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Dimitrios Tsiotas
Department of Regional and Economic Development, Agricultural University of Athens, Nea Poli, Amfissa 33100, Greece

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Case report
Published: 03 August 2021 in Cities
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Within the context of the growth poles theory, the areas that lack critical sizes, instead of polycentric structures, develop restricted urban “dipoles” and “tripoles” that are often not studied in the literature within a well-defined context. This paper aims to conceptualize these peculiar urban structures more deeply. It configures a methodological framework quantitatively defining dipoles and polycentric structures through edge distribution partitioning. The analysis is applied to Greek commuting data at the intercity and interregional geographical scale, defining dipoles within a more realistic empirical context comparatively to the percentile and boxplot outlier detection. Overall, the proposed method has a scale-free property due to its structural than numeric configuration and contributes to a more realistic detection of city dipoles, providing insights into the effect of scale and polycentrism in urban structures.

ACS Style

Dimitrios Tsiotas; Nikolaos Axelis; Serafeim Polyzos. A methodological framework for defining city dipoles in urban systems based on a functional attribute. Cities 2021, 103387 .

AMA Style

Dimitrios Tsiotas, Nikolaos Axelis, Serafeim Polyzos. A methodological framework for defining city dipoles in urban systems based on a functional attribute. Cities. 2021; ():103387.

Chicago/Turabian Style

Dimitrios Tsiotas; Nikolaos Axelis; Serafeim Polyzos. 2021. "A methodological framework for defining city dipoles in urban systems based on a functional attribute." Cities , no. : 103387.

Journal article
Published: 22 July 2021 in Processes
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With the advent of the first pandemic wave of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), the question arises as to whether the spread of the virus will be controlled by the application of preventive measures or will follow a different course, regardless of the pattern of spread already recorded. These conditions caused by the unprecedented pandemic have highlighted the importance of reliable data from official sources, their complete recording and analysis, and accurate investigation of epidemiological indicators in almost real time. There is an ongoing research demand for reliable and effective modeling of the disease but also the formulation of substantiated views to make optimal decisions for the design of preventive or repressive measures by those responsible for the implementation of policy in favor of the protection of public health. The main objective of the study is to present an innovative data-analysis system of COVID-19 disease progression in Greece and her border countries by real-time statistics about the epidemiological indicators. This system utilizes visualized data produced by an automated information system developed during the study, which is based on the analysis of large pandemic-related datasets, making extensive use of advanced machine learning methods. Finally, the aim is to support with up-to-date technological means optimal decisions in almost real time as well as the development of medium-term forecast of disease progression, thus assisting the competent bodies in taking appropriate measures for the effective management of the available health resources.

ACS Style

Konstantinos Demertzis; Dimitrios Taketzis; Dimitrios Tsiotas; Lykourgos Magafas; Lazaros Iliadis; Panayotis Kikiras. Pandemic Analytics by Advanced Machine Learning for Improved Decision Making of COVID-19 Crisis. Processes 2021, 9, 1267 .

AMA Style

Konstantinos Demertzis, Dimitrios Taketzis, Dimitrios Tsiotas, Lykourgos Magafas, Lazaros Iliadis, Panayotis Kikiras. Pandemic Analytics by Advanced Machine Learning for Improved Decision Making of COVID-19 Crisis. Processes. 2021; 9 (8):1267.

Chicago/Turabian Style

Konstantinos Demertzis; Dimitrios Taketzis; Dimitrios Tsiotas; Lykourgos Magafas; Lazaros Iliadis; Panayotis Kikiras. 2021. "Pandemic Analytics by Advanced Machine Learning for Improved Decision Making of COVID-19 Crisis." Processes 9, no. 8: 1267.

Journal article
Published: 03 June 2021 in Scientific Reports
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This paper proposes a new method for converting a time-series into a weighted graph (complex network), which builds on electrostatics in physics. The proposed method conceptualizes a time-series as a series of stationary, electrically charged particles, on which Coulomb-like forces can be computed. This allows generating electrostatic-like graphs associated with time-series that, additionally to the existing transformations, can be also weighted and sometimes disconnected. Within this context, this paper examines the structural similarity between five different types of time-series and their associated graphs that are generated by the proposed algorithm and the visibility graph, which is currently the most popular algorithm in the literature. The analysis compares the source (original) time-series with the node-series generated by network measures (that are arranged into the node-ordering of the source time-series), in terms of a linear trend, chaotic behaviour, stationarity, periodicity, and cyclical structure. It is shown that the proposed electrostatic graph algorithm generates graphs with node-measures that are more representative of the structure of the source time-series than the visibility graph. This makes the proposed algorithm more natural rather than algebraic, in comparison with existing physics-defined methods. The overall approach also suggests a methodological framework for evaluating the structural relevance between the source time-series and their associated graphs produced by any possible transformation.

ACS Style

Dimitrios Tsiotas; Lykourgos Magafas; Panos Argyrakis. An electrostatics method for converting a time-series into a weighted complex network. Scientific Reports 2021, 11, 1 -15.

AMA Style

Dimitrios Tsiotas, Lykourgos Magafas, Panos Argyrakis. An electrostatics method for converting a time-series into a weighted complex network. Scientific Reports. 2021; 11 (1):1-15.

Chicago/Turabian Style

Dimitrios Tsiotas; Lykourgos Magafas; Panos Argyrakis. 2021. "An electrostatics method for converting a time-series into a weighted complex network." Scientific Reports 11, no. 1: 1-15.

Journal article
Published: 26 February 2021 in Tourism and Hospitality
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Within the context that tourism-seasonality is a composite phenomenon described by temporal, geographical, and socio-economic aspects, this article develops a multilevel method for studying time patterns of tourism-seasonality in conjunction with its spatial dimension and socio-economic dimension. The study aims to classify the temporal patterns of seasonality into regional groups and to configure distinguishable seasonal profiles facilitating tourism policy and development. The study applies a multilevel pattern recognition approach incorporating time-series assessment, correlation, and complex network analysis based on community detection with the use of the modularity optimization algorithm, on data of overnight-stays recorded for the time-period 1998–2018. The analysis reveals four groups of seasonality, which are described by distinct seasonal, geographical, and socio-economic profiles. Overall, the analysis supports multidisciplinary and synthetic research in the modeling of tourism research and promotes complex network analysis in the study of socio-economic systems, by providing insights into the physical conceptualization that the community detection based on the modularity optimization algorithm can enjoy to the real-world applications.

ACS Style

Dimitrios Tsiotas; Thomas Krabokoukis; Serafeim Polyzos. Detecting Tourism Typologies of Regional Destinations Based on Their Spatio-Temporal and Socioeconomic Performance: A Correlation-Based Complex Network Approach for the Case of Greece. Tourism and Hospitality 2021, 2, 113 -139.

AMA Style

Dimitrios Tsiotas, Thomas Krabokoukis, Serafeim Polyzos. Detecting Tourism Typologies of Regional Destinations Based on Their Spatio-Temporal and Socioeconomic Performance: A Correlation-Based Complex Network Approach for the Case of Greece. Tourism and Hospitality. 2021; 2 (1):113-139.

Chicago/Turabian Style

Dimitrios Tsiotas; Thomas Krabokoukis; Serafeim Polyzos. 2021. "Detecting Tourism Typologies of Regional Destinations Based on Their Spatio-Temporal and Socioeconomic Performance: A Correlation-Based Complex Network Approach for the Case of Greece." Tourism and Hospitality 2, no. 1: 113-139.

Journal article
Published: 24 November 2020 in Research in Transportation Economics
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Network science has provided new ways and effective methods in the modeling of communication systems. According to this discipline, systems of economic and spatial interaction are considered as spatial networks and are modeled into graphs. This approach allows studying transportation networks and other spatial networks of national and global economic importance in terms of graph theory and statistical mechanics and it can provide new insights for the structure and functionality of these systems, which are not visible through the prism of spatial and economic analysis. Within this context, this paper models the interregional road transportation network in Greece (GRN), a spatial network of prime economic importance for its country, into a geo-referenced primal graph and it discusses its geographical and topological features under the regional economics' perspective. The results show that GRN has a mesh (lattice-like) structure subjected to spatial constraints and that it is ruled by primary developmental dynamics, where many aspects of network topology are related to economic aspects of the road network. Overall, the paper highlights that measures of network topology are related to different aspects of the network's socio-economic framework and thus they can be considered as indicators of economic performance for this transportation network.

ACS Style

Dimitrios Tsiotas. Drawing indicators of economic performance from network topology: The case of the interregional road transportation in Greece. Research in Transportation Economics 2020, 101004 .

AMA Style

Dimitrios Tsiotas. Drawing indicators of economic performance from network topology: The case of the interregional road transportation in Greece. Research in Transportation Economics. 2020; ():101004.

Chicago/Turabian Style

Dimitrios Tsiotas. 2020. "Drawing indicators of economic performance from network topology: The case of the interregional road transportation in Greece." Research in Transportation Economics , no. : 101004.

Journal article
Published: 20 November 2020 in Physics
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This paper proposes a method for examining chaotic structures in semiconductor or alloy voltage oscillation time-series, and focuses on the case of the TlInTe2 semiconductor. The available voltage time-series are characterized by instabilities in negative differential resistance in the current–voltage characteristic region, and are primarily chaotic in nature. The analysis uses a complex network analysis of the time-series and applies the visibility graph algorithm to transform the available time-series into a graph so that the topological properties of the graph can be studied instead of the source time-series. The results reveal a hybrid lattice-like configuration and a major hierarchical structure corresponding to scale-free characteristics in the topology of the visibility graph, which is in accordance with the default hybrid chaotic and semi-periodic structure of the time-series. A novel conceptualization of community detection based on modularity optimization is applied to the available time-series and reveals two major communities that are able to be related to the pair-wise attractor of the voltage oscillations’ phase portrait of the TlInTe2 time-series. Additionally, the network analysis reveals which network measures are more able to preserve the chaotic properties of the source time-series. This analysis reveals metric information that is able to supplement the qualitative phase-space information. Overall, this paper proposes a complex network analysis of the time-series as a method for dealing with the complexity of semiconductor and alloy physics.

ACS Style

Dimitrios Tsiotas; Lykourgos Magafas; Michael Hanias. Examination of Chaotic Structures in Semiconductor or Alloy Voltage Time-Series: A Complex Network Approach for the Case of TlInTe2. Physics 2020, 2, 624 -639.

AMA Style

Dimitrios Tsiotas, Lykourgos Magafas, Michael Hanias. Examination of Chaotic Structures in Semiconductor or Alloy Voltage Time-Series: A Complex Network Approach for the Case of TlInTe2. Physics. 2020; 2 (4):624-639.

Chicago/Turabian Style

Dimitrios Tsiotas; Lykourgos Magafas; Michael Hanias. 2020. "Examination of Chaotic Structures in Semiconductor or Alloy Voltage Time-Series: A Complex Network Approach for the Case of TlInTe2." Physics 2, no. 4: 624-639.

Journal article
Published: 30 June 2020 in Scientific Reports
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The fitness model was introduced in the literature to expand the Barabasi-Albert model’s generative mechanism, which produces scale-free networks under the control of degree. However, the fitness model has not yet been studied in a comprehensive context because most models are built on invariant fitness as the network grows and time-dynamics mainly concern new nodes joining the network. This mainly static consideration restricts fitness in generating scale-free networks only when the underlying fitness distribution is power-law, a fact which makes the hybrid fitness models based on degree-driven preferential attachment to remain the most attractive models in the literature. This paper advances the time-dynamic conceptualization of fitness, by studying scale-free networks generated under topological fitness that changes as the network grows, where the fitness is controlled by degree, clustering coefficient, betweenness, closeness, and eigenvector centrality. The analysis shows that growth under time-dynamic topological fitness is indifferent to the underlying fitness distribution and that different topological fitness generates networks of different topological attributes, ranging from a mesh-like to a superstar-like pattern. The results also show that networks grown under the control of betweenness centrality outperform the other networks in scale-freeness and the majority of the other topological attributes. Overall, this paper contributes to broadening the conceptualization of fitness to a more time-dynamic context.

ACS Style

Dimitrios Tsiotas. Detecting differences in the topology of scale-free networks grown under time-dynamic topological fitness. Scientific Reports 2020, 10, 1 -16.

AMA Style

Dimitrios Tsiotas. Detecting differences in the topology of scale-free networks grown under time-dynamic topological fitness. Scientific Reports. 2020; 10 (1):1-16.

Chicago/Turabian Style

Dimitrios Tsiotas. 2020. "Detecting differences in the topology of scale-free networks grown under time-dynamic topological fitness." Scientific Reports 10, no. 1: 1-16.

Journal article
Published: 30 June 2020 in International Journal of Environmental Research and Public Health
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Within the complex framework of anti-COVID-19 health management, where the criteria of diagnostic testing, the availability of public-health resources and services, and the applied anti-COVID-19 policies vary between countries, the reliability and accuracy in the modeling of temporal spread can prove to be effective in the worldwide fight against the disease. This paper applies an exploratory time-series analysis to the evolution of the disease in Greece, which currently suggests a success story of COVID-19 management. The proposed method builds on a recent conceptualization of detecting connective communities in a time-series and develops a novel spline regression model where the knot vector is determined by the community detection in the complex network. Overall, the study contributes to the COVID-19 research by proposing a free of disconnected past-data and reliable framework of forecasting, which can facilitate decision-making and management of the available health resources.

ACS Style

Konstantinos Demertzis; Dimitrios Tsiotas; Lykourgos Magafas. Modeling and Forecasting the COVID-19 Temporal Spread in Greece: An Exploratory Approach based on Complex Network Defined Splines. International Journal of Environmental Research and Public Health 2020, 17, 4693 .

AMA Style

Konstantinos Demertzis, Dimitrios Tsiotas, Lykourgos Magafas. Modeling and Forecasting the COVID-19 Temporal Spread in Greece: An Exploratory Approach based on Complex Network Defined Splines. International Journal of Environmental Research and Public Health. 2020; 17 (13):4693.

Chicago/Turabian Style

Konstantinos Demertzis; Dimitrios Tsiotas; Lykourgos Magafas. 2020. "Modeling and Forecasting the COVID-19 Temporal Spread in Greece: An Exploratory Approach based on Complex Network Defined Splines." International Journal of Environmental Research and Public Health 17, no. 13: 4693.

Journal article
Published: 22 June 2020 in Physics
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Within the context of Greece promising a success story in the fight against the disease, this paper proposes a novel method for studying the evolution of the Greek COVID-19 infection curve in relation to the anti-COVID-19 policies applied to control the pandemic. Based on the ongoing spread of COVID-19 and the insufficient data for applying classic time-series approaches, the analysis builds on the visibility graph algorithm to study the Greek COVID-19 infection curve as a complex network. By using the modularity optimization algorithm, the generated visibility graph is divided into communities defining periods of different connectivity in the time-series body. These periods reveal a sequence of different typologies in the evolution of the disease, starting with a power pattern, where a second order polynomial (U-shaped) pattern intermediates, being followed by a couple of exponential patterns, and ending up with a current logarithmic pattern revealing that the evolution of the Greek COVID-19 infection curve tends towards saturation. In terms of Gaussian modeling, this successive compression of the COVID-19 infection curve into five parts implies that the pandemic in Greece is about to reach the second (decline) half of the bell-shaped distribution. The network analysis also illustrates stability of hubs and instability of medium and low-degree nodes, implying a low probability of meeting maximum (infection) values in the future and high uncertainty in the variability of other values below the average. The overall approach contributes to the scientific research by proposing a novel method for the structural decomposition of a time-series into periods, which allows removing from the series the disconnected past-data facilitating better forecasting, and provides insights of good policy and decision-making practices and management that may help other countries improve their performance in the war against COVID-19.

ACS Style

Dimitrios Tsiotas; Lykourgos Magafas. The Effect of Anti-COVID-19 Policies on the Evolution of the Disease: A Complex Network Analysis of the Successful Case of Greece. Physics 2020, 2, 325 -339.

AMA Style

Dimitrios Tsiotas, Lykourgos Magafas. The Effect of Anti-COVID-19 Policies on the Evolution of the Disease: A Complex Network Analysis of the Successful Case of Greece. Physics. 2020; 2 (2):325-339.

Chicago/Turabian Style

Dimitrios Tsiotas; Lykourgos Magafas. 2020. "The Effect of Anti-COVID-19 Policies on the Evolution of the Disease: A Complex Network Analysis of the Successful Case of Greece." Physics 2, no. 2: 325-339.

Conference paper
Published: 10 March 2020 in Sustainable Transport Development, Innovation and Technology
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This chapter aims to extract information about the complaints management strategies of the Greek hotels and to measure their interaction with the TripAdvisor users. The research builds on the comments and complaints being available at this website and performs a statistical analysis to detect differences between different hotel-classes (1-star up to 5-star). The results show a limited overall existence of responses, which is unevenly distributed over the high-class and against the lower-class hotels, illustrating a conventional pattern of complaints management “quality” in the tourism sector in Greece. Overall, this chapter highlights the importance of the information being available in travel and tourism social-media websites and it motivates for further research and the hotel companies to get involved with such applications.

ACS Style

Dimitrios Tsiotas; Spyros Niavis; Dimitrios Belias; Labros Sdrolias. What Can the TripAdvisor Tell Us About the Complaints Management Strategies? The Case of the Greek Hotels. Sustainable Transport Development, Innovation and Technology 2020, 999 -1005.

AMA Style

Dimitrios Tsiotas, Spyros Niavis, Dimitrios Belias, Labros Sdrolias. What Can the TripAdvisor Tell Us About the Complaints Management Strategies? The Case of the Greek Hotels. Sustainable Transport Development, Innovation and Technology. 2020; ():999-1005.

Chicago/Turabian Style

Dimitrios Tsiotas; Spyros Niavis; Dimitrios Belias; Labros Sdrolias. 2020. "What Can the TripAdvisor Tell Us About the Complaints Management Strategies? The Case of the Greek Hotels." Sustainable Transport Development, Innovation and Technology , no. : 999-1005.

Conference paper
Published: 10 March 2020 in Sustainable Transport Development, Innovation and Technology
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This chapter assesses the competitiveness of the Greek coastal destinations, in a comparative context. To do so, it develops various indicators which help destinations to conceptualize both their dynamics and their structural advantages. To better depict the competitiveness of destinations, the indicators are formulated by using the user-generated data being available at the TripAdvisor website. Under this data-mining process, the benchmarking can highlight critical features of the tourism industry, which cannot be revealed when analysis is based on the typical official data. The results signify a gap of competitiveness between the insular and non-insular destinations but also they reveal some critical features of the tourism-supply, which can facilitate the sustainable development of all Greek destinations.

ACS Style

Spyros Niavis; Dimitrios Tsiotas. Assessing the Competitiveness of Greek Coastal Destinations. Sustainable Transport Development, Innovation and Technology 2020, 957 -962.

AMA Style

Spyros Niavis, Dimitrios Tsiotas. Assessing the Competitiveness of Greek Coastal Destinations. Sustainable Transport Development, Innovation and Technology. 2020; ():957-962.

Chicago/Turabian Style

Spyros Niavis; Dimitrios Tsiotas. 2020. "Assessing the Competitiveness of Greek Coastal Destinations." Sustainable Transport Development, Innovation and Technology , no. : 957-962.

Preprint
Published: 27 January 2020
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Network Science is an emerging discipline using the network paradigm to model communication systems as pair-sets of interconnected nodes and their linkages (edges). This paper applies this paradigm to study an interacting system in regional economy consisting of daily road transportation flows for labor purposes, the so-called commuting phenomenon. In particular, the commuting system in Greece including 39 non-insular prefectures is modeled into a complex network and it is studied using measures and methods of complex network analysis and empirical techniques. The study aims to detect the structural characteristics of the Greek interregional commuting network (GCN) and to interpret how this network is related to the regional development. The analysis highlights the effect of the spatial constraints in the structure of the GCN, it provides insights about the major road transport projects constructed the last decade, and it outlines a populationcontrolled (gravity) pattern of commuting, illustrating that high-populated regions attract larger volumes of the commuting activity, which consequently affects their productivity. Overall, this paper highlights the effectiveness of complex network analysis in the modeling of systems of regional economy, such as the systems of spatial interaction and the transportation networks, and it promotes the use of the network paradigm to the regional research.

ACS Style

Dimitrios Tsiotas; Labros Sdrolias; Dimitrios Belias. The network paradigm as a modeling tool in regional economy: the case of interregional commuting in Greece. 2020, 1 .

AMA Style

Dimitrios Tsiotas, Labros Sdrolias, Dimitrios Belias. The network paradigm as a modeling tool in regional economy: the case of interregional commuting in Greece. . 2020; ():1.

Chicago/Turabian Style

Dimitrios Tsiotas; Labros Sdrolias; Dimitrios Belias. 2020. "The network paradigm as a modeling tool in regional economy: the case of interregional commuting in Greece." , no. : 1.

Preprint
Published: 27 January 2020
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Technological developments worldwide are contributing to the improvement of transport infrastructures and they are helping to reduce the overall transport costs. At the same time, such developments along with the reduction in transport costs are affecting the spatial interdependence between the regions and countries, a fact inducing significant effects on their economies and, in general, on their growth-rates. A specific class of transport infrastructures contributing significantly to overcoming the spatial constraints is the airtransport infrastructures. Nowadays, the importance of air-transport infrastructures in the economic development is determinative, especially for the geographically isolated regions, such as for the island regions of Greece. Within this context, this paper studies the Greek airports and particularly the evolution of their overall transportation imprint, their geographical distribution, and the volume of the transport activity of each airport. Also, it discusses, in a broad context, the seasonality of the Greek airport activity, the importance of the airports for the local and regional development, and it formulates general conclusions.

ACS Style

Serafeim Polyzos; Dimitrios Tsiotas. Regional airports in Greece, their characteristics and their importance for the local economic development. 2020, 1 .

AMA Style

Serafeim Polyzos, Dimitrios Tsiotas. Regional airports in Greece, their characteristics and their importance for the local economic development. . 2020; ():1.

Chicago/Turabian Style

Serafeim Polyzos; Dimitrios Tsiotas. 2020. "Regional airports in Greece, their characteristics and their importance for the local economic development." , no. : 1.

Preprint
Published: 15 January 2020
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This paper expands the degree-based consideration of the preferential attachment growth process and applies five different connectivity criteria (node degree, clustering coefficient, betweenness centrality, closeness centrality, and eigenvector centrality) to define the development of new links in the networks. Based on statistical inference, the analysis shows that all the available control attributes are capable generating SF networks, that the proposed generalized preferential attachment growth process produces networks of statistically different topologies, under different control-attributes, and that the betweenness centrality is the control-attribute generating networks of better topology. Overall, this paper introduces a multi-dimensional conceptualization of preferential attachment, which can motivate further research and can provide new tools for the modeling and interpretation of real-world networks that currently cannot be fully explained by the degree-driven BA models.

ACS Style

Dimitrios Tsiotas. Preferential attachment: a multi-attribute growth process generating scale-free networks of different topologies. 2020, 1 .

AMA Style

Dimitrios Tsiotas. Preferential attachment: a multi-attribute growth process generating scale-free networks of different topologies. . 2020; ():1.

Chicago/Turabian Style

Dimitrios Tsiotas. 2020. "Preferential attachment: a multi-attribute growth process generating scale-free networks of different topologies." , no. : 1.

Original software publication
Published: 23 December 2019 in SoftwareX
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In this study, we provide the VisExpA (Visibility Expansion Algorithm), a computational code that implements a recently published method, which allows generating a visibility graph from a complex network instead of a time-series that is currently applicable. The proposed algorithm is applied to a complex network and it uses a node-wise control-attribute (network-nodes topological measure) to define the node-heights to which the original (time-series) visibility algorithm is applied. The VisExpA applies the idea of visibility graph from the field of time-series to complex networks and it allows interpreting the network topology as a landscape, making it a valuable tool of analysis in many disciplines.

ACS Style

Dimitrios Tsiotas; Avraam Charakopoulos. VisExpA: Visibility expansion algorithm in the topology of complex networks. SoftwareX 2019, 11, 100379 .

AMA Style

Dimitrios Tsiotas, Avraam Charakopoulos. VisExpA: Visibility expansion algorithm in the topology of complex networks. SoftwareX. 2019; 11 ():100379.

Chicago/Turabian Style

Dimitrios Tsiotas; Avraam Charakopoulos. 2019. "VisExpA: Visibility expansion algorithm in the topology of complex networks." SoftwareX 11, no. : 100379.

Journal article
Published: 13 September 2019 in Journal of Destination Marketing & Management
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This paper assesses the comparative performance of the Mediterranean coastal destinations using data envelopment analysis, considering both the efficiency and effectiveness dimensions. The analysis does not only provide a benchmarking framework for the destinations, but a framework to reveal, in a comparative context, the trade-offs between efficiency and effectiveness, the sources of inefficiency, and the pillars of effectiveness, for each region. This paper advances the current literature in destination performance benchmarking, under the production frontier method, by incorporating the effectiveness dimension to the broadly used efficiency consideration. This advancement is of critical importance, considering that the results of this paper support the lack of a strong relationship between destinations' efficiency and effectiveness. Therefore, individual destinations' assessments, based only on one of the two performance dimensions, may lead to biased estimations that may mislead policy interventions.

ACS Style

Spyros Niavis; Dimitrios Tsiotas. Assessing the tourism performance of the Mediterranean coastal destinations: A combined efficiency and effectiveness approach. Journal of Destination Marketing & Management 2019, 14, 100379 .

AMA Style

Spyros Niavis, Dimitrios Tsiotas. Assessing the tourism performance of the Mediterranean coastal destinations: A combined efficiency and effectiveness approach. Journal of Destination Marketing & Management. 2019; 14 ():100379.

Chicago/Turabian Style

Spyros Niavis; Dimitrios Tsiotas. 2019. "Assessing the tourism performance of the Mediterranean coastal destinations: A combined efficiency and effectiveness approach." Journal of Destination Marketing & Management 14, no. : 100379.

Research article
Published: 18 June 2019 in PLOS ONE
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Aiming at serving the interdisciplinary demand in network science, this paper introduces a new concept for complex networks, named network stiffness, which is extracted from structural engineering by assuming that a complex network behaves similarly with a structured framework. This analogy allows interpreting that a complex network can resist against any cause attempting to induce deformation changes to the network's structure, regardless of whether the network is material or not. Within this framework, this paper examines the context of applying the conceptual analogy of stiffness from the field of structural engineering to network science and then it develops computational approaches capturing different aspects of network stiffness so that to be used in complex network analysis. The implementation of these approaches to a real-world network (global inbound tourism network) shows that stiffness can produce interesting insights to complex network analysis about the factors related to changes caused to the structure and the status of a complex network.

ACS Style

Dimitrios Tsiotas. Network stiffness: A new topological property in complex networks. PLOS ONE 2019, 14, e0218477 .

AMA Style

Dimitrios Tsiotas. Network stiffness: A new topological property in complex networks. PLOS ONE. 2019; 14 (6):e0218477.

Chicago/Turabian Style

Dimitrios Tsiotas. 2019. "Network stiffness: A new topological property in complex networks." PLOS ONE 14, no. 6: e0218477.

Conference paper
Published: 29 May 2019 in Sustainable Transport Development, Innovation and Technology
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Tourism is a complex socioeconomic phenomenon that has been diachronically studied through the prism of different disciplines and by using diverse methods and models. Despite its composite nature, tourism has not adequately been examined by researchers from the disciplines studying complexity, such as physics, mathematics, complexity theory, and the modern network science. This paper innovates to be amongst a couple of works that describe the system of the international tourism demand using the network paradigm and modeling it as a complex network (the GITN) in order to provide insights about the network structure and functionality in terms of the interactions existing between its source and destination markets. The analysis is applied using measures and methods of complex network analysis (CNA) and the results are compared with a previous work studying three versions based on different top-market configuration per country of the GITN, where differences are recorded. Overall, the analysis illustrates the existence of hierarchies and of spatial constraints in the structure of GITN and it provides some interesting insights to the governments and to tourism policy makers about the global dynamics of the tourism phenomenon.

ACS Style

Dimitrios Tsiotas; Spyros Niavis; Dimitrios Belias; Labros Sdrolias. Modeling the International Tourism Demand as a Complex Network: The Case of the Global Inbound Tourism Market. Sustainable Transport Development, Innovation and Technology 2019, 809 -817.

AMA Style

Dimitrios Tsiotas, Spyros Niavis, Dimitrios Belias, Labros Sdrolias. Modeling the International Tourism Demand as a Complex Network: The Case of the Global Inbound Tourism Market. Sustainable Transport Development, Innovation and Technology. 2019; ():809-817.

Chicago/Turabian Style

Dimitrios Tsiotas; Spyros Niavis; Dimitrios Belias; Labros Sdrolias. 2019. "Modeling the International Tourism Demand as a Complex Network: The Case of the Global Inbound Tourism Market." Sustainable Transport Development, Innovation and Technology , no. : 809-817.

Conference paper
Published: 29 May 2019 in Sustainable Transport Development, Innovation and Technology
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Air transportation is a component of the national economies and plays an important role in the conduct of communication (especially amongst peripheral places), in the promotion of tourism, and generally in the economic and regional development. Within this context, this paper studies the regional dimension of the air transport in Greece, emphasizing to the factors that determine the attractiveness of the Greek regional airports by excluding the metropolitan cases of the Athens’ and Thessaloniki’s airports. The analysis is applied on air traffic statistics and on available spatial and financial information. For the study and the evaluation of the airport dynamics, a complex multiplier index is proposed, the results of which comply with the observations of the common practice and they can be used in other areas of application. The overall approach illustrates the contribution of the small and regional airports to tourism and regional development in Greece.

ACS Style

Dimitrios Tsiotas; Spyros Niavis; Serafeim Polyzos. The Dynamics of Small and Peripheral Airports in Tourism and Regional Development: The Case of Greece. Sustainable Transport Development, Innovation and Technology 2019, 781 -789.

AMA Style

Dimitrios Tsiotas, Spyros Niavis, Serafeim Polyzos. The Dynamics of Small and Peripheral Airports in Tourism and Regional Development: The Case of Greece. Sustainable Transport Development, Innovation and Technology. 2019; ():781-789.

Chicago/Turabian Style

Dimitrios Tsiotas; Spyros Niavis; Serafeim Polyzos. 2019. "The Dynamics of Small and Peripheral Airports in Tourism and Regional Development: The Case of Greece." Sustainable Transport Development, Innovation and Technology , no. : 781-789.

Journal article
Published: 15 March 2019 in Proceedings of the National Academy of Sciences
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The scale-free (SF) property is a major concept in complex networks, and it is based on the definition that an SF network has a degree distribution that follows a power-law (PL) pattern. This paper highlights that not all networks with a PL degree distribution arise through a Barabási−Albert (BA) preferential attachment growth process, a fact that, although evident from the literature, is often overlooked by many researchers. For this purpose, it is demonstrated, with simulations, that established measures of network topology do not suffice to distinguish between BA networks and other (random-like and lattice-like) SF networks with the same degree distribution. Additionally, it is examined whether an existing self-similarity metric proposed for the definition of the SF property is also capable of distinguishing different SF topologies with the same degree distribution. To contribute to this discrimination, this paper introduces a spectral metric, which is shown to be more capable of distinguishing between different SF topologies with the same degree distribution, in comparison with the existing metrics.

ACS Style

Dimitrios Tsiotas. Detecting different topologies immanent in scale-free networks with the same degree distribution. Proceedings of the National Academy of Sciences 2019, 116, 6701 -6706.

AMA Style

Dimitrios Tsiotas. Detecting different topologies immanent in scale-free networks with the same degree distribution. Proceedings of the National Academy of Sciences. 2019; 116 (14):6701-6706.

Chicago/Turabian Style

Dimitrios Tsiotas. 2019. "Detecting different topologies immanent in scale-free networks with the same degree distribution." Proceedings of the National Academy of Sciences 116, no. 14: 6701-6706.