Spectrum Auction and Investment in Telecom Industry - A Suggested Policy

2009 ◽  
Author(s):  
Debabrata Datta
Keyword(s):  
Spectrum Auction ◽  
Telecom Industry

scholarly journals Spectrum Auction and Investment in Telecom Industry: A Suggested Policy

2012 ◽  
Vol 37 (1) ◽  
pp. 19-30 ◽  
Author(s):  
Debabrata Datta
Keyword(s):  
Optimal Investment ◽  
Revenue Maximization ◽  
Policy Practice ◽  
Spectrum Auction ◽  
Maximum Profit ◽  
The Social ◽  
Interest Charge ◽  
Telecom Industry ◽  
The Government ◽  
Telecom Infrastructure

Recently, Indian telecommunication industry has passed through an auction process of 3G spectrum, which has enabled the government to collect hefty license fees. The successful bidders are expected to borrow this bid amount from the commercial banks and repay from the revenue to be generated from the new services. This paper looks at this issue theoretically. The telecommunication firms operate on the basis of acquisition of airwave space, which is licensed by the government. The usual policy practice is to distribute the available spectrum by an ascending auction. As per the economic theory, auction has two merits. Firstly, auction ensures that spectrum goes to the most efficient firm, which is by definition the firm that makes the maximum profit among all. This firm by virtue of their maximum profit bids the highest amount in the auction and gets the spectrum. Secondly, spectrum auction ensures revenue maximization of the government. This result of efficiency optimization however holds under the assumption of perfect information and no uncertainty. Uncertainty and irrationality like over-optimism can lead to problems like ‘winners‘ curse' or ‘broke winners’ under auction. Still auction is market-based and less controversial than discretionary distribution. However, this paper argues that high amount of auction bid can result in several deficiencies in the telecom industry. An issue of debate is whether high auction bid will result in higher price for the services. Under the assumption of infinite time horizon, high license fee is a sunk cost and therefore does not raise price. But this paper shows that a high license fee can raise the lending bank�s interest charge for which not only price rises but the infrastructural investment in the telecom industry suffers. After the acquisition of spectrum through auction the industry needs infrastructural investments to roll out the quality services. Inadequate investment in infrastructural activities like procurement of quality equipments, erection of tower, etc., may result in lower quantum of services with degraded qualities. This is in fact a reality in India where not only rural telecom infrastructure is vastly inadequate, the urban telecom infrastructure is also under severe stress. In this paper, using the tool of game theory we show how capacity and quantity choice game of firms ends up in high auction bid and sub-optimal investment on infrastructure. Then how can the social planners simultaneously achieve the twin objective of growth and revenue maximization? The paper shows that these objectives are realized if a part of the license fee is spent for the subsidization of infrastructural investment in the telecom industry.

Role of Value Added Services in Shaping Indian Telecom Industry

2011 ◽  
Author(s):  
Sanjeet Singh ◽  
Gagan Deep Sharma ◽  
Mandeep Mahendru
Keyword(s):  
Value Added ◽  
Telecom Industry

Exploration of Product Centric Factors in Telecom Industry

2015 ◽  
Vol 8 (1) ◽  
Author(s):  
Swati Ganeti ◽  
Rajat Agarwal ◽  
Murali Krishna Medudula ◽  
Mahim Sagar
Keyword(s):  
Service Quality ◽  
Service Provider ◽  
Service Providers ◽  
Network Connectivity ◽  
Factor Loading ◽  
The Other ◽  
Relative Importance ◽  
Network Connection ◽  
Telecom Service ◽  
Telecom Industry

Telecom industry is one of those industries which has changed dramatically during the past decade. With more and more players entering in this industry, competition is ever increasing. The war between these players is slowly shifting from the price to the augmentation. This paper aims at exploring such factors which influence a customers preference of one telecom service provider (TSP) over the other. It is a descriptive research where study has been conducted among the consumers of different telecom service providers (TSPs). By reviewing the existing literature in this domain, we explored different factors which affect the consumers decision to prefer one telecom service provider over the other. A consumer targeted questionnaire was designed where consumers were asked about the factors they consider (with their relative importance quantified using Likert scale), before buying a new network connection to know the relative importance of the various factors. Factor Analysis was performed to club various variables into distinct factors. Statistical techniques then helped in identifying the relative importance. From the Factor Loading matrix the following five factors were generated:- Overall service quality, Point of Purchase Differentiator, Promotion Measures, Tariff Plans and Size of the Network. Further study in the behavioural perceptions of consumer shows that the most important factor in influencing the customer buying behavior is Service Quality. The second most important factor is cost and various plans offered by the telecom service provider. Network connectivity was considered by almost all the respondents and consumers prefer the largest network player. The study also found that promotional measures dont influence the customers as expected.

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>

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