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This study addresses foreign markets selection decisions by Russian mobile telecommunications operators and the impact of top management team composition on the degree of firms’ internationalization.

The qualitative exploratory study analyzed 24 foreign market entry decisions and the composition of the top management team of the two leading Russian mobile telecommunications operators, VimpelCom and Mobile Telesystems (MTS/AFK Sistema).

Russian mobile telecommunications operators adopted a gradual approach to foreign market selection, as the study revealed the positive impact of the target market’s geographic proximity to Russia on the investment decision. The international background of the top management team was positively related to the increasing distance of the selected foreign markets.

Further studies may include quantitative evaluation of investment decisions by mobile telecommunications operators from other emerging-market firms, as well as a longer observation period and investment decisions by firms operating in other industries.

Russian and other emerging-market firms should evaluate the importance of the top management team composition and international experience prior to initiation of the internationalization process.

Russian multinationals represent a relatively understudied phenomenon, despite the importance of outward foreign direct investments from Russia among other emerging-market firms.

The purpose of this paper is to benchmark the Indian mobile telecommunication service providers for relative efficiencies. In this paper, a method for benchmarking performance of mobile telecom utilities based on data envelopment analysis (DEA) is presented. The paper discusses some concepts between quality performance and benchmarking and the results include performance efficiency and sensitivity‐based classification of utilities. Also, peer‐to‐peer comparison of inefficient with efficient utilities is provided. Based on these results, inefficient utilities can develop strategic plans to improve performance.

The authors use DEA to measure comparative efficiencies of mobile telecom companies and two different DEA models, CCR and BCC, were applied to evaluate the relative efficiency of mobile telecom operators in India. Sensitivity‐based classification of utilities is carried out by removing one or more inputs or outputs from the base model to construct a new DEA model. Comparisons of DEA efficiencies from the base model with the structurally perturbed models show the impact on efficiency. Data include annual and quarterly reports showing various quality parameters.

DEA is used to derive the benchmarks based on the comparison of the 126 utilities which include public sector undertaking (PSU) operators (MTNL and BSNL) and private operators of the Indian mobile telecommunication sector. The result includes performance efficiency and peer‐to‐peer comparison of inefficient utilities with efficient utilities. Based on these results, inefficient utilities can develop strategic plans to improve their performance. Sensitivity analysis, based on removal of one or more variables from the base model to determine changes in DEA efficiencies is done for selecting the strength of parameters of utilities for performance improvement.

Benchmarking of service utilities in the telecom sector is virtually non‐existent at the national level in India. This research identifies the different variables and then a model is prepared for benchmarking of the service providers in India. Based on the efficiency analysis, benchmarks can be set, and utility efficiency scores can be obtained based on the set benchmarks. These scores can help develop a strategic plan for mitigating the factors that contribute to the system inefficiencies.

This paper is one of the few published studies that benchmark the performance of mobile telecom services in India. This research promises to be amongst the first of the works carried out taking specific parameters of mobile telecom utilities of India.

Contends the best strategy for facing up to the growing demand for services in mobile communications is to learn from the experience of other countries around the globe. Addresses the key role of regulation, formulating policy framework, overcoming incumbents’ resistance and public scrutiny. Summarizes that the mobile communications sector is the fastest growing area within telecommunications.

The purpose of this paper is to explain the determinant factors of switching behavior in the Thai cellular market before the Mobile Number Portability (MNP) policy is implemented.

A binary logit model and individual survey data from the National Telecommunications Commission 2009 are used to estimate the intention of mobile phone consumers to switch.

The results show that subscriber characteristics, including age, government officer, self‐employed, internet use, central region, and southern region, are significant in explaining the switching behavior of Thai mobile subscribers. They also indicate that the mobile operators' customers are confronted with different switching costs. The subscribers of the largest mobile operator have the highest switching costs. This study also shows that the largest mobile operators will gain more switching subscribers than smaller operators. The implementation of MNP will help to lower the switching costs of smaller mobile operators rather than of larger operators, as the subscribers of smaller operators are more likely to switch and move to larger mobile operators, as the larger operators provide better quality network coverage. The study shows that the expected impact of implementing MNP without national mobile roaming regulations would be worse for smaller mobile operators. The smaller operators need to compete on both price and quality improvement. In the short run, it would not be possible for the smaller operators to compete with the larger operators due to the inequality in the quality of network coverage.

The result is useful to developing countries considering implementing MNP regulation.

The objective of this paper is to understand the success factors of mobile operators.

Explores the business practices of leading carriers in Japan, South Korea, China, Europe and the USA.

The paper finds several common characteristics in the more successful markets including a handset design and quality of service that are aligned with the operators' service concepts, effective billing systems, reasonable prices, and targeted marketing strategies. While these internal factors can be easily copied by a mobile operator, it is found that there are additional, external factors such as the existing customer base and its preferences, government policy, technological constraints and value chain dynamics that can greatly affect the transferability of a mobile operator's business model to another market.

The findings present opportunities for further research including the possibility of developing a new theory into which factors are more difficult to transfer and why.

The practical implications of this paper are that operators who wish to pursue profitable business models need to take into account the factors of a successful business model and which ones are easily transferable in their respective markets and which ones are not.

The paper is unique in that we compare the business models of mobile operators across five different countries.

Airtel, the leading mobile operator in India was going to launch the “Airtel Zero” platform that would charge service providers and OTT providers on the internet for mobile data traffic but would allow end consumers free access to the web sites that were signed up for the platform. The case revolves around the questions of pricing these data services to the service providers in a market where the price to one set of customers (the end consumer) was not independent of the price to another set of customers (the OTT service providers) - typical of two sided markets. Issues of net neutrality and competition have been considered alongside.

On October 1, 2017, Gopal Vittal, Managing Director and Chief Executive Officer-India and South Asia, Bharti Airtel, was in his New Delhi office reviewing current trends and Airtel's position in Indian Telecom. His primary concern was the shifting data consumption trend in the Indian Telecom Industry (Exhibit 1) and the disruptive changes that were impacting pricing and profitability since the entry of Reliance Jio Infocomm Limited (Jio) in September 2016. Data consumption in Indian telecom had started increasing exponentially after the entry of Jio who offered lifetime free voice services followed by rock-bottom data tariffs. As Vittal reviewed the data, he wondered if the voice market through a non-VOIP provision was now saturated and would rapidly decline. He was also concerned about the price and revenue implications for Airtel. How might the voice market evolve? How should he act on the pricing front to enable Airtel revenues to continue to grow in the context of what appeared to be predatory pricing by Reliance Jio?

Case A uses the context of unfair, non-transparent process of spectrum allocation by the Indian government to private operators that led to Supreme Court (SC) cancel 122 licenses. It gives scope to discuss the relationship between policy and regulatory agencies and their effectiveness, role of other institutes outside telecom sector such as the Prime Minister Office, Empowered Group of Ministers and the Comptroller & Auditor General of India.

In the telecommunication industry we observe trends such as unbundling, convergence, and new business models. To accelerate innovation, mobile telecommunication companies are more and more working together with companies from other industrial sectors (such as media and IT). The Cyclic Innovation Model helps to understand all those activities in this rather chaotic business environment. This particularly applies to mobile telecommunication companies that are developing mobile data innovations (such as Lucio). All those innovations are steps along a transition path towards a wireless future.