Use of Artificial Intelligence For Service Personalisation and Operational Process Optimisation in the Restaurant Industry

My dissertation work focuses on service operations management problems, with the presence of information technologies and strategic customers. Information technology is a game-changer, both as an enabler and a disruptor. It creates new business opportunities, reshapes the interactions of the stakeholders, and provides additional information. However, the benefit conferred by these new business models and additional information is unclear. For example, the explosion of information technology has enabled the food delivery business to expand so that more customers have access to it. Delivery platforms claim that they generate demand, but some restaurants feel differently. Chapter 1 investigates the long-term impact of food delivery services on the restaurant industry. We model a restaurant serving food to customers as a stylized single-server queue with two streams of customers: tech-savvy customers who have access to a delivery platform, and traditional customers who only have the walk-in option. We show that the platform does not necessarily increase demand for the restaurant. Furthermore, when the delivery service is sufficiently convenient, more customers having access to the platform may hurt the platform itself and the society. This is because the restaurant can become a delivery-only kitchen and raise its food price, leaving little surplus for the platform and consumers. But this would not happen when the pool of delivery workers could be capped. It is implied that limiting the labor pool size provides a simple yet effective means for the platform to improve its profit and meanwhile the social welfare. Besides the restaurant and food delivery industry, information technologies have been broadly applied in healthcare systems. In Chapter 2, we study how to improve the waits in an open-shop service system using information technology and analytics. Our work is motivated by a large healthcare clinic that implemented two information technology systems (auto-routing and SMS systems) to improve waits. We empirically evaluate the clinic's automation efforts and find that its IT implementations have negligible impacts on wait times. We identify two reasons: neither the project fundamentally changed the clinic's operation while the new IT allows immediate customer routing. Such immediate decisions reduce the system's flexibility and cause unproductive idleness. The clinic continued to use a station-level first-come-first-served (FCFS) priority policy. Then, customers tend to experience long delays at their last few stations. We use a stylized queueing model and simulations to demonstrate that priority policies considering customers' system-level characteristics outperform the FCFS discipline. Furthermore, to overcome the tension between pooling, which allows postponement of decisions, and behavioral considerations, which prefer early decisions that smooth transfer between stations, we propose a buffer strategy that enables the system to gather and effectively use more information for decision making. Chapters 1 and 2 show that with the increasing use of IT in service operations, service providers and social planners need to understand how IT reshapes and influences the service system so that they can derive maximum benefits from the emerging IT. In addition to the system efficiency, another important factor in service operations that service providers must pay attention to is customers' waiting experience. Customers' waiting experience depends on the total wait and how it is distributed over the entire service process. Therefore, in Chapter 2, we consider the wait time from both macro system-level perspective, such as total wait, and micro station-level perspective, such as excessive waits at stations. We demonstrate the efficacy of our proposed policies in shortening macro- and micro-level delays. Moreover, service providers can manage the waiting experience by creating a pleasant waiting area, providing distractions, and other strategies. Chapter 3 studies how can a service provider use entertaining activities with discounts to distract and delight waiting customers. We model this phenomenon by considering an M/M/1 queue operated by a profit-maximizing service provider that offers discounts through entertaining activities to strategic customers. We identify the profit-maximizing discount follows a threshold strategy and show that the service provider benefits from this strategy only if price-sensitive customers' demand is sufficiently large. Moreover, such a discount strategy should be implemented with probability 1 to the entire market.

<span style="font-family: Times New Roman; font-size: small;"> </span><p style="margin: 0in 0.5in 0pt; text-align: justify; mso-pagination: none; mso-layout-grid-align: none;" class="MsoNormal"><span style="font-size: 10pt;"><span style="font-family: Times New Roman;">This paper empirically examines the impact of environment friendly practices on restaurants in attracting customers.<span style="mso-spacerun: yes;"> </span>The restaurant industry is witnessing the green movement. Restaurant owners adopt green practices to their properties with the purpose of creating a distinctive image that can differentiate them from their competitors. Therefore, restaurateurs strive to get this competitive advantage by introducing green practices into their restaurants. However, little research has been done in the service sector to prove whether or not organic and sustainable service businesses such as restaurants can have a competitive advantage based on the organic and sustainability factors alone.<span style="mso-spacerun: yes;"> </span>The purpose of this research is to unfold these relationships through empirical analysis.<span style="mso-spacerun: yes;"> </span>The results of this research show that the dimension Sustainability is easily identified by the customers and does bring customers back to the restaurants.<span style="mso-spacerun: yes;"> </span>The results also indicate that restaurant industry need to do better job in creating awareness among their customers about the environment friendly practices used in their businesses.</span></span></p><span style="font-family: Times New Roman; font-size: small;"> </span>

The purpose of this article is to conduct a comprehensive analysis and improvement of business process management in the hotel and restaurant industry, considering current challenges, particularly global and national economic, social, and technological changes. The article examines the impact of war on the hotel and restaurant industry, specifically determining that military actions have led to significant losses in the hotel and restaurant business in both quantitative and financial terms. Key external factors affecting the competitiveness of the industry and its ability to withstand the consequences of the war are highlighted. It is established that business process management in the hotel and restaurant industry is a complex activity aimed at effective planning, organization, implementation, and control of all operational processes in hotels and restaurants. The goal of business process management in the hotel and restaurant industry is to achieve effective coordination of all operational and managerial actions within the organization. A classification of business processes in the hotel and restaurant industry has been developed, dividing them into primary, auxiliary, development, and management processes. Based on the proposed classification of business processes, authorial management models have been suggested to ensure business adaptation to unstable conditions, improve competitiveness and sustainability of enterprises in the industry, and optimize their operations to achieve long-term success. The integration of modern technologies, innovation implementation, and strategic management are crucial for achieving long-term success. Key principles of business process management in the hotel and restaurant industry have been formulated and substantiated, particularly customer orientation, quality control, and marketing strategy. Therefore, it is proven that for achieving sustainable development in the hotel and restaurant business, it is necessary to focus on integrating innovations into all business processes, especially in managing customer interaction and quality control.

The purpose of the article is to study the world experience of applying digital technologies in the activities of hotel and restaurant facilities in the context of digitalization of society and the prospects for their transition to digital management. The article explores the process of introducing digital technologies into the service sector, in particular the HoReCa sphere. It is proved that the implementation of the paradigm of the digital economy involves a deep restructuring of business models and business processes of hotel and restaurant enterprises. The analysis of the essence of the concept of «digitalization» is carried out. It is proved that the modern hotel and restaurant business largely depends on Internet technologies as the main instrument for increasing competitiveness. One of the most effective instruments for promoting the services of the hospitality industry is social networks. An aggregate of conditions indicating the need to use digital technology for the successful promotion of services of hotel and restaurant business enterprises in the market is described. The article carries out an analysis of the most advanced digital technologies that are being introduced into the field of hospitality: agency interfaces, blockchain technologies, robotics, augmented reality technologies, artificial intelligence, the Internet of Things (IoT), 5G, smart cities, and other platforms. The use of digital technologies allows the consumer to achieve the formation of a unique experience along with unforgettable impressions, and the hotel and restaurant industry – to get regular consumers, profits and ensure competitiveness in the service market. It is proved that an increase in the level of digitalization leads to an increase in the country’s economic indicators. The use of digital technologies in the hotel and restaurant business is characterized as a transformation from the digitalization of individual business tasks and processes to the digital transformation of the entire business. Prospects for further research in this direction is to determine the economic effect of the use of digital technologies, study the problems of their implementation in the hotel and restaurant industry, the further development of the hospitality industry.

Among several industry characteristics, capital intensity plays an important explanatory role for the restaurant industry. A restaurant needs physical buildings, equipment, fixtures, and furniture all ready at the launch of a business; these require considerable capital expenditures. Considering capital intensity as a significant restaurant industry characteristic, educators and practitioners who focus on this industry are strongly encouraged to investigate the implications and effects of capital intensity in food service operations. The purpose of this study is to examine the effect of capital intensity on a firm's value performance in the U.S. restaurant industry. The investigation period spans from 2000 to 2008. Findings suggest that capital intensity has a negative effect on U.S. restaurant firms' value performance.

Objective: This study analyzes unstructured data extracted from social media and online reviews to explore perceptions of serving robots and identify strategies for advancing food technology. Methods: This study used online reviews, social media posts, and survey data to examine emotional responses and perception changes related to serving robots. This study also conducted a semantic network analysis to identify relationships among key concepts. Then, implications were drawn regarding the role of serving robots and customer acceptance in the food tech industry. Results: This study identified keywords related to serving robots through text mining and centrality analysis to analyze their frequency and importance. Additionally, CONCOR analysis revealed five clusters: ‘service operations,’ ‘serving robot,’ ‘technology and industry,’ ‘food and menu,’ ‘smart technology,’ and ‘customer experience.’ Implications: The analysis results showed that serving robots are not merely automated devices but play a crucial role in enhancing operational efficiency and customer service in the restaurant industry. These findings highlight the need for food tech research that goes beyond a technology-centric approach to incorporate a human-centered perspective, improving service experiences and customer satisfaction.

This study investigates the impact of self-service kiosk adoption on key performance outcomes (sales, operating costs, and profitability) in the restaurant industry with a particular focus on how these effects vary depending on customer demand levels. Using data from the 2020 Restaurant Management Survey conducted in South Korea, we perform regression analyses to examine the effects of kiosk adoption and average daily visitor count on business performance. The analysis reveals a dual pattern: although restaurants with kiosks tend to have higher average sales than those without, increasing customer demand diminishes the positive effects of kiosk adoption on reducing operating costs and enhancing profitability. These findings indicate that the effectiveness of kiosk adoption is highly contingent on operational contexts such as demand intensity. This study highlights the limitations of viewing technology adoption as universally beneficial and emphasizes the need for context-sensitive operational strategies. By analyzing the interaction between technology, demand conditions, and performance, this research contributes to a deeper understanding of digital transformation in service operations and provides empirical evidence to guide more strategic implementation of self-service technologies.

The assimilation of Artificial Intelligence (AI) in restaurant industry represents a revolutionary shift. AI has enabled this industry by optimizing the food deliveries to the customers in no time, route optimization by determining the most effective route for each delivery person and for every order as well. AI interacts with the road infrastructure, weather conditions, traffic status and enable the driver to reach his destination in the stipulated time for every order. AI analyses historical data and make predictions for the future by conducting various algorithm based analysis. Artificial Intelligence has also helped the marketers to decide on dynamic pricing structure and keeping their customer alive with them. One of the major task accomplished by AI is usage of Chabot, which has enabled the customers to get personalized solutions of their problems. This paper aims to identify and develop the transformation and revolution, which has been taken place due to the use of AI in shaping consumer behaviour towards online food delivery services by doing an exploratory analysis based on the published literature in Food delivery applications. This paper suggest that AI is not only a medium of getting customer data and promoting sales but also a strong tool to provide customization and develop a future ready ecosystem for restaurant industry. This paper will throw light on the challenges and issues related to Artificial Intelligence (AI) in the restaurant industry.

This paper aims to discuss the impacts of COVID-19 on restaurant marketing and management practices and outlines a three-pronged research agenda to stimulate knowledge development in the restaurant sector. This paper is based on an overview of the relevant literature on social media in food advertising. The authors also investigated trends in hospitality services to suggest a research agenda. This paper presents a research agenda in three dimensions - Artificial Intelligence (AI) and digital media ads and the importance of social media ads during Covid 19. First, different types of artificial intelligence (mechanical, thinking and feeling) may open distinct research streams at the intersection of health crises and restaurants, in light of the COVID-19 pandemic. In addition, this paper recommends that researchers move beyond typical perspectives on precedents and the results of restaurant cleanliness and cleanliness to delve into. Moreover, to help restaurants recover from the COVID-19 pandemic. The proposed research streams are expected to provide actionable insights to promote development and sustainability in the restaurant sector. Authenticity / Value - This paper appears to be a frontier study, looking critically at the potential impacts of the COVID-19 pandemic, the impacts of COVID-19 on the restaurant industry and how restaurant owners can respond to such post-pandemic recovery challenges.

The restaurant industry is a fiercely competitive sector, demanding constant adaptation to shifting consumer preferences. Market testing plays a pivotal role in devising successful strategies, offering insights into consumer behavior, trends, and competition. While traditional qualitative methods like SWOT analysis are prevalent, emerging technologies such as Artificial Intelligence are transforming the landscape. Bayesian Optimization, in particular, shows promise in optimizing menu offerings and pricing strategies. This study delves into a diverse dataset, examining key metrics like ratings, number of ratings, and average cost. It uncovers correlations between services like online ordering/table booking and customer satisfaction. Cuisine analysis reveals dominant choices, guiding menu specialization. Geographical insights inform pricing strategies tailored to specific areas. The study concludes that market testing, in synergy with innovative technologies, forms the bedrock of effective restaurant strategies. It advocates for a continuous, adaptive approach in this dynamic industry. The research suggests avenues for future exploration including in-depth consumer behavior analysis and ethical considerations in AI implementation.

The article explores methodological approaches to analyzing contemporary challenges, threats, and prospects for the development of the hospitality and restaurant industry (HRI) within the context of global transformations and Ukraine’s wartime realities. It reveals the essence and multifaceted nature of HRI as an object of scientific research, encompassing not only the material aspects of service provision (accommodation and catering) but also significant non-material components related to consumers’ emotional experiences, the ambiance of establishments, and the quality of interpersonal interactions. Key global challenges and threats impacting HRI development are classified, including technological shifts, growing demands for sustainable development, geopolitical instability, workforce shortages, and others. Special attention is given to the analysis of specific problems and threats faced by Ukraine’s hospitality and restaurant industry under military aggression, such as infrastructure destruction, labor migration, and constrained consumer demand. The study underscores the practical necessity of updating the methodology for HRI research, emphasizing its fundamental distinction: augmenting traditional scientific principles with flexibility, interdisciplinarity, technological integration, and practical orientation. A range of contemporary methodological approaches is identified and substantiated, grounded in the active use of digital technologies, big data analytics, artificial intelligence (AI), the Internet of Things (IoT), and other innovative tools. Prospective directions for advancing the methodology of HRI research in Ukraine are outlined, focusing on adaptability, localization of tools, and integration into the European scientific sphere. Proposed strategies include leveraging digital platforms for infrastructure restoration, adopting green technologies, adapting European best practices in environmental, social, and governance (ESG) responsibility, developing tourist clusters, and emphasizing the social role of HRI.

Purpose This study aims to examine the evolution of restaurant revenue management (RRM), highlighting emerging research areas and challenges. It aims to provide a structured overview of revenue optimisation strategies, emphasising the impact of digital transformation, customer behaviour shifts and technological advancements. The study offers practical insights for restaurant operators on leveraging data-driven strategies, including dynamic pricing, artificial intelligence (AI)-powered forecasting and menu engineering, to enhance profitability and customer satisfaction. By mapping the field’s trajectory, the research identifies opportunities for future investigation, ensuring that restaurant managers and academics have a clear framework for optimising revenue performance in an increasingly digital and competitive environment. Design/methodology/approach This study employs a systematic literature review (SLR) to analyse 108 articles published between 1997 and 2023 from major academic databases. The methodology ensures a structured, transparent and replicable synthesis of research trends in RRM. Following a five-step process, the study identifies key strategic levers and methodological gaps, integrating recent developments in big data analytics, digital transformation and AI-driven forecasting models. By categorising RRM literature into five strategic levers, this research provides a comprehensive understanding of the field’s evolution and its implications for future revenue management practices in the restaurant industry. Findings The impact of COVID-19 has accelerated digital transformation in the restaurant industry, driving a fundamental shift in RM research. Adopting digital menus, consolidating online reservations and expanding delivery services have prompted new research avenues in data analytics, capacity optimisation, price personalisation and operational efficiency. As the industry evolves, academic literature reflects a clear transition toward data-driven RM, leveraging sophisticated tools to maximise profitability and enhance the customer experience in the post-pandemic landscape. Originality/value This is the first systematic review integrating post-pandemic digitalisation trends in RRM. The study introduces an expanded framework that incorporates information and sales management as key revenue levers. It explores AI-driven decision-making, real-time data analytics, and behavioural pricing strategies, setting the foundation for future research in restaurant revenue optimisation. By addressing the sector’s ongoing digital transformation, this study provides valuable recommendations for industry practitioners and researchers, helping restaurants to implement innovative revenue strategies that improve financial performance while enhancing customer experience in an evolving, technology-driven market.

Research purpose:This comprehensive study analyzes the current risk state within the largest restaurant chain in Vietnam.Identified risks in the restaurant chain include process execution, food safety, labor safety, financial management, restaurant reputation, tangible asset loss, system failures, and internal fraud. Research motivation:The critical need for effective risk management strategies within the largest restaurant chain in Vietnam, driven by the industry's heightened vulnerability to risks such as food safety, operational inefficiencies, and financial instability.By exploring the root causes of various risks and proposing advanced management strategies, the research aspires to contribute significantly to enhancing the risk management capabilities of the Vietnamese restaurant industry, thereby safeguarding its long-term viability and competitiveness. Research design, approach, and method:The author employs a mixed-method approach, combining quantitative data from the investigation and survey of risk events throughout 2023 with qualitative analysis to explore the root causes of these risks. Main findings:The results indicate that risks are primarily concentrated in three main groups: food safety, process execution, and workplace safety.Furthermore, the study reveals differences in risk distribution between restaurant chains in Vietnam's Northern and Southern regions.Risk events are also more prevalent in major cuisines which are BBQ, Hotpot and Others, particularly in Hanoi and Ho Chi Minh City.The study also highlights that inconsistencies in employee training, insufficient supervision, and the underutilization of modern management technologies contribute to operational challenges. Practical/managerial implications:The research underscores the necessity of adopting advanced risk management strategies, including integrating artificial intelligence (AI) and blockchain and incorporating ESG criteria into risk management to enhance risk detection, improve transparency, and strengthen brand reputation.

Artificial Intelligence (AI) has rapidly become a critical technology for businesses seeking to improve efficiency and profitability. One area where AI is proving particularly impactful is in service operations management, where it is used to create AI-powered service operations (AIServiceOps) that deliver highvalue services to customers. AIServiceOps involve the use of AI to automate and optimize various business processes, such as customer service, sales, marketing, and supply chain management. The rapid development of Artificial Intelligence has prompted many changes in the field of Information Technology (IT) Service Operations. IT Service Operations are driven by AI, i.e., AIServiceOps. AI has empowered new vitality and addressed many challenges in IT Service Operations. However, there is a literature gap on the Business Value Impact of Artificial intelligence (AI) Powered IT Service Operations. It can help IT build optimized business resilience by creating value in complex and ever-changing environments as product organizations move faster than IT can handle. So, this research paper examines how AIServiceOps creates business value and sustainability, basically how AIServiceOps makes the IT staff liberation from a low-level, repetitive workout and traditional IT practices for a continuously optimized process. One of the research objectives is to compare Traditional IT Service Operations with AIServiceOPs. This paper provides the basis for how enterprises can evaluate AIServiceOps and consider it a digital transformation tool. The paper presents a case study of a company that implemented AI-powered service operations (AIServiceOps) and analyzes the resulting business outcomes. The study shows that AIServiceOps can significantly improve service delivery, reduce response times, and increase customer satisfaction. Furthermore, it demonstrates how AIServiceOps can deliver substantial cost savings, such as reducing labor costs and minimizing downtime.

The leagility strategy has been successfully implemented in manufacturing and supply chain management. However, the literature on how to employ the leagile paradigm in service management is very limited. This paper explores how to employ the leagility paradigm with queuing theory in service operations. The queuing models further the understanding of the variability associated with service operations and provide science-based guidelines for implementing a leagile strategy in service operations. A real-world case study in the fast food restaurant industry illustrates that the leagile approach yields reliable results for designing service operations to match customer demand. The research findings suggest that, given modifications to the leagility principles in the service operations management context, leagility can serve as an efficient tool to create cost-effective service operations and quickly respond to changing marketplace demand.