Δημοσιεύσεις

@article{lessi2019christina,

title = {Christina Lessi (Editor),“D2. 1 Use Case Description and Scenario Analysis,” 5G-HEART Project, Deliverable D2. 1.},

author = {Christina Lessi and Tilemachos Doukoglou and Velissarios Gezerlis and Panayiotis Verrios and Andonis Georgiou and Konstantinos Tzalas and Maria Diamanti and Grigoris Kakkavas and Adamantia Stamou and Vasileios Karyotis and others},

year  = {2019},

date = {2019-01-01},

publisher = {CORDIS-European Commission},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Karyotis2019551,

title = {A Markov Random Field Framework for Modeling Malware Propagation in Complex Communications Networks},

author = {V. Karyotis},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068941002&doi=10.1109%2fTDSC.2017.2703622&partnerID=40&md5=2eaddbe72ca542b6f71f846ca8250533},

doi = {10.1109/TDSC.2017.2703622},

issn = {15455971},

year  = {2019},

date = {2019-01-01},

journal = {IEEE Transactions on Dependable and Secure Computing},

volume = {16},

number = {4},

pages = {551-564},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {The proliferation of complex communication networks (CCNs) and their importance for maintaining social coherency nowadays have urgently elevated the need for protecting networking infrastructures from malicious software attacks. In this paper, we propose a Markov Random Field (MRF) based spatio-stochastic framework for modeling the macroscopic behavior of a CCN under random attack, where malicious threats propagate through direct interactions and follow the Susceptible-Infected-Susceptible infection paradigm. We exploit the MRF framework for analytically studying the propagation dynamics in various types of CCNs, i.e., lattice, random, scale-free, small-world and multihop graphs, in a holistic manner. By combining Gibbs sampling with simulated annealing, we study the behavior of the above systems for various topological and malware related parameters with respect to the general random attacks considered. We demonstrate the effectiveness of the MRF framework in capturing the evolution of SIS malware propagation and use it to assess the robustness of synthetic and real CCNs with respect to the involved parameters. It is found that random networks are more robust, followed by scale-free, regular and small-world, while multihop emerge as the most vulnerable of all. © 2004-2012 IEEE.},

note = {cited By 10},

keywords = {Complex networks; Image segmentation; Magnetorheological fluids; Markov processes; Simulated annealing; Stochastic systems; Structural frames, Gibbs sampling; Malware propagation; Markov Random Fields; Network robustness; Network science, Malware},

pubstate = {published},

tppubtype = {article}

}

@article{Vitoropoulou2019604,

title = {Sensing and monitoring of information diffusion in complex online social networks},

author = {M. Vitoropoulou and V. Karyotis and S. Papavassiliou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85054326149&doi=10.1007%2fs12083-018-0684-7&partnerID=40&md5=390e817a3dd9238e84b5acc810114175},

doi = {10.1007/s12083-018-0684-7},

issn = {19366442},

year  = {2019},

date = {2019-01-01},

journal = {Peer-to-Peer Networking and Applications},

volume = {12},

number = {3},

pages = {604-619},

publisher = {Springer New York LLC},

abstract = {Sensing and monitoring information diffusion in online social networks is a complex problem of prominent importance, typically requiring significant sensing resources to address it properly. In this paper, we propose an inference approach for an information diffusion process where information is considered to belong to different classes, characterized by different spreading dynamics and possibly different topical content. Our framework utilizes social network analysis metrics in order to reduce the sensing resources that would be required in an otherwise exhaustive approach, while employing statistical learning and probabilistic inference for maintaining the accuracy of information tracking, whenever needed. The proposed framework defines an edge coloring scheme, based on which it is possible to keep track of information diffusion. We assume that the latter spreads according to various biased random walks that represent the dynamics of the considered classes of information. We have employed learning for the inference of those cases where backtracking leads to multiple potential choices for information paths. We demonstrate the operation and efficacy of our approach in characteristic online social networks, such as distributed wireless (spatial) and scale-free (relational) topologies, and draw conclusions on the impact of topology on information spreading. Finally, we discuss the emerging trends applicable for each topology and provide broader guidelines on the suitability of the proposed information diffusion inference scheme for each network. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.},

note = {cited By 6},

keywords = {Biased random walk; Information diffusion; Information sensing; Network Monitoring; On-line social networks, Complex networks; Random processes; Topology, Social networking (online)},

pubstate = {published},

tppubtype = {article}

}

@article{Stamou2019,

title = {Autonomic Network Management and cross-layer optimization in Software Defined radio environments},

author = {A. Stamou and G. Kakkavas and K. Tsitseklis and V. Karyotis and S. Papavassiliou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85061190116&doi=10.3390%2ffi11020037&partnerID=40&md5=458dca75a6acc2729e6c5b6043737655},

doi = {10.3390/fi11020037},

issn = {19995903},

year  = {2019},

date = {2019-01-01},

journal = {Future Internet},

volume = {11},

number = {2},

publisher = {MDPI AG},

abstract = {The demand for Autonomic Network Management (ANM) and optimization is as intense as ever, even though significant research has been devoted towards this direction. This paper addresses such need in Software Defined (SDR) based Cognitive Radio Networks (CRNs). We propose a new framework forANMand network reconfiguration combining Software Defined Networks (SDN) with SDR via Network Function Virtualization (NFV) enabled Virtual Utility Functions (VUFs). This is the first approach combining ANM with SDR and SDN via NFV, demonstrating how these state-of-the-art technologies can be effectively combined to achieve reconfiguration flexibility, improved performance and efficient use of available resources. In order to show the feasibility of the proposed framework, we implemented its main functionalities in a cross-layer resource allocation mechanism for CRNs over real SDR testbeds provided by the Orchestration and Reconfiguration Control Architecture (ORCA) EU project. We demonstrate the efficacy of our framework, and based on the obtained results, we identify aspects that can be further investigated for improving the applicability and increasing performance of our broader framework. © 2019 by the authors.},

note = {cited By 10},

keywords = {Analog circuits; Cognitive radio; Network function virtualization; Network management; Radio; Radio receivers; Resource allocation; Software defined networking; Testbeds; Transfer functions; Virtual reality, Autonomic network management; Cognitive radio networks (CRNs); Cross layer optimization; Cross layer resource allocations; Network re-configuration; Reconfiguration control; Software-defined radios; State-of-the-art technology, Software radio},

pubstate = {published},

tppubtype = {article}

}

@article{Rey2019,

title = {Mathematical models for malware propagation},

author = {Á. M. D. Rey and L. -X. Yang and V. A. Karyotis},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060084175&doi=10.1155%2f2019%2f6046353&partnerID=40&md5=9219676dc581f3dae9893a149eab04c4},

doi = {10.1155/2019/6046353},

issn = {19390114},

year  = {2019},

date = {2019-01-01},

journal = {Security and Communication Networks},

volume = {2019},

publisher = {Hindawi Limited},

note = {cited By 0},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Pateli2019224,

title = {How functional involvement affects the transformation of external knowledge into innovation outcomes},

author = {A. Pateli and S. Lioukas},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85026368715&doi=10.1111%2fradm.12280&partnerID=40&md5=c78eaad9385faf3f5b3712e650287abc},

doi = {10.1111/radm.12280},

year  = {2019},

date = {2019-01-01},

journal = {R and D Management},

volume = {49},

number = {2},

pages = {224-238},

note = {cited By 16},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kostagiolas2018information,

title = {Information seeking behavioural paths of physicians for diabetes mellitus care: a qualitative comparative analysis of information needs, sources, and barriers},

author = {Petros A Kostagiolas and Panos E Kourouthanassis and Konstantina Martzoukou and Nikolaos Korfiatis and Dimitrios Niakas},

year  = {2018},

date = {2018-01-01},

journal = {Health Systems},

volume = {7},

number = {1},

pages = {13--28},

publisher = {Taylor & Francis},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pappas2018combining,

title = {Combining system success factors with trust to explain e-government adoption using fsQCA},

author = {Ilias Pappas and Panos Kourouthanassis and Patrick Mikalef and Michail Giannakos},

year  = {2018},

date = {2018-01-01},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{stai2018temporal,

title = {Temporal dynamics of information diffusion in twitter: Modeling and experimentation},

author = {Eleni Stai and Eirini Milaiou and Vasileios Karyotis and Symeon Papavassiliou},

year  = {2018},

date = {2018-01-01},

journal = {IEEE Transactions on Computational Social Systems},

volume = {5},

number = {1},

pages = {256--264},

publisher = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{karyotis2018big,

title = {Big data clustering via community detection and hyperbolic network embedding in IoT applications},

author = {Vasileios Karyotis and Konstantinos Tsitseklis and Konstantinos Sotiropoulos and Symeon Papavassiliou},

year  = {2018},

date = {2018-01-01},

journal = {Sensors},

volume = {18},

number = {4},

pages = {1205},

publisher = {MDPI},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Stamolampros20183083,

title = {Exploring the behavioral drivers of review valence: The direct and indirect effects of multiple psychological distances},

author = {P. Stamolampros and N. Korfiatis},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053781813&doi=10.1108%2fIJCHM-04-2017-0239&partnerID=40&md5=3c5477911950017332b4b30d0f5ea67e},

doi = {10.1108/IJCHM-04-2017-0239},

year  = {2018},

date = {2018-01-01},

journal = {International Journal of Contemporary Hospitality Management},

volume = {30},

number = {10},

pages = {3083-3099},

note = {cited By 30},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Chopdar2018109,

title = {Mobile shopping apps adoption and perceived risks: A cross-country perspective utilizing the Unified Theory of Acceptance and Use of Technology},

author = {P. K. Chopdar and N. Korfiatis and V. J. Sivakumar and M. D. Lytras},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85047471379&doi=10.1016%2fj.chb.2018.04.017&partnerID=40&md5=efa14f8ce95ef9855a4132624d441e6a},

doi = {10.1016/j.chb.2018.04.017},

year  = {2018},

date = {2018-01-01},

journal = {Computers in Human Behavior},

volume = {86},

pages = {109-128},

note = {cited By 272},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Huang2018165,

title = {Mobile shopping cart abandonment: The roles of conflicts, ambivalence, and hesitation},

author = {G. -H. Huang and N. Korfiatis and C. -T. Chang},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85039166777&doi=10.1016%2fj.jbusres.2017.12.008&partnerID=40&md5=dcfbaa0e2bb3f69d3568db71931a0ae0},

doi = {10.1016/j.jbusres.2017.12.008},

year  = {2018},

date = {2018-01-01},

journal = {Journal of Business Research},

volume = {85},

pages = {165-174},

note = {cited By 89},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kostagiolas201813,

title = {Information seeking behavioural paths of physicians for diabetes mellitus care: a qualitative comparative analysis of information needs, sources, and barriers},

author = {P. A. Kostagiolas and P. E. Kourouthanassis and K. Martzoukou and N. Korfiatis and D. Niakas},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062670775&doi=10.1080%2f20476965.2017.1390050&partnerID=40&md5=059b70f7e4fdbf73c8f3e70fe44d67a9},

doi = {10.1080/20476965.2017.1390050},

year  = {2018},

date = {2018-01-01},

journal = {Health Systems},

volume = {7},

number = {1},

pages = {13-28},

note = {cited By 15},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Karyotis2018,

title = {Big data clustering via community detection and hyperbolic network embedding in IoT applications},

author = {V. Karyotis and K. Tsitseklis and K. Sotiropoulos and S. Papavassiliou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045428827&doi=10.3390%2fs18041205&partnerID=40&md5=0f53454f4ddc5ba09779ce173c69b61f},

doi = {10.3390/s18041205},

issn = {14248220},

year  = {2018},

date = {2018-01-01},

journal = {Sensors (Switzerland)},

volume = {18},

number = {4},

publisher = {MDPI AG},

abstract = {In this paper, we present a novel data clustering framework for big sensory data produced by IoT applications. Based on a network representation of the relations among multi-dimensional data, data clustering is mapped to node clustering over the produced data graphs. To address the potential very large scale of such datasets/graphs that test the limits of state-of-the-art approaches, we map the problem of data clustering to a community detection one over the corresponding data graphs. Specifically, we propose a novel computational approach for enhancing the traditional Girvan-Newman (GN) community detection algorithm via hyperbolic network embedding. The data dependency graph is embedded in the hyperbolic space via Rigel embedding, allowing more efficient computation of edge-betweenness centrality needed in the GN algorithm. This allows for more efficient clustering of the nodes of the data graph in terms of modularity, without sacrificing considerable accuracy. In order to study the operation of our approach with respect to enhancing GN community detection, we employ various representative types of artificial complex networks, such as scale-free, small-world and random geometric topologies, and frequently-employed benchmark datasets for demonstrating its efficacy in terms of data clustering via community detection. Furthermore, we provide a proof-of-concept evaluation by applying the proposed framework over multi-dimensional datasets obtained from an operational smart-city/building IoT infrastructure provided by the Federated Interoperable Semantic IoT/cloud Testbeds and Applications (FIESTA-IoT) testbed federation. It is shown that the proposed framework can be indeed used for community detection/data clustering and exploited in various other IoT applications, such as performing more energy-efficient smart-city/building sensing. © 2018 by the authors. Licensee MDPI, Basel, Switzerland.},

note = {cited By 9},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Stai2018256,

title = {Temporal Dynamics of Information Diffusion in Twitter: Modeling and Experimentation},

author = {E. Stai and E. Milaiou and V. Karyotis and S. Papavassiliou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85040913521&doi=10.1109%2fTCSS.2017.2784184&partnerID=40&md5=7974b86c93a772693bc3d1ec0fa67f3e},

doi = {10.1109/TCSS.2017.2784184},

issn = {2329924X},

year  = {2018},

date = {2018-01-01},

journal = {IEEE Transactions on Computational Social Systems},

volume = {5},

number = {1},

pages = {256-264},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {Twitter constitutes an accessible platform for studying and experimenting with the dynamics of information dissemination. By exploiting this and using real data, in this paper, we study the temporal dynamics of topic-specific information spread in Twitter, where we assume that each topic corresponds to a hashtag. We develop an epidemic model for information spread in Twitter and we validate it using real data for several hashtags chosen so as to cover a variety of characteristics. Contrary to the existing works in literature, which define the informed Twitter users as those who have produced/reproduced tweets with a specific hashtag, our model considers as informed a superset of Twitter users who have seen/produced/reproduced tweets with a specific hashtag. Thus, it does not underestimate the extent of information propagation in the network. The evaluation results indicate a satisfactory performance of the proposed epidemic model for all hashtag types examined; while more importantly, they allow studying the impact of several factors, such as the need of time-varying infection rates depending on the hashtag type. © 2014 IEEE.},

note = {cited By 40},

keywords = {Adaptation models; Computational model; Epidemic modeling; Hashtags; Infection rates; Information propagation; Tagging; Twitter, Analytical models; Data structures; Dynamics; Epidemiology; Information dissemination; Mathematical models, Social networking (online)},

pubstate = {published},

tppubtype = {article}

}

@article{pappas2017interplay,

title = {The interplay of online shopping motivations and experiential factors on personalized e-commerce: A complexity theory approach},

author = {Ilias O Pappas and Panos E Kourouthanassis and Michail N Giannakos and George Lekakos},

year  = {2017},

date = {2017-01-01},

journal = {Telematics and Informatics},

volume = {34},

number = {5},

pages = {730--742},

publisher = {Pergamon},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{mikalef2017online,

title = {Online information search behaviour of physicians},

author = {Patrick Mikalef and Panos E Kourouthanassis and Adamantia G Pateli},

year  = {2017},

date = {2017-01-01},

journal = {Health Information & Libraries Journal},

volume = {34},

number = {1},

pages = {58--73},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kourouthanassis2017explaining,

title = {Explaining travellers online information satisfaction: A complexity theory approach on information needs, barriers, sources and personal characteristics},

author = {Panos E Kourouthanassis and Patrick Mikalef and Ilias O Pappas and Petros Kostagiolas},

year  = {2017},

date = {2017-01-01},

journal = {Information & Management},

volume = {54},

number = {6},

pages = {814--824},

publisher = {North-Holland},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pappas2017sense,

title = {Sense and sensibility in personalized e-commerce: How emotions rebalance the purchase intentions of persuaded customers},

author = {Ilias O Pappas and Panos E Kourouthanassis and Michail N Giannakos and Vassilios Chrissikopoulos},

year  = {2017},

date = {2017-01-01},

journal = {Psychology & Marketing},

volume = {34},

number = {10},

pages = {972--986},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pappas2017emotions,

title = {Emotions in Motion: The Combined Effect of Positive and Negative Emotions on Personalised E-Commerce},

author = {Ilias O Pappas and Panos E Kourouthanassis and Sofia Papavlasopoulou and Vassilios Chrissikopoulos},

year  = {2017},

date = {2017-01-01},

journal = {International Journal of Online Marketing (IJOM)},

volume = {7},

number = {1},

pages = {64--78},

publisher = {IGI Global},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pappas2017fuzzy,

title = {Fuzzy-set analysis to understand user experience in mobile applications},

author = {Ilias O Pappas and Patrick Mikalef and Panos Kourouthanassis and Michail N Giannakos},

year  = {2017},

date = {2017-01-01},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{stai2017strategy,

title = {Strategy evolution of information diffusion under time-varying user behavior in generalized networks},

author = {Eleni Stai and Vasileios Karyotis and Antonia-Chrysanthi Bitsaki and Symeon Papavassiliou},

year  = {2017},

date = {2017-01-01},

journal = {Computer Communications},

volume = {100},

pages = {91--103},

publisher = {Elsevier},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{stai2017hyperbolic,

title = {Hyperbolic embedding for efficient computation of path centralities and adaptive routing in large-scale complex commodity networks},

author = {Eleni Stai and Konstantinos Sotiropoulos and Vasileios Karyotis and Symeon Papavassiliou},

year  = {2017},

date = {2017-01-01},

journal = {IEEE Transactions on Network Science and Engineering},

volume = {4},

number = {3},

pages = {140--153},

publisher = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{karyotis2017markov,

title = {A Markov random field framework for modeling malware propagation in complex communications networks},

author = {Vasileios Karyotis},

year  = {2017},

date = {2017-01-01},

journal = {IEEE Transactions on Dependable and Secure Computing},

volume = {16},

number = {4},

pages = {551--564},

publisher = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Stai2017140,

title = {Hyperbolic Embedding for Efficient Computation of Path Centralities and Adaptive Routing in Large-Scale Complex Commodity Networks},

author = {E. Stai and K. Sotiropoulos and V. Karyotis and S. Papavassiliou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029930433&doi=10.1109%2fTNSE.2017.2690258&partnerID=40&md5=0a5e420781c16b09d6ecee7b614924c3},

doi = {10.1109/TNSE.2017.2690258},

issn = {23274697},

year  = {2017},

date = {2017-01-01},

journal = {IEEE Transactions on Network Science and Engineering},

volume = {4},

number = {3},

pages = {140-153},

publisher = {IEEE Computer Society},

abstract = {Computing the most central nodes in large-scale commodity networks is rather important for improving routing and associated applications. In this paper, we introduce a novel framework for the analysis and efficient computation of routing path-based centrality measures, focusing on betweenness and traffic load centrality. The proposed framework enables efficient approximation and in special cases accurate computation of the aforementioned measures in large-scale complex networks, as well as improving/adapting commodity (traffic) routing by identifying and alleviating key congestion points. It capitalizes on network embedding in hyperbolic space and exploits properties of greedy routing over hyperbolic coordinates. We show the computational benefits and approximation precision of our approach by comparing it with state-of-the-art path centrality computation techniques. We demonstrate its applicability on real topologies, characteristic of actual large-scale commodity networks, e.g., data, utility networks. Focusing on two graph embedding types, Rigel and greedy, we compare their impact on the performance of our framework. Then, we exemplify and statistically analyze the dynamic routing adaptation, via the variation of the minimum-depth spanning tree employed for greedy embedding in hyperbolic space. Notably, this allows for efficient routing adaptation according to a simple, distributed computation that can be applied during network operation to alleviate arising bottlenecks. © 2013 IEEE.},

note = {cited By 10},

keywords = {Betweenness centrality; Greedy routing; Hyperbolic geometry; Network embedding; rigel embedding; Traffic loads, Complex networks; Computational efficiency; Distributed computer systems; Traffic congestion, Network routing},

pubstate = {published},

tppubtype = {article}

}

@article{Stai201791,

title = {Strategy evolution of information diffusion under time-varying user behavior in generalized networks},

author = {E. Stai and V. Karyotis and A. -C. Bitsaki and S. Papavassiliou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85009355077&doi=10.1016%2fj.comcom.2016.12.013&partnerID=40&md5=2df1b79f484ed668c1646c1607709f69},

doi = {10.1016/j.comcom.2016.12.013},

issn = {01403664},

year  = {2017},

date = {2017-01-01},

journal = {Computer Communications},

volume = {100},

pages = {91-103},

publisher = {Elsevier B.V.},

abstract = {Modern generalized networks, where physical devices and social players are combined to support seamless and more flexible services, are strongly driven by user behavior and its evolution. A typical example of behavior-affected processes is the information diffusion by users in generalized networks. In this paper, we focus on user strategy selection with respect to information diffusion in generalized networks, and study its evolutionary dynamics and their benefits, as user behavior/interests change over the course of time. We model information diffusion in generalized networks through graphical evolutionary game theory (graphical EGT) and analyze the evolution of the system and its Evolutionary Stable States (ESS) for time-varying fitness values due to time-varying user interests. We perform extensive evaluations based on numerical and simulation results, and study the impact of several parameters on the derived ESS curves (i.e., ESS points over time). Such parameters involve user interests and their fitness values, and the degree distributions and network type of the layers of the generalized network. We thoroughly evaluate via numerical analysis and appropriate examples the existence of ESS loci for the system dynamics depending on the associated parameters. Also, we discuss the relation between (graphical) EGT-based information diffusion analysis and the epidemics-based information diffusion modeling and analysis that is frequently applied in the literature. Our modeling and evaluations can be used to predict the evolution of the cumulative behavior, allowing for efficient design and control of information campaigns. © 2016},

note = {cited By 10},

keywords = {Behavioral research; Game theory; Health; Social networking (online), Evolutionary games; Fitness; Generalized networks; Information diffusion; Time varying behavior, Time varying networks},

pubstate = {published},

tppubtype = {article}

}

@article{Mikalef201758,

title = {Online information search behaviour of physicians},

author = {P. Mikalef and P. E. Kourouthanassis and A. G. Pateli},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85012881810&doi=10.1111%2fhir.12170&partnerID=40&md5=ff612ca71c639b29ac30fa0355da89a4},

doi = {10.1111/hir.12170},

year  = {2017},

date = {2017-01-01},

journal = {Health Information and Libraries Journal},

volume = {34},

number = {1},

pages = {58-73},

note = {cited By 31},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Moraitou2017255,

title = {Smart Health Caring Home: A Systematic Review of Smart Home Care for Elders and Chronic Disease Patients},

author = {M. Moraitou and A. Pateli and S. Fotiou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85032387649&doi=10.1007%2f978-3-319-57348-9_22&partnerID=40&md5=36f2b24f23c5cf87a92d4d7be186766e},

doi = {10.1007/978-3-319-57348-9_22},

year  = {2017},

date = {2017-01-01},

journal = {Advances in Experimental Medicine and Biology},

volume = {989},

pages = {255-264},

note = {cited By 19},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Mikalef20171,

title = {Information technology-enabled dynamic capabilities and their indirect effect on competitive performance: Findings from PLS-SEM and fsQCA},

author = {P. Mikalef and A. Pateli},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84994666919&doi=10.1016%2fj.jbusres.2016.09.004&partnerID=40&md5=078cabc7276e40ec1f53f3ca00a75356},

doi = {10.1016/j.jbusres.2016.09.004},

year  = {2017},

date = {2017-01-01},

journal = {Journal of Business Research},

volume = {70},

pages = {1-16},

note = {cited By 607},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{ringas2016effect,

title = {Effect of Urban Computing on the Public’s Perception of Place, Community, and Infrastructure},

author = {Dimitrios Ringas and Eleni Christopoulou},

year  = {2016},

date = {2016-01-01},

journal = {Enriching Urban Spaces with Ambient Computing, the Internet of Things, and Smart City Design},

pages = {145},

publisher = {IGI Global},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pappas2016explaining,

title = {Explaining online shopping behavior with fsQCA: The role of cognitive and affective perceptions},

author = {Ilias O Pappas and Panos E Kourouthanassis and Michail N Giannakos and Vassilios Chrissikopoulos},

year  = {2016},

date = {2016-01-01},

journal = {Journal of Business Research},

volume = {69},

number = {2},

pages = {794--803},

publisher = {Elsevier},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kourouthanassis2016matter,

title = {A matter of trust and emotions: A complexity theory approach to explain the adoption of EGOVERNMENT services},

author = {Panos Kourouthanassis and Ilias O Pappas and Cleopatra Bardaki and Michail Giannakos},

year  = {2016},

date = {2016-01-01},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{stai2016hyperbolic,

title = {A hyperbolic space analytics framework for big network data and their applications},

author = {Eleni Stai and Vasileios Karyotis and Symeon Papavassiliou},

year  = {2016},

date = {2016-01-01},

journal = {IEEE Network},

volume = {30},

number = {1},

pages = {11--17},

publisher = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Lavranos20162105,

title = {Information seeking for musical creativity: A systematic literature review},

author = {C. Lavranos and P. Kostagiolas and N. Korfiatis and J. Papadatos},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84983262153&doi=10.1002%2fasi.23534&partnerID=40&md5=5508e66ddd3320c87981fbf541f2e72e},

doi = {10.1002/asi.23534},

year  = {2016},

date = {2016-01-01},

journal = {Journal of the Association for Information Science and Technology},

volume = {67},

number = {9},

pages = {2105-2117},

note = {cited By 24},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Zicari201617,

title = {Setting Up a Big Data Project: Challenges, Opportunities, Technologies and Optimization},

author = {R. V. Zicari and M. Rosselli and T. Ivanov and N. Korfiatis and K. Tolle and R. Niemann and C. Reichenbach},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85125454798&doi=10.1007%2f978-3-319-30265-2_2&partnerID=40&md5=5819b069329aa9de0b1f8666c9305f5f},

doi = {10.1007/978-3-319-30265-2_2},

year  = {2016},

date = {2016-01-01},

journal = {Studies in Big Data},

volume = {18},

pages = {17-47},

note = {cited By 15},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Karyotis2016227,

title = {On the evolution of complex network topology under network churn},

author = {V. Karyotis and E. Stai and S. Papavassiliou},

editor = {Mamatas L. Matta I. Papadimitriou P.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84978959144&doi=10.1007%2f978-3-319-33936-8_18&partnerID=40&md5=d66eefa06bcaa59521adbf8ba126608e},

doi = {10.1007/978-3-319-33936-8_18},

issn = {03029743},

year  = {2016},

date = {2016-01-01},

journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},

volume = {9674},

pages = {227-240},

publisher = {Springer Verlag},

abstract = {The future Internet is becoming more diverse, incorporating heterogeneous access networks. The latter are characterized by numerous devices that join/leave the network dynamically, creating intense churn patterns. New approaches to analyze and quantify churn-induced network evolution are required. In this paper, we address such need by introducing a new analysis framework that maps network evolution into trajectories in multi-dimensional vector spaces. Each network instance is characterized by a feature vector, indicating network properties of interest. To demonstrate the potentials of this approach, we exemplify and study the effect of edge churn on various complex topologies, frequently emerging in various communications environments. We investigate via simulation the impact of network evolution, by quantifying its effect on key network analysis metrics, such as the clustering coefficient and the plethora of centrality metrics, employed at large for analyzing topologies and designing applications. The proposed framework aspires to establish more holistic and efficient complex network control. © IFIP International Federation for Information Processing 2016.},

note = {cited By 1; Conference of 14th IFIP WG 6.2 International Conference on Wired/Wireless Internet Communications, WWIC 2016 ; Conference Date: 25 May 2016 Through 27 May 2016; Conference Code:176559},

keywords = {Analysis frameworks; Clustering coefficient; Edge churn; Future internet; Heterogeneous access; Multi-dimensional vectors; Network evolution; Network properties, Complex networks, Internet; Topology; Vector spaces},

pubstate = {published},

tppubtype = {article}

}

@article{Stai201611,

title = {A hyperbolic space analytics framework for big network data and their applications},

author = {E. Stai and V. Karyotis and S. Papavassiliou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84962018671&doi=10.1109%2fMNET.2016.7389825&partnerID=40&md5=452d87373227f1a5a381b819787d5630},

doi = {10.1109/MNET.2016.7389825},

issn = {08908044},

year  = {2016},

date = {2016-01-01},

journal = {IEEE Network},

volume = {30},

number = {1},

pages = {11-17},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {Big data analytics have generated a paradigm shift in modern data analysis and decision making in almost every aspect of human society. Nowadays, massive amounts of generated network and correlated (networked) data pose critical computational and storage challenges, requiring the development of radical techniques to manage, process, and analyze them more efficiently. We propose embedding such data and their correlations in hyperbolic metric spaces as one approach aspiring to radically change current practices. In this article, we explore the potential that such data embedding and the corresponding hyperbolic space based data analytics can offer to networks, their applications, and their services. We demonstrate how this approach may lead to more efficient and scalable problem solving within diverse application domains, such as network design/analysis, network resource allocation optimization, and network economics/marketing, paving the way for more diverse and effective solutions in the future. © 2016 IEEE.},

note = {cited By 26},

keywords = {Big data; Data handling; Data reduction; Decision making; Digital storage; Economics; Information analysis; Measurements; Optimization; Problem solving; Resource allocation; Topology, Current practices; Diverse applications; Effective solution; Network economics; Network resource allocations; Network topology; Resource management; Routing, Information management},

pubstate = {published},

tppubtype = {article}

}

@article{ringas2015field,

title = {Field experience and user evaluation from a real-world internet application in an urban-scale environment},

author = {Dimitrios Ringas and Eleni Christopoulou and Michail Stefanidakis},

year  = {2015},

date = {2015-01-01},

journal = {International Journal of Intelligent Engineering Informatics},

volume = {3},

number = {2-3},

pages = {144--165},

publisher = {Inderscience Publishers (IEL)},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kourouthanassis2015demystifying,

title = {Demystifying the design of mobile augmented reality applications},

author = {Panos E Kourouthanassis and Costas Boletsis and George Lekakos},

year  = {2015},

date = {2015-01-01},

journal = {Multimedia Tools and Applications},

volume = {74},

pages = {1045--1066},

publisher = {Springer US},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kourouthanassis2015should,

title = {Should I stay or should I go? The moderating effect of self-image congruity and trust on social networking continued use},

author = {Panos Kourouthanassis and George Lekakos and Vassilis Gerakis},

year  = {2015},

date = {2015-01-01},

journal = {Behaviour & Information Technology},

volume = {34},

number = {2},

pages = {190--203},

publisher = {Taylor & Francis},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kourouthanassis2015tourists,

title = {Tourists responses to mobile augmented reality travel guides: The role of emotions on adoption behavior},

author = {Panos Kourouthanassis and Costas Boletsis and Cleopatra Bardaki and Dimitra Chasanidou},

year  = {2015},

date = {2015-01-01},

journal = {Pervasive and Mobile Computing},

volume = {18},

pages = {71--87},

publisher = {Elsevier},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{karyotis2015macroscopic,

title = {Macroscopic malware propagation dynamics for complex networks with churn},

author = {Vasileios Karyotis and Symeon Papavassiliou},

year  = {2015},

date = {2015-01-01},

journal = {IEEE Communications Letters},

volume = {19},

number = {4},

pages = {577--580},

publisher = {IEEE},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{stai2015analysis,

title = {Analysis and control of information diffusion dictated by user interest in generalized networks},

author = {Eleni Stai and Vasileios Karyotis and Symeon Papavassiliou},

year  = {2015},

date = {2015-01-01},

journal = {Computational Social Networks},

volume = {2},

number = {1},

pages = {1--31},

publisher = {SpringerOpen},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Huang201577,

title = {Trying before buying: The moderating role of online reviews in trial attitude formation toward mobile applications},

author = {G. -H. Huang and N. Korfiatis},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84944320348&doi=10.1080%2f10864415.2015.1029359&partnerID=40&md5=05be036af388bbca85115ed7ee32b97e},

doi = {10.1080/10864415.2015.1029359},

year  = {2015},

date = {2015-01-01},

journal = {International Journal of Electronic Commerce},

volume = {19},

number = {4},

pages = {77-111},

note = {cited By 74},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Korfiatis201544,

title = {Gender effects and cooperation styles in the Facebook community: A quasi-experimental assessment},

author = {N. Korfiatis and R. Zicari and M. D. Lytras},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84922425047&doi=10.1016%2fj.chb.2014.11.065&partnerID=40&md5=52a769f1e8f03932129d5aaf8ca24bba},

doi = {10.1016/j.chb.2014.11.065},

year  = {2015},

date = {2015-01-01},

journal = {Computers in Human Behavior},

volume = {48},

pages = {44-50},

note = {cited By 2},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kostagiolas20153,

title = {Music, musicians and information seeking behaviour: A case study on a community concert band},

author = {P. A. Kostagiolas and C. Lavranos and N. Korfiatis and J. Papadatos and S. Papavlasopoulos},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84920911175&doi=10.1108%2fJD-07-2013-0083&partnerID=40&md5=238abdaf9f49432da77f8031ee5f2b0b},

doi = {10.1108/JD-07-2013-0083},

year  = {2015},

date = {2015-01-01},

journal = {Journal of Documentation},

volume = {71},

number = {1},

pages = {3-24},

note = {cited By 37},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Stai2015,

title = {Analysis and control of information diffusion dictated by user interest in generalized networks},

author = {E. Stai and V. Karyotis and S. Papavassiliou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046497377&doi=10.1186%2fs40649-015-0025-4&partnerID=40&md5=0ae92df0fd82896146427461de5385ee},

doi = {10.1186/s40649-015-0025-4},

issn = {21974314},

year  = {2015},

date = {2015-01-01},

journal = {Computational Social Networks},

volume = {2},

number = {1},

publisher = {SpringerOpen},

abstract = {The diffusion of useful information in generalized networks, such as those consisting of wireless physical substrates and social network overlays is very important for theoretical and practical applications. Contrary to previous works, we focus on the impact of user interest and its features (e.g., interest periodicity) on the dynamics and control of diffusion of useful information within such complex wireless-social systems. By considering the impact of temporal and topical variations of users interests, e.g., seasonal periodicity of interest in summer vacation advertisements which spread more effectively during Spring–Summer months, we develop an epidemic-based mathematical framework for modeling and analyzing such information dissemination processes and use three indicative operational scenarios to demonstrate the solutions and results that can be obtained by the corresponding differential equation-based formalism. We then develop an optimal control framework subject to the above information diffusion modeling that allows controlling the trade-off between information propagation efficiency and the associated cost, by considering and leveraging on the impact that user interests have on the diffusion processes. By analysis and extensive simulations, significant outcomes are obtained on the impact of each network layer and the associated interest parameters on the dynamics of useful information diffusion. Furthermore, several behavioral properties of the optimal control of the useful information diffusion with respect to the number of infected/informed nodes and the evolving user interest are shown through analysis and verified via simulations. Specifically, a key finding is that low interest-related diffusion can be aided by utilizing proper optimal controls. Our work in this paper paves the way towards this user-centered information diffusion framework. © 2015, Stai et al.},

note = {cited By 9},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Karyotis2015577,

title = {Macroscopic malware propagation dynamics for complex networks with churn},

author = {V. Karyotis and S. Papavassiliou},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84927730777&doi=10.1109%2fLCOMM.2015.2399925&partnerID=40&md5=70ea29f069651e438d8b63decdc8a8f6},

doi = {10.1109/LCOMM.2015.2399925},

issn = {10897798},

year  = {2015},

date = {2015-01-01},

journal = {IEEE Communications Letters},

volume = {19},

number = {4},

pages = {577-580},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {In this letter, a queueing-based approach for modeling malware propagation in complex networks with churn (dynamic node variation) is introduced. The proposed methodology captures the dynamics of SIS-type malware, especially in time-varying networks, where nodes enter and leave due to their limited energy reserves, or as the outcome of malware attacks. We demonstrate the developed model in various complex networks, showing how it can be exploited for analytically quantifying network reliability and further used for increasing the robustness of the network against generic malware attacks. © 2015 IEEE.},

note = {cited By 22},

keywords = {Complex networks, Computer crime; Malware; Queueing networks; Time varying networks, Developed model; Dynamic nodes; Limited energies; Malware attacks; Malware propagation; Network reliability; Network robustness; Product forms},

pubstate = {published},

tppubtype = {article}

}

@article{Stai201562,

title = {On the impact of network evolution on NUM resource allocation problems in wireless multihop networks},

author = {E. Stai and V. Karyotis and S. Papavassiliou},

editor = {Ruehrup S. Papavassiliou S.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84949024570&doi=10.1007%2f978-3-319-19662-6_5&partnerID=40&md5=9f0317d3b63d47b67de012a4df648216},

doi = {10.1007/978-3-319-19662-6_5},

issn = {03029743},

year  = {2015},

date = {2015-01-01},

journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},

volume = {9143},

pages = {62-75},

publisher = {Springer Verlag},

abstract = {Network churn is one of the primary reasons for network topology evolution, creating a dynamic environment that all designed and developed mechanisms have to cope with. In this work, we focus on studying the impact of network evolution on the resource allocation mechanisms in wireless multihop networks, and thus set the scene for more pragmatic network optimization. More specifically, we study the impact of topology evolution in the form of node and edge churn on the Network Utility Maximization (NUM) mechanism, where the latter is employed as a form of intelligent resource allocation framework and implementation. Our study in this paper serves as a stepping stone for a more realistic consideration of cross-layer design, capable of coping with the dynamic nature of the evolutionary changes that take place in each network inevitably. This work aspires to stimulate the interest and further research on improving and developing network optimization and control mechanisms under more realistic operational conditions. © Springer International Publishing Switzerland 2015.},

note = {cited By 0; Conference of 14th International Conference on Ad-Hoc Networks and Wireless, ADHOC-NOW 2015 ; Conference Date: 29 June 2015 Through 1 July 2015; Conference Code:157969},

keywords = {Ad hoc networks; Dynamics; Mobile ad hoc networks; Network layers; Resource allocation; Topology; Wireless networks, Cross-layer design; Network utility maximization; Network utility maximizations (NUM); Optimality; Realistic operational conditions; Resource allocation problem; Topology evolution; Wireless multi-hop network, Wireless ad hoc networks},

pubstate = {published},

tppubtype = {article}

}

@article{Mikalef2015625,

title = {Purchasing alignment under multiple contingencies: A configuration theory approach},

author = {P. Mikalef and A. Pateli and R. S. Batenburg and R. Van De Wetering},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84929301553&doi=10.1108%2fIMDS-10-2014-0298&partnerID=40&md5=0fba4546958b248b9a503523b09ee0ec},

doi = {10.1108/IMDS-10-2014-0298},

year  = {2015},

date = {2015-01-01},

journal = {Industrial Management and Data Systems},

volume = {115},

number = {4},

pages = {625-645},

note = {cited By 74},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kourouthanassis2015217,

title = {Exploring the online satisfaction gap of medical doctors: An expectation-confirmation investigation of information needs},

author = {P. E. Kourouthanassis and P. Mikalef and M. Ioannidou and A. Pateli},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84912102822&doi=10.1007%2f978-3-319-09012-2_15&partnerID=40&md5=f2033b8935a32de0cf4c6118e9b818f8},

doi = {10.1007/978-3-319-09012-2_15},

year  = {2015},

date = {2015-01-01},

journal = {Advances in Experimental Medicine and Biology},

volume = {820},

pages = {217-228},

note = {cited By 7},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kourouthanassis2014analysing,

title = {Analysing m-commerce research: technology, applications and research themes},

author = {Panos E Kourouthanassis and Christos K Georgiadis},

year  = {2014},

date = {2014-01-01},

journal = {International journal of mobile communications},

volume = {12},

number = {1},

pages = {1--11},

publisher = {Inderscience Publishers Ltd},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pappas2014shiny,

title = {Shiny happy people buying: the role of emotions on personalized e-shopping},

author = {Ilias O Pappas and Panos E Kourouthanassis and Michail N Giannakos and Vassilios Chrissikopoulos},

year  = {2014},

date = {2014-01-01},

journal = {Electronic Markets},

volume = {24},

pages = {193--206},

publisher = {Springer Berlin Heidelberg},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{kostagiolas2014work,

title = {Work-related factors influencing doctors search behaviors and trust toward medical information resources},

author = {Petros Kostagiolas and Nikolaos Korfiatis and Panos Kourouthanasis and Georgios Alexias},

year  = {2014},

date = {2014-01-01},

journal = {International Journal of Information Management},

volume = {34},

number = {2},

pages = {80--88},

publisher = {Pergamon},

keywords = {},

pubstate = {published},

tppubtype = {article}

}