Information Industry Research Articles

Conducting industry informant interviews to advance healthy food retail initiatives: challenges, opportunities, and lessons.

Retail food environments influence dietary health, yet efforts to improve them have had limited success. Recruiting informants from the food and beverage retail industry for insider information has been challenging due to the sensitivity of inquiries and proprietary protections. Moreover, which recruitment approaches are successful are seldom disseminated. This paper aimed to bridge this gap by detailing the complexities of recruiting and interviewing four food industry insider groups-independent store owners, corporate chain managers, food and beverage distributors, and sales representatives of major companies-to provide insights and specific guidance for future research. From October 2021 to November 2022, we interviewed 49 industry informants to explore business and commercial practices used in the US food retail sector. Recruitment methods were tailored to each group, and qualitative data were collected through in-person or virtual 'walk-along' interviews with customized interview guides. Across the study, we experienced distinct challenges around participant inaccessibility, hierarchy within corporate chains, skepticism, mistrust and variation in knowledge across industry groups. We detail our response to these challenges through four lessons learned, including persistence and flexibility, the importance of vetting, the value of trust-building measures and adapting the study protocol to new information. Given our success in reaching industry groups and accessing insider information, we provide key recommendations that future researchers can use to engage diverse industry groups and advance efforts to promote healthy food retail.

Business Development Strategy in Telecommunication Company at PT XYZ

The rapid and dynamic growth of the telecommunications and information industry in the era of Society 5.0 presents significant challenges for telecommunication providers, including PT XYZ, a leading telecommunications service company in Indonesia. This study aims to analyze internal and external factors affecting PT XYZ's business revenue, formulate alternative strategies, and prioritize business strategies to address challenges and enhance revenue. Using qualitative methods, data collection involved observation, interviews, surveys, and literature reviews, drawing from primary and secondary sources. The study employed SWOT, PESTLE, and Porter’s Five Forces analyses to evaluate the company’s environment comprehensively. Findings indicate that PT XYZ is positioned in cell I (Grow and Build) in the IE matrix, with IFE and EFE scores of 3.851 and 3.0, respectively. Recommended strategies include market penetration, product development, and integrative strategies such as ERP implementation to enhance operational efficiency and adapt to technological changes. The study underscores the importance of creating a diverse portfolio of customer-driven technology products and expanding market reach while adopting effective risk management practices. These strategies are expected to sustain PT XYZ’s competitive position and drive revenue growth in the telecommunications industry.

A Security Posture Assessment of Industrial Control Systems Based on Evidential Reasoning and Belief Rule Base.

With the rapid advancements in information technology and industrialization, the sustainability of industrial production has garnered significant attention. Industrial control systems (ICS), which encompass various facets of industrial production, are deeply integrated with the Internet, resulting in enhanced efficiency and quality. However, this integration also introduces challenges to the continuous operation of industrial processes. This paper presents a novel security assessment model for ICS, which is based on evidence-based reasoning and a library of belief rules. The model consolidates diverse information within ICS, enhancing the accuracy of assessments while addressing challenges such as uncertainty in ICS data. The proposed model employs evidential reasoning (ER) to fuse various influencing factors and derive security assessment values. Subsequently, a belief rule base is used to construct an assessment framework, grounded in expert-defined initial parameters. To mitigate the potential unreliability of expert knowledge, the chaotic mapping adaptive whale optimization algorithm is incorporated to enhance the model's accuracy in assessing the security posture of industrial control networks. Finally, the model's effectiveness in security assessment was validated through experimental results. Comparative analysis with other assessment models demonstrates that the proposed model exhibits superior performance in ICS security assessment.

A Systems Thinking Approach to Improving Firms’ Competitive Capabilities and Firm Performance

AbstractThis research aims to establish how systems thinking (ST) can be used to develop firm competitive capabilities (CC) and improve firm performance (FP). The focus is on ST applications in the South African information and communications technology (ICT) industry. The methodology includes Structural text condensation of relevant literature combined with interviews involving a selection of participants. From the analysis, some of the key findings are that ST enables the firm to contextualize itself in the wider systems environment, which results in improvements in FP. The research stream is specifically on soft ST and its contribution to improvements in firm CC and FP. This research creates an opportunity for further research into how soft ST can be leveraged in delivering firm CC and improvements in FP. The theoretical contribution made in this paper is exploring the relationship/linkage between the different concepts of soft ST, CC and FP.

A nonvolatile magnon field effect transistor at room temperature

Information industry is one of the major drivers of the world economy. Its rapid growth, however, leads to severe heat problem which strongly hinders further development. This calls for a non-charge-based technology. Magnon, capable of transmitting spin information without electron movement, holds tremendous potential in post-Moore era. Given the cornerstone role of the field effect transistor in modern electronics, creating its magnonic equivalent is highly desired but remains a challenge. Here, we demonstrate a nonvolatile three-terminal lateral magnon field effect transistor operating at room temperature. The device consists of a ferrimagnetic insulator (Y3Fe5O12) deposited on a ferroelectric material [Pb(Mg1/3Nb2/3)0.7Ti0.3O3 or Pb(Zr0.52Ti0.48)O3], with three Pt stripes patterned on Y3Fe5O12 as the injector, gate, and detector, respectively. The magnon transport in Y3Fe5O12 can be regulated by the gate voltage pulses in a nonvolatile manner with a high on/off ratio. Our findings provide a solid foundation for designing energy-efficient magnon-based devices.

Ultra-high precision nano additive manufacturing of metal oxide semiconductors via multi-photon lithography

As a basic component of the versatile semiconductor devices, metal oxides play a critical role in modern electronic information industry. However, ultra-high precision nanopatterning of metal oxides often involves multi-step lithography and transfer process, which is time-consuming and costly. Here, we report a strategy, using metal-organic compounds as solid precursor photoresist for multi-photon lithography and post-sintering, to realize ultra-high precision additive manufacturing of metal oxides. As a result, we gain metal oxides including ZnO, CuO and ZrO2 with a critical dimension of 35 nm, which sets a benchmark for additive manufacturing of metal oxides. Besides, atomic doping can be easily accomplished by including the target element in precursor photoresist, and heterogeneous structures can also be created by multiple multi-photon lithography, allowing this strategy to accommodate the requirements of various semiconductor devices. For instance, we fabricate an ZnO photodetector by the proposed strategy.

Data Protection Considerations in Competition Law Assessments: A Qualitative Document Analysis of EU Decision Texts

Abstract Personal data are both protected by a fundamental right and serves as a source of market power. As such, a complex interplay between data protection and competition law arises, sparking debate among policymakers and scholars on whether to incorporate data protection considerations (DPCs) in competition law assessments. Proponents argue that competition cases involving such an interplay require a normative contribution from data protection law, while opponents emphasize the practical challenges of considering data protection as a non-economic public policy objective. We identify nine ways in which data protection might ultimately surface in competition law assessments, categorized into five areas: (i) competition enforcement actions, (ii) existing legal and regulatory framework, (iii) personal data collection, (iv) exclusionary abuses, and (v) alleviation of competition concerns. Using a multiple-step approach for qualitative document analysis, we explore how these considerations have surfaced in the European Commission’s decisional practice through a dataset of 2.041 EU competition decision texts based on articles 101 TFEU and 102 TFEU and the EU Merger Regulation. We identify 53 decisions where DPCs have surfaced, especially in the information and communication industry, where they are more frequently subjected to commitments. In line with the evolving literature, we observe an increasingly integrationist trend as these considerations surface more frequently, particularly since the adoption of the General Data Protection Regulation in 2016 and the Digital Markets Act proposal in 2020. We also find a pattern where data protection provisions are included in commitments as a ‘tick-the-box’ exercise. Several influential alleviations of competition concerns suggest that the Commission is more comfortable using data protection to approve transactions unconditionally rather than as a substantive argument for commitments. We conclude by making a case for a more collaborative approach based on the European Court of Justice’s recent Meta Platforms (2023) judgment. Data protection should be considered in competition law assessments if its normative contribution is required. Such a stance would simply align with the internal logic of competition law without unlawfully expanding its material scope.

Factors associated with Ontario dairy producers' management and care of down dairy cattle.

The objective of this study was to better understand current management practices for down cows in Ontario, Canada, and to identify factors associated with the adoption of acceptable practices. An online survey was distributed to all dairy producers in Ontario, Canada (n = 3,367) and was available from November 2020 to March 2021, inclusive. Dairy producers were identified through their provincial dairy organization and contacted via email, and the survey was also promoted via social media. The survey was comprised of 134 questions, 31 of which were related to down cow management. Descriptive statistics were evaluated, and 2 logistic regression models were generated using Stata 17, exploring factors associated with 1) relocating down cows with hip lifters and 2) assisting cows to stand within an hour after discovering a down cow. A total of 226 producers responded (7.4%). Participants were predominantly male (68%), farm owners (78%), and 30-39 years old (29%). Producers reported relocating down cows with a boat or sled (32.6%), front-end loader bucket (31.4%), hip lifters (28.0%), or 'other' (with a text box to further describe) (8.0%). The median time to relocating a down cow after identifying her was 1 h (range 0 - 17h). Farms that relocated a down cow sooner after identifying her as down, were more likely to use appropriate methods to move the cow. However, we also found that farms that provided feed and water sooner to down cows, were more likely to use an inappropriate method (hip lifters) to move her. Farms that used hip lifters to move cows had higher odds of assisting a cow to stand within an hour following the discovery of recumbency. Additionally, producers who waited longer to relocate a down cow were less likely to assist the cow to stand within one hour of finding them down. Research has identified effective management practices for down cows, yet there remains a gap in understanding the implementation and the decision-making process of producers. Data from this study will be helpful in designing future research that further explores the barriers and motivations of producers when implementing evidence-based management plans to care for down dairy cows and may help inform current industry extension efforts.

The Performance Implications of Management Control Systems and Dynamic Capabilities: Evidence from Vietnam

Drawing on the resource-based view and dynamic-capability view, this study examines the relationship between the interactive use of management control systems, dynamic capabilities, and firm performance in the Vietnamese information and communication technology industry. The research model and hypotheses have been tested by partial least squares-structural equation modelling (PLS-SEM) with 240 survey samples obtained from managers working in Vietnamese information and communication technology firms. The results indicate that the interactive use of management control systems has a positive effect on dynamic capabilities. Additionally, both the interactive use of management control systems and dynamic capabilities have direct positive effects on firm performance. The results reveal that dynamic capabilities complementary mediate the relationships between the interactive use of management control systems and firm performance. This study provides theoretical and managerial implications for Vietnamese information and communication technology firms that are striving to develop management control systems and dynamic capabilities for enhancing firm performance.

Factors impacting investment decisions in ict industry

The article analyzes the main factors influencing investors’ decisions on the advisability of investing capital in companies in the information and communication technology industry. The present article’s relevance lies in identifying the main investment objectives that determine investment decisions in innovative sectors of the economy which comprise security, growth and stable income and in identifying the most impacting factors on investment attraction in the ICT industry in a number of developed and developing European countries, the main factors being: political stability, legal environment, investments attraction policies; taxation; infrastructure development, level of country digitalization, science and technology; workforce, competitiveness in terms of cost and productivity

Enhancing cybersecurity protocols in tax accounting practices: Strategies for protecting taxpayer information

This paper highlights the importance of enhancing cybersecurity measures in tax accounting to protect taxpayer data. It proposes strategies to ensure compliance and enhance data security in the context of evolving cyber threats. This study investigated the cybersecurity landscape within the tax accounting sector, focusing on prevalent threats, the effectiveness of existing security measures, and areas for improvement. Utilizing a mixed-methods approach, the research combined qualitative interviews with cybersecurity experts and tax accounting professionals, quantitative surveys of 200 tax accounting firms, and detailed case studies of firms that experienced significant cyberattacks. The findings reveal that phishing attacks, ransomware, data breaches, malware, and insider threats are the most common cybersecurity challenges faced by tax accounting practices. While measures such as encryption, multi-factor authentication (MFA), firewalls, intrusion detection systems (IDS), regular security audits, and comprehensive employee training prove effective, their inconsistent implementation across the industry highlighted the need for standardized protocols. The study identified significant gaps in resource allocation, particularly for smaller firms and non-profits, and underscores the necessity for formal incident response plans. Recommendations include enhanced training programs, development of standardized security protocols, resource support for smaller firms, regular security audits, comprehensive incident response plans, and adoption of advanced technologies. The study calls for further exploration of emerging threats, cost-effective solutions for smaller firms, the impact of artificial intelligence (AI) and machine learning (ML), longitudinal studies on cybersecurity practices, and analysis of policy and regulatory impacts. These insights aim to enhance the cybersecurity posture of tax accounting practices, ensuring the protection of sensitive taxpayer information and overall industry resilience.

Інформаційно-комп’ютерна технологія підтримки психічного здоров’я людини з урахуванням її характерологічних властивостей

Introduction. The current stage of the development of society is characterized by an avalanche-like increase in information, which, due to the continuous and rapidly growing pace, has acquired the character of the information industry. Currently, the problem of developing and using information systems in those areas of activity that are related to human health, especially in the areas of psychosocial status of a person who was under the negative influence of stressogenic factors caused by the state of war, is gaining relevance. Therefore, the development of information technology, which includes methods of operative diagnosis of the psychological state of a person, methods of qualifying corrective and rehabilitation measures with the involvement of the willpower of the victims, taking into account their characterological properties and the strength of the personal "I", are of great importance. Providing psychological support to persons who have been under the negative influence of psychogenic factors is an urgent and rather complex problem. We consider it expedient to involve the means of modern computer technologies in its solution. The purpose of the paper is to develop a computer decision-making support system for the rehabilitation of the psychosocial state of health of a person who was under the negative influence of psychogenic factors, taking into account personal character traits. Results. A hierarchical structure of health assessment technology was developed, taking into account personal characterological properties. On the basis of a hierarchical approach, an information-technological structure of classification and evaluation of human character properties has been developed. A program algorithm for the application of rehabilitation measures depending on the strength of manifestation of characterological properties of the individual has been synthesized. A computer system was developed to support rehabilitation decision-making by a person with psychological problems, taking into account his personal character traits. Conclusions. The developed classification of the working information array, which is carried out using a hierarchical approach, systematizes and transforms a huge amount of unordered data related to the psychological component, taking into account the character, into an information product convenient for further computer-technological transformations. The developed information technology, implemented in a computer decision support system, is a constructive tool for increasing the accessibility and efficiency of providing the necessary specific information to the user when choosing rehabilitation measures, taking into account the personal characteristics of his character. Taking into account the characterological components of mental status in the developed computer support system for making rehabilitation decisions by persons who were under the influence of psychological overstrain in connection with martial law increases the purposefulness of recommendations in the case of independent selection of health measures. Keywords: human character, hierarchical modeling, negative psychogenic factors, mental health, computer decision support system.

Characteristics, drivers and ecological risk assessment of microplastics in the surface water of urban rivers in Guangdong-Hong Kong-Macao Greater Bay Area cities - A case study of Dongguan city

In the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), microplastic pollution in urban rivers is a prominent problem due to the developed economy and high industrial intensity. Using the Xiaohai River, Hanxi River and Dongguan Canal in Dongguan City, an important node city in the GBA, as an example, microplastic characteristics, drivers and ecological risks in the surface water of three rivers were investigated. Results showed that the average abundance of rivers in the wet period (1646.22 ± 154.73 items/m3) was 4.7 times higher than that in the dry period (351.09 ± 34.2 items/m3). Microplastics were mainly in the form of fragments and fibers, with a size range of 30–500 μm, and appeared transparent with white color. The microplastic polymer types PE, PP, PET and PA accounted for more than 70%. There are large differences in the characteristics of microplastic pollution during different hydrological periods. Redundancy analysis showed that the distribution of plastics, chemical materials, packaging and printing industries along the rivers dominated the differences in microplastic abundance. The electronic information industry contributed most to the composition of microplastic polymer types. The polymer hazard index, pollution load index, and potential ecological risk index for rivers indicate a medium-high risk classification or higher. Therefore, the industrial layout along the urban rivers should be rationalized, the disposal of microplastics in wastewater should be increased, and the use of green plastic products should be promoted. This study provides support for the management of microplastic pollution in urban surface water in the GBA.

Teaching Reform of RFID Principles and Application Course with Information Industry Integration for System Capability Cultivation

The rapid development of the domestic information industry ecosystem has put forward higher requirements for the quality of computer talent training in colleges and universities. In response to the current issues of outdated course content and lagging teaching strategies in RFID principles and application courses at applied undergraduate institutions, measures have been proposed to promote the cultivation of talent for the autonomous and controllable RFID industry, taking the system capability as the main line. Under the guidance of the engineering education certification standards, based on the Tyler curriculum development model, domestic RFID platforms are introduced into the classroom. Through innovative reforms of the objectives, content, methods, and evaluation system of the RFID principles and application courses, the integration into the information industry ecosystem is actively promoted, enhancing the effective integration of the education chain, industry chain, innovation chain, and talent chain, contributing to the national strategy of independent control.

Application of high performance computing and deep neural network learning in intelligent city mechanical product recommendation

Intelligent city is a product of the deep integration of information technology, industrialization and urbanization, which has a large number of intelligent mechanical products. The users widely evaluate their application characteristics, and the selection of mechanical products based on user evaluation has become a trend. Nowadays, personalized mechanical product recommendation based on user evaluation is more and more widely used. However, due to the sparse evaluation data, the recommendation accuracy needs to be improved. In this paper, the principle of matrix decomposition is deeply analyzed in order to provide useful ideas for solving this problem. The bias weight hybrid recommendation model of user preference and rating object characteristics is proposed, and the corresponding hybrid recommendation algorithm is designed. First, estimated data obtained using the matrix decomposition principle is supplemented to the sparse data matrix. Secondly, according to the characteristics of users and ratings, initial positions were set based on the statistical distribution of high-performance computing data, and bias weights were set by incorporating each feature. Finally, the nonlinear learning ability of deep neural network learning is used to enhance the classification effectiveness. Practice has proved that the constructed model is reasonable, the designed algorithm converges fast, the recommendation accuracy is improved by about 10%, and the model better alleviates the problem of sparse scoring data. The practical application is simple and convenient, and has good application value.

Preface

Abstract During June 21-22, 2024, the 2nd International Conference on Computer Technology and Information Science (CTIS2024) was successfully held online. This conference included keynote speeches, invited speeches, oral and poster presentations. Prof. Yong Yue from Xi’an Jiaotong-Liverpool University (XJTLU), China; Assoc. Prof. Lei Chen from Shandong University, China and Dr. Binqiang Wang from Inspur (Beijing) Electronic Information Industry Co. Ltd attended the conference and delivered keynote speeches. In addition, experts and scholars from the Guizhou Normal University, Guiyang, China; Harbin Institute of Technology; IEIT SYSTEMS Co., Ltd.; Kansai University, Osaka, Japan and other universities and institutes shared wonderful speeches. This conference proceedings included 7 accepted articles selected from 39 submissions, all the papers have been through rigorous review and process to meet the requirements of international publication standard. We would like to express our gratitude to the reviewers of these manuscripts, who provided constructive criticism and stimulated comments and suggestions to the authors. We are extremely grateful as organizers, technical program committee and editors and extend our most sincere thanks to all the authors for their excellent contribution and work. Our sincere gratitude also goes to the IOP Publishing editors and managers for their helpful cooperation during the preparation of the proceedings. On behalf of the Organizing Committee of CTIS2024. List of Technical Program Committee is available in this Pdf.

Розвиток систем обліково-аналітичного забезпечення в умовах цифрової трансформації інформаційної індустрії

The article analyzes the current state and development of accounting and analytical systems in the context of the digital transformation of the information industry, a critical issue for enterprises in this sector. The study examines the main trends and challenges companies face due to the active implementation of digital technologies in accounting and analytical activities. It characterizes the critical aspects of how digital transformation impacts the processes of data collection, processing, and analysis within the modern information industry. The article proposes new approaches to organizing accounting and analytical systems that meet the digital economy’s demands. It explores the potential of modern information technologies to enhance the effectiveness of management decisions based on the analysis of large data sets, which contributes to increasing enterprises’ competitiveness in the digital environment. Additionally, the article highlights the necessity of integrating advanced technologies into financial control and management processes. The research identifies prospects for developing accounting and analytical systems, considering global digital trends. Recommendations are developed to improve the adaptability of information industry enterprises to the rapidly changing digital environment. Through a comprehensive analysis, the article underscores the importance of adapting to and leveraging digital transformation to enhance operational efficiency and maintain a competitive edge. The findings suggest that the ongoing digital revolution in accounting and analytics presents opportunities and challenges, requiring businesses to innovate and continuously adapt their systems and processes. This will ensure they remain resilient and competitive in an increasingly digitized global market. In the future, research in this field should focus on integrating the latest digital technologies, such as artificial intelligence and blockchain, which can significantly improve the accuracy and speed of data processing. Also, an important direction is the development of new analytical forecasting models based on big data, which will help to make management decisions more effectively. Keywords: Digital transformation, accounting systems, analytical systems, information industry, big data, competitiveness, financial control, management efficiency, modern information technologies, digital economy.

Revolutionizing Network Intelligence: Innovative Data Mining and Learning Approaches for Knowledge Management in Next-Generation Networks

The Information and Communication (ICT) industry, a global giant among service sectors, is known for both its massive scale and its unforgiving demands. Here, downtime is unacceptable, requiring constant high availability – often at the stringent Sigma Six standard. Redundancy is a common solution, but it comes at a cost. To meet these demands proactively, the ability to predict load and growth becomes crucial. This project aims to develop a prototype, or proof of concept, that utilizes data mining to provide early warnings and growth forecasts for the ICT industry with good accuracy. Big data is key to making discoveries in any data analysis project. Normally, this data comes from real-time system logs. However, for this initial test, I used a dataset called MIT Reality Mining. This dataset is useful because real-world companies, especially in the tech industry (ICT), are often hesitant to share their current information. By using MIT Reality Mining, I could still find trends and potential reasons behind them in the ICT industry. It's important to remember that this is a limited functionality prototype. While it can serve as a guideline for Telcos looking to implement data warehouses, the actual implementation details will need to adapt to the specific needs of each industry.

Achieving the United Nations sustainable development goals – innovation diffusion and business model innovations

Purpose The study aims to analyse the race towards green development and United Nations sustainable development goals (SDGs) in the cases of Huawei and Shell. Both companies are the leaders in their respective industries. Huawei is an example case study representing the information and communications technology (ICT) industry whereas Shell is an example case study representing the oil and gas industry. The research analyses of the races in achieving UN SDGs were undertaken based on the innovation diffusion framework with the use of machine learning algorithms trained to extract data on sustainability activities and initiatives. Design/methodology/approach The research analyses the two case studies of Huawei and Shell. The research was undertaken through the steps of training machine learning algorithms, industry benchmarking and evaluating the performance of the race. The analyses regarding the activities and initiatives of Huawei and Shell in contributing towards SDGs are based on the data in the past 10 years (Years 2010–2019) using machine learning to extract data on sustainability activities and initiatives. In the case of Huawei, 313 sustainability reports were fed to the unsupervised machine learning algorithms revealing 15,101 sustainability actions and initiatives related to UN SDGs in the ICT industry. In the case of Shell, 2,015 sustainability reports were fed to the unsupervised machine learning algorithms revealing 47,365 sustainability actions and initiatives related to UN SDGs in the oil and gas industry. Findings The analyses of findings revealed that Huawei and Shell performed very well in progressing towards the UN SDGs. Huawei had strong performance in the ICT industry with regard to SDGs No. 3, 4, 7, 8, 11, 12 and 16 while Shell had strong performance in the oil and gas industry with regard to SDGs No. 3, 4, 6, 7, 8, 12 and 16. Both companies had placed a focus on achieving SDG 12 responsible consumption and production, SDG 7 affordable and clean energy and SDG 4 quality education. The synthesised business model innovations of Huawei and Shell had shown their environmental, social and governance strategies – Huawei’s 2030 vision for green development and Shell’s 2050 vision for net zero emissions. Practical implications The five pillars of people, planet, prosperity, peace and partnership according to the UN 2030 agenda for sustainable development have shown the way a company operates to promote sustainable eco-systems. The extent to which both Huawei and Shell link corporate strategies to the UN SDGs has reflected their implementation progress. Furthermore, the business model innovations of Huawei and Shell provides a useful framework which can be applied to encourage other companies/organisations in various industries to undertake ESG activities in practice. Originality/value The main contribution of this research is the application of machine learning algorithms and the innovation diffusion model in analysing the SDGs performance. The study applies the innovation diffusion framework to explore strategic actions and initiatives of Huawei and Shell in transitioning towards sustainability. The use of machine learning algorithms has identified their sustainability approach in achieving the UN SDGs.

Social problems of the informatization of the society

The article is devoted to the problems of the impact of informatization on society. Some theories of the post-industrial information society are discussed. These theories are constructed on emphasizing the role of the influence of informatization on the social development of society. An attempt is made to trace the basic ideas of D. Bell's, Y. Masuda's, J. J. Servan-Schreiber's, and A. Toffler's theories of the information society. Some other empirical researches on the economic and social consequences of informatization are analyzed. The attention is paid to phenomena of the information industry, the social role of electronic communications, information technology and work, social limitations on the use, and political aspects of the new information technology, as well as the problems of the international transfer of information.