Hasil untuk "Management information systems"

Joseph F. Hair, Carole L. Hollingsworth, A. Randolph et al.

I. Theory

William H. DeLone, E. McLean

A. Erica, Lumi Gantari, Olivia Qurotulain et al.

This study delves into integrating data analytics applications within Management Information Systems (MIS), exploring their impact on decision-making processes in organizational settings. The discussion synthesizes qualitative and quantitative methodologies, presenting insights from scholarly literature, surveys, and interviews. Scholarly discourse highlights the transformative potential of data analytics tools in facilitating informed decision-making, aligning with practical applications showcased in empirical studies. However, inherent challenges surface, primarily concerning data quality, as revealed by 62\% of respondents, underscoring the need for organizations to address these obstacles. Despite challenges, substantial adoption rates of data analytics tools (78\%) affirm their growing recognition in decision-making within diverse industries. Reported enhancements in operational efficiency (35\%) and competitive advantage (22\%) among organizations leveraging data analytics validate their efficacy in driving organizational performance metrics within MIS. Further research should address ethical implications, longitudinal analyses of data analytics efficacy, and interdisciplinary collaborations exploring the nexus between data analytics and managerial decision-making. This study is a foundational step, providing empirical evidence and future research trajectories essential for organizations aiming to optimize decision-making through data analytics applications within Management Information Systems.

Bhima Bhima, Achani Rahmania Az Zahra, Tio Nurtino

This research delves into AI's role in enhancing Management Information Systems for organizational efficiency. It employs cross-sector case studies to showcase AI's potential in automating tasks, offering predictive insights from historical data, and bolstering decision-making. While AI promises substantial benefits, it also poses technical and ethical challenges during implementation. AI integration emerges as a game-changer, liberating organizations from mundane tasks through automation. Predictive analytics empowers firms to foresee trends, fostering a competitive edge in decision-making. Yet, obstacles include algorithm compatibility with existing systems and the demand for heightened technical proficiency. Ethical considerations loom large, demanding robust privacy and fairness guidelines in AI data usage. This research underscores the importance of employee AI training and multidisciplinary teams for tackling technical hurdles. Ethical principles should permeate AI development and utilization. The study recommends a three-fold strategy: First, prioritize employee AI training for seamless adoption. Second, establish cross-disciplinary teams to navigate technical complexities. Third, embed ethics in every AI facet to maintain trust. In conclusion, a holistic approach allows organizations to seamlessly integrate AI into Management Information Systems, yielding operational efficiencies, superior decision-making, and a competitive edge in a dynamic business landscape.

Chao Wang, Jun-Feng Hao, He Huang et al.

Traffic flow forecasting is a critical and essential technology in the field of Intelligent Transportation Systems (ITS), as it plays a pivotal role in optimizing traffic management, improving road safety, and enhancing the overall efficiency of transportation networks. However, current research neglects the relationships between the local and global traffic flow data. Additionally, the predefined static graph structure fails to adequately capture the dynamic spatial features of traffic flow. To address the these challenges, this paper proposes a Dual-Channel Dynamic Gated Spatio-Temporal graph network (DC-DGST) for traffic flow prediction. We consider hourly slices as the local feature and daily slices to be the global feature of traffic flow. The DC-DGST framework employs a dual-channel structure to capture spatiotemporal dependencies between global and local features. It transforms the predefined static graph into a dynamic graph, enabling the establishment of connections between input data and historical information. Furthermore, we design gated spatio-temporal blocks based on residual structures within the spatio-temporal module. Specifically, we utilize Graph Gated Neural Networks (GGNNs) to learn and integrate both static and dynamic graphs, while Transformer encoders are used to capture long-range dependencies in the temporal sequence. We conducted a series of experiments on four publicly available benchmark datasets: PEMS03, PEMS04, PEMS07, and PEMS08. The results demonstrate that our model significantly outperforms baseline models. Moreover, the dual-channel structure effectively captures the correlation between local and global traffic flow features, while the dynamic graph enhances the model’s overall performance.

Jacopo Armini, Fabio Gianni, Stefano Niccolai

Georeferenced Access Points as a Strategic Node in the Evolution of Territorial Information Systems - This paper explores the strategic role of georeferenced access points and civic numbering as foundational components of advanced Territorial Information Systems (SIT) within Italian public administrations. The quality and consistency of georeferenced street and building numbers represent a fundamental component of territorial data infrastructures, enabling reliable integration between cadastral datasets, administrative services and emergency response systems. Drawing from the experience of LdP Progetti GIS — involving more than 130 municipalities across five regions — the article demonstrates how the integration of Accesses, Buildings and Street Toponyms enables an interoperable Web-GIS ecosystem supporting digital services, data governance and operational decision-making. Real case studies from the municipalities of Siena, Arezzo, Empoli and Pistoia illustrate concrete applications such as emergency management, fiscal intelligence (TARI compliance), housing planning and economic activity monitoring. The results highlight significant improvements in administrative efficiency, transparency and open-data availability, positioning geospatial infrastructures as a key enabler of digital transformation in the Public Sector.

Serhiy O. Semerikov, Pavlo P. Nechypurenko, Tetiana A. Vakaliuk et al.

Abstract The increasing sophistication of Learning Management Systems (LMS) has generated vast amounts of educational data with untapped potential for enhancing teaching and learning. While previous research has examined relationships between LMS components and overall student performance, less attention has been paid to how these components influence specific grade distributions. This study employs multivariate analysis techniques to investigate how Moodle components relate to distinct grade categories (A-F) across 985 courses at a Ukrainian pedagogical university. Using multiple regression models, canonical correlation analysis, and cluster analysis, we identify significant relationships between specific Moodle components and grade outcomes. Information components (particularly teacher presence) strongly predict excellence, while Activity x Communication interactions support satisfactory performance. Resource diversity combined with structured activities correlates with reduced failure rates. We further identify four distinct course design clusters with characteristic grade distribution patterns. The findings demonstrate how learning analytics can move beyond descriptive insights toward prescriptive guidance. This nuanced understanding of grade distribution patterns provides practical guidance for tailoring course design to diverse pedagogical objectives and student needs, thus contributing to the emerging field of personalized digital learning environments.

Ayda Mussa Yousif Abdulrahman, Rafiduraida binti Abdul Rahman

This research aims to investigate the current operational status of the Ajman Police, focusing on identifying elements and issues that affect operational excellence. Using change management models, including Kotter's 8 Step Model and the ADKAR Model, the paper critically examines the hierarchical structure of the Ajman Police, its specialist groups, and their performance indicators. The problem statement highlights the negative impact of traditional and rigid organizational structures on innovation, responsiveness, and the limitations of implementing effective public safety measures, prevention, and community policing. The research design adopted is a qualitative methodology, and a sample of senior police officers was interviewed to record their views on the issues of operation and preparedness to change. In conducting the study, Semi-structured interviews were conducted with 10 participants. Results indicate that the Ajman Police has already ventured into technological advancements and civil policing. However, there are still gaps in continuous development, innovation, and the implementation of modern change management practices. The research proposes a culturally, operationally, and technologically oriented framework for change management, specifically tailored to the context of the Ajman Police. The study makes a significant research contribution to both the practice and theory fields by providing a guideline for a change management roadmap for the Ajman Police and other similar agencies, ensuring operational excellence in fast-changing environments.

Xiahua Wei, Naveen Kumar, Han Zhang

Generative AI technologies, particularly Large Language Models (LLMs), have transformed information management systems but introduced substantial biases that can compromise their effectiveness in informing business decision-making. This challenge presents information management scholars with a unique opportunity to advance the field by identifying and addressing these biases across extensive applications of LLMs. Building on the discussion on bias sources and current methods for detecting and mitigating bias, this paper seeks to identify gaps and opportunities for future research. By incorporating ethical considerations, policy implications, and sociotechnical perspectives, we focus on developing a framework that covers major stakeholders of Generative AI systems, proposing key research questions, and inspiring discussion. Our goal is to provide actionable pathways for researchers to address bias in LLM applications, thereby advancing research in information management that ultimately informs business practices. Our forward-looking framework and research agenda advocate interdisciplinary approaches, innovative methods, dynamic perspectives, and rigorous evaluation to ensure fairness and transparency in Generative AI-driven information systems. We expect this study to serve as a call to action for information management scholars to tackle this critical issue, guiding the improvement of fairness and effectiveness in LLM-based systems for business practice.

Sandra Coello Suarez, V. Sanchez Padilla, Ronald Ponguillo-Intriago et al.

Parameter monitoring and control systems are crucial in the industry as they enable automation processes that improve productivity and resource optimization. These improvements also help to manage environmental factors and the complex interactions between multiple inputs and outputs required for production management. This paper proposes an automation system for broiler management based on a simulation scenario that involves sensor networks and embedded systems. The aim is to create a transmission network for monitoring and controlling broiler temperature and feeding using the Internet of Things (IoT), complemented by a dashboard and a cloud-based service database to track improvements in broiler management. We look forward this work will serve as a guide for stakeholders and entrepreneurs in the animal production industry, fostering sustainable development through simple and cost-effective automation solutions. The goal is for them to scale and integrate these recommendations into their existing operations, leading to more efficient decision-making at the management level.

Kristina Spasić, Bojana Novićević Čečević, Ljilja Antić

The new industrial era has brought new opportunities and chances for the entire business development. Smart machines, artificial intelligence, cloud computing, the Internet of Things, big data are taking over many jobs and roles, thus leaving room for the development of new skills and abilities. The rapid technological development in terms of automation and digitization has made machines replace human work. In this sense, it is a matter of time when technology will replace traditional accountants. (Management) accountants who want to adapt and survive in the digital world have to improve their offer and change the focus from data calculation to interpretation of results and business management. Thus, by applying new digital information technology tools, management accounting can provide quality information for determining the costs of products and services, performance measurement, planning and control, strategic and operational decision-making and the like. The general objective of this paper is to review the potential impact of digital information technologies on the usefulness of cost accounting systems and organizational performance in healthcare institutions in the Republic of Serbia with the help of statistical analysis of the relationship between the selected variables. The results of the analysis show that digital technologies have a great impact on the usefulness of the cost accounting system. Also, the largest number of respondents pointed out that improved IT systems have a positive effect on increasing organizational performance.

A. Yu. Mikhaylov

The article presents an in-depth analysis of the formation and development of the capital market (stocks and bonds segment) in China. The factors determining the valuation of shares that are in circulation are highlighted. While the first factor identifies an assessment based on the company’s financial statements, the second factor considers current market conditions and investor sentiment. Examining historical data, it is interesting to note that from 2000 to 2006, the total market capitalization of stocks remained stable and amounted to a substantial 4 trillion yuan. However, in 2007 There was a significant shift when the market capitalization grew significantly and reached as much as 30 trillion yuan. This sudden growth can be explained by various reasons, such as increased investor confidence, favorable economic conditions and the introduction of progressive financial regulation. In addition, it is important to note that in the same year, the Shanghai Composite index (a key indicator of the Chinese stock market) reached an unprecedented value of 6,123.04 points. This indicator demonstrated the stability and potential of the Chinese capital market, and attracted both domestic and international investors. Thus, the analysis presented in the article reveals the intricacies of the Chinese capital market and the mechanisms of its assessment. This analysis establishes the importance of both book value and market value in determining the valuation of outstanding shares. In addition, historical trends have highlighted the resilience and vulnerability of the market to external shocks, as evidenced by significant fluctuations in market capitalization. In general, this study helps to understand the Chinese capital market and its evolution over time.

Jeanina-Biliana Ciurea , Venera-Cristina Manciu

Change management is a complex process by which organisations adapt to new market conditions, technologies, regulations or consumer needs. In the context of trade SMEs, changes can have a significant impact on long-term competitiveness and sustainability. This paper aims to analyse the management of change in trade SMEs, carrying out a comparative study between retail and traditional trade.

Muhammad Rofiqul Islam, Abdullah Al Mehdi

This study investigates the impact of Hofstede's cultural dimensions on abnormal core earnings management in multiple national cultural contexts. We employ an Ordinary Least Squares (OLS) regression model with abnormal core earnings as the dependent variable. The independent variables analyzed include Hofstede's dimensions: Power Distance Index (PDI), Individualism (IDV), Masculinity (MAS), and Uncertainty Avoidance Index (UAI). Our findings reveal that individualism is positively associated with abnormal core earnings, suggesting that cultures characterized by high individualism may encourage practices that inflate earnings due to the prominence of personal achievement and rewards. In contrast, masculinity negatively correlates with abnormal core earnings, indicating that the risk-taking attributes associated with masculine cultures may deter earnings management. Interestingly, uncertainty avoidance is positively linked to abnormal core earnings, supporting the notion that managers tend to engage more in earnings management to minimize fluctuations in financial reports in cultures with high uncertainty avoidance. The relationship between power distance and abnormal core earnings is found to be non-significant, indicating no substantial effect in this context. These findings contribute to the literature on cultural influences in financial reporting, providing valuable insights for policymakers and multinational firms concerning the cultural contexts within which financial decisions and reporting occur.

Kristina Dzeparoska, Jieyu Lin, Ali Tizghadam et al.

Automated management requires decomposing high-level user requests, such as intents, to an abstraction that the system can understand and execute. This is challenging because even a simple intent requires performing a number of ordered steps. And the task of identifying and adapting these steps (as conditions change) requires a decomposition approach that cannot be exactly pre-defined beforehand. To tackle these challenges and support automated intent decomposition and execution, we explore the few-shot capability of Large Language Models (LLMs). We propose a pipeline that progressively decomposes intents by generating the required actions using a policy-based abstraction. This allows us to automate the policy execution by creating a closed control loop for the intent deployment. To do so, we generate and map the policies to APIs and form application management loops that perform the necessary monitoring, analysis, planning and execution. We evaluate our proposal with a use-case to fulfill and assure an application service chain of virtual network functions. Using our approach, we can generalize and generate the necessary steps to realize intents, thereby enabling intent automation for application management.

Samayita Guha, Subodha Kumar

J. Martins, F. Branco, R. Gonçalves et al.

Abstract The continuous use of dynamic and disruptive ICT as energizing elements of the educational process is a reality of current days, where millennials are the centre of an education paradigm in which students are much more inclined to use technologies than enrolling in a traditional non-digital course. Considering education management information systems (EMIS) capacities to collect, analyse, process and publish information and data, it is easy to perceive their relevance to both education organizations and students. Nevertheless, and despite EMIS complexity and inherent possibilities, the existing literature does not provide for a detailed characterization on the impact these systems might have on students’ success. Thus, this research focuses on understanding the use of EMIS by students and the arising of net benefits; it introduces an EMIS success model which posits that to ensure net benefits for students, education institutions must safeguard that their education management information systems are of high quality, while at the same time students are maintained satisfied with the system and engage in continuous use. To assess the posed model, an empirical study has been performed, involving students from higher education institutions. Findings from the study allow us to perceive that, as information systems (IS) success models state, EMIS use and students’ satisfaction are predictors of net benefits. This same model also claims that the available information quality and EMIS inherent service quality are also strong determinants of both continuous EMIS use and student satisfaction.

Penny Hendriyati, Farida Agustin, U. Rahardja et al.

One of the most important things in universities is the development of information systems and management of integrated data, important because of the high needs and completeness of attributes in each component related to academic affairs in all universities. Primary data in academics are students and lecturers. Data management and governance are well taken care of in order to deliver information to be accurate, transparency, accountability and actual. Lecturers and students can apply the SDLC model to produce a system that will later improve or replace the old system, through the design and implementation of data management information systems. In the application of policies towards lecturers and students, in this information system will provide formulation and overview to the leadership.

Esteban Rodríguez Torres, Carlos Alberto Gómez Cano, Verenice Sánchez Castillo

Introduction: management information systems currently play a crucial role in optimizing, filtering, and transforming information, which is essential for making wise decisions in companies. Objective: to describe the importance of information systems in the organizational ecosystem of companies. Methods: a document review of articles in the Scopus database was conducted to examine the influence of management information systems on decision-making in the business sector. Results: after a meticulous selection process, a total of 20 documents were analyzed. These documents were segmented in Scopus publishers as follows: Springer (5), Taylor & Francis (5), Elsevier (5), and Wiley (5). A thematic synthesis process was employed, and the most relevant information was coded and described. Conclusions: the results show that management information systems constitute a fundamental link in making wise decisions in the business sector, since they exponentially facilitate data access and control, which are subsequently used and classified as less relevant, relevant, or highly relevant information. Additionally, these systems optimize real working time, leading to a considerable increase in efficiency and effectiveness factors in companies.