Telecom sector – BSNL and MTNL

2022 ◽  
pp. 126-132
Author(s):  
Sudhir Naib
Keyword(s):  
Telecom Sector

Welfare Effects of Introducing Competition in the Telecom Sector in Djibouti

2019 ◽  
Author(s):  
Xavier Stephane Decoster ◽  
Gabriel Lara Ibarra ◽  
Vibhuti Mendiratta ◽  
Marco Santacroce
Keyword(s):  
Welfare Effects ◽  
Telecom Sector

Impact of Big Data over Telecom Industry

2018 ◽  
Vol 6 (2) ◽  
Author(s):  
Muhammad Waqar Khan ◽  
Muhammad Asghar Khan ◽  
Muhammad Alam ◽  
Wajahat Ali
Keyword(s):  
Big Data ◽  
Data Science ◽  
Cell Phones ◽  
Smart Phones ◽  
World Population ◽  
Huge Amount ◽  
Scale Down ◽  
Telecom Industry ◽  
Telecom Sector ◽  
Theoretical Computing

<p>During past few years, data is growing exponentially attracting researchers to work a popular term, the Big Data. Big Data is observed in various fields, such as information technology, telecommunication, theoretical computing, mathematics, data mining and data warehousing. Data science is frequently referred with Big Data as it uses methods to scale down the Big Data. Currently<br />more than 3.2 billion of the world population is connected to internet out of which 46% are connected via smart phones. Over 5.5 billion people are using cell phones. As technology is rapidly shifting from ordinary cell phones towards smart phones, therefore proportion of using internet is also growing. There<br />is a forecast that by 2020 around 7 billion people at the globe will be using internet out of which 52% will be using their smart phones to connect. In year 2050 that figure will be touching 95% of world population. Every device connect to internet generates data. As majority of the devices are using smart phones to<br />generate this data by using applications such as Instagram, WhatsApp, Apple, Google, Google+, Twitter, Flickr etc., therefore this huge amount of data is becoming a big threat for telecom sector. This paper is giving a comparison of amount of Big Data generated by telecom industry. Based on the collected data<br />we use forecasting tools to predict the amount of Big Data will be generated in future and also identify threats that telecom industry will be facing from that huge amount of Big Data.</p>

scholarly journals A Narrative Approach to Corporate Relations: The Historical Background on Telenor’s Success

2021 ◽  
pp. 1-36
Author(s):  
SVERRE A. CHRISTENSEN
Keyword(s):  
Business Strategy ◽  
Historical Background ◽  
Narrative Approach ◽  
Societal Values ◽  
Self Interest ◽  
Equipment Supplier ◽  
Supplier Relations ◽  
Telecom Sector ◽  
Public Telephone

This article examines the development of buyer-supplier relations in the telecom sector. The literature on telecoms in Scandinavia has been dominated by the narrative praising the trusting and collaborative relations between Telia, the Swedish public telephone operator (PTO), and Ericsson, the equipment supplier. The Norwegian PTO, Telenor, diverted from this path and was a pioneer in preferring competitive tenders and arm’s length relations with its suppliers starting in the 1970s. The article argues that Telenor’s history and nationality had a significant impact on its business strategy. In addition, the article examines why some business narratives persist while others remain unknown. One finding is that shareholder-friendly narratives have a handicap because they focus on self-interest and money, and not societal values.

Impact of regulatory announcements on systemic risk in the Indian telecom sector

2018 ◽  
Vol 13 (5) ◽  
pp. 1395-1416 ◽  
Author(s):  
Sushma Priyadarsini Yalla ◽  
Som Sekhar Bhattacharyya ◽  
Karuna Jain
Keyword(s):  
Risk Premium ◽  
Systemic Risk ◽  
Service Providers ◽  
Policy Makers ◽  
Content Type ◽  
Risk Premiums ◽  
Buffering Hypothesis ◽  
Research Findings ◽  
Telecom Sector ◽  
The Impact

Purpose Post 1991, given the advent of liberalization and economic reforms, the Indian telecom sector witnessed a remarkable growth in terms of subscriber base and reduced competitive tariff among the service providers. The purpose of this paper is to estimate the impact of regulatory announcements on systemic risk among the Indian telecom firms. Design/methodology/approach This study employed a two-step methodology to measure the impact of regulatory announcements on systemic risk. In the first step, CAPM along with the Kalman filter was used to estimate the daily β (systemic risk). In the second step, event study methodology was used to assess the impact of regulatory announcements on daily β derived from the first step. Findings The results of this study indicate that regulatory announcements did impact systemic risk among telecom firms. The study also found that regulatory announcements either increased or decreased systemic risk, depending upon the type of regulatory announcements. Further, this study estimated the market-perceived regulatory risk premiums for individual telecom firms. Research limitations/implications The regulatory risk premium was either positive or negative, depending upon the different types of regulatory announcements for the telecom sector firms. Thus, this study contributes to the theory of literature by testing the buffering hypothesis in the context of Indian telecom firms. Practical implications The study findings will be useful for investors and policy-makers to estimate the regulatory risk premium as and when there is an anticipated regulatory announcement in the Indian telecom sector. Originality/value This is one of the first research studies in exploring regulatory risk among the Indian telecom firms. The research findings indicate that regulatory risk does exist in the telecom firms of India.

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