Growth Of Information Technology Research Articles

Informaciona podrška u procesu revizije finansijskih izveštaja

In modern times, financial statements audit without application of information technologies is inconceivable. Many factors add to necessity of incorporating informational support into the auditing process, such as: a large number of client's transactions and a large volume of client's data to be audited; application of information technology in client's accounting data processing; availability of client's data in electronic form; emergence of an increasing number of auditing activities that need to be implemented within strict deadlines; dislocation of audit team members etc. This paper aims at observing the major specifics of integration of informational support into financial statements audit. The main method used in this paper for investigation of the impact of information technologies on auditing process is the existing literature analysis from several aspects: the role of audit in professional decision-making, methodology of financial statements audit and information technology types applied in audit. Our work shows that the emergence of information technologies helps auditors in the audit process.

ПЕРИОДИЗАЦИЯ А.Н. КОЛМОГОРОВА КАК ОСНОВА ПРЕДСТАВЛЕНИЙ ОБ ИСТОРИИ РАЗВИТИЯ МАТЕМАТИЧЕСКОЙ НАУКИ

The periodization of the development of mathematical science was proposed by A.N. Kolmogorov. He identifies four periods in the development of mathematics. The basis of periodization includes assessment of the content, level of achievements and features of mathematical research: its most important methods, results, ideas. Particular attention is paid to the development of probability theory structured according to Kolmogorov periods. The prerequisites for the formation of probability theory began to appear during the second millennium BC — the first period. During the period of accumulation of knowledge (before 600 BC), the concept of “chance” — the main concept in the science in question – began to develop. Until the third period, the concept was invariably associated with the philosophical category “fate,” that is, a certain predetermined process, which contradicts modern ideas about chance. Probability Theory received its unofficial name precisely from the period of elementary mathematics (before the 15–16th centuries) — the second period. The next period was called by Kolmogorov “Mathematics of Variables” (XVII–XVIII centuries). Since the beginning of the period of modern mathematics (since the 19th century), random variables and the patterns associated with them have come to the fore in probability theory. This is due to the general scientific growth in the 19th century. The main problems that arose by the end of the third period are being solved: all the basic concepts, rules for their application, and theorems are clearly defined. By the beginning of the 20th century — the fourth period–there was a need to formalize the acquired knowledge. Andrei Nikolaevich built a system based on modern and already developed by that time set theory and measure theory. The periodization of the development of mathematical science, proposed by A.N. Kolmogorov, with the rapid progress of mathematical knowledge and the emergence of information technologies in the future may require adjustments to the last stage of development of the history of mathematics or will lead to the emergence of a new stage of periodization.

National industrial investment fund and China's integrated circuit industry technology innovation

Since the emergence of information technology, the integrated circuit industry has been a major contributor to sustained economic expansion. This paper proposes a theoretical model premised on the pertinent theories of technological progress in late-mover countries and concludes that it is challenging for late-mover countries to rely solely on market mechanisms to elevate the level of social technology; state policy support is indispensable. In addition, this paper employs the panel data of 81 A-share listed integrated circuit companies in China from 2011 to 2019 and implements the Difference in differences (DID) method to evaluate the impact of the National Integrated Circuit Industry Investment Fund on the technological innovation of the integrated circuit industry, and adopts the double-difference propensity score matching method for supplemental verification. This paper concludes that the National Integrated Circuit Industry Investment Fund has significantly enhanced industrial technological innovation and that the estimated results premised on the difference-in-difference based on propensity score matching (PSM-DID) method and the placebo test are not substantially differentiated from the benchmark regression results. The effects of industrial investment funds on policy are evidently different across different regions and industry chains, in accordance with research on industry heterogeneity. The promotion effect of the core link is significantly stronger than the support link in terms of branches of the industrial chain, and the Pearl River Delta region has a more pronounced promotion effect in terms of regions. Verification of the mechanism demonstrates that industrial investment funds can relieve corporate financing constraints, optimize corporate human capital structure, promote corporate RandD (research and development) investment, and subsequently promote technological innovation in the integrated circuit industry through the aforementioned three effects. On the one hand, the research presented in this paper offers empirical support and policy guidance for the implementation of technological innovation in China's integrated circuit industry. On the other hand, it also has significant reference value for fostering the growth of industrial investment funds.

Impact of the development of information society on healthcare efficiency: Empirical evidence from 31 Chinese provinces.

The development of information society has deeply changed the style of the healthcare service delivery and medical information access. This study aims to investigate how the information society development affects the efficiency of healthcare system in China, and explore provincial disparities in the impact. Based on the two-stage Data Envelopment Analysis (DEA) framework, this paper uses a panel data from 31 Chinese provinces from 2014 to 2017 to estimate efficiency of healthcare service and analyze the influence of the development of information society on efficiency. With the information society index (ISI) increased from 0.423 to 0.488 during the sample period, the healthcare efficiency experienced a slight decrease from 0.892 to 0.869. Moreover, the pure technical efficiency (PTE) is much lower than the scale efficiency (SE), and thus is the key to enhance the overall technical efficiency (TE). The time-fixed Tobit regression analysis suggests that information society development leads to a significant increase in PTE, but results in a decrease in SE, and therefore has little effect on TE. Further analysis reveals that the impact differs sharply between low-efficiency and high-efficiency provinces. For the low-efficiency provinces, the TE increases significantly with the development of the information society, mainly due to a considerable increase in PTE. In contrast, the TE decreases for the high-efficiency provinces, mainly caused by a decrease in SE. This paper highlights the importance of information infrastructure investment in healthcare system and the application of emerging information technologies to breakout the time and space boundaries of healthcare services in improving overall efficiency. In inefficient provinces, it is also necessary to properly control the growth of healthcare inputs.

중국 노인용 웨어러블 워치의 디자인 요소가 사용자 인식과 사용의향에 미치는 영향

With the aging of the population intensifies, the medical care of the elderly has brought a heavy burden to the social and economic development. Facing the rapid growth of the elderly population and the increasingly prominent problems of the elderly, the new scientific and technological means represented by “Internet” have provided a new way of thinking to solve the problems of the elderly. At present, wearable watches for health monitoring of the elderly have been launched in the market. This paper hopes to test the influence of design factors of wearable watches on user perception and willingness to use through the application of technology acceptance model, so as to improve the willingness of the elderly users to use the product. Technology acceptance model is mainly used to study users’ acceptance behavior and attitude towards emerging information technology. Through the first study on the design factors of wearable watches and technology acceptance model, it determined the four design factors of wearable watches including functionality, aesthetics, interactivity and compatibility, and the three variables of user perception in technology acceptance model including perceived pleasantness, perceived ease of use and perceived usefulness. In this paper, 236 questionnaires were collected by questionnaire survey. Firstly, SPSS26.0 was used to test and analyze the reliability and validity of the questionnaire data, and used structural equation software to test the model hypothesis. The results show that functionality has a positive impact on perceived pleasantness, perceived ease of use and perceived usefulness, aesthetics has a positive impact on perceived pleasantness and perceived ease of use, interactivity has a positive impact on perceived ease of use, compatibility has a positive impact on perceived ease of use, perceived usefulness, perceived ease of use and perceived pleasure have a positive impact on willingness to use. The results of the study can provide reference for the developers of wearable watches for the elderly to formulate marketing strategies, and provide data and practical theoretical basis for product design.

Multifunctional Spin Logic Operations in Graphene Spin Circuits

Spin-based computing, combining logic and nonvolatile magnetic memory, is promising for emerging information technologies. However, the realization of a universal spin logic operation, representing a reconfigurable building block with all-electrical spin-current communication, has so far remained challenging. Here, we experimentally demonstrate reprogrammable all-electrical multifunctional spin logic operations in a nanoelectronic device architecture, utilizing graphene buses for spin communication and mixing and nanomagnets for writing and reading information at room temperature. This device realizes a multistate spin-majority logic operation, which is reconfigured to achieve (n)and, (n)or, and xnor Boolean operations, depending on the magnetization of inputs. The results are in good agreement with the predictions from a spin-circuit model, providing an experimental demonstration of a spin-based logic unit that takes advantage of the vector nature of spin, as opposed to conventional scalar charge-based devices. These spin logic operations in large-area graphene are fully compatible with industrial fabrication processes and represent a promising platform for scalable all-electric spin-based logic-in-memory computing architecture.

Supply chain finance: What are the challenges in the adoption of blockchain technology?

As an emerging information technology, blockchain has aroused extensive discussions around the world and been suggested as a solution to address current issues in supply chain finance (SCF). The Chinese government also attaches great importance to this technology, and many Chinese state-owned enterprises have invested in establishing their own blockchain research and development centres. However, there is a lack of studies on identifying challenges when deploying this technology; theoretical framework and conceptual exposition are also scarcely seen. Therefore, the aim of this study is to investigate the challenges and obstacles in the adoption of blockchain technology in SCF. An exploratory case study of a Chinese state-owned enterprise was conducted to build up an initial conceptual framework. Semi-structured interview was applied to collect data from the case firm's employees, top management, and technical specialists. The results of the analysis indicate that in the adoption of blockchain technology, there are technological, operational, and other challenges. From a technological perspective, framework identification, cross-chain interoperability, and data governance are major barriers; whereas, from an operational perspective, the new business process and transformation in the entire supply chain are identified as challenges. Besides, other obstacles such as the elimination of jobs and regulatory issues are also not neglectable. This study contributes to research on blockchain and supply chains by shedding light on the challenges of blockchain adoption through an exploratory case study of a Chinese state-owned enterprise. A conceptual framework was generated as a basis for future research, and the findings also provide insights for companies that may or are planning to adopt blockchain technology.

Research and practice on the intelligent transformation of the gate control system in a large hydropower station

With the development of information technology, the research on the hydropower stations intelligence has gradually become an important indicator for the evaluation of the hydropower industry. Therefore, it is of great significance to carry out the intelligent transformation of relevant equipment and systems in hydropower stations by integrating emerging information technology. In view of the implementation content of the intelligent project transformation of the gate control system in a large hydropower station, this research studies the structural design of the control system, the power supply design, the component selection, the multiple landing gate function, the intelligent protection and monitoring function, and the intelligent network architecture design of IEC61850, and analyses the practice on the intelligent transformation. Therefore, this paper can provide a certain reference for the intelligent transformation, research, and development of the gate control system of hydropower stations.

Machine Learning-Driven Approach for a COVID-19 Warning System

The emergency of the pandemic and the absence of treatment have motivated researchers in all the fields to deal with the pandemic situation. In the field of computer science, major contributions include the development of methods for the diagnosis, detection, and prediction of COVID-19 cases. Since the emergence of information technology, data science and machine learning have become the most widely used techniques to detect, diagnose, and predict the positive cases of COVID-19. This paper presents the prediction of confirmed cases of COVID-19 and its mortality rate and then a COVID-19 warning system is proposed based on the machine learning time series model. We have used the date and country-wise confirmed, detected, recovered, and death cases features for training of the model based on the COVID-19 dataset. Finally, we compared the performance of time series models on the current study dataset, and we observed that PROPHET and Auto-Regressive (AR) models predicted the COVID-19 positive cases with a low error rate. Moreover, death cases are positively correlated with the confirmed detected cases, mainly based on different regions’ populations. The proposed forecasting system, driven by machine learning approaches, will help the health departments of underdeveloped countries to monitor the deaths and confirm detected cases of COVID-19. It will also help make futuristic decisions on testing and developing more health facilities, mostly to avoid spreading diseases.

Service Strategy Analysis of Big Data Management in Small and Medium-sized Enterprises

As the basic force to promote the development of national economy, small and medium-sized enterprises face many difficulties in their development process. And big data technology can help them improve the efficiency of enterprise management and enhance the viability of enterprises. The rise of the Internet, relying on big data technology, effectively alleviates the financing problems of SMEs. At the same time, it has a great impact on the traditional credit business of commercial banks. The legal service platform for small and medium-sized enterprises, with the development of emerging information technologies such as Internet, big data and sharing economy, has unique service advantages, which can achieve economies of scale and scope in the process of legal services, and has important practical significance for the healthy and rapid development of small and medium-sized enterprises. However, the innovation and development of small and medium-sized technology-based enterprises are difficult to achieve only by themselves, and they need to be provided with targeted and professional knowledge services by internal knowledge service departments, intermediary service agencies, and government departments, so as to improve the knowledge reserves of small and medium-sized technology-based enterprises and promote their development and innovation. This paper analyzes the relationship between SMEs and big data technology, puts forward problems in terms of awareness, technology, policy and talent, and gives corresponding strategies to help SMEs develop.

Lean and agile supply chain strategies: the role of mature and emerging information technologies

PurposeThe significant changes that supply chains (SCs) are undergoing and the emergence of disruptive technologies have led to a growing effort to integrate novel and mature technologies into existing SC strategies. Thus, this study investigates the relationships between mature information technologies (ITs), emerging IT and the lean supply chain (LSC) and agile supply chain (ASC) strategies.Design/methodology/approachAn empirical study based on structural equation modeling of survey data from 256 Spanish focal companies has been conducted to test six hypotheses.FindingsDrawing on resource orchestration, our results point to mature IT use being an enabler of both LSC and ASC strategy implementation. The results also show an LSC mediating effect on the relationship between mature IT and ASC when SCs follow both strategies. Also, the implementation of emerging IT requires a process of consolidation over time to be genuinely useful as a facilitating mechanism for developing both the lean and agile strategies along the SC. In this sense, a suitable mix needs to be orchestrated between emerging and mature IT.Originality/valueThis study sheds light on the relevance of the mature IT and emerging IT in the context of two SC strategies (lean/agile) and provides practical and theoretical implications.

Emerging information technologies for the next generation of elderly care

Emerging information technologies for the next generation of elderly care

Research on the Path of College Education and Teaching Reform Driven by Artificial Intelligence

With the development of intelligent education and teaching in colleges and universities, the mixed teaching mode of online and offline has become the focus of current college education and teaching reform. From the perspective of concepts and technologies related to online teaching, as well as teachers and students involved in online teaching, there are still problems in online teaching in Chinese universities, such as insufficient interaction between teachers and students, weak autonomy of students' learning, insufficient mastery of new technologies by teachers, and imperfect online teaching platforms. The emerging information technology with AI as the core not only helps to improve the learning experience and teaching efficiency but also plays an important role in realizing personalized learning and improving students' awareness and ability of autonomous learning. This paper studies the problems existing in the online teaching process of Chinese colleges and universities and probes into the education and teaching reform path in colleges and universities based on artificial intelligence technology.

Game-Based Formative Assessment of Analogical Reasoning in Preschool Children: Support from the Internet of Things Technology

Emerging information technology such as Internet of Things (IoT) has been continuously applied and deepened in the field of education, and the learning analytics technology based on children’s games is gradually moving toward practical application research, but there are few empirical studies on the micro level of emerging information technology and learning analytics methods in the evaluation of young children’s learning process and learning effects. As the research content, the study examines preschool children’s analogical reasoning abilities, reflecting their thinking levels and processing abilities. Using a decision tree model in learning analytics, the process data and result data of children’s analogical reasoning games based on Internet of Things technology are analyzed, and the classification model of preschool children’s analogical reasoning is constructed. The study found that the learning analysis of analogical reasoning based on games mediated by IoT technology is feasible and effective.

When is the processing of data from medical implants lawful? The legal grounds for processing health-related personal data from ICT implantable medical devices for treatment purposes under EU data protection law.

Medicine is one of the biggest use cases for emerging information technologies. Data processing brings huge advantages but forces lawmakers and practitioners to balance between privacy, autonomy, accessibility, and functionality. ICT-connected Implantable Medical Devices plant themselves firmly between traditional medical equipment and software that processes health-related personal data, and these implants face many data management challenges. It is essential that healthcare providers and others can identify and understand the legal grounds they rely on to process data. The European Union is currently updating its framework, and the special provisions in the GDPR, the current ePrivacy Directive, and the coming ePrivacy Regulation all provide enhanced thresholds for processing data. This article provides an overview and explanation of the applicability of the rules and the legal grounds for processing data. We find that only a cumulative application of the GDPR and the ePrivacy rules ensure adequate protection of this data and present the legal grounds for processing in these cases. We discuss the challenges in obtaining and maintaining valid consent and necessity as a legal ground for processing and offer use case-specific discussions of the role of consent long-term and the lack of an adequate 'vital interest' exception in the ePrivacy rules.

A Bibliometric Study of Digital Government in Domestic and Foreign Area

The digital government is supported by emerging information technology, with an integrated online government service platform as the carrier, through the all-round and systematic reform of the government, to achieve a new government operation model of precise governance and efficient service, which is one of the main contents of the construction of digital China. This paper adopts bibliometric method and comparative analysis method to analyze the theoretical connotation and construction practice of digital government at home and abroad, in order to provide reference for the related construction.

Evolution dynamic of intelligent construction strategy of coal mine enterprises in China

The intelligent construction of coal mining enterprises is the fundamental strategy to prevent and curb major coal mine accidents, and the core technical support to realize the high-quality development of the coal industry. Considering the intelligent construction of coal mining enterprises enabled by emerging information technologies such as 5G and artificial intelligence, this paper constructs a Moran process stochastic evolutionary game model of intelligent construction of coal mining enterprises. Based on the fixed point probability of the Moran process, the probability of successful invasion of the "intelligent construction" strategy and the "traditional production" strategy in the limited coal mining enterprise group is calculated. By comparing the probability of individual fixed point and the probability of neutral mutation, the dominant condition of the strategy under strong selection and weak selection is obtained. The research shows that external stochastic factors, the number and scale of enterprises, the intensity of capacity replacement and the cost-benefit of intelligent construction are the main factors affecting the intelligent construction behavior of coal mining enterprises. When the intelligent construction of coal mining enterprises is in the cultivation period, the intelligent construction of underground coal mines dominated by stochastic factors can be effectively promoted by increasing the intensity of capacity reduction replacement. For the open-pit coal mine dominated by expected payoffs, reducing the number of mining rights and improving the concentration of open-pit coal mining industry will have a better effect on promoting its intelligent cultivation process. When the intelligent construction of coal mining enterprises is in the mature stage, with the improvement of the cost and benefits of intelligent construction, "intelligent construction" strategy will become a general consensus of coal mining enterprises. In addition, this paper analyzes the relevant parameters through specific examples to verify the effectiveness of the conclusions, which provides a scientific basis for effectively accelerating the intelligent construction of coal mining enterprises and promoting the transformation and upgrading of the coal industry.

Critical Factors Affecting the Promotion of Emerging Information Technology in Prefabricated Building Projects: A Hybrid Evaluation Model

Emerging information technology (EIT), characterized by intelligence, digitization, and automation, can facilitate activities such as stakeholder cooperation, information management, and construction management to enhance the overall performance in prefabricated building projects (PBPs). A variety of EITs are currently being used in PBPs, but their development is relatively sluggish and still in the infancy stage. Previous studies have explored the challenges and barriers of EIT in PBPs; however, the correlations between these factors have not been thoroughly examined. Therefore, the goal of this study is to pinpoint the characteristics and connections between EIT-affecting elements. Based on the technology–organization–environment (TOE) framework, this study firstly summarizes 20 influencing factors of EIT adoption and promotion in PBPs mentioned in the previous literature through a literature review. Then, EIT experts were invited to conduct semi-structured interviews to evaluate the relationship and the degree of influence among 20 influencing factors. Finally, the DEMATEL-ISM approach was used to assess the characteristics of each factor and the hierarchy between them. The results demonstrated that the influencing degree of the environmental dimension was more significant and had a greater influence on the whole network of influencing factors. The factors of the organizational dimension have a higher influenced degree and are easily influenced by other factors. Due to the current lack of awareness of EIT, the majority of the technology-related influencing factors have a less significant effect on adopting and promoting EIT. In summary, this study assists in analyzing the characteristics and correlations of the factors that influence EIT adoption and promotion in PBPs and identifies critical influencing factors. It also aids the government and stakeholders in developing a deeper understanding and knowledge of EIT, thereby promoting the development of EIT in PBPs.

The Technology-Oriented Pathway for Auxiliary Diagnosis in the Digital Health Age: A Self-Adaptive Disease Prediction Model.

The advent of the digital age has accelerated the transformation and upgrading of the traditional medical diagnosis pattern. With the rise of the concept of digital health, the emerging information technologies, such as machine learning (ML) and data mining (DM), have been extensively applied in the medical and health field, where the construction of disease prediction models is an especially effective method to realize auxiliary medical diagnosis. However, the existing related studies mostly focus on the prediction analysis for a certain disease, using models with which it might be challenging to predict other diseases effectively. To address the issues existing in the aforementioned studies, this paper constructs four novel strategies to achieve a self-adaptive disease prediction process, i.e., the hunger-state foraging strategy of producers (PHFS), the parallel strategy for exploration and exploitation (EEPS), the perturbation–exploration strategy (PES), and the parameter self-adaptive strategy (PSAS), and eventually proposes a self-adaptive disease prediction model with applied universality, strong generalization ability, and strong robustness, i.e., multi-strategies optimization-based kernel extreme learning machine (MsO-KELM). Meanwhile, this paper selects six different real-world disease datasets as the experimental samples, which include the Breast Cancer dataset (cancer), the Parkinson dataset (Parkinson’s disease), the Autistic Spectrum Disorder Screening Data for Children dataset (Autism Spectrum Disorder), the Heart Disease dataset (heart disease), the Cleveland dataset (heart disease), and the Bupa dataset (liver disease). In terms of the prediction accuracy, the proposed MsO-KELM can obtain ACC values in analyzing these six diseases of 94.124%, 84.167%, 91.079%, 72.222%, 70.184%, and 70.476%, respectively. These ACC values have all been increased by nearly 2–7% compared with those obtained by the other models mentioned in this paper. This study deepens the connection between information technology and medical health by exploring the self-adaptive disease prediction model, which is an intuitive representation of digital health and could provide a scientific and reliable diagnostic basis for medical workers.

Implications of Blockchain Application to Accounting Education and Accounting Practice

Accounting is part of the information system of a company that generates the most important information for the decision-making process. This process should be supported by new technologies to respond to all business requirements. Disruptive technologies change the way of performing business transactions and their implementation in business practice was notably accelerated by the pandemic. In this context, Blockchain technology has been articulated as the future of the accounting profession and there is a growing body of research regarding the impact of the blockchain on accounting practice and the accountancy profession. Many advantages arise from blockchain technology's distinctiveness, but also many risks that need special attention. Consequently, evolving conditions require professional accountants around the world to master new skills related to emerging information technologies. Being accustomed to information technologies is one of the basic prerequisites for the quality service that professional accountants offer to clients. Accounting education, especially at universities, has an important role in forming competent professional accountants and enabling required skills that are an essential part of professional competence. Accounting education has a challenging role in this context to incorporate and transfer knowledge regarding new technologies. This paper aims to analyse the recent research to investigate the impact of blockchain technology on accounting practice. The paper also focuses on the analyses of means of the inclusion of blockchain technology into accounting education and curriculum, by conducting a literature review of relevant sources. Research findings enable further understanding of the implications of blockchain technology in the accounting context, both for accounting practice and accounting education. Results can serve accounting educators since this topic is not sufficiently explored and needs further analysis.