Governments around the globe are in a quest for successful e-government services. In this pursuit, one of the most significant barriers to e-government resilience is insufficient training. The objective of this study is to examine the impact of ICT training programs on the success of e-government services to improve digital competency along with decreasing the digital divide concerning developing societies. The pragmatic research process served as a baseline of this study, and a quasi-experimental research approach was implemented for testing the control group. The results of e-government training revealed a significant increase in the trainees’ self-efficacy regarding the use of e-government applications. This study proved that e-government ICT training programs directed at citizens can create a positive impact in conjunction with increasing digital literacy. Such training programs could also lessen the digital divide, enrich citizens’ potential, and promote more equitable usage of public services in developing societies.

Digitization and lightning expansions in digital technology have made it possible to collect data on almost anything, making it easier to quantify and integrate the collected data. The diffusion of IoT technologies has fostered the government-citizen relationship, creating a powerful argument for public value creation. Thus, IoT service orchestration can influence the development and trustworthiness of intention to use behavior. This study aims to explore the success factors of IoT service orchestration to create public value in smart government by integrating ISST and cognitive trust into TAM. Based on the literature and research outcomes, a comprehensive IoT-based Public Value Model (IoT-PVM) was developed to provide a complete picture of system success. This conceptual model is validated analytically through a quantitative method using PLS-SEM. The findings highlight that IoT service orchestration can enable the government to deliver public value, just as public trust has a parental role in building citizens’ positive behavior intentions towards the use of IoT in e-government services. The model explains 71.8% variance in perceived ease of use, 59.7% in public trust, 62.6% in perceived usefulness, 61.9% in usage behavior intention, and 69.8% of public value creation. The study results and discussion offer valuable insights regarding the public value creation of IoT-empowered public services and also contribute to academic research literature and are practically helpful for policymakers for designing IoT service orchestration and making government smarter, more transparent, and responsive to citizens.

This study investigates the application of Artificial Intelligence (AI) in academic libraries through a bibliometric analysis of 354 publications indexed in Scopus from 2010 to 2023. Using Bibliometrix, VOS Viewer, and MS Excel, it examines publication trends, influential authors, sources, geographical contributions, and thematic evolution. The findings reveal a surge in AI-related research in recent years, with significant contributions from scholars like Cox AM and Stock WG. Collaborative research accounts for 75% of publications, indicating its high impact. The Journal of Academic Librarianship emerges as the leading source, while China, the USA, and India lead in publication output. Key research themes include AI integration in library services, data mining, and user personalization, with notable collaborations between Indonesia-Malaysia and Nigeria-South Africa. A thematic analysis identifies artificial intelligence, machine learning, and chatbots as pivotal areas. The study underscores the interdisciplinary nature of AI research in academic libraries and its growing influence on enhancing library operations, resource discovery, and user experiences. By identifying research gaps and future directions, the findings provide valuable insights for library professionals and policymakers, enabling more strategic AI adoption to improve efficiency, automate routine tasks, and enhance decision-making in library management.

The wide acceptability of ICTs and social media enriches the delivery platform of e-government (E-gov) services. The public can explore problems, provide ideas, and design solutions to improve E-gov services (EGS) in a convenient and timely manner. The role of the public transforms from passive users to active, informed partners or co-creators of EGS innovations and problem solving. However, value co-creation is an interactive process, and service value can only be created through joint efforts of all participants. This study builds an influence factor model of public engaging intention towards EGS value co-creation, based on technology acceptance theory, trust theory, and motivation theory, to explore the impact factors and impact paths. Comprehensive validation is further conducted through path analysis using structural equation modeling (SEM) methods. Path analysis interprets how the public will accept and adopt value co-creation behavior for EGS. The results presented in this study might be helpful for government policymakers or IT managers seeking to enhance EGS value creation through designing more effective incentive mechanisms. This study also introduces a comprehensive picture of the potential paradigm of public service value creation in an era of increasing user dominance.

Sensor-based human activity recognition (HAR) can provide users with more convenience and security than machine vision-based methods. The ideal HAR application would achieve high-accuracy and low-latency performance with minimal hardware consumption. However, so far, the speed-accuracy tradeoff in mobile device-based HAR has rarely been systematically analyzed and discussed. In contrast to the static networks of existing deep HAR models, this paper aims to design a resource-efficient dynamic network, called RepHAR, for low-cost hardware-constrained HAR tasks. This paper first combines multi-branch topologies and structured re-parameterization techniques for HAR. Specifically, RepHAR decouples the model into a training time and inference time architecture by using the idea of structural re-parameterization. That is to say, the model has a multi-branch topology at training time, but it no longer has the same model structure at inference time and is transformed into a plain CNN structure. As a result, RepHAR achieves a tradeoff between speed and accuracy by simultaneously obtaining the accuracy gain of a multi-branch network and the high-speed inference of a plain CNN. On four publicly available datasets (including UCI-HAR, PAMAP2, UNIMIB-SHAR, and OPPORTUNITY), RepHAR can achieve 0.83%-2.18% accuracy improvement and 12%-44% parameter reduction, which demonstrates the effectiveness of the proposed method. Finally, on the embedded Raspberry Pi, the RepHAR runs 72% faster than the multi-branch CNN model, demonstrating its usefulness and practicality. Our model and codes will be released soon.

Purpose: The public sector use of the internet of Things (IoT) technology is an emerging field with a potential for a variety of institutional applications in the fields of information gathering and policy implementation to establish resilience for modern society. In this context, we aim to investigate the success factors which can positively influence the continuous usage intention of IoT service with the mediation effect of perceived public value.Design/methodology/approach: A conceptual model based on the strong literature and theoretical background is tailored to provide factors for IoT services success in the public sector. A quantitative survey was conducted through 381 citizens using IoT services to validate the proposed conceptual model using structural equation modeling approach in order to examine the influence of identified constructs on the continuous usage intention.Findings: The results highlighted that the proposed model successfully accounted for about 59% perceived variance in public value creation and 63% perceived variance in citizens' continuous usage intention. IoT services success is best dignified by the perceptions of citizens who use the services, therefore, this study identifies the positive role of digital society affinity in context of social sustainability and it climaxes that the real value of IoT in public sector comes from establishment of services on top of the service delivery and that's where the public value is going to be created.Practical implications: The use of IoT technology in public services will fetch much benefit to the citizens as well as to the government. The study findings are significant in identifying good practices for generating public value in digital society affinity.Originality/value: The integrated conceptual model explores the driving factors of citizens' inclination towards IoT technology in a social context. Through this study, we can analyze the role of perceived public value in enhancing the citizens' engagement with IoT services. The government policymakers and ICT managers take help from this study to designing IoT public services with making the government more responsive to citizens.