Pub Date : 2023-06-30DOI: 10.17323/2587-814x.2023.2.7.19
A. Akopov
This article presents a new approach to modeling and optimizing individual decision-making strategies in multi-agent socio-economic systems (MSES). This approach is based on the synthesis of agent-based modeling methods, machine learning and genetic optimization algorithms. A procedure for the synthesis and training of artificial neural networks (ANNs) that simulate the functionality of MSES and provide an approximation of the values of its objective characteristics has been developed. The feature of the two-step procedure is the combined use of particle swarm optimization methods (to determine the optimal values of hyperparameters) and the Adam machine learning algorithm (to compute weight coefficients of the ANN). The use of such ANN-based surrogate models in parallel multi-agent real-coded genetic algorithms (MA-RCGA) makes it possible to raise substantially the time-efficiency of the evolutionary search for optimal solutions. We have conducted numerical experiments that confirm a significant improvement in the performance of MA-RCGA, which periodically uses the ANN-based surrogate-model to approximate the values of the objective and fitness functions. A software framework has been designed that consists of the original (reference) agent-based model of trade interactions, the ANN-based surrogate model and the MA-RCGA genetic algorithm. At the same time, the software libraries FLAME GPU, OpenNN (Open Neural Networks Library), etc., agent-based modeling and machine learning methods are used. The system we developed can be used by responsible managers.
{"title":"Modeling and optimization of strategies for making individual decisions in multi-agent socio-economic systems with the use of machine learning","authors":"A. Akopov","doi":"10.17323/2587-814x.2023.2.7.19","DOIUrl":"https://doi.org/10.17323/2587-814x.2023.2.7.19","url":null,"abstract":"This article presents a new approach to modeling and optimizing individual decision-making strategies in multi-agent socio-economic systems (MSES). This approach is based on the synthesis of agent-based modeling methods, machine learning and genetic optimization algorithms. A procedure for the synthesis and training of artificial neural networks (ANNs) that simulate the functionality of MSES and provide an approximation of the values of its objective characteristics has been developed. The feature of the two-step procedure is the combined use of particle swarm optimization methods (to determine the optimal values of hyperparameters) and the Adam machine learning algorithm (to compute weight coefficients of the ANN). The use of such ANN-based surrogate models in parallel multi-agent real-coded genetic algorithms (MA-RCGA) makes it possible to raise substantially the time-efficiency of the evolutionary search for optimal solutions. We have conducted numerical experiments that confirm a significant improvement in the performance of MA-RCGA, which periodically uses the ANN-based surrogate-model to approximate the values of the objective and fitness functions. A software framework has been designed that consists of the original (reference) agent-based model of trade interactions, the ANN-based surrogate model and the MA-RCGA genetic algorithm. At the same time, the software libraries FLAME GPU, OpenNN (Open Neural Networks Library), etc., agent-based modeling and machine learning methods are used. The system we developed can be used by responsible managers.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44446211","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}
Pub Date : 2023-06-30DOI: 10.17323/2587-814x.2023.2.71.84
I. Nikolaev
Online recruitment systems have accumulated a huge amount of data on the real labor market in recent years. Of particular interest to the study are the data on the real requirements of the labor market contained in the texts of online vacancies, as well as the process of extracting and structuring them for further analysis and use. The stage of compiling an up-to-date list of requirements for a position profile in the recruitment process is very time-consuming and requires a large amount of effort from an HR specialist related to monitoring changes in entire industries and professions, as well as analyzing relevance of existing requirements on the market. In this article, the author proposes a conceptual model of a recommendation system that allows one to reduce the burden on an HR specialist at the stage of forming an up-to-date list of requirements for a position profile in the recruitment process. The model is based on a combination of the following components: a graph model of labor market requirements based on the ESCO taxonomy adapted for the Russian language; and an intelligent method of forming recommendations for compiling an up-to-date list of requirements in the recruitment process based on neural network models of the language on the architecture of transformers, ESCO skills taxonomy and corpus online vacancies of the Russian labor market. The article also provides a conceptual algorithm for the work of the recommendation system and possible options for recommendations on updating the list of requirements of the position profile in the recruitment process based on an analysis of the needs of the real labor market.
{"title":"An intelligent method for generating a list of job profile requirements based on neural network language models using ESCO taxonomy and online job corpus","authors":"I. Nikolaev","doi":"10.17323/2587-814x.2023.2.71.84","DOIUrl":"https://doi.org/10.17323/2587-814x.2023.2.71.84","url":null,"abstract":"Online recruitment systems have accumulated a huge amount of data on the real labor market in recent years. Of particular interest to the study are the data on the real requirements of the labor market contained in the texts of online vacancies, as well as the process of extracting and structuring them for further analysis and use. The stage of compiling an up-to-date list of requirements for a position profile in the recruitment process is very time-consuming and requires a large amount of effort from an HR specialist related to monitoring changes in entire industries and professions, as well as analyzing relevance of existing requirements on the market. In this article, the author proposes a conceptual model of a recommendation system that allows one to reduce the burden on an HR specialist at the stage of forming an up-to-date list of requirements for a position profile in the recruitment process. The model is based on a combination of the following components: a graph model of labor market requirements based on the ESCO taxonomy adapted for the Russian language; and an intelligent method of forming recommendations for compiling an up-to-date list of requirements in the recruitment process based on neural network models of the language on the architecture of transformers, ESCO skills taxonomy and corpus online vacancies of the Russian labor market. The article also provides a conceptual algorithm for the work of the recommendation system and possible options for recommendations on updating the list of requirements of the position profile in the recruitment process based on an analysis of the needs of the real labor market.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45021941","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}
Pub Date : 2023-06-30DOI: 10.17323/2587-814x.2023.2.20.40
N. Dneprovskaya, Innessa Shevtsova
The purpose of this study is a conceptual description of the implementation of knowledge management systems (KMS) as a mechanism for universities’ strategic development. Knowledge management (KM) practice from around the world proved the positive influence of KMS on productivity of educational institutions. The theoretical provisions and concept for KMS are determined based on an analysis of international experience of KMS use in higher education (HE). Theoretical provisions consist of 1) the staff activities as an object of KM and knowledge because of these activities, 2) the specificity of HE restrains a transfer of the KM mechanism from business to HE, and 3) the uniqueness of each university determines the structure and content of KMS for strategic development. The KM process in HE is reflected in the Socialization-Externalization-Combination-Internalization (SECI) model, where each stage contains a list of staff activities and a set of digital services. The novelty of the KM process model in HE is that knowledge flows in a wave, not a spiral. In this motion, knowledge passes from uncodified to partly codified and codified form. The study demonstrates that knowledge can go the from stage of partly codified to uncodified for revision, and knowledge flow can stop at any stage. The advantage of the concept we designed is the ability to control the flow of knowledge before it takes the codified form of a document. The digital environment for KM first allows management to control faculty activities at the initial stage of uncodified knowledge through measurement of activities, and then to estimate the knowledge flow itself. The gathered indicators help to make decisions to motivate or restrain faculty. The university management gets a complete picture of faculty activities with knowledge and the intensity of knowledge flow in training courses and educational programs.
{"title":"A knowledge management system in the strategic development of universities","authors":"N. Dneprovskaya, Innessa Shevtsova","doi":"10.17323/2587-814x.2023.2.20.40","DOIUrl":"https://doi.org/10.17323/2587-814x.2023.2.20.40","url":null,"abstract":"The purpose of this study is a conceptual description of the implementation of knowledge management systems (KMS) as a mechanism for universities’ strategic development. Knowledge management (KM) practice from around the world proved the positive influence of KMS on productivity of educational institutions. The theoretical provisions and concept for KMS are determined based on an analysis of international experience of KMS use in higher education (HE). Theoretical provisions consist of 1) the staff activities as an object of KM and knowledge because of these activities, 2) the specificity of HE restrains a transfer of the KM mechanism from business to HE, and 3) the uniqueness of each university determines the structure and content of KMS for strategic development. The KM process in HE is reflected in the Socialization-Externalization-Combination-Internalization (SECI) model, where each stage contains a list of staff activities and a set of digital services. The novelty of the KM process model in HE is that knowledge flows in a wave, not a spiral. In this motion, knowledge passes from uncodified to partly codified and codified form. The study demonstrates that knowledge can go the from stage of partly codified to uncodified for revision, and knowledge flow can stop at any stage. The advantage of the concept we designed is the ability to control the flow of knowledge before it takes the codified form of a document. The digital environment for KM first allows management to control faculty activities at the initial stage of uncodified knowledge through measurement of activities, and then to estimate the knowledge flow itself. The gathered indicators help to make decisions to motivate or restrain faculty. The university management gets a complete picture of faculty activities with knowledge and the intensity of knowledge flow in training courses and educational programs.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47792155","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}
Pub Date : 2023-06-30DOI: 10.17323/2587-814x.2023.2.55.70
Ansel Shaidullin
Digital innovative products often become a significant factor in the revision of companies’ business strategies and influence consumer preferences. A key component in the process of formulating such strategies is understanding the implications underlying the attributes of digital products. This requires a good understanding of their nature and characteristics. To date, there is no solid basis for classifying various digital products according to their inherent characteristics. This paper presents a new interpretation of “digital products” based on the analysis of 2954 scientific articles from the Scopus database. It discusses the problems of differentiation of digital products from other types of products (such as “cyber-physical products,” “digitized products,” “smart products,” etc.). We also developed a new classification of digital products by the method of highlighting their key attributes. The purpose of the study is to develop an advanced classification of digital products based on their differentiation from other types of products. The classification we constructed based on the principles of differentiation will allow innovators and businessmen to create more profound and more advanced business models.
{"title":"The problem of interpretation, differentiation and classification of digital products","authors":"Ansel Shaidullin","doi":"10.17323/2587-814x.2023.2.55.70","DOIUrl":"https://doi.org/10.17323/2587-814x.2023.2.55.70","url":null,"abstract":"Digital innovative products often become a significant factor in the revision of companies’ business strategies and influence consumer preferences. A key component in the process of formulating such strategies is understanding the implications underlying the attributes of digital products. This requires a good understanding of their nature and characteristics. To date, there is no solid basis for classifying various digital products according to their inherent characteristics. This paper presents a new interpretation of “digital products” based on the analysis of 2954 scientific articles from the Scopus database. It discusses the problems of differentiation of digital products from other types of products (such as “cyber-physical products,” “digitized products,” “smart products,” etc.). We also developed a new classification of digital products by the method of highlighting their key attributes. The purpose of the study is to develop an advanced classification of digital products based on their differentiation from other types of products. The classification we constructed based on the principles of differentiation will allow innovators and businessmen to create more profound and more advanced business models.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49554522","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}
Pub Date : 2023-06-30DOI: 10.17323/2587-814x.2023.2.41.54
M. Matveev, Natalya Aleynikova, M. Titova
This article deals with the problem of improving the effectiveness of a marketplace. The stakeholders of a marketplace are buyers and sellers. The objects are the aggregate of homogeneous products. The effectiveness of the trading platform, which can be characterized by the number of transactions made, will depend on how sufficiently the sellers put up offers. The paper looks at mathematical models to support the decision-making of the seller in making such offers. Focusing not only on the buyer demand but also on the presence of competitors on the site is a distinguishing feature of the models. To describe the competition, the apparatus of game theory is offered, namely the normal form of the game with a bimatrix model with two players: the seller – customer of service and the coalition of other sellers. To match offer and demand, as well as to find the probability of a transaction, fuzzy set theory and aggregation using the Choquet integral are used.
{"title":"Decision support technology for a seller on a marketplace in a competitive environment","authors":"M. Matveev, Natalya Aleynikova, M. Titova","doi":"10.17323/2587-814x.2023.2.41.54","DOIUrl":"https://doi.org/10.17323/2587-814x.2023.2.41.54","url":null,"abstract":"This article deals with the problem of improving the effectiveness of a marketplace. The stakeholders of a marketplace are buyers and sellers. The objects are the aggregate of homogeneous products. The effectiveness of the trading platform, which can be characterized by the number of transactions made, will depend on how sufficiently the sellers put up offers. The paper looks at mathematical models to support the decision-making of the seller in making such offers. Focusing not only on the buyer demand but also on the presence of competitors on the site is a distinguishing feature of the models. To describe the competition, the apparatus of game theory is offered, namely the normal form of the game with a bimatrix model with two players: the seller – customer of service and the coalition of other sellers. To match offer and demand, as well as to find the probability of a transaction, fuzzy set theory and aggregation using the Choquet integral are used.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45045325","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}
Pub Date : 2023-06-30DOI: 10.17323/2587-814x.2023.2.85.97
Feng Wang
The contribution of the real estate industry to the global and regional economy is remarkable, yet in today’s evolving digital technology and digital economy, the digital transformation of the real estate industry is lagging behind other industries. This is, on the one hand, due to the solidified processes and systems linked to the upstream and downstream real estate industries, and, on the other hand, due to the fact that digital technology disrupts traditional ways of doing business, making the industry full of uncertainty. The digital transformation of the real estate industry is a broad and emerging concept. Various related research fields are concerned with the penetration and application of different innovative technologies to the industry. This study provides a systematic review focusing on the field of smart real estate using the bibliometric analysis approach under the guidance of PRISMA. The bibliometric analyses were performed in RStudio by utilizing 22 scientific documents indexed in Scopus and Web of Science that were published from 2012 to 2022. The findings suggest that: (i) smart real estate research is still a new but rapidly emerging field; (ii) only limited academic institutions from a few countries, such as the University of New South Wales in Australia, have shown significant contributions; (iii) the research exhibits specific collaborative network characteristics, leading to a high concentration of authors and citations; and (iv) data-driven topics such as “machine learning,” “information management,” “data analytics” and “big data” indicate a high degree of research density and centrality.
房地产行业对全球和区域经济的贡献是显著的，但在数字技术和数字经济不断发展的今天，房地产行业的数字化转型滞后于其他行业。这一方面是由于房地产上下游行业的流程和体系固化，另一方面是由于数字技术颠覆了传统的经营方式，使行业充满了不确定性。房地产行业的数字化转型是一个广泛而新兴的概念。各种相关的研究领域都关注不同的创新技术在工业中的渗透和应用。本研究在PRISMA的指导下，运用文献计量学分析方法对智能房地产领域进行了系统综述。文献计量学分析在RStudio中进行，利用在Scopus和Web of Science中检索的2012年至2022年发表的22篇科学文献。研究结果表明:(1)智能房地产研究仍然是一个新兴但迅速崛起的领域;(ii)只有少数国家的有限学术机构，如澳大利亚的新南威尔士大学，做出了重大贡献;(3)研究呈现出特定的协同网络特征，作者和被引频次高度集中;(iv)数据驱动的主题，如“机器学习”、“信息管理”、“数据分析”和“大数据”，表明研究密度和中心性很高。
{"title":"The present and future of the digital transformation of real estate: A systematic review of smart real estate","authors":"Feng Wang","doi":"10.17323/2587-814x.2023.2.85.97","DOIUrl":"https://doi.org/10.17323/2587-814x.2023.2.85.97","url":null,"abstract":"The contribution of the real estate industry to the global and regional economy is remarkable, yet in today’s evolving digital technology and digital economy, the digital transformation of the real estate industry is lagging behind other industries. This is, on the one hand, due to the solidified processes and systems linked to the upstream and downstream real estate industries, and, on the other hand, due to the fact that digital technology disrupts traditional ways of doing business, making the industry full of uncertainty. The digital transformation of the real estate industry is a broad and emerging concept. Various related research fields are concerned with the penetration and application of different innovative technologies to the industry. This study provides a systematic review focusing on the field of smart real estate using the bibliometric analysis approach under the guidance of PRISMA. The bibliometric analyses were performed in RStudio by utilizing 22 scientific documents indexed in Scopus and Web of Science that were published from 2012 to 2022. The findings suggest that: (i) smart real estate research is still a new but rapidly emerging field; (ii) only limited academic institutions from a few countries, such as the University of New South Wales in Australia, have shown significant contributions; (iii) the research exhibits specific collaborative network characteristics, leading to a high concentration of authors and citations; and (iv) data-driven topics such as “machine learning,” “information management,” “data analytics” and “big data” indicate a high degree of research density and centrality.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45736569","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}
Pub Date : 2023-03-31DOI: 10.17323/2587-814x.2023.1.37.52
R. Shcherbakov, Sofya Privorotskaya, K. Vishnevskiy
This paper investigates the impact of external shocks on the spread of digital technologies. Using the example of the COVID-19 pandemic, we identify and describe four patterns that reflect the uneven response of different digital technologies to external conditions undergoing transformation. The patterns differ in both the magnitude of the pandemic’s impact and the timing of the resulting effects. Video conferencing, business continuity and telemedicine services showed a dramatic increase in demand at the beginning of COVID-19 and a gradual decline in the later stages. A more moderate response in the early weeks of the pandemic is typical of e-commerce and online entertainment. Delayed effects are seen in digital logistics services and digital currencies, which reacted much later than other technologies. Finally, a slow decline in significance after the pandemic began has been observed for biometrics and cybersecurity technologies. Similar patterns may describe the transformation of the spread of digital technologies not only under the influence of COVID-19, but also in the face of dramatic economic and social changes of other origins.
{"title":"Diffusion of digital technologies in the face of external shocks: The case of the COVID-19 pandemic","authors":"R. Shcherbakov, Sofya Privorotskaya, K. Vishnevskiy","doi":"10.17323/2587-814x.2023.1.37.52","DOIUrl":"https://doi.org/10.17323/2587-814x.2023.1.37.52","url":null,"abstract":"This paper investigates the impact of external shocks on the spread of digital technologies. Using the example of the COVID-19 pandemic, we identify and describe four patterns that reflect the uneven response of different digital technologies to external conditions undergoing transformation. The patterns differ in both the magnitude of the pandemic’s impact and the timing of the resulting effects. Video conferencing, business continuity and telemedicine services showed a dramatic increase in demand at the beginning of COVID-19 and a gradual decline in the later stages. A more moderate response in the early weeks of the pandemic is typical of e-commerce and online entertainment. Delayed effects are seen in digital logistics services and digital currencies, which reacted much later than other technologies. Finally, a slow decline in significance after the pandemic began has been observed for biometrics and cybersecurity technologies. Similar patterns may describe the transformation of the spread of digital technologies not only under the influence of COVID-19, but also in the face of dramatic economic and social changes of other origins.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43122787","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}
Pub Date : 2023-03-31DOI: 10.17323/2587-814x.2023.1.53.65
V. Matokhin, A. Sigal
Accounting ensures the collection and systematization of documented information about the facts of the economic life of enterprises and organizations. The information collected is systematized and formalized in various forms of reporting. One of the key forms of reporting is the balance sheet. The balance sheet is based on the principle of double entry, according to which each change in the financial resources of the organization is reflected in at least two accounts related assets and liabilities. Thus, the condition of the balance of the volumes of the generalized values of assets and liabilities is realized. The control element of the balance sheet is the equality of the values of assets and liabilities. However, this control element does not allow us to identify the systemic difference (diversity) of balance sheets with equality of distributed funds. Namely, the equality condition is integral in nature and its fulfillment is not related to the specific nature of item-by-item distributions, since, at a given size of the total cost of the balance sheet, the condition can be fulfilled by various options for the distribution of financial resources by assets and liabilities. Therefore, within the framework of this article, an attempt has been made to introduce a new control element of the balance sheet, taking into account the uneven distribution of financial resources by assets and liabilities of credit and financial organizations.
{"title":"Entropy approach to the analysis of banks’ balance sheets","authors":"V. Matokhin, A. Sigal","doi":"10.17323/2587-814x.2023.1.53.65","DOIUrl":"https://doi.org/10.17323/2587-814x.2023.1.53.65","url":null,"abstract":"Accounting ensures the collection and systematization of documented information about the facts of the economic life of enterprises and organizations. The information collected is systematized and formalized in various forms of reporting. One of the key forms of reporting is the balance sheet. The balance sheet is based on the principle of double entry, according to which each change in the financial resources of the organization is reflected in at least two accounts related assets and liabilities. Thus, the condition of the balance of the volumes of the generalized values of assets and liabilities is realized. The control element of the balance sheet is the equality of the values of assets and liabilities. However, this control element does not allow us to identify the systemic difference (diversity) of balance sheets with equality of distributed funds. Namely, the equality condition is integral in nature and its fulfillment is not related to the specific nature of item-by-item distributions, since, at a given size of the total cost of the balance sheet, the condition can be fulfilled by various options for the distribution of financial resources by assets and liabilities. Therefore, within the framework of this article, an attempt has been made to introduce a new control element of the balance sheet, taking into account the uneven distribution of financial resources by assets and liabilities of credit and financial organizations.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43459767","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}
Pub Date : 2023-03-31DOI: 10.17323/2587-814x.2023.1.66.85
It is common knowledge that information and communication technologies (ICTs) have made continuous inroads in the knowledge management field; thus, this study is modeled to examine the impact of ICTs on inter-organizational knowledge sharing (IOKS) and its subsequent effect on the growth of small and medium-sized enterprises (SMEs). The study adopts a descriptive survey design, using the quantitative research approach. Using the simple random sampling technique, a web-based questionnaire was used to collect data from 187 respondents. Results showed that IOKS among SMEs is not carried out to a great extent, which means that it is not a common practice among SMEs. Findings showed that less than half of the SMEs used training programs, internship programs, research collaboration and workshops for IOKS. It further showed that IOKS enhances sales, productivity, profit, organizational assets and equity. This study provides evidence of how ICT systems/tools have been used in IOKS and their impact on the growth of SMEs.
{"title":"The impact of ICT on inter-organizational knowledge sharing for SMEs growth","authors":"","doi":"10.17323/2587-814x.2023.1.66.85","DOIUrl":"https://doi.org/10.17323/2587-814x.2023.1.66.85","url":null,"abstract":"It is common knowledge that information and communication technologies (ICTs) have made continuous inroads in the knowledge management field; thus, this study is modeled to examine the impact of ICTs on inter-organizational knowledge sharing (IOKS) and its subsequent effect on the growth of small and medium-sized enterprises (SMEs). The study adopts a descriptive survey design, using the quantitative research approach. Using the simple random sampling technique, a web-based questionnaire was used to collect data from 187 respondents. Results showed that IOKS among SMEs is not carried out to a great extent, which means that it is not a common practice among SMEs. Findings showed that less than half of the SMEs used training programs, internship programs, research collaboration and workshops for IOKS. It further showed that IOKS enhances sales, productivity, profit, organizational assets and equity. This study provides evidence of how ICT systems/tools have been used in IOKS and their impact on the growth of SMEs.","PeriodicalId":41920,"journal":{"name":"Biznes Informatika-Business Informatics","volume":null,"pages":null},"PeriodicalIF":0.6,"publicationDate":"2023-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47492788","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}
Pub Date : 2023-03-31DOI: 10.17323/2587-814x.2023.1.7.17
Yury Zelenkov, A. Suchkova
Customer retention is one of the most important tasks of a business, and it is extremely important to allocate retention resources according to the potential profitability of the customer. Most often the problem of predicting customer churn is solved based on the RFM (Recency, Frequency, Monetary) model. This paper proposes a way to extend the RFM model with estimates of the probability of changes in customer behavior. Based on an analysis of data relating to 33 918 clients of a large Russian retailer for 2019–2020, it is shown that there are recurring patterns of change in their behavior over a single year. Information about these patterns is used to calculate the necessary probability estimates. Incorporating these data into a predictive model based on logistic regression increases prediction accuracy by more than 10% on the metrics AUC and geometric mean. It is also shown that this approach has limitations related to the disruption of behavioral patterns by external shocks, such as the lockdown due to the COVID-19 pandemic in April 2020. The paper also proposes a way to identify these shocks, making it possible to forecast degradation in the predictive ability of the model.
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