Institutional Repository of Academic Research University of Macedonia
Not a member yet
2215 research outputs found
Sort by
Decomposition and aggregation of tone efficiencies
No full textIn this paper we investigate the decomposition and aggregation of cost efficiencies when input prices vary across decision-making units. In particular, we compare and contrast four alternative decompositions, three of which are compatible with non-homogeneous (in terms of quality) inputs. We also examine the relations among the alternative cost efficiency measures and their components. Our theoretical results indicate that, when input prices vary across decision-making units, the Färe and Grosskopf cost-based efficiency measure is equal to (i) the Tone cost efficiency measure; (ii) the Tone and Tsutsui cost efficiency measure if there is no technical inefficiency; and (iii) the input spending efficiency measure if there is no allocative inefficiency in the sense of Tone. In addition, based on the denominator rule, we derive appropriate weights for aggregating consistently these cost efficiencies and their components across decision-making units. All these provide helpful guidelines for the appropriate applications of these decompositions at both the individual and the aggregate level. We illustrate this by a simple study case for hospitals.11910289
Pre-recruiting HR marketing for new Gen Talent acquisition: the Mediating Role of Word of Mouth
No full texthe purpose of this study is to investigate how, at the pre-recruitment stage, product brand awareness and publicity of a company affect the knowledge of the company's Employer Brand and the intention to apply for a job in this company. Furthermore, it will be investigated whether these associations are strengthened by the mediating effect of the positive Word of Mouth about the company as a desired employer. The Structural Equation Modeling (PLS-SEM) software was used on a sample of 737 students and recently graduates from Greek public universities. Overall, the findings of our research indicate the impact of a company's product/service brand awareness on the formulation of positive comments about the company as an employer. Indeed, product knowledge, when linked to company publicity initiatives and both are leveraged in a general pre-recruiting marketing plan of the HR department, positive Word of Mouth (WOM) commentary is enhanced. The information that job seekers receive from employees' feedback helps them to gain practical and useful details about the work conditions and the opportunities for training and personal development within it. Moreover, through the descriptions of the employee experience in the company the job seekers’ intention to search employment in this particular employer is strengthened.Η μελέτη εξετάζει πώς η προϋπάρχουσα γνώση των προϊόντων μιας εταιρείας και η θετική δημοσιότητά της ενισχύουν την αναγνωρισιμότητα του employer brand και διαμορφώνουν θετικές στάσεις στους νέους υποψηφίους στη φάση της προ-προσέλκυσης. Με δείγμα 737 φοιτητών και νέων αποφοίτων ελληνικών πανεπιστημίων και με χρήση PLS-SEM, τα αποτελέσματα δείχνουν ότι το θετικό Word of Mouth από εργαζόμενους λειτουργεί ως κρίσιμος μεσολαβητικός μηχανισμός, επηρεάζοντας την αντίληψη για τις ευκαιρίες εκπαίδευσης και ανάπτυξης και ενισχύοντας την πρόθεση υποβολής αίτησης. Η μελέτη καταδεικνύει ότι ο συνδυασμός publicity, product brand awareness και θετικού WOM ενισχύει την ελκυστικότητα εργοδοτών για τη νέα γενιά.505511Proceedings of the 19th European Conference on Management Leadership and Governance (ECMLG 2023
Analyzing repositories of OER using web analytics and accessibility tools
No full textOpen Educational Resources (OER) provide learning opportunities for all. Usually, OER and links to OER are curated in Repositories of OER (ROER) for open access and use by anyone, including people with disabilities, at any place at any time. This study analyzes the reputation/ authoritativeness, usage, and accessibility of thirteen popular ROER for teaching and learning using three Web Analytics and five Web Accessibility tools. A high difference among the ROER was observed in almost every metric. Millions of users visit some of these ROER every month and on average stay 2-26 min per visit and view 1.1-8.5 pages per visit. Although in many ROER most of their visitors come from the country where the ROER hosting institute operates, other ROER (such as DOER, MIT OCW, and OpenLearn) have managed to attract visitors from all over the world. In some ROER, their visitors come directly to their website while in a few other ROER visitors are coming after visiting a search engine. Although most ROER are accessible by users with disabilities, the Web Accessibility tools revealed several errors in few ROER. In most ROER, less than one third of the traffic is coming from mobile devices although almost everyone has a mobile phone nowadays. Finally, the study makes suggestions to ROER administrators such as interconnecting their ROER, collaborating, exchanging good practices (such as Commons and MIT OCW), improving their website accessibility and mobile-optimized design, as well as promoting their ROER to libraries, educational institutes, and organizations.2241243125
Assessing teachers' digital competence in primary and secondary education: Applying a new instrument to integrate pedagogical and professional elements for digital education
No full textTeachers' digital competence (DC) is an important condition for the effective application of technology in education. Although several DC tools have been designed, adjustments to digital education and pedagogical or professional components are still scarce. Therefore, this study aims at developing a new instrument for assessing teachers' DC regarding their pedagogical and professional activities in the context of digital school and digital education. The study also examines the teachers' total DC scores and explores the differences between teacher profiles on a sample of 845 teachers in primary and secondary education in Greece. The final instrument comprises 20 items allocated in six components: 1) Teaching preparation; 2) Teaching delivery & students' support; 3) Teaching evaluation & revision; 4) Professional development; 5) School's development; and 6) Innovating education. The PLS-SEM analysis indicated the validity and reliability of the model in respect to its factorial structure, internal consistency, convergence validity, and model fitness. The results revealed DC inefficiency among teachers in Greece. Primary school teachers reported significantly lower scores in Professional development and Teaching delivery & students support. Female teachers reported significantly lower scores in Innovating education and School's development, but they reported higher scores in Professional development. The contribution and practical implications are discussed in the paper.12
Data reduction via multi-label prototype generation
No full textA very common practice to speed up instance based classifiers is to reduce the size of their training set, that is, replace it by a condensing set, hoping that their accuracy will not worsen. This can be achieved by applying a Prototype Selection or Generation algorithm, also referred to as a Data Reduction Technique. Most of these techniques cannot be applied on multi-label problems, where an instance may belong to more than one classes. Reduction through Homogeneous Clustering (RHC) and Reduction by Space Partitioning (RSP3) are parameter-free single-label Prototype Generation algorithms. Both are based on recursive data partitioning procedures that identify homogeneous clusters of training data, which they replace by their representatives. This paper proposes variations of these algorithms for multi-label training datasets. The proposed methods generate multi-label prototypes and inherit all the desirable properties of their single-label versions. They consider clusters that contain instances that share at least one common label as homogeneous clusters. It is shown via an experimental study based on nine multi-label datasets that the proposed algorithms achieve good reduction rates without negatively affecting classification accuracy.5261
Integrated statistical indicators from Scottish linked open government data
No full textOpen Government Data (OGD), including statistical data, such as economic, environmental and social indicators, are data published by the public sector for free reuse. These data have a huge potential when exploited using Machine Learning methods. Linked Data technologies facilitate retrieving integrated statistical indicators by defining and executing SPARQL queries. However, statistical indicators are available in different temporal and spatial granularity levels as well using different units of measurement. This data article describes the integrated statistical indicators that were retrieved from the official Scottish data portal in order to facilitate the exploitation of Machine Learning methods in OGD. Multiple SPARQL queries as well as manual search in the data portal were employed towards this end. The resulted dataset comprises the maximum number of compatible datasets, i.e., datasets with matching temporal and spatial characteristics. In particular, the data include 60 statistical indicators from seven categories such as health and social care, housing, and crime and justice. The indicators refer to the 6,976 "2011 data zones" of Scotland, while the year of reference is 2015. Data are ready to be used by the research community, students, policy makers, and journalists and give rise to plenty of social, business, and research scenarios that can be solved using Machine Learning technologies and methods.4610877
Integrating Augmented Reality, Gamification, and Serious Games in Computer Science Education
No full textThis study aims to evaluate the impact of using augmented reality, gamification, and serious games in computer science education. The study presents the development process of an educational mobile application, describes an experiment that was conducted and involved 117 higher education students, and analyzes the results of a 49-item paper-based questionnaire. In total, 8 research questions were explored. The results of the study revealed that several educational benefits can be yielded when integrating such applications in teaching and learning activities and actively involving students in the design and development process. In particular, the application was assessed as an effective learning tool that could enrich and improve the educational process and create interactive, inclusive, and student-centered learning environments. Its use led mostly to positive effects and experiences while maintaining the negative ones to a minimum and most students expressed positive emotions. Students were able to learn in a more enjoyable and interesting manner, and their motivation, engagement, self-efficacy, and immersion were greatly increased. Students’ innate need for autonomy, competence, and relatedness was satisfactorily met and both their intrinsic and extrinsic learning motivations were triggered. They felt a sense of belonging and cultivated their social skills. The potential of the application to improve students’ knowledge acquisition and academic achievements was also observed. The application also enabled students to improve their computational thinking and critical thinking skills. Therefore, the potential of combining augmented reality, gamification, and serious games to enhance students’ cognitive and social–emotional development was highlighted.13661
Middle‐ and secondary‐school students' STEM career interest and its relationship to gender, grades, and family size in Kazakhstan
No full textDespite pervasive educational efforts, student interest in STEM careers continues to decline in many countries. The present study seeks to better understand this phenomenon by examining how internal factors (gender) and external factors (school grades, grade level, family size) relate to Kazakh students' STEM career interests. To this end, a newly developed instrument (STEM Career Interest Survey) based on social cognitive career theory was used to assess interest in STEM careers among middle‐ and secondary students in Kazakhstan. The survey was completed by a sample of 396 Kazakh students in grades 7 to 12. Our statistical analyses revealed that (1) female students were generally less interested in STEM careers than male students; (2) students with higher grades in physics classes were significantly more interested in STEM careers than low‐performing students; (3) students at higher grade levels were generally more interested in STEM careers than those in lower grade levels; (4) the number of siblings was positively associated with student interest in mathematics careers; and, (5) family support and role models were significantly correlated with student STEM career interest. Our findings suggest that student development of interest in STEM careers constitutes an epigenetic phenomenon that involves complex interactions between internal factors (e.g., self‐efficacy) and external factors (e.g., gender stereotypes). Based on this, it is argued that the promotion of student interest in STEM careers is a multifaceted problem whose resolution requires, among other things, dispelling stereotypes in students' sociocultural context through systematic renegotiation of traditional gender-technology relations characteristic of a country's culture.107240142
On the use of Chatbots and Knowledge Graphs for Public Service information provision based on Life Events: The case of Travelling Abroad
No full textCitizens during different stages of their lives seek information about Public Services (PS)related to life events. To accommodate this need, the public sector provides PS informationaround life events, such as getting married or travelling abroad. This information is oftenprovided through structured web pages and web-based dialogue systems. However, chatbotsand knowledge graphs are two technologies that can be also used for the same purpose due totheir advantages. The aim of this paper is to investigate chatbots-knowledge graphs integrationfor PS information provision based on life events. For this reason, we develop and evaluate aproof-of-concept chatbot-knowledge graph integration based on CPSV-AP for PS informationrelated to the "Travel Abroad" life event.3449Proceedings EGOV-CeDEM-EPart 2023, September 05-07, Corvinus University of Budapest, Hungar
Towards a Fitting Representation Method for Redesign Evaluation and Cost-Based Optimization
No full textThe prospect of continuously modifying and improving the various business operations played a central role in the evolution of the concept of business processes (BPs). As a consequence, Business Process Redesign (BPR) emerged as a vital practice in the Business Process Management (BPM) discipline and is embodied in most BPM lifecycle models. So far, only a few BPR initiatives investigate how the improvement process can be methodically supported and what is also overlooked is the a priori evaluation of BPR impact. In this paper the authors present the representation phase of the Business Process Redesign Capacity Assessment (BP-RCA) framework and how this phase is formulated for a cost-based optimization technique. In this context, the authors elaborate on a fitting representation method that combines the established Business Process Model and Notation (BPMN2.0) standard and an adapted graph-based structure, initially designed for agent concepts. The method incorporates: (a) the necessary elements for capturing the execution logic, (b) the information for measuring performance and (c) the model constraints that affect redesign. Through applying the representation method to BP models from literature, the authors intend to showcase its usability and the fact that it is amenable to cost-based optimization techniques. By applying the representation, a practitioner is assisted towards a more straightforward calculation of complexity metrics that indicate the applicability of BPR. In this sense, the application of the proposed method is a fundamental feature of the BP-RCA and is essential for redesign decision making at an earlier-than-runtime stage.2937Operational Research in the Era of Digital Transformation and Business Analytic