AIS Electronic Library (AISeL)
Not a member yet
72426 research outputs found
Sort by
User Support Services and Transparency in Public Finance Information Systems: Evidence from Korea’s e-Naradoum
No full textThis study examines the role of user support services in improving transparency in government subsidy management systems, focusing on Korea’s e-Naradoum platform. Research on Public Management Information Systems (PMIS) within Information System Success (ISS) frameworks has largely focused on how system, information, and service quality influence organizational performance through user satisfaction. This study highlights the direct impact, instead of the mediated effects of user support services, such as training and call centers, on perceived transparency in public finance. Structural equation analysis of survey data from e-Naradoum users reveals that system and information quality enhance transparency perception indirectly via user satisfaction, while user support services promote transparency directly, independent of satisfaction levels. The findings suggest that user assistance programs improve transparency by helping users navigate complex administrative processes and identify mechanisms to combat corruption, particularly in mandatory-use contexts. A comparative analysis further indicates that private-sector users who are less familiar with public administration procedures benefit more from user training and information quality than public officials. These results underscore the need to incorporate well-targeted user support services into the design of digital public finance systems, as investments in training and technical assistance can enhance regulatory compliance and public trust
ICT-Powered Equality: The Roles of Fintech Adoption and Financial Inclusion in Reducing Gender Income Inequality
No full textInformation and Communication Technology (ICT) has transformed financial access, enabling fintech to deliver efficient services, notably to previously excluded women. Using a provincial panel dataset from China spanning 11 years (2010-2021), we employ econometric techniques, including fixed-effect models and two-step generalized method of moments (GMM), to address potential endogeneity and heteroskedasticity concerns. Drawing on the Information and Communication Technology for Development (ICT4D) theoretical framework, this research introduces financial inclusion as a mediating variable, offering novel insights into how ICT-enabled financial innovations influence gender-based economic disparities. The findings indicate that financial technology reduces gender income inequality, with this effect partially mediated by enhanced financial inclusion. However, the impact of fintech adoption varies across economic regions, with more pronounced effects in less developed areas. This study advances our understanding of fintech’s role in bridging gender-based economic divides and offers empirical evidence to inform targeted policies and interventions. The results are particularly relevant for policymakers, fintech companies, and educators seeking to promote gender equality and financial inclusion. This study contributes to ongoing efforts to create a more equitable and inclusive society in which women have equal access to financial resources and opportunities, thereby fostering economic growth and social well-being
Legibility & Rural Development in the American High-Tech Economy
No full textThis paper examines how rural communities in the United States are made and make themselves legible to opportunities in the high-tech economy. Drawing on the concept of economic legibility, I develop a case study based on two years of ethnographic research on the high-tech economy in a remote region of the rural Midwest. Through ethnographic evidence, this paper argues that legibility does not reside within a passive set of assets but is actively formed in an ongoing relational process developed by internal and external actors across multiple scales. Rural communities cultivate legibility both through utilizing existing assets (e.g., digital infrastructure, higher education partnerships, local leadership) and working towards developing needed assets (e.g., entrepreneurial culture, tech workforce, investment capital) to become viable participants in the high-tech economy. By examining how legibility can be understood as co-constituted rather than imposed from outside, this paper challenges traditional power dynamics in development frameworks and offers implications for how ICTD research can better examine the relationship between rural communities and high-tech economic opportunities. The findings provide a nuanced understanding of how rural places negotiate their participation in contemporary economic development, balancing regional identity preservation with technological transformation while maintaining agency in determining which aspects of the high-tech economy best serve their development goals
How Cryptocurrency Could Improve Basic Income Programs: A Design Science Research Approach
No full textBasic income policies attracted a lot of attention from policymakers and researchers during the pandemic. Considering the evidence of these policies’ effectiveness, many believe that they are here to stay, keeping local governments prepared for new emergency crises. In this paper, we investigate the use of blockchain to improve digital payment platforms for basic income. We analyse the case of the Brazilian city of Maricá, where a basic income program created by the local government for the most vulnerable residents is paid in Mumbucas – a local currency accepted only within the city. With more than 70,000 Mumbuca users in a city of 200,000 inhabitants, the initiative in Maricá has become one of the world’s largest regional basic income programmes. We adopt the design science research (DSR) approach to analyse the case and propose improvements to the existing platform, considering this implementation as two entangled sub-artefacts: the public policy and the digital local currency. We conclude the case analysis by proposing alternatives for improving the artefact with a blockchain solution. This study contributes to the discussion regarding basic income, local currencies, blockchain digital platforms, and the DSR approach for producing impactful research in the ICT4D field
Work-Family Frustration When You and Your Partner Both Work From Home: The Role of ICT Permeability, Planning, and Gender
No full textThis paper presents a 10-day diary study of psychological and relational costs of working from home for individuals in live-in partnerships when both partners work from home (WFH). As employees rely on the permeability afforded by information and communication technologies (ICTs) to coordinate work, family responsibilities, and interactions with each other, they experience heightened after-work frustration due to the blurring of the boundary between work and family roles and strain on their cognitive and emotional resources. We integrate boundary theory and ego depletion theory (EDT), developing and testing a framework centered on after-work family role frustration in the WFH context. Our theoretical framework posits that the extent of work-to-family ICT permeability in WFH situations is positively associated with levels of after-work frustration. This frustration affects job productivity and can lead to potential conflict between partners. Given recent WFH-related findings showing that women bear a greater proportion of domestic responsibilities while also meeting job demands, we also examine the moderating effect of gender on the relationship between ICT permeability and after-work frustration. Additionally, we investigate the mitigating role of planning behavior in interrupting the cycle of ICT permeability and frustration. Our findings strongly support the proposed model, providing empirical evidence of the psychological costs of working from home and the effectiveness of planning as a mitigation strategy. Our study makes a significant theoretical contribution by illuminating the relationships among ICT permeability, after-work frustration, and work-family dynamics. This research extends the literature on the WFH phenomenon enabled by advanced ICTs such as email, text messaging, mobile phones, and remote meeting apps (e.g., Microsoft Teams, Zoom, and Google Meet). It provides critical insights for research on the future of work surrounding the well-being aspects of WFH. Practically, our findings offer actionable insights for individuals and organizations, helping them recognize and mitigate the psychological costs of working from home while better managing work-family boundaries to improve overall well-being
The Influence of Socio-Demographic Factors on Digital Capital in Higher Education
No full textTechnology influences development in numerous ways, including through education and training. It is both a didactic tool and a defining feature of students’ personal growth and social experiences. The ability of students to develop personal digital capital (an extension of Bourdieu’s multi-dimensional concept of capital) is a major determinant of their educational and career success and, by extension, national economic development. This study examines the influence of socio-demographic factors – age, gender, degree type, income, and parental education – on the personal development of digital capital among university students. Applying a structural equation model with data from an Iran-based survey (n = 421), the study finds that disparities in digital capital are explained by gender, income, and other socio-demographic factors. The finding that digital access supersedes digital competence in explaining inequalities in digital capital highlights pathways for targeted policy intervention
Content Success vs. Follower Growth: Unpacking the Dual Impact of Collaborative Creation on Creator Performance
No full textCollaborative content creation (co-creation) has become a prevalent strategy for driving innovation and monetization in the creator economy. Unlike open collaboration among participants with limited interaction, co-creation among socially connected creators introduces external social capital through peer networks, while simultaneously reshaping internal social capital as shifts in content style transform follower relationships. This reallocation of social capital complicates value creation and capture, making the impact of co-creation on creator performance difficult to predict. Drawing on value co-creation and social capital theories, this study examines how co-creation affects creators’ content- and account-level performance. We conceptualize value creation as occurring across two stages—content production and consumption—and investigate the moderating roles of network embeddedness and collaborator diversity. Using data from BiliBili, a leading Chinese creator platform, we find that greater engagement in co-creation enhances content-level performance but reduces follower growth. Network embeddedness intensifies both effects, whereas collaborator diversity weakens them. These findings reveal the inherent value trade-offs within co-creation and highlight the need to balance content innovation with a distinct personal identity in creator strategies
Understanding Data Infrastructure Providers: Value Creation and Adoption Barriers in the Case of Data Spaces
No full textThe growth of data-driven innovation has transformed traditional value chains into dynamic data ecosystems, exemplified by emerging data spaces. Using data infrastructure providers as an illustrative example of data infrastructure integration, this research explores how diverse stakeholders collaboratively create and individually capture value within such ecosystems. Despite their potential, data spaces face considerable barriers hindering widespread adoption. This study uses a systematic literature review, qualitative case analyses, and expert interviews to examine how data space service providers, as integrators of data infrastructures, create and capture value. Employing the e3-value model, we illustrate value flows within data ecosystems. Results indicate service providers primarily deliver consulting, data management, and technical integration services. However, barriers remain regarding standardization, data sovereignty, technical know-how, acceptance, and economic sustainability. We propose solutions such as standardization efforts, decentralized architectures, enhanced training initiatives, user-friendly technologies, and sustainable monetization strategies. Our research offers theoretical contributions and practical recommendations to advance economically sustainable and broadly accepted data sharing ecosystems
Teaching Case: Balancing Innovation and Operations: A Systems Analysis Case of Technology Adoption in a Trucking Company
No full textThis case presents a classic systems analysis and design conundrum: how to incorporate new technology into existing ongoing operations without hurting the bottom line? Antelope Trucking and Logistics, a small regional trucking business, is faced with adapting its aging information technology systems to take advantage of global positioning capability. Because of the company’s size and relative inexperience with technology, they don’t have the expertise to identify the most efficient ways to implement changes. In the past, they successfully relied on faculty and students from a local university to act as consultants and developers for small projects, but now they need to make a much bigger change. The needed functionality will impact their core competitive advantage, i.e., deliveries. They must decide how to proceed: negotiate with their incumbent vendor and possibly pay too much for a product, further customize a stalled student project and pay less money (or almost none) but maintain full control, do nothing, or seek out another solution entirely. This case takes students through the decision-making process from the point of view of a small company entrepreneur, from problem identification to researching unknown technologies, and ultimately, how to decide what to do. It also introduces students to the information technology used in the complex freight and logistics industry
CarbConscious: Carbon-Aware Scheduling for Sustainable Large Language Model Operations
No full textLarge language model (LLM) inference operations now account for 70-90% of production AI compute resources, yet carbon optimization strategies for these workloads have received limited attention. This paper presents a carbon-aware orchestration framework that dynamically shifts LLM inference workloads across temporal and spatial dimensions based on real-time electricity grid carbon intensity data. Our multi-objective optimization approach balances carbon emissions reduction, service level agreement (SLA) compliance, and operational cost management through a Pareto-optimal decision support model. Using hybrid electricity grid data combining historical records from open-source carbon intensity APIs with synthetic augmentation spanning 12 global regions over 30 days, our simulation experiments demonstrate carbon reductions of 35-52% for mixed-latency workloads while maintaining 99.5% SLA compliance. The framework contributes to the Green Information Systems literature by providing actionable sustainability mechanisms for inference-dominated production systems