This study presents a blockchain-based traceability system designed specifically for the olive oil supply chain, addressing key challenges in transparency, quality assurance, and fraud prevention. The system integrates Internet of Things (IoT) technology with a decentralized blockchain framework to provide real-time monitoring of critical quality metrics. A practical web application, linked to the Ethereum blockchain, enables stakeholders to track each stage of the supply chain via tamper-proof records. Key functionalities include smart contracts that automate quality checks, ensuring data integrity and providing immediate verification of product authenticity. Initial user feedback highlights the system’s potential to enhance transparency and reduce fraud risks in the olive oil market, supporting consumer trust and regulatory compliance. This approach offers a scalable solution adaptable to other high-value agricultural products, demonstrating the blockchain’s transformative potential for secure and transparent food traceability.

The outstanding growth in digital technologies has raised higher education teachers’ attention towards developing digital competences for effectively fulfilling students’ learning requirements and keeping up with the rapidly evolving global education system. Nowadays, higher education teachers can find a plethora of online courses provided by educational organizations, universities, and businesses for reskilling and upskilling. The objective of this paper is to provide results from the assessment of existing massive open online courses regarding their potential to cover a large range of digital competences that higher education teachers should possess. A total of one hundred and sixty-two (162) online courses from three prominent international digital platforms, offering massive open online courses, were subjected to evaluation using a model incorporating six categories of attributes aligned with pertinent digital competences. The results indicate that the majority of the existing online courses lack sufficient coverage of key digital competences required by higher education teachers. Notably, these inadequately addressed competences regard evaluating students’ performance in the digital environment and ensuring positive online student experiences through collaborative engagement and self-reflection. The findings of this study offer valuable insights not only to higher education teachers, but also to online course developers and education policy-makers. The identified gaps in digital competences underscore the pressing need for substantial improvements in existing online courses or the development of new courses to effectively bridge these competence gaps. By addressing these shortcomings, higher education institutions can better equip their teachers to navigate the digital realm and elevate the overall quality of education in the digital era.

In recent years, wineries have incorporated social media into their marketing strategies to promote their products and services. They offer wineries the opportunity to interact with their customers in real time, allowing them to share their experiences, preferences, and feelings, and create a sense of community. The objective of this paper is to investigate digital presence and consumer engagement and reactions in social media used by the Greek winery industry, using a three-step methodology. The study focuses specifically on Facebook and Instagram and compares data for the period between 2019 and 2022, including the COVID-19 outbreak, collected from the profiles of 311 Greek wineries using a social media analytics tool. The contribution of this work lies in demonstrating the change in consumers’ engagement and reactions witnessed on wineries’ profiles. The outcomes indicate consistently limited interactions on these profiles, reflecting low levels of consumer engagement and overall reactions across social media platforms. These findings underscore the necessity for additional research into wineries’ marketing strategies and the motivations driving user engagement. The proposed methodology can be used as a social media brand engagement approach that aids brands in attracting audience attention and fostering active participation in various business sectors.

This paper explores the application of Blockchain technology in food traceability, focusing specifically on olive oil. It addresses the significant challenges in the food industry, such as verifying authenticity and detecting harmful substances. The research highlights the potential of Blockchain to enhance traceability by leveraging its decentralized and secure architecture, which en-sures data integrity and facilitates rapid monitoring throughout the supply chain. The paper also examines the synergy between Blockchain and the Internet of Things (IoT), which is critical for real-time tracking in product production. The research conducted has led to a practical demonstration through a web application connected to the Ethereum test network, designed for the quality control of olive oil via smart contracts. Overall, this study provides a comprehensive analysis of Blockchain technology and its transformative potential in ensuring food traceability, particularly for high-value commodities like olive oil.

The unprecedented production and sharing of data, opinions, and comments among people on social media and the Internet in general has highlighted sentiment analysis (SA) as a key machine learning approach in scientific and market research. Sentiment analysis can extract sentiments and opinions from user-generated text, providing useful evidence for new product decision-making and effective customer relationship management. However, there are concerns about existing standard sentiment analysis tools regarding the generation of inaccurate sentiment classification results. The objective of this paper is to determine the efficiency of off-the-shelf sentiment analysis APIs in recognizing low-resource languages, such as Greek. Specifically, we examined whether sentiment analysis performed on 300 online ordering customer reviews using the Meaning Cloud web-based tool produced meaningful results with high accuracy. According to the results of this study, we found low agreement between the web-based and the actual raters in the food delivery services related data. However, the low accuracy of the results highlights the need for specialized sentiment analysis tools capable of recognizing only one low-resource language. Finally, the results highlight the necessity of developing specialized lexicons tailored not only to a specific language but also to a particular field, such as a specific type of restaurant or shop.