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With the development of information technology (IT), governments around the globe are using state-of-the-art IT interfaces to implement the so-called 3E’s in public service delivery, that is, economy, efficiency and effectiveness. Two of these IT interfaces relate to Artificial Intelligence (AI) and Internet of Things (IoT). While AI focuses on providing a “human” garb for computing devices, thereby making them “intelligent” devices, IoT relies on interfaces between sensors and the environment to make “intelligent” decisions. Recently, the convergence of AI and IoT – also referred to as Artificial Intelligence of Things (AIoT) – is seen as a real opportunity to refurbish the public service delivery formats. However, there is limited understanding as to how AIoT could contribute to the improvisation of public service delivery. This study aims to create a modular framework for AIoT in addition to highlighting the drivers and barriers for its integration in the public sector.

This descriptive-explanatory study takes a qualitative approach. It entails a thorough examination of the drivers and barriers of integrating AI and IoT in the public sector. A review of literature has led to the development of a conceptual framework outlining the various factors that contribute to creating public value.

Value creation occurs when AI and IoT coalesce in the public service delivery mechanisms.

AIoT is a cutting-edge technology revolutionizing health care, agriculture, infrastructure and all other industrial domains. This study adds to the growing body of knowledge on the public sector's use of AI and IoT. Understanding these disruptive technologies is critical to formulating policies and regulations that can maximize the potential benefits for the public-sector organizations.

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.

The evolution from emerging technologies to smart libraries is thoroughly analyzed thematically and bibliometrically in this research study, spanning 2013 through 2022. Finding and analyzing the significant changes, patterns and trends in the subject as they are represented in academic papers is the goal of this research.

Using bibliometric methodologies, this study gathered and examined a large corpus of research papers, conference papers and related material from several academic databases.

Starting with Artificial Intelligence (AI), the Internet of Things (IoT), Big Data (BD), Augmentation Reality/Virtual Reality and Blockchain Technology (BT), the study discusses the advent of new technologies and their effects on libraries. Using bibliometric analysis, this study looks at the evolution of publications over time, the geographic distribution of research and the most active institutions and writers in the area. A thematic analysis is also carried out to pinpoint the critical areas of study and trends in emerging technologies and smart libraries. Some emerging themes are information retrieval, personalized recommendations, intelligent data analytics, connected library spaces, real-time information access, augmented reality/virtual reality applications in libraries and strategies, digital literacy and inclusivity.

This study offers a thorough overview of the research environment by combining bibliometric and thematic analysis, illustrating the development of theories and concepts during the last ten years. The results of this study helps in understanding the trends and future research directions in emerging technologies and smart libraries. This study is an excellent source of information for academics, practitioners and policymakers involved in developing and applying cutting-edge technology in library environments.

The need for mechanization in company operations during the pandemic has been further illustrated by the pressure to use recent technologies for sustainable business practices. Recent technologies like Internet of Things (IoT), artificial intelligence (AI), big data and cloud are being abandoned in favour of automating business activities during and after the pandemic, to build flexibility and sustainability. The objective of this paper is to give an outline of the literature on the bang of digital metamorphosis on organizational adaptability. The paper focuses on the future of business sustainability from dislocations by espousing recent technologies from different perspectives. As well as the anticipated disruptive developments, the benefits of technology on economics and business are also being felt, but still in their early stages. Similar ideas and methods must be implemented as quickly as is practical, and governments and enterprises must be ready and willing to do so. The transition to a commercial environment that emphasizes technology from alternative distribution channels will have a direct influence on organizational structures. Additionally, they could have training in or experience in positive sciences, which will aid in creating the corporate environment of the future sustainably. Absolutely the variety of technologies in business helps to accelerate business activities and attain the maximum goal before and after the pandemic. It still appears that a hypothetical model is required that could simplify the incorporation of using these technologies during a disaster with business processes. The findings may be applied to manage technology and speed up corporate resilience for a better economy.

The United Nations (UN) adopted Sustainable Development Goals (SDGs); agenda 2030 focuses on Climate Action (goal 13), targeting climate adaptability, as well as resilience, awareness and improving policy mechanisms on climate change. In order to enhance climate adaptability, climate-smart agricultural practices (CSAP) is a necessary step. CSAP is a sustainable agriculture approach with a strong focus on climate dimensions. The three pillars of climate-smart agriculture (CSA) are ‘Adaptation’: adapting to climate change; ‘Resilience’: building resilience against it and ‘Remove’: reducing carbon emissions. The new world economy uses Industry 4.0 technologies for sustainable advancement, including blockchain technology, big data analytics, artificial intelligence (AI), augmented and virtual reality, industrial Internet of Things (IoT) and services. Hence, technology plays a significant role in climate sustainable agriculture practices. This chapter shall consider three technologies consisting of IoT, AI and blockchain technology which contribute to CSAP in pre-harvesting (monitoring climate as well as fertility status, soil testing, etc.), harvesting (tilling, fertilisation, seed operations, etc.) and post-harvesting (predicting weather factors, seed varieties, etc.) periods of agriculture. All these three technologies work like the human nervous system; IoT helps in converting various information regarding demography, climate change, local agricultural needs, etc. into world data; AI works like a brain in combination with IoT, helps predict the use of climate-smart technology and blockchain, the memory part of the nervous system which deals with supply-side and ensures traceability as well as transparency for consumers as well as farmers. Hence, this chapter shall contribute to the importance of these three technologies in adopting CSAP in three stages of agriculture.

The purpose of this paper is to gain an understanding of the current research on Internet-plus.

The authors collected scholarly publications from the scientific databases Web of Science, Core Collection, Inspec and Compendex (Ei Village 2) and performed statistical analysis of the retrieved data from five perspectives.

The research on Internet-plus has obtained increasing attention in China. The top three research fields were social science, education and management.

The study will help researchers understand the current trends on Internet-plus.

With the rise of digital media and content marketing, business-to-business (B2B) technology firms increasingly use narratives in their marketing strategy. If research has studied the impact of narrative on audiences, the structuration of the narrative strategies is still an overlooked area. The purpose of this paper is to understand the structuration of narrative strategies.

Authors studied the cases of narratives on the Internet of Things produced by two leading technology firms, IBM and Cisco, between 2012 and 2016. Material includes advertising campaigns, blogs, written customer cases, white papers, public speeches and selling discourses.

The research highlights the importance of metanarratives as the core of the structuration of seemingly different contents. It also shows how firms tap into fundamental mythic archetypes and broader sociocultural narratives to try and legitimate the emerging technology. Finally, research also introduces the concept of transmedia strategy and illustrates its use by the two firms studied.

The results are based on only two cases of multinational firms, limiting the generalization of the findings.

The results of the research may encourage firms to use more narrative branding strategies. They also offer directions for the key elements to manage when elaborating a narrative strategy (defining key metanarratives, identifying and using broader sociocultural narratives, designing a transmedia strategy).

The paper is among the first to try to understand the structuration of narrative branding strategies. While exploratory, it contributes to research on B2B branding and digital branding by bringing the narrative into B2B branding research.

India's agri-food industry is rapidly expanding to keep up with the country's growing population. With the help of the fourth Industrial Revolution (Industry 4.0), modernization is creating a new revolution in the agri-food sector. Its applications in the food supply chain as a supply chain 4.0 (SC 4.0) have made it convenient to deliver products efficiently from farms to consumers. The various technologies such as the internet of things (IoT), artificial intelligence (AI), big data analytics and blockchain, etc., have impacted emerging supply chains. But many challenges are perceived by stakeholders toward the adoption of SC 4.0 technologies in India. The authors identified the challenges of adopting SC 4.0 for the agri-food sector and used the Total Interpretive Structural Modeling (TISM) tool to analyze those challenges. Based on literature research, nine major issues were diagnosed and then simulated using expert opinion. Primary data were also gathered with the help of a questionnaire to identify the status of acceptance level of these technologies. This study highlights the importance of government support, availability of sources of funds, customer orientation toward food safety, the commitment of management toward modernization, aware and well trained and motivated employees are a few of the major factors impacting the adoption of SC 4.0 technologies.

Manufacturing in Mauritius is mostly export-oriented. Any supply chain (SC) failure or resilience deficit may result in cancellation of orders and loss of customers, market share and revenue and reduce capability to compete globally. Addressing this challenge is complex, although digital technologies and artificial intelligence (AI) models can improve resilience by assisting decision-making and mitigate risks, thus infusing greater predictability across the SC.

Supply chains are facing increasing disruptions and uncertainties owing to extreme weather events, the war in Ukraine, market volatility and the ongoing COVID-19 pandemic, among other factors. Manufacturing industries and their supply chains essentially create thousands of jobs that enable economic growth and sustain export capability. In addition, they need to maintain or increase both productivity and efficiency and recover quickly from unforeseen or unexpected challenges – that is they need to be resilient. Transformation initiatives, whether in production or supply chain management (SCM), are never easy. Process changes not supported by data or hurried human decisions can sometimes have unintended consequences, mainly adverse. However, in times of greater uncertainty (war and pandemic), setbacks can have greater consequences on the business. Manufacturers are already apprehensive and report slowing exports as recession concerns have caused consumers and businesses to pull back on spending. There is therefore a need to reduce uncertainty and augment resilience by unlocking and synthesising insights that emanate from the power of data analytics, AI and machine learning to improve the resilience efficiency balance.

This chapter will discuss the opportunities arising from the adoption and implementation of digital technologies and AI in SCM, leading to better value creation, less greenhouse gas emissions and resilience. The hurdles that enterprises are facing to integrate AI in their logistics and SCs will also be highlighted. This work comments on initiatives that uphold the objectives of SDG 8 – decent work and economic growth, SDG 9 – industry, innovation & infrastructure and SDG 13 – climate action.

Amid rapid global urbanization, cities confront many complex challenges, including sustainability, waste management, energy consumption and resource allocation. Two emerging paradigms – smart cities and circular economies (CEs) – have shown promise in addressing these issues. Smart cities utilize cutting-edge technologies like internet of things (IoT), artificial intelligence (AI) and big data analytics to create interconnected, efficient urban ecosystems. Meanwhile, the CE model aims for a regenerative system focused on minimizing waste and maximizing the utilization of resources. However, these paradigms have rarely been studied in conjunction, resulting in a gap in the existing literature. This bibliometric analysis aims to bridge this gap by mapping the interdisciplinary research landscape that integrates smart cities and CEs. Specifically, the study identifies key thematic intersections, influential authors, leading academic journals and potential directions for future research. Through this analysis, we provide a comprehensive overview of the existing body of work and lay the groundwork for the evolution of this interdisciplinary domain.