Management (Montevideo) (Journal)
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The Effect of Working Capital and Investment Decisions on Small Firm Financial Sustainability and Growth
Get PDFIntroduction: The industry of small and medium-sized enterprises (SMEs) has a key impact on the economy by creating jobs, encouraging innovation, and facilitating expansion. Many SMEs have issues with stability because their working capital is not utilized properly, and investment approaches are not well-structured. This research aims to analyze the effects of working capital components and investment decisions on the ability of small firms to grow and remain sustainable.Method: Data for analysis were obtained from 230 SMEs in the manufacturing, services, and retail sectors. Financial practices and characteristics of the firms were summarized using descriptive statistics. Result: Using multiple linear regression analysis, it was found that accounts receivable, inventory, and investment decisions were key factors in determining if a corporate entity can remain sustainable and achieve growth in revenue and assets. Conclusion: The results highlight that managing finances and planning investments for the short to medium term are important for the stability and results of SMEs. The research supports introducing financial literacy and strengthening the capacity to assist small business owners when making decisions
Legislative Categorization of Crimes Committed with the Help of Cryptocurrencies
Get PDFIntroduction: The legal regime of cryptocurrency in different countries of the world is heterogeneous. In some, it is not defined at all, which leads to legal conflicts, including when qualifying crimes committed with cryptocurrency use. The situation is further complicated because such crimes can occur in the territories of several states where cryptocurrency has a different legal regime. Traditional legislation and mechanisms for combating money laundering and terrorist financing are practically ineffective in the landscape of crimes involving the use of cryptocurrency.Objectives: The aim of the study is to systematise the main patterns of crimes related to the use of cryptocurrency, as well as analyse existing vectors of their legal assessment, appropriate design and application of effective methods of combating these crimes.Methods: Based on the methods of analysis and synthesis, qualitative data analysis, using content analysis as the primary research tool, it is shown that the main problem in preventing the use of cryptocurrency in predicate crimes lies in the technical difficulty of identifying a person or group of persons who carry out cryptocurrency transactions for illegal purposes. Such goals may be aimed at legalising funds, i.e., concealing their illegal origin, making payments in a hidden network, organising various fraudulent schemes, financing terrorism, and other crimes.Results: The article argues that given the technical specifics of cryptocurrency transactions and the technical capabilities of "masking" the origin of cryptocurrency funds, it is necessary to develop methods for studying trace formation and develop an algorithm for establishing and consolidating forensically significant information for this type of crime. The results indicate that the future of law enforcement in the fight against cryptocurrency-related crime will require a multifaceted approach. Agencies must adopt a proactive approach by foreseeing emerging criminal strategies. To protect the public from crimes using digital assets, law enforcement must be flexible, progressive, and technologically savvy as cryptocurrencies continue to develop. The development of provisions on cryptocurrency also determines the theoretical significance of the work as an object and means of committing crimes, a surrogate means of payment during the commission of certain crimes.Conclusions: The practical significance of the work lies in the possibility of using its results to solve problems arising in the law-making activities of state authorities and law enforcement activities, as well as in developing recommendations for improving criminal legislation in the field of cryptocurrency-related crimes
The Metamorphosis of Global Trade Routes: Immediate Challenges and Advanced Logistics Techniques
Get PDFIntroduction: In the context of dynamic global transformations, digitalisation is becoming a key factor in improving the efficiency and sustainability of global supply chains. Emerging technologies such as artificial intelligence, blockchain, and the Internet of Things (IoT) have demonstrated the potential to optimise logistics processes and mitigate operational risks.Objective: This study aimed to evaluate the measurable impact of specific digital technologies on logistics efficiency and supply chain sustainability, as well as to assess their role in supporting transparency, cost reduction, and fraud prevention.Methods: A mixed-methods approach was employed, combining qualitative analysis with comparative quantitative assessment. The study analysed case-based data on the integration of blockchain for secure documentation, AI-driven route optimisation and sales forecasting, and IoT-based monitoring systems to enhance service quality and reduce delays.Results: The findings revealed that the implementation of AI reduced delivery time by an average of 15%, while blockchain applications decreased document-processing fraud incidents by 23%. Additionally, IoT solutions contributed to a 12% improvement in inventory visibility and reduced losses.Conclusions: Modern digital tools have practical applicability in reshaping supply chain operations, improving resilience and responsiveness. Future research should focus on the development of adaptive risk management frameworks tailored to the cybersecurity and cost-related challenges of digital transformation
The Power Of ESG: Logistic Analysis Of Sustainability-Driven Investment Decisions In Emerging Markets
Get PDFIntroduction: Sustainability is increasingly becoming a major concern in global investment, especially in the energy sector, which faces intense pressure from stakeholders to improve transparency and accountability. Environmental, Social, and Governance (ESG) has emerged as a strategic indicator that goes beyond traditional financial performance in assessing a company\u27s long-term risk and attractiveness.
Objective: This study aims to analyse the effect of ESG performance on sustainable investment decisions in Indonesian energy companies, considering financial variables as control factors.
Method: This study uses a quantitative approach with logistic regression analysis on 155 observations of energy companies during the period 2019–2023. The main independent variable is the ESG score, while the control variables include Return on Assets (ROA), Return on Equity (ROE), Debt to Equity Ratio (DER), and company size.
Results: The results show that ESG has a positive and significant effect on sustainable investment, as indicated by a high odds ratio value. DER was found to have a significant negative effect, while ROA, ROE, and company size had no significant effect on investment decisions.
Conclusion: These findings confirm that ESG performance is a more decisive strategic factor than traditional financial indicators in attracting long-term investment in the energy sector. This study contributes to the ESG literature in emerging markets and suggests strengthening ESG reporting and green investment policies in Indonesia
Cost-benefit analysis of indigenous music as a strategy for sustainable tourism development in Andean communities in Ecuador
Get PDFIntroduction: Indigenous music in Ecuador\u27s Andean communities represents a valuable cultural heritage with the potential to promote sustainable tourism. Its integration into tourist routes can generate economic benefits and strengthen local cultural identity.Objective: To evaluate the relationship between the cost-benefit analysis (CBA) of indigenous music and its cultural and economic impact on Andean communities in Ecuador within the context of sustainable tourism development, considering financial variables.Method: A mixed-methods study with a concurrent design was conducted. The qualitative phase consisted of ethnographic research in the parish of Sicalpa, Colta canton, with participant observation, 700 sound recordings, and 20 audiovisual recordings. The quantitative phase used a cost-benefit analysis (CBA) and contingent valuation to estimate the economic value of musical heritage and tourists\u27 willingness to pay. Indicators such as Net Present Value (NPV) and Internal Rate of Return (IRR) were calculated to assess the financial viability of musical tourism routes.Results: Indigenous music has significant economic value, with tourists willing to pay a high price for authentic experiences. The CBA projects a positive NPV of $150,000 USD over 5 years and an IRR of 18%, exceeding the social discount rate. Direct economic benefits (employment, income) and indirect benefits (strengthening of cultural identity, social cohesion) were identified.Conclusion: Indigenous music is a cost-effective strategy for sustainable tourism development in the Ecuadorian Andes, generating positive economic and social returns. The implementation of public policies that support community management and the creation of tourism products based on musical heritage is recommended
Occupational risks for the personnel of agricultural production companies in Ecuador
Get PDFIntroduction: occupational risk is one of the problems that persist in public and private institutions. Today, occupational health and safety at work have become a global concern within work activities. Occupational risk is the proximity, contiguity or imminence of a possible work-related occupational injury, which implies a correlation between the worker and the employer.Objective: to determine the main risk factors to which agricultural workers are exposed.Method: A review of the literature was carried out from databases such as SciELO, Scopus, ClinicalKey. Filters were used for the selection of articles in English and Spanish, empirical methods such as logical history and analysis and synthesis were used for the collection and understanding of the information obtained. A total of 20 bibliographic references were selected that addressed different considerations on the subject.Development: occupational hazards are dangerous situations present in the work environment that can cause incidents or accidents, resulting in physical injuries, psychological damage and trauma, the main objective is to eliminate or reduce the probability of these events through the planning and adaptation of preventive measures.Conclusions: The relevance of the study on occupational risk prevention lies in its potential to reduce occupational diseases and promote the adoption of preventive measures that mitigate accidents in the workplace and in other related area
Advertising semiotics and its impact on consumer emotions
Get PDFThis opinion article exposes the impact of advertising as a crucial economic function for society, as it allows companies to publicize their products or services by showing their characteristics and benefits. However, the objective of this document is to analyze advertising and the impact it has on customer perception, taking advantage of campaigns with innovative visual elements that allow focusing the attention of the target audience. Where semiotics, for its part, also plays a very important role in the process. Semiotics is a discipline that studies signs and the way they are interpreted.The concepts of the theorists Saussure and Peirce are exposed, where their models allow to explain the relationship between the sign, meaning and interpretant. Initially Saussure proposed the binary model of sign, which is composed of the signifier and meaning. On the other hand, Peirce, in turn, contributed new concepts and a more social approach with his theory of the triad. Both approaches are essential for understanding how visual, auditory and textual signs are used.Finally, we analyze how advertising semiotics allows brands to establish an emotional connection with consumers, encouraging purchases through the use of color and music
AI-Powered Human Resource Management for Enhancing Employee Recruitment Efficiency and Talent Retention in Organizations
Get PDFArtificial Intelligence (AI)-powered Human Resource Management (HRM) systems address inefficiencies in recruitment and employee retention. Traditional methods are slow, biased, and reactive. Integrating AI enables predictive insights, automated screening, and employee satisfaction monitoring, transforming HR practices into data-driven, strategic decision-making processes. This research aims to evaluate the impact of AI on improving recruitment efficiency and talent retention. It investigates whether AI-based tools significantly reduce hiring time, enhance job candidate fit, and predict attrition risk. Data was sourced from 1,000 anonymzed employee records, including 400 resumes, 280 satisfaction responses, and 320 attrition cases across the IT and finance sectors. Collected over a three-year period, the dataset supports recruitment analysis and employee retention prediction using AI-based models. Five variables were analyzed: recruitment time (RT), candidate-job match score (CJMS), employee satisfaction score (ESS), retention rate (RR), and AI-predicted attrition risk (APAR). These variables represent both continuous and ordinal data types, suitable for independent sample t-tests and regression analysis in SPSS 25. SPSS analysis showed significant reductions in recruitment time (p < 0.01) and improvements in job match scores. Among independent sample t-test results, the highest t-value was observed for CJMS (t = 22.15, p < 0.001). Spearman’s correlation indicated a strong positive link between satisfaction and retention. Regression analysis confirmed high predictive accuracy of AI-based attrition risk models. In regression findings, APAR had the highest R² value (R² = 0.42, p < 0.001). AI-powered HR systems significantly enhance recruitment efficiency and retention strategies. Statistical evidence confirms the effectiveness of AI in predicting attrition and improving candidate-job alignment, enabling organizations to make proactive, data-informed HR decisions and foster a more stable workforce
Enhancing Enterprise Human Resource Management Through Intelligent Strategies Using Hybrid Deep Learning Models
Get PDFIntroduction: Enterprise Human Resource Management (HRM), which tracks, evaluates, and improves employee performance, is essential to the expansion of a firm. However, conventional techniques like decision trees and linear regression frequently fall short in identifying intricate, non-linear relationships in employee data, which reduces their usefulness for making decisions in real time.Objective: The research aims to develop an intelligent, accurate, and scalable model for forecasting employee performance using a hybrid Deep Learning (DL) approach called the Intelligent Water Drops Driven Dynamic Long Short-Term Network (IntWD-DynLSTN).Methods: A real-world HR dataset that includes employee information like task completion rates, training hours, attendance, and performance ratings is used to train the algorithm. Preprocessing included encoding categorical data, using Z-score normalization, and addressing missing values by imputation. High-level characteristics were extracted from the structured HR data using Convolutional Neural Networks (CNN). These attributes were subsequently fed into a Dynamic Long Short-Term Network (DynLSTN) to identify sequential patterns in monthly employee performance. Finally, model hyperparameters were adjusted using the Intelligent Water Drops (IntWD) technique to enhance generality and accuracy.Results: Experimental results show that the proposed IntWD-DynLSTN model achieves higher prediction accuracy (0.98), precision (0.97), recall (0.97), and F1-score (0.98) compared to traditional and baseline methods.Conclusions: A scalable and dependable method for forecasting employee performance is provided by the suggested hybrid DL methodology. In dynamic organizational settings, it gives HR managers a strong tool for data-driven decision-making, facilitating quick interventions and efficient workforce management
Multidimensional CSR Communication Strategies for Enhancing Financial Outcomes and Stakeholder Trust in Organizations
Get PDFIntroduction: Corporate Social Responsibility (CSR) has become a crucial element of modern business strategies, with organizations increasingly expected to contribute to societal well-being alongside their financial goals.Objective: The objective is to investigate how various CSR communication strategies, such as transparency and stakeholder engagement, affect stakeholder trust. It also aims to understand their contribution to financial performance, using data analysis to identify significant relationships between these factors.Methodology: Data collected through interviews with 30 CSR managers and executives, analyzing CSR reports from 15 organizations, and surveying 129 stakeholders (employees, consumers, and investors) on their perceptions of CSR communication and trust using a Likert scale (1-5). Independent variables include transparency in CSR communication, engagement with stakeholders, frequency of communication, CSR messaging strategy, and CSR focus areas. IBM SPSS 26 was used for data analysis. Multiple regression and ANOVA revealed significant positive relationships between CSR communication strategies (transparency, engagement, frequency) and stakeholder trust.Results: Descriptive statistics indicated higher trust in organizations with more frequent, transparent CSR communication and greater engagement with stakeholders.Conclusion: The investigation concludes that transparent, frequent, and engaging CSR communication strategies are essential in building stakeholder trust. Companies that focus on strategic, honest, and consistent communication across relevant CSR areas experience stronger stakeholder relationships and improved financial outcomes.