Institutional Repository of Academic Research University of Macedonia
Not a member yet
2215 research outputs found
Sort by
Cross-Efficiency aggregation based on the denominator rule
No full textIn this paper we propose an alternative cross-efficiency aggregation scheme that is based on the theory underlying the aggregation of self-appraisal efficiency scores. For this purpose, we apply the denominator rule to aggregate the cross-efficiency scores obtained from the multiplier form of the DEA model. This results in a share-weighted average cross-efficiency that takes explicitly into account the relative importance of each element of the cross efficiency matrix by means of either the opportunity cost of resources used or the value of outputs produced, depending upon the orientation chosen to measure efficiency. It turns out that the proposed share-weighting average cross-efficiency uses the simple arithmetic average of the estimated input and output weights from the self-appraisal form of the DEA model to compute the ultimate cross-efficiency. As this is a set of common (across decision-making units) input and output weights, it allows for complete ranking and comparison of all (efficient and inefficient) decision-making units.23812191
Educators’ Ability to Use Augmented Reality (AR) for Teaching Based on the TARC Framework: Evidence from an International Study
No full textAugmented Reality (AR) can enhance learning experience by offering various benefits to learners. However, its integration in classroom practice remains challenging and one reason of this is the lack of teachers’ AR competences. The Teachers’ AR Competences (TARC) framework defines the main AR competences that educators should have in order to successfully employ AR in their teaching: Creating, Using and Managing AR resources. The current study, building upon the TARC framework, aims to examine the effect of the TARC components of Creation and Management to the educators’ ability to Use AR in class. It is the first study that investigates the impact of the educators’ AR competences on their ability to use AR in classes. Moreover, while studies for primary and secondary teachers’ AR skills exist, this is the first study that explores also university lecturers’/professors’ ability to use AR in classes. A survey was conducted with 150 educators around the globe. Regression analysis revealed that the Creation and the Management competences significantly predict university lecturers’/professors’ and primary/secondary school teachers’ ability to Use AR in their classes. Study findings deemed important for educators and education administration and implications are discussed.936 LNNS6977Smart Mobile Communication & Artificial Intelligenc
The effect of organizational culture and leadership on performance: A case of a subsidiary in Colombia
No full textThis study aims to determine the level of culture of a new subsidiary of a company in Colombia and define strategies to increase the level of culture in a way that promotes the organization in this region. Following the organizational culture theories, the Organizational Culture Assessment Instrument was used to measure the aspects of organizational culture. The transfer and adoption of culture are achieved through knowledge sharing within and across the departments and units of large organizations. The comparison between the current and desired state of culture shows a gap in the clan culture, as the company wishes to establish a working environment that promotes teamwork and employee participation, creates confidence, and provides opportunities for professional development. Executives can measure the strength of organizational culture with the aim of updating, strengthening, or modifying the existing culture to improve performance and gain sustainability.49211513
Display advertising: the role of context and advertising appeals from a resistance perspective
No full textPurposeThis research aims to investigate the role of consumer resistance (CR), display advertising context, appeal and type of exposure for the successful launch of a brand into a new market.Design/methodology/approachTo accomplish this goal, two experiments manipulated the digital context of advertising (congruent vs. incongruent), the advertising appeal (emotional vs. informative) and the type of exposure (incidental vs. forced) using an energy drink brand. In Study 1, data were collected from 80 participants using eye-tracking and an online questionnaire. In Study 2, a total of 138 participants visited a website with the targeted display ad and responded to an online questionnaire.FindingsOverall, the results of two studies show that the relationship between CR and display advertising effectiveness is moderated by the advertising context and advertising appeal in incidental exposure, whereas only the advertising context moderates this relationship in forced exposure when launching a brand into a new market. Moreover, the study illustrates the importance of collecting subjective and objective data in advancing the knowledge and understanding of interactive marketing communications such as display advertising.Originality/valueThe study is a novel attempt within the well-established realm of interactive marketing and, specifically, of digital advertising to examine the persuasive effects of display ad features such as the context, appeal and exposure on display ad effectiveness, considering consumers' predispositions such as resistance to change.18219821
On Implementing Social Community Clouds Based on Markov Models
No full textSocial networks reflect, to a wide extent, the real-world relationships that allow users to connect and share information. The number of people that interact in social networks keeps increasing, and the devices used are equipped with more and more computational capacities. This gives rise to the formulation of social clouds, which refer to resource-sharing infrastructures that enable friends to share their resources within the social network. As modern applications become more and more sophisticated, users should be able to share their own services and computing resources through social networks. This poses many challenges for the design options of a computing system composed of a set of trusted friends. The spotlight turns on the design of a proper trust model that considers the suitability of the trusted users to execute an application’s tasks and on the fair distribution of these tasks among these users. Therefore, social networks and their trust-based applications in a distributed environment have seen increasing attention in the research community. In this regard, we present a social community cloud implementation model, where friendly relationships determine resource provisioning. The issues of fairness and allocation of time are of great importance and they are thoroughly investigated. We use extensive simulations to illustrate that the communities can be employed to construct cloud infrastructures, such that the shared resources can be utilized fairly and efficiently. Our experiments have shown that our model achieves a higher allocation rate (percentage of tasks successfully allocated and completed) than competitive models and reduces the average response time and the total execution time. Finally, our work does not overutilize the resources.1118910
Advanced Algorithms for the Reclaimer Scheduling Problem with Sequence-Dependent Setup Times and Availability Constraints
No full textScheduling of reclaimers activities in dry bulk terminals significantly impact terminal throughput, a crucial performance indicator for such facilities. This study addresses the Reclaimer Scheduling Problem (RSP) while considering periodic preventive maintenance activities for reclaimers. These machines are integral for reclaiming dry bulk materials stored in stockyards, facilitating their loading onto vessels via ship-loaders. The primary aim of the objective function entails the minimization of the overall completion time, commonly referred to as the makespan. Since this problem is
NP-hard, we propose a novel greedy constructive heuristic. The solutions obtained from this heuristic serve as the starting point for an efficient General Variable Neighborhood Search (GVNS) algorithm to handle medium-scale instances resembling real stockyard configurations. Computational experiments are conducted by comparing the proposed methods across various problem instances. The results demonstrate that the developed GVNS, coupled with the constructive heuristic for initial solution finding, efficiently improves scheduling efficacy. Thus, it emerges as a new state-of-the-art algorithm for this problem.1475329130
Exploring the Dynamic Behavior of Crude Oil Prices in Times of Crisis: Quantifying the Aftershock Sequence of the COVID-19 Pandemic
No full textCrude oil prices crashed and dropped into negative territory at the onset of the COVID-19 pandemic. This extreme event triggered a series of great-magnitude aftershocks. We seek to investigate the cascading dynamics and the characteristics of the series immediately following the oil market crash. Utilizing a robust method named the Omori law, we quantify the correlations of these events. This research presents empirical regularity concerning the number of times that the absolute value of the percentage change in the oil index exceeds a given threshold value. During the COVID-19 crisis, the West Texas Intermediate (WTI) oil prices exhibit greater volatility compared to the Brent oil prices, with higher relaxation values at all threshold levels. This indicates that larger aftershocks decay more rapidly, and the period of turbulence for the WTI is shorter than that of Brent and the stock market indices. We also demonstrate that the power law’s exponent value increases with the threshold value’s magnitude. By proposing this alternative method of modeling extreme events, we add to the current body of literature, and the findings demonstrate its practical use for decision-making authorities—particularly financial traders who model high-volatility products like derivatives.12172743275
Reduction Through Homogeneous Clustering: Variations for Categorical Data and Fast Data Reduction
No full textReduction through Homogeneous Clustering (RHC) and its editing variant (ERHC) represent effective methods for reducing data in the context of instance-based classification. Both RHC and ERHC are based on an iterative k-means clustering procedure that builds homogeneous clusters. Therefore, they are inappropriate for data reduction tasks that need to be performed quickly, especially, when run over large training datasets. Moreover, since they are based on k-means clustering, they are inappropriate for categorical data. This paper introduces a set of variations to the RHC and ERHC algorithms. More specifically, addressing the iterative nature of k-means clustering in RHC and ERHC, we present new adaptations known as RHC2 and ERHC2. These variations strategically replace the complete execution of k-means clustering with a streamlined task, demonstrating significant improvements in speed. Additionally, we extend the scope of our study to address categorical data by introducing new variations of RHC and ERHC. The adaptations designed for handling categorical data are denoted as RHCM and ERHCM and are based on k-modes clustering. Our experimental study spans diverse datasets and includes statistical tests. The findings reveal a notable performance improvement in execution time for adaptations we propose compared to RHC, ERHC and two other prominent data reduction techniques. Moreover, RHC2 and ERHC2 are found to outperform their predecessors in data reduction effectiveness. Concerning RHCM and ERHCM, performance evaluations conducted on various categorical datasets indicate that these variations efficiently minimize the dataset size, with a relatively modest compromise in accuracy.5667
UK Foreign Direct Investment in uncertain economic times
No full textThis paper uses time-varying Bayesian models to assess the impact of the shifting, and progressively more volatile (especially since the EU Referendum vote in 2016) macroeconomic landscape on Foreign Direct Investment (FDI) inflows to the UK. FDI inflows are depressed in response to higher UK-specific economic and geopolitical uncertainty. A stronger real exchange rate and a higher interest rate also have a negative effect. It benefits from lower UK corporate tax rates and higher US uncertainty, the latter creating investment opportunities in the UK. Rising economic policy uncertainty since the EU Referendum, has led to FDI losses of up to 0.5% of GDP.14710313
Gender equality in science, technology, engineering and mathematics: industrial vis-a-vis academic perspective
No full textThe aim of this study is to present the findings of a qualitative study aiming at capturing key stakeholders’ perceptions with regard to: (a) gender equality in academia and the workplace; (b) challenges, needs, and experiences in academia and workplace with regard to gender. This research captures the current situation of gender equality in the fields of Science, Technology, Engineering and Mathematics (STEM) and provides a deep understanding of the needs, challenges and experiences both men and women encounter in academia vis-a-vis the industry. Forty-one interviews were conducted in Cyprus, Greece, Italy, Slovenia, and Spain. Data collected demonstrate a variety of challenges faced by all genders in the workplace and in academia, as well as the need for more concrete actions that will allow for a gender-balanced perspective to be heard in the STEM fields. Implications for practitioners, policymakers and researchers are also provided.3