Institutional Repository of Academic Research University of Macedonia
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2215 research outputs found
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Environmental dynamism and sustainability: the mediating role of innovation, strategic flexibility and HR development
No full textPurpose: The purpose of this paper is to examine whether environmental dynamism can drive firms to adopt sustainability, taking into consideration the mediating role of the innovation process, strategic flexibility and human resource development in this relationship. Design/methodology/approach: The proposed framework is tested by confirmatory factor analysis and finally structural equation modeling (SEM) using the survey data from 513 Greek firms. Findings: The results show that environmental dynamism drives firms to sustainability, but the introduction of innovation process, strategic flexibility and human resource development fully mediate the effect of this relationship. Research limitations/implications: This study explores three organizational factors. In future research it would be very interesting to explore other topics that affect sustainability. Moreover, it might be useful for researchers to examine firms' digital capability and ambidextrous sustainability. Practical implications: This study offers clear implications for managers, proving that innovation process, strategic flexibility and human resource development are critical factors in achieving sustainability. Originality/value: This empirical study determines the contribution of environmental dynamism to sustainability taking into consideration the role of three critical organizational factors as mediators in this relationship.6161697171
The impact of mutual funds’ ESG scores on their financial performance during the COVID-19 pandemic. A data envelopment analysis
No full textPurpose: The purpose of this study is to evaluate the performance of mutual funds during the COVID-19 pandemic with environmental, social and governance (ESG) criteria. The main research question is whether mutual fund performance differs with respect to the level of the mutual fund’s ESG score. Design/methodology/approach: The data set contains global fund data, and mutual fund performance is analyzed using two types of data envelopment analysis (DEA) models: the DEA portfolio index (DPEI) and the range direction measure (RDM) DEA. Propensity score matching and logistic regression are also applied. Findings: The results reveal that: nonequity mutual funds present significantly higher performance compared to the performance of equity mutual funds; mutual funds with high ESG scores are associated with significantly higher performance compared to those with low to medium ESG scores; funds with high ESG scores experience higher performance irrespective of their type; and efficiency scores derived from the RDM DEA are significantly higher than those derived from the DPEI model. Research limitations/implications: Investors, fund managers and market participants can benefit from the findings of this study and improve their investment decision-making process, including more sustainable funds in their portfolios. Regulators and policymakers should further promote or even require the inclusion of more sustainable investments in the financial products offered by institutional investors. The main limitation of the study is related to data availability regarding the ESG score of mutual funds. Originality/value: To the best of the authors’ knowledge, this is the first study that provides robust evidence in support of a positive association between ESG scores and mutual fund performance during the pandemic-induced crisis applying a DEA methodology.2371457148
IoT-Based Big Data Secure Transmission and Management over Cloud System: A Healthcare Digital Twin Scenario
No full textThe Internet of Things (IoT) was introduced as a recently developed technology in the telecommunications field. It is a network made up of real-world objects, things, and gadgets that are enabled by sensors and software that can communicate data with one another. Systems for monitoring gather, exchange, and process video and image data captured by sensors and cameras across a network. Furthermore, the novel concept of Digital Twin offers new opportunities so that new proposed systems can work virtually, but without differing in operation from a “real” system. This paper is a meticulous survey of the IoT and monitoring systems to illustrate how their combination will improve certain types of the Monitoring systems of Healthcare–IoT in the Cloud. To achieve this goal, we discuss the characteristics of the IoT that improve the use of the types of monitoring systems over a Multimedia Transmission System in the Cloud. The paper also discusses some technical challenges of Multimedia in IoT, based on Healthcare data. Finally, it shows how the Mobile Cloud Computing (MCC) technology, settled as base technology, enhances the functionality of the IoT and has an impact on various types of monitoring technology, and also it proposes an algorithm approach to transmitting and processing video/image data through a Cloud-based Monitoring system. To gather pertinent data about the validity of our proposal in a more safe and useful way, we have implemented our proposal in a Digital Twin scenario of a Smart Healthcare system. The operation of the suggested scenario as a Digital Twin scenario offers a more sustainable and energy-efficient system and experimental findings ultimately demonstrate that the proposed system is more reliable and secure. Experimental results show the impact of our proposed model depicts the efficiency of the usage of a Cloud Management System operated over a Digital Twin scenario, using real-time large-scale data produced from the connected IoT system. Through these scenarios, we can observe that our proposal remains the best choice regardless of the time difference or energy load.1316916
Analysing inefficiency in a non-parametric spatial-dynamic by-production framework: A k-nearest neighbour proposal
No full textThis paper accounts for spatial effects by benchmarking farms against their k-nearest neighbours (KNN) and measuring their inefficiency in a non-parametric dynamic by-production setting. The optimal number of neighbours (Formula presented.) against which farms are compared corresponds to the value of (Formula presented.) that maximises the Moran I test for spatial autocorrelation of the good and the bad output of the farms' two sub-technologies. The inefficiency scores for farms' good output, variable inputs, investments and bad outputs are then computed and compared with those calculated based on a global technology, which benchmarks all farms together. The application focuses on an unbalanced panel of specialised Dutch dairy farms over the period 2009–2016 that contains information on their exact geographical locations. The results suggest that the inefficiency scores exhibit statistically significant differences between the KNN and the global model. Specifically, the inefficiencies are generally deflated when a KNN technology is considered, suggesting that ignoring spatial effects can overestimate inefficiency.74259160
Information Systems Strategy and Security Policy: A Conceptual Framework
No full textAs technology evolves, businesses face new threats and opportunities in the areas of information and information assets. These areas include information creation, refining, storage, and dissemination. Governments and other organizations around the world have begun prioritizing the protection of cyberspace as a pressing international issue, prompting a renewed emphasis on information security strategy development and implementation. While every nation’s information security strategy is crucial, there has not been much work conducted to define a method for gauging national cybersecurity attitudes that takes into account factors and indicators that are specific to that nation. In order to develop a framework that incorporates issues based on the current research in this area, this paper will examine the fundamentals of the information security strategy and the factors that affect its integration. This paper contributes by providing a model based on the ITU cybersecurity decisions, with the goal of developing a roadmap for the successful development and implementation of the National Cybersecurity Strategy in Greece, as well as identifying the factors at the national level that may be aligned with a country’s cybersecurity level.12238
A Low-Cost Gamified Urban Planning Methodology Enhanced with Co-Creation and Participatory Approaches
No full textTargeted nature-based small-scale interventions is an approach commonly adopted by urban developers. The public acceptance of their implementation could be improved by participation, emphasizing residents or shopkeepers located close to the areas of interest. In this work, we propose a methodology that combines 3D technology, based on open data sources, user-generated content, 3D software and game engines for both minimizing the time and cost of the whole planning process and enhancing citizen participation. The proposed schemes are demonstrated in Piraeus (Greece) and Gladsaxe (Denmark). The core findings can be summarized as follows: (a) the time and cost are minimized by using online databases, (b) the gamification of the planning process enhances the decision making process and (c) the interactivity provided by the game engine inspired the participation of non-experts in the planning process (co-creation and co-evaluation), which decentralizes and democratizes the final planning solution.153229
Turkey: From a thriving economic past towards a rugged future? - An empirical analysis on the Turkish financial markets
No full textTurkey had been economically thriving after the end of the economic crisis of 2001. Nonetheless, the recent depreciation of the Turkish lira proved the eventual fragility of the Turkish economy. This research attempts to examine whether the financial markets behavior had forecast this economic collapse. The results support that negative dynamics take place between the nominal exchange rate of Turkish lira and the Turkish stock market index in the long-run. Simultaneously, it is estimated that the uncovered equity parity had been in effect during the last decade but its impact highly deteriorated after March 2018. The Turkish policy makers will sooner or later have to either abandon the low interest rate policy or apply for financial assistance from the IMF.5410099
Performance comparison of physics-based and machine learning assisted multi-fidelity methods for the management of coastal aquifer systems
No full textIn this work we investigate the performance of various lower-fidelity models of seawater intrusion in coastal aquifer management problems. The variable density model is considered as the high-fidelity model and a pumping optimization framework is applied on a hypothetical coastal aquifer system in order to calculate the optimal pumping rates which are used as a benchmark for the lower-fidelity approaches. The examined lower-fidelity models could be classified in two categories: (1) physics-based models, which include several widely used variations of the sharp-interface approximation and (2) machine learning assisted models, which aim to improve the efficiency of the SI approach. The Random Forest method was utilized to create a spatially adaptive correction factor for the original sharp-interface model, which improves its accuracy without compromising its efficiency as a lower-fidelity model. Both the original sharp-interface and Machine Learning assisted model are then tested in a single-fidelity optimization method. The optimal pumping rated which were calculated using the Machine Learning based SI model sufficiently approximate the solution from the variable density model. The Machine Learning assisted approximation seems to be a promising surrogate for the high-fidelity, variable density model and could be utilized in multi-fidelity groundwater management frameworks.
Educational Story-Based Game for Capturing the Learner's Personality
No full textIn recent years with the help of digital games there is an increasing interest in creating Serious Games for learning through play. With the help of machine learning algorithms, an educational serious game can be used, not only to assist the learner in his/her studies, but also to extract insights about the learner's personality. In game-based learning we take into account that the student behaves differently according to his/her individual characteristics while learning by playing. The most used method to model the learner's personality is the self-report using questionnaires. The drawback of this approach is that the learner may not assess himself correctly or his/her answers' may be biased towards the more socially acceptable responses rather than being truthful. In this paper, we explore the idea of having an alternative method of learning a person's personality model and thus to better create interactive and engaging methods to assist learners in their studies. A story-based game with gamified learning elements was created for helping the learners study and evaluate their knowledge in the programming language C. The students learn by evaluating code snippets and depending on their response the game would give constructive feedback. At the same time students' in-game behavior is captured and thus their personality traits could be determined. For modeling the learner's personality we used the Five-Factor Model (OCEAN), a taxonomy of five personality traits (Openness, Conscientiousness, Extraversion, Agreeableness, and Neuroticism), each of which combines many personality characteristics. To evaluate the efficiency of the proposed serious game, we gathered data from 107 first year Computer Science students from the University of Macedonia. The students played the game and filled in the Big Five Inventory (BFI) questionnaire to capture their OCEAN traits. The BFI questionnaire was used as a ground truth. After the data gathering, we used machine learning techniques and also classification algorithms to create our model. The goodness of the model was assessed using different metrics and the results showed that it is effective to model both the extraversion and openness personality dimensions using serious games instead of questionnaires.17693699Proceedings of the 17th European Conference on Games Based Learnin
Aggregating faculty members’ research effectiveness to the department or university level: Exact versus approximate solutions
No full textUsing the Benefit-of-the-Doubt (BoD) model, we estimate research effectiveness at the university level based on the research effectiveness scores of its faculty members with three different set of aggregation weights: an exact and two approximates. Our empirical results for the university of Macedonia, Greece indicate that both set of approximate weights tend to overestimate considerably the research effectiveness at the university level as the faculty level research effectiveness scores are highly positively correlated with both set of the approximate aggregation weights.9010174