Competition In Telecommunications Research Articles

Strategic Approach Adopted by Airtel to Stand Strongly in the Competitive Telecom Market

Bharti Airtel's strategy measures to survive in the cutthroat telecom business are examined in depth in this research.

통신사 서비스에서의 교차 구매 행동에 대한 고객 충성도 모델 개발

The purpose of this study is to examine the effect of information quality(IQ) on customer satisfaction and loyalty within cross-buying contexts in the telecommunications industry. The research uses a survey of 215 participants and a structural equation model to analyze how IQ influences loyalty, employing Cronbach's alpha(CA), correlation, and confirmatory factor analysis(CFA) for measurement validity. Results indicate that all indicators, including word of mouth(WOM) and accessibility IQ, show high reliability(CA > 0.7). The model demonstrates that customer satisfaction—mediated by contextual IQ—affects loyalty significantly. This investigation highlights the critical role of IQ in fostering loyalty and satisfaction in Korea's competitive telecom market, emphasizing the need for precise information delivery while avoiding spam. It also points to the necessity of future research on user needs in loyalty building, particularly in scenarios where secondary purchases accompany primary ones.

Customer Retention Analysis for Telecom Industry

Abstract: In today’s highly competitive telecom industry, retaining customers is vital for sustaining business growth and profitability. Customer churn, the phenomenon where customers switch from one service provider to another, poses a significant challenge for telecom companies. Predicting churn can help these companies take proactive measures to retain valuable customers. This study explores the application of machine learning algorithms for predicting customer churn in the telecom industry. Additionally, the research contributes to the existing body of knowledge in the field of customer churn prediction, showcasing the potential of machine learning algorithms in addressing complex business challenges.

Investigating the Relationship Between Brand Equity and Customer Loyalty the Moderating Effect of Customer Satisfaction in the Telecom Industry

The study explores the connection between brand equity and customer loyalty in the telecom industry. It specifically examines how customer satisfaction plays a moderating role in this relationship. The research employed structural equation modeling and involved 386 Ethio telecom customers. Several aspects were evaluated, including reliability, convergent validity, and sample adequacy. The study's findings highlight a strong positive correlation between brand equity and customer loyalty within the telecom industry. Factors such as positive brand image, perceived quality, brand awareness, and brand associations were found to have significant influences on customer loyalty. Furthermore, customer satisfaction was identified as a moderator, enhancing the positive impact of brand equity on loyalty. Based on the results, the study emphasizes the importance of brand equity and customer satisfaction in fostering loyalty in the telecom industry. It suggests that telecom companies should invest in building a strong brand image, improving perceived quality, increasing brand awareness, and cultivating favorable brand associations. Policymakers and regulators are also encouraged to create a competitive telecom market that promotes innovation, high-quality service delivery, and reasonable pricing. The practical implications of these findings are significant for the industry. They underscore the need for strong brand equity strategies and the delivery of exceptional customer experiences. By prioritizing these aspects, telecom companies can enhance customer loyalty and gain a competitive advantage in the market.

Telecom customer churn prediction model : Analysis of machine learning techniques for churn prediction and factor identification in telecom sector

This research project leverages exploratory data analysis (EDA) on a telecom company’s customer data to predict user churn. Utilizing Python and its libraries, including Pandas, NumPy, Matplotlib, and Scikit-Learn, it identifies key parameters crucial for accurate predictions. The results and predictions are visualized using the Flask framework and Power BI analytics tool. In the highly competitive telecommunications sector, customer churn poses a significant challenge, with an annual churn rate of 15-25%. This study addresses the escalating phenomenon of consumers freely switching between providers, leading to financial losses for businesses. By employing machine learning models, it aims to forecast potential churners, enabling companies to focus targeted retention efforts and mitigate losses. The tool’s efficacy lies in its ability to analyze patterns among churned users, offering a solution to a pressing issue in the telecom industry. Beyond its immediate application, this tool can be extended to other industries, providing valuable insights for customer retention strategies.

Customer Retention Analysis for Telecom Industry

Abstract: In today’s highly competitive telecom industry, retaining customers is vital for sustaining business growth and profitability. Customer churn, the phenomenon where customers switch from one service provider to another, poses a significant challenge for telecom companies. Predicting churn can help these companies take proactive measures to retain valuable customers. This study explores the application of machine learning algorithms for predicting customer churn in the telecom industry. Additionally, the research contributes to the existing body of knowledge in the field of customer churn prediction, showcasing the potential of machine learning algorithms in addressing complex business challenges.

Experience Marketing and Customer Retention in the Nigerian Telecommunications Industry

The Nigerian Telecommunications Industry is classified as the fastest-growing and most competitive Telecommunications industry in the world. It has the largest subscriber base in Africa with over 150 million subscribers. Due to the increased competitiveness in the telecommunication industry in Nigeria, customer retention has become the focus of telecommunication providers. It is in this light that this paper is built. Hence, the general objective of the paper is to determine the effect of experience marketing on customer retention in the Nigerian Telecommunications industry. The study made use of primary data gotten through a validated set of structured questionnaires which was distributed to a selected sample of 402 respondents within the six states of the south-south geo-political zone of the Niger Delta Area of Nigeria, which are Akwa-Ibom, Bayelsa, Calabar, Edo, Delta and River States. The paper adopted correlation and regression analysis to test the formulated research questions and hypotheses. After the analysis, it was discovered that there was a strong and positive effect of experience marketing on customer retention in the Nigerian Telecommunications industry. The study, therefore, concluded that Customer Service Quality, Customer Brand Relationship, and Customer Emotional Experience are good indicators and dimensions of Experience Marketing that could increase the degree to which customer retention is enhanced in Telecommunication Firms in Nigeria. Hence, it was recommended, among others, that Telecommunication operators in Nigeria must switch from the traditional marketing approach to an experience-based marketing strategy if they want to remain relevant and competitive in the globalised telecommunication industry.

Impact of Quality of Service on Customer Loyalty: A Critical Study of Cellular Mobile Broadband Sector in Pakistan

Quality of Service (QoS) is the degree to which a service provided by an operator promotes customer satisfaction. In telecommunications sector service quality is a set of specific parameters provided by service providers to their customers, which are necessary for achieving the required functionality of the requested service. In current global competitive telecommunication business market, the quality of a service is being considered as a differentiator for users if service features or price of services of service providers are similar. The potential of growth and scope for telecommunication services in general and mobile broadband services in developing countries like Pakistan is encouraging. The objective of this research work is to analyze the impact of service quality gaps with customer loyalty in the mobile broadband sector of Pakistan. The cellular mobile operators in Pakistan are facing issue of declining customer loyalty and increasing churn rate of customers in search of their expected quality of service. In this research the service quality gaps will be considered as independent variables while customer loyalty as dependent variable. The SERVQUAL model proposed by Parasuraman, Zeithaml and Berry (1988) will be used to probe the effects of five dimensions of service quality viz. tangibility, assurance, responsiveness, reliability, and empathy on consumer loyalty. Data of 200 current LTE broadband consumers using mobile service of four cellular mobile operators of Pakistan (Jazz-PMCL, Ufone-PTML, Zong-CMPak and Telenor) will be collected through structured questionnaires. The response received from end users of broadband services through these questionnaires will be analyzed through SPSS to determine the causal relationship of service quality dimensions and customer loyalty. The results of analysis will depict that the service quality dimensions will have significant and positive impact on customer loyalty.

Formulation Strategy of Kisel SIM Card’s Facing Business Digitalization in Telecommunications Industry

However, for starter pack sellers, this prepaid card re-registration policy has decreased starter pack sales, previously the policy was applied to merchants who could enjoy the benefits of buying and selling starter packs by selling an average of 100 starter packs per day. This has an impact on the performance of the packing business and the manufacture of starter packs in the Cellular Telecommunications Cooperative (KISEL). There was a decline in sales on SIM cards from 2018 to 2020. This research was conducted at the Sim Card Logistics Management Department with the legal entity Cellular Telecommunications Cooperative (KISEL). The author analyzes the declining production of SIM card and its impact on employee well-being and focuses on the development of SIM card strategies in the face of business digitization in the increasingly competitive telecommunications industry. To obtain the results of priority strategy analysis, data processing and analysis techniques were carried out using 7s Mckinsey Analysis, PESTLE Analysis, Internal Factor Evaluation (IFE) Analysis, External Factor Evaluation (EFE) Analysis, Internal-External Matrix (IE), SWOT Analysis, SWOT Matrix, QSPM Analysis (Quantitative Strategic Planning Matrix). Based on the results, priorities of Kisel's strategy include: first is the procurement and targeting of ideal machines for faster delivery processes, increasing promotion and popularity through social media, the third is Improving adaptive work culture with new lifestyle habits, fourth Improving facilities and facilities for employees and the last is Coordinating intensive with new partners to negotiate the fulfillment of raw material needs. Keywords: SWOT, QSPM, Kisel, Internal-External Matrix, Digitalization

A Novel Telecom Customer Churn Analysis System Based on RFM Model and Feature Importance Ranking

Aim/Purpose: In this paper, we present an RFM model-based telecom customer churn system for better predicting and analyzing customer churn. Background: In the highly competitive telecom industry, customer churn is an important research topic in customer relationship management (CRM) for telecom companies that want to improve customer retention. Many researchers focus on a telecom customer churn analysis system to find out the customer churn factors for improving prediction accuracy. Methodology: The telecom customer churn analysis system consists of three main parts: customer segmentation, churn prediction, and churn factor identification. To segment the original dataset, we use the RFM model and K-means algorithm with an elbow method. We then use RFM-based feature construction for customer churn prediction, and the XGBoost algorithm with SHAP method to obtain a feature importance ranking. We chose an open-source customer churn dataset that contains 7,043 instances and 21 features. Contribution: We present a novel system for churn analysis in telecom companies, which encompasses customer churn prediction, customer segmentation, and churn factor analysis to enhance business strategies and services. In this system, we leverage customer segmentation techniques for feature construction, which enables the new features to improve the model performance significantly. Our experiments demonstrate that the proposed system outperforms current advanced customer churn prediction methods in the same dataset, with a higher prediction accuracy. The results further demonstrate that this churn analysis system can help telecom companies mine customer value from the features in a dataset, identify the primary factors contributing to customer churn, and propose suitable solution strategies. Findings: Simulation results show that the K-means algorithm gets better results when the original dataset is divided into four groups, so the K value is selected as 4. The XGBoost algorithm achieves 79.3% and 81.05% accuracy on the original dataset and new data with RFM, respectively. Additionally, each cluster has a unique feature importance ranking, allowing for specialized strategies to be provided to each cluster. Overall, our system can help telecom companies implement effective CRM and marketing strategies to reduce customer churn. Recommendations for Practitioners: More accurate churn prediction reduces misjudgment of customer churn. The acquisition of customer churn factors makes the company more convenient to analyze the reasons for churn and formulate relevant conservation strategies. Recommendation for Researchers: The research achieves 81.05% accuracy for customer churn prediction with the Xgboost and RFM algorithms. We believe that more enhancements algorithms can be attempted for data preprocessing for better prediction. Impact on Society: This study proposes a more accurate and competitive customer churn system to help telecom companies conserve the local markets and reduce capital outflows. Future Research: The research is also applicable to other fields, such as education, banking, and so forth. We will make more new attempts based on this system.

Governing digital circulation: the quest for data control and sovereignty in Germany

ABSTRACT How is the circulation of digital data to be governed? This question is the subject of often conflicting political rationalities. Focusing on internet and data politics in Germany, we identify fundamental problematizations in governing data circulation on the basis of a mixed-methods analysis of the public–political discussion. In doing so, we elaborate the genealogy of a tension between two political rationalities. On the one hand, there are the political rationalities of a global information society since the 1990s. These have propelled the free circulation of data across national borders and Germany’s integration into an international and competitive telecommunications and information technology market. In these rationalities, state intervention in the circulation of data is seen as a dangerous obstacle to economic competitiveness and social prosperity. On the other hand, there are the political rationalities of a digitally sovereign statehood since the early 2010s. These consider state intervention in data circulation as a guarantor of economic prosperity, democracy and the ability to govern. We argue that prominent political technologies of territorial regulation of data circulation currently discussed and experimented within Germany can be interpreted as attempts to harmonize this field of tension.

Intelligent Decision Forest Models for Customer Churn Prediction

Customer churn is a critical issue impacting enterprises and organizations, particularly in the emerging and highly competitive telecommunications industry. It is important to researchers and industry analysts interested in projecting customer behavior to separate churn from non-churn consumers. The fundamental incentive is a firm’s intent desire to keep current consumers, along with the exorbitant expense of gaining new ones. Many solutions have been developed to address customer churn prediction (CCP), such as rule-based and machine learning (ML) solutions. However, the issue of scalability and robustness of rule-based customer churn solutions is a critical drawback, while the imbalanced nature of churn datasets has a detrimental impact on the prediction efficacy of conventional ML techniques in CCP. As a result, in this study, we developed intelligent decision forest (DF) models for CCP in telecommunication. Specifically, we investigated the prediction performances of the logistic model tree (LMT), random forest (RF), and Functional Trees (FT) as DF models and enhanced DF (LMT, RF, and FT) models based on weighted soft voting and weighted stacking methods. Extensive experimentation was performed to ascertain the efficacy of the suggested DF models utilizing publicly accessible benchmark telecom CCP datasets. The suggested DF models efficiently distinguish churn from non-churn consumers in the presence of the class imbalance problem. In addition, when compared to baseline and existing ML-based CCP methods, comparative findings showed that the proposed DF models provided superior prediction performances and optimal solutions for CCP in the telecom industry. Hence, the development and deployment of DF-based models for CCP and applicable ML tasks are recommended.

THE IMPACT OF SOCIAL MEDIA ON GEN-Y EMPLOYEES’ WORK PERFORMANCE IN A TELCO, MALAYSIA

Generation-Y (Gen-Y) is the largest generational cohort in the global workforce, surpassing 50 percent in 2020, making them the most influential group to impact work performance. Highly competitive telecommunication companies continuously look for ways to improve employees' work performance. This research focuses on how social media improves the work performance of Gen-Y employees of a telco in Malaysia through social media use, shared vision, network ties, trust, and knowledge transfer. This research discovered an insignificant relationship between social media use at the workplace and work performance. This is because social media is currently not an official workplace tool, and its usage is limited among Gen-Y employees in the telco. It was also uncovered that using social media to act as a tool to gain trust did not influence work performance, even though the telco's primary official communication tool is email and a mobile app for communication and collaboration purposes. Nevertheless, this research uncovered that shared vision, network ties, and knowledge transfer is significant for the telco's Gen-Y employees to enhance their work performance. In conclusion, the telco's management can leverage social media to improve the work performance of Gen-Y employees by developing a social media strategy to provide a suitable framework with proper guidelines, policies, and procedures.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu_01/0967/a.php" alt="Hit counter" /></p>

Dynamic Competition in Telecommunications: A Systematic Literature Review

Telecommunication is the most competitive and fastest-growing market in the globe. Dynamic competition in telecom is produced by battle among companies to produce more reliable or more economical commodities. All developed countries such as U.S, Canada, and China are developing policies to reduce the rivalry among big corporations. The main objective of this paper is to outline the appropriate studies pertaining to Dynamic Competition in Telecommunications with the intentions of revealing what has already been investigated on this subject, as a medium of conducting future research. Moreover, we will also review the impact of competition on customer satisfaction and service quality in telecom businesses. Our literature review is based on 60 renowned research publications from 1990 to date, synthesizes the crucial details of competitive interaction in the telecom sphere.

OPTIMIZATION OF PROJECT COLOCATION AT PT. XYZ USING PERT AND CPM METHODS BASED ON POM-QM FOR WINDOWS APPLICATION

The development of cellular technology continues to increase, so that currently there will be fifth generation (5G) technology. Therefore, the need for telecommunications towers and competition among contractors will increase. The optimization of the colocation project at PT. XYZ has been carried out using the case of the Mekarsari Banjar site, West Java Province using the CPM-PERT method with the POM-QM for Windows application. PERT and CPM methods are methods used to manage project completion time more efficiently and effectively. The result of the research shows that the real project processing time at PT. XYZ on this site for 19 days with a normal fee of Rp. 32,811,000,-. In accelerated conditions, the colocation project can be carried out for 10 days with a Z value = 3.77 with a probability of 99.992% with a total cost of Rp. 34,181,000,- with project effectiveness is around 47.36%.

Cost assessment of elasticity for a 5G broadband network

AbstractIn the highly competitive telecommunications market, operators need to consider techniques that might lead to a more cost‐efficient use of the network resources. The recently proposed concept of resource elasticity focuses on the inherent cost reductions achieved by tailoring the resource utilization of network elements, such as radio and cloud elements, to the real network demand. However, no research has been conducted so far regarding the cost benefits that such schemes could bring to 5G networks, in terms of total cost of ownership. This article makes a novel contribution by analyzing the cost benefits of employing elasticity in a 5G network providing users with a broadband service in a hotspot area. The area exemplarily analyzed was the Port of Hamburg in Germany, which is a realistic scenario and which receives a considerable number of additional mobile users when a cruise ship arrives at the port. The results show that, for the different scenarios analyzed, the total radio access network cost reductions of using elasticity compared to a non‐elastic network range from 2.5% to 4.4%. Considering the edge cloud site‐related cost component alone, a 16.4% saving from elasticity was found. Further research is needed to understand the benefits of elasticity for other types of 5G use cases in different types of areas.

Rain Effect on 4G LTE In-Car Electromagnetic Propagation Analyzed Through MDT Radio Data Measurement Reported by Mobile Phones

Mobile networks’ evolution is strictly related to connected cars evolution, making in-car propagation modeling and analysis key enablers in the forthcoming telecommunication competition scenario. The recent availability of mobile device power measurements enriched by GPS position, the so-called 3GPP minimization of drive test (MDT) feature, nowadays, empowers new approaches to propagation studies targeting mobile service and quality improvements. The novelty of the research presented in this article is the use of a huge quantity of MDT geolocated radio measurements in a connected state (more than 370 million during the three-day MDT campaign) along 187 km of Italian A22 Motorway, part of the planned Munich-Bologna EU cross-border corridors for connected and automated mobility (CAM). In particular, MDT measurements of LTE received signal received power (RSRP) are compared between rain and dry road situations, showing how wet environments reshape electromagnetic propagation, even for LTE frequency bands (below 3 GHz) that have line-of-sight propagation marginally influenced by rain. Explanations of measured effects and simulations are presented. The rain effect on cellular propagation should be carefully considered in the perspective of connected car evolution, specifically considering new worldwide available 5G bands, more affected by rain situations, and autonomous driving scenarios.

A COMPARATIVE STUDY OF TELECOMMUNICATION SERVICE QUALITY AND CUSTOMER SATISFACTION BETWEEN NTC AND NCELL IN NEPAL

Nepal Telecommunication (NTC) and Ncell are the two main telecom players in Nepal at the moment. Ncell has been primarily focused on offering Global System for Mobile (GSM) mobile lines, while NTC offers all types of phone services. Although NTC remains the countrys leading provider of total subscribers, Ncell recently overtook NTC as the countrys leading provider of GSM mobile lines. This study aims to assess customer satisfaction in two highly competitive Nepalese telecom industries and make a comparison based on service quality. Descriptive and inferential tools are used to draw the comparative analysis. The research identifies the security service quality dimension as the major dimension of both telecommunication networks. It also locates reliability service quality of the NTC network is highly correlated with customer satisfaction whereas the security of the Ncell network is highly correlated with customer satisfaction. Tangibles are a high effect on customer satisfaction of NTC whereas security highly affects customer satisfaction of Ncell network. This study will aid the telecommunications industry in general, as well as the service quality, in better understanding their main areas of strength and, as a result, better framing their decision-making strategies to increase customer satisfaction and gain a competitive advantage.

Next-Wave of E-commerce: Mobile Customers Churn Prediction using Machine Learning

With the swift increase of mobile devices such as personal digital assistants, smartphones and tablets, mobile commerce is broadly considered to be a driving force for the next wave of ecommerce. The power of mobile commerce is primarily due to the anytime-anywhere connectivity and the use of mobile technology, which creates enormous opportunities to attract and engage customers. Many believe that in an era of m-commerce especially in the telecommunication business retaining customers is a big challenge. In the face of an extremely competitive telecommunication industry, the value of acquiring new customers is very much expensive than retaining the existing customer. Therefore, it has become imperative to pay much attention to retaining the existing customers in order to get stabilized in a market comprised of vibrant service providers. In the current market, a number of prevailing statistical techniques for customer churn management are replaced by more machine learning and predictive analysis techniques. In this study, we employed the feature selection technique to identify the most influencing factors in customer churn prediction. We adopt the wrapper-based feature selection approach where Particle Swarm Optimization (PSO) is used for search purposes and different classifiers like Decision Tree (DT), Naïve Bayes, k-NN and Logistic regression is used for evaluation purposes to assess the enactment on optimally sampled and abridged dataset. Lastly, it is witnessed through simulations that our suggested method accomplishes fairly thriving for forecasting churners and hence could be advantageous for exponentially increasing competition in the telecommunication sector.

Insights on the impact of telecommunication companies on the environment

Abstract To perform their business operations, telecommunication companies need to consume energy. This paper aims to analyze and compare the energy consumption and their greenhouse gas emissions for there of the biggest telecommunication companies: Vodafone, Orange and Telekom. Although the scientific literature proposed some analysis on the environmental measures that the telecommunication companies have to take, there is a shortage of researchers focused on GRI reporting data and the pairwise comparison method. The authors compared these telecommunication companies’ emissions under the following criteria: energy consumption (GRI 302-1), scope 1 (GRI 305-1), scope 2 (GRI 305-2) and scope 3 (GRI 305-3) greenhouse gas emissions, reduction of emissions (GRI 305-5), using the pairwise comparison method. To reduce their emissions, companies developed a sustainability strategy. This paper will further emphasize what are the plans to reduce emissions for the company which, following the analysis, pollutes the most. To provide an overview of the future of the company which, by the analysis, pollutes the most, the authors have identified and analyzed what are the main actions that the company should take to reduce their impact on the environment. To do so, the authors firstly analyze the causes of the pollution produced by the telecommunication company using Ishikawa diagram. Then, it identifies what are the main organizational processes that can be improved using APQC standardization, to show that the improvement can be made if the organization adjusts their organizational processes. This paper is an enhancement to the studies form the field because it provides a comparative analysis on three of the most competitive telecommunication companies in the world, uses GRI criteria and pairwise comparison method and gives an overview on the next steps for the telecommunication company to reduce their greenhouse gas emissions.