Showing 28 results for Risk
Shimelis Mihretu, Mahesh Gopal,
Volume 32, Issue 4 (12-2021)
Abstract
The study investigates the impact of work environment on organizational performance in Ethiopiachr('39')s Arjo Dedessa Sugar Factory (ADSF) and Finchaa Sugar Factory (FSF), as well as the relationship between physical work environment, work-related risk and injuries, psychological work environment, and social work environment. The total number of people employed in two industries is 867 and 2824. To examine the work-related environment condition, a stratified random sampling technique was used to select a sample of 266 and 338 employees. A 60% response rate has been achieved. Statistical software SPSS V 23.0 was used to analyze and determine the relationship between dependent and independent variables using Pearson correlation and linear regression analyses. The findings show that employees in ADSF have a moderate social work environment compared to those in FSF, but both organizationschr('39') physical work environments are the least conducive. Both ADSF and FSFchr('39')s physical work environments had statistically significant effects on their performance. The suggestion was made to improve the social environment in order to improve the employeeschr('39') psychological health.
Sara Motevali Haghighi, Sima Motevali Haghighi,
Volume 33, Issue 2 (6-2022)
Abstract
In today's world, COVID-19 pandemic has affected many organizations. Pandemic issues have created financial and social problems for businesses. Crisis and risk management have a significant impact on reducing consequences of pandemics. Rapid response to risk enhances the performance of organizations in times of crisis. Therefore, a framework to provide risk treatment in a pandemic crisis seems essential. To do this, this paper presents a framework to identify risk factors posed by pandemics. In this regard comprehensive risk factors by considering sustainability concept are illustrated for university. Then, identified risk factors are evaluated by best–worst methodology (BWM) and then the important risks are recognized. Using the importance of risk and the strengths and weaknesses of the business, solutions to reduce the impact of risk are suggested to managers. The results of this paper can be used in order to enhance resiliency of the organization in front of the pandemics from social and financial viewpoints.
Yulial Hikmah, Vindaniar Yuristamanda, Ira Rosianal Hikmah, Karin Amelia Safitri,
Volume 33, Issue 2 (6-2022)
Abstract
Flood is a serious problem that can occur in many countries in the world. For tropical countries such as Indonesia, flooding is generally caused by rainfall that is high above normal. Almost all cities in Indonesia experience flooding every year, including DKI Jakarta, the capital city of Indonesia. Based on data from the National Disaster Management Agency (BNPB) in 2020, East Jakarta is a city that is prone to flooding. Considering that there are so many losses caused by flooding, it is necessary to have a disaster mitigation effort to minimize the possible risk of flooding. One of the risk mitigations due to natural disasters is to buy insurance products. However, not all people buy flood-impacted insurance products because of their economic and social factors. This research aims to create a model with Probit Regression Model to determine the factors that influence Indonesian's interest to buy flood-impacted insurance products. Furthermore, this study conducts a test. The results show that from the 19 factors used, eight factors significantly affect Indonesia's interest in purchasing flood-impacted insurance products. In the end, this research calculates the level of model accuracy and obtained 84.3%.
Budi Suprapto, Paulus Dian Wicaksana, Mohd Fazli Mohd Sam ,
Volume 33, Issue 3 (9-2022)
Abstract
Technological developments are very rapidly making changes in consumer behaviour where there is a transition from offline transactions to online in Yogyakarta. The purpose of this study is to evaluate and validate the influence of online trust and the factors that influence it is e-commerce knowledge, perceived reputation, perceived risk, perceived technology, prior purchase experience, to the intention of purchasing online. This study also examines the effect of perceived technology and prior purchase experience on online purchase intentions. Respondents in this study are about 260 respondents. Respondents must be domiciled in Yogyakarta and have conducted online transactions in the last 3 months. Analysis of data on research using Smart PLS 3.0. The test of measurement model that is convergent validity, discriminant validity, and internal consistency reliability is done to ensure the validity and reliability of the questionnaire and then tested the structural model to test the hypothesis, besides the fit model, predictive relevance and effect size of each latent variable. This study found that perceived risk is the most influencing factor of consumer confidence followed by prior purchase experience, perceived technology, and perceived reputation. The study also found that perceived technology and trusts influence online purchase intentions. While e-commerce knowledge has no effect on consumer trust and prior purchase experience has no effect on the intention of purchasing online.
Nur Afni Kutanga, Annisa Kesy Garside, Dana Marsetiya Utama,
Volume 34, Issue 1 (3-2023)
Abstract
Palm oil is a commodity whose demand continues to increase, requiring proper risk management in the supply chain. This study aims to develop a hybrid method that integrates probability impact matrix, analytical network process, and house of risk to mitigate strategies in the palm oil supply chain. The Probability Impact Matrix (PIM) method is used to map the priority risk agents and determine the occurrence value of the risk agents, and Analytical Network Process (ANP) is used to determine the severity value of the risk event. Furthermore, the House of Risk (HOR) is proposed to determine the priority of the mitigation strategy. The proposed method was applied in a case study on the palm oil supply chain in Indonesia. The research results show that ten priority risk agents and 6 mitigation strategies were obtained based on the proposed method to overcome risk agents in palm oil supply chain
Muh Syarif, Ismie Roha Mohamed Jais, Iffan Maflahah, Ihsannudin Ihsannudin,
Volume 36, Issue 1 (3-2025)
Abstract
The research focuses on improving the performance of the corn supply chain in Madura Island, Indonesia. The purpose of the study is to identify, evaluate, and prioritize risks that have the potential to disrupt the smooth operation of the corn supply chain. The research method uses Failure Mode and Effects Analysis (FMEA) to identify risk levels and Root Cause Analysis (RCA) approach for mitigation strategies. Risk level assessment is based on severity, probability, and detectability at the level of farmers, middlemen, processing industries, and distributors. Based on the analysis, it shows that the risks are a priority in handling and prevention as well as proposals that can be made to improve the root cause of the occurrence of risks with the highest category based on the RPN value at the farmer level are the occurrence of pest and disease attacks (648), the middleman level is when the amount of corn is abundant (336), the processing industry level is the price of corn is unpredictable (252), and the level of distributors is a limitation in product promotion (324). To improve the efficiency and quality of the corn supply chain, namely increasing storage capacity, using more efficient processing technology, flexible production planning, and more innovative marketing strategies. The managerial implications of corn-supply chain risk assessment are the need to improve product quality, corn supply stability, price management, and strengthen partnerships and mutual benefits between all parties in the supply chain. Every element of the supply chain needs to encourage the adoption of modern technologies in maize cultivation, processing, and distribution to increase productivity and reduce risks associated with manual processes. It is necessary to establish mitigation strategies to address environmental risks, including the implementation of sustainable agricultural practices and early warning systems.
Ahmad Mohammadpour Larimi, Babak Shirazi, Iraj Mahdavi,
Volume 36, Issue 2 (6-2025)
Abstract
location-inventory problem (LIP) is a significant issue in supply chain management (SCM), aiming to reduce and integrate the costs of inventory and location. Perishable-LIP (PLIP) includes products, particularly those with a short expiration date, also known as perishable items. This feature necessitates the supply chain to maintain high reliability and resilience to minimize costs faced with disruption risks. Implementing reliability and resilience in PLIP (R2-PLIP) requires methods such as lateral transshipment. These methods not only enhance the reliability and resiliency of the SC but also mitigate the risks associated with supply disruptions and demand fluctuations. Demand for perishable products is influenced by their expiration dates. By incorporating lateral transshipment, companies can ensure a more balanced inventory distribution. This study investigates the role of lateral transshipment in enhancing supply chain robustness. A multi-objective optimization model is developed, focusing on minimizing costs while maximizing resilience and service levels. The project aims to optimize the overall system efficiency. Additionally, the sensitivity analysis conducted in the research indicates that the shortage cost and the DC capacity each had the greatest variations in one of the objective functions. This research provides practical insights for designing resilient perishable supply chains.
Ida Lumintu, Achmad Maududie,
Volume 36, Issue 3 (9-2025)
Abstract
Effective inventory management is critical for mitigating inefficiencies such as overproduction, excessive holding costs, and stockouts. This study leverages DBSCAN and GMM clustering methods, combined with Principal Component Analysis (PCA) for dimensionality reduction, to categorize inventory data into distinct risk-based clusters. The analysis highlights that DBSCAN outperformed GMM, achieving a silhouette score of 0.62 compared to 0.49, while identifying three meaningful inventory clusters. Each cluster reflects unique combinations of risk factors, providing actionable insights for optimizing inventory levels. The study demonstrates how these clusters enable targeted strategies to address inefficiencies and improve overall inventory management. Limitations include the reliance on historical data, which may not fully capture dynamic market conditions, and the assumption of fixed clustering parameters. The findings underscore the importance of choosing clustering algorithms suited to the data's characteristics and highlight the potential of PCA in enhancing computational efficiency. Future research should explore dynamic clustering techniques and integrate real-time data streams to refine inventory management strategies further.
