Sustainable Information Systems Research Articles

A cross-sectional study of data linkage and artificial intelligence practices across European countries

Abstract Background The availability of different data sources is increasing with the possibility to link them with each other. However, linked administrative data can be complex to use and may require advanced expertise and skills in statistical analysis. The main objectives of this study were to describe the use of data linkage and artificial intelligence (AI) in routine public health activities and the constraints to linking different data sources. Methods A cross-sectional survey was performed across European countries to explore the current practices applied by national institutes of public health, health information and statistics for innovative use of data sources (i.e., the use of data linkage and/or AI). Results In Europe, the use of data linkage and AI at national institutes of public health, health information and statistics varies. The use data linkage in routine by applying a deterministic method or a combination of two types of linkages (i.e., deterministic & probabilistic) for public health surveillance and research purposes is common in majority of European countries. The use of AI to estimate health indicators is not frequent among these institutes. The complex data regulation laws, lack of human resources, skills and problems with data governance, were reported by European countries as main constraints to routine data linkage for public health surveillance and research. Conclusions Our study showed that the majority of European countries have integrated data linkage in their routine public health activities but only a few use AI. A sustainable national health information system allowing to link different data sources are essential to contribute to public health research. Moreover, it supports evidence-informed health policy making processes with an overview of various aspects affecting population health and may contribute to European pandemic preparedness.

Driving sustainable energy transitions with a multi-source RAG-LLM system

By 2035, the UK aims to upgrade all homes to achieve a net-zero economy by 2050, thereby reducing energy consumption, household costs, and improving living conditions. Small and Medium-sized Enterprises (SMEs) play a crucial role in this transition. However, many SME contractors lack essential information on Sustainable Energy Initiatives (SEIs) and the relevant Energy landscape necessary for driving Sustainable Energy Transitions (SETs). This knowledge gap poses risks to SME interventions, potentially leading to increased costs and inefficiencies. Accessing timely information on SEIs including government policies, funding, technologies, and environmental impacts from various media sources is essential for guiding effective SETs and understanding the relevant Energy landscape, thereby facilitating informed decision-making. Currently, SMEs lack an integrated system that consolidates data from diverse media sources into a centralized Information System (IS), limiting their ability to effectively navigate SEIs. To address this gap, this research introduces an Energy Chatbot, a sustainable IS that utilizes Large Language Models (LLMs) integrated with multi-source Retrieval Augmented Generation (RAG). This system encompasses diverse media sources, including news articles, government reports, industry publications, academic research, and social media. The Energy Chatbot is designed to enhance decision-making for SMEs by providing comprehensive Energy sector insights through a Question Answering (QA) system. Key findings emphasize that this approach reduces costs by utilizing open-source models. Moreover, the Energy Chatbot provides SMEs with access to up-to-date information, enabling them to identify long-term sustainability strategies and maintain a competitive edge in the evolving Energy landscape.

Industry 5.0 Research in the Sustainable Information Systems Sector: A Scoping Review Analysis

Industry 4.0, centered on cyber-physical production systems, has been criticized for prioritizing profit over social and environmental concerns. In contrast, Industry 5.0 emphasizes AI efficiency while promoting human-centric, resilient, and sustainable approaches, integrating economic, social, and environmental systems. Previous research has often focused solely on conceptual frameworks and technologies, overlooking Industry 5.0's sector-specific impacts. This study addresses that gap by conducting a scoping review to map research findings, identify trends, and highlight knowledge gaps and future research opportunities. By systematically analyzing literature from the Scopus database (2016-present), the study refined a large dataset to focus on Industry 5.0's relevance. The analysis revealed significant attention to sectors like Industry and Producer Services, while Agriculture and Retail, particularly natural resource-based sectors like agriculture and fisheries, are often neglected. Key findings indicate that Industry 5.0 is likely to be driven by the industrial sector, followed by product services and financial industries. The study also highlights the strong connection between IoT and AI in optimizing operations with real-time data and automation and identifies blockchain as a promising technology for enhancing transparency and security, despite existing implementation challenges. This research not only serves as a foundational record of Industry 5.0's implications across various sectors but also provides valuable insights into its role in Information Systems (IS). It lays the groundwork for future exploration of Industry 5.0 in diverse sectors and industries.

Exploring customer engagement on Facebook marketplace for second-hand clothing

PurposeThis study aims to explore customers’ second-hand clothing purchases and their engagement on the Facebook marketplace.Design/methodology/approachA conceptual model is developed, building upon the online second-hand shopping motivation (OSSM) scale. Data gathered from 409 respondents was analysed using covariance-based structural equation modelling.FindingsThe results highlight that economic, convenience, ideological motivations and environmental concerns impact customers’ purchase intention. Conversely, status consumption was found to impede customers’ purchase intentions. Notably, the elements of social media engagement, including consumption, contribution and creation, demonstrated significance as a consequence of customers’ second-hand clothing purchase intention.Originality/valueThis study’s findings contribute to the knowledge encompassing sustainable fashion consumption, information systems and second-hand social media shopping. It uniquely explores customer behaviours related to second-hand clothes shopping on the Facebook marketplace by building upon the OSSM scale. These findings offer valuable insights, showcasing the determinants that can increase customer-centric social media engagement. These results inform online retailers on Facebook marketplace about sustainable practices, aligning with UN Sustainable Development Goals 12, 13 and 8, to promote a green global economy.

Development of a Sustainable Information System Using Structured Routing and Livewire Methods in Educational Institutions in Jakarta

Development of a Sustainable Information System Using Structured Routing and Livewire Methods in Educational Institutions in Jakarta

Sustainable Information System for Enhancing Virtual Company Resilience Through Machine Learning in Smart City Socio-Economic Scenarios

Abstract This paper introduces an innovative framework for the management of virtual companies in smart urban environments, with an emphasis on socio-economic resilience facilitated by Sustainable Information Systems. The system aims to equip virtual enterprises in smart cities with tools for robust operations amid socio-economic challenges. Its effectiveness is evidenced by improvements in investment risk assessment, business process simulation, and HR project management, enhancing efficiency and foresight. A key feature is predictive analytics for crisis demand forecasting, enabling swift market adjustments and strategic inventory management. It also helps identify alternative clients and suppliers, ensuring business continuity. Integrating machine learning and augmented reality, the system supports automation and strategic decision-making, significantly benefiting the e-commerce sector by addressing fluctuating demand, supply chain issues, and market adaptations during crises. The Sustainable Information System for Virtual Company Management in Smart Cities offers crucial support for e-businesses facing these socio-economic challenges, facilitating their navigation through turbulent times. Its meticulously designed architecture and functionalities make it a powerful instrument for assisting virtual companies in crisis conditions, fostering their sustainable growth within the socio-economic framework of smart urban settings. Comparative studies with existing models underscore this system’s superior efficiency and holistic approach, highlighting its contribution to enhancing the operational efficiency of virtual companies by 95%, reducing the time needed for critical activities like investment risk analysis and business process simulation, and bolstering the socio-economic resilience of smart cities against crises

Healthcare Information Systems (HIS): Implementation Challenges in Developing Countries

In developing nations, the establishment of sustainable healthcare information systems (HIS) is often hindered by insufficient government policies and outdated technology. Bangladesh is a notable example where many patients lack proper healthcare access due to fragmented and non-digitally recorded data. Research has shown that standardized hospital healthcare systems can streamline patient management, increasing the capacity to serve more patients simultaneously. These systems have the potential to improve healthcare in developing nations significantly. This article offers an overview of the key obstacles that impede HIS implementation in these countries. The study looked at relevant information systems literature using a systematic literature review (SLR). The systematic literature review (SLR) was governed by a review process, and relevant studies were gathered from three databases: IEEE Xplore, EBSCO Databases, and ScienceDirect. A total of 4014 papers were initially found. However, only 11 main studies were included for analysis after a careful selection procedure governed by inclusion and exclusion criteria. This study found 24 obstacles to adopting Healthcare Information Systems (HIS) in developing countries, divided into six groups. These obstacles include a lack of financial assistance, inadequate infrastructure, inadequate education and awareness, cultural and political obstacles, reluctance to change, and poor system quality.
 Bangladesh Journal of Medical Science Vol. 23 No. 02 April’24 Page : 314-326

Challenges in the adoption of sustainability information systems: A study on green IS in organizations

Economic, social and ecological sustainability presents one of the greatest challenges of our society. As a result, there is growing pressure on a variety of organizations to implement sustainability programs, such as inclusion training related to social sustainability, cost management programs related to economic sustainability, and perhaps most importantly, green (information) systems related to environmental sustainability. Not only is multi-faceted sustainability most beneficial to organizations at large, but also there are several categorical thresholds that organizations must meet in order to be certified. For these reasons, companies are increasingly adopting information systems (IS) for sustainability in their operations. Specifically, programs designed to influence employee motivation, attitudes, beliefs, and behaviors are gaining attention. While there is a long tradition of research on technology adoption, such sustainability systems harbor several new phenomena, both with respect to individual and organizational adoption. Therefore, in this study, we explore the challenges of adopting sustainability systems in organizational contexts. Using activity theory and innovation diffusion theory, and with technology adoption theory as the backdrop of our investigation, we conduct a qualitative field study in four small- and medium- sized companies. Using both theory-guided deductive and inductive interpretation phases, we illuminate adoption challenges through combined intersections of adoption stages (knowledge, persuasion, decision, implementation, and confirmation) and activity domains (subject, instrument, object, community, rules). We then shed light on the severity and importance of these challenges through an expert validation study with green IS experts. In discussing the challenges in light of motivational and green IS design, we posit four dilemmas in green IS adoption that arise from tensions in the specific context of sustainability in organizations. Our findings expand existing knowledge in research on green IS, motivational IS design and sustainable behavior change interventions and yield several theoretical and practical avenues for future inquiry and endeavour.

Sustainable Information Systems: Insights from Inside

This study is at the intersection of digital technologies and environmental sustainability, focusing on the concept of digital eco-responsibility. Through interviews with a diverse range of organizations, we aimed to identify their perspectives, challenges, and practices regarding digital eco-responsibility. The research revealed that while digitalization is often seen as a solution for growth, it also poses significant environmental challenges, contributing to global greenhouse gas emissions and resource consumption. Organizations recognize the importance of addressing these challenges and have initiated various eco-responsible practices such as responsible digitalization and digital sobriety. However, implementing these practices effectively requires contextualized strategies tailored to organizational needs and cultures. This study is based on a literature review and interviews conducted with 8 experts. It aims to identify the perspectives and practices of digital eco-responsibility across diverse organizations. It emphasizes the need for continuous improvement and monitoring of eco-responsible practices to mitigate the environmental impact of digital technologies. By exploring insights from these organizational interviews, this research contributes to a deeper understanding of digital eco-responsibility and offers valuable insights for developing sustainable digital strategies across different sectors.

A Conceptual Design for Smart Risk Assessment

Technology cannot be separated from the development of Industry 4.0 in which smart working is the focus. One of the company’s activities that helps the company to achieve its quality goals and objectives is risk management. Based on observations of one SMEs, poor risk management is still found. The risks that occur have not been identified, assessed, and treated appropriately. In addition, documentation that has not been conducted makes the risks that occur later not be handled properly. The aim of this study is to develop a conceptual model of smart risk assessment. The step of this research includes identifying stake holders (as users), identifying functional design, designing context diagram (CD) and data flow diagram (DFD), and designing fidelity prototype. The users involve the production manager, operational manager, and director. The functional design integrates stake holders’ requirements and ISO 31000:2018 risk management process. The design of fidelity prototype focuses on risk assessment, risk treatment, and documentation of risk management. This application is expected to become one of the sustainable development and information systems on Industries.

Conceptual Framework of an Information for Emergency Management for Higher Education in Thai Supply Chain

The objective of research were to develop conceptual framework of an information for emergency management for higher education in Thai supply chain and to evaluate conceptual framework of an information for emergency management for higher education in Thai supply chain. The research sample totalling ten experts consisted of five experts on supply chain , five experts on information system. All of expert must have educational qualification at the doctoral degree level, and must have more than more than four years of work experience The research tool was questionnaire assessing the suitability about conceptual framework of an information for emergency management for higher education in Thai supply chain comprises five elements namely main components suppliers, University, Good service and security, Customers. The data analysed by using arithmetic mean and standard deviation. The assessment about conceptual framework of an information for emergency management for higher education in Thai supply chain using Black-Box technique. The overall model evaluation result was validated at a “Good” level, suggesting that conceptual framework of an information for emergency management for higher education in Thai supply chain aims to support sustainable information system development.

Green Balanced Scorecard: A Tool of Sustainable Information Systems for an Energy Efficient Business

A green balanced scorecard allows businesses to monitor their environmental progress and energy use, as well as quantify their achievements toward decreasing their ecological footprint. The scope of the current research is twofold: (i) to highlight the new sustainable profile of the Balanced Scorecard; and (ii) to investigate the contribution of the Sustainable Balanced Scorecard to the achievement of the energy efficiency and environmental goals of businesses. The present research study applies the rigorous bibliometric analysis technique and the PRISMA method for the years 2011–2023 to investigate the most popular research sources and documents, where the most frequently used keywords and research trends are utilized to answer the research question. In addition, findings from the network, content, and cluster analyses were visualized with the use of the bibliometric tools of Biblioshiny and VOSviewer. The results of the study indicate that businesses have made it a priority to build an energy-efficient management system based on the Sustainable Balanced Scorecard, which will help them achieve their organization’s environmental strategic goals. Moreover, a new era in the Sustainable Balanced Scorecard, that of the Contact Balanced Scorecard, has started emerging in the field. This article explains how the Sustainable Balanced Scorecard benefits organizations by enabling them to enhance their performance on both the economic and social fronts as well as the environmental front. Finally, by employing strategic evaluation methods like the Sustainable Balanced Scorecard to analyze organizations’ sustainability performance, the present study effort supports the sustainable growth of enterprises.

Developing and testing a protocol using a common data model for federated collection and analysis of national perinatal health indicators in Europe.

Context: International comparisons of the health of mothers and babies provide essential benchmarks for guiding health practice and policy, but statistics are not routinely compiled in a comparable way. These data are especially critical during health emergencies, such as the coronavirus disease (COVID-19) pandemic. The Population Health Information Research Infrastructure (PHIRI) project aimed to promote the exchange of population data in Europe and included a Use Case on perinatal health. Objective: To develop and test a protocol for federated analysis of population birth data in Europe. Methods: The Euro-Peristat network with participants from 31 countries developed a Common Data Model (CDM) and R scripts to exchange and analyse aggregated data on perinatal indicators. Building on recommended Euro-Peristat indicators, complemented by a three-round consensus process, the network specified variables for a CDM and common outputs. The protocol was tested using routine birth data for 2015 to 2020; a survey was conducted assessing data provider experiences and opinions. Results: The CDM included 17 core data items for the testing phase and 18 for a future expanded phase. 28 countries and the four UK nations created individual person-level databases and ran R scripts to produce anonymous aggregate tables. Seven had all core items, 17 had 13-16, while eight had ≤12. Limitations were not having all items in the same database, required for this protocol. Infant death and mode of birth were most frequently missing. Countries took from under a day to several weeks to set up the CDM, after which the protocol was easy and quick to use. Conclusion: This open-source protocol enables rapid production and analysis of perinatal indicators and constitutes a roadmap for a sustainable European information system. It also provides minimum standards for improving national data systems and can be used in other countries to facilitate comparison of perinatal indicators.

Supply Chain Information Operation Model for Lifelong Learning in the National Credit Bank Format

The objectives of this research to develop supply chain information operation model for lifelong learning in the national credit bank format and to evaluate the model The sample groups were ten experts in supply chain. The research tool was evaluation form to evaluate supply chain information operation model for lifelong learning in the national credit bank format comprises five main components, namely Suppliers, Manufacturer, education customers and The data analysed by using arithmetic mean and standard deviation The overall evaluation result about supply chain information operation model for lifelong learning in the national credit bank format was a high level. suggesting that supply chain information operation model for lifelong learning in the national credit bank format to support sustainable Information system development.

A Lightweight Blockchain-Based Remote Mutual Authentication for AI-Empowered IoT Sustainable Computing Systems

Internet of Things (IoT) has led to significant advancements in communication technologies, specifically, concerning IoT Based Sustainable Information Systems. Lately, Industry-Academic communities have made great strides for the development of security in IoT-based applications, such as traffic management, industrial automation systems, military surveillance systems, transportation, parking, etc. The sustainable IoT converges AI and blockchain technologies for enhancing quality of individual’s life. As a result, emerging IoT applications operate a distributed ledger technology to provide robust-level of encryption and execution for contractual agreement that resolves interoperability and security issues. Thus, this paper proposes a blockchain-based remote mutual authentication (B-RMA) that considers smart devices and cloud networks to offer security and privacy. The proposed B-RMA can coexist with IoT based smart environment to decentralize the processing of user authentication requests. The prominence of the proposed strategies including security efficiency and privacy protection is evaluated using informal security analysis. Moreover, a run-time platform "Node.js" was used to analyze the communication metrics such as execution time, throughput, and overhead ratio over the concurrent requests. The investigation results prove that the B-RMA achieves a scalable environment, accordingly.

Developing and testing a protocol using a common data model for federated collection and analysis of national perinatal health indicators in Europe

Context: International comparisons of the health of mothers and babies provide essential benchmarks for guiding health practice and policy, but statistics are not routinely compiled in a comparable way. These data are especially critical during health emergencies, such as the coronavirus disease (COVID-19) pandemic. The Population Health Information Research Infrastructure (PHIRI) project aimed to promote the exchange of population data in Europe and included a Use Case on perinatal health. Objective: To develop and test a protocol for federated analysis of population birth data in Europe. Methods: The Euro-Peristat network with participants from 31 countries developed a Common Data Model (CDM) and R scripts to exchange and analyse aggregated data on perinatal indicators. Building on recommended Euro-Peristat indicators, complemented by a three-round consensus process, the network specified variables for a CDM and common outputs. The protocol was tested using routine birth data for 2015 to 2020; a survey was conducted assessing data provider experiences and opinions. Results: The CDM included 17 core data items for the testing phase and 18 for a future expanded phase. 28 countries and the four UK nations created individual person-level databases and ran R scripts to produce anonymous aggregate tables. Seven had all core items, 17 had 13-16, while eight had ≤12. Limitations were not having all items in the same database, required for this protocol. Infant death and mode of birth were most frequently missing. Countries took from under a day to several weeks to set up the CDM, after which the protocol was easy and quick to use. Conclusion: This open-source protocol enables rapid production and analysis of perinatal indicators and constitutes a roadmap for a sustainable European information system. It also provides minimum standards for improving national data systems and can be used in other countries to facilitate comparison of perinatal indicators.

Digitalization as a problem or solution? Charting the path for research on sustainable information systems

Digitalization has permeated all aspects of human lives, economies, and societies. This transformation has been driven by the rapid growth in computing power, storage capabilities, and data transmission infrastructures. These changes have enabled innovations, such as cloud computing, artificial intelligence, smartphones, digitalized homes, (semi) autonomous vehicles, quantum computing, and more. Digitalization has further resulted in faster, more effective service delivery by many organizations. The phenomenon of digitalization relies on an increasingly finite supply of resources, such as crude oil, silicon, and energy. Over the past 150 years, humans have consumed as many natural resources as they have consumed in the past 20,000 years. In part, this increasing clip of consumption has been driven by digitalization, as novel, technology-based solutions, such as blockchain, supplant older, slower low-tech solutions, such as books and ledgers, to process data and create value. Digitalization’s demand for resources may be leading us to an environmental abyss. Consider cryptocurrencies such as Bitcoin, whose electricity consumption is approximately equal to the energy needs of small nations such as Malaysia or Sweden. Such consumption evokes the question, is, “is more digitalization really better, or given the harm to the planet, is this one context where less is more?”. In this paper, we develop a research agenda for understanding the full cost of digitalization and its impact on sustainability. We do so in three parts; first, we offer a crisp definition of sustainability; second, we offer a concise review of the digitalization and sustainability literature; and third, we offer suggestions for research that advances our understanding of how digitalization impacts sustainability.

Improving Information Systems Sustainability by Applying Machine Learning to Detect and Reduce Data Waste

Big data are key building blocks for creating information value. However, information systems are increasingly plagued with useless, waste data that can impede their effective use and threaten sustainability objectives. Using a constructive design science approach, this work first, defines digital data waste. Then, it develops an ensemble artifact comprising two components. The first component comprises 13 machine learning models for detecting data waste. Applying these to 35,576 online reviews in two domains reveals data waste of 1.9% for restaurant reviews compared to 35.8% for app reviews. Machine learning can accurately identify 83% to 99.8% of data waste; deep learning models are particularly promising, with accuracy ranging from 96.4% to 99.8%. The second component comprises a sustainability cost calculator to quantify the social, economic, and environmental benefits of reducing data waste. Eliminating 5948 useless reviews in the sample would result in saving 6.9 person hours, $2.93 in server, middleware and client costs, and 9.52 kg of carbon emissions. Extrapolating these results to reviews on the internet shows substantially greater savings. This work contributes to design knowledge relating to sustainable information systems by highlighting the new class of problem of data waste and by designing approaches for addressing this problem.

How feasible is creating a natural disaster information management open-access repository (NDIM-OAR) in Iran?

Although creating sustainable information systems is highly important to facilitate information flow in natural disaster information management (NDIM), only a few LIS studies have focused on evaluating the feasibility of related technological solutions. An open access repository (OAR) for NDIM has been assessed by Technical, Economic, Legal, Operational, Scheduling, Cultural, and Behavioral (TELOS-CB) dimensions, using the PSI technique. Five NDIM stakeholder groups participated including governmental, public, and research institutions, NGOs (non-governmental organizations), and LIS specialists. The results indicate that the NDIM-OAR is technically more feasible, while the cultural dimension has been considered the most challenging. NGOs have the largest scoring range and governmental stakeholders have the most coherent scoring. Despite of the wide range and seemingly excessive sensitivity of NDM information in Iran, more in-depth, interpretive, cross-disciplinary studies are required reaching a comprehensive decision for an NDIM-OAR. The research is among the first multi-disaster, multi-stakeholder feasibility analyses in LIS.

Preserving the Distributed Fragments of Cultural Heritage: Need for Building a Sustainable Information System in India

Abstract Cultural heritage is an intrinsic segment of the life of the individual who is connected to it and is inherited from one generation to the other. Every heritage item embeds knowledge in historical, cultural, social, scientific, spiritual, and technological forms. Creating a digital database for discovery and expression of cultural heritage plays a significant role in enhancing its visibility and ensuring long-term sustainability. Many of the natural and cultural heritage items in India which are substantially rich in their content are not identified and documented, which consequently lose their social, cultural, historic, and economic utilities. The present study highlights the potential of developing a single-window comprehensive Cultural Heritage Information System (CHIS) to efficiently preserve, document, and manage the cultural heritage assets of the country. This also examines the prerequisites, issues, and challenges which can hinder its sustainable development. It is perceived from the study that there is no such integrated single-window national-level digital platform that prevails in the country to perform the cultural heritage documentation. The study points up the need of constructive efforts, both at individual and institutional levels in India, to ameliorate the situation to safeguard and promote the cultural heritage of the country. The information system developed can act as a unique source of reference and an extensive guide for researchers from different disciplines, tourists as well conservation activists.