Елеонора Терещенко, Оксана Школенко, Марія Ковальова
et al.
The article is devoted to a comprehensive study of enterprise resilience determinants to external economic shocks through factor analysis. The modern economic environment is characterized as one of high volatility and unpredictability, creating significant challenges for stable enterprise functioning. Theoretical approaches to understanding enterprise resilience are analyzed: systemic, resource-based, dynamic-adaptive, and ecosystem approaches. An original definition of enterprise resilience is proposed as an organization's integral capacity to maintain functionality, rapidly adapt to environmental changes, and transform challenges into development opportunities through the effective combination of internal resources with external network linkages.
Factor analysis of resilience determinants identified five primary groups of factors: financial-economic, operational-technological, organizational-managerial, market-marketing, and socio-institutional. It was established that financial-economic and operational-technological determinants have the highest priority, ensuring the enterprise's basic ability to function under crisis conditions. Types of external economic shocks and mechanisms of their impact on enterprise activities are systematized. Enterprise adaptation strategies to crisis conditions are analyzed: resource conservation, diversification, innovative adaptation, partnership cooperation, and rapid transformation.
A system of scientifically based recommendations for enhancing organizational resilience has been developed, including quantitative benchmarks and implementation tools. Special attention is paid to the Ukrainian experience of enterprises operating under martial law, which creates a unique empirical basis for international resilience research.
The practical significance of the research results lies in their potential application by enterprise management to develop resilience enhancement strategies, by government bodies to formulate business support policies during crises, and by scientists for further development of organizational resilience theory. The study contributes to understanding the multidimensional nature of organizational resilience and provides a comprehensive framework for strategic decision-making under uncertainty.
Background: Staphylococcus aureus is a pathogen most of which develop into Methicillin-resistant Staphylococcus aureus. To prevent bacterial resistance, herbal medicine is needed. Mango plants have secondary metabolite compounds that can inhibit bacterial growth. Gedong gincu mango is a specific mango variety that grows widely in Cirebon district. There has been no research that knows the secondary metabolite content and its potential as an antibacterial, especially the peel part which only becomes waste.
Aims: To find out the chemical compounds contained and determine the potential of mango peel extract (Mangifera indica L.) var. gedong gincu in inhibiting the growth of Staphylococcus aureus.
Methods: This research is an experimental with a posttest only control group design. Phytochemical screening test employed a qualitative method. The extract was made using the maceration method with 70% ethanol solvent. Antibacterial testing with well diffusion method, and given four treatment concentrations (W/V), namely 25%, 50%, 75%, 100%. The measurement on the inhibitory zone after 24 hours at temperature of 370C.
Results: Gedong gincu mango peel extract contains secondary metabolite compounds flavonoids, tannins, saponins, and steroids. The inhibitory activity of gedong gincu mango peel extract with a concentration of 25% gedong gincu mango peel extract has an average inhibition zone of 11,55 mm, 50% average inhibition zone 13,55 mm, 75% average inhibition zone 14,88 mm, and 100% average inhibition zone 16,22 mm in inhibiting the growth of Staphylococcus aureus p(<0.05).
Conclusion: Mango peel extract var. gedong gincu with a concentration of 25% has the potential to inhibit the growth of Staphylococcus aureus bacteria.
Francisco Miguel Salguero-Caparrós, Eva María Sánchez-Teba, Guillermo Bermúdez-González
et al.
Without a doubt, small and medium-sized enterprises (SMEs) are one of the European economy’s great strengths as they employ over half of the total workforce. As a result, the current EU-OSHA strategy for 2022–2027 emphasizes the need to pay special attention to the specific problems of SMEs in order to improve health and safety management in these organizations. The objective of this study is to analyze the existing research gaps and from this point to trace future research lines in terms of the thematic evolution in the field of research on health and safety management specifically in SMEs through an exhaustive bibliometric analysis, in terms of both structure and concept. We used the Science Mapping Analysis Software Tool (SciMAT) program, an open-source software tool that builds scientific maps in a longitudinal framework, to identify the main topics covered within this thematic area over time. This bibliometric analysis concludes that it is essential to broaden knowledge about conceptual models for workplace risk analysis and assessment in order to boost occupational health and safety management performance with a special interest among SMEs. The emphasis is on integrating the Resilience Engineering paradigm and the emerging Safety II approach to address these challenges effectively.
In the face of global economic uncertainty, financial auditing has become essential for regulatory compliance and risk mitigation. Traditional manual auditing methods are increasingly limited by large data volumes, complex business structures, and evolving fraud tactics. This study proposes an AI-driven framework for enterprise financial audits and high-risk identification, leveraging machine learning to improve efficiency and accuracy. Using a dataset from the Big Four accounting firms (EY, PwC, Deloitte, KPMG) from 2020 to 2025, the research examines trends in risk assessment, compliance violations, and fraud detection. The dataset includes key indicators such as audit project counts, high-risk cases, fraud instances, compliance breaches, employee workload, and client satisfaction, capturing both audit behaviors and AI's impact on operations. To build a robust risk prediction model, three algorithms - Support Vector Machine (SVM), Random Forest (RF), and K-Nearest Neighbors (KNN) - are evaluated. SVM uses hyperplane optimization for complex classification, RF combines decision trees to manage high-dimensional, nonlinear data with resistance to overfitting, and KNN applies distance-based learning for flexible performance. Through hierarchical K-fold cross-validation and evaluation using F1-score, accuracy, and recall, Random Forest achieves the best performance, with an F1-score of 0.9012, excelling in identifying fraud and compliance anomalies. Feature importance analysis reveals audit frequency, past violations, employee workload, and client ratings as key predictors. The study recommends adopting Random Forest as a core model, enhancing features via engineering, and implementing real-time risk monitoring. This research contributes valuable insights into using machine learning for intelligent auditing and risk management in modern enterprises.
The ever growing Internet of Things (IoT) connections drive a new type of organization, the Intelligent Enterprise. In intelligent enterprises, machine learning based models are adopted to extract insights from data. Due to the efficiency and privacy challenges of these traditional models, a new federated learning (FL) paradigm has emerged. In FL, multiple enterprises can jointly train a model to update a final model. However, firstly, FL trained models usually perform worse than centralized models, especially when enterprises training data is non-IID (Independent and Identically Distributed). Second, due to the centrality of FL and the untrustworthiness of local enterprises, traditional FL solutions are vulnerable to poisoning and inference attacks and violate privacy. Thirdly, the continuous transfer of parameters between enterprises and servers increases communication costs. To this end, the FedAnil+ model is proposed, a novel, lightweight, and secure Federated Deep Learning Model that includes three main phases. In the first phase, the goal is to solve the data type distribution skew challenge. Addressing privacy concerns against poisoning and inference attacks is covered in the second phase. Finally, to alleviate the communication overhead, a novel compression approach is proposed that significantly reduces the size of the updates. The experiment results validate that FedAnil+ is secure against inference and poisoning attacks with better accuracy. In addition, it shows improvements over existing approaches in terms of model accuracy (13%, 16%, and 26%), communication cost (17%, 21%, and 25%), and computation cost (7%, 9%, and 11%).
Jan-Micha Bodensohn, Ulf Brackmann, Liane Vogel
et al.
Large Language Models (LLMs) promise to automate data engineering on tabular data, offering enterprises a valuable opportunity to cut the high costs of manual data handling. But the enterprise domain comes with unique challenges that existing LLM-based approaches for data engineering often overlook, such as large table sizes, more complex tasks, and the need for internal knowledge. To bridge these gaps, we identify key enterprise-specific challenges related to data, tasks, and background knowledge and extensively evaluate how they affect data engineering with LLMs. Our analysis reveals that LLMs face substantial limitations in real-world enterprise scenarios, with accuracy declining sharply. Our findings contribute to a systematic understanding of LLMs for enterprise data engineering to support their adoption in industry.
This article examines the characteristics of entrepreneurship among Scheduled Castes (SCs) in India using the 5th (2005) and 6th (2013) Economic Census data of the Central Statistical Office. The study employs the method of shift-share analysis to compare the growth of the enterprises at all India levels with that of SC-owned enterprises. The analysis reveals that the number of SC-owned enterprises has been increasing, with a significantly higher rate of change compared to the previous period. However, the prevalence of under-representation of SCs in the business field continues. The wholesale and retail trade, manufacturing and livestock are the three major activities in which SCs were concentrated. The emergence of new SC entrepreneurs has been influenced by several motivational factors, while there are also several factors that have a negative impact on the existence of SC entrepreneurs.
Dimas Wahyu Wibowo, Muhammad Shulhan Khairy, Muhammad Akhlis Rizza
et al.
Wringinsongo Village, Tumpang Subdistrict, Malang Regency maintains a clean environment through environmentally friendly waste management. One of Wringinsongo's BUMDes (Village-Owned Enterprises) is the Waste Bank, which uses waste as a potential sector. It needs to get special attention related to its governance because the recording is still less effective and there are often calculation errors caused by the recording system using paper. Based on these conditions, it is necessary to develop an application to help record transaction activities at the Waste Bank. The Wringinsongo Village Waste Bank application can be accessed on both the web platform and Android mobile devices, based on the ease of access to the system by village managers and officials. After developing the application, socialization, and training were conducted to the Waste Bank manager and village officials to provide information on how to use the application. After three months of use, feedback was taken to get responses related to the use of the application. The result is that BUMDes managers find it easy to record and obtain accurate and faster calculation results.
In a world of rapid and continuous change and constant competition, innovation is becoming an important element in the sustainable development of companies and regions. A key factor in the success of innovation processes is the accounting aspect, which involves the systematisation, analysis and documentation of innovative changes. The study of this topic is becoming increasingly relevant due to the need to identify and solve problems related to innovation accounting. It aims at combining two strategically important areas – innovative development of enterprises and modern approaches to accounting and financial management. Purpose of the article. The purpose of the publication is to identify the key aspects of the problems associated with accounting for innovation activities at enterprises, as well as to reflect the role of such accounting in ensuring their economic sustainability. Methodology. The methodological basis of the work was formed by general scientific and special research methods: comparison, analysis, generalisation, graphic and tabular. The information base is based on official statistics, company reports and accounts, Internet resources and publications, and the results of the authors' own research. Practical implications. The research examines the problems of accounting for innovation activities of enterprises and makes proposals for their solution. The Ukrainian legislation regulating accounting lacks a coherent methodology for accounting for innovation costs. In order to provide the necessary analytical information on the costs of innovation activity, it is recommended to use accounts of the eighth class, opening sub-accounts of the third, fourth and higher order. Value/originality. The sources of financing and peculiarities of accounting for innovation activities of enterprises are studied, the main of which are the state resources and resources of enterprises and other business entities. Among the non-traditional sources of financing are venture capital funds, business incubators, business angels and crowdfunding.
IntroductionSport tourism is a type of recreational trip where tourists temporarily leave their home to participate in sports activities, watch sports events or go to places that are related to sports activities. In other words, sports tourism is a phenomenon that is socially, economically, and culturally significant because of the unique interaction between an activity, people, and place. Many residents of Europe, who are deprived of this natural blessing of the world, consider desertification to be an attractive field of tourism. Domestic and foreign tourists can be attracted to Yazd province by its traditional, historical, cultural, geographical, and climatic architecture, handicrafts, and desert attractions. One of the most important features of the Yazd desert is its suitable space for activities and entertainment for different age groups, from children and babies to adventurous young people and middle-aged people. They can engage in various activities such as walking on sand dunes, watching the surfaces of salt marshes, salty rivers, seeing the clear sky and stars at night and the sunrise. The literature and research background indicate that the majority of research has concentrated on the factors or obstacles that contribute to the development of tourism in the desert, or the motivations of tourists. There is no research on sports tourism in the desert. Considering the high reception of foreign tourists from the city of Yazd and the variety of tourists who travel to Yazd from different parts of the world, solutions have been provided for the prosperity of the tourism industry in the city of Yazd as well as the country's tourism. It is important to consider the possibility of resolving tourism problems and increasing the number of foreign tourists in the regions. Nevertheless, the standard of living is slowly rising, and physical and mental health, recreation, and free time have become necessary for everyday life. It is crucial to address this issue by meeting people's diverse sports needs and improving their healthy living standards. Sports tourism as a means of maintaining physical and mental health and spending leisure time has many advantages. Promoting and developing tourism and economic prosperity can be achieved by developing sports tourism in the deserts of Yazd. Thus, the researcher decided to determine the factors that affect the acceptance of sports tourism in the desert by students at Yazd University. Material and MethodsThe current research was applied for specific purposes and used descriptive-correlational data collection methods. The statistical population of this research was the students of Yazd University, of whom 375 were selected as a sample according to Morgan's table using a simple random method. The research tool was the Alam Talab questionnaire (2014), whose validity was obtained by asking the opinions of experts in the field of sports tourism, and its reliability was obtained through Cronbach's alpha of 0.89. During descriptive analysis, SPSS version 26 software was employed, and Smart PLS version 4 software was utilized for structural equation modeling. Results and DiscussionIt was discovered that among the individual factor variables, the factor of obtaining pleasure and relaxation, which has a factor load of 1.199, is the most significant factor than physical fitness with a factor loads of 1.040. Among the variables of social factors, the mass media factor with a factor load of 0.929 is the most important item and the peer factor with a factor load of 0.724 is the least important item. The positive and significant effect of enjoyment and relaxation on the acceptance of sports tourism in the desert was confirmed, but the effect of fitness, mass media, family and peers on the acceptance of sports tourism in the desert was rejected. According to the coefficient of determination value of 0.124, the model does not fit well. According to the obtained results, it is suggested to have group tours with trained tour leaders during the competition season, preferably in autumn and winter, and with discounts or free sports insurance for emerging desert disciplines such as camel riding, sand riding, off-road, paragliding and Shooting with flying targets should be held in the deserts near and far of Yazd city. It is appropriate to provide extensive information about these events through mass media and national and local social networks. It is essential to prepare and make available to tourists complete and detailed maps of the routes, attractions, sports tourism facilities, and information in the desert camps of Yazd city. Finally, a specific trustee body in the tourism industry should be accountable for overseeing the activities of sports tourism tours.
Febry Prima Sanjaya, Vella Nur Aisyah, Tanti Handriana
Penelitian ini bertujuan untuk melakukan pemetaan tema penelitian terkait manajemen strategi dan pemasaran. Metode penelitian yang digunakan yaitu dengan analisis bibliometrik, di mana sumber data penelitian berasal dari database Scopus. Studi ini menghasilkan temuan bahwa kedua disiplin ini memiliki keterkaitan yang erat, dengan tema-tema seperti stakeholder engagement, employee participation, dan human resource management menjadi fokus utama penelitian. Tema baru yang berkembang marketing strategy. Marketing strategy adalah rencana terperinci yang merumuskan cara perusahaan untuk mencapai tujuan pemasaran dan bisnisnya dengan mengidentifikasi target pasar, pesaing, serta sumber daya yang digunakan. Penelitian ini menyarankan untuk penelitian berikutnya untuk lebih mengungkapkan wawasan yang lebih detail tentang bagaimana perusahaan mengembangkan, mengimplementasikan, dan mengevaluasi strategi pemasaran dalam berbagai situasi bisnis. Implikasi dari temuan ini adalah pentingnya mengintegrasikan aspek-aspek kedua disiplin ini dalam pengembangan strategi bisnis yang sukses.
Economics as a science, Management of special enterprises
Algorithmic trading or Financial robots have been conquering the stock markets with their ability to fathom complex statistical trading strategies. But with the recent development of deep learning technologies, these strategies are becoming impotent. The DQN and A2C models have previously outperformed eminent humans in game-playing and robotics. In our work, we propose a reinforced portfolio manager offering assistance in the allocation of weights to assets. The environment proffers the manager the freedom to go long and even short on the assets. The weight allocation advisements are restricted to the choice of portfolio assets and tested empirically to knock benchmark indices. The manager performs financial transactions in a postulated liquid market without any transaction charges. This work provides the conclusion that the proposed portfolio manager with actions centered on weight allocations can surpass the risk-adjusted returns of conventional portfolio managers.
Data is becoming more complex, and so are the approaches designed to process it. Enterprises have access to more data than ever, but many still struggle to glean the full potential of insights from what they have. This research explores the challenges and experiences of Iranian developers in implementing the MLOps paradigm within enterprise settings. MLOps, or Machine Learning Operations, is a discipline focused on automating the continuous delivery of machine learning models. In this study, we review the most popular MLOps tools used by leading technology enterprises. Additionally, we present the results of a questionnaire answered by over 110 Iranian Machine Learning experts and Software Developers, shedding light on MLOps tools and the primary obstacles faced. The findings reveal that data quality problems, a lack of resources, and difficulties in model deployment are among the primary challenges faced by practitioners. Collaboration between ML, DevOps, Ops, and Science teams is seen as a pivotal challenge in implementing MLOps effectively.
Frans Sudirjo, Bhaswarendra Guntur Hendratri, Rika Desiyanti
et al.
This study examines the effects of social capital, innovation, and market orientation on the growth of Micro and Small Enterprises (MSEs) in the Special Capital Region of Jakarta. Using a quantitative research approach, data were collected from 160 MSEs through a structured questionnaire, and the relationships between the variables were analyzed using Structural Equation Modeling-Partial Least Squares (SEM-PLS). The results reveal that all three factors—social capital, innovation, and market orientation—significantly contribute to the growth of MSEs. Innovation was identified as the most critical factor, followed by social capital and market orientation. The findings highlight the importance of fostering innovation, adopting market-oriented strategies, and leveraging social networks for the sustainable growth of MSEs. This study provides valuable insights for entrepreneurs and policymakers on how to support the development of MSEs in competitive urban environments.
The purpose of this article is to analyze the trends in the development of the financial sector, as well as the digital technologies used in this area, to identify the fundamental drivers for improving the ecosystem of the financial sector of the economy. Achieving sustainable business growth is one of the urgent tasks of management, both at the level of individual enterprises and organizations and the national economic system as a whole. This issue is of the highest relevance in the context of the high dynamism of the external environment and the growing level of uncertainty. When writing the article, the following research methods were used: trend analysis, visual graphical analysis, descriptive statistics, correlation-regression analysis, and cross-tabulation. Based on the results of the analysis, it can be concluded that the following indicators have the greatest impact on the ecosystem of the financial sector: the share of financial organizations that had special software for managing the procurement of services; the share of financial organizations that had special software for managing the sales of services. With regards to the Russian financial sector, there is a weakness in the development of the ecosystem, which is partly due to the insufficient use of complex digital solutions in managing financial flows, for example, the use of ERP systems (enterprise resource planning), CRM systems (customer relationship management), and SCM systems (supply chain management). We believe that the conclusions and results presented in this article can be used as methodological tools for developing strategies for improving the ecosystem of the financial sector in the context of the transition to a digital economy.
Penelitian ini bertujuan untuk menggambarkan strategi promosi melalui media sosial yang digunakan oleh salah satu perusahaan fashion lokal di Kota Bandung, yakni myrubylicious fashion store. Metode penelitian yang digunakan ialah deskriptif kualitatif dengan teknik pengumpulan data melalui wawancara terbuka dan dokumentasi. Hasil pengumpulan data kemudian dianalisis menggunakan tiga tahapan yakni data direduksi, data disajikan, kemudian disimpulkan. Hasil penelitian menunjukkan bahwa myrubylicious menggunakan teknik bauran promosi yang terdiri atas 5 aspek yakni advertising, personal selling, direct marketing, public relations, dan sales promotion. Kelima aspek ini digunakan oleh myrubylicious sebagai alat memaksimumkan strategi promosi perusahaan dengan tujuan akhir yakni meningkatkan laba perusahaan. Bentuk strategi promosi ini mampu membuat myrubylicious terus bertahan di tengah gempuran bisnis fashion semakin marak.
Economics as a science, Management of special enterprises
Endris Assen Ebrahim, Ahmet Toy, Yissa Hassen Kassim
IntroductionThe growth or performance of Micro and Small-Scale Enterprises (MSSEs) is widely recognized for their important contributions to economic developments in developing countries. Small and Medium-sized businesses (MMEs) in most developing nations encounter obstacles throughout and after the start-up process. This research aims to explore the determinants of the growth of MSSEs with a special emphasis on five work sectors: manufacturing, trade, construction, service, and urban agriculture in Dessie Town, Ethiopia.MethodsThe primary data was collected using a self-questionnaire from a sample of 218 managers/owners of MSE operators. Both descriptive and inferential analysis were used to analyze the collected data. Descriptive narrations were used to analyze qualitative data as a concurrent triangulation strategy. The sample respondents were selected using a stratified random sampling method based on the type of business sector. This practical study provoked nine major issues affecting the growth of MSSEs in town: political & legal factors, including bureaucratic bottlenecks system, the COVID-19 pandemic, working premises, market-related issues, road infrastructures, management system, technology-related factors, and entrepreneurial-related factors. The results show that linear and positive substantial to strong significant relationships or associations exist between some independent variables and the growth of MSSEs. Among the expected nine determinants of MSSEs' growth and performance, only political & legal-related, management-related, market-related, technology-related, infrastructure-related, entrepreneur-related factors, and COVID-19 pandemic were statistically significant. Besides, the nominated factors explained the total variations in the MSSEs' growth and performance at a 5% significance level. Realizing this conclusion, the government and non-government bodies and operators of MSSEs should give attention to management, marketing, technology infrastructure, and entrepreneur-related factors.
The purpose of this study was to analyze the effect of financial literacy and financial technology toward the financial behavior. This type of research is explanatory research using a sample of 389 undergraduate students at UIN Maulana Malik Ibrahim Malang from the 2018-2021 class. We collected data through an online questionnaire (google form) and analyzed it using SEM-PLS with the help of SmartPLS 3 software. The results indicates that financial literacy had a positive significant effect on student financial behavior and financial technology had a negative and significant effect on student financial behavior.
Economics as a science, Management of special enterprises
Enterprise relation extraction aims to detect pairs of enterprise entities and identify the business relations between them from unstructured or semi-structured text data, and it is crucial for several real-world applications such as risk analysis, rating research and supply chain security. However, previous work mainly focuses on getting attribute information about enterprises like personnel and corporate business, and pays little attention to enterprise relation extraction. To encourage further progress in the research, we introduce the CEntRE, a new dataset constructed from publicly available business news data with careful human annotation and intelligent data processing. Extensive experiments on CEntRE with six excellent models demonstrate the challenges of our proposed dataset.