Artificial intelligence applications in the telecommunications industry

Qi, Jiayin; Wu, Feng; Li, Ling; Hu, Shu

doi:10.1111/j.1468-0394.2007.00433.x

Cited by 37 publications

(15 citation statements)

References 103 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Existing literatures have identified the success factors for IT adoption (Oliveira & Martins, 2011) and have examined the process of how companies adopt IT innovations. Previous studies on AI mainly focus on techniques and applications (Qi, Wu, Li, & Shu, 2007;Walczak, 2016). However, organizational or managerial issues regarding AI, particularly, the success factors that affect AI adoption are overlooked.…”

Section: Introductionmentioning

confidence: 99%

Explore success factors that impact artificial intelligence adoption on telecom industry in China

Chen

2020

Journal of Management Analytics

Self Cite

139

142

View full text Add to dashboard Cite

As the core driving force of the new round of informatization development and industrial revolution, the disruptive achievements of artificial intelligence (AI) are rapidly and comprehensively infiltrating into various fields of human activities. Although technologies and applications of AI have been widely studied and factors that affect AI adoption are identified in existing literature, the impact of success factors on AI adoption remains unknown. Accordingly, this paper proposes a framework to explore the impacts of success factors on AI adoption in telecom industry by integrating the technology, organization, and environment (TOE) framework and diffusion of innovation (DOI) theory. Particularly, this framework consists of factors regarding external environment, organizational capabilities, and innovation attributes of AI. The framework is empirically tested with data collected by surveying telecom companies in China. Structural equation modeling is applied to analyze the data. The study provides support for firms' decision-making and resource allocation regarding AI adoption.

show abstract

Section: Introductionmentioning

confidence: 99%

Explore success factors that impact artificial intelligence adoption on telecom industry in China

Chen

2020

Journal of Management Analytics

Self Cite

139

142

View full text Add to dashboard Cite

show abstract

“…Parts of their information systems have become fairly mature. As Figure 2 illustrates, typical information systems include business support systems (BSS), operating support systems (OSS) and management support systems (MSS) (Qi et al 2006(Qi et al , 2007. As marketoriented systems, BSS provide the interface between telecommunication enterprises and their customers and support the overall marketing activities.…”

Section: New Characters Of Information Systems In Telecommunication Ementioning

confidence: 99%

A security evaluation approach for information systems in telecommunication enterprises

Yan

2008

Enterprise Information Systems

View full text Add to dashboard Cite

In recent years, information systems in telecommunication enterprises have been characterised by boundary expansion and increase of departmental-level applications. These changes increase the complexity of security evaluation and pose new challenges to enterprises' information security. Taking into account the behaviour characters of system users, we put forward a system security evaluation approach based on access paths. This approach can help evaluators and users find out potential security risks without figuring out the boundary of systems explicitly. It has no special requirements for system scale and can be used in the evaluation of enterprise-level and departmentallevel systems. This paper also presents the formal definition of access path and related evaluation rules.

show abstract

“…In [27], the author's group investigate the new flexible use of the Hopfield neural network to perform dynamic call admission control. The self-learning approach of the neural network has been used to design a CAC in [28], [29]. According to the literature survey most of the proposed CAC approach, select the number of users as input parameter according to their types of service.…”

Section: Previous Workmentioning

confidence: 99%

Neuro-Fuzzy based Call Admission Control for next Generation Mobile Multimedia Networks

2019

ijeat

View full text Add to dashboard Cite

As the demand of the mobile users are increasing day by day, wireless/mobile multimedia networks still need advancement in terms of, reliable traffic performance, link availability, efficient bandwidth utilization, and user mobility, that can attain extremely consistent wireless communication and data transmission over the networks. Due to the emerging demand of multimedia services a high-speed network and call admission control (CAC) scheme is required, which not only guarantees the quality of services (QoS) for new and handoff calls but also results in optimum resource utilization in bursty traffic network environments. The main objective of this integrated neural fuzzy based CAC scheme is to improve QoS with decent resource allocation, such that it minimizes the probability of call dropping and call blocking in mobile multimedia networks. The proposed neural fuzzy CAC scheme is a hybrid approach that integrates the semantic rule ability of fuzzy logic (FL) controller and self-training capability of a neural network (NN) which is further enhanced to construct an efficient computational model for traffic control and fair radio resources allocation for new calls and handoff calls. The simulation results conclude that a neural fuzzy based CAC can achieve minimal call dropping probabilities and maximum resource utilization in high-speed networks as compared to fuzzy logic based CAC and conventional CAC or existing CAC schemes

show abstract

Artificial intelligence applications in the telecommunications industry

Cited by 37 publications

References 103 publications

Explore success factors that impact artificial intelligence adoption on telecom industry in China

Explore success factors that impact artificial intelligence adoption on telecom industry in China

A security evaluation approach for information systems in telecommunication enterprises

Neuro-Fuzzy based Call Admission Control for next Generation Mobile Multimedia Networks

Contact Info

Product

Resources

About