Operating System Market Research Articles

An empirical assessment of the impact of network effects on competitive processes in the operating systems market

Modern technology markets are characterized by the presence of a network effect, a phenomenon that significantly affects network adoption. While providing the advantage of belonging to a network, network effects can curb the diffusion of alternative technological products, which can negatively influence public welfare. The purpose of this article is to work out a method of a compound impact analysis of direct network effect, critical mass and standardization when assessing changes in the competitive environment on a two-sided software market using the case of operating systems (OS). The theory of network effects constitutes the methodological framework of the study. The research method is an econometric analysis of the impact of the installed base of users, switch of standards and gain of a critical mass of users by applying a basic within model and a difference GMM model. The database consists of monthly country data on website visitors’ activity from the StatCounter web analytics service by desktop, mobile, and tablet devices for the period from 2009 to 2019. The study shows that, due to the saturation effect, markets experience a slowdown in the influence of network effects. The desktop OS market is characterized by the presence of a de facto standard, that is Windows OS, which indicates the monopolization of this segment. OSX, Android, and iOS are industrywide standards. The proposed approach allows analyzing a direct network effect jointly with gain of a critical mass of users and switch of standards.

Sustainable use of a smartphone and regulatory needs

AbstractThe significance of information and communication technologies (ICT) for the Paris Climate Agreement is continuously increasing because of its growing energy consumption. Here we examine the question for the smartphone and extend the investigation to more aspects of sustainability. Critical issues are identified for ten UN Sustainable Development Goals. Measurements of smartphone energy consumption show that a significant savings potential can be unlocked by reducing the data outflow and the large amount of personal data stored in data centers. Main discrepancies are also traced to the oligopolistic market structure of operating systems (OSs), messenger services, and social media apps. Technical means for a sustainable smartphone use are suggested as alternative OSs, social media channels of the Fediverse, as well as free and open‐source software. Finally, societal conditions are emphasized to make the market for OSs and apps more diverse so that a sustainable smartphone use can generally prevail.

STABILITY ANALYSIS OF CELLULAR OPERATING SYSTEM MARKET SHARE IN INDONESIA WITH THE COMPETITIVE LOTKA-VOLTERRA MODEL

The current increase in smartphone users has caused various mobile device operating system companies to compete with each other to create a mobile device operating system that is suitable and acceptable to the public. Competition among mobile operating system market shares can be analyzed using the Lotka-Volterra model. This study aims to reconstruct the Lotka-Volterra model for the cellular operating system market share in Indonesia. In addition, a stability analysis was carried out, which aims to determine the stability of the competitive model for the market share of the operating system in Indonesia. The results of the study show that a competitive Lotka-Volterra model can be built on the Android and iOS operating system market share in Indonesia. In this model, there are four equilibrium points, one of which is unstable, and the other three equilibrium points are conditionally stable.

Innovative Approach to Android Malware Detection: Prioritizing Critical Features Using Rough Set Theory

The widespread integration of smartphones into modern society has profoundly impacted various aspects of our lives, revolutionizing communication, work, entertainment, and access to information. Among the diverse range of smartphones available, those operating on the Android platform dominate the market as the most widely adopted type. With a commanding 70% share in the global mobile operating systems market, the Android OS has played a pivotal role in the surge of malware attacks targeting the Android ecosystem in recent years. This underscores the pressing need for innovative methods to detect Android malware. In this context, our study pioneers the application of rough set theory in Android malware detection. Adopting rough set theory offers distinct advantages, including its ability to effectively select attributes and handle qualitative and quantitative features. We utilize permissions, API calls, system commands, and opcodes in conjunction with rough set theory concepts to facilitate the identification of Android malware. By leveraging a Discernibility Matrix, we assign ranks to these diverse features and subsequently calculate their reducts–streamlined subsets of attributes that enhance overall detection effectiveness while minimizing complexity. Our approach encompasses deploying various Machine Learning (ML) algorithms, such as Support Vector Machines (SVM), K-Nearest Neighbor, Random Forest, and Logistic Regression, for malware detection. The results of our experiments demonstrate an impressive overall accuracy of 97%, surpassing numerous state-of-the-art detection techniques proposed in existing literature.

F3l: an automated and secure function-level low-overhead labeled encrypted traffic dataset construction method for IM in Android

Fine-grained function-level encrypted traffic classification is an essential approach to maintaining network security. Machine learning and deep learning have become mainstream methods to analyze traffic, and labeled dataset construction is the basis. Android occupies a huge share of the mobile operating system market. Instant Messaging (IM) applications are important tools for people communication. But such applications have complex functions which frequently switched, so it is difficult to obtain function-level labels. The existing function-level public datasets in Android are rare and noisy, leading to research stagnation. Most labeled samples are collected with WLAN devices, which cannot exclude the operating system background traffic. At the same time, other datasets need to obtain root permission or use scripts to simulate user behavior. These collecting methods either destroy the security of the mobile device or ignore the real operation features of users with coarse-grained. Previous work (Chen et al. in Appl Sci 12(22):11731, 2022) proposed a one-stop automated encrypted traffic labeled sample collection, construction, and correlation system, A3C, running at the application-level in Android. This paper analyzes the display characteristics of IM and proposes a function-level low-overhead labeled encrypted traffic datasets construction method for Android, F3L. The supplementary method to A3C monitors UI controls and layouts of the Android system in the foreground. It selects the feature fields of attributes of them for different in-app functions to build an in-app function label matching library for target applications and in-app functions. The deviation of timestamp between function invocation and label identification completion is calibrated to cut traffic samples and map them to corresponding labels. Experiments show that the method can match the correct label within 3 s after the user operation.

A Comparative Analysis of Amazon, Microsoft, and Apple's Stock Investment Value

This paper provides a comparative analysis of the stock investment value of Amazon, Microsoft, and Apple, three global companies that investors may consider when investing in stocks. The author analyzes each company's business diversity, financial situation, and industry competition. Amazon is a leading e-commerce company with strong domestic and international competitors in the field of e-commerce and cloud computing. Microsoft is a stable company with a dominant position in the personal computer operating system market and a growing market share in the field of cloud computing. Apple has a diverse product line, including hardware and software products, and faces competition from many competitors, but maintains its competitiveness in the market by investing in technological innovation. The paper concludes that the stock market is full of opportunities and challenges. And investors need to have a certain risk awareness and long-term investment vision. The analysis provided in this paper can help different investors to select stocks that suit their preferences and investment objectives. The paper uses data from Yahoo Finance and company websites to provide an overview of each company's performance, net sales, and stock prices. And compare the calculation results. Then select the stocks that investors with different preferences prefer.

App stores, antitrust and their links to net neutrality: A review of the European policy and academic debate leading to the EU Digital Markets Act

Google and Apple together control 99% of the European smartphone operating system market. What are the distinctive European policy and academic contributions to the ongoing global debate on how this new source of market power should be controlled?

Analysing mobile forensic datasets: A systematic review on availability, efficacy, and limitations

Everyday there is an increase in the number of malwares being created which presents a significant danger to the Android systems holding a large share in the operating systems market. This surge in malware creation also makes it challenging to analyse and detect these malicious applications. Machine learning techniques are commonly used for malware detection, but the development of an effective system requires a reliable dataset to train and test it. This paper provides an overview of the most commonly used datasets in malware detection research conducted between 2015-2020, based on their performance, usability, availability, and effectiveness. By analysing and comparing these datasets, this paper aims to provide insights into the selection of appropriate datasets for future research in this area.

Комплексное влияние сетевых эффектов, критической массы и стандартизации на конкуренцию на рынке операционных систем

The competition policy mechanisms in specific sectors of the economy work out, provided that balanced protection tools are used, and incentives are maintained to launch a new product or technology onto the market. However, strong network effects lead to the presence of a small number of manufacturers or even a single player, which hinders the spread of alternative products and contributes to a single product network formation. The relevance of this research is driven by the need to competition analysis in the software market affected by the network effects. The purpose of this review article is to justify the need for a compound impact analysis of network effects, critical mass and standardization as an assessment optimization tool of the competition state in the two- sided software market, specifically in the operating systems markets. The object of the research is an operating system itself, and the subject is the influence of network effects, critical mass and standardization on competitive processes in the operating systems market. The following issues were performed: the results systematization of theoretical studies and approaches to econometric modeling of network externalities, the strategies identification for analysis of standards and installed base of users and sales, introduction of the operating system and software concepts, the development of recommendations for analysis of the phenomenon of network effects with an emphasis on the standardization process in the furtherance of competition and industrial policy. Analysis of the examined phenomena impact shows that the introduction of a generally accepted network effects definition at the legislative level, distinction between the direct and indirect network effects, consideration of this phenomenon as a barrier to entry into the market, and concord of the network effects and standard setting theory can decrease the possibility of type I and II errors in the law enforcement practice.

Mobile Development of Android-Based Beginner E-Voting System

<p><em>One of the implementations of Pancasila democracy in Indonesia is the implementation of the election of leaders, by voting. In addition to within the scope of government, the implementation can also be carried out within the scope of educational institutions such as schools or campuses, where voters are referred to as novice voters. Elections are still carried out conventionally which requires a large nominal budget, as well as problems or fraud that often occur during elections. So in this study, a digital voting system was created using an electronic device, namely an Android-based mobile e-voting system that can be accessed via a smartphone. the existence of this system is considered to be able to provide convenience and comfort in the implementation of the voting process and provide an important role to the generation of novice voters who are now entering the digital era where technology is developing rapidly, namely to continue to cultivate democratic values in it. Based on the data obtained, smartphone users now have a percentage value of 66.31% among the public and 33.69% of people do not own a smartphone. While the survey results related to the operating system market pairs in Indonesia, accounting for 91.56% of Android users, show that the majority of smartphone users in Indonesia use Android, with this the e-voting system has the potential to be used by the general public, especially novice voters. For this reason, this e-voting system aims to provide convenience and comfort in the implementation of the election process.</em></p>

MALWARE PROTECTION SYSTEM ON ANDROID

Abstract: At the moment of writing this report (august 2018), the Android has a worldwide market share of 76.88%, being in an ascending slope since 2009, with an increase of 4.14% since the same period on last year and leaving its rival iOS far behind, at 20.38%[1]. Also, Google announced in 2017 that more than 2 billion users are monthly active on devices. These 2 facts make this OS the most important one on the mobile devices and not only smartphones, as nowadays even the smartwatches are using Android (named Wear) being in continuously improving the experience to be as close as the one on phones[2].
 
 [1] Mobile Operating System Market Share Worldwide, http://gs.statcounter.com/os-marketshare/mobile/worldwide
 [2] The best Wear OS smartwatches: LG, Fossil, Huawei, Polar and more, https://www. wareable.com/smartwatches/ best-android-watch.

Fine-grained analysis method for Android volatile memory

Android dominates the mobile operating system market. Volatile memory analysis of Android devices has been the focus of research on mobile forensics technology. However, due to the semantic gap between the kernel and the volatile memory allocator, existing Android volatile memory analysis methods are coarse-grained. With the volatile memory capacity of Android devices increasing, these methods cannot satisfy the need of Android volatile memory analysis accuracy. In this paper, we first discuss the address space layout of Android processes and the management mechanism of Jemalloc, the default Android volatile memory allocator. Then, we bridge the semantic gap by utilizing the boundary auto alignment feature of the data structure of Jemalloc. Finally, we propose a Fine-grained Analysis Method for Android volatile Memory, called FAMAM. Experimental results shows that FAMAM has an accurate data analysis capability as well as a good robustness. In addition, we successfully use FAMAM to discover new storage patterns for username and password of Wechat.

Logical acquisition method based on data migration for Android mobile devices

Android dominates the mobile operating system market. The data acquisition method of Android devices has been the focus of research on mobile forensics technology. However, due to the continuous updates of the Android system version and the deployment of security technologies, existing data acquisition methods are limited and difficult to apply to new Android mobile devices. In order to address this problem, we propose a logical acquisition method based on system-level data migration services provided by Android mobile device manufacturers. The experimental result demonstrates that, for unrooted Android mobile devices, the proposed method is superior to existing logical forensic methods in terms of data acquisition capability.

Motivations of application developers: Innovation, business model choice, release policy, and success

ABSTRACTThis study provides insights into the success of smartphone applications (apps) based on the chosen business model and version release strategy, and relates these variables to the motivations of their third-party innovators in the smartphone operating system market. The analysis is based on a questionnaire focusing on motivational factors and demographics of developers, coupled with secondary data on the apps themselves and their success. We find that apps developed due to the personal needs of the developer for new functionalities result in higher success in terms of number of downloads, whereas many of the intrinsic motivations outlined in user innovation theory do not have a significant impact on app success. Our findings imply that while some insights from user innovation theory are applicable to understanding factors that contribute to the potential success of apps, the smartphone application software ecosystem has its own dynamics, including the absence of learning effects over several apps that require further focus and more in-depth research.

An android malware dynamic detection method based on service call co-occurrence matrices

With the market share of Android mobile devices increasing, Android has come to dominate the smartphone operating system market. It also draws the attention of malware authors and researchers. The number of Android malicious applications is constantly increasing. However, due to the limitations of static detection in code obfuscation and dynamic loading, the current research of Android malicious code detection needs to be deeply studied in dynamic detection. In this paper, a new Android malware identification method is proposed. This method extracts the feature of Android system service call sequences by using a co-occurrence matrix and uses machine-learning algorithm to classify the feature sequence and to verify whether this feature sequence can expose Android malware behaviors or not. By using 750 malware samples and 1000 benign samples, this paper has designed an experiment to evaluate this method. The results show that this method has a high detection precision rate (97.1%) in the best case and a low false-positive rate (2.1%) in the worst case based on the system service call co-occurrence matrix.

Changing Markets in Operating Systems; a Socio-Economic Analysis

This paper explores into the character of the market for operating systems in order to reach a better understanding of the characteristics, consequences of fragmentation, and impact in the overall development of the internet and the digital economy. For this purpose we consider the effects on trade and innovation, and on the significance for the architectures of networks in the digital economy. The article includes a review of the various forms of market definition of software operating systems to understand their economic characteristics from a socio-technological view. From the early dominance of IBM’s OS/360 to UNIX-related systems and the disk operating systems [DOS] of IBM and Microsoft through to Apple’s Mac OS and Google systems [Chrome OS and Android], there has been a succession of dominant players. We address the economic theory behind markets in platforms and its relationship with operating systems. Arguments are presented to describe three major sectors where the operating systems market requires further analysis: a) boundaries between the standard roles of consumption and production are blurred in the consideration of operating systems b) novel concepts of ownership c) the decoupling between services and physical supports raises issue of control rather than ownership. In the digital mobile environment, consumers do produce valuable services, or add value to the standard services sold to them. These generate information and data. These data become necessary for the actors operating in other layers of the production chain to add value to their services and products, and to generate brand-new services and applications. Thus, a novel situation occurs: the overall welfare of the system cannot be subdivided into consumer surplus and producer surplus; producers might appropriate some part of the overall welfare by becoming “consumers” themselves of the information and data generated by the (previously-labelled) consumers. We suggest that policy guidelines based on the standard industrial organization analysis are no longer quite so valid and legitimate. The concept of surplus changes meaning when the “consumption” side of the ecosystem can add value and generate new surplus to the “production side”. In the digital mobile industry, most of the inputs used by consumers are not really owned by them. Most of the inputs (intended in terms of both services and goods) utilized by the end user cannot be employed by the latter at will, according to their own “utility function”. The concept of ownership in law and economics is defined by the condition that the “owner” has the right to exclude others from the use of their property and can control the way in which others can restrain their use. The problem of control retraces standard issues covered by “vertical analysis” in competition policy (in terms of foreclosure, discrimination, and fair usage). The literature dealing with the problem of vertical restraints addressess: how ownership in one layer of the chain affects the control of elements or modules in other layers of the vertical production chain, and therefore their usage. The way in which vertical restraints shifts the rights of actors along the chain is a problem much less developed in the literature and we are not aware of any work explicitly modelling and developing this issue.

Cross-platform Mobile Development Based on MDA Approach

Nowadays, the mobile operating systems market (Android, IOS, Windows Phone …) continues to grow. It has become a real challenge for application vendors to provide versatile applications in this competitive market in a short time. The challenge is even greater if the application is planned for multiple platforms whose the operating systems uses different technologies, namely, IOS/Objective-C environment for the Phone and the IPad, Java SDK for Android, etc. This fragmentation makes mobile application development rather difficult and very expensive, hence the use of cross-platform development. To address the cross-platform development different approach exist, the choice was focused on the MDA approach whose principle is the elaboration of various UML models. By studying in detail various target platforms on the basis of a set of criteria and performing a model for each criterion, the aim of our research work is to elaborate a meta-model from UML models realized for each platform.

A study of android malware detection techniques in virtual environment

With the rapid development of mobile environment, cyber-attacks have become more commonplace and more sophisticated. In smartphone operating system market, in particular, Android platform accounts ...

The diffusion process, competitive relationship, and equilibrium analysis of smartphone operating systems

ABSTRACTThis study started from the perspective of predicting science and technology competition, building on this to discuss the dynamic competition between Android and iOS by sales volume in each quarter. The Lotka–Volterra system of equations, one well-known competitive diffusion models, has been adopted to represent the competitive situations of the smartphone operating system market, with the Lyapunov function used to carry out equilibrium and stability analysis. The results showed that Android and iOS have a predator–prey relationship, in which iOS serves as the predator, and Android as a prey. The equilibrium and stability analysis show that both products are able to coexist in the market, and thus, each system has its own stable sales volume.

As Antitrust Case Ends, Microsoft is Victorious in Defeat

As the final judgment in the celebrated Microsoft case ends, this piece very briefly assesses the impact of its remedy. When evaluated in terms of its most important goals, the remedy has proven to be a failure. Microsoft's monopoly power in the PC operating systems market is now as great as it was when the case was brought in 1998 or the remedy was ordered in 2002. The article also very briefly discusses the implications of this remedy for Google and AT&T.