Modern Driver Research Articles

CPD: Navigating the glare

Kevin Gutsell considers the visual challenges faced by modern drivers and discusses some of the available lens designs and coatings

Precise Adverse Weather Characterization by Deep-Learning-Based Noise Processing in Automotive LiDAR Sensors

With current advances in automated driving, optical sensors like cameras and LiDARs are playing an increasingly important role in modern driver assistance systems. However, these sensors face challenges from adverse weather effects like fog and precipitation, which significantly degrade the sensor performance due to scattering effects in its optical path. Consequently, major efforts are being made to understand, model, and mitigate these effects. In this work, the reverse research question is investigated, demonstrating that these measurement effects can be exploited to predict occurring weather conditions by using state-of-the-art deep learning mechanisms. In order to do so, a variety of models have been developed and trained on a recorded multiseason dataset and benchmarked with respect to performance, model size, and required computational resources, showing that especially modern vision transformers achieve remarkable results in distinguishing up to 15 precipitation classes with an accuracy of 84.41% and predicting the corresponding precipitation rate with a mean absolute error of less than 0.47 mm/h, solely based on measurement noise. Therefore, this research may contribute to a cost-effective solution for characterizing precipitation with a commercial Flash LiDAR sensor, which can be implemented as a lightweight vehicle software feature to issue advanced driver warnings, adapt driving dynamics, or serve as a data quality measure for adaptive data preprocessing and fusion.

Data-Based Energy Demand Prediction for Hybrid Electrical Vehicles

To achieve a resource-efficient automotive traffic, modern driver assistance systems minimize the vehicle’s energy demand through speed optimization algorithms. Based on predictive route data, the required energy for upcoming operation points has to be determined. This paper presents a method to predict the energy demand of a hybrid electrical vehicle. Within this method, data-based approaches, such as neural networks, Gaussian processes, and look-up tables, are applied and assessed regarding their ability to predict the behavior of separate powertrain parts. The applied approaches are trained using measured data of a test vehicle. As a result, for every separate powertrain part, the best-suited data-based approach is selected to obtain an optimal energy demand prediction method. On a validation data set, this method is able to predict the transmission ratio of the gearbox causing a rmse of 0.426. The combustion engine’s torque prediction results in an rmse of 19.01 Nm and the electric motor torque prediction to 19.11 Nm. The root mean square error of the motor voltage results to 1.211 V.

The use of artificial intelligence technology in Chinese show business

: The object of the study is artificial intelligence technology in Chinese show business. The subject of the study is the following technologies of Chinese show business, at the basis of which we can find an artificial intelligence: virtual idols, digital avatars, virtual influencers. The following aspects of these technologies are considered in detail: making a profit, strengthening national identity. Special attention is focused on the fact that the development of artificial intelligence technology is part of the state policy of the People's Republic of China, which is reflected in the country's regulatory legal acts. The theoretical basis of the study is the work of the following authors: A.M. Gridnev, G. A. Ioakimidi, M. D. Pysin, K. F. Lee, H. Khan and others. The following methods are used in the article: analysis of special literature, publications of mass media, normative legal acts, synthesis, deduction. The study showed that virtual idols and influencers such as "Xiangwan Big Devil", digital copies of celebrities (B. Sa, S. Zhu, B. Gao, Ya. Long) and presenter Xiao Xi bring additional profits and attract an audience, as well as strengthen the national image and unity of China. The scientific novelty of this study lies in the detailed systematization of information and cultural analysis of the phenomenon of "virtual influencer", which is gaining popularity in the modern digital world. The results of the study provide valuable data for the development and implementation of artificial intelligence strategies in China, especially in such areas as industry, defense, social sphere and show business. These findings contribute to the formation of standards and ethical principles for artificial intelligence, which is critically important for the successful digital transformation of the country. The study highlights China's strategic goals of using AI as a driver of modernization of the national economy by 2030. The document identifies key stages of development and goals, including the development of standards and the widespread introduction of AI in various sectors. China views AI as an important tool to strengthen its position on the world stage, striving to become a leader in high technology, which will undoubtedly have a significant impact on the global economy and the development of technological innovations.

Digital Services as Tools for Implementing the ‘Public Participation 2.0’ Concept in Post-War Recovery in Ukraine

The article presents an attempt to solve the complex problem of the formation and implementation of the state policy of digitization in the post-war and post-war reconstruction of Ukraine by highlighting the practical aspects and risks of using digital services as tools for the implementation of the concept of “public participation 2.0”. It was found that an effective tool for solving the problems of post-war and post-war reconstruction of Ukraine is a target plan aimed at: compensation for the losses caused by the war; acceleration of socio-economic recovery and growth; improving the quality of life. The strategic goals of the recovery plan of Ukraine in the direction of digitalization include the following: formation of a developed digital economy / IT industry; restoration and development of digital infrastructure; citizens and businesses have access to high-quality, affordable and convenient public services, digital solutions and electronic identification; strengthening cyber security and resilience of digital infrastructure; involvement of a public initiative with the support of international technical assistance, as well as business projects using web technologies. Among the key problems and associated risks of the implementation of the concept of “Public Participation 2.0” and the implementation of technological solutions based on Web 2.0 in the processes and projects of reconstruction in the war and post-war period, the emphasis should be focused on the problems of duplicating the functionality of various institutions and information content. Authors stressed on inconsistency of interaction with the final beneficiaries, which leads to excessive regulation, untimeliness of operational decision-making and response to requests, as well as to the irrational use of resources aimed at the post-war restoration of facilities and infrastructure with using modern digital technologies. It has been proven that digital technologies, in particular, Web 2.0 technologies, should become the driver of post-war modernization of Ukraine, and a special role in this process belongs to public authorities, territorial communities and proactive public structures, as direct subjects of reconstruction processes in the war and post-war period. They are tasked with creating comprehensive recovery plans for their territories; their executive bodies create various advisory bodies, commissions and advisory councils, which adopt, or contribute to, transparent, impartial and professional decision-making on compensation for destroyed real estate objects, since reconstruction projects that are already being implemented are usually supported by budgets communities. A clear understanding is offered regarding the further capabilities of using the “Public Participation 2.0” model and Web 2.0-based solutions in projects of in the wartime and post-war recovery in Ukraine, which consists in optimizing and increasing efficiency of digital services and applying more productive communications with communities

Mapping Two Decades of AI in Construction Research: A Scientometric Analysis from the Sustainability and Construction Phases Lenses

The construction industry plays a vital role in the urbanization process and global economy, and there is a growing interest in utilizing artificial intelligence (AI) technologies to improve sustainability, productivity, and efficiency. However, there is a lack of comprehensive analysis regarding the progression of AI in the construction context, particularly from the sustainability angle. This study aims to fill this gap by conducting a scientometric analysis of AI research in construction by focusing on historical clusters, emerging trends, research clusters, and the correlation between sustainability pillars and key project stages. A Scopus search, between January 2000 and July 2023, was conducted that used 25 construction industry-related keywords, resulting in a total of 9564 publications. After evaluating practical AI applications in construction, 3710 publications were selected for further analysis using VOSviewer for visual diagrams and to further understand connections and patterns between literature. The findings revealed that: (a) Literature on AI in construction has experienced steady growth over the past two decades; (b) Machine learning, deep learning, and big data are seen as the key enabling digital technologies in the construction sector’s performance; (c) Economic and governance pillars of sustainability exhibit the highest potential for AI adoption; (d) Design and construction phases demonstrate substantial advantages for AI adoption; (e) AI technologies have become, despite adoption challenges, a strong driver of construction industry modernization, and; (f) By incorporating AI, the construction industry can advance towards a more sustainable future by consolidating its processes and practices.

The level of digitalization of Russian enterprises in the investment and construction sector

Introduction. The modern vector of development of the Russian Federation is associated with the transition to a digital model in a variety of aspects: — from the penetration of information technologies into the social sphere and private life of people to their impact on the pace of development of industries and national economies, the effectiveness of public administration, the development of international cooperation. The configuration of global spheres of human activity is undergoing significant changes under the influence of digitalization and radically new emerging human needs and the enterprise management process. Various studies and analytical reviews are of key importance in determining the level of digitalization of the regions of the Russian Federation, allowing to assess the dynamics of the incremental level of digitalization in the business process of enterprises. The results of a study devoted to the analysis of the level of digitalization of Russian enterprises and organizations in the investment and construction sector are presented (ICS). Construction is one of the key sectors of the economy. Thus, its share in the gross domestic product (GDP) is estimated at 5–6 % (according to Rosstat, 5.6 % in 2019), and the share of employed in it is about 9 %. The scale and importance of the construction sector suggest that improving the efficiency of enterprises, including through the introduction of digital technologies as the main modern driver of productivity and efficiency processes, can have an impact on the development of the domestic economy as a whole.
 
 Materials and methods. The basis of the study is a selective correspondence direct survey in the format of an online questionnaire. The following methods were used: the system approach, general theoretical methods of cognition (analysis, synthesis, analogy, generalization, comparison, comparison and others), graphical modelling.
 
 Results. The results of respondents’ assessment of the level of digitalization of Russian enterprises in the investment and construction sector are presented, confirming the activation of the industry in the digital environment. The success factors of these processes are identified, which include: the availability of digital infrastructure and qualified personnel, which in turn is determined by the financial capabilities of enterprises, the presence of digital culture, as well as the ability to develop and retain personnel.
 
 Conclusions. The analysis proves that there are all prerequisites for the effective development of digital relations within enterprises and the industry as a whole. The transition to “digital” will ultimately increase the economic efficiency and manageability of all internal and external organizational and production processes of enterprises and increase the share of the industry’s GDP.

The development of Kondratieff’s theory of long waves: the place of the AI economy humanization in the ‘competencies-innovations-markets’ model

The motivation to conduct this study is related to the uncertainty of the impact of the AI economy on the economic cycle and the need to unlock the potential of Industry 4.0 in stabilizing the global economic system amid a series of crises. The article discusses the fundamental issues of the emergence of a new theory related to the evolution of Kondratieff waves in the context of modern drivers of long-term economic development (MANBRIC technologies), taking into account the acceleration of the development of innovations and competencies. The spiraling dynamics of the co-development of competencies and the expansion of new markets are shown, which makes it possible to transform the decline phase of the Kondratieff wave into a similar linear process of maintaining economic growth rates close to the existing ones. As a result, based on the authors’ model “competencies-innovations-markets”, it is proved that subject to humanization, the AI economy allows the reduction of the cyclical nature of the world economic system. The main idea of the article is to smooth out Kondratieff’s long waves due to the humanization of the AI economy.

STATE FINANCIAL INCLUSION AS A DRIVER OF MODERNIZATION OF THE PENSION SYSTEM OF UKRAINE

The article considers the policy of state financial inclusion as a driver of modernization of the pension system of Ukraine. A systematic approach to the regulation of state financial inclusion policy and its indicators has been developed, which provides the optimal model for financing pension benefits and social needs of the working age population, taking into account the modernized hierarchy of the pension system and its efficiency in allocating budget resources. It is substantiated that financial inclusion in the system analysis of the state pension system is a platform of the general theory of systems, includes a number of interconnected components of the open financial system from the standpoint of allocation of budgetary resources to social needs. It is proved that the systemic approaches to the use of the methodological paradigm of financial inclusion in the pension system focuses on various aspects of the budget financing process and reflects the conceptual platform for the development of pensions. Models of pension systems and methods of the World Bank according to the levels of pension provision are presented. The directions of financial inclusion in the state pension system in the context of “state – business – society” and the scheme of optimization of state financing of social programs of the pension system are given. The size of pensioners by types and size of pensions in the regions of Ukraine, the coefficient of replacement of lost income in Europe is analyzed. The ratio of the own revenues of the Pension Fund of Ukraine is determined, taking into account the part of the paid single contribution to the obligatory state social insurance, divided into the obligatory state pension insurance to GDP. The total current pension expenditures from GDP in European countries are estimated. The scheme of actuarial calculations of pension provision in the state financial inclusion of the pension system for short-, medium- and long-term periods is proposed.

СУЧАСНІ ІМПЕРАТИВИ ГЛОБАЛІЗАЦІЇ РИНКУ ПРАЦІ: ФОРМИ І СТРУКТУРА

The development of the world labor market at the current stage of world economic progress is characterized by the systemic influence on its structural dynamics of a number of global imperatives, which manifests itself at the levels of demographic, transnational, scientific and technical, regional integration, and institutional and regulatory factors. Their synergistic effect leads to the transformation of the world labor market into an open competitive system of a global type, the quantitative and qualitative parameters of which are determined, on the one hand, by the complex action of the mechanisms of the objective economic laws of value, the capitalist population, demand and supply of labor, concentration of production, competition; and from the second – the specifics of the expanded reproduction of labor resources within the framework of national economies and at the international level. The purpose of the article is to characterize the structure-forming imperatives of globalization of the labor market. The modern economic nature of the structure-forming imperatives of the globalization of the labor market actualizes an important methodological issue regarding the comprehensive renewal of the theoretical foundations of its research at the level of the operation of economic laws and the influence of emergent factors. global economic transformations and the deep organic connection of the labor market with structural changes in the international economic system and all forms of international economic relations. The development of the global format of the functioning of the labor market is the result of the convergence of cultural traditions, moral values of different peoples and nations, their psychological and socio-cultural characteristics, attitudes to work and learning, the degree of self-education, discipline and responsibility, which, "integrating" into global institutions, acquire qualitatively new features. So, we can conclude that together they ensure the effective functioning of operational and functional business models of international companies and firms and are a powerful driver of modernization of the institutional, organizational, economic and technological basis of the world economy on the platform of global business networks.

Драйвери розвитку економіки Німеччини в контексті мегатренду диджиталізації

Digitalization is one of the key modern drivers of influence on the development of the economies of both individual countries and the world economy as a whole. Accordingly, the megatrend of digitalization determines both opportunities and challenges for national economies with the most significant focus on the largest economies of the countries to which the German economy belongs. The aim of the article is to analyze the features of the complex of actions of the part of the Federal Republic of Germany to support digitalization in the traditional sectors of the economy. The article discusses the features of transformation under the influence of digitalization in the traditional sectors of the German economy, which leads to significant changes in the driving forces of the economic model of the Federal Republic. It is noted that the German economy faces a number of short-term challenges, including the long-term consequences of the COVID-19 pandemic and the Russian-Ukrainian war. In particular, under the influence of exogenous factors, the inflation rate in Germany increased to 7.9% in 2022 from 3.1% in 2021. These crisis challenges have put a certain strain on various sectors of the German economy, creating new challenges for economic development. It is noted that the Federal Government of Germany applies an integrated approach aimed at stimulating both economic development at the short-term stage and long-term growth, based on investments in renewable energy and digitalization. It is emphasized that this balanced approach within the framework of the public policy has contributed to reducing Germany’s dependence on existing exogenous challenges, also to the active emergence of Germany as a leader in the world economic transformation. The key directions of the public policy of digital transformation of Germany are allocated. In addition, the main challenges of digital transformation for the national economy of the Federal Republic of Germany are emphasized. The proposed research can be useful for specialized scientists and analysts, research centers, authorities of both the State and the local levels, and international organizations. The prospects of this study are seen in the analysis of cases of leading national economies on digital transformation and their adaptation in Germany.

Implementation of Bootstrap Technique in Detection of Road Sign Using Artificial Intelligence

Abstract: In today's world, automated tasks have made nearly everything we perform simpler. In an endeavour to concentrate on the road, drivers frequently overlook signs on the side of a road, which might be dangerous for them and nearby motorists. If there was an rapid means to inform the driver before causing them to change their focus, this problem may be avoided. If TSDR (Traffic Sign Detection and Recognition) identifies and understands signs in this circumstance, it may warn the driver of any impending signs. This not only ensures traffic safety, but also gives the driver peace of mind when traveling through uncharted or challenging roads. Not being able to interpret the sign's meaning is another significant problem. (Traffic Sign Recognition), which is a crucial element of modern driver assistance systems that contributes to driver safety, autonomous vehicle safety, and increased driving comfort. In comparison to previous decades, road conditions have vastly improved in today's globe. The vehicle's speed obviously increased. As a result, there may be opportunities for drivers to disregard necessary traffic signs while driving. This study investigates a systemIt helps drivers see traffic signs and prevent tragedies. TSR is a difficult process, and its accuracy is dependent on two factors: the feature extractor and the classifier.. To do both feature extraction and classification, most current popular algorithms use CNN (Convolutional Neural Network). In this work, we use CNN to the recognition of traffic signs. 43 unique traffic datasets will be used to build the CNN. Sign classes, as well as the TensorFlow library. The findings will indicate a 95% accuracy rate

Is My Driver Observation Model Overconfident? Input-Guided Calibration Networks for Reliable and Interpretable Confidence Estimates

Driver observation models are rarely deployed under perfect conditions. In practice, illumination, camera placement and type differ from the ones present during training and unforeseen behaviours may occur at any time. While observing the human behind the steering wheel leads to more intuitive human-vehicle-interaction and safer driving, it requires recognition algorithms which do not only predict the correct driver state, but also determine their prediction quality through realistic and interpretable confidence measures. Reliable uncertainty estimates are crucial for building trust and are a serious obstacle for deploying activity recognition networks in real driving systems. In this work, we for the first time examine how well the confidence values of modern driver observation models indeed match the probability of the correct outcome and show that raw neural network-based approaches tend to significantly overestimate their prediction quality. To correct this misalignment between the confidence values and the actual uncertainty, we consider two strategies. First, we enhance two activity recognition models often used for driver observation with temperature scaling – an off-the-shelf method for confidence calibration in image classification. Then, we introduce Calibrated Action Recognition with Input Guidance (CARING) – a novel approach leveraging an additional neural network to learn scaling the confidences depending on the video representation. Extensive experiments on the Drive&Act dataset demonstrate that both strategies drastically improve the quality of model confidences, while our CARING model outperforms both, the original architectures and their temperature scaling enhancement, leading to best uncertainty estimates.

Objective assessment of vehicle controllability in straight-line motion

Introduction (statement of the problem and relevance). The problem of vehicle handling and stability during rectilinear motion was raised in the first half of the 20th century, and today this issue is still relevant. The requirements for handling, including during rectilinear movement of modern cars, are getting tougher. Straight-line stability and long-distance directional stability affect driver's fatigue, his driving safety and pleasure, as well as car fuel efficiency. Besides it, to provide modern driver assistance system, the car should possess good straight-line stability. At the same time, the design mustn't be affected by unbalanced forces and torques that could cause the trajectory deviation of the vehicle. There comes a need for an objective controllability and stability assessment of the car in a straight line.The purpose of the research was to analyze the existing methods for studying rectilinear motion controllability, to develop objective parameters for evaluating such motion, and to apply the worked out solutions when analyzing vehicle tests results.Methodology and research methods. Mathematical analysis, comparison, experiments, measurements were applied as research methods.Scientific novelty and results. The results have been presented in the form of a developed straight motion evaluation parameters list and were processed by calculating objective evaluation parameters. The scientific novelty is presented by the parameters of the driver's work objective assessment, and the first step has been made to correlate the objective and subjective assessment of the test driver.Practical significance. The developed method of the objective assessment can be applicable to all vehicles with traditional steering control.

Understanding modern drivers of the employee experience in healthcare

Employee engagement has been considered the guiding metric to convey the health, loyalty, and performance of the healthcare workforce. However, the pandemic created new challenges and stimulated deeper conversations around remote work, systemic racism, inclusivity, trust, well-being, and mental illness, which calls into question whether engagement alone is enough. Using an employee experience model deployed in other industries, we identified key drivers of six employee experience (EX) outcomes. We conducted a panel study with close to 5,000 nurses and physicians to identify and prioritize current key drivers specific to the healthcare employee experience. Relative weights analyses suggest that being treated with respect, strategic alignment, work-life balance, and growth and development are key themes in driving employee experience. Subsequent analysis revealed key differences across physician and nurse experiences, especially in relation to wellbeing, burnout, and intent to stay, where nurses scored significantly lower than physicians across these outcomes. Experience Framework This article is associated with the Staff & Provider Engagement lens of The Beryl Institute Experience Framework (https://www.theberylinstitute.org/ExperienceFramework). Access other PXJ articles related to this lens. Access other resources related to this lens.

Evolutionary trends in improving radio interfaces on GERAN/UTRAN/E-UTRAN networks

Mobile communications are the modern drivers of the rapid development of information communication technologies. This development is provided by the expansion of the range of user services and an increase in the volume of transmitted traffic. Mobile radio-access technologies, services, standards with different types of radio interfaces are used worldwide nowadays. The article discusses the important features of the functioning of such interfaces, presents data on functional characteristics. This research also shows the main directions of development of radio interfaces intended for use in mobile communication systems.

Transforming fire governance in British Columbia, Canada: an emerging vision for coexisting with fire

The dominant command and control fire governance paradigm is proven ineffective at coping with modern wildfire challenges. In response, jurisdictions globally are calling for transformative change that will facilitate coexisting with future fires. Enacting transformative change requires attention to historical governance attributes that may enable or constrain transformation, including diverse actors, objectives, worldviews of fire, decision-making processes and power, legislation, and drivers of change. To identify potential pathways for transformative change, we systematically examined the history of fire governance attributes in British Columbia (BC), Canada (until 2020), a region that has experienced seven catastrophic fire seasons in the twenty-first century. By reviewing 157 provincial historical documents and interviewing 19 fire experts, we delineated five distinct governance eras that demonstrated the central role of government actors with decision-making power shaping fire governance through time, superseding First Nations fire governance starting in the 1870s. The emerging vision for transformation proposed by interviewees focuses on the need for increased decision-making power for community actors, yet legacies of entrenched government power and organizational silos between fire and forestry continue to constrain transformation. Although progress to overcome constraints has been made, we argue that enabling transformative change in fire governance in BC will require intervention by the provincial government to leverage modern drivers of change, including recent catastrophic fire seasons and reconciliation with First Nations.

Do we go or we stay? : Drivers of Migration from the Global South to the Global North

Migration from south to north nowadays is becoming unprecedented and alarming. Earlier scholars classified drivers of migration into push and pull factors. Modern trends of migration cannot be limited to push and pull factors. Regards, the Foresight conceptual framework on migration is adopted to explain determinants of modern migration. The study aims to identify trends and patterns of earlier and modern drivers of migration and to reveal contributions of migrants to origin countries. The paper adopts sampling methods of desktop research, relevant journals and magazines on migration gathered for the write-up. Findings revealed that in the olden days, migrations were mainly driven by push and pull factors; however, modern days drivers comprise macro (push and push) factors such as; unemployment, non-economic, and environment. Meso drivers are distances, social networks, technologies and Diasporas links. Micro reasons are age, sex, attitude, education and marital status. These factors are considered before whether to migrate or not. The paper argues that migration can result in brain drain, and can also lead to brain gain. The skilled workers lost from developing to developed countries return home, establish businesses, and train non-migrants. Remittances flow to origin countries are used for development. However, some scholars view remittances as causes of inflation, termed it ‘Dutch disease’. The paper concludes that in earlier days, when meso and micro factors were not there as drivers of migration, they now play significant roles in migration. Therefore, it is recommended that good governance and democratic principles be revamped and rejuvenated in the global south to ensure economic growth and development which will ameliorate migration to the Western world for seeking greener pastures.

МОДЕРНІЗАЦІЯ СИСТЕМИ ІНФОРМАЦІЙНО-АНАЛІТИЧНОГО СЕРВІСУ БІЗНЕС-АДМІНІСТРУВАННЯ

Тhe article substantiates the technologies and tools of modernization of the information and analytical service system of business administration. It has been proven that the main vectors of recovery and post-war business development are related to the development of strategies capable of ensuring the effective use of available resources, strengthening economic security and competitive advantages, and minimizing possible risks. An urgent issue in the formation of competitive strategies is the relevance of information, its reliability and usefulness for decision-making. Informativity of management is provided by the system of information and analytical service of business management. It is a complex of IT services provided by the information service of the business entity, and contribute to the formation of a single information field of relevant accounting and analytical data, aimed at satisfying the information requests of users at all levels of management. Innovation and digitization are defined as the driver of modernization of the information and analytical system of business administration. Digital innovative tools for the collection, systematization, accumulation, processing and storage of financial and non-financial data about the business environment, performance results, prospects for socio-ecological and economic development, etc. have been identified, which allow providing the necessary information for management decision-making in real time. Along with subsystems of data generation and storage, the subsystem of information protection is recognized as the most important element of the information and analytical service system of business management. It is noted that the creation of such a subsystem requires a systematic approach and the implementation of a number of legal, organizational, economic and technological measures, coordinated interaction of specialists in relevant fields of knowledge for the formation of effective data protection mechanisms. The concept of technology for ensuring information security of the business administration information and analytical service system was formed. In order to ensure the digital efficiency and reliability of the information and analytical service system of business management, it is recommended to align IT goals with the strategic goals of the enterprise and to apply the latest developments in the field of corporate management, in particular practical methods of COBIT 5 in combination with BiSL. The proposed proposals provide the tools necessary to ensure trust and value, allow you to optimize the structure of the business administration information and analytical service system, ensure the effectiveness of risk management, help avoid potential confusion and maximize business opportunities.

The Analysis of Automatic Adjustment Mechanism of Balance of Payments-Evidence from Manufactured Goods Exporters

The balance of payments is the most scientific and complete record of international economic exchanges and transaction flows, and will be affected by interest rates, exchange rates, trade, finance, foreign exchange management and foreign investment. Studies related to balance of payment dominate in those increasingly open and developing economies, particularly for the manufactured goods exporters where manufacturing is the backbone, driver and display of modernization. This paper explores time trend analysis to analyze the automatic adjustment mechanism of balance of payments for manufactured goods exporters based on data from United Nations Conference on Trade and Development. The stability, cointegration, and causality tests are performed followed by multiple regression analysis that corporates one-period lagged and log-formed models. The results are found to be consistent with theoretical analysis except for foreign direct investment. Granger causality tests demonstrate consumer price index and export are the causes of foreign direct investment, which might distort the explanation of foreign direct investment to balance of payment for manufactured goods exporters.