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The Journal of Financial, Accounting and Economics
Published by PT. Global World Scientific
ISSN : -     EISSN : 30319064     DOI : https://doi.org/10.58857/JFAE.2024.v01.i02.p05
Core Subject : Economy, Science,
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance
The Journal of Financial, Accounting, and Economics (JFAE) is a scientific journal published by the Global World Scientific which aims to publish articles of empirical and theoretical studies in the field of Accounting, Finance, and Economics. Editors accept articles in English or Bahasa and were not delivered or published in another journal. Determination of the article that appeared determined by expert editors review results through a blind review process. JFAE focuses related on various themes, topics and aspects Financial, Accounting, and Economics, including (but not limited) to the following topics: Accounting, Behavioral Accounting, Financial Management, Behavioral Finance, Sharia Banking, Conventional Banking, Capital Market, Economics Development, and Behavioral Economics.
Arjuna Subject : Bisnis, Menejemen, dan Akutansi (semua kategori) - Bisnis, Menejemen, dan Akutansi (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "vol. 3 no. 1 (2026)" : 5 Documents clear
Liquidity Management Risks and Financial Performance of Tier-1 Savings and Credit Cooperatives (SACCOS) in Kenya Philip Leakey Okello; Peter Mwai Kinuthia
The Journal of Financial, Accounting, and Economics Vol. 3 No. 1 (2026)
Publisher : PT. Global World Scientific

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58857/JFAE.2026.v03.i01.p03

Abstract

This study empirically investigates the effect of financial structure variables—specifically, the cash to deposit ratio, deposits to total assets ratio, and loan to deposit ratio—on the financial performance of Savings and Credit Cooperative Organizations (SACCOs) in Kenya. The research utilized an explanatory design and implemented a quantitative panel data methodology including 30 SACCOs over a period of ten years. Data were examined utilizing Random-Effects Generalized Least Squares (GLS) regression, with model selection directed by the Hausman specification test. The regression analysis indicated that the three financial structure indicators had favorable and statistically significant effect on financial performance, as assessed by return on assets (ROA). Higher cash to deposit ratios improved the liquidity and solvency of SACCOs; increased deposit-to-asset ratios bolstered financial stability and resource mobilization; and effective loan-to-deposit ratios promoted credit intermediation and income generation. These findings highlight the significance of liquidity management, maximizing deposit mobilization, and fortifying lending techniques to improve SACCO sustainability. Policymakers and SACCO management are urged to closely observe these structural indicators while enacting reforms intended to enhance operational scale and modernize outdated institutions
Risk Management Strategies: Avoidance, Reduction, Sharing, and Retention - Systematic Literature Review I Kadek Julianaya
The Journal of Financial, Accounting, and Economics Vol. 3 No. 1 (2026)
Publisher : PT. Global World Scientific

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58857/JFAE.2026.v03.i01.p04

Abstract

The increasingly complex, dynamic, and uncertain organizational environment demands that organizations develop risk management strategies that are not only oriented towards reducing losses but also support resilience, sustainability, and value creation. The four main risk management strategies—avoidance, reduction, sharing/transfer, and retention—have different characteristics and consequences and can be used individually or in combination according to the risk characteristics and capacity of the organization. This study aims to map the development of research on these four strategies, identify the context and factors that influence their selection, analyze the relationships and combinations between strategies, and identify remaining research gaps. The study used the Systematic Literature Review (SLR) method with a literature search and selection process that refers to the PRISMA 2020 principles. The literature was searched through several academic databases using a combination of keywords related to risk management strategies, enterprise risk management, and the organizational risk context. Of the 256 identified publications, after going through the screening and eligibility assessment stages, 15 publications were obtained that met the criteria for qualitative analysis. The synthesis results show that avoidance is primarily relevant for extreme risks and risks beyond tolerance limits, reduction is the most widely implemented strategy through strengthening internal controls and capacity, sharing/transfer is increasingly developed through collaboration, insurance, reinsurance, and alternative risk transfer mechanisms, while retention is developing as a strategic decision to bear risks that are still within the organization's capacity. The findings also show that these strategies are not mutually exclusive, but form a portfolio of risk responses influenced by risk characteristics, organizational capacity, information quality, technology, governance, risk culture, and the external environment. The research identifies the need for an integrative conceptual model, longitudinal and mixed methods studies, broadening the cross-sector context, and developing risk effectiveness measurements that include financial, resilience, sustainability, and social dimensions. This research contributes by strengthening the perspective that modern risk management is an integrative, adaptive, and contextual system in supporting organizational sustainability.
Risk Assessment and Risk Tolerance in Strengthening the Effectiveness of Organizational Risk Management: A Systematic Literature Review Dewa Gede Raka Brahma Kumara
The Journal of Financial, Accounting, and Economics Vol. 3 No. 1 (2026)
Publisher : PT. Global World Scientific

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58857/JFAE.2026.v03.i01.p02

Abstract

This study aims to systematically examine the risk assessment process and the determination of risk tolerance levels in the context of organizational risk management. The method used is a Systematic Literature Review (SLR), which involves analyzing various scientific publications released between 2015 and 2025, obtained from databases such as Scopus, Web of Science, and Google Scholar. The findings reveal that risk assessment plays a crucial role in identifying, analyzing, and evaluating potential threats to the achievement of organizational objectives. Meanwhile, risk tolerance serves as the threshold for risk acceptance, enabling organizations to balance risks and opportunities in strategic decision-making. Factors such as organizational culture, resource capacity, and external conditions were found to influence the level of risk tolerance applied. The literature synthesis indicates that alignment between risk tolerance and risk appetite can enhance the effectiveness of risk management and strengthen an organization’s competitiveness and sustainability. This study provides a theoretical contribution to understanding the relationship between risk assessment and risk tolerance, as well as serving as a practical guide for organizations in developing adaptive and measurable risk management systems.
Integration of Risk Assessment and Risk Prioritization in Organizations: A Systematic Literature Review Ni Kadek Indah Prayanti
The Journal of Financial, Accounting, and Economics Vol. 3 No. 1 (2026)
Publisher : PT. Global World Scientific

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58857/JFAE.2026.v03.i01.p01

Abstract

Risk management is a strategic aspect that supports an organization’s sustainability amid increasing complexity, uncertainty, and the dynamics of the business environment. As various risk management approaches evolve, risk evaluation and risk prioritization have become two complementary stages in developing effective mitigation decisions. However, various studies indicate that these two processes are still often examined separately, thus failing to produce a comprehensive risk management framework. This study aims to identify research developments, the dominant methods used, research trends, the strengths and limitations of existing approaches, as well as research gaps related to the integration of risk evaluation and risk prioritization. The study employed a Systematic Literature Review (SLR) method in accordance with the PRISMA guidelines. The literature search was conducted using the Google Scholar, Scopus, and IEEE Xplore databases to identify articles published between 2015 and 2025. After undergoing the processes of identification, screening, eligibility assessment, and selection based on inclusion criteria, 25 articles were identified and analyzed in depth using a thematic analysis approach. The study’s findings indicate that the integration of risk evaluation and prioritization methods is increasingly evolving through the use of hybrid models—such as FMEA–AHP, FMEA–TOPSIS, FMEA–ANP, and the House of Risk—and is supported by the application of Artificial Intelligence, Machine Learning, Big Data Analytics, and Enterprise Risk Management. This integration has proven capable of enhancing the objectivity of assessments, the effectiveness of resource allocation, and the quality of decision-making in risk management. Nevertheless, existing research still faces several limitations, including a focus predominantly on large industrial sectors, a lack of empirical validation, limited attention to human behavioral factors, and the underutilization of dynamic models in small and medium-sized organizations. Therefore, future research needs to develop risk evaluation and prioritization models that are more adaptive, integrated, and empirically validated to address the challenges of an increasingly complex organizational environment.
Quantitative Risk Analysis: Expected Monetary Value, Monte Carlo, and Decision Tree - Systematic Literature Review Ni Nengah Wina Sugianti
The Journal of Financial, Accounting, and Economics Vol. 3 No. 1 (2026)
Publisher : PT. Global World Scientific

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58857/JFAE.2026.v03.i01.p05

Abstract

Quantitative risk analysis (QRA) is an important approach to support decision-making under conditions of uncertainty, particularly in the fields of project management, business, and finance. This study aims to systematically analyze the development of the application of three main methods in quantitative risk analysis, namely Expected Monetary Value (EMV), Monte Carlo Simulation (MCS), and Decision Tree Analysis (DTA), and to identify research trends, advantages, limitations, and opportunities for integration of these three methods. The study uses a Systematic Literature Review (SLR) approach with reference to the PRISMA guidelines. The literature search process was conducted through the Scopus, Web of Science, ScienceDirect, Google Scholar, Portal Garuda, Neliti, and Indonesia OneSearch databases for the 2020–2025 publication period. From the results of the identification process of 84 articles, 12 articles were obtained that met the inclusion criteria and passed the quality assessment for further analysis. The synthesis results show that Monte Carlo Simulation is the most dominant method because it is able to model uncertainty probabilistically, while Expected Monetary Value is effective for decision-making with measurable probabilities, and Decision Tree Analysis excels in visualizing decision alternatives and their consequences. Furthermore, recent research shows a trend toward a hybrid approach that integrates EMV, MCS, and DTA to produce a more comprehensive risk analysis. This study also identifies three main gaps: limited integration between methods, minimal application in the information technology and digital finance sectors, and low utilization of advanced simulation software in the Indonesian context. The research findings are expected to serve as a reference for academics and practitioners in selecting and developing quantitative risk analysis methods that are appropriate to the characteristics of the uncertainty faced and encourage the development of more adaptive and integrated risk analysis models in the future.

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