Hasil untuk "Management information systems"

B. Dervin

Binbin Yong, Jun Shen, Xin Liu et al.

Abstract Immunization is an indispensable mechanism for preventing infectious diseases in modern society, and vaccine safety is closely related to public health and national security. However, issues such as vaccine expiration and vaccine record fraud are still widespread in vaccine supply chains. Therefore, an effective management system for the supervision of vaccine supply chains is urgently required. As the next generation of core technology after the Internet, blockchain is designed to build trust mechanisms that can change current information management methods. Meanwhile, the development of machine learning technologies provides additional ways to analyze the data in information management systems. The main objective of this study is to develop a “vaccine blockchain” system based on blockchain and machine learning technologies. This vaccine blockchain system is designed to support vaccine traceability and smart contract functions, and can be used to address the problems of vaccine expiration and vaccine record fraud. Additionally, the use of machine learning models can provide valuable recommendations to immunization practitioners and recipients, allowing them to choose better immunization methods and vaccines.

Bing Liang, Guoqing Shi, Yuexi Wu et al.

Global climate change-induced sea level rise has emerged as a critical environmental challenge for coastal cities in the 21st century. Shanghai, China's economic, financial, and shipping hub, faces significantly amplified inundation risks in its coastal areas due to the compounding effects of sea level rise, land subsidence, and storm surges. This study constructs a multi-case simulation framework using the sixth assessment report of intergovernmental panel on climate change sea level projection data, land subsidence monitoring records, and historical storm surge data to evaluate the impacts of three cases on future inundation risks: sea level rise alone (case1), sea level rise combined with land subsidence (case 2), and sea level rise coupled with land subsidence and storm surges (case 3). Leveraging Autoregressive Integrated Moving Average model time-series modeling, Geographic Information System spatial analysis, and numerical simulations, the study predicts relative sea level rise and inundation extents for 2050, 2070, and 2100. Results indicate that Shanghai's relative sea level rise rate far exceeds the global average, with land subsidence and storm surges synergistically amplifying disaster risks in low-lying coastal zones. Under case 1, the projected inundation area reaches 361.32 km2 by 2100. Case 2 increases this area to 460.97 km2, while case 3 shows a dramatic escalation to 1,331.91 km2 by 2100-a surge of 870.94 km2 compared to case 2-highlighting the dominant role of storm surges in extreme weather events. Spatial analysis identifies Chongming District, Pudong New Area, and Fengxian District as high-risk zones, with Chongming Island being the most severely affected (54.5% inundation by 2100). This study elucidates the compound impact mechanisms of sea level rise, land subsidence, and storm surges in Shanghai, providing a scientific foundation for coastal disaster mitigation and adaptive urban management. Recommendations include enhancing coastal flood defenses, optimizing land-use planning, improving extreme weather early-warning systems, and fostering international collaboration and technological innovation to bolster urban resilience against climate risks.

A. Huizing, Patricia Carlson

Kun Sang, Luoning Xiang, Guiye Lin

Against the background of environmental change, this study investigates the relationship between landscape changes and perceptions along the historical railway using a combination of Historical Geographic Information Systems (HGIS) and Fuzzy-set Qualitative Comparative Analysis (fsQCA). After quantifying the changes by GIS, the research aims to understand how different types of landscape changes affect physical, psychological, and cultural perceptions among locals. By integrating historical maps with remote sensing data and questionnaire, the study provides a comprehensive analysis of landscape evolution over time. The findings reveal that cropland and urban areas both showed significant increases along the railway; forest and water body both decreased over 70 years. The presence of forest change led to significant cultural perceptions and cropland change influenced the psychological perceptions of landscape. This research contributes to the understanding of the interplay between landscape change and human perception, offering valuable insights for sustainable landscape management and heritage conservation.

Amir Amir, Moch. Syafi’i

This study aims to analyze the implementation of public service management at Banyuputih Community Health Center (Puskesmas). The main focus of the research includes planning, organizing, implementation, and supervision processes in the delivery of healthcare services. A descriptive qualitative approach was employed to obtain an in-depth understanding through observation, interviews, and documentation. The results indicate that public service management has been carried out in a relatively systematic manner, although several obstacles remain, such as limited medical personnel, inadequate facilities, and suboptimal evaluation systems. Improvement efforts are continuously being made through enhanced internal coordination and the refinement of service information systems. These findings highlight the importance of strengthening managerial functions in public services, particularly in the health sector, to improve community satisfaction and institutional performance.

Alexander Frummet, Emanuel Slany, Jonas Amling et al.

Conversational agents such as Microsoft Copilot and Google Gemini assist users with complex search tasks but often generate misleading or fabricated references. This undermines trust, particularly in high-stakes domains such as medicine and finance. Explainable information retrieval (XIR) aims to address this by making search results more transparent and interpretable. While most XIR research is domain-agnostic, this paper focuses on auditing -- a critical yet underexplored area. We argue that XIR systems can support auditors in completing their complex task. We outline key challenges and future research directions to advance XIR in this domain.

Patrick Prieur, Aline Belloni

With the evolution of process approaches within organizations, the increasing importance of quality management systems (like ISO 9001) and the recent introduction of ISO 30401 for knowledge management, we examine how these different elements converge within the framework of an Integrated Management System. The article specifically demonstrates how an ISO30401-compliant knowledge management system can be implemented by deploying the mechanisms of the SECI model through the steps of the PDCA cycle as applied in the processes of the integrated management system.

Gueorgui Petkov

Risk management strives to reach the standards of theoretical systematicity and empirical precision achieved in natural science models. To this end, a set of risk-informed and performance-based standards was developed in the form of statistically validated measures. The set enables the systematic extraction by deterministic and probabilistic analysis of potentially objective risk assessments and well-defined decisions. However, much of the data and models are subjectively influenced by the uncertainty of the context in which they are related and derived. Current risk analysis contains a large amount of risk-related information, but without the context of the models, its results lack sufficient predictive and explanatory power to be a solid basis for decisions. Therefore, to model the entire site of a multi-unit nuclear power plant as an integrated system connecting facility and activity, it is necessary to consider not only the technological conditions, but also the entire site context, including human, organizational, and environmental factors. An interface tool for dynamic deterministic-probabilistic safety analysis should be used to contextualize and complement existing risk indicators, but not to replace them. This article presents the possibilities of risk contextualization for nuclear systems through the symptom-based context quantification procedure of the Performance Evaluation Teamwork method.

Niklas Braun, Markus Steimle, Martin Törngren et al.

As simulation is increasingly used in scenario-based approaches to test Automated Driving Systems, the credibility of simulation results is a major concern. Arguably, credibility depends on the validity of the simulation setup and simulation models. When selecting appropriate simulation models, a trade-off must be made between validity, often connected to the model's fidelity, and cost of computation. However, due to the large number of test cases, expert-based methods to create sufficiently valid simulation setups seem infeasible. We propose using design contracts in order to semi-automatically compose simulation setups for given test cases from simulation models and to derive requirements for the simulation models, supporting separation of concerns between simulation model developers and users. Simulation model contracts represent their validity domains by capturing a validity guarantee and the associated operating conditions in an assumption. We then require the composition of the simulation model contracts to refine a test case contract. The latter contract captures the operating conditions of the test case in its assumption and validity requirements in its guarantee. Based on this idea, we present a framework that supports the compositional configuration of simulation setups based on the contracts and a method to derive runtime monitors for these simulation setups.

Saumya Kothari, Harsh Shah, Utkarsh Prajapati et al.

Mid-cap companies, generally valued between \$2 billion and \$10 billion, provide investors with a well-rounded opportunity between the fluctuation of small-cap stocks and the stability of large-cap stocks. This research builds upon the long-short equity approach (e.g., Michaud, 2018; Dimitriu, Alexander, 2002) customized for mid-cap equities, providing steady risk-adjusted returns yielding a significant Sharpe ratio of 2.132 in test data. Using data from 2013 to 2023, obtained from WRDS and following point-in-time (PIT) compliance, the approach guarantees clarity and reproducibility. Elements of essential financial indicators, such as profitability, valuation, and liquidity, were designed to improve portfolio optimization. Testing historical data across various markets conditions illustrates the stability and resilience of the tactic. This study highlights mid-cap stocks as an attractive investment route, overlooked by most analysts, which combine transparency with superior performance in managing portfolios.

Weronika Łajewska, Damiano Spina, Johanne Trippas et al.

The increasing reliance on digital information necessitates advancements in conversational search systems, particularly in terms of information transparency. While prior research in conversational information-seeking has concentrated on improving retrieval techniques, the challenge remains in generating responses useful from a user perspective. This study explores different methods of explaining the responses, hypothesizing that transparency about the source of the information, system confidence, and limitations can enhance users' ability to objectively assess the response. By exploring transparency across explanation type, quality, and presentation mode, this research aims to bridge the gap between system-generated responses and responses verifiable by the user. We design a user study to answer questions concerning the impact of (1) the quality of explanations enhancing the response on its usefulness and (2) ways of presenting explanations to users. The analysis of the collected data reveals lower user ratings for noisy explanations, although these scores seem insensitive to the quality of the response. Inconclusive results on the explanations presentation format suggest that it may not be a critical factor in this setting.

A. Weijters, Wil M.P. van der Aalst

Contemporary workflow management systems are driven by explicit process models, i.e., a completely specified workflow design is required in order to enact a given workflow process. Creating a workflow design is a complicated time-consuming process and typically, there are discrepancies between the actual workflow processes and the processes as perceived by the management. Therefore, we propose a technique for rediscovering workflow models. This technique uses workflow logs to discover the workflow process as it is actually being executed. The workflow log contains information about events taking place. We assume that these events are totally ordered and each event refers to one task being executed for a single case. This information can easily be extracted from transactional information systems (e.g., Enterprise Resource Planning systems such as SAP and Baan). The rediscovering technique proposed in this paper can deal with noise and can also be used to validate workflow processes by uncovering and measuring the discrepancies between prescriptive models and actual process executions.

Kuan-Tse Huang, Yang W. Lee, Richard Y. Wang

N. Whitsed

Rebecca J. McLain, Robert H. G. Lee

Sardjono Wahyu, Cholidin Achmad, Johan

As the industrial players began starting to face the reality of the fourth industrial revolution, telecommunication industry is one of those significant business sectors required to adapt and remain to survive in such challenging situations, especially by the threats of their competitors. Artificial Intelligence (AI) plays an essential role in today’s telecommunication industry. It can make predictions about decisions, examine big data points to offer solutions, and interact with customers in real-time. Many telco firms and organizations use Customer Relationship Management (CRM) to achieve effectiveness in a company’s productivity and efficiency in the operational activities. This assessment revealed that an AI-driven CRM system could give a better solution for the telecommunication industry to manage relationships with externals, boost marketing and sales programs, prospect consumer data information, and record operational cases, all in one centralized location.

Rúsbel Domínguez-Domínguez, Omar A. Flores-Laguna, Jair del Valle-López

The purpose of this research was to know the degree of administrative knowledge, the degree of training of human resources, the degree of commitment of administrators and the degree of effectiveness of the administration for information security risk based on ISO/IEC 27001.The population consisted of 81 subjects (66 administrators and 15 ITD personnel). Those evaluated were employers of the administrative office of the university and also staff of the Information Technology Department (ITD). To make the comparisons, three groups of managers were formed according to classifications of administrative staff, the classification was as follows: (a) first-line manager, (b) middle management and (c) top management. About the results, it can be corroborated that administrative staff with a lower rank have more problems in making the best decisions in relation to the implementation of an ISMS, it should be noted that the first-line manager is the one who has more contact with the students and is the one who is less involved in the implementation of an ISMS. It can also be inferred that the institutionś planners are not fully trained in the institutionś information security efforts. This in turn prevents the generation of proposals for initiatives to implement an ISMS. With this shortcoming, it is possible that security breaches could be generated.

Alexander Benlian, William J. Kettinger, A. Sunyaev et al.

ALEXANDER BENLIAN (benlian@ise.tu-darmstadt.de; corresponding author) is a Professor of Management Information Systems (MIS) at Technische Universität Darmstadt, Germany, where he serves as Dean of the Department of Business, Economics, and Law. His former academic position was Ludwig-Maximilians-University of Munich, where he received a Ph.D. He has also served as a senior consultant with McKinsey & Company. Dr. Benlian’s research interests include the transformative value of cloud computing, online platforms, digital transformation, and digital business models, with over 150 academic publications in these areas. His work has appeared in Journal of Management Information Systems, Journal of the AIS, Journal of Strategic Information Systems, MIS Quarterly Executive, and others. He is Associate Editor of the European Journal of Information Systems and International Journal of Electronic Commerce and serves the Editorial Review Board of the Journal of Service Research.

Siti Saadah, Kaenova Mahendra Auditama, Ananda Affan Fattahila et al.

COVID-19 was classified as a pandemic in March 2020, and then in July 2021, this virus had its variance that spreads all over the world including Indonesia. The probability of the detrimental of its effect cannot be avoided, because this virus has a huge transmission risk during daily activity. To prevent suffering from COVID-19, people certainly need to be vaccinated. In responding to its vaccine, the citizen of Indonesia become expressive, so they try to express opinions, for example by uploading text on Twitter. Those expressions can be learned using deep learning frameworks which are BERT, CNN-LSTM, and IndoBERTweet to get knowledge about negative speech categories such as anxiety, panic, and emotion, or positive speech such as vaccines whether worked well. By then, these three methods accomplish in carrying out the prediction of sentiments about vaccination using dataset tweets on Twitter from January-2021 to March-2022, for instance using IndoBERT succeeds to classify sentiments as positive sentiment at around 80%, and then IndoBERTweet at 68%, in addition using CNN-LSTM reach 53% with the total of using 2020 dataset from Twitter. According to these results, a lesson learned for continued improvement for Indonesia's Government or authorities can be acquired in ending the COVID-19 pandemic.