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This study investigates the motivation among customers to be more loyal to online food delivery applications (OFDA) services even after the COVID-19 epidemic by using perceived service quality aspects in Sri Lanka. The data were gathered by physically distributing a self-administrated questionnaire to clients in Sri Lanka who continue to use OFDA services on platform to customer (P2C) service delivery platforms to buy food despite the COVID-19 outbreak. Multiple regression is employed to analyse 287 effective observations, and the data revealed the significant positive effect of interaction, environment, outcome, and food qualities on customer loyalty to OFDA services. In fact, there is no impact from the delivery quality on customer loyalty to OFDA services due to outsourced food delivery. The findings suggest regular improvements in attributes such as interaction, environment, outcome, and food qualities in this hyper-competitive business environment. Further, this study sets substantial facts for the interested parties to establish an exemplary delivery system and other technological advancements to have a sustainable competitive advantage and solid customer base in the long run.

Purpose: The purpose of this chapter is to review and critically evaluate robots, artificial intelligence and service automation (RAISA) applications in the restaurant industry to educate professors, graduate students, and industry professionals.

Design/methodology/approach: This chapter is a survey of applications of RAISA in restaurants. The chapter is based on the review of professional and peer-reviewed academic literature, and the industry insight section was prepared based on a 50-minute interview with Mr. Juan Higueros, Chief Operations Officer of Bear Robotics.

Findings: Various case studies presented in this chapter illustrate numerous possibilities for automation: from automating a specific function to complete automation of the front of the house (e.g., Eatsa) or back of the house (e.g., Spyce robotic kitchen). The restaurant industry has already adopted chatbots; voice-activated and biometric technologies; robots as hosts, food runners, chefs, and bartenders; tableside ordering; conveyors; and robotic food delivery.

Practical implications: The chapter presents professors and students with a detailed overview of RAISA in the restaurant industry that will be useful for educational and research purposes. Restaurant owners and managers may also benefit from reading this chapter as they will learn about the current state of technology and opportunities for RAISA implementation.

Originality/value: To the best of the authors’ knowledge, this chapter presents the first systematic and in-depth review of RAISA technologies in the restaurant industry.

In the last few decades, the obesity rate has increased along with the increasing of away-from-home food consumption at restaurants (Wei & Miao, 2013), especially the food consumption at quick-service restaurants (QSRs). Previous research stated that the main factors that influence the customers’ food selection are found. Price and quality of food are the most significant things that mostly concerned customers when they are in decision-making process. There is a controversial argument between several studies that identified calorie labelling on menu influences consumers on food choice, while others said vice versa. However, several studies argued that calorie information does not have as much impact on customers’ food purchasing as other factors such as food’s quality, ranges of food, price of food, restaurant’s atmosphere, and speed of food service (Carey & Genevive, 1995). The aim of this chapter is to examine the importance of representing calorie information on menu and its effects on customer decision-making especially at QSRs. Therefore, the following questions have been addressed in this chapter:

What are the factors that influence consumer choice at QSRs?

Does calorie labelling on menus impact customer purchasing at QSRs?

This chapter starts with the introduction of the topic and reviewing previous research on menu labelling and calorie information at QSRs. This chapter aims to provide a better understanding of customer decision-making when ordering a food with regard to calorie information on the menu and the customer preference.

To analyze more deeply and in a systemic perspective food system outcomes, and the contribution that small farming can give to the achievement of those outcomes, a detailed analysis of food systems is required, which highlights its components, activities and dynamics. Thus, this chapter deepens the analysis of the food system. We first reflect on the complexity of the concept of food system, discussing the abundance of different conceptualizations proposed in the scientific and political debate on the base of different disciplines and perspectives. Then, a comprehensive representation is shown, which is then unpacked. The food system actors, assets and functions are explored, with an eye on power relations among actors and on the main drivers of change. Governance (that also includes actors external to the food systems) is called ‘reflexive’, as long as it characterizes a system that is able to reflect upon the conditions and the forms of its own functioning, to detect and analyze threats and to change accordingly, with the involvement of actors external to the food systems. This analysis, which represents the focus of this section, provides the base for the description of the food system vulnerability developed in Chapter 4. Drivers of change and governance emerge as key categories to consider.

This chapter describes public agriculture services’ business goals, purpose, and strategy. It reinforces agriculture organizations’ fundamental bureaucratic administrative culture (Tier 1). The authors describe the influence that political appointees as leaders may play in shaping public sector cultures. The bureaucratic culture of agriculture is deconstructed, and each of the five layers is described in detail. Additionally, the authors explain why behavior is the dominant layer and the most critical starting point for understanding agriculture cultures. The public service culture (Tier 2) brings an essential element of leveling, access, and equity to the larger context. It brings the focus back to service to the people and community rather than performance. It also gives greater emphasis to the role of safety and well-being. The chapter lays out the landscape of external influencing cultures (Tier 3) in agriculture. Finally, the potential value and challenges of developing internal knowledge, learning, and collaboration (KLC) cultures (Tier 4) are explored.

This chapter discusses the high adoption of plastic bags/packages by food providers in Malaysia during pandemic that resulted in a long-time lockdown. Under the federal government act of ‘Movement Order Control’ (MCO), people had no choice but to order food or purchase food ingredients via online food delivery services. Such situation made the food delivery business instantly one of the top and essential economic contributors. However, this also severely impacted our environment specifically the growing usage of plastic bag, plastic food container, and parcel packaging. While the food delivery company introduces a campaign to reduce and replace the plastic bag/packages, the awareness level is still very low. This chapter highlights the introduction of food delivery business striving in the COVID-19 pandemic, the severity of plastic usage and challenges of sustainability marketing campaign in Malaysia.

The purpose of this research is to evaluate the perceptions of local tourists concerning the importance and performance of their dining experience and restaurant selection factors at tourist destinations. Five hundred forty-one questionnaires collected from a series of on-site surveys at popular tourist destinations were analyzed. The results of importance–performance analysis (IPA) illustrate that no attribute fell in the Concentrate Here quadrant; staff service, service speed, food quality, interior design, comfort, cleanliness, restaurant scent, food scent attributes, and the “food service” factor fell under the Keep up the Good Work quadrants; noise, music, new experience, price attributes, and the “servicescape” factor fell in the Low Priority quadrant; servicescape lighting fell in the Possible Overkill quadrant. In conclusion, restaurants at popular tourist destinations have done very well in most service items and seem to have reached the professional standards expected by mass tourists.

Life is changing very fast, and its impact is observed in food pattern, consumer behavior and its ultimate market. In these broad outlines, 300 customers were studied in Anand districts of Gujarat. The restaurants and parlors that were studied were franchise models of Gujarat state only. Here in this study, six franchise food retailers were purposively selected. Data were analyzed through cluster analysis techniques. At the end, it was found high quality, better service, convenient location, presentation of food in parlor and restaurants, and zero time delivery are playing key roles for getting customers for the food.

We examine the extent to which food prices and restaurant outlet density are associated with adolescent fruit and vegetable consumption, body mass index (BMI), and the probability of overweight. We use repeated cross-sections of individual-level data on adolescents from the Monitoring the Future Surveys from 1997 to 2003 combined with fast food and fruit and vegetable prices obtained from the American Chamber of Commerce Researchers Association and fast food and full-service restaurant outlet density measures obtained from Dun & Bradstreet. The results suggest that the price of a fast food meal is an important determinant of adolescents’ body weight and eating habits: a 10% increase in the price of a fast food meal leads to a 3.0% increase in the probability of frequent fruit and vegetable consumption, a 0.4% decrease in BMI, and a 5.9% decrease in probability of overweight. The price of fruits and vegetables and restaurant outlet density are less important determinants, although these variables typically have the expected sign and are often statistically associated with our outcome measures. Despite these findings, changes in all observed economic and socio-demographic characteristics together only explain roughly one-quarter of the change in mean BMI and one-fifth of the change in overweight over the 1997–2003 sampling period.