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Data trust is an innovative form of data capitalization. Personal data play a critical role in digital economy and data circulation. To solve the institutional and technical boundaries on personal data access, risk management and going concern that reside in current literature and practice on data trusts, a novel franchised data trust operation mechanism was proposed, which entitled state-owned telecom operators to exercise personal data trusts with the aims of effective personal data protection and sustainable operation of data trusts. The proposal makes a cutting edge exploration on data trusts studies and practice.

The digital twin network is an important direction for the transformation and upgrading of the communication industry, and a key lever for telecom operators to implement national strategies and empower the digital economy.The research results of digital twin maturity in the industry were drawn on, the connotation of digital twin network was analyzed, and a set of digital twin network capability maturity model and evaluation method suitable for telecom operators was put forward.Through systematic description of the development stage of digital twin networks and quantitative evaluation of the maturity of digital twin networks capability, it is helpful for operators to identify technical or organizational weaknesses, improve expected results, and promote innovation and collaboration among different organizations in the industry.

With the increasing inequality of network attack and defense in the Internet era, threat intelligence has become one of the important tools to narrow this gap.Based on the analysis of the research status of threat intelligence at home and abroad, a set of construction methods of threat intelligence systems suitable for telecom operators were proposed, including six steps: intelligence planning, intelligence production, intelligence analysis, intelligence management, intelligence sharing and intelligence application.Meanwhile a set of multi-source intelligence fusion assessment mechanisms was presented, and the technologies and methods were systematically expounded involved in the four stages of intelligence aggregation analysis, intelligence reputation analysis, intelligence correlation analysis and intelligence aging analysis, so as to help the telecom operators build the ability of intelligence fusion analysis.At the same time, the principles of intelligence production and synchronous application were given for intrusion and loss intelligence, which provided a useful reference for telecom operators to apply threat intelligence technology to build a security protection system.

Copyright of Telecommunications Science is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the context of 2G/3G transition, it is a general trend for NB-IoT and LTE Cat.1 to undertake their business development.On the basis of reviewing and analyzing the current status and trends of the 2G/3G-IoT (Internet of things) business, sorting out the IoT business development strategies of the three major domestic telecom operators at the terminal, network and application levels, the three existing business models of telecom operators in the NB-IoT and LTE Cat.1 business area were summarized, including traffic-oriented, platform-supported, and application-enabled.Finally, from three aspects of business opportunity expansion, product marketing and team services, the future upgrade of the business model was prospeted.

Copyright of Telecommunications Science is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Modern telecom operators will have to change their business approach, organization, products development and services development, customer approach and many other important issues if they want to be competitive on the telecom markets in the following years and decades. They will have key roles in this period dubbed the Industry 4.0 era. There are many different models of analysis for telecom operators, but they all have a partial approach to analysis and none of them gives a complete picture of the analysis of telecoms. The Comprehensive Techno-Economic (CTE) model for the analysis of telecom operator potentials is a new and original model for analysis and will significantly help in their transformation processes. This model will enable a quick and easy analysis of the potential of the telecom operator, but also of individual parts of it, regardless of other parts of the company. Despite the fact that the model is easy to define the input data and that it is fast in applying the analysis, it gives precise and mathematically defined results from which one can see the assessment of the potential of telecom or independent assessment of its parts. The main advantages of this model are simplicity, speed of telecom analysis, accuracy of results and its modularity, i.e., independent evaluation of individual parts. Such a model is necessary for telecom operators to achieve fast and reliable potential assessment, analysis, modeling and the easier adaptation of new products and services. This is a unique model with a scientific background and theoretical settings, and it provides practical application in the telecommunication market. [ABSTRACT FROM AUTHOR]

Copyright of Telecommunications Science is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Telecom operators allocate a significant amount of resources to retain their customers as the organic growth in the number of customers is slowing down. Gamified loyalty programs, branded apps, and over-the-top (OTT) services emerged as ways to develop customer acquisition and retention strategies. Despite these strategies, some mobile customers still churn; therefore, churn prediction plays an essential role in the sustainable future of telecom businesses. Churn prediction is used both to detect customers with a high propensity to churn and to identify the reasons behind their churn behavior. This study examines several features affecting the churn behavior of mobile customers, including branded apps, gamified loyalty programs, and OTT services. In this study, the secondary data is provided by a telecom operator and contains the attributes of both churner and non-churner mobile customers. Logistic regression and random forest classifiers are compared in terms of their predictive power, and we used the latter as the machine learning algorithm in the churn prediction model. To understand the variable importance, mean decrease in impurity and permutation importance are performed. The key findings of this research reveal that while gamified loyalty giveaways and branded app strategies are effective, OTT service strategies show lower importance in predicting mobile customer churn behavior. • The usage of company's own OTT apps is not a strong predictor of mobile customer churn behavior. • Gamified loyalty giveaways are very effective strategies for customers' retention. • Remaining Months Before Contract Expiration is an important predictor of CCB. • Unlike Gender, Age is a strong predictor of churn behavior. • Random Forest has a strong predictive power of churn behavior. [ABSTRACT FROM AUTHOR]

SUMBooST2 research develops universally applicable data science methodology which extracts key urban mobility parameters and origin/destination matrices from the anonymized big data set gathered from telecom operator. The methodology (toolbox) provides transport planners with a method for fast, efficient, and reliable provision of data on movements within the certain area. Origin/destination matrices with modal split will provide transport planners with valid input data for the planning of urban transport systems. The algorithms which separate relevant mobility data from the overall dataset are the unique part of the toolbox. The algorithms to identify passenger car trips are developed in 2020 project SUMBooST, and they are being upgraded in 2021 to detect trips made by active mobility modes and public transport. For the methodology to be valid, it must be implemented in representative number of cities. Previous SUMBooST project included implementation and validation in the City of Rijeka, and SUMBooST2 continues with two other cities, City of Zagreb, and City of Dubrovnik. The aim of the paper is to present innovative toolbox for the boost of sustainable urban planning based on big data science.

The quality-of-service (QoS)/quality-of-experience (QoE) demands of mobile services are soaring and have overwhelmed the obsolescent capability of 3G and 4G cellular networks. The emerging 5G networks will bring an unprecedented promotion in transmission data rates. However, the satisfaction of some service requirements is still in dilemma, especially the end-to-end (E2E) latency which varies in different applications. Multi-access edge computing (MEC), a promising technology in 5G cellular networks, can provide ultra-low E2E latency and reduce traffic load on mobile backhaul networks. The potential benefits of MEC for 5G and beyond services have been explored by preliminary studies. What remains is the uncertainty of revenue from the investment of MEC which will shake operators’ decisions about whether and how to deploy MEC in cellular networks. In this light, this paper designs a MEC-assisted 5G and beyond ecosystem inclusive of three players: private (local) telecom operators, backhaul, and cloud service owners. We propose a revenue maximization model for private (local) telecom operators and cloud service owners to minimize the cost from the end-user perspective while satisfying the latency requirement. The derived model indicates that two players’ revenues can be maximized by optimizing MEC resources and backhaul capacity. The game-theoretic analyses also reveal the optimized hybrid strategy of MEC and cloud for efficient mobile traffic management.

SUMBooST2 research develops universally applicable data science methodology which extracts key urban mobility parameters and origin/destination matrices from the anonymized big data set gathered from telecom operator. The methodology (toolbox) provides transport planners with a method for fast, efficient, and reliable provision of data on movements within the certain area. Origin/destination matrices with modal split will provide transport planners with valid input data for the planning of urban transport systems. The algorithms which separate relevant mobility data from the overall dataset are the unique part of the toolbox. The algorithms to identify passenger car trips are developed in 2020 project SUMBooST, and they are being upgraded in 2021 to detect trips made by active mobility modes and public transport. For the methodology to be valid, it must be implemented in representative number of cities. Previous SUMBooST project included implementation and validation in the City of Rijeka, and SUMBooST2 continues with two other cities, City of Zagreb, and City of Dubrovnik. The aim of the paper is to present innovative toolbox for the boost of sustainable urban planning based on big data science. [ABSTRACT FROM AUTHOR]

In recent years, the telecom industry has faced digital transformation challenges and fierce market competition. The challenges push telecom operators to grow their subscriber bases by offering lower prices and improved services and new features, which puts pressure on operators' profitability. In addition, the rise of Internet companies gradually erodes the profit of the traditional telecom operators. Therefore, paying attention to the critical factors impacting firm sustainable growth can help operators get out of the predicament. Based on the resource-based view (RBV), this study explores the factors that influence the firm sustainable growth. Multiple regression model is applied to empirically test the hypotheses with longitudinal time-series panel data from major telecom operators in China. The study provides empirical evidence for sustainable growth research and useful insights for practitioners on the way to keep sustainable growth. [ABSTRACT FROM AUTHOR]

With the implementation of cryptography law,the application of cryptography in information system in China has been promoted to the legal level,which requires the application of public key infrastructure in the mutual trust of network entities to be strengthened.A scheme of constructing unified telecom public key infrastructure with strict hierarchical structure was proposed,that is,establishing a national telecom root CA as a trust anchor,and each major telecom operator becomes an independent sub-ca,forming a certificate trust chain of “national telecom root CA- telecom operator sub-ca” and providing PKI security services.This scheme can not only realize the mutual recognition between telecom operators,but also help unify the telecom public key infrastructure to become a globally trusted electronic authentication service provider,so as to have more influence and say in the formulation of international certification standards.

Blockchain is another disruptive technological revolution after the IoT,cloud computing and big data.Blockchain technology and typical application cases were firstly introduced,and then the role of blockchain technology and blockchain in operators were analyzed.Secondly,combined with the characteristics of the blockchain,the application of blockchain in multiple operators were focused on,such as infrastructure,international roaming settlement,digital points issuance and trading,data storage,cross-border payment,identity verification,and credit reporting.Finally,the challenges faced by operators in the comprehensive application of blockchain were introduced.

The subject of the article is the architecture of information systems of telecom operators (BSS/OSS), requirements for it and the processes of its transformation. The goal is to transform the existing information environment of the operator into an open digital ecosystem, in accordance with business and technological requirements for the functionality and architecture of information systems of communication operators, which will introduce new business models, services and products, communication channels, and increase competitiveness. The following tasks were solved at the study: analysis of the current state of telecommunications and information systems used by telecom operators; analysis of requirements for business support and operational information systems, collection and analysis of requirements for the architecture of modern information systems in the field of telecommunications, analysis of the transformation process from the existing BSS/OSS architecture of the communication operator into the target architecture of the digital communications provider, elaboration of a recommendations for an intermediate architecture. To solve these problems, methods of system and business analysis were used, in particular, methods of analysis of software requirements, technologies for developing software application architecture. The following results were obtained. The current state of the telecommunications services industry, the features of the existing information systems of telecommunications operators (BSS/OSS) and the requirements for the architecture of such systems was analyzed. Strategies of transition to modern architecture was considered and analyzed. The target architecture of the digital service provider's information ecosystem and the process of transforming the existing BSS/OSS architecture into the target architecture were considered. Intermediate migration architecture was proposed. Conclusions: the transformation to modern information architecture will ensure compliance of BSS/OSS systems with market requirements and new technologies, adapt to their changes, allow operators to increase competitiveness, reduce operating and capital costs, create technological conditions for open digital ecosystem and transform the operator into a digital services provider. It was recommended to use an intermediate architecture based on the open standardized TMF API for such transformation.

In recent years,the development of IoT is in full swing.It is of great significance for the current transformation and development of domestic telecom operators.In this context,the business model is very important for operators to achieve “overtaking” in the IoT industry.Based on the analysis of the operation status of the IoT of operators,the development strategies of the IoT industry at home and abroad were compared,and three different development strategies was summarized.Telecom operators had advantages in customers,channels and other aspects,but limited by many factors.It was suggested that in constructing the development model,they should follow the principle of gradual progress,fully according to their own enterprise positioning,combined with national policies,pay attention to their own positioning in the industry chain of the IoT,pay attention to risks,and ultimately realize it.Better development model improve the current situation of increasing revenue in the telecommunications industry.

Modern telecom operators will have to change their business approach, organization, products development and services development, customer approach and many other important issues if they want to be competitive on the telecom markets in the following years and decades. They will have key roles in this period dubbed the Industry 4.0 era. There are many different models of analysis for telecom operators, but they all have a partial approach to analysis and none of them gives a complete picture of the analysis of telecoms. The Comprehensive Techno-Economic (CTE) model for the analysis of telecom operator potentials is a new and original model for analysis and will significantly help in their transformation processes. This model will enable a quick and easy analysis of the potential of the telecom operator, but also of individual parts of it, regardless of other parts of the company. Despite the fact that the model is easy to define the input data and that it is fast in applying the analysis, it gives precise and mathematically defined results from which one can see the assessment of the potential of telecom or independent assessment of its parts. The main advantages of this model are simplicity, speed of telecom analysis, accuracy of results and its modularity, i.e., independent evaluation of individual parts. Such a model is necessary for telecom operators to achieve fast and reliable potential assessment, analysis, modeling and the easier adaptation of new products and services. This is a unique model with a scientific background and theoretical settings, and it provides practical application in the telecommunication market.

With the Ministry of Industry and Information Technology announcing that it has issued a test frequency license to China Telecom, China Mobile and China Unicom for the low and medium frequency band of the 5G mobile communication system, China's 5G commercial pace has officially begun. The global deployment, commercial situation and the oriented industrial network characteristics of 5G were introduced. It was pointed out that 5G would continue to consolidate the foundation for interconnectivity of all things, fully enable the industrial internet, and accelerate the integration of multi-industry internet.

Copyright of Telecommunications Science is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Over-the-top (OTT) service refers to content included in basic telecommunications subscriptions without the additional features provided by telecom operators. The booming OTT business has had a huge impact on traditional telecommunications businesses such as voice and short message services, and the sense of crisis among telecommunications operators shows that the channeling trend has become more and more obvious. Faced with competition on the distribution of interests between channels and contents, telecommunications operators and OTT service providers are engaged in a fierce competition and cooperation game. To explore this competition relationship, this paper first establishes an evolutionary model, discussing the competition and cooperation behaviors of telecommunications operators and OTT service providers, and then conducts research on the degree of the effects of cooperation in terms of the combination of strategic factors, including cooperation cost sharing, the benefits distribution mechanism, research and development benefits, spillover effect, and network externality. Additionally, a replicator dynamic system is developed to study the influence of related strategic factors on evolutionary equilibrium. Finally, to verify the theoretical results, a simulation experiment is conducted to further clarify the meaning of the model and obtain meaningful results. The evolutionary game model and method provided in this paper are expected to help both parties make better decisions for future operating strategies. [ABSTRACT FROM AUTHOR]

Copyright of Telecommunications Science is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In the era of rapid development of big data,telecom operator has abundant big data assets and need to unlock the potential of huge data in pipelines through the innovation and development of big data services urgently.The construction of telecom big data ecosystem would help telecom operator solve the problems encountered in the development of big data services effectively and new value growth would be brought out.The target form and construction steps of telecom big data ecosystem were also clarified.

The development of big data at home and abroad was reviewed.On the basis of carefully analyzing the background,advantages and current situation of the development of big data,it was thought that the further development of telecommunication big data was the main component of promoting the national big data strategy project,and suggestions to promote the deepening development of telecom operators’ big data was proposed.

The challenge and demands of telecom operator’ digital marketing were briefly analyzed,the advantages of internet thought were also drawled and then the personalized recommendations were proposed to help telecom operator’s digital marketing,and the history of carrier’s personalized recommendation was introduced.Then the principle and implementation process of telecom operator’s personalized recommendation which bases on carrier merchandise,user behavior data and the computing ability of big data platform was described.Finally,the implementation scenario of personalized recommendation in telecom operator digital content business was described,and the value and future of personalized recommendation have prospected.

With the popularity of big data and cloud computing technology,data of telecom operators collected is increa-singly larger,and much more various.The data faces the risk of broken security management,hacker attacks,and imper-fection of risk assessment,etc.The current situation of data security in the environment was analyzed,and a more com-plete data security implementation plan was put forward.From the two aspects of data security technology and manage-ment,several strategies were proposed,including security classification,privacy protection,data desensitization encryption and security protection.The proposed schema has been implemented in China Telecom data security protection project.

Mobile data traffic increases gradually.Operator's business model is transferring from “telephone traffic management” to “traffic management”.Big data management will become the main development direction of operators.For big data management,operators explore the value and application of DPI technology and make the unified DPI system standards to offer comprehensive and standard traffic data.The insufficiency of traditional DPI deployment mode was analyzed,and the unified DPI system to offer basic data security for accelerating development of big data was presented.

Copyright of Telecommunications Science is the property of Beijing Xintong Media Co., Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

From the perspective of some enterprises' big data value technology, despise application, value construction and despise operation problems, the importance of business innovation for big data transformation of enterprises was discussed, the characteristics of big data business innovation were analyzed and combined with the characteristics of telecom operators business and data, the big data business innovation mode suitable for telecom operators was studied, the functional framework of business innovation support system was designed, the implementation strategies and suggestions were proposed.

The concept of artificial intelligence has been proposed for more than 60 years，with the development of internet of things and big data technology，more and more AI technology applications have been achieved.One of the most remarkable AI technology integration application is automatic driving technology.Firstly，the progress of automatic driving technology was studied.Secondly，key technologies of automatic driving were analyzed.Thirdly， the relationship between the telecom operator information service architecture and the requirements of automatic driving was analyzed.In the end，the technology breakthrough point of information service architecture with the core of application of artificial intelligence technology in the future were given.