Theodoros Anagnostopoulos, Chu Luo, Jino Ramson, Klimis Ntalianis, Vassilis Kostakos and Christos Skourlas
The purpose of this paper is to propose a distributed smartphone sensing-enabled system, which assumes an intelligent transport signaling (ITS) infrastructure that operates…
Abstract
Purpose
The purpose of this paper is to propose a distributed smartphone sensing-enabled system, which assumes an intelligent transport signaling (ITS) infrastructure that operates traffic lights in a smart city (SC). The system is able to handle priorities between groups of cyclists (crowd-cycling) and traffic when approaching traffic lights at road junctions.
Design/methodology/approach
The system takes into consideration normal probability density function (PDF) and analytics computed for a certain group of cyclists (i.e. crowd-cycling). An inference model is built based on real-time spatiotemporal data of the cyclists. As the system is highly distributed – both physically (i.e. location of the cyclists) and logically (i.e. different threads), the problem is treated under the umbrella of multi-agent systems (MAS) modeling. The proposed model is experimentally evaluated by incorporating a real GPS trace data set from the SC of Melbourne, Australia. The MAS model is applied to the data set according to the quantitative and qualitative criteria adopted. Cyclists’ satisfaction (CS) is defined as a function, which measures the satisfaction of the cyclists. This is the case where the cyclists wait the least amount of time at traffic lights and move as fast as they can toward their destination. ITS system satisfaction (SS) is defined as a function that measures the satisfaction of the ITS system. This is the case where the system serves the maximum number of cyclists with the fewest transitions between the lights. Smart city satisfaction (SCS) is defined as a function that measures the overall satisfaction of the cyclists and the ITS system in the SC based on CS and SS. SCS defines three SC policies (SCP), namely, CS is maximum and SS is minimum then the SC is cyclist-friendly (SCP1), CS is average and SS is average then the SC is equally cyclist and ITS system friendly (SCP2) and CS is minimum and SS is maximum then the SC is ITS system friendly (SCP3).
Findings
Results are promising toward the integration of the proposed system with contemporary SCs, as the stakeholders are able to choose between the proposed SCPs according to the SC infrastructure. More specifically, cyclist-friendly SCs can adopt SCP1, SCs that treat cyclists and ITS equally can adopt SCP2 and ITS friendly SCs can adopt SCP3.
Originality/value
The proposed approach uses internet connectivity available in modern smartphones, which provide users control over the data they provide to us, to obviate the installation of additional sensing infrastructure. It extends related study by assuming an ITS system, which turns traffic lights green by considering the normal PDF and the analytics computed for a certain group of cyclists. The inference model is built based on the real-time spatiotemporal data of the cyclists. As the system is highly distributed – both physically (i.e. location of the cyclists) and logically (i.e. different threads), the system is treated under the umbrella of MAS. MAS has been used in the literature to model complex systems by incorporating intelligent agents. In this study, the authors treat agents as proxy threads running in the cloud, as they require high computation power not available to smartphones.
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Vassilis Kostakos and Panos A. Kostakos
The purpose of this paper is to present a prototype system that can be used to capture longitudinal socialising processes by recording people's encounters in space.
Abstract
Purpose
The purpose of this paper is to present a prototype system that can be used to capture longitudinal socialising processes by recording people's encounters in space.
Design/methodology/approach
The paper presents the results of a longitudinal study, carried out with members of the public, which demonstrates the capabilities of the system.
Findings
The findings show that community structure can be inferred from physical interactions, and that different locations exhibit varying community structures.
Originality/value
The paper argues that such a system can usefully be deployed in environments where people interact and socialise, as a mechanism for inferring the underlying network structure of those people's relationships.
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Yong Liu, Hongxiu Li, Xiaoyu Xu, Vassilis Kostakos and Jukka Heikkilä
The purpose of this paper is to model the effect of alternative products in motivating consumers’ e-service switching behavior in the context of the social network game (SNG…
Abstract
Purpose
The purpose of this paper is to model the effect of alternative products in motivating consumers’ e-service switching behavior in the context of the social network game (SNG) industry. In particular, the effects of both alternative attractiveness and change experience on switching behavior are quantified.
Design/methodology/approach
With the aid of a leading e-service provider in China, 220,000 questionnaires were distributed to the players of a SNG. Valid responses from potential switching users are included in the data analysis. Structural equation modeling technique is utilized to test the research framework.
Findings
The study found that alternative attractiveness negatively affects both the perceived service quality and individual users’ satisfaction with their current SNG. Additionally, alternative attractiveness has a strong and positive impact on both switching intention and behavior. The results show that users’ satisfaction and perceptions on service quality deteriorate significantly when faced with the presence of attractive SNG alternatives. The effect is stronger for the customers used to switching.
Originality/value
The study is among the first to introduce cognitive dissonance theory to explain e-service switching behavior. A number of new hypotheses are proposed, tested and supported. The results of the study illustrate the use of cognitive dissonance as an alternative perspective of understanding users’ switching behavior in a real-world free-choice situation.