Fig 4 - uploaded by Maurizio Naldi
Content may be subject to copyright.
Source publication
Concentration phenomena concern the ICT market. Though the regulatory action has been active mainly in the telecom network operators industry, even more significant worldwide concentration phenomena affect other industries. The market of mobile operating systems is analysed through two concentration indices to get a quantitative picture of the curr...
Context in source publication
Context 1
... is extremely close to 1, which means that the 4 dominant firms take all the market. Even in the years of HHI depression, the CR4 was well above the 0.6 barrier, with most of the market just redistributing among the dominant players. Finally, in order to assess whether the market structure is closer to an oligopoly or to a monopoly, we plot in Fig. 4 the market share owned by the top operating system. We observe a behaviour quite similar to the HHI, with a dip around 2011, where the dominant operating system (then Symbian) held roughly 1/3 of the overall market. But both before and after that dip, the market saw instead an operating system getting an absolute majority. Since 2013, ...
Citations
... W dzisiejszych czasach najpopularniejszymi systemami operacyjnymi na urządzenia mobilne są Android oraz iOS. Z tych dwóch częściej wybierany jest system Android, z blisko 80% udziałem w całym rynku systemów operacyjnych na urządzenia mobilne [2]. ...
This publication presents a multi-criteria comparison of two mobile applications built with the use of Android and Flutter SDK. The former has been implemented with Kotlin and the latter with Dart. The benchmarking process examines factors such as execution time and CPU usage during data and disk operations. During the analysis, attention was paid to the length and volume the source code, community support and the availability of libraries. The comparative analysis shows that a mobile application written using Android SDK is often not only faster and more efficient, but also has greater community support and the number of libraries available. In addition, an analysis of the source code volume showed that Flutter has more concise but more difficult to navigate code than Android.
... As one of the most common general purpose operating systems, Linux is not immune to security risks [5]. However the Linux operating system is extensively used on both web servers [6] as well as mobile devices [7]. With more then 2.5 billion active Android devices in the world [8], the security of the Linux operation system is of great significance. ...
The Linux kernel is one of the dominating operating systems used today. Like any complex system, the Linux kernel has a large attack surface that can include vulnerabilities. When adversaries exploit vulnerabilities in common software systems like the Linux kernel, the consequences can be severe. It is therefore crucial for the improvement of digital infrastructure security, to identify and mitigate software areas which are prone to be attacked. While there are already different approaches to assess and mitigate the attack surface of Linux, this research project aims to identify the risks associated with different Linux kernel components, by using software complexity metrics. The resulting measures can help identify highly complex kernel features to create secure kernel configurations.
... The market structure refers to the characteristics of the market either organizational or competitive, that describes the nature of competition and the pricing policy followed in the market. An operator holding a very large share of the market may take advantage of its position towards its customers, which in turn have little or no room to oppose (Naldi, 2016). Further explanation of oligopoly market structure in the terms of operating systems which are the subject of this paper is presented in the following subchapters. ...
... The market structure refers to the characteristics of the market either organizational or competitive, that describes the nature of competition and the pricing policy followed in the market. An operator holding a very large share of the market may take advantage of its position towards its customers, which in turn have little or no room to oppose (Naldi, 2016). Further explanation of oligopoly market structure in the terms of operating systems which are the subject of this paper is presented in the following subchapters. ...
Market structure and the degree of competition has been a subject of interest for researchers for a long period of time. Oligopoly is one of the structures which play an important role in studying market power, business behavior and the performance of market players, whilst it represents a market situation in which only few producers serve to majority of users. Perfect real-life examples are mobile operating systems, as iOS and Android partake in over 99% of the market, making it one of the most accurate examples of oligopoly situations on the level of the EU, as well as the global level. This paper discusses the meaning of oligopoly markets that are of especially interesting to be observed in today's globalized market. Nowadays, when the flow of good is frequent and easier than ever, it is interesting to have such structures that define competition and succeed to maintain extremely high market shares. Furthermore, study analyses the competitive dynamics of the operating systems market and draws conclusions on their impact on market competition, as well as their influence on growth and employment rate. Finally, the paper discusses further research directions and suggests its implication.
... Market concentration is measured using Herfindahl-Hirchman Index (HHI). The HHI is calculated using the following formula (Naldi, 2016); ...
... For this purpose, we adopted the methodology presented in Table 1. HHI below 0.15 indicate non-concentrated, between 0.15 and 0.25 moderately concentrated and indices above 0.25 imply highly concentrated markets (Naldi, 2016). ...
... Where M is the number of firns whose whose market share are known, R is the unknown market share Q=R/S M , S M is the market share of smallest firm whose market share is knowm Source: (Naldi, 2016) ...
The purpose of this paper is to provide an event study based evidence on whether the effect of sponsorship announcements on stock returns differs based on market concentration. The study sample includes 17 sponsorship announcements occured during the period of 2011 and 2016 for10 firms listed in BIST. In order to test whether stock return is affected by sponsorship announcements, abnormal return (AR), cumulative abnormal return (CAR) were tested by using t-tests for event window [-5, +5]. According to the results, in [-5 +5] event window 13 events revelaed statistically significant AR and CAR before and after the event day. Accordingly, sponsorship announcements are associated with stock returns of sponsoring firms. A Mann-Whitney U test indicated statistically significant difference in abnormal returns between firms operating in non-concentrated industries and firms in concentrated industries. In concentrated markets sponsorship announcements created negative abnormal returns. On the other hand, sponsorship announcements created positive abnormal returns in non-concentrated industries. The study extends the current knowledge through providing empirical evidence for the role of market competitive structure.
... Although NN focuses on operators' behaviour, it is important to note that threats to internet openness have also been observed in regard to other segments of the internet value-chain. Notably, Noam (2015) and Naldi (2016) have highlighted the worrying concentration of the mobile operating system market. Moreover, several dominant online platforms have been criticised for leaving limited space for competitors (Haucap and Heimeshoff 2013) or for putting in place a variety of discriminatory practices 6 that may harm consumers and other businesses (European Commission 2015b; House of Lords 2016). ...
The internet is a general-purpose network grounded on openness, decentralisation and interoperability. Such features have allowed innovation to flourish, lowering barriers to communication, participation and cooperation, thus empowering end-users. ‘General purpose’ means that the purpose for which the internet is used is not predefined by the operator but can be autonomously decided by the end-user. Accordingly, the network neutrality (NN) principle mandates non-discriminatory treatment of internet traffic to preserve the general-purpose nature of the internet, unleashing end-users’ creativity. This paper starts by exploring the NN debate, stressing that the NN rationale is to preserve an open and decentralised internet architecture, empowering end-users and protecting their rights. Subsequently, it argues that the combination of reduced data caps and zero-rating (ZR) schemes may create artificial scarcity, raise the price of the open internet and jeopardise the achievement of the NN rationale. It provides a taxonomy of ZR models and emphasises that several ZR practices might impose on the internet a centralised configuration that characterises less innovative networks, such as the Minitel. The phenomenon that I define as ‘Minitelisation’ of the internet consists of the shift from a user-centric, general-purpose network to one with predefined purposes, thereby creating passive consumers of predetermined services, rather than active internet users.
The concentration of market power is typically measured by the Hirschman–Herfindahl Index (HHI). When a new company enters the market, the changes in the HHI reflect the change in concentration and may elicit a regulatory intervention. In this paper, we evaluate the potential benefits (HHI decrease) or harms (HHI increase) in advance of the new entry. We identify the volume of sales achieved by the newcomer leading to either situation in two paradigmatic cases: market expansion and market stagnation. We also find the maximum benefit achievable (the minimum HHI value) after the new entry. The formulas are applied to a real‐world case: a merger in the mobile telecom market.
The Hirschman–Herfindahl Index (HHI) is a well known measure of market concentration. However, its exact computation would require the knowledge of the market share of all the companies. In this paper, accurate estimates of the HHI are computed even if just the market shares of the top companies are known (or just the top company and a few scattered ranked companies), by providing tight lower and upper bounds for the HHI. Similarly, when just the sales of the top companies are known, an upper bound is provided, which is the most relevant value if dominant positions have to be identified.
