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The goals of the contemporary environment in this new era of the Internet of Things (IoT), digital technologies (DTs) and smartisation are to enhance economic, social and environmental sustainability while also concentrating on the citizens' quality of life. As these initiatives advance, more determination is required to offer effective approaches to the problem posed by the accomplishment of the Sustainable City Project in Nigeria as a developing nation. To address these problems and facilitate the process for Nigeria's major cities to become ‘smart cities’, universities, research institutions and other stakeholders must collaborate alongside. This chapter aims to establish a model or framework that addresses urban intelligence, social inclusion, resilience and technological innovation, mobility, urbanisation and residents' quality of life. The reviews of the characteristics and management of smart cities in developed countries were documented to serve as a comparison study of the cities in African sub-Saharan regions. This will assist in building models that can produce predictions about possible smart solutions in the areas of mobility, urban infrastructure and ecological problems brought on by climate change in African cities. This chapter brings attention to the body of knowledge by envisioning the benefits to the government and citizens in making appropriate decisions to enhance sustainable development, a better resilience environment, improved infrastructure, smart city environments and residents' quality of life. The study's implications centre on how the government could prioritise urban features and services as indicated in the smart cities framework.

Globally, urban planners and decision makers are pursuing place-based initiatives to develop and enhance urban infrastructure to optimise city performance, competitiveness and sustainability credentials. New discourses associated with big data, Building Information Modelling, SMART cities, green and biophilic thinking inform research, policy and practice agendas to varying extents. However, these discourses remain relatively isolated as much city planning is still pursued within traditional sectoral silos hindering integration. This research explores new conceptual ground at the Smart – Natural City interface within a safe interdisciplinary opportunity space. Using the city of Birmingham UK as a case study, a methodology was developed championing co-design, integration and social learning to develop a conceptual framework to navigate the challenges and opportunities at the Smart-Natural city interface. An innovation workshop and supplementary interviews drew upon the insights and experiences of 25 experts leading to the identification of five key spaces for the conceptualisation and delivery at the Smart-Natural city interface. At the core is the space for connectivity; surrounded by spaces for visioning, place-making, citizen-led participatorylearning and monitoring.The framework provides a starting point for improved discussions, understandings and negotiations to cover all components of this particular interface. Our results show the importance of using all spaces within shared narratives; moving towards ‘silver-green’ and living infrastructure and developing data in response to identified priorities. Whilst the need for vision has dominated traditional urban planning discourses we have identified the need for improved connectivity as a prerequisite. The use of all 5 characteristics collectively takes forward the literature on socio-ecological-technological relationships and heralds significant potential to inform and improve city governance frameworks, including the benefits of a transferable deliberative and co-design method that generates ownership with a real stake in the outcomes.

This research navigates the confluence of data analytics, machine learning, and artificial intelligence to revolutionize the management of urban services in smart cities. The study thoroughly investigated with advanced tools to scrutinize key performance indicators integral to the functioning of smart cities, thereby enhancing leadership and decision-making strategies. Our work involves the implementation of various machine learning models such as Logistic Regression, Support Vector Machine, Decision Tree, Naive Bayes, and Artificial Neural Networks (ANN), to the data. Notably, the Support Vector Machine and Bernoulli Naive Bayes models exhibit robust performance with an accuracy rate of 70% precision score. In particular, the study underscores the employment of an ANN model on our existing dataset, optimized using the Adam optimizer. Although the model yields an overall accuracy of 61% and a precision score of 58%, implying correct predictions for the positive class 58% of the time, a comprehensive performance assessment using the Area Under the Receiver Operating Characteristic Curve (AUC-ROC) metrics was necessary. This evaluation results in a score of 0.475 at a threshold of 0.5, indicating that there's room for model enhancement. These models and their performance metrics serve as a key cog in our data analytics pipeline, providing decision-makers and city leaders with actionable insights that can steer urban service management decisions. Through real-time data availability and intuitive visualization dashboards, these leaders can promptly comprehend the current state of their services, pinpoint areas requiring improvement, and make informed decisions to bolster these services. This research illuminates the potential for data analytics, machine learning, and AI to significantly upgrade urban service management in smart cities, fostering sustainable and livable communities. Moreover, our findings contribute valuable knowledge to other cities aiming to adopt similar strategies, thus aiding the continued development of smart cities globally.

As the world continues to urbanise, cities face increasing pressure to become more sustainable, efficient and livable. Sustainable smart cities are emerging as a promising solution to this challenge, leveraging technology and data to improve urban systems and services while reducing environmental impact. This chapter provides an overview of the concept of sustainable smart cities and its implications for urban development. It explores the key features of sustainable smart cities, including their focus on technology, data and citizen engagement and the challenges they are facing in terms of infrastructure, data management, social equity, environmental sustainability, governance and regulations. The chapter also highlights the implications of sustainable smart cities for urban planners, policymakers and other stakeholders, emphasising the need for collaborative approaches that engage citizens and stakeholders in the design and implementation of smart city initiatives.

This chapter examines the six smart city dimensions that serve as pillars in smart city projects. These dimensions are crucial in the development and evaluation of smart city initiatives, representing key areas for consideration. This chapter offers a detailed analysis of the smart city ecosystem, focusing on the governance, environment, people, living, mobility, and economy dimensions. It challenges the prevailing media portrayal of the smart city strategy and engages in the current academic debate surrounding these dimensions. This chapter defines, discusses, and explains each dimension, incorporating case studies from cities such as Copenhagen, San Francisco, Lisbon, and Barcelona. It also includes interviews and factual data to highlight the internal implementation and objectives of the smart city within each dimension. This chapter provides a comprehensive understanding of the smart city ecosystem, its implementation, and the potential benefits and challenges associated with each dimension.

This chapter concludes the book by addressing the complexities and challenges associated with smart cities. Despite the widespread enthusiasm and progressive policies surrounding smart cities, navigating this world remains a desirable yet complex challenge. Drawing on existing literature, this final chapter serves as a synthesis of the key points covered throughout the book and offers practical guidelines for navigating the landscape of smart cities. This chapter provides valuable tips and insights for both citizens and policymakers, recognizing their pivotal roles in shaping the future of smart cities. Additionally, it delves into the current challenges faced by smart city initiatives and discusses potential future directions. Emphasizing the need for ongoing adaptation and innovation, this chapter highlights the importance of overcoming obstacles and capitalizing on opportunities in the rapidly evolving digital age. By offering a comprehensive overview and practical recommendations, this chapter aims to equip readers with the knowledge and tools to navigate the complexities of smart cities effectively. It concludes the book on a forward-looking note, emphasizing the dynamic nature of smart city development and the continuous need for adaptation and innovation.

The purpose of this chapter is to develop academic answers to the key rural areas and smart villages and digital agriculture. This chapter analyses the National level initiatives of Government of India Mission to convert rural areas into smart cities. The Union Ministry of urban development collaborates with State Government and nominate a particular city or cities in their state. Financial incentives or benefits will be provided to enhance the quality of the city. Coimbatore being a cosmopolitan city it is also a combination of rural villages and urban township. The main objective of this chapter is to identify and explore the initiatives of SMART CITIES MISSION a joint venture activity initiated by Government of India and State Government of Tamil Nadu. The results clearly indicate how digital technologies play a pivotal role to enhance the quality of eco-friendly initiatives and to improve the smart villages and agriculture. The key recommendations are the lessons learnt from other smart cities initiatives in other states and how Coimbatore can be an example and adopt key takeaways from other states and cities around the world.

Smart HR 4.0 is a new concept characterized by adopting innovative technologies of Industry 4.0 (I4.0) in the HR domain. This study attempts to identify the key factors of Smart HR 4.0 to foster organizational innovation ambidexterity.

Based on review of literature and survey from expert opinions by using the Delphi method, 12 factors were found most suitable for this study. Further, the fuzzy-TISM technique was used to establish contextual relationships and develop a hierarchical model on the identified factors. Subsequently, the MICMAC analysis was applied to classify these factors according to their driving and dependence power.

This study framed a conceptual hierarchical model of Smart HR 4.0 and established contextual relationships among identified factors. Result shows that smart organic structure, industry–institute interface, IT-enabled system and ambidextrous leadership are important factors as they have the highest driving power. Further, knowledge management, learning culture and psychological empowerment are the linkage factors having both driving as well as dependency power in the whole system.

This study can guide the managers in smoothly implementing these practices to manage their human capital amidst digital disruption, ensuring innovation competitiveness of the firm. The structural hierarchical framework of Smart HR 4.0 may serve as a blueprint for HR professionals and business leaders to attain organizational innovation ambidexterity in the current wave of digital disruptions (Industry 4.0).

This study provides a holistic model of smart HR 4.0 integrating innovation ambidexterity in I4.0.

Digitalization accelerates the need of tourism and hospitality ecosystems to reframe business models in line with a data-driven orientation that can foster value creation and innovation. Since the question of data-driven business models (DDBMs) in hospitality remains underexplored, this paper aims at (1) revealing the key dimensions of the data-driven redefinition of business models in smart hospitality ecosystems and (2) conceptualizing the key drivers underlying the emergence of innovation in these ecosystems.

The empirical research is based on semi-structured interviews collected from a sample of hospitality managers, employed in three different accommodation services, i.e. hotels, bed and breakfast (B&Bs) and guesthouses, to explore data-driven strategies and practices employed on site.

The findings allow to devise a conceptual framework that classifies the enabling dimensions of DDBMs in smart hospitality ecosystems. Here, the centrality of strategy conducive to the development of data-driven innovation is stressed.

The study thus developed a conceptual framework that will serve as a tool to examine the impact of digitalization in other service industries. This study will also be useful for small and medium-sized enterprises (SMEs) managers, who seek to understand the possibilities data-driven management strategies offer in view of stimulating innovation in the managers' companies.

The paper reinterprets value creation practices in business models through the lens of data-driven approaches. In this way, this paper offers a new (conceptual and empirical) perspective to investigate how the hospitality sector at large can use the massive amounts of data available to foster innovation in the sector.

Digitalising cities requires new urban governance processes that account for rapidly changing environments and technological advances. In this context, agile development methods have become valuable, if not necessary. However, agile development contradicts public administration practices of risk aversion and long-term planning. The purpose of this study is to discuss practical avenues for navigating these two contradictions by adapting agile development to the needs of public sector organisations.

The authors review the collaborative elaboration of Dresden’s smart city strategy as a critical case study. Dresden’s smart city strategy was developed using agile development and quadruple-helix innovation. The year-long co-creation process involved stakeholders from various groups to conceive an integrated and sustainable vision for digitalisation-based urban development.

Despite the apparent contradictions, this study finds that key aspects of agile development are feasible for public sector innovation. Firstly, risks can be strategically managed and distributed among administration and non-administration stakeholders. Secondly, while delivering value through short iterative loops, adherence to formal processes remains possible. Informal feedback cycles can be harmoniously combined with official statements, allowing iterative progress.

The empirical material is based on a single case study and thus risks overemphasising the general applicability of the proposed methods.

This paper outlines practical steps to greater agility for public administration engaged in digitalising cities. The paper conceptualises a forward and lateral momentum for the agile development of a smart city strategy that aims to reconcile formal policymaking processes with short-term loops and risk aversion with experimental value creation. This approach balanced risks, created value and enhanced the strategy‘s alignment with strategic frameworks, ultimately promoting innovation in the public sector.

This paper proposes a novel, empirically grounded conceptualisation of implementing agile methods that explicitly recognises the peculiarities of public administrations. It conceptualises the orchestrated and pragmatic use of specific agile development methods to advance the digitalisation of cities.