The wide use of digital technologies has transformed all aspects of society and changed the modern marketing concept. Trade has been affected in particular. The development and wide use of digital technologies in the trading industry as well as the application of new implementation tools in marketing activities have led to the formation of innovation marketing. The article deals with the study of the evolution of marketing in trade. The comparison of marketing concepts and implementation mechanisms used for manufacturing and trade has revealed significant differences in these areas. The trade industry is currently experiencing an increase in innovation activity. Innovations of different origin have changed the product and affected such things as trade and technological processes, distribution of goods, and business processes of the trading enterprise. A significant number of innovations have been brought about by the development of the digital economy. However, the great advantages offered by the digital economy are offset by threats such as job cuts, lack of qualified personnel and cyber security challenges. In the case for trade, job losses occur due to the elimination of intermediaries, this achieved through the use of digital platforms and marketplaces linking suppliers and end-consumers. Besides, the growth of e-commerce and the gradual reduction of retail space in actual stores, as well as the reduction of cashiers and accountants, can also contribute to job losses. The second threat -- the lack of qualified personnel -- arises due to the changes in professional requirements at labor market. Commercial and operational personnel along with marketing specialists of commercial enterprises must satisfy high requirements established for those who apply innovative technologies in order to find solutions to problems. The third threat is posed by the growing number of cyberattacks which cause financial losses, breach of contractual obligations, loss of business reputation, and breaking up a trust of both partners and customers.
{"title":"Marketing concepts development in the digital economic environment","authors":"I. Krasyuk, T. Kirillova, S. Amakhina","doi":"10.1145/3372177.3373304","DOIUrl":"https://doi.org/10.1145/3372177.3373304","url":null,"abstract":"The wide use of digital technologies has transformed all aspects of society and changed the modern marketing concept. Trade has been affected in particular. The development and wide use of digital technologies in the trading industry as well as the application of new implementation tools in marketing activities have led to the formation of innovation marketing. The article deals with the study of the evolution of marketing in trade. The comparison of marketing concepts and implementation mechanisms used for manufacturing and trade has revealed significant differences in these areas. The trade industry is currently experiencing an increase in innovation activity. Innovations of different origin have changed the product and affected such things as trade and technological processes, distribution of goods, and business processes of the trading enterprise. A significant number of innovations have been brought about by the development of the digital economy. However, the great advantages offered by the digital economy are offset by threats such as job cuts, lack of qualified personnel and cyber security challenges. In the case for trade, job losses occur due to the elimination of intermediaries, this achieved through the use of digital platforms and marketplaces linking suppliers and end-consumers. Besides, the growth of e-commerce and the gradual reduction of retail space in actual stores, as well as the reduction of cashiers and accountants, can also contribute to job losses. The second threat -- the lack of qualified personnel -- arises due to the changes in professional requirements at labor market. Commercial and operational personnel along with marketing specialists of commercial enterprises must satisfy high requirements established for those who apply innovative technologies in order to find solutions to problems. The third threat is posed by the growing number of cyberattacks which cause financial losses, breach of contractual obligations, loss of business reputation, and breaking up a trust of both partners and customers.","PeriodicalId":368926,"journal":{"name":"Proceedings of the 2019 International SPBPU Scientific Conference on Innovations in Digital Economy","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116370647","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Information technologies are fundamentally changing modern society. Almost any human activity becomes the source of data for possible analysis and processing. The authors have analyzed more than hundred examples of data mining in modern society presented in open sources focusing on the field of education. In this study, the interdisciplinary approach is used. It makes possible to consider human activity as the basis for data analysis as the complex social phenomenon from the perspective of the sociology of communication and global Internet usage. At the same time, the authors note that the current development of technologies allows analyzing behavior of people not only in the Internet (online), but also in everyday life (offline) with the help of individual devices (cameras in smartphones and computers, fitness trackers, etc.) and with the use of facial recognition for various social situations. This study focuses on learning process and human behavior usage as the source of data in this area because information and communication technologies have changed the format of modern education. Therefore a significant part of education content has moved to the online environment. Integration of various data concerning e-learning, human movement, Biological Feedback can establish complex digital education model with prognostic and recommendatory functions that take into account behavior, individual characteristics, knowledge and skills in dynamics. This model supports a lifelong trajectory of personal development not limited by initial and final indicators and framework of educational institution. Nowadays technologies that allow tracking human behavior are causing discussions related to ethics and the issue of human freedom, though they provide deeper analysis of people's activities. Certainly these opportunities can be the benefit for society and miscellaneous social environment.
{"title":"Human behavior as the source of data in the education system","authors":"N. Almazova, D. Bylieva, V. Lobatyuk, A. Rubtsova","doi":"10.1145/3372177.3373340","DOIUrl":"https://doi.org/10.1145/3372177.3373340","url":null,"abstract":"Information technologies are fundamentally changing modern society. Almost any human activity becomes the source of data for possible analysis and processing. The authors have analyzed more than hundred examples of data mining in modern society presented in open sources focusing on the field of education. In this study, the interdisciplinary approach is used. It makes possible to consider human activity as the basis for data analysis as the complex social phenomenon from the perspective of the sociology of communication and global Internet usage. At the same time, the authors note that the current development of technologies allows analyzing behavior of people not only in the Internet (online), but also in everyday life (offline) with the help of individual devices (cameras in smartphones and computers, fitness trackers, etc.) and with the use of facial recognition for various social situations. This study focuses on learning process and human behavior usage as the source of data in this area because information and communication technologies have changed the format of modern education. Therefore a significant part of education content has moved to the online environment. Integration of various data concerning e-learning, human movement, Biological Feedback can establish complex digital education model with prognostic and recommendatory functions that take into account behavior, individual characteristics, knowledge and skills in dynamics. This model supports a lifelong trajectory of personal development not limited by initial and final indicators and framework of educational institution. Nowadays technologies that allow tracking human behavior are causing discussions related to ethics and the issue of human freedom, though they provide deeper analysis of people's activities. Certainly these opportunities can be the benefit for society and miscellaneous social environment.","PeriodicalId":368926,"journal":{"name":"Proceedings of the 2019 International SPBPU Scientific Conference on Innovations in Digital Economy","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122001112","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Industry 4.0, which is aimed at the global introduction of cyber-physical systems into industry, has determined further development pathways for cluster systems; one of the pathways is digitalization of business processes, which enables cutting costs significantly, manufacturing a high-tech innovative product, reducing time for communication between all the participants in the industrial cluster, revealing new sources for project funding, simplifying human work via relevant software and robotics adopted in the industry. All these factors become more urgent in the framework of functioning high-tech industrial clusters, which have not evolved only from the protocluster to the innovative active industrial cluster, but overtook their rivals by using these innovative available tools of the digital economy. In this paper the authors have presented a range of the most applicable methods to measure the digital potential of the industrial cluster (in regard to quantity, quality and mixed research methods); they have reviewed the literature that reveal the concept "innovative potential" of an industry enterprise and a cluster; the authors have considered 13 stages of digital potential measurement for the industrial cluster, including the following: identification of measurement parameters, classification of parameters by 6 subpotentials, expert evaluation of parameters, tabulation of the obtained expert survey results, selection of most significant parameters, final preparation of groups of factors, determination of a scale and units of measure for every selected factor to evaluate, collection of information from accessible sources, reduction of the received data to a unified measurement system, calculation of an integral index based on the developed scales, final stage includes guideline development. On the basis of the presented stages the authors worked out a relevant measurement algorithm, novelty and peculiarity of which imply allowance for indicators that characterize cluster digitalization (i.e. digital potential) when calculating a final integral value.
{"title":"Development of Algorithm to Measure Digital Potential of High-tech Industrial Cluster","authors":"A. Babkin, L. Tashenova, D. Mamrayeva, P. Azimov","doi":"10.1145/3372177.3373352","DOIUrl":"https://doi.org/10.1145/3372177.3373352","url":null,"abstract":"Industry 4.0, which is aimed at the global introduction of cyber-physical systems into industry, has determined further development pathways for cluster systems; one of the pathways is digitalization of business processes, which enables cutting costs significantly, manufacturing a high-tech innovative product, reducing time for communication between all the participants in the industrial cluster, revealing new sources for project funding, simplifying human work via relevant software and robotics adopted in the industry. All these factors become more urgent in the framework of functioning high-tech industrial clusters, which have not evolved only from the protocluster to the innovative active industrial cluster, but overtook their rivals by using these innovative available tools of the digital economy. In this paper the authors have presented a range of the most applicable methods to measure the digital potential of the industrial cluster (in regard to quantity, quality and mixed research methods); they have reviewed the literature that reveal the concept \"innovative potential\" of an industry enterprise and a cluster; the authors have considered 13 stages of digital potential measurement for the industrial cluster, including the following: identification of measurement parameters, classification of parameters by 6 subpotentials, expert evaluation of parameters, tabulation of the obtained expert survey results, selection of most significant parameters, final preparation of groups of factors, determination of a scale and units of measure for every selected factor to evaluate, collection of information from accessible sources, reduction of the received data to a unified measurement system, calculation of an integral index based on the developed scales, final stage includes guideline development. On the basis of the presented stages the authors worked out a relevant measurement algorithm, novelty and peculiarity of which imply allowance for indicators that characterize cluster digitalization (i.e. digital potential) when calculating a final integral value.","PeriodicalId":368926,"journal":{"name":"Proceedings of the 2019 International SPBPU Scientific Conference on Innovations in Digital Economy","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130255957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
N. Lomakin, A. Shokhnekh, S. Sazonov, M. Maramygin, D. Tkachenko, O. Angel
The relevance of the research study is due to the fact that the article attempts to prove or falsify the hypothesis that the "AI-Decision Tree" neural network model makes it possible to obtain a forecast of Russia's GDP for various scenarios. Various aspects of the AI application in the field of big data processing, deep learning and forecasting have been investigated in the article. However, experience has proven that, certain issues of using artificial intelligence require further scientific research in order to achieve a balanced and sustainable growth of the financial and economic system. Theoretical foundations of sustainable economic growth in the country have been studied. The authors have reviewed modern domestic and foreign literature on the topic and paid special attention to the issues of balanced financial and economic system and sustainable economic growth in modern conditions. We demonstrate the factors increasing risk and market uncertainty and other in order to achieve a balanced and sustainable growth of the financial system based on the AI-system "Decision Tree" developed. The trends in functioning of the financial and economic system have been determined; the dynamics of the balanced profit volumes in real sector organizations has been traced quarterly for the period of 2015-2018. Live data of the Federal State Statistics Service showed that the balanced financial result (profit except for loss) of organizations (apart from small business entities, banks, insurance organizations and state and municipal institutions) in current prices decreased by 8.5% in 2017. In order to visualize the dynamics of the effective factor - GDP a neural network model "AI-quantization of data" has been developed. In order to achieve a balanced and sustainable growth of the financial system based on the AI-system "Decision Tree" developed.
{"title":"Digital Ai \"Decision Tree\" for Predicting Russian GDP Value Based on Big Data Mining to Ensure Balanced and Sustainable Economic Growth","authors":"N. Lomakin, A. Shokhnekh, S. Sazonov, M. Maramygin, D. Tkachenko, O. Angel","doi":"10.1145/3372177.3373351","DOIUrl":"https://doi.org/10.1145/3372177.3373351","url":null,"abstract":"The relevance of the research study is due to the fact that the article attempts to prove or falsify the hypothesis that the \"AI-Decision Tree\" neural network model makes it possible to obtain a forecast of Russia's GDP for various scenarios. Various aspects of the AI application in the field of big data processing, deep learning and forecasting have been investigated in the article. However, experience has proven that, certain issues of using artificial intelligence require further scientific research in order to achieve a balanced and sustainable growth of the financial and economic system. Theoretical foundations of sustainable economic growth in the country have been studied. The authors have reviewed modern domestic and foreign literature on the topic and paid special attention to the issues of balanced financial and economic system and sustainable economic growth in modern conditions. We demonstrate the factors increasing risk and market uncertainty and other in order to achieve a balanced and sustainable growth of the financial system based on the AI-system \"Decision Tree\" developed. The trends in functioning of the financial and economic system have been determined; the dynamics of the balanced profit volumes in real sector organizations has been traced quarterly for the period of 2015-2018. Live data of the Federal State Statistics Service showed that the balanced financial result (profit except for loss) of organizations (apart from small business entities, banks, insurance organizations and state and municipal institutions) in current prices decreased by 8.5% in 2017. In order to visualize the dynamics of the effective factor - GDP a neural network model \"AI-quantization of data\" has been developed. In order to achieve a balanced and sustainable growth of the financial system based on the AI-system \"Decision Tree\" developed.","PeriodicalId":368926,"journal":{"name":"Proceedings of the 2019 International SPBPU Scientific Conference on Innovations in Digital Economy","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124585081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Real estate business in Russia, throughout 30 years of its modern history, shows a trend for a slower growth and transfer to new operation tools. In Russia, differently from other countries, there is still no licensing of real estate activity or multi-listings. That is why it is important to study if this sector of the economy needs to have operations and business processes digitalized. The paper is aimed at determining the demand for integrators on the example of digitalization of real estate business. The main methods used in the work are the method of observation and data collection, the abstracting method and the logical method. The paper demonstrates that integrators in the real estate sector provide services for a commission equal to 20% of users' earnings, which is comparable to the amount of remuneration integrators obtain in hospitality business and taxi. It has been found out that the share of users' earnings that integrators receive for their services is, on average, not less than two times higher of the same indicator in other spheres of economic activity, investigated by the Licensing Industry Merchandiser's Association. Using the Azgaldov-Karpova method, it has been identified that the degree of value of a real estate market integrator exceeds by 2.5 times the peak figure of the value indicator obtained based on statistical analysis of industry average data. According the conducted research study, it has been concluded that the degree of value of an integrator in the real estate sphere is appreciated as immense by market players, which is a sign of high demand for the considered technologies in real estate business. The study presents the prospects of digitalization of real estate business, which represents interest for real estate market players.
{"title":"Evaluating the Need for Integrators on the Example of Digitalization of Real Estate Business","authors":"A. Romanenko, A. Druzhinin, N. Alekseeva","doi":"10.1145/3372177.3373306","DOIUrl":"https://doi.org/10.1145/3372177.3373306","url":null,"abstract":"Real estate business in Russia, throughout 30 years of its modern history, shows a trend for a slower growth and transfer to new operation tools. In Russia, differently from other countries, there is still no licensing of real estate activity or multi-listings. That is why it is important to study if this sector of the economy needs to have operations and business processes digitalized. The paper is aimed at determining the demand for integrators on the example of digitalization of real estate business. The main methods used in the work are the method of observation and data collection, the abstracting method and the logical method. The paper demonstrates that integrators in the real estate sector provide services for a commission equal to 20% of users' earnings, which is comparable to the amount of remuneration integrators obtain in hospitality business and taxi. It has been found out that the share of users' earnings that integrators receive for their services is, on average, not less than two times higher of the same indicator in other spheres of economic activity, investigated by the Licensing Industry Merchandiser's Association. Using the Azgaldov-Karpova method, it has been identified that the degree of value of a real estate market integrator exceeds by 2.5 times the peak figure of the value indicator obtained based on statistical analysis of industry average data. According the conducted research study, it has been concluded that the degree of value of an integrator in the real estate sphere is appreciated as immense by market players, which is a sign of high demand for the considered technologies in real estate business. The study presents the prospects of digitalization of real estate business, which represents interest for real estate market players.","PeriodicalId":368926,"journal":{"name":"Proceedings of the 2019 International SPBPU Scientific Conference on Innovations in Digital Economy","volume":"462 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128370005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The main purpose of the study is to develop a simulation model that reflects aggregate impact assessment of an enterprise's external and internal environmental factors on its business value. Based on external and internal enterprise environmental factors and the rate of environmental changes, enterprise management evaluates each strategic decision to manage competitive advantages. Increased business value is seen as a quantitative indicator of an effective strategy. The paper describes theoretical and practical aspects of simulation modelling. A discrete simulation model in the form of a diagrammatic model of the operators-and-relations structure was chosen as the main simulation tool. The paper also defines external and internal environmental factors that emerge at certain stages of the industry life cycle and examines the key relations between them. The interaction between variables that represent the operation of the system and changes in the external environment was depicted graphically. As a result, a simulation model for assessing the impact of external and internal environmental factors on business value was developed. It includes variables as the key components of the system and demonstrates causal relationships between them. The model can be used to upgrade the strategic decision-making process. However, at the moment the described approach cannot be fully realized due to the lack of a decent informational base on individual enterprises and industries as a whole. The findings can be used to assess the potential impact of digitalization on strategic decision-making as well as its indirect impact on business value and development costs of digital models for enterprises.
{"title":"Simulation Model for Business Value Strategic Management in Digital Transformation Era","authors":"S. Gutman, E. Rytova, Tatyana Bogdanova","doi":"10.1145/3372177.3373091","DOIUrl":"https://doi.org/10.1145/3372177.3373091","url":null,"abstract":"The main purpose of the study is to develop a simulation model that reflects aggregate impact assessment of an enterprise's external and internal environmental factors on its business value. Based on external and internal enterprise environmental factors and the rate of environmental changes, enterprise management evaluates each strategic decision to manage competitive advantages. Increased business value is seen as a quantitative indicator of an effective strategy. The paper describes theoretical and practical aspects of simulation modelling. A discrete simulation model in the form of a diagrammatic model of the operators-and-relations structure was chosen as the main simulation tool. The paper also defines external and internal environmental factors that emerge at certain stages of the industry life cycle and examines the key relations between them. The interaction between variables that represent the operation of the system and changes in the external environment was depicted graphically. As a result, a simulation model for assessing the impact of external and internal environmental factors on business value was developed. It includes variables as the key components of the system and demonstrates causal relationships between them. The model can be used to upgrade the strategic decision-making process. However, at the moment the described approach cannot be fully realized due to the lack of a decent informational base on individual enterprises and industries as a whole. The findings can be used to assess the potential impact of digitalization on strategic decision-making as well as its indirect impact on business value and development costs of digital models for enterprises.","PeriodicalId":368926,"journal":{"name":"Proceedings of the 2019 International SPBPU Scientific Conference on Innovations in Digital Economy","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115071423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
N. Lomakin, A. Shokhnekh, S. Sazonov, Alena Polianskaia, Gennady Lukyanov, A. Gorbunova
The article represents theoretical foundations investigated for application of artificial intelligence systems in Big Data processing. The most comprehensive list of tools for data analysis and machine learning has been considered. A comparative Hadoop framework and Deductor analytical platform opportunity analysis has been performed. An AI-system has been proposed for predicting the cost of innovative products in the context of digitalization of the Russian economy. A hypothesis that a neural network makes it possible to obtain a forecast for the cost of innovative products in the Russian Federation has been put forward and proved. The neural network model included such parameters as GDP (billion rubles), key rate (%), RTS index, output of innovative products (billion rubles), costs of innovative products (billion rubles), dollar exchange rate (rubles), balanced profit (billion rubles), risk (σ), loans originated (billion rubles), VIX-Index and forecast for the volume of innovative products (billion rubles). The list of parameters presented reflects the development of both the economic sphere and Russia's financial sector quarterly for the period of from 2015 to 2018. Based on quantization and subsequent visualization of big data and using a multidimensional diagram, the artificial intelligence system developed allows revealing the GDP trend in Russia depending on the cost of innovative products and the VIX option stock-exchange quotation in the global economic landscape. The AI-system that enables prediction for the cost of innovative products using the "what-if" function in the Deductor platform has been developed.
{"title":"Hadoop and Deductor Based Digital Ai System for Predicting Cost of Innovative Products in Conditions of Digitalization of Economy","authors":"N. Lomakin, A. Shokhnekh, S. Sazonov, Alena Polianskaia, Gennady Lukyanov, A. Gorbunova","doi":"10.1145/3372177.3373810","DOIUrl":"https://doi.org/10.1145/3372177.3373810","url":null,"abstract":"The article represents theoretical foundations investigated for application of artificial intelligence systems in Big Data processing. The most comprehensive list of tools for data analysis and machine learning has been considered. A comparative Hadoop framework and Deductor analytical platform opportunity analysis has been performed. An AI-system has been proposed for predicting the cost of innovative products in the context of digitalization of the Russian economy. A hypothesis that a neural network makes it possible to obtain a forecast for the cost of innovative products in the Russian Federation has been put forward and proved. The neural network model included such parameters as GDP (billion rubles), key rate (%), RTS index, output of innovative products (billion rubles), costs of innovative products (billion rubles), dollar exchange rate (rubles), balanced profit (billion rubles), risk (σ), loans originated (billion rubles), VIX-Index and forecast for the volume of innovative products (billion rubles). The list of parameters presented reflects the development of both the economic sphere and Russia's financial sector quarterly for the period of from 2015 to 2018. Based on quantization and subsequent visualization of big data and using a multidimensional diagram, the artificial intelligence system developed allows revealing the GDP trend in Russia depending on the cost of innovative products and the VIX option stock-exchange quotation in the global economic landscape. The AI-system that enables prediction for the cost of innovative products using the \"what-if\" function in the Deductor platform has been developed.","PeriodicalId":368926,"journal":{"name":"Proceedings of the 2019 International SPBPU Scientific Conference on Innovations in Digital Economy","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125023411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nadezhda Bulatova, E. Dugina, E. Dorzhieva, Maria Siniavina
The paper is concerned with the development of a regional transport and logistics system under digitalization. The paper proposes a technology for determining strategic directions for regional transport and logistics system (RTLS) development under digitalization which comprises methodological tools for analyzing the spatial structure of freight consumption and freight generation by all the participants in a transportation service system along with an algorithm and a guidance package for arranging modes for the information interaction of its participants under the control of the single information provider, and their transformation, making it possible to ensure product and material exchanges at different levels: regional, interregional and intercountry. The concepts and stipulations of this technology are considered, drawing on the properties of a transport and logistics system as an economic system along with such principles of information provision as the comprehensiveness, divisibility, interrelatedness, orderliness, integrability, complexity, emergent nature and structuredeness of its elements. The objective of the given study is to create a technology for determining strategic directions for RTLS development under digitalization. The study intends to broaden the RTLS research domain, which makes it possible to expand theoretical knowledge of the current trends in its operation in the frame of digitalization. The general scientific methods of inquiry such as observation, analysis, generalization were used to reach the stated objective. Pursuing strategic directions for the development of a transport and logistics system within the framework of the proposed projects will allow for establishing an efficient program/project management system for area development and eliminating regional economic growth limitations related to the lack of harmonization among the participants in transportation processes.
{"title":"Technology for determining strategic directions for the development of a regional transport and logistics system under digitalization","authors":"Nadezhda Bulatova, E. Dugina, E. Dorzhieva, Maria Siniavina","doi":"10.1145/3372177.3373353","DOIUrl":"https://doi.org/10.1145/3372177.3373353","url":null,"abstract":"The paper is concerned with the development of a regional transport and logistics system under digitalization. The paper proposes a technology for determining strategic directions for regional transport and logistics system (RTLS) development under digitalization which comprises methodological tools for analyzing the spatial structure of freight consumption and freight generation by all the participants in a transportation service system along with an algorithm and a guidance package for arranging modes for the information interaction of its participants under the control of the single information provider, and their transformation, making it possible to ensure product and material exchanges at different levels: regional, interregional and intercountry. The concepts and stipulations of this technology are considered, drawing on the properties of a transport and logistics system as an economic system along with such principles of information provision as the comprehensiveness, divisibility, interrelatedness, orderliness, integrability, complexity, emergent nature and structuredeness of its elements. The objective of the given study is to create a technology for determining strategic directions for RTLS development under digitalization. The study intends to broaden the RTLS research domain, which makes it possible to expand theoretical knowledge of the current trends in its operation in the frame of digitalization. The general scientific methods of inquiry such as observation, analysis, generalization were used to reach the stated objective. Pursuing strategic directions for the development of a transport and logistics system within the framework of the proposed projects will allow for establishing an efficient program/project management system for area development and eliminating regional economic growth limitations related to the lack of harmonization among the participants in transportation processes.","PeriodicalId":368926,"journal":{"name":"Proceedings of the 2019 International SPBPU Scientific Conference on Innovations in Digital Economy","volume":"188 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125332628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Industrial development plays a significant role in increasing a country's economic growth and competitiveness. Some countries expand their industrial development using corridors or special economic zone. However, limited publication is found regarding how a nation dealing with their industrial corridor and its impact to economic growth. This research is aimed to evaluate the focus of industrial development of Indonesia by taking into account Sulawesi corridor, Bali-Nusa Tenggara corridor, and Maluku-Papua corridor located on eastern part of the country. These corridors are expected to improve economic activities in the region and increase the national competitiveness in general. Data were obtained through pairwise comparison and analyzed using a location quotient (LQ), which aims to rank overall potential industries in a particular region. While pairwise comparison was used to process the result from LQ analysis to determine the industry with the highest potential by taking into account variables related to regional development extracted from public records. The research found two alternative scenarios for the decision-making process based on development cost, government capacity, and completion time. The first scenario considered government ability to fund all required projects to support the country's economic expansion in the future. While the second scenario evaluated a limited budget from the government allocation to accelerate infrastructure development. Both scenarios are used to make opposing decisions that need to be considered in the nearest future. The result is used as an academic exercise for those interested in regional development, government officials dealing with the economic masterplan, and other stakeholders in both national and international.
{"title":"Mapping Industrial Corridors","authors":"M. Berawi, P. Miraj, Gunawan Saroji","doi":"10.1145/3372177.3373315","DOIUrl":"https://doi.org/10.1145/3372177.3373315","url":null,"abstract":"Industrial development plays a significant role in increasing a country's economic growth and competitiveness. Some countries expand their industrial development using corridors or special economic zone. However, limited publication is found regarding how a nation dealing with their industrial corridor and its impact to economic growth. This research is aimed to evaluate the focus of industrial development of Indonesia by taking into account Sulawesi corridor, Bali-Nusa Tenggara corridor, and Maluku-Papua corridor located on eastern part of the country. These corridors are expected to improve economic activities in the region and increase the national competitiveness in general. Data were obtained through pairwise comparison and analyzed using a location quotient (LQ), which aims to rank overall potential industries in a particular region. While pairwise comparison was used to process the result from LQ analysis to determine the industry with the highest potential by taking into account variables related to regional development extracted from public records. The research found two alternative scenarios for the decision-making process based on development cost, government capacity, and completion time. The first scenario considered government ability to fund all required projects to support the country's economic expansion in the future. While the second scenario evaluated a limited budget from the government allocation to accelerate infrastructure development. Both scenarios are used to make opposing decisions that need to be considered in the nearest future. The result is used as an academic exercise for those interested in regional development, government officials dealing with the economic masterplan, and other stakeholders in both national and international.","PeriodicalId":368926,"journal":{"name":"Proceedings of the 2019 International SPBPU Scientific Conference on Innovations in Digital Economy","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114948083","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The problems of development of audit activity have signified a drop of audit companies' business reputation. During the transformations of the global market economy of the last decades of the 21st century, the questions of minimizing costs amidst growing competition and the requirements for high professionalism of auditors, as well as the growing needs of investors and owners due to changing markets and legislation, become highly relevant in the future consideration of the issue. The article discusses and tests the methodology for using statistical research in audit based on audit materials where sampling is used as a main instrument. We analyze the possibilities of selective research utilization during an audit check of a huge amount of accounting data and reports, evaluation of the results of the check and their extrapolation to the entire population of data taking into account the correlation of the elements of the sample. In order to minimize the number of mistakes in the auditor's conclusion, we offer a sampling procedure that takes into account the points of highest risk and a method for risk evaluation. We have developed document templates to provide to auditors aimed to systemize the source data to select the sampling type, auditor's actions when processing accounting data and reports, the results of audit sampling and to reflect all the steps of sampling research at any stage of accounting process. Additionally, we have developed a set of indicators that make up the base for sampling research in audit. The method offered has been approbated on enterprise's data, which has confirmed that using these instruments of digital economics is possible, that it does not reduce the quality of the audit results, and its practical applicability from the point of view of minimization of labor.
{"title":"Method of Audit Sampling as an Instrument of Audit Services in Digital Economy","authors":"A. Petrova, E. Pokivailova","doi":"10.1145/3372177.3374653","DOIUrl":"https://doi.org/10.1145/3372177.3374653","url":null,"abstract":"The problems of development of audit activity have signified a drop of audit companies' business reputation. During the transformations of the global market economy of the last decades of the 21st century, the questions of minimizing costs amidst growing competition and the requirements for high professionalism of auditors, as well as the growing needs of investors and owners due to changing markets and legislation, become highly relevant in the future consideration of the issue. The article discusses and tests the methodology for using statistical research in audit based on audit materials where sampling is used as a main instrument. We analyze the possibilities of selective research utilization during an audit check of a huge amount of accounting data and reports, evaluation of the results of the check and their extrapolation to the entire population of data taking into account the correlation of the elements of the sample. In order to minimize the number of mistakes in the auditor's conclusion, we offer a sampling procedure that takes into account the points of highest risk and a method for risk evaluation. We have developed document templates to provide to auditors aimed to systemize the source data to select the sampling type, auditor's actions when processing accounting data and reports, the results of audit sampling and to reflect all the steps of sampling research at any stage of accounting process. Additionally, we have developed a set of indicators that make up the base for sampling research in audit. The method offered has been approbated on enterprise's data, which has confirmed that using these instruments of digital economics is possible, that it does not reduce the quality of the audit results, and its practical applicability from the point of view of minimization of labor.","PeriodicalId":368926,"journal":{"name":"Proceedings of the 2019 International SPBPU Scientific Conference on Innovations in Digital Economy","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122345177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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