Food & Beverage Revenue Management – Menu Design

1.0 Background:

1.1 F&B RM & Components

The origin of an airline’s yield management has proven its success and over time, it evolved as revenue management (RM). RM principle (Kimes et al., 1998) can extend to the F&B sector as the capacity (i.e., seat) is perishable. There is a demand (based on time), and the demand can be separated into distinct segments. In terms of the costing structure, the fixed cost is relatively high, and the variable cost tends to be low. The strategic levers can be conducted through duration management, capacity management (table mix/setup), and price management (demand-based pricing and price fences) (Tyagi & Bolia, 2022). The measurement focuses on two strategic dimensions: time and inventory, known as RevPASH (or revenue per available seat hour).

RM is composed of five “rights”, which is selling the “right product” to the “right customer” at the “right time” for the “right price” and on the “right channel”. One way to tackle these 5 rights is through menu design. The menu can be used to influence how the consumer’s decision, including expectations, spending, and attitudes which leads to the restaurant’s success (IP & Chark, 2023; Lee et al., 2017). 

1.2 Menu design, analysis, and engineering

The presentation of dishes involves dish names, descriptions, positioning, pricing, graphic design and visualization (Fedosova, 2022). In the RM perspective, it refers to menu design, menu analysis, or menu engineering. These terms are often interchangeable. Jones and Mifll (2001) differentiate its definition. Menu analysis and menu engineering are the analytical tools to measure the menu and dish performance. Menu analysis refers to the techniques that enable to influence consumer decision-making. Menu engineering refers to the portfolio analysis for comparing the dish/product performance.

The most popular menu engineering method was developed by Michael Kasavana and Donald Smith in the 1980s, based on the Boston Consulting Group analysis model (Fedosova, 2022). This menu engineering model analyses each dish into 4 categories based on popularity and profit, namely Stars, Workhorses, Puzzles and Dogs. This could be outdated given most menu is now paperless.

1.3 Psychological Framework

Lee et al., (2017) revealed menu design has a stimulus effect on the consumer’s decision to order dishes through visual responses (Milosavljevic et al., 2012) this can be known as ‘impulse buying action (Stern, 1962). This impulse buying behaviour is associated with the psychological aspect of decision-making. Fedosova (2022) called it “brain science”. He revealed several effective psychological tricks that influence the choice of dishes on the menu. They are the order of the dish; menu structure; assortment and number of items in the menu; currency signs; price location; creative descriptions; colour; and photos.

1.4 The rise of electronic menu

Many studies are focusing on paper menu design (Kadek et al., 2020; Lee et al., 2017; Morrison, 1996; Yang, 2012). One of the interesting papers conducted by Yang (2012) studied the eye movements of restaurant menus on gaze motion and consumer scan paths. However, the COVID-19 pandemic made restaurants transition to paperless menus or electronic menus (through QR codes or display on tablets or other advanced technologies such as AR).

2.0 Research Aim/Objectives:

As stated above, this research project aims to investigate how electronic menu designs can have an impact on a restaurant’s revenue. It attempts to answer not limited to the following research questions:

1.           What are the key components/ factors when designing an electronic menu? How is it compared to paper-menu?

2.           How can digitalization better track consumer decisions (other than eye movement)?

3.           Other electronic or innovative technological tools can help boost revenue such as AR?

3.0 Proposed method:

The plan for this project involves using a (quasi) experimental design to study how electronic menu designs affect restaurant revenue. By changing design features and comparing revenue in different situations, the project hopes to learn how electronic menus influence customer behavior and boost restaurant income. Through careful testing and analysis, the research aims to shed light on how technology can improve dining experiences and economic success in the hospitality industry.

Academic Qualifications:

A first degree (at least a 2.1) ideally in Statistics with a good fundamental knowledge of F&B and/or revenue management.

 

English Language Requirement:

IELTS score must be at least 6.5 (with no less than 6.0 in each of the four components), Other equivalent qualifications will be accepted. Full details of the University’s policy are available online.

Essential Attributes:

·        Experience of fundamental independent academic research projects at the MSc or MPhil

·        Competent in statistics and/or psychological theories

·        Knowledge of technology such as computer design which helps to understand the concept of menu design.

·        Good written and oral communication skills

·        Strong motivation, with evidence of independent research skills relevant to the project

·        Good time management

Desirable Attributes:

A Mphil or MSc-level qualification in technology and evidence of strong analytical skills.