Showing 660 results for Type of Study: Research
Dede Rukmayadi, Yayan Saputra, Rifki Muhendra, Zulfa Fitri Ikatrinasari,
Volume 35, Issue 1 (3-2024)
Abstract
Although the existence of swimming pools is very important for people who need to exercise or just have fun with their families, there are still few studies conducted to explore how to analyze the strategic planning of swimming pool companies in order to grow and develop. For this reason, this research will carry out strategic planning for the company Oasis Pool. The research stage consists of analyzing the internal and external strategies of the Oasis Pool company using the AHP SWOT method. In the second stage, a structural analysis of Oasis Pool's corporate strategy is carried out using the interpretative structural modeling (ISM) method. The results showed that the most appropriate strategy in the development of Oasis Pool's business is a growth strategy. This strategy can be implemented by maximizing fast response services and always maintaining spare parts availability to increase customer satisfaction. Furthermore, the key element of the strategy that will determine the success of Oasis Pool's corporate strategic planning is to maintain fast response to improve service quality. In order to maintain Oasis Pool's business to grow and develop and win the market competition, it is necessary to do the following things such as: design a good work system, active management to make improvements and innovations and keep up with technological developments. The main contribution of this article is to assist swimming pool managers such as Oasis Pool in carrying out effective strategic planning using AHP - SWOT and ISM methods.
Renny Rochani, Wahyudi Sutopo, Satrio Fachri Chaniago,
Volume 35, Issue 1 (3-2024)
Abstract
Electric motorcycles (EM) are promising solutions for eco-friendly vehicles, but there are some dilemmas caused by the fossil-based energy used for charging and the limited charging infrastructure. This article proposes solving these dilemmas by designing a Solar-Powered Mobile Battery Swap Charging Station (MBSCS) for EM infrastructure. MBSCS will integrate solar power plants as a sustainable energy source and using battery swap system to accommodate EM. Design thinking methodology is used to develop the initial design of MBSCS and technical indicator assessment through focus group discussions with expert panelists. Simulations are conducted using PVSyst software to evaluate various system variants defined according to the selected components. The results of this study provide the MBSCS initial design, technical indicators to assess the MBSCS system, simulation results, and optimal system variant configuration. The findings of this study will mainly contribute to a solution for EM challenges and offer an environmentally friendly charging infrastructure. This study is expected to serve as an alternative solution for future mobile charging stations designed to answer the limited charging infrastructure as well as to demonstrate the potential use of portable solar power plant to overcome dependence on fossil-based energy.
Halim Dwi Putra, Iphov Kumala Sriwana , Husni Amani ,
Volume 35, Issue 1 (3-2024)
Abstract
The construction industry is one of the high-demand industries related to business and projects. Robust materials management that is subject to inventory management is the highest factor to enhance the Supply chain management (SCM) performance that will indicate the project's success within the complexity of the project. This research aims to measure the performance of Supply Chain Management at PT Cahaya Amal Taqwa as a new housing developer who focuses on subsidized housing that faces a project delay because they have less data documentation and analysis from previous projects. The issue is most newcomer construction projects never analyze and measure their supply chain management (SCM) which leads them to confusion about the project improvement. The research uses the Supply Chain Operational Reference (SCOR) method to know how much inventory management impacts supply chain management performance and how it overcomes the issues. Most studies only measure the SCM performance and show which aspects need to be developed without any scheme of solution offered. This research presents the scheme of improvement for the inventory model and provides forecasting for the whole SCM performance after the implementation of a new model of inventory management. The findings confirm that inventory management significantly impacts the whole supply chain management performance in the construction industry. The development of a solution system brought comprehensive results by classifying KPIs for inventory management and an interdependence network was created to define the new model of inventory system for the solution. This research proves that improving an aspect will impact significantly the whole SCM performance instead of improving KPIs one by one.
Amal Qassim,
Volume 35, Issue 1 (3-2024)
Abstract
This study aims to explore gender differences in occupational stress sources, coping strategies, and emotional well-being among academic staff in Saudi public universities. The leading theory of transactional stress and coping implies the impact of stress and coping strategies on the health and well-being of people. The study surveyed 475 academic staff, 340 females and 137 males employed in Saudi public universities. They were invited to participate in the study by responding to the questionnaire. The study's significant findings reveal distinct variations in occupational stress levels between male and female academic staff. Additionally, it highlights gender-based differences in coping strategies employed by academic staff. Furthermore, the study identifies a prevalent issue of suboptimal levels of emotional well-being among academic staff at public universities in Saudi Arabia. These findings underscore the importance of addressing gender-specific stressors and promoting strategies for enhancing emotional well-being within the academic environment. The presented results consider relevant research, and the practical implications indicate that when Saudi-based universities implement policies and support systems for their staff members, they should consider the gender-based differences emphasized in this study. This could involve providing targeted support programs and policies to address the specific stressors that male and female academics face. Also, encouraging open communication, promoting work-life balance, and fostering a culture of well-being can contribute to creating a more inclusive and supportive academic environment for all faculty members.
Ag Kaifah Riyard Kiflee, Nornajihah Nadia Hasbullah, Faerozh Madli,
Volume 35, Issue 2 (6-2024)
Abstract
Over the years, the attention given to corporate social responsibility (CSR) and sustainability topics has received a lot of attention significantly and various new terms have been introduced. This result has sparked a wide-ranging and unspecified discussion, particularly in the fields of economics and business management. The presents of functional CSR and sustainability enable management to make better decisions for the benefit of the entire society. As a result, understanding the topic of interest and broadening research collaboration are critical for advancing research development. The purpose of this study is to identify global research trends in CSR and sustainability based on publication numbers, co-authorship, affiliated countries, and keyword co-occurrences. This study used RTools and Prisma for its analysis. The findings indicate a significant rise in the number of articles published in the field of corporate social responsibility and sustainability since 2015. The USA contributed more than half of the publications, with Italy and Spain following closely behind.
Mansour Abedian, Amirhossein Karimpour, Morteza Pourgharibshahi, Atefeh Amindoust,
Volume 35, Issue 2 (6-2024)
Abstract
The area coverage of machines on the production line to address the scheduling and routing problem of autonomous guided vehicles (AGV) is an innovative way to improve productivity in manufacturing enterprises. This paper proposed a new model for the optimal area coverage of machines in the production line by applying a single AGV to minimize both the transfer costs and the number of breakpoints of AGV. One of the unique advantages of the area coverage employed in the present study is that it minimizes transfer costs and breakpoints, and makes it possible to provide service for several machines simultaneously since the underlying assumption was finding a path to ensure that every point in a given workspace is covered at least once. Since rail AGV is used in this study, AGV can only pass horizontal and vertical distances in the production line. The reversal of the AGV path in vertical and horizontal distances implies failure and breakpoint in the present paper. The simulation results confirm the feasibility of the proposed method.
Zahra Taherikhonakdar, Hamed Fazlollahtabar,
Volume 35, Issue 2 (6-2024)
Abstract
These days, industries, individuals and organizations are highly dependent on software. Software plays an important role in our daily life. They use in embedded systems, databases, computers, mobiles etc. Great demand for ICT cause environmental problem and endanger the future sustainability. In this case, sustainable development has become a hot research topic in software engineering community. Sustainability as a software quality is a general term. Therefore, there is a chance that software developers mislead about develops sustainable software. Therefore, there are some questions that should be answered to help practitioners to develop sustainable software: how developers could develop green and sustainable software? What requirements should be considered to reach green and sustainable software? Which non-functional requirement has an effect on each sustainability dimension? In this paper, we selected 20 non-functional requirements out of 60. It was identified the effective non-functional requirements in green and sustainable software development by using Delphi method then via interpretive structural modeling (ISM). The study aimed to pave the way for software eco-labeling and help users to choose the green and sustainable one. Also, provide software developers with guideline to develop green and sustainable software by identifying effective non-functional requirements. This would lead to the sustainable future and green environment.
Ali Salmasnia, Elahe Heydarnezhad, Hadi Mokhtari,
Volume 35, Issue 2 (6-2024)
Abstract
Abstract. One of the important problems in managing construction projects is selecting the best alternative for activities' execution to minimize the project's total cost and time. However, uncertain factors often have negative effects on activity duration and cost. Therefore, it is crucial to develop robust approaches for construction project scheduling to minimize sensitivity to disruptive noise factors. Additionally, existing methods in the literature rarely focus on environmentally conscious construction management. Achieving these goals requires incorporating the project scheduling problem with multiple objectives. This study proposes a robust optimization approach to determine the optimal construction operations in a project scheduling problem, considering time, cost, and environmental impacts (TCE) as objectives. An analytical algorithm based on Benders decomposition is suggested to address the robust problem, taking into account the inherent uncertainty in activity time and cost. To evaluate the performance of the proposed solution approach, a computational study is conducted using real construction project data. The case study is based on the wall of the east coast of Amirabad port in Iran. The results obtained using the suggested solution approach are compared to those of the CPLEX solver, demonstrating the appropriate performance of the proposed approach in optimizing the time, cost, and environment trade-off problem.
Dian Dewi, Yustinus Hermanto, Martinus Sianto, Jaka Mulyana, Dian Trihastuti, Ivan Gunawan,
Volume 35, Issue 2 (6-2024)
Abstract
Supply chain agility (SCA) has emerged as a significant focus for industries and businesses, serving as a cornerstone for gaining a competitive edge and playing a pivotal role in supply chain management. This importance is further underscored in the context of Product–Service Systems (PSS), which involve the development of both products and services. Despite the existing body of research on SCA and PSS, there has been a notable dearth of empirical studies examining the readiness of PSS SCA. This study makes a substantial contribution by developing a valid and reliable framework to assess the readiness of PSS for supply chain agility. The process involves defining domains, generating items, analyzing agreement among raters, testing for response bias, and conducting exploratory and confirmatory factor analyses. Using structural equation modeling, the model's validity and reliability were evaluated through an online survey with 405 participants from official motorcycle service partners. The findings identify six key capability constructs: collaboration, knowledge transfer, service partner development, information sharing, logistic integration and supply chain agility. This examination of PSS SCA readiness and its constructs provides a validated tool for industry practitioners to enhance their supply chain agility.
Daniel Atnafu, Shimelis Zewdie Werke,
Volume 35, Issue 2 (6-2024)
Abstract
The incorporation of sustainable practices becomes crucial as firms transition from Industry 4.0 to Industry 5.0. Therefore, this systematic review explores the relationship between the two sustainability approaches; Green Human Resource Management (GHRM) and Green Supply Chain Management (GSCM) using peer-reviewed studies from 2016-2023, retrieved from Scopus and Web of Science databases. 2016 marks the starting point as the first relevant paper emerged in the literature in that year. The PRISMA approach was used to identify relevant studies, resulting in the inclusion of 30 studies for analysis purposes. The study reveals a growing interest in understanding the relationship between GHRM and GSCM practices and their impact on sustainable performance. The majority of reviewed studies utilized quantitative survey methods, suggesting the need for future research utilizing qualitative and mixed methods for gaining deeper insights. The review indicates that most studies are conducted in emerging countries, and there is a significant gap in research on the relationship between GHRM and GSCM practices in other context. Finally, the study provides valuable insights for practitioners and researchers, emphasising the importance of integrating GHRM and GSCM practices for a sustainable competitive advantage.
Melinska Ayu Febrianti, Qurtubi Qurtubi, Roaida Yanti, Hari Purnomo,
Volume 35, Issue 2 (6-2024)
Abstract
The retail industry is a vital sector of the world economy and is characterized by fierce competition, tight profit margins, and demanding consumers. Understanding customer buying behavior patterns is essential in devising the best retail strategy to enhance product sales. This research aims to comprehend customer shopping behaviors based on retail sales transactions and formulate the best strategies. By employing multi-level association rules, the dataset is arranged hierarchically into categories, sub-categories, and items. The sales transaction data used comprises 5830 transaction records over a month. The results of this study reveal 24 associations of categories, 49 associations of sub-categories, and 12 associations of product items. Moreover, the proposed marketing strategy offers recommendations including store layout improvement, planogram design, and bundled product offerings. This research addresses the gap in empirical evidence from a previous study and suggests further observation from diverse locations to authenticate the findings, which may yield various outcomes
Tenaw Tegbar Tsega, Thoben Klaus-Dieter, Rao D.k.nageswara, Bereket Haile Woldegiorgis,
Volume 35, Issue 2 (6-2024)
Abstract
Ethiopia has made enormous efforts in the leather industry to gain manufacturing capabilities that can be scaled up to other sectors. Those efforts have resulted in the industry shifting its role from raw material supplier to producer of value-added products for the global supply chain (GSC). However, the industry has faced severe challenges in generating the expected revenue, utilizing capacity, and finally coping with the global competitive environment. Studies reveal that manufacturing firms tackle similar challenges by improving their supply chain performance (SCP). The challenges that appeared in the leather industry of Ethiopia could also be solved by improving its SCP. Nonetheless, there is a lack of study on the basic characteristics and SCP of the industry after it has shifted its role. The main objective of this study is, therefore, to measure the SCP to know where it stands using a bench mark and identify the elements that contribute considerably to the low overall SCP in order to lay the foundation for subsequent improvement. To achieve the research objective, data was collected from primary and secondary sources through a questionnaire, survey, observation, and focus group discussion. The data is analyzed using the supply chain operations reference model (SCOR version 12.0). Accordingly, the overall SCP is found to be 67.33%, suggesting an average rating as per the set benchmark. The source process is identified as the most influential element for the overall low SCP, with a percentage gap of 17.23%. Taking corrective action on the identified elements could help the industry overcome the existing challenges by improving its SCP.
Mariam Atwani, Mustapha Hlyal , Jamila El Alami ,
Volume 35, Issue 2 (6-2024)
Abstract
In today's dynamic and competitive manufacturing landscape, accurate demand forecasting is paramount for optimizing production processes, reducing inventory costs, and meeting customer demands efficiently. With the advent of Artificial Intelligence (AI), there has been a significant evolution in demand forecasting methods, enabling manufacturers to enhance the accuracy of the forecasts.
This systematic literature review aims to provide a comprehensive overview of the state-of-the-art on demand forecasting models in the manufacturing sector, whether AI-based models or hybrid methods merging both the AI technology and classical demand forecasting methods. The review begins by establishing an overview on demand forecasting methods, it then outlines the systematic methodology used for the literature search.
The review encompasses a wide range of scholarly articles published up to September 2023. A rigorous screening process is applied to select relevant studies. Accordingly, a thorough analysis in the basis of the forecasting methods adopted and data used have been carried out. By synthesizing the existing knowledge, this review contributes to the ongoing advancement of demand forecasting practices in the manufacturing sector providing researchers and practitioners an overview on the advancements on the use of AI models to improve the accuracy of demand forecasting models.
Ebaa Dasan Barghouthi,
Volume 35, Issue 2 (6-2024)
Abstract
The patient has a legitimate role in evaluating the healthcare services provided to them; this evaluation can be measured through patient satisfaction, which is considered an effective tool to evaluate the provided services and the quality program for hospitals. This study aims to examine the association between patient satisfaction and hospital accreditation status. Cross-sectional design with a random sampling technique for adult hospitalized patients. The SERVQUAL instrument was utilized to measure the patient's satisfaction. The sample size included 800 patients from the two phases based on the inclusion and exclusion criteria. The obtained data was analyzed using SPSS version 26. The study revealed that patient satisfaction was high both before and after accreditation. The order of the patient satisfaction dimensions was as follows: assurance, reliability, tangibles, responsiveness, and empathy. The highest subscale in this phase was assurance, with a mean of (4.49), and the lowest score was empathy, with a mean of (4.25). In the pre-accreditation phase, reliability was the highest subscale, with a mean of (4.46), and the lowest score was responsiveness, with a mean of (4.13). In addition, the study revealed that there is an association between the satisfaction subscales (tangibles, responsiveness, and assurance) and accreditation status, except for reliability and empathy. The study concludes that the high level of satisfaction in the post-accreditation phase may relate to the high level of patient care standards and safety environment implemented in the hospital as requirements of accreditation, which gives evidence that the hospital accreditation status had a positive impact on patient satisfaction.
Amin Amini, Alireza Alinezhad, Davood Gharakhani,
Volume 35, Issue 2 (6-2024)
Abstract
The selection of a sustainable supplier is a multi-criteria decision-making issue that covers a range of criteria (quantitative-qualitative). Selecting the most eco-friendly suppliers requires balancing tangible and intangible elements that may be out of sync. The problem gets more complicated when volume discounts are taken into account, as the buyer needs to decide between two issues: 1) What are the best sustainable suppliers? 2) Which amount needs to be bought from each of the selected eco-friendly suppliers? In current study a combined attitude of best-worst method (BWM) ameliorated via multi-objective mixed integer programming (MOMIP) and rough sets theory is developed. The aim of this work is to contemporaneously ascertain the order quantity allocated to these suppliers in the case of multiple sourcing, multiple products with multiple criteria and with capacity constraints of suppliers and the number of suppliers to employ. In this situation, price reductions are offered by suppliers based on add up commerce volume, not on the amount or assortment of items acquired from them. Finally, a solution approach is proposed to solve the multi-objective model, and the model is demonstrated using a case study in Iran Khodro Company (IKCO). The results indicate that ISACO is the most sustainable supplier and the most orders are assigned to this supplier.
Kafa Al Nawaiseh, Abdullah Al Khatib, Fayiz Sharari, Victor Soultanian, Al’a Jaradat,
Volume 35, Issue 2 (6-2024)
Abstract
The world today gives much importance to human resource management which is viewed as the gate towards effective performance. In this respect, the application of intelligent human resources management increases the effectiveness of HRM and brings about effective performance. Given the importance of this topic, this study sought to evaluate the future direction of intelligent human resources management applications in employee performance measurement and data analysis in the industrial sector in Jordan. It specifically evaluated the effect of intelligent human resources management applications (recruitment and talent acquisition, learning and development, benefits and incentives, workforce planning and improvement) on measuring the performance of employees and analyzing data in the Jordanian industrial sector. This research used the descriptive-inferential method (Inductive Descriptive Methodology). The population included all employees in the supervisory authorities of the 33 industrial companies listed on the ASE, while the sample includes 146 participants. This research found that human resources management applications directly affect measuring the performance of employees and analyzing data in the Jordanian industrial sector. The novelty of this research is that, unlike the previous studies like Al-Wakeel and Ibraheem (2020) and Wang (2024) that were applied to samples from different countries other than Jordan, it specifically addresses the effect of HRM practices on measuring the performance of employees and analyzing data in the Jordanian industrial sector. This research provides the Industrial Sector in Jordan with the necessary knowledge of the future directions of intelligent human management. Adopting intelligent human resource management is deemed important for the Jordanian industrial sector. It is very important to carry out this research to highlight the effect of human resources management applications on measuring the performance of employees and analyzing data in the Jordanian industrial sector.
Fakhri Ikhwanul Alifin, Bermawi Priyatna Iskandar, Nadia Fasa, Fransisca Debora,
Volume 35, Issue 2 (6-2024)
Abstract
This study develops warranty cost models for repairable products subject to Lemon Laws, encompassing Critical and Non-Critical components forming a multi-component system. Failures can arise naturally or be induced by other components (i.e., failure interaction), defining a lemon if recurrent failures reach a threshold (k) during the warranty period. A lemon declaration triggers a refund or replacement by the manufacturer. Four warranty cost models are proposed from the manufacturer's standpoint, considering failure mechanisms. Increasing failure thresholds in the warranty scheme substantially decreases warranty cost rates. For instance, a threshold (k) of 5 in refund and replacement schemes yields the lowest cost rates of 33.7159 and 25.8249, respectively. Failure interactions escalate total warranty costs; for instance, in a refund scheme (k = 5), costs with failure interaction reach 31.0169 compared to 28.7603 without. Similar trends apply to replacement schemes. Moreover, a lower warranty cost rate will extend the period, indicating regulation fulfillment due to a closer warranty period to the Lemon period. Sensitivity analysis also underscores the role of higher reliability in reducing warranty costs and complying with Lemon Laws. Finally, maintenance strategies and product reliability are emphasized to fulfill Lemon Laws with minimal costs, i.e., fewer warranty claims.
Hamed Salehi Mourkani, Anwar Mahmoodi, Isa Nakhai Kamalabadi,
Volume 35, Issue 3 (9-2024)
Abstract
This research investigated the problem of joint inventory control and pricing for non-instantaneous deteriorating products; while, the quantity dependent trade credit is allowed. It was observed here that the buyer order amount is equal or more than the amount specified by the seller. The Shortage was not permitted in the system. It was aimed in present study to find a procedure for achieving the optimal selling price and replenish cycle and to be able to maximize the system's profit. To do so, first, the system's total profit function was derived. Then, the uniqueness of the optimal replenishment cycle for a given price was proved. Next, the concavity of the total profit function concerning the price was revealed, depending on the trade credit policy. Thereafter, an algorithm was provided to fulfill the optimal solution and eventually a dual-purpose numerical analysis was carried out both to show the model performance and to evaluate the sensitivity of the main parameters.
Kuswanto Kuswanto,
Volume 35, Issue 3 (9-2024)
Abstract
Cooperative performance efficiency describes the level of cooperative ability to utilize resources to generate profits. Efficient performance will increase productivity and strengthen business competitiveness. This study was conducted on 34 secondary cooperatives at the provincial level throughout Indonesia. Data was analyzed from 2019 - 2021 using the DEA (Data Envelopment Analysis) method. The results of the analysis show that the efficiency of cooperative performance in Indonesia is very low because the use of input resources exceeds the target needed to generate optimal profits. By using the DEA method, the level of achievement of input use in generating optimum profits is described in detail, starting from the number of cooperative members, utilization of own capital, utilization of external capital, utilization of assets, and the level of business volume developed by the cooperative. The results of this study greatly contribute to improving cooperative performance by evaluating the use of input resources in generating optimum profits according to the capacity of the cooperative
Theodore Alvin Hartanto, Seng Hansun,
Volume 35, Issue 3 (9-2024)
Abstract
One method to diagnose retinal diseases is by using the Optical Coherence Tomography (OCT) scans. Annually, it is estimated that around 30 million OCT scans are performed worldwide. However, the process of analyzing and diagnosing OCT scan results by an ophthalmologist requires a long time so machine learning, especially deep learning, can be utilized to shorten the diagnosis process and speed up the treatment process. In this study, several pre-trained deep learning models are compared, including EfficientNet-B0, ResNet-50V2, Inception-V3, and DenseNet-169. These models will be fine-tuned and trained with a dataset containing OCT scanned images to classify four retinal conditions, namely Choroidal Neovascularization (CNV), Diabetic Macular Edema (DME), Drusen, and Normal. The models that have been trained are then tested to classify the test set and the results are evaluated using a confusion matrix in terms of accuracy, recall, precision, and F1-score. The results show that the model with the best classification results in the batch size of 32 scenario is the ResNet-50V2 model with an accuracy value of 98.24%, precision of 98.25%, recall of 98.24%, and F1-score of 98.24%. While for the batch size of 64, the EfficientNet-B0 model is the model with the best classification results with an accuracy value of 96.59%, precision of 96.84%, recall of 96.59%, and F1-score of 96.59%.
