Гедонистический анализ доходов от пакетов телекоммуникационных услуг

The telecommunication industry (also referred to as telecom) touches almost every business and individual around the world. Numerous studies agree that it is woven into the lives of billions of people (Serentschy 2012; Laitsou, et al. 2017; Nokia and Oliver Wyman 2019; Siddiqui and Siddiqui 2020):
• there is a link between the economic growth of a country (Mehmood and Siddiqui 2013) and the development of the telecommunications infrastructure (Laitsou, et al. 2017). Its development is also associated with poverty alleviation (Decoster, et al. 2019).
• the telecommunication sector is one of the main government sources for tax collection (Gruber and Koutroumpis 2011). In many developing countries, telecom revenues account for a significant portion of the country’s gross domestic product (GDP).
• the COVID-19 crisis demonstrated the extent to which our society depends on telecommunication technologies (Nattermann and Sauer-Sidor 2020). The crisis also put the importance of connectivity into the spotlight (Diop 2020). Forced to switch to technological solutions, businesses and individuals have begun relying on the telecom infrastructure as much as never before (Veligura, et al. 2020; World Bank 2020).
Overall, researchers and industry experts agree that digitalization is not only a buzzword but a new reality that is being enabled by the telecom infrastructure (Decoster, et al. 2019; Forbes 2020). Thus, it is not surprising that there exists a large body of research exploring the characteristics, trends and performance of the companies in this industry.
Research problem and relevance
Telecom is a capital-intensive industry that requires high-volume investments into infrastructure and new services. It is challenging to measure the impact of these services on the telecom’s financial performance partly because companies have shifted towards bundling practices where a customer purchases not a single product but a combination of several features. Therefore, telecom revenue drivers are not always clear.
Besides, the telecommunication sector is facing increased pressure from regulators who introduce upper tariffs on telecommunication services. To successfully address regulators’
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concerns, telecom needs to be able to justify price increases and better understand what drives the price of the bundle.
According to the Economist Industry report (2019), the average revenue per user (ARPU) indicator has stagnated or has been decreasing in many telecommunication markets for several years. Consultancy agencies are recommending telecom to go beyond their core competencies and include additional services in the bundle (Bamberger et al. 2018). Nevertheless, there is not enough research about how these bundled services impact telecom’s financial performance.
Research questions, aim and objectives
The research aim of this master thesis is to analyze how services offered in a bundle affect telecom’s revenues. Thus, there are two research questions:
1) How do external (market environment) and internal factors (service features) impact the average revenue per user (ARPU) across different countries?
2) What are the bundle price drivers? Since most of the telecom services are offered in bundles, we will use this term interchangeably with bundle revenue drivers.
To answer these questions, we first look at the high-level relationship between bundled services and ARPU and then have a closer look at what service features, in particular, drive the bundle prices. Following the example of Bughin and Mendonça (2007), we use a sequential methodology and construct two models to define revenue and then bundle price drivers.
There are three main objectives:
• to divide the bundle into several components (revenue streams)
• to determine which of these services have a higher impact on telecom’s revenues
• to identify to which extent each driver impacts ARPU and/or the bundle price
The research paper structure
This research paper consists of three chapters (excluding Introduction and Conclusion). In the “Literature overview” chapter, we introduce the main definitions and theoretical background of the bundling phenomenon and its relation to telecom’s revenue management. In this chapter, we also provide a brief overview of the hedonic approach and its use cases.
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In the “Practical implementation” chapter, we apply the theory and explain our methodology and two models. We also discuss the data collection process and describe the datasets that were used for the construction of both models.
In the “Econometric analysis” chapter, we construct the models that were described in the second chapter and provide a detailed econometric analysis of 14 model specifications. The managerial and academic implications of the empirical research are discussed in “Conclusion” which also summarizes the whole paper. To make sure that all the relevant details are included in the paper, we also added “Appendix” with additional information on the econometric analysis and the data.