Information Management

Table of Contents

1. Frontmatter

2. Data-Driven Intelligent Decision-Making System and Optimization Design

   1. Frontmatter

   2. Empirical Analysis and Validation of Robotic Process Automation (RPA) Implementation Challenges

      Mutlaq B. Aldajani

      Abstract

      The purpose of this research is to identify and categorize challenges inherent in digital work initiatives, with a particular focus on robotic process automation (RPA). The study began with the development of a conceptual framework to emphasize significant themes and propositions concerning RPA implementation, based on a review of existing literature. The proposed framework underwent a rigorous validation process using qualitative data gathered through an in-depth case study analysis. Data collection methods included interviews with IT experts in RPA solutions, which provided insights into the challenges they encountered. The analysis identified five distinct themes: organizational, technological, human, process, and data. Notably, the framework differed from the feedback of one interviewee, who proposed a new theme focused on data challenges, including low availability of digital data, low data quality, and unstructured data formats. The study identified eighteen challenges categorized under the aforementioned themes, making it highly relevant to RPA theory and practice.

   3. Incorporate Provenance for Relevant Decision Making

      Belfrit Victor Batlajery, Trientje Marlein Tamtelahitu, Joanna Cristy Patty, Hennie Tuhuteru

      Abstract

      The relationship between events in the food supply chain can be modelled as a graph and can be used to perform some measurements (i.e. risk - a notion of a possible undesired outcome). However, performing such measurements without complete and relevant information increases uncertainty and leads to bad decisions. Meanwhile, provenance is a record of what actually occurs in a set of processes, including any aspect that contributes to those events. By integrating provenance, we gain benefits including increased relevance and better contextual decision-making. Capturing the provenance of something can be done with PROV, as a standard provenance language, and can also be expressed as a Provenance Graph (PG). Potentially, uncertainty will be reduced, allowing more reasonable and relevant decisions. In this work, we introduce the integration of provenance with uncertainty and risk in a set of processes to capture relevant and contextual information for better decision making.

   4. Development of a Decision Support Tool for Safety in Transit Assessment at Stations: A Case Study of Bangkok's Suburban Rail Stations

      Kanokporn Sripathomswat

      Abstract

      Safety is a critical factor influencing the preference and use of public transit, yet it remains one of the most challenging aspects to quantify. Ensuring safety at transit stations, particularly suburban train stations like those on Thailand's Dark Red Line, yields numerous benefits. These include enhanced accessibility to public transportation, better utilization of existing serviced land, increased transit ridership, and reduced vehicular traffic pollution in Bangkok. This research aims to develop criteria and a decision support tool to assist decision-makers in evaluating passenger safety at transit stations in the city. This research focuses on a pilot project involving transit stations along Thailand's Dark Red Line. The study begins by collecting data from all stations along the line and then identifying and determining key safety criteria. These criteria include proximity to bus stops, the number of crime-prone areas, passenger pick-up/drop-off points, CCTV coverage, and traffic accident statistics. Using input from decision-makers, these criteria were weighted and analyzed through the Fuzzy TOPSIS multi-criteria decision-making approach to evaluate stations’ performance. The final ranking was determined using the closeness coefficient from the ideal solution, which identified the station with the highest relative closeness score as the optimal candidate for developing an intermodal transportation hub. A decision support tool was then developed using Microsoft Excel. The findings of this pilot case study provide practical guidelines for station area development. Moreover, the results offer valuable insights that can be extended to other transit lines, improving intermodal connections and guiding the design of built environments that foster safer and more efficient transit systems.

   5. An Innovative Edge-Based Decision Support System from the SILVANUS Project

      Michal Sworzeniowski, Thuy Truong, Mustafa Al-Bado, Deirbhile Healy

      Abstract

      Frequent large-scale wildfires have detrimental effects on ecosystems, degrade air and water quality, harm biodiversity, and diminish natural aesthetics. An edge-based decision support system is essential for preventing and mitigating wildfire incidents. This paper introduces a novel solution for an edge-based wildfire decision support system, developed as part of the SILVANUS project, an EU Commission-funded initiative aimed at wildfire management. The solution exhibits the challenges and solutions for an environment that features cloud-edge deployment, multi-tenancy, and diverse data sources and consumption methods. This paper overviews the system components, context and user products. The evaluation shows that the proposed solution sped up the ingestion time for small-size files by around 20-fold and for large-size files by around 33-fold.

   6. Enhancing Decision-Making Through Business Intelligence: An EDAS Approach to Evaluating Distance from Average Solutions

      Vamsi Kavuri, Pallavi D R, Mahesh Kumar Mishra, C. Kalpana, M. Ramachandran

      Abstract

      This research explores how business intelligence (BI) influences decision-making, employing the Evaluation Based on Distance from Average Solution (EDAS) technique to analyse ten prominent BI tools. With the rapid expansion of data in the wake of Industry 4.0, selecting an optimal BI system has become a pivotal factor in maintaining a competitive edge. Although BI analytics is utilised by 97% of large enterprises, a well-defined assessment framework remains indispensable. By leveraging a multi-criteria decision-making (MCDM) methodology, this study scrutinises ten BI platforms–among them Tableau, Microsoft Power BI, Qlik Sense, Looker, SAP BusinessObjects, and Oracle Analytics Cloud–against six critical dimensions: user adoption, data processing, visual representation, and customer support. Results rank Oracle Analytics Cloud highest (0.86382), followed by SAP BusinessObjects (0.66845) and Looker (0.53517). Microsoft Power BI, despite 90% adoption and affordability, ranked ninth due to feature limitations, while Tableau placed sixth. The study highlights BI trade-offs–Power BI is cost-effective, Tableau excels in visualisation, and suitability depends on organisational needs.

   7. Index Redundancy Mitigation in Datasets Using Graphs and Shapley Values

      Ghurumuruhan Ganesan, Siddharth Chatterjee, Abhiram Lokanathan

      Abstract

      Often in data management and preprocessing for prediction, it may be necessary to reduce or undersample the size of a given dataset to a manageable size by removing redundancy. This is typically done to improve the overall performance in terms of accuracy. In this paper, we use graph and economics inspired methodologies to perform “smart” undersampling and obtain a “nice” set of data points that are as dissimilar as possible. We begin with a graph-theoretic model where vertices in the graph represent data point indices and demonstrate how stable vertex sets could be used to extract data subsets of given redundancy. We then invoke the concept of Shapley value allocation from economics together with nearest neighbour approach to obtain low redundancy data subsets of given size. We explain the theoretical motivations behind our methods and also briefly illustrate using real-life datasets from Kaggle.

3. Modern Integrated Information System Design and Intelligent Platform Construction Based on Microservice Architecture

   1. Frontmatter

   2. Formation of Requirements Traceability in the Process of Information Systems Design

      Grigory Tsiperman

      Abstract

      The traceability of requirements in the information system design process is considered an important property of the project, one of its quality characteristics. The point here is that traceability provides the processes of validation and verification of software systems, and that the system model based on requirements traceability reduces the system's dependence on developers and, in general, makes it as clear as possible. One of the challenges of the traceability process, dubbed ‘The grand challenge of traceability’ among traceability researchers, is its integration into the design process. In this paper, to achieve this goal, we propose the application of the Adaptive Clustering Method (ACM) of Information System developed by the author, which is based on the idea of a seamless system architecture that provides explicit interconnection of project artifacts of different levels of abstraction.

   3. Smart Sports User Experience: An Empirical Study from Alibaba, China

      Mingguang Liu, Enhuizi Wu, Jingna Wang

      Abstract

      The advent of the experience economy has led to a notable surge in user expectations regarding the quality of the experience they seek. This paper takes Alibaba Smart Ping Pong Champion on the Cloud Challenge as its case study. It begins by identifying user experience demand as its starting point and then employs a questionnaire survey method and an ASEB grid analysis model to conduct a comprehensive analysis of the design of the entire process and each link in Alibaba Smart Ping Pong Champion on the Cloud Challenge. It then proceeds to undertake a detailed examination of the status quo of the user experience on the site, which reveals the existence of four key issues. On this basis, this study puts forward improvement and development suggestions covering technology, design, service and business from the four levels of user value realisation, user emotional satisfaction, personalised service provision and user demand response. The aim is to explore new paths and perspectives to enhance the user experience of smart sports, and to provide theoretical and practical guidance for the development of smart sports around the world.

   4. Performance-Driven MarketCloud: Techniques for Achieving Peak Efficiency

      William P. Rey, Kieth Wilhelm Jan D. Rey

      Abstract

      This study focuses on optimizing MarketCloud, an e-commerce platform, to enhance its performance and user experience. By implementing a structured approach that included pre-optimization assessments, targeted optimization strategies, and post-optimization evaluations, significant improvements were achieved. Initial analysis identified key performance issues such as high client-side workloads and inefficient JavaScript. Optimization efforts involved refining client-side processes, addressing render-blocking resources, and employing a Content Delivery Network (C.D.N.). Post-optimization, MarketCloud’s performance rating improved from 60% to 99%, and its GTmetrix grade increased from C to A. Key web vitals also showed significant gains: Largest Contentful Paint (L.C.P.) improved to 694 ms, Total Blocking Time (T.B.T.) reduced to 89 ms, and Cumulative Layout Shift (C.L.S.) maintained a score of 0. These results highlight the effectiveness of the optimization strategies in enhancing loading times, interactivity, and visual stability, providing a better user experience and setting a foundation for future improvements.

   5. “Juiciness” and Interactive Infographics: An Ethnographic Perspective

      Bruno Campos

      Abstract

      The present study presents the results from interviews conducted with designers about their impressions of “juicy design” in interactive infographics and data visualization. The interviewees, experts in data visualization and design, discuss their familiarity with and application of juicy design principles—characterized by rich visual and interactive feedback—in their work. They explore the potential benefits and drawbacks of incorporating such elements, considering factors like audience, subject matter, and the risk of overstimulation. The interviews also examine the challenges of implementing juicy design, including technical limitations and the difficulty of measuring its impact on user engagement and information retention. Finally, the interviewees speculate on the future role of juicy design within the field. The responses acquired from the conversations provide some key insights about the application of “juiciness” within interactive infographics. According to the interviewees, potential benefits might include enhanced engagement, improved content understanding and increased memorability. On the other hand, some of the drawbacks would be distractions, overstimulation and inappropriate tone. While there is a belief that juicy design will become more prominent, its growth will be influenced by practical considerations like cost, time, and technical complexity. Designers are generally interested in exploring juicy design but want to do so in a way that is intentional and serves the overall goals of their projects. The future of juicy design is likely to be one where it is used more frequently, but in a way that is carefully considered and integrated.

   6. Smart Resume Filter for Vocational Qualification Analysis

      Jing Liu, Yu Fu, Yonggang Luo

      Abstract

      This study aims to develop a smart resume filter system using AI and ML to enhance the efficiency and accuracy of resume screening in talent acquisition. The methodology involves collecting job requirement texts from recruitment websites in the US and China, preprocessing data with NLP tools, and using Word2Vec and LDA for vocational qualification analysis and candidate matching. The system shows potential to improve candidate selection accuracy and efficiency. However, it underutilizes advanced AI models and focuses narrowly on textual data. Future research should integrate large-scale models and multimodal learning for a more comprehensive assessment. This study contributes by innovatively applying AI in recruitment, detailing the development methodology, and highlighting areas for improvement, including ethical considerations and continuous updates to feature extraction processes.

   7. Visio Creativia: A Perspective on Procedural Generation for Metaverse-Ready Art Galleries

      William Hurst, Orestis Spyrou, Fatih Furkan Erkeç, Caspar Krampe

      Abstract

      Procedural content generation has the potential to speed up the development of Metaverse-ready content, reducing human labour effort. The technique has been widely deployed within the computer game development domain for a considerable period of time and to great effect. However, its application for the next vision of the Web is yet to be widely adopted. Thus, this paper presents the tool ‘Visio Creativia’, developed under the EU Horizon Next Generation Internet funding, for exploring the potential of procedural content generation for the creation of Metaverse-ready art galleries, as well as other areas of application. The tool is assessed by means of two case study applications, with feedback provided through an expert user engagement and broader testing. Results indicate that the tool enhances the overall building experience, with a standard deviation and mean score of 0.45 and 6.1, on a 7-point Linkert scale.

   8. Defining a Cloud-Based Platform for Monitoring Port Authority Performance

      Marcello Risitano, Mariarosalba Angrisani, Marco Ferretti, Giuseppe La Ragione

      Abstract

      The increasing complexity of modern maritime and logistics operations has necessitated the adoption of advanced digital solutions to monitor and enhance port performance. This paper presents an innovative cloud-based platform designed to support port authorities in performance monitoring through an adaptive data-driven Decision Support System (DSS). The proposed platform integrates a multi-dimensional performance dashboard, offering a holistic evaluation of port activities by tracking key performance indicators (KPIs) across operational, economic, and environmental domains. By leveraging real-time data analytics, predictive modeling, and cloud computing, this system enhances decision-making processes and fosters collaboration among multiple stakeholders, including terminal operators, port authorities, concessionaires, and environmental agencies.

      The research explores the limitations of traditional monitoring frameworks, which often lack real-time integration and comprehensive data analysis capabilities and presents the cloud-based DSS as a transformative tool that enables proactive governance, optimised resource allocation, and strategic alignment with sustainability and decarbonisation policies. A prototype implementation of the platform in the Central Tyrrhenian Sea Port Authority illustrates its practical applications, demonstrating improved operational efficiency, enhanced stakeholder coordination, and better compliance with environmental regulations. The findings highlight the potential for the system’s scalability and adaptability across different port environments, paving the way for a new era of digitalised and data-driven port management.

   9. Production of Video Clips by Indigenous Artists

      Cristián Londoño-Proaño, Fernando Endara

      Abstract

      The video clip has been adapted to the digital environment and has gained popularity on platforms such as YouTube. This study analyzes the technocumbia video clips of indigenous artists in Ecuador, using a mixed methodology to observe their production and cultural representation. The findings show that these video clips, in addition to entertaining, serve as commercial vehicles that incorporate indigenous cultural symbols, such as Andean landscapes, traditional dress, and the use of the Kwichua language. The research concludes that these video clips combine tradition and modernity, contributing to cultural self-representation and intercultural communication on the internet.

   10. Design, Development, and Evaluation of OMG - Oh My Gas: A Cloud-Based Platform and Mobile App for LPG Supply Management

       William P. Rey, Keith Wilhelm Jan D. Rey, Althea Jodie B. Labayan

       Abstract

       The “OMG - Oh My Gas” (OMG) study explores the development and evaluation of a cloud-based platform and mobile application designed to optimize Liquefied Petroleum Gas (LPG) supply management. This study aimed to create a user-friendly system that streamlines the ordering process, enhances customer satisfaction, and improves operational efficiency for LPG suppliers. The research involved a comprehensive design and development phase, followed by rigorous performance testing and usability assessments. The findings demonstrated that the OMG platform effectively meets its design goals, with notable improvements in order management and user interaction compared to traditional LPG systems. Performance testing confirmed the system’s reliability and responsiveness, while user feedback highlighted strengths in usability and areas for further refinement. The study concludes that the OMG platform represents a significant advancement in LPG management and offers valuable insights for future enhancements and scalability within the industry.

   11. CiteSpace-Based Visualization and Analysis of Bimodal Innovation Research

       Quanmin Bai, Xiaoxia Niu, Qian Wang, Mingxuan Lv

       Abstract

       This paper employs the Web of Science core database and the visual knowledge mapping software CitesSpace to quantitatively evaluate the basic features and thematic hotspots of literature related to binary innovation from 2002 to 2023. This summary provides an overview of the research field and explores potential future research themes and directions. The study demonstrates that dual innovation has attracted the attention of a diverse range of researchers. However, the small number of highly productive authors are geographically dispersed, which has resulted in the inability to form a core research group. In terms of regional distribution, the countries with the highest output of results are China, the United States, and the United Kingdom. China has experienced a period of rapid growth in this field in recent years, becoming the country with the highest number of publications. (2) From the perspective of keywords, the research can be divided into three themes: the conceptual derivation of dual innovation, influencing factors, and the influencing role. (3) From the perspective of research evolution, a number of research hotspots have emerged successively and demonstrated sustained vitality as the research has deepened. Furthermore, in light of technological advancement and the growing complexity of external factors, there is a growing interest in how to select a dual innovation strategy in the context of economic policy uncertainty. Finally, this paper identifies the shortcomings of the research and suggests avenues for future investigation.

   12. Analysis of the Current Situation and Countermeasures of International Standard Transformation Based on Big Data

       Jia Li, Xiaoyan Du

       Abstract

       The National Standardization Development Outline has made clear provisions on “actively adopting international standards” and “improving the consistency between Chinese standards and international standards”, and has proposed rigid goals such as “achieving an international standard transformation rate of 85%”. In order to implement the requirements of the Outline and improve the consistency level of domestic and international standards in China with high quality, this article provides detailed analysis of the current situation of international standards transformation, including the distribution of years, types, and fields of transformed and untransformed international standards, as well as the transformation cycle of transformed international standards. It also deeply analyzes the problems and reasons that exist in the process of international standards transformation, puts forward the suggestions and opinions on the international standards transformation, with the aim of scientifically, timely, and effectively transforming international standards, fully leveraging the role of international standard transformation in promoting international trade and exchange, and improving the level of standardization and openness.