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Today’s in-demand skills may not be needed tomorrow. As companies are adopting a new group of technologies, they are in huge need of information technology (IT) professionals who can fill various IT positions with a mixture of technical and problem-solving skills. This study aims to adopt a sematic analysis approach to explore how the US Information Systems (IS) programs meet the challenges of emerging IT topics.

This study considers the application of a hybrid semantic analysis approach to the analysis of IS higher education programs in the USA. It proposes a semantic analysis framework and a semantic analysis algorithm to analyze and evaluate the context of the IS programs. To be more specific, the study uses digital transformation as a case study to examine the readiness of the IS programs in the USA to meet the challenges of digital transformation. First, this study developed a knowledge pool of 15 principles and 98 keywords from an extensive literature review on digital transformation. Second, this study collects 4,093 IS courses from 315 IS programs in the USA and 493,216 scientific publication records from the Web of Science Core Collection.

Using the knowledge pool and two collected data sets, the semantic analysis algorithm was implemented to compute a semantic similarity score (DxScore) between an IS course’s context and digital transformation. To present the credibility of the research results of this paper, the state ranking using the similarity scores and the state employment ranking were compared. The research results can be used by IS educators in the future in the process of updating the IS curricula. Regarding IT professionals in the industry, the results can provide insights into the training of their current/future employees.

This study explores the status of the IS programs in the USA by proposing a semantic analysis framework, using digital transformation as a case study to illustrate the application of the proposed semantic analysis framework, and developing a knowledge pool, a corpus and a course information collection.

The Internet of Things (IoT) has attracted a lot of attention in both industrial and academic fields for recent years. Artificial intelligence (AI) has developed rapidly in recent years as well. AI naturally combines with the Internet of Things in various ways, enabling big data applications, machine learning algorithms, deep learning, knowledge discovery, neural networks and other technologies. The purpose of this paper is to provide state of the art in AI powered IoT and study smart public services in China.

This paper reviewed the articles published on AI powered IoT from 2009 to 2018. Case study as a research method has been chosen.

The AI powered IoT has been found in the areas of smart cities, healthcare, intelligent manufacturing and so on. First, this study summarizes recent research on AI powered IoT systematically; and second, this study identifies key research topics related to the field and real-world applications.

This research is of importance and significance to both industrial and academic fields researchers who need to understand the current and future development of intelligence in IoT. To the best of authors’ knowledge, this is the first study to review the literature on AI powered IoT from 2009 to 2018. This is also the first literature review on AI powered IoT with a case study of smart public service in China.

When integrating smart elements offered by emergent technologies, libraries are facing the challenges of technological renovation and maintaining their operation using emerging technology. Given the importance of smart library, new technologies are needed in building new libraries or renovation of existing libraries. The purpose of this paper is to propose a risk warning system for library construction or renovation in the aspect of risk management.

The proposed Internet of Things (IoT)-based system consists of sensors that automatically monitor the status of materials, equipment and construction activities in real time. AI techniques including case-based reasoning and fuzzy sets are applied.

The proposed system can easily track material flow and visualize construction processes. The experiment shows that the proposed system can effectively detect, monitor and manage risks in construction projects including library construction.

Compared with existing risk warning systems, the proposed IoT-based system requires less data for making dynamic predictions. The proposed system can be applied to new builds and renovation of libraries.

Semantic Web is an extension of the World Wide Web by tagging content with “meaning”. In general, question answering systems based on semantic Web face a number of difficult issues. This paper aims to design an experimental environment with custom rules and scalable data sets and evaluate the performance of a proposed optimized backward chaining ontology reasoning system. This study also compares the experimental results with other ontology reasoning systems to show the performance and scalability of this ontology reasoning system.

The authors proposed a semantic question answering system. This system has been built using ontological knowledge base including optimized backward chaining ontology reasoning system and custom rules. With custom rules, the proposed semantic question answering system will be able to answer questions that contain qualitative descriptors such as “groundbreaking” resesarch and “tenurable at university x”. Scalability has been one of the difficult issues faced by an optimized backward chaining ontology reasoning system and semantic question answering system. To evaluate the proposed ontology reasoning system, first, the authors design a number of innovative custom rule sets and corresponding query sets. The innovative custom rule sets and query sets will contribute to the future research on evaluating ontology reasoning systems as well. Then they design an experimental environment including ontologies and scalable data sets and metrics. Furthermore, they evaluate the performance of the proposed optimized backward chaining reasoning system on supporting custom rules. The evaluation results have been compared with other ontology reasoning systems as well.

The proposed innovative custom rules and query sets can be effectively employed for evaluating ontology reasoning systems. The evaluation results show that the scalability of the proposed backward chaining ontology reasoning system is better than in-memory reasoning systems. The proposed semantic question answering system can be integrated in sematic Web applications to solve scalability issues. For light weight applications, such as mobile applications, in-memory reasoning systems will be a better choice.

This paper fulfils an identified need for a study on evaluating an ontology reasoning system on supporting custom rules with and without external storage.

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.

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.

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.

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.

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.