The development of a data collection and analysis system based on social network users’ data

Rudikowa, Lada; Myslivec, Oleg; Sobolevsky, Stanislav; Nenko, Aleksandra; Savenkov, Ilia

doi:10.1016/j.procs.2019.08.195

Cited by 4 publications

(3 citation statements)

References 10 publications

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“…In our case, the results of the expert research were implemented to the SNA method process as presented in the Figure 2. The method allows indicating the direction of each relationship, interrelationships between elements, and their influence on the defined sets of issues [46,47]. The main advantage of the SNA method is its ability to reconstruct, visualize, and analyze complex and multilevel relationships occurring in a given phenomenon, taking into account both direct and indirect relationships between issues [44].…”

Section: Methods and Stages Of Researchmentioning

confidence: 99%

Open Innovation in the Shared Mobility Market

Turoń

Kubik

2021

Journal of Open Innovation: Technology, Market, and Complexity

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The market for shared mobility services is growing very quickly. New types of vehicles have been introduced, and the offer of available services and functionalities has expanded, the purpose of which is to improve the quality of service. Despite all the improvements, it is still not possible to speak of achieving full availability of systems that meet the needs of users. This is due to the reluctant involvement of operators of shared mobility systems in joining Mobility as a Service platforms based on the idea of open innovation. The aim of the article is to analyze the factors influencing the limitations in the development of open innovations in the form of Mobility as a Service (MaaS) services. The authors focus on identifying the challenges and concerns faced by shared mobility service providers. The article supports the development of the concept of open innovation in shared mobility services. It also contains practical recommendations for the development of MaaS systems. The results of the developed research can be used by operators of shared mobility services, transport authorities, or IT service providers providing MaaS services to strengthen cooperation and integration using the language of mutual benefit.

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Section: Methods and Stages Of Researchmentioning

confidence: 99%

Open Innovation in the Shared Mobility Market

Turoń

Kubik

2021

Journal of Open Innovation: Technology, Market, and Complexity

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“…SNA combines elements of statistics, sociology, and social psychology and was introduced by Moreno in 1934 [53][54][55]. Now, SNA is widely used in many research disciplines, such as social and behavioral sciences, computer science, technological forecasting, production, project management, environmental and energy sciences, and risk management [56][57][58][59][60]. SNA characterizes networked structures by nodes/knots (individual actors, people, or things within the network) with the relationships described as named arrows between the nodes (relationships or interactions) that connect them [55].…”

Section: Methodsmentioning

confidence: 99%

“…SNA characterizes networked structures by nodes/knots (individual actors, people, or things within the network) with the relationships described as named arrows between the nodes (relationships or interactions) that connect them [55]. These relationships could include interdependence, communication, the level of influence, competence, linkage, or the economy [55][56][57][58][59][60]. SNA discovers the relationships between individuals and assesses the impact of these relationships on the behavior of individuals.…”

Section: Methodsmentioning

confidence: 99%

A Holistic Approach to Electric Shared Mobility Systems Development—Modelling and Optimization Aspects

et al. 2020

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Due to the development of the shared economy, increasingly more shared mobility providers have launched services based on the use of electric vehicles. The increasing growth of electric shared mobility services has produced various types of problems that do not occur (or occur with a limited effect) under conventional shared mobility systems. This increase in electric shared mobility problems has led to many effects, including limitations of the system zones or going out of business. To avoid difficulties in the functioning of electric shared mobility systems, various scientific studies have been undertaken to model and optimize the operation of these systems. Modeling and optimization mainly relate to one category of the system—for example, only to bike sharing. However, to understand the system of electric shared mobility holistically, there is a need to define the criteria generally as stimulants or destimulants. Based on these assumptions, we conducted research on the identification of factors influencing the development of electric shared mobility services. We conducted our own expert research based on the Social Network Analysis method. The aim of this study was to determine the factors that influence the development or recession of services in the entire electric shared mobility market in reference to selected stakeholders. The obtained results indicate a non-standard approach to the modeling and optimization of electric shared mobility services. This study could be used as support for creating electric shared mobility models and could also be helpful for service providers or local mobility managers through the developed recommendations.

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Applying the Approach Based on Several Social Network Analysis Metrics to Identify Influential Users of a Brand

Kamalzadeh

Haghighat

2021

2021 Eighth International Conference on Social Network Analysis, Management and Security (SNAMS)

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The development of a data collection and analysis system based on social network users’ data

Cited by 4 publications

References 10 publications

Open Innovation in the Shared Mobility Market

Open Innovation in the Shared Mobility Market

A Holistic Approach to Electric Shared Mobility Systems Development—Modelling and Optimization Aspects

Applying the Approach Based on Several Social Network Analysis Metrics to Identify Influential Users of a Brand

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