Hasil untuk "Management information systems"

Chanchal Molla, Khaled Islam, Md. Razib Hossain et al.

This study investigates the impact of metaverse platforms on electronic commerce (E-commerce) performance, focusing on customer engagement as a mediating factor. Given the challenge of low customer engagement in online shopping, it is crucial to examine how immersive technologies, such as the metaverse, affect e-commerce success. A structured online questionnaire was used to collect primary data from 300 active Metaverse users. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) to assess the relationship between the adoption of the metaverse, customer engagement, and performance in e-commerce. The findings show that the extended reality has a direct positive effect on e-commerce, whereas the digital realm has an indirect positive impact on the performance through the customer engagement. Customer engagement partially mediates this relationship, highlighting that businesses can optimize the advantages of the metaverse by promoting increased user engagement and interaction. This study theoretically advances our understanding of how immersive technologies impact the evolution of online consumer behavior and online business performance. This study guides e-commerce managers to use interactive, social, and gamified features to boost engagement and loyalty.

AgustiQori Al-Mubarak, Ismi Rahmawati, Oetari Oetari

Optimal drug management and drug inventory control can minimize costs and the number of orders in the next planning period. The purpose of this study was to evaluate drug management in the Pharmacy Installation of Harapan Insan Sendawar Hospital with SWOT analysis improvement strategies. The research design was descriptive based on retrospective and concurrent data. All quantitative data were compared with the indicators of The Department of Health (2008), WHO (1993), Minister of Health Regulation (2013), and Pudjaningsih in Satibi (2022). Furthermore, qualitative analysis was carried out with a SWOT approach as an alternative improvement strategy in the Pharmacy Installation based on quantitative data output and internal capital and external influences. The results of the study that meet the standards are: the level of drug availability (15,6 months) and the average prescription service time (non-compounded prescription 23,37 minutes & prescription 39,8 minutes). Results that did not meet the standard were: percentage of stock card matches with drugs (94,73%), inventory turnover ratio (2,22 times), percentage of expired drugs (4,7%), percentage of dead stock (8,97%), number of drug items per prescription sheet (3,57 items), percentage of generic drug prescriptions (76,25%). SWOT analysis of the pharmacy installation falls within the first quadrant, namely focusing on development, improving services and establishing cooperation. The conclusion drawn is that pharmacy installations can adopt aggressive strategies by enhancing the development of management information systems to optimize inventory control.    

Alireza Sarsangi Aliabad, Ara Toomanian, Majid Kiavarz et al.

Extended Abstract:1. IntroductionElectricity is an essential input for all production systems and a necessity for all modern families. Hence, relevant energy policies are needed to induce efficient electricity consumption in the residential sector in many countries due to the effects of global warming and security of energy supply. Forecasting electricity demand at a regional or national level is crucial for planning to ensure optimal energy management. Various factors influence household consumption patterns. Factors such as employment rate, residential area, distance from green space, etc. affect electricity consumption. The purpose of this study is to investigate the impact of various factors on electricity consumption in residential homes in Yazd city. The results of this study will be useful for making management decisions for planning to reduce electricity consumption.2. Research MethodologyThe present study was conducted in the city of Yazd, which has a hot and dry climate and is extremely hot in the summer. Data on electricity consumption of Yazd city subscribers was obtained from the provincial electricity distribution company for the years 2016 to 2019. Data related to the city's buildings, such as (current use, building height, area, building shape, and building age), as well as streets, existing street widths, and the location of parks and green spaces, were obtained from the municipality. Spatial configuration indices including: connectivity, depth, coherence and control were estimated. The urban physical parameters of the components of parcel area, building area, yard area, building height, building volume were calculated. Then, association rules were used to examine the existing relationships. Spatial Association Rules are a set of rules that describe the relationships between different features in spatial data. These rules are a capability to find unknown relationships in spatial data. Spatial association rules are rules that indicate the implication of a set of features on another set of features in a spatial database. These rules are introduced to discover the rules between products in large-scale transactional data. 3. Results and discussionResidential electricity consumption data was analyzed using Moran's spatial autocorrelation index and based on Euclidean distance. The results of the study of hot and cold spots of residential electricity consumption data in the study area showed that the distribution of electricity consumption in residential homes is asymmetrical. That is, the number of homes with very high electricity consumption is greater than the number of homes with very low electricity consumption.In total, 3.2 percent of the number of parcels in the region is made up of Low_High outliers and 4.7 percent is High_Low. In the present study, the Apriori algorithm was used. The Apriori algorithm is known as one of the main methods in data mining for discovering association rules. The results of the rule review using Apriori showed that in rule one: buildings with a height of 5 to 8 meters that are located in a new urban context are most likely (93%) to have an annual electricity consumption of more than 3,500 units. Rule two: buildings that are located in a new urban context and their control is less than 1 are most likely (87%) to have an annual electricity consumption of more than 3,500 units. Rule three: buildings that are located in parcels with an area of 150 to 250 square meters and a local connectivity of 2-3 are most likely (74%) to have an annual electricity consumption of more than 3,500 units. Rule four: buildings that are located in parcels with an area of 150 to 250 square meters and in a new urban context and with a yard area of less than 75 square meters are most likely (61%) to have an annual electricity consumption of more than 3,500 units.4. ConclusionAssociation rules are able to extract patterns that cannot be easily identified by traditional methods and provide useful information for optimizing energy consumption.One of the major challenges in using association rules in big data is the need for time-consuming and resource-intensive processing, especially when the data is complex and contains a large number of features. Association rules are usually designed for discrete data, and for numerical data, complex preprocessing such as converting the data to categorical values may be required. Also, the appropriate selection of parameters such as minimum support and confidence can be difficult and have a significant impact on the quality and applicability of the extracted results. It is suggested that in future studies, hourly electricity consumption data should be used if possible so that the effects of more factors can be examined. -

Mohammad Farid Naufal, Selvia Ferdiana Kusuma

Background: Diagnosing many medical ailments, including infections, immunological problems, and hematological diseases, is a process that depends on precise as well as quick identification of blood cell. Conventional methods for blood cell identification may include skilled pathologists visually inspecting the cell under a microscope, which is a time-consuming choreography. This method is not appropriate for processing vast amounts of data, because the process is time-consuming and is prone to human mistakes. Objective: This study aimed to improve YOLOv8 architecture, offering a more efficient and simplified model for blood cell identification. In addition, the main objective of the analysis was to reduce computational load as well as amount of parameters and still maintaining or improving detection performance. Methods: GhostBottleneck and C3Ghost modules used in the study were included in the head and backbone of YOLOv8 architecture for improvement. All versions of YOLOv8 was subjected to the changes including n, s, m, l, and x. During the analysis, the efficacy of the recommended method was evaluated using a dataset of seven kinds of blood, namely basophil, eosinophil, lymphocyte, monocyte, neutrophil, platelets, and red blood cells (RBCs). The analysis also tested the proposed method on the well-known Blood Cell Count and Detection (BCCD) dataset, which was a common benchmark in this field, for comparing the performance. Performance of the model relating to past studies was assessed through this process. Results: The investigation used GhostBottleneck and C3Ghost modules to reduce GFLOPS by 45.56% and the number of parameters by 76.55%. Mean average precision (mAP50) of 0.984 was achieved using recommended method. Additionally, on BCCD, the method scored 0.94 on New Cell Dataset. Conclusion: Modifications performed to YOLOv8 design significantly increased its blood cell detection efficiency and effectiveness. The improvements showed that the changed model was suitable for real-time use in settings with constrained resources. Keywords: Blood Cell Detection, C3Ghost, Ghostbottleneck, YOLOv8

M. Ya. Kletsel, E. V. Petrova, S. S. Girshin et al.

The efficient and sustainable functioning of energy systems is a critical element for supplying of electricity necessary to maintain the vital functions of modern society. Therefore, the integration of meteorological data into the management of electrical grids is becoming increasingly important. Meteorological data, such as information on weather conditions, temperature, wind and precipitation, play an essential role in the operational and strategic management of power systems. Their use allows optimizing the operation of generating and distribution stations, using the maximum capacity of lines, as well as improve the planning of repair work and infrastructure upgrades. On the basis of the weather conditions, operators of electric power grids can make more informed decisions regarding the distribution and management of energy resources.The research is aimed at determining the role of meteorological data in the management strategies of modern energy systems.

Adeola Bamgboje-Ayodele, David N Borg, Steven M McPhail et al.

Objectives To synthesise the literature on clinical decision support (CDS) systems for chronic obstructive pulmonary disease (COPD). We aimed to (1) describe existing COPD CDS systems that have been designed, developed or are being used in practice, (2) describe the impact of COPD CDS systems on outcomes and (3) identify barriers and facilitators to implementation of COPD CDS systems. Methods Five databases were searched to identify relevant studies. All studies in English that described clinician-facing COPD CDS systems designed for, or implemented in, hospitals and hospital-in-the-home settings were included. A qualitative narrative synthesis was undertaken, guided by the RE-AIM framework ( Reach, Effectiveness, Adoption, Implementation and Maintenance ). Results Twelve studies reporting the use of CDS in hospital ( n  = 7) and hospital-in-the-home ( n  = 5) settings were included. Implementation efforts to reach target users were scantly reported, and low-to-medium adoption rates were observed. The reported effectiveness of the CDS systems was mixed. Only one study reported facilitators to the implementation of CDS systems, none reported on barriers to the implementation of CDS systems, and none reported any information on successful strategies to maintain implementation of CDS systems. Conclusion The use of CDS systems in the management of patients with COPD in hospital-related settings is an important emerging field of research. Evidence suggests that the field has largely focused on systems targeted at physicians, often with incomplete descriptions and limited evaluations. Many opportunities to optimise and evaluate the implementation and use of COPD CDS systems in hospital settings remain, including robust evaluation of their impact on patient, clinician and health service outcomes.

Chi-Ho Jeon, Duy-Cuong Nguyen, Gitae Roh et al.

Globally, bridges are rapidly aging, and traditional maintenance approaches face significant challenges in terms of efficiency and cost. To overcome these challenges, considerable research has been conducted to introduce enhanced bridge management systems (BMSs) based on bridge information modeling (BrIM) from various perspectives. However, most studies have highlighted the advantages of BrIM, while neglecting the practical issues that potential users may encounter on existing bridges. The primary problem is digitizing existing bridges that have not yet adopted BrIM. The universal applicability of BrIM should be carefully considered from the perspective of national maintenance authorities managing thousands of bridges, because modeling based on commercial software is expected to be time-consuming and costly. Therefore, in this study, information and functional requirements were derived from interviews with stakeholders, including bridge owners, managers, and site inspectors. Based on this understanding, a data-driven modeling approach using basic bridge information was implemented, and an inventory code system was integrated to efficiently manage and utilize the data. Moreover, mapping and deep learning-based vectorization were considered for managing inspection information, and features for bridge assessment, dashboards, and reporting were incorporated to support decision-making. The developed BrIM demonstrated the potential for enhancing maintenance efficiency through a case study. Particularly, significant improvements were observed in mandatory documentation tasks, along with their investigation and analysis, as required by regulations. Additionally, efficient modeling and data management were achieved for the existing bridge.

Claudia Pau, Mihaela Martin, Răzvan Văduva

Good governance and sustainable development are key to consolidating a sustainable and efficient future. Based on the challenges they have faced over time, both the European Union and the UN have implemented the 2030 Agenda for Sustainable Development, hoping for a full integration of the proposed objectives into public policy. This study has a theoretical approach focusing on the gradual historical evolution of these two concepts underlying once more their importance for the new social reality.

Tariq T.Y.A., Iman A.-F., Essia R.A. et al.

Earlier research on corporate governance, which includes board size as one of its major components, and business performance has expanded substantially in the last three decades. In this research, we analyze several studies that have been published between 2013 and 2021 to give a clear picture of the relationship. Furthermore, a brief review of the previous studies that have been done in several countries are introduced. We indicated that the number of publications that meet our search parameters had risen gradually over time, peaking in 2013 and other years. We identified two key types called (1) board size and firm performance as well as (2) CEO duality. We see a shift away from theoretical ideas, for instance, ‘responsibility,’ ‘society,’ and ‘morals,’ and toward increasingly concrete and workable phrases like ‘CEO duality’ and board size. Our research reveals that the study on firm performance and corporate governance is shifting from a theoretical strategy towards a more tactical and operational strategy.

Milon Chowdhury, Md. Shaha Nur Kabir, Hyeon-Tae Kim et al.

The system-specific selection of aeroponic nutrient system components, specifically pumps, pipes, and tanks, is very important to improve system efficiency and minimize costs, as these components vary for different systems with different crop water requirements and design specifications. In this study, methods were suggested for determining the most suitable sizes of pumps, pipes, and tanks based on the plant water consumption and irrigation interval targeted to improve the usual procedures to design an aeroponic nutrient management system, and applied to a case. Factors affecting the size calculation are discussed, and calculation methods were suggested based on basic hydraulic principles. A recycle-type aeroponic nutrient management system, cultivating 500 plants in 21 plant beds, was considered for a case study. Application of the size calculation methods in the case study showed that an irrigation pump with a 37 Lmin–1 flow rate at 900 kPa capacity and nutrient pumps with a 5 Lmin–1 flow rate at 40 kPa capacity with 19-mmdiameter pipes were required to deliver the mixed nutrients and supply stock solutions into the mixing tank, along with nutrient mixing, stock nutrients, and distilled water tanks of 750, 40, and 685 L, respectively. Calculation was demonstrated to show the variations in the sizing of the pumps, pipes, and tanks by number of plants. Validation tests were performed for the selected irrigation pump capacity, and the results showed that the Nash-Sutcliffe efficiency coefficient (NSE), coefficient of determination (R2), and root-mean-square error (RMSE) values were 0.410, 0.98, 0.109 Lmin–1 and 0.775, 0.99, 34.91 kPa for flow rate and pressure, respectively. The case study also showed that these sizing procedures increased the plant bed coverage efficiency of the irrigation pump by 33%, while increasing the nutrient mixing tank size by 133%. This study would provide useful information on the efficient sizing of pumps, pipes, and tanks for minimizing costs and maximizing crop production in aeroponic nutrient management systems.

Loga-Księska Wiktoria, Sordyl Justyna, Ryguła Artur

Increasing the number of vehicles on the road network and the growing popularity of sustainable development of urban areas have resulted in the need for implementing efficient and cost-effective traffic measurement methods. From the perspective of traffic management, up-to-date information about vehicle density and access to historical data are the key components of traffic variability analyses. Rapid technological development based on Intelligent Transport Systems (ITS) has popularised the wireless sensor networks (WSN) application. The solution enables continuous monitoring of selected area using multiple wireless and low-cost sensors connected within a network. Those systems are dynamically evolving tools for solving an effective traffic management issues in city centres and urban environments. In the study, authors have performed a traffic variability and its dynamics analysis in a selected area using a multi-sensor network for traffic volume monitoring. The article presents the results of research conducted between years 2015 - 2018 throughout the city of Bielsko-Biala with the support of OnDynamic multimodal system. Within the context of the analyses, basic traffic parameters have been determined and variability trends have been identified on selected road sections. Long-term research indicated the minor variation in a number of vehicle detections and relatively stable traffic volume in the city centre during the analysis period.

Patrick Biggar, Dennis Hidde, Markus Ketteler

Background/Aims: In 2015, approximately 70,000 patients with end-stage renal disease were treated chronically with dialysis in Germany. However, there is only sparse information regarding subjective appreciation of the different aspects of extracorporeal renal replacement therapies. This study was performed to gain insight into the needs and appreciation of services in dialysis centers in Germany including the views not only of the patients but also of the caregivers, physicians, and nurses. Methods: A cross-sectional written voluntary questionnaire survey based on the international RAND Kidney Disease Quality of Life Short Form (version 1.3) comprising 510 adult dialysis patients, 274 caregivers, 29 physicians, and 60 nurses in 30 dialysis centers across Germany. Results: Although patients were mostly satisfied with present treatment options, room for improvement exists. Patients were less critical of services than doctors and nurses. Factors such as trustworthy contact with staff at the centers as well as information exchange with other patients and among caregivers play a significant role in the patients’ perception of a high-quality dialysis treatment facility. Therefore, continued cost saving, in particular regarding personnel, may subjectively counteract the objective technical improvements of dialysis. Conclusions: High-quality technical standards are essential for successful dialysis therapy; however, additionally, we recommend an array of communicative and social tools employed by all stakeholders to convey and exchange information and also support subjective well-being. This survey represents one of the largest evaluations to date. The data are also of potential international relevance for non-German health management systems.

Jochen Nürk

A model for managing strategic alignment and dynamic capabilities (DC) of Supply Chain Management (SCM) information systems (IS) has been developed and applied to a traditional German steel company and a highly innovative Austrian steel company. Different concepts of leading researchers have been combined to get a holistic and detailed view of IS capabilities' impact on strategic fit. The model enables companies to identify ideal levels to strategic fit needed from SC integration and its antecedents for predefining architectural artefacts as sources for dynamic capabilities. The study contributes to new insights into the IT productivity paradox, where possibilities from IS investments remain unused. Essential concepts for optimising SC performance by reducing SC complexity and increasing SC agility have been identified and integrated. The study highlights value enabler and Artificial Intelligence (AI) methods of digital SC models and how the model's ontology can be used to increase alignment autonomy. Finally, the approach supports organisational learning and development of cognitive profiles through collective assimilation and sensemaking effects.

David J. Harris, Shawn D. Taylor, Ethan P. White

Biodiversity forecasts are important for conservation, management, and evaluating how well current models characterize natural systems. While the number of forecasts for biodiversity is increasing, there is little information available on how well these forecasts work. Most biodiversity forecasts are not evaluated to determine how well they predict future diversity, fail to account for uncertainty, and do not use time-series data that captures the actual dynamics being studied. We addressed these limitations by using best practices to explore our ability to forecast the species richness of breeding birds in North America. We used hindcasting to evaluate six different modeling approaches for predicting richness. Hindcasts for each method were evaluated annually for a decade at 1,237 sites distributed throughout the continental United States. All models explained more than 50% of the variance in richness, but none of them consistently outperformed a baseline model that predicted constant richness at each site. The best practices implemented in this study directly influenced the forecasts and evaluations. Stacked species distribution models and “naive” forecasts produced poor estimates of uncertainty and accounting for this resulted in these models dropping in the relative performance compared to other models. Accounting for observer effects improved model performance overall, but also changed the rank ordering of models because it did not improve the accuracy of the “naive” model. Considering the forecast horizon revealed that the prediction accuracy decreased across all models as the time horizon of the forecast increased. To facilitate the rapid improvement of biodiversity forecasts, we emphasize the value of specific best practices in making forecasts and evaluating forecasting methods.

Mohamad Sorani, Sogand Tourani, Hamid Reza Khankeh et al.

Introduction: Prehospital Emergency Medical Care (EMC) is a critical service in disaster management. The aim of this study was to explore the challenges of prehospital Emergency Medical Services (EMS) during disaster response in Iran. Methods: A qualitative study was conducted from April 2015 to March 2017. Data were collected through in-depth, semi-structured interviews with 23 experienced individuals in the field of disaster that were selected using purposeful sampling. Data were analyzed using content analysis approach. Results: Fifteen sub-themes and the following six themes emerged in the analysis: challenges related to people, challenges related to infrastructure, challenges related to information management systems, challenges related to staff, challenges related to managerial issues and challenges related to medical care. Conclusions: Iran’s prehospital EMS has been chaotic in past disasters. Improvement of this process needs infrastructure reform, planning, staff training and public education.Â

Trésor Kanyiki

Lucas T. Khoza, Agnieta B. Pretorius

Background: ‘Knowledge is power’ and software developing organisations are dependent on knowledge to achieve and maintain a competitive advantage. Subsequently, knowledge sharing is a key factor for modern software developing organisations to succeed in today’s competitive environment. For software developing organisations to reach their goals and objectives, knowledge sharing – and in particular the sharing of useful knowledge – needs to be targeted. To promote knowledge sharing, factors influencing knowledge sharing need to be identified and understood. Objective: This study seeks to identify factors that negatively influence knowledge sharing in software development in the developing country context. Method: Expert sampling as a subcategory of purposive sampling was employed to extract information, views and opinions from experts in the field of information and communication technology, more specifically from those who are involved in software development projects. Four Johannesburg-based software developing organisations listed on the Johannesburg Stock Exchange (JSE), South Africa, participated in this research study. Quantitative data were collected using an online questionnaire with closed-ended questions. Results: Findings of this research reveal that job security, motivation, time constraints, physiological factors, communication, resistance to change and rewards are core factors negatively influencing knowledge sharing in software developing organisations. Conclusions: Improved understanding of factors negatively influencing knowledge sharing is expected to assist software developing organisations in closing the gap for software development projects failing to meet the triple constraint of time, cost and scope.

K. Ewusi-Mensah

K. Clarke

Yu. Tryus, I. Stetsenko, I. Herasymenko et al.

We consider conceptual approaches to creation of information systems, learning management school, which uses modern methods of decision-making and simulational modeling, web-technologies. The main criteria for the selection of development tools of the system are: openness, free of charge, easy to use and independence from system software and hardware. The chosen technology and the system itself satisfies such requirements as: focus on national and international standards in the field of higher education, adherence to service-oriented architecture, ensuring stable operation with a large number of users, support for a clear division of user rights to obtain and change information resources, software modularity the final product and its ability to integrate into the corporate information system of the university