zaidan BB, Hashim M, Albahri OS, Albahri AS, Hadi A, Mohammed KI. 2018. Systematic review of an automated multiclass detection and classification system for acute Leukaemia in terms of evaluation and benchmarking, open challenges, issues and methodological aspects. J Med Syst, 42, 204.
• Ardiansyah I. 2020. The application of menu engineering technique in determining marketing strategy at the den of kalaha restaurant jakarta. J Bus Entrep, 8(1): 18-39.
• Arora HD, Naithani A, Gupta S. 2022. Distance measures of Pythagorean fuzzy TOPSIS approach for online food delivery apps. Int J Eng, 35(10): 1877-1886.
• Arsić SN, Pamučar D, Suknovic M, Janošević M. 2019. Menu evaluation based on rough MAIRCA and BW methods. Serb J Manag, 14(1): 27-48.
• Bowers KM, Suzuki S. 2014. Menu-labeling usage and its association with diet and exercise: 2011 BRFSS sugar sweetened beverage and menu labeling module. Prev Chronic Dis, 11: E02. doi: 10.5888/pcd11.130231.
• Bruemmer B, Krieger J, Saelens BE. Chan N. 2012. Energy, saturated fat, and sodium were lower in entrées at chain restaurants at 18 months compared with 6 months following the implementation of mandatory menu labeling regulation in King County, Washington. J Acad Nutr Diet, 112(8): 1169-1176.
• Byrd K, Almanza B, Ghiselli RF, Behnke C, Eicher-Miller HA. 2018. Adding sodium information to casual dining restaurant menus: beneficial or detrimental for consumers? Appetite, 125: 474-485.
• Byrd K, Almanza B. 2021. Restaurant menu labeling for calories and sodium: Effect of consumer mindset of immediate versus future consequences. J Foodserv Bus Res, 24(3): 310-347.
• Cantu-Jungles TM, McCormack LA, Slaven JE, Slebodnik M, Eicher-Miller HA. 2017. A meta-analysis to determine the impact of restaurant menu labeling on calories and nutrients (ordered or consumed) in US adults. Nutrients, 9(10): 1088.
• Cevikcan E, Cebi S, Kaya I. 2009. Fuzzy VIKOR and fuzzy axiomatic design versus to fuzzy TOPSIS: an application of candidate assessment. J Mult-Valued Log Soft Comput, 15(2-3): 181-208.
• Coskun A, Genç HU, Coskun A. 2023. How sustainable is your menu? Designing and assessing an interactive artefact to support chefs’ sustainable recipe-planning practices. In Proceedings of the 6th ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societie, August 16-19, Cape Town, South Africa, pp: 90-98.
• Detopoulou P, Al-Khelefawi ZH, Kalonarchi G, Papamikos V. 2022. Formulation of the menu of a general hospital after its conversion to a “COVID Hospital”: a nutrient analysis of 28-day menus. Front. Nutr, 9: 833628.
• DiPietro R. 2017. Restaurant and foodservice research: A critical reflection behind and an optimistic look ahead. Int J Contemp Hosp Manag, 29(4): 1203-1234.
• Dowray S, Swartz JJ, Braxton D, Viera AJ. 2013. Potential effect of physical activity based menu labels on the calorie content of selected fast food meals. Appetite, 62: 173-181.
• Dumanovsky T, Huang CY, Bassett MT, Silver LD. 2010. Consumer awareness of fast-food calorie information in New York City after implementation of a menu labeling regulation. Am J Public Health, 100(12): 2520-2525.
• Elbel B, Kersh R, Brescoll VL, Dixon LB. 2009. Calorie labeling and food choices: a first look at the effects on low-income people In New York City: Calorie information on menus appears to increase awareness of calorie content, but not necessarily the number of calories people purchase. Health Aff, 28(Suppl1): w1110-w1121.
• Falbe J, Musicus AA, Sigala DM, Roberto CA, Solar SE, Lemmon B, Sorscher S, Nara D, Hall, MG. 2023. Online RCT of icon added-sugar warning labels for restaurant menus. Am J Prev Med, 65(1): 101-111.
• Fang CY. 2020. From the total-factor framework to food cost performance disaggregation—developing an innovative model to enhance menu performance. Sustainability, 12(22): 9552.
• Gerend MA. 2009. Does calorie information promote lower calorie fast food choices among college students? J Adolesc Health, 44(1): 84-86.
• Hamdallah ME, Srouji AF. 2018. Menu engineering in Jordanian health-care centers: a modified balanced scorecard approach. In 8th International Conference on Engineering, Project, and Product Management (EPPM 2017) Proceedings, pp: 109-118. URL: https://link.springer.com/book/10.1007/978-3-319-74123-9#about-this-book (accessed date, March 15, 2022).
• Hermida CEC, Aráuz MBB. 2023. Menu engineering: A benchmark methodology for improving the profitability of a restaurant company. J Surv Fish Sci, 10(3S): 3067-3079.
• Ho HP, Lin YC, Fu CJ, Chang CT. 2022. On the personal diet considering qualitative and quantitative issues. Comput Ind Eng 164: 107857.
• Hobin E, Lillico H, Zuo F, Sacco J, Rosella L, Hammond, D. 2016. Estimating the impact of various menu labeling formats on parents’ demand for fast-food kids’ meals for their children: An experimental auction. Appetite, 105: 582-590.
• Hobin E, Weerasinghe A, Schoer N, Vanderlee L, Shokar S, Orr S, Poon T, Hammond D. 2022. Efficacy of calorie labelling for alcoholic and non-alcoholic beverages on restaurant menus on noticing information, calorie knowledge, and perceived and actual influence on hypothetical beverage orders: a randomized trial. Can J Public Health, 113(3): 363-373.
• Huang Y, Burgoine T, Theis DR, Adams J. 2022. Differences in energy and nutrient content of menu items served by large chain restaurants in the USA and the UK in 2018. Public Health Nutr, 25(10): 2671-2679.
• Hur J, Jang SS. 2015. Consumers’ inference-dynamics about healthy menu promotions in a bundle context. Int J Hosp Manag, 44: 12-22.
• Hwang J, Lorenzen CL. 2008. Effective nutrition labeling of restaurant menu and pricing of healthy menu. J Foodserv, 19(5): 270-276.
• Hwang CL, Yoon K. 1981. Multiple attribute decision making methods and applications, a state-of-the-art survey. Springer, London, UK, pp: 269.
• İpek SL, Göktürk D. 2021. Industry 4.0 approaches in food and bio industry: recent developments and future trends. Adv Artif Intell Res, 1(1): 29-42.
• Jeong E, Jang SS. 2016. Imagine yourself being healthy: The mental simulation effect of advertisements on healthy menu promotion. Int J Hosp Manag, 53: 81-93.
• Jia J, Van Horn L, Linder JA, Ackermann RT, Kandula NR, O'Brien MJ. 2023. Menu calorie label use and diet quality: a cross-sectional study. Am J Prev Med, 65(6): 1069-1077.
• Juliana J, Pramezwary A, Nukak NA, Situmorang JMH. 2021. Using contribution of menu engineering in upscale restaurants to enhance sales volume. Int J Soc Sci Manag Stud, 2(4): 1-12.
• Kwong LYL. 2005. The application of menu engineering and design in Asian restaurants. Int J Hosp Manag, 24(1): 91-106.
• Lai HBJ, Karim S, Krauss SE, Ishak FAC. 2020. A review of approaches to manage menu profitability. Int J Revenue Manag, 11(3): 151-171.
• Linassi R, Alberton A, Marinho SV. 2016. Menu engineering and activity-based costing: an improved method of menu planning. Int J Contemp Hosp Manag, 28(7): 1417-1440.
• Morrison P. 1996. Menu engineering in upscale restaurants. Int J Contemp Hosp Manag, 8(4): 17-24.
• Mutlu H, Demirçakmak İL, Doğan M. 2022. Menu engineering in the restaurant business: A study on kitchen chefs. J Tour Gastron Stud, 10 (4): 3537-3553.
• Nerisafitra P, Putri PH. 2017. Establishing decision support system for determination healthy menu based in multi criteria and interatice approach. In Proceeding of 4th International Conference on Computer Applications and Information Processing Technology (CAIPT), August 8-1, Kuta, Bali, pp: 1-5.
• Nicolosi RJ, Wilson TA, Lawton C, Handelman GJ. 2001. Dietary effects on cardiovascular disease risk factors: beyond saturated fatty acids and cholesterol. J Am Coll Nutr, 20(sup5): 421S-427S.
• Obbagy JE, Condrasky MD, Roe LS, Sharp JL, Rolls BJ. 2011. Chefs' opinions about reducing the calorie content of menu items in restaurants. Obesity, 19(2): 332-337.
• Papathanasiou J, Ploskas N. 2018. Multiple criteria decision aid. Methods, examples and python implementations. Springer, London, UK, pp: 173.
• Patel A, Lopez NV, Lawless HT, Njike V, Beleche M, Katz DL. 2016. Reducing calories, fat, saturated fat, and sodium in restaurant menu items: Effects on consumer acceptance. Obesity, 24(12): 2497-2508.
• Rudelt A, French S, Harnack L. 2014. Fourteen-year trends in sodium content of menu offerings at eight leading fast-food restaurants in the USA. Public Health Nutr, 17(8): 1682-1688.
• Sampaio RM, Coutinho MBC, Mendonça D, da Silva Bastos D, Henriques P, Camacho P, Anastácio A, Pereira S. 2017. School nutrition program: Assessment of planning and nutritional recommendations of menus. Rev Chil Nutr, 44(2): 170-176.
• Sanayei A, Mousavi SF, Yazdankhah A. 2010. Group decision making process for supplier selection with VIKOR under fuzzy environment. Expert Syst Appl, 37(1): 24-30.
• Sarı F. 2018. Comparison of TOPSIS and VIKOR multi criteria decision analysis techniques. Selcuk Univ J Eng Sci Tech, 6, 825-831.
• Scourboutakos MJ, Corey PN, Mendoza J, Henson SJ, L’Abbé MR. 2014. Restaurant menu labelling: Is it worth adding sodium to the label? Can J Public Health, 105(5): e354-e361.
• Sigala DM, Hall MG, Musicus AA, Roberto CA, Solar SE, Fan S, Sorscher S, Nara D, Falbe J. 2022. Perceived effectiveness of added-sugar warning label designs for US restaurant menus: An online randomized controlled trial. Prev Med, 160, 107090.
• Sisti JS, Prasad D, Niederman S, Mezzacca TA, Anekwe AV, Clapp J, Farley SM. 2023. Sodium content of menu items in New York City chain restaurants following enforcement of the sodium warning icon rule, 2015–2017. PLoS One, 18(5): e0274648.
• Tan TH, Chang CS, Chen YF. 2012. Developing an intelligent e-restaurant with a menu recommender for customer-centric service. IEEE Trans Syst Man Cybern Part C (Applications and Reviews), 42(5): 775-787.
• Tom M, Wibowo S, Grandhi S. 2015. A fuzzy multicriteria decision making model for restaurant menu ranking. In Proceeding of IEEE 7th International Conference on Cybernetics and Intelligent Systems (CIS) and IEEE Conference on Robotics, Automation and Mechatronics (RAM), 15-17 July, Angkor Wat, Cambodia, pp: 104-108.
• Tom M, Annaraud K. 2017. A fuzzy multi-criteria decision making model for menu engineering. In Proceeding of IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 9-12 July, Roma, Italy, pp: 1-6.
• Turnwald BP, Jurafsky D, Conner A, Crum AJ. 2017. Reading between the menu lines: Are restaurants’ descriptions of “healthy” foods unappealing? Health Psychol, 36(11): 1034.
• Umamaheswari A, Kumari P. 2014. Fuzzy TOPSIS and fuzzy VIKOR methods using the triangular fuzzy hesitant sets. Int J Comput Sci Inf Technol Res, 4(3): 15-24.
• Wolfson JA, Moran AJ, Jarlenski MP, Bleich SN. 2018. Trends in sodium content of menu items in large chain restaurants in the US. Am J Prev Med, 54(1): 28-36.
• World awareness weeks. World Action on Salt, Sugar and Health (WASSH), https://www.worldactiononsalt.com/awarenessweek/ (accessed date, March 15, 2022).
• Yamamoto JA, Yamamoto JB, Yamamoto BE, Yamamoto LG. 2005. Adolescent fast food and restaurant ordering behavior with and without calorie and fat content menu information. J Adolesc Health, 37(5): 397-402.