The convergence of artificial intelligence, cyber-physical systems, and cross-enterprise data ecosystems has propelled industrial intelligence to unprecedented scales. Yet, the absence of a unified trust foundation across data, services, and knowledge layers undermines reliability, accountability, and regulatory compliance in real-world deployments. While existing surveys address isolated aspects, such as data governance, service orchestration, and knowledge representation, none provides a holistic, cross-layer perspective on trustworthiness tailored to industrial settings. To bridge this gap, we present \textsc{Trisk} (TRusted Industrial Data-Service-Knowledge governance), a novel conceptual and taxonomic framework for trustworthy industrial intelligence. Grounded in a five-dimensional trust model (quality, security, privacy, fairness, and explainability), \textsc{Trisk} unifies 120+ representative studies along three orthogonal axes: governance scope (data, service, and knowledge), architectural paradigm (centralized, federated, or edge-embedded), and enabling technology (knowledge graphs, zero-trust policies, causal inference, etc.). We systematically analyze how trust propagates across digital layers, identify critical gaps in semantic interoperability, runtime policy enforcement, and operational/information technologies alignment, and evaluate the maturity of current industrial implementations. Finally, we articulate a forward-looking research agenda for Industry 5.0, advocating for an integrated governance fabric that embeds verifiable trust semantics into every layer of the industrial intelligence stack. This survey serves as both a foundational reference for researchers and a practical roadmap for engineers to deploy trustworthy AI in complex and multi-stakeholder environments.
This study investigated the relationship of TESDA Industry Core Competencies with the employment rates of graduates from the Diploma in Hotel and Restaurant Technology program at Samar National School of Arts and Trade (SNSAT), Taft, Eastern Samar. Utilizing a quantitative correlational research design, data were collected from 48 graduates between 2022 and 2024 through survey questionnaires assessing the competencies learned, industry-required skills, and employment status. Findings revealed that graduates reported a very high mastery of TESDA core competencies, particularly in areas such as food and beverage service, bartending, cookery, event management, and housekeeping. Industry demands prioritized core competencies (52%) over basic (27%) and common competencies (21%), indicating strong alignment with TESDA’s curriculum. The average employment rate was 62%, with variability across the years studied. Correlation analysis showed a statistically significant moderate positive relationship between TESDA core competencies and industry-required competencies, confirming the relevance of TESDA training to employer needs. However, no significant relationship was found between core competencies and graduates’ employment status or nature of employment, suggesting that factors beyond skill mastery influence job placement. The study concludes that TESDA’s technical education effectively equips graduates with industry-relevant skills, enhancing employability. Nonetheless, to improve employment outcomes, additional support mechanisms such as career guidance, job placement assistance, and stronger industry partnerships are recommended. Continuous curriculum updates and sustained training quality are essential to maintaining the program’s effectiveness in meeting evolving hospitality industry demands.
Зінаїда Богданівна Живко, Наталія Федорівна Павленчик, М. Є. Стадник
The relevance of the study is determined by the specifics of the activities of hotel and restaurant complexes and the importance of the role of personnel in ensuring the proper quality of services provided. It is noted that the need for innovative development of hotel and restaurant complexes and improvement of their personnel management requires a transition from traditional management methods to more modern ones that take into account all areas of the management process: selection and training of personnel, labor standards and motivation, greater involvement of employees in the management process, etc. The principles, functions, tools, and methods of innovative personnel management are described. The need to apply an individual approach and take into account job responsibilities in the process of personnel management in the hospitality industry is emphasized in order to ensure high performance of each employee, improve the quality of service, increase the professionalism of personnel and reduce its turnover, improve the performance of the establishment, etc. The success of personnel management in hotel and restaurant businesses largely depends on the process of developing a manager-leader who is able to communicate effectively with the team, find an individual approach to each employee, stimulating their full commitment and contributing to their job satisfaction; stabilize crisis situations in the team and in production or in the management process; study the essence of business processes and ensure that the team is focused on achieving the strategic goals of the establishment. The formation of an effective leadership climate in hotel and restaurant establishments requires a number of stages and coverage of key areas. Thus, the management of personnel in hotel and restaurant complexes must take into account the specifics of their activities, the need for innovative development, consumer needs, the use of innovative approaches in management, the formation of a favorable corporate climate, and adherence to the principles of leadership.
The recent development of Agentic AI systems, empowered by autonomous large language models (LLMs) agents with planning and tool-usage capabilities, enables new possibilities for the evolution of industrial automation and reduces the complexity introduced by Industry 4.0. This work proposes a conceptual framework that integrates Agentic AI with the intent-based paradigm, originally developed in network research, to simplify human-machine interaction (HMI) and better align automation systems with the human-centric, sustainable, and resilient principles of Industry 5.0. Based on the intent-based processing, the framework allows human operators to express high-level business or operational goals in natural language, which are decomposed into actionable components. These intents are broken into expectations, conditions, targets, context, and information that guide sub-agents equipped with specialized tools to execute domain-specific tasks. A proof of concept was implemented using the CMAPSS dataset and Google Agent Developer Kit (ADK), demonstrating the feasibility of intent decomposition, agent orchestration, and autonomous decision-making in predictive maintenance scenarios. The results confirm the potential of this approach to reduce technical barriers and enable scalable, intent-driven automation, despite data quality and explainability concerns.
Pascal Wullschleger, Majid Zarharan, Donnacha Daly
et al.
We investigate the utility of Large Language Models for automated taxonomy generation and completion specifically applied to taxonomies from the food technology industry. We explore the extent to which taxonomies can be completed from a seed taxonomy or generated without a seed from a set of known concepts, in an iterative fashion using recent prompting techniques. Experiments on five taxonomies using an open-source LLM (Llama-3), while promising, point to the difficulty of correctly placing inner nodes.
India's growing population and economy have significantly increased the demand and consumption of natural resources. As a result, the potential benefits of transitioning to a circular economic model have been extensively discussed and debated among various Indian stakeholders, including policymakers, industry leaders, and environmental advocates. Despite the numerous initiatives, policies, and transnational strategic partnerships of the Indian government, most small and medium enterprises in India face significant challenges in implementing circular economy practices. This is due to the lack of a clear pathway to measure the current state of the circular economy in Indian industries and the absence of a framework to address these challenges. This paper examines the circularity of the 93-textile industry in India using the C-Readiness Tool. The analysis comprehensively identified 9 categories with 34 barriers to adopting circular economy principles in the textile sector through a narrative literature review. The identified barriers were further compared against the findings from a C-readiness tool assessment, which revealed prominent challenges related to supply chain coordination, consumer engagement, and regulatory compliance within the industry's circularity efforts. In response to these challenges, the article proposes a strategic roadmap that leverages digital technologies to drive the textile industry towards a more sustainable and resilient industrial model.
Mari Ashiga, Vardan Voskanyan, Fateme Dinmohammadi
et al.
Recent advancements in Large Language Models (LLMs) for code optimization have enabled industrial platforms to automate software performance engineering at unprecedented scale and speed. Yet, organizations in regulated industries face strict constraints on which LLMs they can use - many cannot utilize commercial models due to data privacy regulations and compliance requirements, creating a significant challenge for achieving high-quality code optimization while maintaining cost-effectiveness. We address this by implementing a Mixture-of-Agents (MoA) approach that directly synthesizes code from multiple specialized LLMs, comparing it against TurinTech AI's vanilla Genetic Algorithm (GA)-based ensemble system and individual LLM optimizers using real-world industrial codebases. Our key contributions include: (1) First MoA application to industrial code optimization using real-world codebases; (2) Empirical evidence that MoA excels with open-source models, achieving 14.3% to 22.2% cost savings and 28.6% to 32.2% faster optimization times for regulated environments; (3) Deployment guidelines demonstrating GA's advantage with commercial models while both ensembles outperform individual LLMs; and (4) Real-world validation across 50 code snippets and seven LLM combinations, generating over 8,700 variants, addresses gaps in industrial LLM ensemble evaluation. This provides actionable guidance for organizations balancing regulatory compliance with optimization performance in production environments.
The formation of market relations in the Ukrainian economy on the model of sustainable development necessitates the improvement of marketing, its ability to counteract the challenges of the negative impact of a changing market environment, where imperfections in the market conditions of hotel and restaurant services, excessive hotel and restaurant supply against the background of a decline in consumer demand for this type of service, and the lack of an effective organizational and economic mechanism for the development of the hotel and restaurant business at the regional level remain urgent. At the same time, the intensification of competition in the field of tourism and hospitality in the modern period necessitates the introduction by business entities of innovative marketing strategies adapted to industry micro- and macroeconomic risks and current problems of development of the Ukrainian hotel and restaurant business, etc. The study aims to generalize and develop theoretical and methodological foundations and practical recommendations for improving the methods and tools for implementing effective marketing strategies of enterprises in the hotel and restaurant business. It is determined that in a highly competitive environment, effective marketing plays a crucial role in the tourism and hospitality industry. The expediency of using the concept of “adaptive marketing strategy” as a way to achieve the strategic marketing goals of enterprise through the implementation of prompt and effective management decisions to ensure the necessary level of viability of enterprise and maximum satisfaction of consumer needs is substantiated, and a model of the basic determinants of forming an adaptive marketing strategy for enterprises in the hotel and restaurant industry (HRI) is proposed. It has been determined that several specific features and industry-specific conditions are necessary for developing the modern hotel and restaurant industry, and the need to introduce marketing activities that correspond to more innovative and evolutionary modified models of “5P… 7P”. Generalizing several existing theoretical and methodological approaches will allow us to highlight important accents, which, if considered at the development stage, will allow us to succeed in the final stage of its implementation: 1. Assessment of the value of profit growth. 2. Features of positioning the hotel/restaurant service/product on the target consumer market. 3. Increase in market share and sales volume. 4. Development of new segments of the consumer market and entry into new markets. 5. Marketing pricing. The methods for analyzing the adaptive marketing strategy of enterprises and the latest trends in the development of the hotel and restaurant business on a marketing basis are determined. It is proven that the implementation of a comprehensive adaptive marketing strategy for the hotel and restaurant business, focused on the consumer in the system of increasing customer focus, leads to long-term cooperation with the consumer through the offer of innovative services/products, additional services, competitive prices with high-quality 100% service. Keywords: marketing, adaptive marketing strategy, hotel and restaurant business, marketing tools, competitive advantages, hotel and restaurant service/product, marketing management system.
Актуальність. Функціональне харчування – це сучасна концепція здорового способу життя, що передбачає використання інгредієнтів, які не лише мають високу поживну цінність, а й характеризуються біологічною активністю, сприяючи зміцненню здоров’я та зниженню ризику розвитку певних захворювань. Молоко та молочні продукти посідають провідне місце серед функціональних продуктів харчування сьогодення та майбутнього. Морозиво як популярний представник десертної групи популярне на ринку завдяки своїй високій харчовій цінності, гнучкості рецептури та широкій віковій аудиторії споживачів. У цьому контексті розроблення та впровадження вітчизняними виробниками інноваційних десертних харчових продуктів, виготовлених виключно з натуральної сировини, із пониженим вмістом калорій, збагачених цінними рослинними компонентами й біологічно активними речовинами, є актуальними і важливими напрямами сучасної харчової промисловості. Мета статті – аналіз ринку вітчизняного морозива, основних тенденцій виробництва морозива функціонального спрямування, наукове обґрунтування розроблення рецептур низьколактозного морозива із пробіотичними властивостями. У процесі дослідження застосовано методи емпіричного та теоретичного узагальнення, аналізу й синтезу наукової та технічної інформації, експертне оцінювання тенденцій розвитку ринку, а також елементи експериментального моделювання рецептури низьколактозного морозива на основі використання пробіотичних культур та компонентів, що знижують вміст лактози. Результати. Створено інноваційні рецептури морозива комбінованого білкового складу з використанням соєвого йогурту та компонентів рослинного походження, що є джерелами біологічно активних речовин. Висновки та обговорення. Перспективним напрямом розвитку галузі морозива є цільове виробництво інноваційних видів заморожених десертів функціонального призначення із застосуванням сучасних технологічно ефективних інгредієнтів та збагачувачів, що мають оздоровчий потенціал.
Hospitality industry. Hotels, clubs, restaurants, etc. Food service, Commerce
In the field of food, as in other fields, the measurement of emotional responses to food and their sensory properties is a major challenge. In the present protocol, we propose a step-by-step procedure that allows a physiological description of odors, aromas, and their hedonic properties. The method rooted in subgroup discovery belongs to the field of data science and especially data mining. It is still little used in the field of food and is based on a descriptive modeling of emotions on the basis of human physiological responses.
Víctor Julio Ramírez-Durán, Idoia Berges, Arantza Illarramendi
Many different worldwide initiatives are promoting the transformation from machine dominant manufacturing to digital manufacturing. Thus, to achieve a successful transformation to Industry 4.0 standard, manufacturing enterprises are required to implement a clear roadmap. However, Small and Medium Manufacturing Enterprises (SMEs) encounter many barriers and difficulties (economical, technical, cultural, etc.) in the implementation of Industry 4.0. Although several works deal with the incorporation of Industry 4.0 technologies in the area of the product and supply chain life cycles, which SMEs could use as reference, this is not the case for the customer life cycle. Thus, we present two contributions that can help the software engineers of those SMEs to incorporate Industry 4.0 technologies in the context of the customer life cycle. The first contribution is a methodology that can help those software engineers in the task of creating new software services, aligned with Industry 4.0, that allow to change how customers interact with enterprises and the experiences they have while interacting with them. The methodology details a set of stages that are divided into phases which in turn are made up of activities. It places special emphasis on the incorporation of semantics descriptions and 3D visualization in the implementation of those new services. The second contribution is a system developed for a real manufacturing scenario, using the proposed methodology, which allows to observe the possibilities that this kind of systems can offer to SMEs in two phases of the customer life cycle: Discover & Shop, and Use & Service.
Oscar Trull, Angel Peiro-Signes, J. Carlos Garcia-Diaz
et al.
The increase in travelers and stays in tourist destinations is leading hotels to be aware of their ecological management and the need for efficient energy consumption. To achieve this, hotels are increasingly using digitalized systems and more frequent measurements are made of the variables that affect their management. Electricity can play a significant role, predicting electricity usage in hotels, which in turn can enhance their circularity - an approach aimed at sustainable and efficient resource use. In this study, neural networks are trained to predict electricity usage patterns in two hotels based on historical data. The results indicate that the predictions have a good accuracy level of around 2.5% in MAPE, showing the potential of using these techniques for electricity forecasting in hotels. Additionally, neural network models can use climatological data to improve predictions. By accurately forecasting energy demand, hotels can optimize their energy procurement and usage, moving energy-intensive activities to off-peak hours to reduce costs and strain on the grid, assisting in the better integration of renewable energy sources, or identifying patterns and anomalies in energy consumption, suggesting areas for efficiency improvements, among other. Hence, by optimizing the allocation of resources, reducing waste and improving efficiency these models can improve hotel's circularity.
The article provides a comprehensive analysis of the modern phenomenon of hospitality in various aspects at different levels. Two semantic interpretations of hospitality, conventionally interpreted as “hospitality-trait” and “hospitality-sphere”, are proposed and substantiated. “Hospitality-trait” is an important characteristic of any entity that, on a commercial or other basis, receives and serves guests for certain reasons. “Hospitality-sphere” is a derivative of “hospitality-traits” and is a product of its institutionalization, namely, a field of activity whose main profile task is to provide quality services to guests. An author’s model of the hospitality sector of society was built, consisting of four levels – the “core”, which includes a complex of hotel-restaurant and tourist business enterprises, and its three “superstructure circles”, a system of enterprises and subjects of each of the following among which gradually reduces the level specialization in hospitality services, but in one way or another applies the features of hospitality in its activities. The presented model of the field of hospitality can serve as an additional basis for the adoption of legislative and regulatory acts and for the adoption of managerial decisions regarding the regulation of the manifestation of hospitality traits in the work of any enterprises and subjects of economic activity, mainly in the field of hotel, restaurant and tourism business. Current directions of research in the field of hospitality are outlined, among which the most important are the problems of measuring the degree of hospitality of its various subjects, as well as improving the system of training specialized personnel. Important directions are also the definition and analysis of the features of hospitality at different levels of spatial and organizational scale and territorial coverage (hospitality of the state, people, region, city, locality, enterprise, institution, industry, social stratum, individual family, individual person, etc.), study of spatial aspects of hospitality, justification of distinctions between “stationary” and “mobile” hospitality, especially during tourist trips, hospitality research at different stages of hospitality product consumption, etc. Argued proposals for improving the quality of education for the “core” of the hospitality sector, primarily strengthening the psychological training of future specialists, using psychological trainings, quests, situational exercises (case studies), etc., are provided. Hospitality in the process of specialized education in the training of specialists in the field of service should pass through all educational components, both during theoretical training and during training of practical skills.
This study uses an Institutional DINESERV model to examine the influence of service quality dimensions (i.e., food quality, atmosphere, service quality, convenience, and price) on customer satisfaction and return patronage in a Student Operated Restaurant (SOR). A total of 62 guests were surveyed at a university SOR in South Africa. Factor analysis, ANOVA, correlation, and regression analyses were used to analyse data. The findings show that all service quality dimensions significantly and positively affected customer satisfaction and revisit intentions. Hospitality programs that use restaurants as teaching labs must concentrate their efforts in these areas to equip students with competencies that better meet these industry needs. This study is unique because it extensively explored the influence of service quality on customer satisfaction and return patronage in an immersive experiential learning program, the student-operated restaurant. This area has been underexplored in contemporary literature.
Hospitality industry. Hotels, clubs, restaurants, etc. Food service, Business
Considering the limited number of studies on the early detection of crises and insolvencies in the tourism industry, there are several research gaps. Therefore, this study analyzes which financial and non-financial variables significantly influence the financial distress of the tourism businesses (hotels and restaurants) in Austria. The resource-based and network-based views were used as theoretical foundations to determine which variables influence the probability of financial distress, with a total of 776 observations from 2005 to 2015 inclusive. The results show that variables describing the endogenous unsystematic risk of tourism businesses (firm-specific level and destination level) make the greatest contribution to explaining financial distress, while exogenous unsystematic and exogenous systematic risk variables show little or no relevance.
Daman Deep Singh, Amit Kumar, Abhijnan Chakraborty
The k-SERVER problem is one of the most prominent problems in online algorithms with several variants and extensions. However, simplifying assumptions like instantaneous server movements and zero service time has hitherto limited its applicability to real-world problems. In this paper, we introduce a realistic generalization of k-SERVER without such assumptions - the k-FOOD problem, where requests with source-destination locations and an associated pickup time window arrive in an online fashion, and each has to be served by exactly one of the available k servers. The k-FOOD problem offers the versatility to model a variety of real-world use cases such as food delivery, ride sharing, and quick commerce. Moreover, motivated by the need for fairness in online platforms, we introduce the FAIR k-FOOD problem with the max-min objective. We establish that both k-FOOD and FAIR k-FOOD problems are strongly NP-hard and develop an optimal offline algorithm that arises naturally from a time-expanded flow network. Subsequently, we propose an online algorithm DOC4FOOD involving virtual movements of servers to the nearest request location. Experiments on a real-world food-delivery dataset, alongside synthetic datasets, establish the efficacy of the proposed algorithm against state-of-the-art fair food delivery algorithms.
This paper examines the sociotechnical infrastructure of an "indie" food delivery platform. The platform, Nosh, provides an alternative to mainstream services, such as Doordash and Uber Eats, in several communities in the Western United States. We interviewed 28 stakeholders including restauranteurs, couriers, consumers, and platform administrators. Drawing on infrastructure literature, we learned that the platform is a patchwork of disparate technical systems held together by human intervention. Participants join this platform because they receive greater agency, financial security, and local support. We identify human intervention's key role in making food delivery platform users feel respected. This study provides insights into the affordances, limitations, and possibilities of food delivery platforms designed to prioritize local contexts over transnational scales.
Vito Napolitano, Olga Polverino, Paolo Santonastaso
et al.
Clubs of rank k are well-celebrated objects in finite geometries introduced by Fancsali and Sziklai in 2006. After the connection with a special type of arcs known as KM-arcs, they renewed their interest. This paper aims to study clubs of rank n in PG$(1,q^n)$. We provide a classification result for (n-2)-clubs of rank n, we analyze the $\mathrm{ΓL}(2,q^n)$-equivalence of the known subspaces defining clubs, for some of them the problem is then translated in determining whether or not certain scattered spaces are equivalent. Then we find a polynomial description of the known families of clubs via some linearized polynomials. Then we apply our results to the theory of blocking sets, KM-arcs, polynomials and rank metric codes, obtaining new constructions and classification results.
We propose a novel service-based ecosystem to crowdsource wireless energy to charge IoT devices. We leverage the service paradigm to abstract wireless energy crowdsourcing from nearby IoT devices as energy services. The proposed energy services ecosystem offers convenient, ubiquitous, and cost-effective power access to charge IoT devices. We discuss the impact of a crowdsourced wireless energy services ecosystem, the building components of the ecosystem, the energy services composition framework, the challenges, and proposed solutions.