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Quantitative Economics and Management Studies
Published by PT. Mattawang Mediatama Solution
ISSN : -     EISSN : 27226247     DOI : https://doi.org/10.35877/qems
Core Subject : Economy, Science, Education,
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Mathematics
Journal of Quantitative Economics and Management Studies (QEMS) is an international peer-reviewed open-access journal dedicated to interchange for the results of high-quality research in all aspects of economics, management, business, finance, marketing, accounting. The journal publishes state-of-art papers in fundamental theory, experiments, and simulation, as well as applications, with a systematic proposed method, sufficient review on previous works, expanded discussion, and concise conclusion. As our commitment to the advancement of science and technology, the QEMS follows the open access policy that allows the published articles freely available online without any subscription.
Arjuna Subject : Ilmu Ekonomi, Ekonometrika dan Keuangan (semua kategori) - Ilmu Ekomomi dan Ekonometrika
Articles 20 Documents
 1   2 
Search results for , issue "Vol. 5 No. 3 (2024)" : 20 Documents clear
Optimizing Organizational Performance Through a Conversation-Based Performance Management System Approach Tati Ariaini; Aryana Satrya
Quantitative Economics and Management Studies Vol. 5 No. 3 (2024)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems2622

Abstract

This study examines the need for an effective performance management system within organizations. Prior research indicates that such systems significantly enhance business outcomes (Pulakos, Mueller-Hanson & Arad, 2019). O’Kane, McCracken & Brown (2022) introduced a conversation-based performance management model grounded in social exchange theory (SET), suggesting that discussions between supervisors and subordinates foster positive reciprocal relationships. This research aims to analyze the effectiveness of the performance management system implemented by a private trading company in Indonesia. The qualitative study involved semi-structured interviews with the Board of Directors, HRD, Line Managers, and Staff, as well as focus group discussions with Senior Managers. Findings reveal gaps in the system's implementation, notably the absence of feedback processes central to this model. Identified factors contributing to these gaps include goal alignment, feedback frequency, skills development, and formality, alongside environmental factors such as design, development function, buy-in, culture, and linkage with other systems. The study underscores the importance of feedback and explores the system's effectiveness from various perspectives, offering insights that contribute to the literature on performance management systems, particularly conversation-based approaches in private companies in Indonesia.
Strategic Implementation of Big Data Automation for Wastage Management Reporting Using Analytical Hierarchy Process in The Tobacco Industry Ilham Guspuji Maulana; Yos Sunitiyoso
Quantitative Economics and Management Studies Vol. 5 No. 3 (2024)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems2623

Abstract

In today's data-driven era, big data automation is crucial, often referred to as "the new oil." Industries, particularly the fast-moving consumer goods (FMCG) sector like the tobacco industry, must undergo digital transformation to stay competitive. The integration of big data automation with reporting processes is significantly correlated, as it can automate repetitive reporting tasks, enhancing efficiency. This automation enables decision-makers to make faster and more accurate decisions. This research focuses on assessing the capacity and factors involved in the collaboration between the operations department and the digital team to automate repetitive reporting processes by integrating big data from various sources such as SAP and Microsoft Forms. The study employs a combination of qualitative and quantitative methods, along with the Analytic Hierarchy Process (AHP), to identify optimal business solutions. Insights from this research prioritize big data automation and reporting projects to meet business needs. Results indicate among four alternative project groups, the Central Data Wastage project is the top priority with a score of 51.7%, followed by SMD Wastage at 25.2%, PMD Wastage at 14.7%, and FMD Wastage at 8.4%. Five stakeholders participated in this research, including a product manager, business user, business analyst, and two developers. These participants contributed to assessing criteria, sub-criteria, and alternative project groups. This research not only helps prioritize projects but also facilitates seamless digitalization within the operations team, fostering synergy with the digital team.
The Influence of Role Ambiguity and Workload Moderated by Resilience on Employee Burnout Ahmad Fadli; Muhammad Imam Muttaqijm; Muljadi Muljadi
Quantitative Economics and Management Studies Vol. 5 No. 3 (2024)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems2634

Abstract

The purpose of this research is to determine the effect of Role Ambiguity, Workload moderated by Resilience on employee Burnout at PT. United Waru Biscuits manufacturing. Cikande Branch. The research method used is associative with a quantitative approach. Data collection techniques, data questionnaires and literature study. The partial research results of the first test using a one sample t-test showed; The first test of the Ambiguity variable on Burnout obtained a t-count value of 11.983 > t-table 1.988, with a significance of 0.000 < 0.05, this shows that there is a positive and significant influence, the second test of the Workload variable on Burnout obtained a t-count value of 6.813 > t -table 1.988 with a significance of 0.000 < 0.05, this shows that there is a positive and significant influence, the third test of Role Ambiguity on Employee Burnout which is moderated by Resilience obtained a t-count value of 1.045 < t-table 1.988, with a significance of 0.299 > 0, 05 This shows that there is no positive and significant influence. The fourth test of Workload on Employee Burnout moderated by Resilience obtained a t-count value of 1.695 < t-table 1.988, with a significance of 0.094 > 0.05, this shows that there is no positive and significant influence.
FMEA-Based Logistic Regression Model for the Evaluation of Photovoltaic Power Plant Risk Dianita Fitriani Program; Ruslan Prijadi
Quantitative Economics and Management Studies Vol. 5 No. 3 (2024)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems2645

Abstract

The purpose of this research is to identify the primary operational risks associated with photovoltaic power plants and develop effective risk management strategies to optimize the operation of existing plants and mitigate risks for future plants that will be constructed as part of the new renewable energy (EBT) transition agenda until 2030. The integration of Failure Mode and Effect Method Analysis (FMEA) with logistic regression provides the formation of a risk treatment ranking that management should prioritize. Risk assessment relies on the expertise and experience of professionals in performing their responsibilities associated with photovoltaic power plants. The research findings have identified 10 potential risks associated with improving photovoltaic power plants operations to prevent failure or damage to the system. These risks are categorized into five stages of the operation process: planning and procurement, installation, operation, and maintenance. Risk rankings and mitigation are generated to prioritize actions aimed at limiting the occurrence of failure/damage and low-capacity factors in photovoltaic power plants as recommendations for the management.
The Influence of Pre-Training Factors on Training Effectiveness Mediated by Motivation to Learn, Motivation to Transfer, and Self-Efficacy – Case Study on Non-Ministerial Government Institutions Kristianto Saputro; Muhammad Irfan Syaebani
Quantitative Economics and Management Studies Vol. 5 No. 3 (2024)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems2646

Abstract

While acknowledging the importance of training, the challenge lies in understanding and optimizing its effectiveness, especially in the context of the government institution’s ever-changing landscape and the associated budgetary considerations. It examines whether pre-training factors—organizational support, training environment, trainer quality, and training need analysis— influence training effectiveness directly or are mediated by motivation to learn, motivation to transfer, and self-efficacy in non-ministerial government institutions in Indonesia. Data were collected from 202 respondents across 19 institutions using purposive sampling and analyzed with Covariance Based-Structural Equation Modeling (CB-SEM) using Lisrel 8.80. The findings reveal that trainer quality significantly affects motivation to learn, motivation to transfer, and self-efficacy but does not directly impact training effectiveness. Instead, its influence is mediated by motivation to transfer and self-efficacy. This underscores the crucial role of trainers in enhancing training effectiveness by boosting participants' motivation and self-efficacy. The study highlights the need for organizations to invest in high-quality trainers through ongoing professional development, robust evaluation systems, and incentives to improve training outcomes and achieve organizational goals more efficiently.
The Influence of Liquidity on Bond Credit Ratings: Evidence from The Indonesian Corporate Bond Market Firly Armanda; Buddi Wibowo
Quantitative Economics and Management Studies Vol. 5 No. 3 (2024)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems2659

Abstract

This study examines the effectiveness of various liquidity proxies in distinguishing between Investment Grade (IG) and High Yield (HY) bonds within the Indonesian corporate bond market. Utilizing logistic regression models across a dataset of 30,738 observations for IG bonds and 176 observations for HY bonds, we evaluated the impact of six liquidity proxies: Range Measure (RG), Hui Heubel ratio (HH), Market Share (MS), Interquartile Range (IR), Imputed Roundtrip Cost (IRC), and Trading Volume (TV). The findings reveal that the Imputed Roundtrip Cost (IRC) is the most reliable indicator of liquidity, demonstrating a significant negative relationship with the likelihood of a bond being classified as IG. This suggests that higher IRC values, which represent higher transaction costs, are associated with lower liquidity. In contrast, the other proxies, including the Hui Heubel ratio, did not show consistent or significant impacts in line with the hypotheses. The study concludes that IRC is the best measure for assessing liquidity in the Indonesian corporate bond market.
Comparative Analysis of Value-at-Risk in Market Risk Prediction in Banks Using GARCH Volatility Girindra Chandra Alam; Buddi Wibowo
Quantitative Economics and Management Studies Vol. 5 No. 3 (2024)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems2661

Abstract

This study aims to compare the disclosure of Value at Risk (VaR) in market risk prediction among banks in Indonesia. By employing comparative and analytical methods, this research examines the effectiveness of VaR disclosure as a market risk prediction tool. Through the evaluation of VaR models disclosed by Indonesian banks and their comparison to a parametric model using asymmetric GARCH volatility for Variance Covariance Value at Risk, this study identifies the extent to which VaR disclosure can be relied upon to predict market risk. This research contributes to the understanding of risk management practices in the Indonesian banking sector and offers recommendations for improving market risk prediction accuracy through more effective VaR disclosures.
MSME Development Through Simple Bookkeeping, Financial Management and Internal Control Training Mirna Wati; Laylan Syafina; Nurwani Nurwani
Quantitative Economics and Management Studies Vol. 5 No. 3 (2024)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems2676

Abstract

This research aims to develop MSMEs in Aek Songsongan Asahan Sub-district through training in simple bookkeeping, financial management, and internal control. This research uses a qualitative research design with a field study approach. Data were collected through interviews, observation, and evaluation. Data analysis used data triangulation, which combines data from various sources. The results showed that the training improved the efficiency and effectiveness of MSME operations, and promoted financial growth and stability. A more detailed discussion compares with previous studies in the last five years that show the positive impact of training in simple bookkeeping, financial management, and internal control on MSMEs. However, this study also explores aspects of sustainability and technology integration that have not been widely discussed in previous studies. This research makes an important contribution in developing MSMEs through human resource capacity building, particularly in the aspects of simple bookkeeping, financial management, and internal control.
Does E-Service Quality and Social Network Really Matter? Examining Its Impact on Trust and Purchase Intention I Gusti Ayu Cynthia Puspita Sari; Nilna Muna
Quantitative Economics and Management Studies Vol. 5 No. 3 (2024)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems2677

Abstract

Current study explored the connection between e-service quality, social networks, purchase intention, and customer trust, specifically focusing on how artificial intelligence impacts e-service quality within insurance companies. This research employed Theory of Planned Behavior as the basis foundation and conducted through a quantitative approach. Denpasar was used as the research location and targeting 150 local communities as respondents. Empirical data was collected through questionnaires and the analysis was performed using Structural Equation Modeling (SEM) with AMOS version 23 software. The findings indicate significant and positive relationships among all variables, leading to the acceptance of all hypothesis. The findings of this research show that the quality of AI-based services and social networks has a significant impact on the level of consumer trust in insurance products. A high level of trust in the quality of insurance products will in turn increase consumers' willingness to use these insurance products, thereby stimulating consumer loyalty towards insurance companies. The results of data analysis highlight that trust is a crucial key in consumer interest in purchasing a product. Interesting findings from this research also emphasize that gender, especially female consumers, show higher interest in insurance products. This is due to the belief that women have a high awareness of health and financial risks, thus motivating them to use insurance products.
The Implementation of Holt-Winters Method to Forecast the Loan Interest Rate of Indonesia Ansari Saleh Ahmar; Abdul Rahman; Mohd. Rizal Mohd. Isa; Rahmat Hidayat
Quantitative Economics and Management Studies Vol. 5 No. 3 (2024)
Publisher : PT Mattawang Mediatama Solution

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35877/454RI.qems2718

Abstract

This study aimed to anticipate the rupiah loan interest rates at commercial banks in Indonesia by employing the Holt-winters method. This study employs data on rupiah loan interest rates from commercial banks in Indonesia. The data comprises a time series element, with monthly intervals spanning from January 2013 to November 2015, which was obtained from the official website of BPS Indonesia. The study demonstrates that the Holt-winters technique yields the most accurate forecasts, as indicated by a Root Mean Square Error (RMSE) of 0.19720630. The parameters alpha, beta, and gamma, set at 0.6, 0.6, and 0.6 respectively, constitute the optimal configuration for this method. These results indicate that the Holt-winters method is an effective tool for capturing seasonality, trends, and patterns in credit interest rate data, making it a reliable choice for future loan interest rate forecasting. The findings of this study are expected to significantly contribute to strategic decision-making in the banking sector, particularly in risk management and loan interest rate strategy determination.

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