Search Results (62)

The deployment of large language models (LLMs) in commercial environments depends critically on the availability of robust digital infrastructure, scalable computing resources, and mature cloud architectures. This study examines how macro-level digital infrastructure, in particular cloud computing adoption, conditions the ability of the European retail sector to deploy and benefit from large language models (LLMs). Using a country-year panel of EU member states from 2017 to 2023, we estimate fixed-effects regressions to quantify the association between enterprise cloud use and retail trade volume growth, and implement an event-study design to explore dynamic responses around changes in cloud uptake. The results show that increases in cloud adoption are significantly associated with higher retail trade growth added and productivity, with especially strong effects in emerging Eastern European markets. We identify a digital threshold of around 20% of enterprises using cloud services, above which the marginal impact on retail performance becomes notably larger. These findings highlight cloud infrastructure as a key enabling condition for LLM-enabled retail applications and inform EU digital and industrial policy targeting regional digital disparities. Full article

Green fintech merges sustainable finance with data-intensive innovation, but national translations of EU rules can create regulatory risk. This study examines how such risk manifests in Central Europe and which policy tools mitigate it. We develop a three-dimension framework—regulatory clarity and scope, supervisory consistency, and innovation facilitation—and apply a comparative qualitative design to Hungary, Slovakia, Czechia, and Poland. Using a common EU baseline, we compile coded national snapshots from primary legal texts, supervisory documents, and recent scholarship. Results show material cross-country variation in labelling practice, soft-law use, and testing infrastructure: Hungary combines central-bank green programmes with an innovation hub/sandbox; Slovakia aligns with ESMA and runs hub/sandbox, though the green-fintech pipeline is nascent; Czechia applies a principles-based safe harbour and lacks a national sandbox; and Poland relies on a virtual sandbox and binding interpretations with limited soft law. These choices shape approval timelines, retail penetration, and cross-border portability of green-labelled products. We conclude with a policy toolkit: labelling convergence or explicit safe harbours, a cross-border sandbox federation, ESRS/ESAP-ready proportionate disclosures, consolidation of recurring interpretations into soft law, investment in suptech for green-claims analytics, and inclusion metrics in sandbox selection. Full article

The aim of this study is to investigate the occurrence of melamine and cyanuric acid in milk, baby food, and protein supplements collected in Croatia. A total of 56 samples were collected during 2022 and 2023 from retail stores in Zagreb, Croatia. Sample preparation involved acetonitrile extraction, followed by analysis using ultra-high-performance liquid chromatography coupled with tandem mass spectrometry (UHPLC-MS/MS). Cyanuric acid concentrations above the limit of quantification (LOQ) were found in five milk samples (33.3% detection frequency), with a range from 0.26 to 0.39 mg/kg and a mean concentration of 0.31 mg/kg. In protein supplements, melamine was detected above the LOQ in six samples (23% detection frequency), with a mean concentration of 0.30 mg/kg and concentrations ranging from 0.20 to 0.57 mg/kg. No concentrations above the LOQ were found in baby food samples. All detected values were below the EU maximum limits (2.5 mg/kg for general food and 1.0 mg/kg for baby food). The accuracy and reliability of the method were verified using certified reference material. This is the first study to confirm the presence of melamine and cyanuric acid in protein supplements and milk on the Croatian market. The detected levels do not indicate a potential health risk to consumers. Full article

Salmonella species isolated from chicken meat pose an increasing threat to public health. According to ECDC data, salmonellosis cases have shown a significant upward trend in many European countries between 2019 and 2023, almost reaching pre-pandemic levels. EFSA reported 77,486 confirmed human cases in the EU in 2023. This corresponds to a notification rate of 18 cases per 100,000 people, compared to 15.4 cases per 100,000 in 2022. This study evaluated the prevalence of Salmonella spp., antimicrobial resistance (AMR) profiles, and the effectiveness of natural biological preservatives in raw chicken meat obtained from retail outlets in Southeast Turkey. Among 100 samples analyzed according to ISO 6579-1:2017, suspicious colonies were detected after selective enrichment in XLD and n = 3 isolates were confirmed to be Salmonella enterica subsp. enterica serovar Infantis by real-time PCR. Disk diffusion tests performed in accordance with EUCAST showed that all isolates were resistant to beta-lactam, tetracycline, trimethoprim, sulfonomid and aminoglycoside groups. All isolates were classified as multidrug-resistant. PCR detected blaTEM-1 (all isolates), aphA1-IAB (all isolates), aadA1 (two isolates), and sul1 (all isolates), while tetA/tetB genes were not detected. Among the natural compounds tested, carvacrol showed the strongest antimicrobial activity (MIC 1.56 µL/mL; MBC 3.125–6.25 µL/mL; inhibition zones 32–35 mm). Eugenol showed moderate effects with higher MIC/MBC values (3.125–6.25 µL/mL/12.25 µL/mL), while α-terpineol was effective only at higher concentrations. These findings are consistent with the global increase in Salmonella Infantis and AMR, supporting carvacrol followed by eugenol and α-terpineol as promising natural alternatives for controlling MDR Salmonella spp. in food safety applications. Full article

The paper investigates disparities in food waste generation across European Union countries between 2020 and 2022, focusing on spatial and sustainability dimensions. It utilizes data for six key food waste parameters and a broad range of environmental, social and economic indicators. A combination of statistical methods, including correlation analysis, cluster analysis and Principal Component Analysis, uncovers multivariate patterns and identifies groups of countries with similar food waste characteristics and related factors. The paper highlights the temporal and spatial dynamics of food waste over the three-year period, particularly in light of the COVID-19 pandemic. While the total volume of food waste remained relatively stable across the EU, notable shifts occurred in waste sources. Household food waste peaked in 2021, likely due to increased time spent at home during pandemic-related lockdowns. Conversely, waste from retail, restaurants and food service sectors showed a consistent increase. The paper identifies non-trivial correlations between food waste and socio-economic variables, suggesting that differences in food waste generation across EU countries are influenced by a complex interplay of factors, including policy effectiveness, cultural practices, consumer behaviour and economic conditions. This comprehensive analysis of food waste patterns across EU countries and over time offers valuable insights for policymakers aiming to reduce waste and promote sustainability. Full article

In a constantly evolving context where non-dispatchable renewable energy sources (RESs) are becoming increasingly widespread, the role of Renewable Energy Communities (RECs) is gaining momentum as a way to promote distributed self-consumption. The spreading of RECs in the European Union (EU) has been supported by the development of technical tools. RECON (Renewable Energy Community ecONomic simulator) is one the most used simulation tools for energy, economic, and financial pre-assessments of RECs in Italy. This software requires, as an input to simulation, the electrical energy use profiles of buildings to estimate the shared energy and, consequently, to calculate economic incentives. However, the availability of reference electrical energy use profiles remains limited, especially when it comes to specific uses such as for organized large-scale retail. To address this issue, this study developed a data-driven model capable of generating electrical energy use profiles specific for organized large-scale retail, using a limited number of inputs, and thereby, addressing the gap in current energy modeling practices. The model validation showed that the model replicates electric energy profiles, on an annual basis, with an average deviation below 5% using minimal inputs. Monthly simulations exhibit greater discrepancies during colder months, which suggest further refinement opportunities. Full article

Food waste poses a significant global challenge with profound economic, environmental, and social implications. Within the European Union, socioeconomic conditions, food affordability, and sustainability initiatives create a complex framework for understanding and mitigating food waste. This study examines how economic and sustainability factors shape food waste patterns across EU member states, employing advanced statistical techniques to uncover underlying dynamics. The analysis focuses on five key variables: the Harmonized Index of Consumer Prices for food, food waste, food retail sales, the Sustainable Development Goals Index, and GDP per capita. Factorial analysis and a general linear model were used to investigate linear relationships, and multilayer Perceptron (MLP) neural networks were employed to model the non-linear relationships driving food waste. At the same time, hierarchical cluster analysis identified four distinct country groups, each characterized by unique combinations of these variables. The results reveal that higher GDP per capita and stronger sustainability performance are associated with lower food waste, whereas higher food prices and increased retail activity present more nuanced influences. The findings underscore the importance of customized policies that address the EU’s diverse socioeconomic and sustainability contexts, offering a pathway toward more sustainable food systems and reduced waste. Full article

Food waste is a chronic and ongoing environmental, economic, and social problem in the European Union. The study will examine trends in food waste from 2021 to 2023, sectoral effects, regional heterogeneity, and socio-economic determinants of waste intensity. Interlinking longitudinal data from Statista and Eurostat, statistical modeling, and cluster analysis are employed by the study to uncover trends in food waste across member states in the EU. The research shows that domestic food wastage remains the leading one, accounting for 50–60% of the total food wastage in the EU. Inefficiencies in manufacturing and retail are identified as important drivers of wastage generation in high-waste nations such as Cyprus and Denmark because inefficiencies in the processes result in increased wastage generation. Spain and Croatia have continued to record low food wastage per capita owing to good wastage management policies and consumer practices. Regression analysis identifies domestic food wastage, manufacturing waste, and retail wastage as the main drivers of total per capita food wastage, with per capita GDP (Gross Domestic Product) and carbon footprint playing weak roles. Cluster analysis places EU countries into three groups: low-waste countries with highly structured food systems, moderately-waste countries where food wastage at domestic levels prevails, and high-waste countries where there is inefficiency at food production, processing, and consumption levels. These findings necessitate specific interventions. Policy needs to address food waste minimization at the household level via consumer awareness and behavior change initiatives and remove inefficiencies in the manufacturing and retail value chains through the simplification of inventory management, redistribution chains, and incentive regulation. Regional, rather than one-size-fits-all, EU-wide policy is required in order to achieve significant progress. Full article

Clostridioides difficile (C. difficile), once considered a predominantly nosocomial pathogen, is increasingly implicated in community-acquired infections (CA-CDIs). This study investigates the prevalence, ribotypes, and antimicrobial susceptibility of C. difficile in Irish pork products and abattoirs, with a focus on the potential public health implications. A total of 180 retail pork products and 150 pig carcase swabs from three abattoirs were examined, alongside 30 environmental lairage samples. The C. difficile isolates were characterised through ribotyping and tested in terms of antimicrobial susceptibility. No C. difficile was isolated from the retail pork, while the carcase swabs yielded a low recovery rate (0.66%). However, the lairage areas were contaminated with C. difficile (33%), and six different ribotypes were identified, including the clinically relevant RT078. The ribotypes exhibited susceptibility to the antibiotics used to treat C. difficile infection (CDI) (fidaxomicin, vancomycin, and metronidazole) but showed resistance to tetracycline (9%) and ciprofloxacin (100%). These findings align with the international findings on antimicrobial resistance in C. difficile and suggest that strict EU food safety standards could mitigate retail pork contamination risks. Nevertheless, the environmental exposure during slaughtering and handling processes presents potential transmission risks for workers. Full article

The EU market offers different types of milk, distinguished by origin, production method, processing technology, fat content, and other characteristics, which are often detailed on product labels. In this context, ensuring the authenticity of milk is crucial for maintaining standards and preventing fraud. Various food authenticity techniques have been employed to achieve this. Among them, near-infrared (NIR) spectroscopy is valued for its non-destructive and rapid analysis capabilities. This study evaluates the effectiveness of a miniaturized NIR device combined with support vector machine (SVM) algorithms and LDA feature selection to discriminate between four commercial milk types: high-quality fresh milk, milk labeled as mountain product, extended shelf-life milk, and TSG hay milk. The results indicate that NIR spectroscopy can effectively classify milk based on the type of milk, relying on different production systems and heat treatments (pasteurization). This capability was greater in distinguishing high-quality mountain and hay milk from the other types, while resulting in less successful class assignment for extended shelf-life milk. This study demonstrated the potential of portable NIR spectroscopy for real-time and cost-effective milk authentication at the retail level. Full article

Aflatoxins (AFs), secondary metabolites produced by fungi, pose significant health risks, especially to children and elderly individuals. In developing countries such as Nepal, the tropical climate promotes fungal growth, leading to elevated levels of AF in animal feed and milk. In this study, we aimed to investigate the occurrence of aflatoxin M1 (AFM1) in dairy milk from the Kathmandu District and to assess husbandry practices contributing to contamination. We collected 84 milk samples, including raw milk from farms, retailers’ milk, and packet milk, and analyzed them using the competitive enzyme-linked immunosorbent assay (c-ELISA) technique. We also interviewed farmers to gather information on feeding and storage practices. All the collected milk samples were contaminated with AFM1, with 97.6% of the samples exceeding the European Union (EU) maximum permissible limit of 50 ppt (0.05 μg/kg). The majority (98.5%) of the farms included paddy straw, and all farms (100%) included concentrate in their feed regimens. Only half (52%) of the farms had proper storage facilities. Straw was mostly stored in sacks outdoors or left open in a shed, while concentrates were stored in a closed room or shed. This study reveals very high levels of AFM1 contamination in the milk samples, presenting a serious public health issue, and recommends comprehensive surveillance and further investigations across the country, especially given the limited research and literature available. Full article

Dichloromethane (DCM) is extensively used around the globe in various applications, such as in closed industrial installations for food processing or pharmaceutical extractions (vitamins, antibiotics, etc.). In the coffee sector, it is used as an extraction agent for the decaffeination process of green coffee beans. Due to its low boiling point, ranging at approx. 40 °C, DCM can be easily removed subsequent to caffeine extraction by applying state-of-the-art solvent stripping processes. The intention of this study is to assess how much DCM, if any, is present in decaffeinated coffee packages as sold to the consumer, as well as how much of the extraction solvent residue is transferred into the finally prepared, consumable coffee beverage. This study sets out to highlight DCM contents of decaf coffees, directly taken from six EU countries’ supermarket shelves. In addition, DCM mass transfer rates from roasted coffee matrices into the corresponding, variously prepared beverages (drip percolated coffee, French press) are determined. All analyses were performed applying a Headspace-GC-MS technique. All presented data demonstrate that DCM residues in the 34 coffee samples analysed have contents well below the DCM maximum residue limits for roasted coffee both in the European Union (2 mg/kg) and the USA (10 mg/kg), with an average of 0.127 mg/kg, median value of 0.059 mg/kg and P95 of 0.444 mg/kg. Furthermore, this study shows that DCM mass transfer rates from the coffee matrices into the corresponding beverages have, for drip coffee, an average of 24.7% and median of 26.8%, and for French press, an average mass transfer of 41.9% and median of 43.1%. Full article

Contaminations with cephalosporin-resistant Escherichia coli across the food chain may pose a significant threat to public health because those antimicrobials are critically important in human medicine. The impact of the presented data is especially significant concerning Poland’s role as one of the leading food producers in the EU. This work aimed to characterize the genomic contents of cephalosporin-resistant Escherichia coli (n = 36) isolated from retail meat to expand the official AMR monitoring reported by EFSA. The ESBL mechanism was predominant (via bla_CTX-M-1 and bla_SHV-12), with the AmpC-type represented by the bla_CMY-2 variant. The strains harbored multiple resistance genes, mainly conferring resistance to aminoglycosides, sulfonamides, trimethoprim, tetracyclines. In some isolates, virulence factors—including intimin (eae) and its receptor (tir) were detected, indicating significant pathogenic potential. Resistance genes showed a link with IncI1 and IncB/O/K/Z plasmids. Cephalosporinases were particularly linked to ISEc9/ISEc1 (bla_CTX-M-1 and bla_CMY-2). The association of virulence with mobile elements was less common—mostly with IncF plasmids. The analysis of E. coli isolated from retail meat indicates accumulation of ARGs and their association with various mobile genetic elements, thus increasing the potential for the transmission of resistance across the food chain. Full article

Despite the cross-border availability of almost all goods and services online due to global Internet access, the domestic origin of sellers remains significant. This study examines the preferences for domestic versus cross-border goods and services in online purchases in the EU online market from 2020 to 2023. We use quantitative methods including ordinary least squares (OLS), decision trees, and spatial autocorrelation analysis. We find significant effects of currency, language(s), and Internet use on domestic online purchases, while cross-border online purchases are further influenced by prices and urbanization. Our analysis reveals patterns based on the origin of the seller: domestic, intra-EU, or non-EU seller. There is a strong preference for electronic goods and services, regardless of the seller’s origin, while physical goods show a decreasing preference from domestic to intra-EU and non-EU sellers. Limited geographical effects and spatial patterns in online retailing were found, with a trend towards domestic localization. These differences in e-commerce by seller origin are primarily driven by country-specific characteristics (language(s), currencies) rather than geographic distance. The variation in the purchase of goods and services also depends on their physical and electronic form, that is, digital ordering and/or digital delivery. The expansion of e-commerce and the importance of country-specific characteristics require the development of standards to measure these influences. Full article

This study examined retailers’ sourcing strategies for clothing made from recycled textile materials in the five largest European clothing retail markets (i.e., the UK, Italy, France, Germany, and Spain), given the increasing availability of such products. The multivariate analysis of variance (MANOVA) was conducted based on the detailed country of origin and product assortment information of thousands of such clothing items for sale in these five EU countries from January 2021 to May 2023. The results show that EU retailers sourced clothing using recycled textile materials diversely from over 40 developing and developed countries across Asia, America, Europe, and Africa. The geographic location of supplying countries statistically affects the detailed assortment of recycled clothing that EU retailers import. However, apart from assortment diversity, no statistical evidence indicates that developing countries had advantages over developed ones regarding product sophistication, replenishment frequency, and pricing in the five EU markets. The study’s findings offer new insights into the business aspects of recycled clothing and reveal promising global sourcing opportunities for such products. The results also imply a potentially significant shift in global apparel trade patterns as retailers embrace fashion circularity and expand sourcing clothing made from recycled textile materials. Full article