Search in Publications
Found 6407 publications
Analysis of Human-Robot Interactions as a Sustainability Factor
Publication Name: Chemical Engineering Transactions
Publication Date: 2023-01-01
Volume: 107
Issue: Unknown
Page Range: 85-90
Description:
Robotic systems are traditionally widespread in the efficient automatization of industrial processes. Recent applications include material handling, reconnaissance, and agricultural tasks, besides the more traditional assembly line tasks. On the other hand, the recent advancements of robotic systems aim at enhancing and even replacing the human workforce in traditional social service tasks, like nursery, clerk positions, eldercare, and catering – collectively called social robotics. Developed countries generally suffer from the decreased available workforce in these areas, threatening the long-term availability of such essential services. The robots providing such services are required to appear and behave human-like to some degree to interact with people seamlessly. Human-like behavior requires complex software and hardware systems with learning capabilities to solve social situations appropriately. This paper investigates the relationship between human-robot interactions and sustainability and identifies the foundational similarities between the aims of the two interdisciplinary fields. The paper proposes the effect of complex interaction capabilities on sustainable factors and their possible qualitative verification. The quantitative factors described in this paper are the social perception of different robots and their expected functions defined by the foundational human-robot interaction roles. The paper proposes the possible contribution of future social robot applications to sustainability factors, such as the effect of telepresence. The paper also presents the result of a qualitative survey of participating university students on the acceptance of different types of robots based on their visual appearance. The assumption of possible integration of robots into social roles and what appearance is perceived as acceptable. In summary, this paper highlights the sustainable factors in human-robot interactions by identifying the effects of social robot roles and mapping between corresponsive sustainability factors, most importantly resolving workforce deficit.
Open Access: Yes
DOI: 10.3303/CET23107015
A Simulation-Optimization Framework for Road Maintenance Scheduling with Adaptive Agent Behavior
Publication Name: Lecture Notes in Networks and Systems
Publication Date: 2026-01-01
Volume: 1768 LNNS
Issue: Unknown
Page Range: 173-189
Description:
Recently, with an increasing number of people traveling by car, there has been a growing demand for effective traffic management, reduced travel times, and improved road and street maintenance plans. Here, it is evident that drivers make a well-informed decision on which route to take by utilizing smartphone routing, traffic announcements, and advancements in navigation technology. In the present study, the authors aim to develop a road maintenance plan that incorporates a bi-level optimization and simulation framework. They focus on the upper level by optimizing the road maintenance plan; at a lower level, intelligent agents acting as savvy passengers seek to minimize driving time and wait times in traffic. To evaluate the intelligent behavior of agents in reducing travel time on blocked routes (due to road repairs) under various scenarios, the authors first calculate the agents’ behavior in finding the optimal travel demand route and then integrate the optimization of the road maintenance plan. The results of this study demonstrated the effectiveness of informing passenger agents and their intelligence in correcting routes and reducing travel time.
Open Access: Yes
Sustainable Consumption from a Domestic Food Purchasing Perspective Among Hungarian Generation Z
Publication Name: Decision Making Applications in Management and Engineering
Publication Date: 2024-01-23
Volume: 7
Issue: 2
Page Range: 401-417
Description:
The relevance of the study is the global consumer trend towards sustainability. Sustainable consumption has positive environmental, social, and economic impacts, which makes it a key issue in the context of food consumption. Preference for regional, and domestic products can significantly support sustainable consumption. The study focused on the demographically and economically important Generation Z from the perspective of sustainable consumption. The main research objective of the study is to analyze the Hungarian food purchasing habits of Generation Z and to segment Generation Z according to the Hungarian food consumption criteria to characterize potential target groups. During the research, qualitative and quantitative data collection was carried out. The study focuses on the presentation of the results of the latter. In the quantitative survey, we conducted a pre-tested standardized questionnaire online survey. Subject recruitment was carried out using a snowball sampling method, resulting in 518 evaluable questionnaires. In a quantitative study, distinct segments of Hungarian food consumers were characterized according to their food consumption preferences. The research also demonstrated that the groups of Generation Z according to Hungarian food consumption preferences differ significantly from each other in terms of their perception of Hungarian food. The research concludes that Generation Z is a group of domestic food consumers with specific characteristics, who could be the main base for sustainable consumption. For those who have not yet developed this motivation, the main reasons are an unsophisticated preference system and a lack of education. Systematic marketing activities aimed at the first component of attitudes are therefore most needed to attract these segments.
Open Access: Yes
Unpacking IT-Driven Digital Transformation in Marketing 4.0 Through a Sociomaterial Gioia Lens
Publication Name: Journal of Global Information Management
Publication Date: 2025-01-01
Volume: 33
Issue: 1
Page Range: Unknown
Description:
The application of Artificial Intelligence (AI)-enabled technologies into the retail environment has led to the emergence of the Marketing 4.0 paradigm, which integrates customer digital and physical touch-points to deliver value. The study used sociomateriality as a theoretical lens to examine how AI-driven marketing practices were enacted, negotiated, and established in retail organizations through human-material entanglements. The crowdsourcing platform Prolific Academic was used to collect data from retail professionals through open-ended essays. Data were analyzed using Gioia's methodology, which led to the identification of five dimensions—sociomaterial entanglement, material agency, situated practices, temporal emergence, and sociomaterial identity—which aligned with sociomateriality theory, encouraging the adoption of Marketing 4.0 in the retail context. The study developed a holistic framework to visualize the relationships that emerged from the participants' responses, addressing the criticalities of the Marketing 4.0 ecosystem.
Open Access: Yes
DOI: 10.4018/JGIM.393626
The recent advances of near-infrared spectroscopy in dairy production—a review
Publication Name: Critical Reviews in Food Science and Nutrition
Publication Date: 2022-01-01
Volume: 62
Issue: 3
Page Range: 810-831
Description:
One of the major issues confronting the dairy industry is the efficient evaluation of the quality of feed, milk and dairy products. Over the years, the use of rapid analytical methods in the dairy industry has become imperative. This is because of the documented evidence of adulteration, microbial contamination and the influence of feed on the quality of milk and dairy products. Because of the delays involved in the use of wet chemistry methods during the evaluation of these products, rapid analytical techniques such as near-infrared spectroscopy (NIRS) has gained prominence and proven to be an efficient tool, providing instant results. The technique is rapid, nondestructive, precise and cost-effective, compared with other laboratory techniques. Handheld NIRS devices are easily used on the farm to perform quality control measures on an incoming feed from suppliers, during feed preparation, milking and processing of cheese, butter and yoghurt. This ensures that quality feed, milk and other dairy products are obtained. This review considers research articles published in reputable journals which explored the possible application of NIRS in the dairy industry. Emphasis was on what quality parameters were easily measured with NIRS, and the limitations in some instances.
Open Access: Yes
A Monte carlo framework for procedural fixture fairness evaluation in league competitions
Publication Name: Annals of Operations Research
Publication Date: 2026-01-01
Volume: Unknown
Issue: Unknown
Page Range: Unknown
Description:
Fairness is a critical yet underexplored dimension of tournament scheduling, where fixture asymmetries can systematically distort competition outcomes. This paper develops a Monte Carlo simulation framework as a general decision-support tool for assessing procedural fairness in league formats, isolating distortions arising from fixture structure rather than team strength or ranking rules. The approach integrates probabilistic match outcome modelling with two complementary fairness indicators: total fairness bias, capturing the magnitude of schedule-induced distortions, and the Gini index, measuring their distribution across participants. By incorporating competition-specific importance weights, the framework enables a context-aware, two-dimensional assessment applicable to any round-robin or multi-phase format, and can be embedded as a modular component into optimization, heuristics, or machine learning–based scheduling systems. To illustrate its applicability, we apply the framework to two European football leagues with structurally asymmetric designs. The results show how corrective mechanisms – such as home/away balancing phases – can significantly reduce fairness distortions compared to uncorrected triple round-robin structures. Beyond the case studies, the contribution is methodological: the framework provides a reproducible tool for fairness assessment and a foundation for fairness-aware optimization and scheduling methods applicable across sports and competition formats. Although demonstrated on football, the methodology is domain-independent and transferable to any context where fairness and equity are of relevance.
Open Access: Yes
Online Paradigms in Education—Nexus of Blockchain and Gamification
Publication Name: Springer Proceedings in Business and Economics
Publication Date: 2023-01-01
Volume: Unknown
Issue: Unknown
Page Range: 379-403
Description:
This is a conceptual paper, which binds together blockchain technology and gamification in higher education context. Both of the definitions provide several opportunities in competitive sphere and there are findings of each advantage in education already. At the same time, there are few findings in the common attributes of gamification and blockchain. The literature review highlights those sources which discuss the common attributes of the two terms and also represents the main trends of findings in the aspect of education. The paper represents a quick study then, in which dominating blockchain services are represented and gamification interpretation is highlighted in them. Through the systematic study of blockchain platforms involved in this paper by random sampling, a conceptual model gives insight into the list of advantages of the conscious application of blockchain technology and gamification in education activity. The paper provides more opportunities to professionals and policymakers in education to get a complex picture of the opportunities given by the common usage of blockchain and gamification. On the other hand, there are segments in the represented blockchain platforms, which can be developed by a gamified situation. The analysis highlights also these issues.
Open Access: Yes
Bridging the funding gap: advancing sustainable food security in West Africa to achieve SDG 2
Publication Name: Discover Sustainability
Publication Date: 2025-12-01
Volume: 6
Issue: 1
Page Range: Unknown
Description:
As the global population exceeds 8 billion, pressure on food systems is growing, especially in developing regions where funding gaps hinder progress toward Sustainable Development Goal 2. This study investigates sustainable food security in West Africa, focusing on the role of the African Development Bank Group (AfDB). A quantitative, secondary research approach is applied, combining a literature review with time series data. Three indicators are examined, undernourishment (2000–2022), food insecurity (2014–2022), and AfDB-funded projects (1970–2023), with a detailed focus on the overlapping period of 2015–2022. Findings reveal significant disparities across countries. From 2015 to 2022, undernourishment decreased in only seven of fifteen countries, while food insecurity rose in nearly all. In 2022, 17% of the population was undernourished, and 61% lived in moderate or severe food insecurity. Although Nigeria recorded a relatively low undernourishment rate, it had the highest absolute number of affected individuals due to its population size. Since 1970, AfDB has financed 339 food security-related projects in the region, with notable growth during the MDG and SDG periods. Ghana and Mali received the most projects, while Côte d’Ivoire and Nigeria attracted the largest funding volumes. Per capita distribution reveals significant disparities, with Cape Verde and Gambia receiving proportionally more support. Over time, project focus evolved from rural development to climate resilience and value chain enhancement, showing the change in development priorities. The study contributes to understanding how long-term, targeted investments by development finance institutions influence food security outcomes in West Africa.
Open Access: Yes
Development in Machine Learning Based Rapid Visual Screening Method for Masonry Buildings
Publication Name: Lecture Notes in Civil Engineering
Publication Date: 2023-01-01
Volume: 433 LNCE
Issue: Unknown
Page Range: 411-421
Description:
The susceptibility of existing buildings to earthquakes is required to be assessed since building stock consists of structures that were constructed before the development of seismic standards, whether by disregarding them or by taking into account lower seismic regulations. Damage to buildings due to earthquakes not only endanger people’s lives but also causes economic losses. Because examining a large number of buildings by employing detailed building assessment methods is computationally expensive, Rapid Visual Screening (RVS) techniques are capable of assessing large building stock. Previous studies demonstrate that accuracy of the conventional RVS methods to precisely determine buildings’ damage states is limited. Therefore, it is required to develop a new RVS method. Since machine learning is extremely competent in establishing a relationship between input parameters and the target variable, this study introduces a new machine learning-based highly accurate RVS method, that can be applied in different countries, for masonry buildings using post-earthquake building screening data of 273 masonry buildings collected after the 2019 Mugello, Italy earthquake. The developed method differs from conventional RVS methods in terms of considered parameters such as spectral acceleration, the fundamental natural frequency of buildings, and the distance to the earthquake source. By comparing calculated building damage states with identified damage states through post-earthquake inspection, the developed method’s potential efficiency has been demonstrated as 88.9% accurate.
Open Access: Yes
