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This paper presents a systematic approach for solving complex prediction problems with a focus on energy efficiency. The approach involves using neural networks, specifically recurrent and sequential networks, as the main tool for prediction. In order to test the methodology, a case study was conducted in the telecommunications industry to address the problem of energy efficiency in data centers. The case study involved comparing four recurrent and sequential neural networks, including recurrent neural networks (RNNs), long short-term memory (LSTM), gated recurrent units (GRUs), and online sequential extreme learning machine (OS-ELM), to determine the best network in terms of prediction accuracy and computational time. The results show that OS-ELM outperformed the other networks in both accuracy and computational efficiency. The simulation was applied to real traffic data and showed potential energy savings of up to 12.2% in a single day. This highlights the importance of energy efficiency and the potential for the methodology to be applied to other industries. The methodology can be further developed as technology and data continue to advance, making it a promising solution for a wide range of prediction problems.

A revolution in wireless communication began in the first decade of the 20th century with the pioneering developments in radio communications by Guglielmo Marconi, who won the Nobel Prize in Physics in 1909. Other highly notable pioneering inventors and developers in the field of electrical and electronic telecommunications include Charles Wheatstone and Samuel Morse (telegraph), Alexander Graham Bell (telephone), Edwin Armstrong, and Lee de Forest(radio), as well as Vladimir K. Zworykin, John Logie Baird and Philo Farnsworth (television). In this paper we have discuss about the services and the quality with basic comparison between the different telecom companies. Numbers of telecom companies providing telecom services in Saudi Arabia which includes fixed and cellular phones as well as internet and issues relating to the provision of other services. Main telecom companies in Saudi Arabia are: STC, Mobily, Zain, ITC, GO Telecom (Etihad Atheeb Telecom), Bayanat and Arab Satellite Communications Organization. Saudi Telecom Company (STC) is the first company in Saudi Arabia, and then allowed Communications Commission to compete with other companies in Saudi Arabia and then it becomes a number one of telecom companies. In Saudi Arabia five companies are in competition: STC Mobile: STC includes landlines, mobile, mobile (phone) and Sawa; ITC (Integrated Telecom Company): second operator after STC and offers internet, broadband, connectivity and satellite services for businesses, consumers and wholesale; Mobily: It provide mobile and internet Fabraupetk (Fiber Optic) New Ground; Zain: its provide only mobile services; GO ATHEEB: A Saudi modern, with an Internet connection line is similar to Ground.

Over two decades, telecommunication market has been continuing a huge growth in urban, semi-urban and rural regions of India. Investigating and choosing the desirable cellular mobile telephone service providers (TSPs) based on operative constraint can facilitate to obtain the ideal of TSPs selection. Here, the evaluation commonly encompasses different TSP options under various operational factors; thus, the assessment of TSPs can be considered as a rigorous multi-criteria decision-making (MCDM) issue. This paper initiates a structure for the exploration of the TSPs in the Madhya Pradesh region, India. To do this, a framework associated with grey relational analysis (GRA) on intuitionistic fuzzy sets (IFSs) is planned to obtain the performance of various telecom participants. The developed approach is based on the conception of the best and worst solutions. To find the attribute weights, a divergence measure is developed and employed by relative comparisons. Additionally, to show the proficiency and practicality, a selection problem of TSPs options of Madhya Pradesh circle, India is presented within the IFSs context. By employing the developed model, an expert can enlarge tactics to enhance the performance by standard operational factors. Comparison and sensitivity analysis are considered to validate the developed approach in the prioritization of the TSPs options.

Purpose – The purpose of this paper is to develop a total interpretive structural modelling (TSIM) of strategic factors related to performance management in the context of Indian Telecom Service Providers taking dual perspectives in account, i.e. enterprise perspective and subscribers’ perspective. Design/methodology/approach – An evolving performance management framework, i.e. flexible strategy game-card has been taken as the basis to develop the strategic performance management model, where strategic factors have been identified through thematic content analysis and the hierarchical structure of factors has been developed using TISM. Findings – Two total interpretive structural models have been developed, one for enterprise-related strategic factors, and another for subscriber-related strategic factors. These hierarchical structures portray the leading and lagging factors of performance, and showcase that financial performance indicators are the lagging indicators. Research limitations/implications – This study has implications for both practitioners and academics. For practitioners, it provides an indicative list of strategic factors relevant for Indian telecom companies, which drive better financial results as well as a list of strategic factors that subscribers consider while assessing the performance of telecom operators. For academics, the methodology used provides a mechanism to conduct an exploratory study by identifying the variables of interest and highlighting their interactions through hierarchical structures. Originality/value – The proposed strategic performance management models developed through qualitative modelling technique is a new effort altogether in the context of Indian telecom operators’. Capturing subscribers’ perspective of firm's performance is neglected in existing performance management literature, and this study makes a contribution in this regard.

Telecommunications is a customer-oriented industry in which client satisfaction is crucial for an organization's survival. Social media plays a vital role in customer decisions, acting as both a search tool and a communication channel. On social media platforms, customers can air their grievances, and a company can use these complaints to improve its products and services. During the first quarter of 2022, sentiment analysis was conducted to evaluate customer satisfaction with telecom services in Saudi Arabia. With a machine-learning approach, more than 90K comments were recorded and categorized as positive, negative, or neutral. For the classification, we utilised a support vector machine (SVM) model with an average accuracy of 88%. After that, We utilised thematic analysis of social engagement opinions. We identified seven themes among the comments related to factors affecting efficiency and satisfaction with telecommunications services: product, package, price, promotion, place, people, and public relations. In conclusion, we recommend some solutions to improve efficiency and increase customer satisfaction in the telecom sector.

In today's digital age, most individuals own smartphones and routinely use telecom services. As a result, understanding users' intentions to continue using specific mobile carriers based on their experiences becomes paramount for corporate sustainability. This study delves into the intricate dynamics of user experiences, aiming to elucidate the primary factors influencing continuance intention. By incorporating a unique theoretical framework that emphasizes customer experiences, this research seeks to bridge a gap in the current literature. Drawing from a sample size of 299 smartphone users who have active subscriptions with telecom services, we employed partial least squares structural equation modeling (PLS-SEM) to rigorously analyze the data. Our findings indicate a significant relationship where the corporate image is influenced by factors such as contract terms, perceived fees, call quality, and call center experience. Moreover, user satisfaction, another pivotal variable, is shaped by the same factors. Both corporate image and user satisfaction were found to be determinants of a user's continuance intention. The distinguishing value of this research lies in its holistic approach to user experience, uniquely integrating various service touchpoints to provide comprehensive insights into user intentions in the telecom domain.

The deepening integration of telecommunication technology into other industries has giving birth to a variety of new applications, such as self-driving, telemedicine, and intelligent manufacturing. Whether the telecom service is traditional or new, users put forward personalized and multidimensional requirements for performance, which results in a conflict between their requirements for customized service and the failure of telecom enterprises to meet every requirement. This contradiction directly influences the sustainability and stable development of the telecom industry. To address this problem, this paper carried out systematic research into collaboration and adaptation between business-model and technological innovation. From the view of business-model innovation, this paper proposes a novel service provision mode named Multidimensional Customization of Telecom Services for Each User to analyze the value of the business model and the factors that influence it. From the view of technological innovation, it will design an implementation scheme corresponding to the business model, and verify its advantages in network-carrying capacity and significance to enterprises’ business value through a simulation experiment. The research shows that the novel mode is beneficial both to telecom users and telecom enterprises. In addition, it addresses this novel mode’s impact on environmental sustainability and the regulation of the telecom industry, as well as the limitations of this research and future research directions.

The recent pandemic has affected the world in many aspects including, communication. Telecom and internet-based communication have witnessed a drastic upsurge due to lockdown and consequent work-from-home situation, being termed as the new normal. Due to the low switching costs and stiff competition, telecom service providers are struggling hard to attract new customers and prevent the existing ones from switching to rival telecom service providers. Hence this study is undertaken with an aim to discover the key factors in the order of their relative worth that could be focused upon by the telecom companies to prevent their customers from churning. For the study, linear discriminant analysis was applied on the collected dataset to predict the customers’ churn behavior. It was found that tariff rates for domestic calls and the number of calls made to the customer service were the significant predictors of the customer churn behavior.

The recent launch of 4G in India initiated disruption in telecom sector with price wars. Knowing the consumers’ willingness to pay (WTP) is vital step toward the survival in such a turbulent situation. We present Van Westendorp price sensitivity model to assess the range of acceptable price as well as the optimal prices for 2 GB and 5 GB data packs to understand the consumer’s WTP for 4G data services. The price sensitivity meter identifies the acceptable range and optimal price points. The estimates obtained are similar to the current prices of the data packs in the same telecom circle which validates suitability of the price sensitivity model.

Switching barriers help telecom service providers create intangible restriction before telecom subscribers preventing them from switching to other service providers. This study aims at ranking the switching barriers to identify critical success factors of telecom service providers to retain customers and attain a competitive advantage in the market. The analytical hierarchy process (AHP) is used as a tool to rank the identified switching barriers. The literature review helped in identifying eight crucial switching barriers which were ranked using the AHP method. A pair-wise comparison is made to obtain opinions from 32 experts and consultants in the field of telecom service provider industry to conduct AHP analysis. The AHP is analysed by pair-wise comparisons generated from expert opinions. The research findings helped in understanding the different priorities and corresponding weights of switching barriers which were eventually ranked based on the weights. This study enables the telecom service providers to adopt suitable strategies based on the ranking. This will help telecom service providers retain customers and thereby gain a competitive advantage.