Customer Churn Prediction Based on HMM in Telecommunication Industry

The rapid development of technology and increasing numbers of customers have saturated the communication market. Communication operators must give focused attention to the problem of customer churn. Analyzing the customer’s communication behavior and building a prediction model of customer churn can provide the advance evidence for communication operators to minimize churn. This paper describes how to design a HMM to predict customer churn based on communication data. First, we oversample churners to increase the number of positive samples and establish the relative balance of positive and negative samples. Second, the continuous numerical attributes that affect communication customer churn are relatively discretized and their monthly values are converted into monthly change tendencies. Next, we select the communication features by calculating the information gains and information gain rates of all communication attributes. We then construct and optimize a prediction model of customer churn based on HMM. Finally, we test and evaluate the model by using a Spark cluster and the communication data set of Taizhou Branch of China Telecom. Experimental evaluation provides proof that our prediction model is exceptionally reliable.

Financial statement analysis

Purpose The Chinese Telecoms Industry has been rapidly growing over the years since 2001. An analysis of financial performance of the three giants in this industry is very important. However, it is difficult to know how many ratios can be used best with little information loss. The paper aims to discuss this issue. Design/methodology/approach A total of 18 financial ratios were calculated based on the financial statements for three companies, namely, China Mobile, China Unicom and China Telecom for a period of 17 years. A principal component analysis was run to come up with variables with significance value above 0.5 from each component. Findings At the end, the authors conclude how financial performance can be analysed using 12 ratios instead of the costly analysis of too many ratios that may be complex to interpret. The results also showed that ratios are all related as they come from the same statements, hence, the authors can use a few to represent the rest with limited loss of information. Originality/value This study will help different stakeholders who are interested in the financial performance of each company by giving them a shorter way to analyse performance. It will also assist those who do financial reporting on picking the ratios which matter in reflecting the performance of their companies. The use of PCA gives unbiased ratios that are most significant in assessing performance.

Prediction of Customer Churn in Telecom Sector using Clustering Technique

These days the data is producing at an incredible rate. Handling and analyzing such a big data in a specific time is the main challenge today. Clustering is majorly familiar with analyzing the data visually and used for efficient decision making process. Clustering is broadly used in a range of applications like education, field of computer science, marketing, insurance, surveillance detection, fraud detection and scientific discovery to mine the functional information from the data. This paper concentrates on the unsupervised learning k-means clustering algorithm to perform the analysis on churn prediction on telecom sector. The selection of distance measures and the category of data that a clustering algorithm cans effort is a decisive step in clustering. It defines how two elements are resemblance with each other and how this resemblance will impact the outline of the clusters. Another foremost difficulty in clustering process is to determine the goodness or validity of the cluster. Hence this paper discusses and addresses the different issues with K-means clustering. Experimentation was done on china telecom data to identify analogous group of clients who more likely to prone from the services is a major task. The results were analyzed to identify best feature, distance measures and validity indices to get qualitative clusters.

Shake-up of Philippine telecoms duopoly faces delay

Subject Delays regarding the Philippines's third telecoms major. Significance The Mislatel consortium of China Telecom and local Philippine firms, which in November 2018 provisionally won the Philippines’s third major telecoms licence, last month delayed the start of its commercial operations to early 2021 from late 2020. The delay is partly due to legislative holdups, as Congress has been preoccupied with next month’s midterm elections. The presidential election is due in 2022. Impacts How the post-midterm Congress deals with the licence transfer will be an early test of its support for President Rodrigo Duterte. Congress delaying its approval beyond this July would be a negative indicator for prospective foreign investors in Philippine industry. The government will dismiss concerns over possible threats to national security from Chinese telecoms companies.

Transparency and Opaqueness in the Chinese ICT Sector: A Critique of Chinese and International Corporate Governance Norms

This article critiques the current Chinese corporate governance framework and the OECD Principles of Corporate Governance (OECD Principles) on which the Chinese framework is largely based through detailed analysis of public disclosures by four prominent Chinese internet and communications technology (ICT) firms. These include State-controlled firms (China Telecom & China Mobile), mixed ownership (ZTE), and privately-controlled firms (Huawei Technologies). The article argues that neither Chinese nor international corporate governance norms deal adequately with the complex group structures that are so common among large Chinese firms. It also reveals deficiencies in the rules on independent directors, supervisory committees, and Chinese Communist Party committees as they are applied by Chinese ICT firms. The article concludes with reform proposals that would provide more useful information and better protection to outside investors and public stakeholders in the unique Chinese corporate environment.