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Research Article
Lessons Learned from the American Federation of Labor Regarding Crisis Leadership and Innovative Managerial Practices in January 1899
Jovana Pavlovic*
Issue:
Volume 13, Issue 5, October 2025
Pages:
244-249
Received:
16 July 2025
Accepted:
5 August 2025
Published:
5 September 2025
Abstract: The study delves into the tactics and crisis handling exhibited by the American Federation of Labor (abbreviated as AFL) focusing on a week in January 1899 as detailed in the AFLs historical letters stored in the Library of Congress (document mss51185, on reel 18, in volume 26). The paper brings attention to lessons, for management, and social science by studying how the AFL handles strikes and national organizing challenges along with its responses to lockouts, in a crisis scenario focusing on decision making under pressure delegation of tasks democratic leadership and intelligence gathering. The research investigates historical events which include The Textile Strike in Augusta, the Ludington Lockout Crisis and Delaware labor intelligence efforts that demonstrate enduring examples of proactive Information Gathering, Strategic Benchmarking, Efficient Communication, Pragmatic Leadership, and Collaborative hotspots - effective management for modern research. Utilizing both the documents and insights, from scholars specialized in labor history reveals how AFL President Samuel Gompers (1850-1924) along with his associates showcased leadership abilities-managing swift decision making alongside seeking input, from others and cultivating inclusive unity-despite the challenges posed by industrial unrest. Samuel Gompers played a role, within the AFL back, in January 1899. During that time frame he contributed to the development of management strategies. Showcased crisis leadership skills.
Abstract: The study delves into the tactics and crisis handling exhibited by the American Federation of Labor (abbreviated as AFL) focusing on a week in January 1899 as detailed in the AFLs historical letters stored in the Library of Congress (document mss51185, on reel 18, in volume 26). The paper brings attention to lessons, for management, and social scie...
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Review Article
The Role of Big Data Technology in Revolutionizing the Insurance Industry in Kenya
Cyprian Omenge Nyambane*
Issue:
Volume 13, Issue 5, October 2025
Pages:
250-259
Received:
30 April 2025
Accepted:
27 June 2025
Published:
8 September 2025
Abstract: Recent years have witnessed the emergence of novel ideas and concepts of big data to face the remarkable rise of amounts of data in many business sectors. Meanwhile, the remarkable growth of internet use and social networks have even added not only huge amounts of data to different business sectors but have also added challenges to conventional data processing systems. To deal with the large amount of data, traditional processing techniques have proved to be inefficient and insufficient to provide accurate and meaningful information required for evidence-based decision making. The insurance industry has also heavily relied on processed data for accurate risk assessment, underwriting and pricing. However, the sector today is also dealing with huge amounts of accumulated data, both structured and unstructured, which has made traditional data processing techniques unable to handle. Big data Analytics is an aspect of innovation which has recently gained major attention from both academics and practitioners. Big data analytics is the process of examining big data to uncover information such as hidden patterns, correlations, market trends and customer preferences. These revelations can significantly impact an organization as it provides deeper insights into customer behaviour, operational efficiency, and market trends. This paper aims to assess the role of Big Data adoption in the insurance industry through literature review. The paper presents big data and insurance industry in Kenya, characteristics of big data, the technologies used in big data implementation. It also looks at the beneficial role of adopting big data technology in the insurance sector and concludes that big data analytics stands out as an enabler to insurance organisations in making data-based decisions and providing customized insurance products and services according to customer needs. Finally, the paper encourages future research to examine the levels of big data adoption and its effect in the insurance industry.
Abstract: Recent years have witnessed the emergence of novel ideas and concepts of big data to face the remarkable rise of amounts of data in many business sectors. Meanwhile, the remarkable growth of internet use and social networks have even added not only huge amounts of data to different business sectors but have also added challenges to conventional dat...
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Research Article
Experimental XGBoost Method for Predicting the Ghana Cedi Exchange Rate Against Major Developed Currencies
Issue:
Volume 13, Issue 5, October 2025
Pages:
260-270
Received:
30 June 2025
Accepted:
11 July 2025
Published:
19 September 2025
Abstract: Exchange rate prediction is a crucial aspect of international finance, impacting decisions by governments, investors, and businesses. Accurate prediction supports the development of sound monetary policies, effective risk management, and strategic international trade planning. According to literature, traditional econometric models like ARIMAX and VAR often struggle to capture the complex, non-linear dynamics of foreign exchange markets. In contrast, machine learning methods, particularly Extreme Gradient Boosting (XGBoost), have shown superior performance due to their ability to handle large datasets, model non-linear relationships, and resist overfitting. This study evaluates the efficacy of the Extreme Gradient Boosting (XGBoost) model by predicting the GHc/USD, GHc/GBP and GHc/EUR exchange rates. Four different types of XGBoost models were employed on the financial data to determine the best performed model. The four different XGBoost models include, the XGBoost all feature, the XGBoost difference feature, the XGBoost ratio feature and the XGBoost lagged feature. The data sourced from Bank of Ghana and World Bank websites spans from January 2015 to March 2025. Findings from the study reveals that the XGBoost lagged feature and XGBoost all feature models outperformed the other two models, with an average R2of 99%, RMSE of 0.05, and MAE of 0.01. Gold price was the biggest contributor to the GHc/USD exchange rate with the feature important score of 80% followed by monthly interest rate 60%, Government debt 25%, M2 20%, price of oil 20%, BCI 15%, and CCI 10%. This result provides valuable insight for financial analyst and policymakers seeking to forecast/predict exchange rates and develop policies aimed at addressing exchange rate menace in Ghana.
Abstract: Exchange rate prediction is a crucial aspect of international finance, impacting decisions by governments, investors, and businesses. Accurate prediction supports the development of sound monetary policies, effective risk management, and strategic international trade planning. According to literature, traditional econometric models like ARIMAX and ...
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Research Article
Integrating Social Dynamics in Water Resource Management: Insights from Secondary Data
Chen Jian*,
Reagan Kapilya
Issue:
Volume 13, Issue 5, October 2025
Pages:
271-287
Received:
27 June 2025
Accepted:
1 September 2025
Published:
19 September 2025
Abstract: This article examines the crucial role of social dynamics in managing water resources, highlighting the importance of considering these factors for effective governance. Through a comprehensive analysis of secondary data drawn from diverse case studies and existing literature, we elucidate how aspects such as stakeholder engagement, cultural values, power dynamics, and social networks shape water management practices. Our findings underscore the importance of integrating these social factors to foster sustainable and equitable governance of water resources. Employing the Social-Ecological Systems Framework, this study systematically examines the interactions between social elements and water use, access, and conservation efforts across various communities. We present a range of case studies that exemplify successful stakeholder engagement and collaborative governance, highlighting the promising outcomes that can arise from incorporating social dynamics into water management strategies. These case studies illustrate how participatory approaches can lead to improved decision-making processes, ensuring that the voices of all stakeholders are heard and valued. Our research indicates that facilitating community involvement and aligning water management policies with local cultural values can significantly enhance both ecological health and social equity. By recognizing the interdependence of social and ecological systems, we propose that water management practices should evolve to reflect local contexts and foster collaboration among diverse stakeholders. This integrative approach not only addresses immediate water-related challenges but also promotes long-term resilience and adaptability in response to changing environmental conditions. This article advocates for a paradigm shift in water resource management that prioritizes social dynamics alongside technical and ecological considerations. By embracing this holistic perspective, we can develop more effective and just water governance frameworks that contribute to achieving the Sustainable Development Goals. Our insights aim to guide policymakers and practitioners in rethinking their strategies, ultimately leading to healthier ecosystems and more equitable access to water resources for all.
Abstract: This article examines the crucial role of social dynamics in managing water resources, highlighting the importance of considering these factors for effective governance. Through a comprehensive analysis of secondary data drawn from diverse case studies and existing literature, we elucidate how aspects such as stakeholder engagement, cultural values...
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Research Article
The Compulsion of 1991: How a Balance of Payments Crisis Forced India's Economic Liberalisation
Partha Majumdar*
Issue:
Volume 13, Issue 5, October 2025
Pages:
288-296
Received:
26 August 2025
Accepted:
5 September 2025
Published:
25 September 2025
Abstract: This report analyses the 1991 Indian economic liberalisation, arguing that it was a reactive response to a severe balance of payments crisis, rather than a proactive ideological shift. The analysis first details the structural weaknesses of the pre-1991 "Licence Raj" economy, highlighting its inefficiencies stemming from state control, import substitution industrialisation policies, and unsustainable debt-fuelled growth during the 1980s. The confluence of external shocks (the Gulf War and the collapse of the Soviet Union) and internal vulnerabilities precipitated a catastrophic depletion of foreign exchange reserves, pushing the nation to the brink of sovereign default. The government's desperate measures, including pledging gold reserves, underscore the lack of viable alternatives. The report emphasises the direct causal link between the stringent conditionalities imposed by the International Monetary Fund (IMF) and World Bank bailout package and the specific reforms implemented under the New Economic Policy (NEP). The NEP's key features—devaluation, trade liberalisation, industrial deregulation, foreign investment liberalisation, and public sector reform—directly correspond to the IMF/World Bank's Structural Adjustment Program. While acknowledging the existence of prior reformist ideas and the growth of the 1980s, the report concludes that the crisis was the indispensable catalyst that transformed desirable but politically impossible reforms into a necessary reality, demonstrating that India's liberalisation was fundamentally a paradigm shift by decree driven by economic necessity.
Abstract: This report analyses the 1991 Indian economic liberalisation, arguing that it was a reactive response to a severe balance of payments crisis, rather than a proactive ideological shift. The analysis first details the structural weaknesses of the pre-1991 "Licence Raj" economy, highlighting its inefficiencies stemming from state control, import subst...
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Research Article
A Study on Credit Rating Factors of Readymade Garments in Bangladesh
Anarus Sadat*
Issue:
Volume 13, Issue 5, October 2025
Pages:
297-310
Received:
22 April 2025
Accepted:
3 September 2025
Published:
26 September 2025
Abstract: This study was conducted to identify the primary financial determinants influencing the credit rating process for readymade garment (RMG) factories in Bangladesh based on seven commonly reported financial factors found in various credit rating reports. The data used in this study were collected from secondary sources, specifically from credit rating reports. These reports were gathered from 50 readymade garment (RMG) factories. This study measures the correlation between credit ratings and the seven common financial determinants through quantitative analysis using the bivariate (Pearson) correlation method. Additionally, a Boolean search technique was employed to collect related studies. In terms of data design, numerical values and positive/negative modifiers from long-term credit ratings (e.g., AAA1, AAA2, BBB1, BBB+, and BBB-) were removed for a better clarity. Data and findings are presented through graphical figures and statistics. The study reveals that rating agencies heavily rely on sales volume when assigning credit ratings to RMG factories in Bangladesh [Sales: r (48) = -.66 (long-term rating rank), p<.05; -.59 (short-term rating rank), p<.05]. Furthermore, the study shows that the majority of RMG factories have received a “ST-3” rating for the short term and a “BBB” rating for the long term. This exploratory study adds value as factory management can directly benefit from its insights, enabling them to understand the strategies needed to enhance their credit ratings. In addition, credit rating agencies will benefit from this study by adopting a more comprehensive framework for assigning credit ratings to RMG factories in Bangladesh.
Abstract: This study was conducted to identify the primary financial determinants influencing the credit rating process for readymade garment (RMG) factories in Bangladesh based on seven commonly reported financial factors found in various credit rating reports. The data used in this study were collected from secondary sources, specifically from credit ratin...
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Research Article
Effect of Tax Policy on Income Inequality in WAEMU Countries
Fatoumbi Djibril Adekola*,
Alinsato Alastaire
Issue:
Volume 13, Issue 5, October 2025
Pages:
311-322
Received:
13 May 2025
Accepted:
22 July 2025
Published:
26 September 2025
Abstract: The role of tax policy in lightening income inequalities, although relatively more analyzed in developed countries, remains one of the least debated subjects on developing countries. The goal of this paper is to analyze the relative effectiveness of different tax policy instruments in reducing inequalities in WAEMU countries. To do this, a VAR modeling in Panel is used. Our results show that direct taxes, personal income tax are more effective in reducing income inequality in WAEMU countries, whereas taxes on goods and services are less effective in reducing income inequality. Finally, the paper draws the necessary tax policy recommendations in order to improve the contribution of taxation in reducing income inequalities in WAEMU countries.
Abstract: The role of tax policy in lightening income inequalities, although relatively more analyzed in developed countries, remains one of the least debated subjects on developing countries. The goal of this paper is to analyze the relative effectiveness of different tax policy instruments in reducing inequalities in WAEMU countries. To do this, a VAR mode...
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