Toward Mobile Web 2.0-Based Business Methods

Mobile service providers (MoSPs) emerge, driven by the ubiquitous availability of mobile devices and wireless communication infrastructures. MoSPs’ customers satisfaction and consequently their revenues, largely depend on the quality of service (QoS) provided by wireless network providers (WNPs) available at a particular location-time to support a mobile service delivery. This chapter presents a novel method for the MoSP’s QoS-assurance business process. The method incorporates a location- and time-based QoS-predictions’ service, facilitating the WNP’s selection. The authors explore different business cases for the service deployment. Particularly, they introduce and analyze business viability of QoSIS.net, an enterprise that can provide the QoS-predictions service to MoSPs, Mobile Network Operators (as MoSPs), or directly to their customers (i.e. in B2B/B2C settings). QoSIS.net provides its service based on collaborative-sharing of QoS-information by its users. The authors argue that this service can improve the MoSP’s QoS-assurance process and consequently may increase its revenues, while creating revenues for QoSIS.net.

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OpenMobileNetwork

International Journal of Business Data Communications and Networking ◽

10.4018/ijbdcn.2013100103 ◽

2013 ◽

Vol 9 (4) ◽

pp. 46-64 ◽

Cited By ~ 8

Author(s):

Abdulbaki Uzun ◽

Eric Neidhardt ◽

Axel Küpper

Keyword(s):

Network Topology ◽

Linked Data ◽

Service Providers ◽

Open Data ◽

Mobile Network ◽

Base Station ◽

Network Provisioning ◽

Crowdsourced Data ◽

Mobile Network Operators

Mobile network operators maintain data about their mobile network topology, which is mainly used for network provisioning and planning purposes restricting its full business potential. Utilizing this data in combination with the extensive pool of semantically modeled data in the Linking Open Data Cloud, innovative applications can be realized that would establish network operators as service providers and enablers in the highly competitive services market. In this article, the authors introduce the OpenMobileNetwork (available at http://www.openmobilenetwork.org/) as an open solution for providing approximated network topology data based on the principles of Linked Data along with a business concept for network operators to exploit their valuable asset. Since the quality of the estimated network topology is crucial when providing services on top of it, the authors further analyze and evaluate state-of-the-art approaches for estimating base station positions out of crowdsourced data and discuss the results in comparison to real base station locations.

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Design and Implementation Approaches for Location-Based, Tourism-Related Services

Geographic Information Systems ◽

10.4018/978-1-4666-2038-4.ch018 ◽

2013 ◽

pp. 258-294

Author(s):

George Kakaletris ◽

Dimitris Varoutas ◽

Dimitris Katsianis ◽

Thomas Sphicopoulos

Keyword(s):

Service Providers ◽

Value Added ◽

Mobile Network ◽

Mobile User ◽

Security And Privacy ◽

Related Services ◽

Positioning Systems ◽

Business Modelling ◽

Tourism Services ◽

Mobile Network Operators

The globally observed recession of mobile services market has pushed mobile network operators into looking for opportunities to provide value added services on top of their high cost infrastructures. Recent advances in mobile positioning technologies enable services that make use of the mobile user location information, offering intuitive, attractive applications to the potential customer. Mobile tourism services are among the primary options to be considered by service providers for this new market. This chapter presents the key concepts, capabilities, and considerations of infrastructures and applications targeted to the mobile tourist, covering data and content delivery, positioning, systems’ interactions, platforms, protocols, security, and privacy as well as business modelling aspects.

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Framework towards the Process of Estimating or Predicting Perceived QoE Based on the Datasets Obtained the Mobile Network

International Journal of Engineering and Advanced Technology - Regular Issue ◽

10.35940/ijeat.b3523.129219 ◽

2019 ◽

Vol 9 (2) ◽

pp. 3627-3631

Keyword(s):

Artificial Intelligence ◽

Consumer Satisfaction ◽

Quality Of Experience ◽

Research Study ◽

Mobile Network ◽

Mobile Internet ◽

Software Defined Network ◽

Network Functionality ◽

Mobile Network Operators

Nowadays, the research study community visualizes a standard shift that is going to put the focus on Quality of Experience metrics, which relate directly to complete consumer satisfaction. Yet, determining QoE coming from QoS sizes is a daunting job that powerful Software Defined Network operators are currently able to tackle through artificial intelligence strategies. In this paper, our experts pay attention to a few essential QoE factors, and we to begin with proposing a Bayesian Network design to anticipate re-buffering proportion. This paper suggested a structure for modeling mobile network QoE, making use of the vast records analytics approach. The planned platform explains the method of estimating or forecasting perceived QoE based upon the datasets obtained or collected from the mobile network to enable the mobile network operators efficiently to deal with the network functionality as well as supply the individuals an adequate mobile Internet QoE.

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FRAMEWORK FOR MODELLING MOBILE NETWORK QUALITY OF EXPERIENCE THROUGH BIG DATA ANALYTICS APPROACH

Journal of Information and Communication Technology ◽

10.32890/jict2018.17.1.8246 ◽

2017 ◽

Author(s):

Ayisat Wuraola Yusuf-Asaju ◽

Zulkhairi Md. Dahalin ◽

Azman Ta’a

Keyword(s):

User Experience ◽

Data Analytics ◽

Network Performance ◽

Laboratory Experiments ◽

Quality Of Experience ◽

Big Data Analytics ◽

Mobile Network ◽

Mobile Internet ◽

Mobile Network Operators

The increase in the usage of different mobile internet applications can cause deterioration in the mobile network performance. Such deterioration often declines the performance of the mobile network services that can influence the mobile Internet user’s experience, which can make the internet users switch between different mobile network operators to get good user experience. In this case, the success of mobile network operators primarily depends on the ability to ensure good quality of experience (QoE), which is a measure of users’ perceived quality of mobile Internet service. Traditionally, QoE is usually examined in laboratory experiments to enable a fixed contextual factor among the participants even though the results derived from these laboratory experiments presented an estimated mean opinion score representing perceived QoE. The use of user experience dataset involving time and location gathered from the mobile network traffic for modelling perceived QoE is still limited in the literature. The mobile Internet user experience dataset involving the time and location constituted in the mobile network can be used by the mobile network operators to make data-driven decisions to deal with disruptions observed in the network performance and provide an optimal solution based on the insights derived from the user experience data. Therefore, this paper proposed a framework for modelling mobile network QoE using the big data analytics approach. The proposed framework describes the process of estimating or predicting perceived QoE based on the datasets obtained or gathered from the mobile network to enable the mobile network operators effectively to manage the network performance and provide the users a satisfactory mobile Internet QoE.

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Prediction of Churn in Telecom Service: Exploring Call Behaviors and using Machine Learning

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.b7189.129219 ◽

2019 ◽

Vol 9 (2) ◽

pp. 3831-3834

Keyword(s):

Machine Learning ◽

Decision Tree ◽

Customer Service ◽

Service Providers ◽

Mobile Network ◽

High Likelihood ◽

Telecom Service ◽

Number Of Customers ◽

Mobile Network Operators

Churn has a significant impact on mobile network operators and telecommunications service providers. Many studies on churn have been reported, but no one can say that they can create universal human tools for predicting churn or that we can see all the reasons for it. The purpose of this study is to derive the call behavior factors of churning customers and to find ways to reduce the churn of target customers who exhibit these call behaviors. For this, this study uses decision tree and machine learning for the prediction of churn in telecom service. Based on the analysis results, first, the fact that the total number of customers who have more than 316.7 in churn shows that the higher the number of calls, the higher the chance of churn. Second, among customers with total day minutes above 316.7, those with customer service calls above 8.5 show a high likelihood of churn among complaining customers. The overall accuracy is 91.4%. Among the customers who predicted not to be churned, the accuracy that would not be churned was 92.87%, and the accuracy that was churned was 78.4% among the customers predicted to be churned

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Design and Implementation Approaches for Location-Based, Tourism-Related Services

Handbook of Research on Geoinformatics ◽

10.4018/978-1-59140-995-3.ch048 ◽

2010 ◽

pp. 433-468

Author(s):

Stelios C.A. Thomopoulos ◽

Nikolaos Argyreas

Keyword(s):

Service Providers ◽

Value Added ◽

Mobile Network ◽

Mobile User ◽

Security And Privacy ◽

Related Services ◽

Positioning Systems ◽

Business Modelling ◽

Tourism Services ◽

Mobile Network Operators

The globally observed recession of mobile services market has pushed mobile network operators into looking for opportunities to provide value added services on top of their high cost infrastructures. Recent advances in mobile positioning technologies enable services that make use of the mobile user location information, offering intuitive, attractive applications to the potential customer. Mobile tourism services are among the primary options to be considered by service providers for this new market. This chapter presents the key concepts, capabilities, and considerations of infrastructures and applications targeted to the mobile tourist, covering data and content delivery, positioning, systems’ interactions, platforms, protocols, security, and privacy as well as business modelling aspects.

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Design and Implementation Approaches for Location-Based, Tourism-Related Services

Information and Communication Technologies in Support of the Tourism Industry ◽

10.4018/978-1-59904-159-9.ch005 ◽

2011 ◽

pp. 114-161

Author(s):

George Kakaletris ◽

Dimitris Varoutas ◽

Dimitris Katsianis ◽

Thomas Sphicopoulos

Keyword(s):

Service Providers ◽

Value Added ◽

Mobile Network ◽

Mobile User ◽

Security And Privacy ◽

Related Services ◽

Positioning Systems ◽

Business Modelling ◽

Tourism Services ◽

Mobile Network Operators

The globally observed recession of mobile services market has pushed mobile network operators into looking for opportunities to provide value added services on top of their high cost infrastructures. Recent advances in mobile positioning technologies enable services that make use of the mobile user location information, offering intuitive, attractive applications to the potential customer. Mobile tourism services are among the primary options to be considered by service providers for this new market. This chapter presents the key concepts, capabilities, and considerations of infrastructures and applications targeted to the mobile tourist, covering data and content delivery, positioning, systems’ interactions, platforms, protocols, security, and privacy as well as business modelling aspects.

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An Exploration of Antecedents of Initial Trust in M-Payments

Journal of Electronic Commerce in Organizations ◽

10.4018/jeco.2021100105 ◽

2021 ◽

Vol 19 (4) ◽

pp. 80-102

Author(s):

Hemantkumar P. Bulsara ◽

Esha A. Pandya

Keyword(s):

Structural Equation ◽

Service Providers ◽

Positive Impact ◽

Mobile Network ◽

Negative Influence ◽

Equation Modeling ◽

Mobile Service ◽

Cross Sectional Survey ◽

Initial Trust ◽

Cross Sectional

This study aims to investigate factors influencing the formation of consumers' initial trust in m-payments in a developing country such as India. Despite being considered a significant pre-adoption factor, initial trust in m-payments has remained underexplored. To fulfill this research gap, a cross-sectional survey of 1,087 respondents has been conducted, and the analysis has been done using factor analysis and structural equation modeling. Results indicate that consumers' awareness about m-payments and perceived integrity of mobile service providers positively influence initial trust, whereas perceived risks have a significant negative influence, and perceived opportunism of service provider has a marginally significant influence on the formation of initial trust. The findings will be helpful to the m-payment vendors, mobile network operators, and technology providers to enhance trust-building mechanisms in mobile payment systems that can have a positive impact on the adoption and usage of m-payments.

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Challenges of SOA adoption in the Telco domain for Latin American researchers

Revista Facultad de Ingeniería ◽

10.19053/01211129.3547 ◽

2015 ◽

Vol 24 (39) ◽

pp. 9 ◽

Cited By ~ 1

Author(s):

Fernando Mendioroz-Cotelo ◽

Álvaro Rendón-Gallón ◽

Juan Carlos Corrales-Muñoz ◽

Julián Andrés Rojas-Meléndez

Keyword(s):

Latin American ◽

Business Models ◽

Service Providers ◽

Mobile Network ◽

Telecommunication Service ◽

Paradigm Shifts ◽

New Business ◽

Service Oriented ◽

Common Interests ◽

Mobile Network Operators

Telecommunication service providers such as Mobile Network Operators are currently under the vortex arising from paradigm shifts imposed by the omnipresence of the Internet. The adoption of Service Oriented Architecture and the shift to Next Generation Networks constitute some of the efforts of these organizations at the conflence toward these new business models. This article introduces a review of the concepts behind these proposals within Telco organizations, identifis gaps and discusses about the challenges that research and development groups are facing in the Latin American context; obstacles to overcome for converging and creating a synergic environment of common interests oriented to the innovation around the subject.

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