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Globalization, along with its technological developments, has brought important changes and developments in all sectors and led to innovation and modernization. In the tourism industry, the concept of smart destination, derived from the concept of smart city, has become widespread to meet the changing needs of tourists. In this context, smart technologies have started to be used in destinations, but more than technology in destinations is needed in terms of sustainability. To ensure sustainability in tourism, these smart technologies must also be eco-friendly. Smart destinations and eco-friendly practices are important for the sustainable development of the tourism industry. The use of technology in destinations can increase sustainability and efficiency, while using eco-friendly practices can protect and preserve the natural environment. In this study, first of all, smart destinations and the characteristics of smart destinations are discussed. Then, smart tourism and related eco-friendly practices are argued. Following this, information about the future of smart destinations is given, and assumptions are mentioned. Afterward, problems and solutions are discussed. Finally, the study has been completed with the conclusion part. The findings of the study revealed that the concept of green especially comes to the fore in smart destinations, that there are studies to prevent all kinds of pollution (air, noise, etc.), and applications such as smart parking systems, smart lighting systems, augmented reality (AR), and virtual reality (VR) are given importance.

Barriers to adequate healthcare in rural areas remain a grand challenge for local healthcare systems. In addition to patients' travel burdens, lack of health insurance, and lower health literacy, rural healthcare systems also experience significant resource shortages, as well as issues with recruitment and retention of healthcare providers, particularly specialists. These factors combined result in complex change management-focused challenges for rural healthcare systems. Change management initiatives are often resource intensive, and in rural health organizations already strapped for resources, it may be particularly risky to embark on change initiatives. One way to address these change management concerns is by leveraging socio-technical simulation models to estimate techno-economic feasibility (e.g., is it technologically feasible, and is it economical?) as well as socio-utility feasibility (e.g., how will the changes be utilized?). We present a framework for how healthcare systems can integrate modeling and simulation techniques from systems engineering into a change management process. Modeling and simulation are particularly useful for investigating the amount of uncertainty about potential outcomes, guiding decision-making that considers different scenarios, and validating theories to determine if they accurately reflect real-life processes. The results of these simulations can be integrated into critical change management recommendations related to developing readiness for change and addressing resistance to change. As part of our integration, we present a case study showcasing how simulation modeling has been used to determine feasibility and potential resistance to change considerations for implementing a mobile radiation oncology unit. Recommendations and implications are discussed.

This chapter provides an overview of the potential use of Intelligent Transport Systems (ITS) and associated artificial intelligence (AI) techniques in the land transport sector in an attempt to achieve related United Nations Sustainable Development Goals (SDGs) targets. ITS applications that have now been extensively tested worldwide and have become part of the everyday transport toolkit available to practitioners have been discussed. AI techniques applied successfully in specific ITS applications such as automatic traffic control systems, real-time image processing, automatic incident detection, safety management, road condition assessment, asset management and traffic enforcement systems have been identified. These methods have helped to provide traffic engineers and transport planners with novel ways to improve safety, mobility, accessibility and efficiency in the sector and thus move closer to achieving the various SDG targets pertaining to transportation.

The world needs more Eastern knowledge and, ergo, more consciousness. Humanity will unlikely experience a quantum leap in consciousness if we keep ignoring Eastern and other sources of perennial wisdom in the design and development of our socioeconomic and ecological systems. This chapter aims to bridge the consciousness gap by exploring the meaning and application of Buddhist and Taoist systems thinking to regenerative systemic leadership, design, development and sustainable transformation.

Purpose: The availability of resilient energy infrastructure and services is crucial to achieving sustainable development goals. However, defined and trustworthy definitions of resilience exist solely for engineering and energy systems, particularly in the industrialised world or metropolitan systems. However, no universally accepted definition considers the distinctive characteristics of rural regions in developing economies. To define resilience for rural power systems in developing countries, this chapter synthesises many perspectives on resilience, energy systems, and rural environments.

Methodology: It draws on extensive literature assessments on resilience, particularly concerning energy systems and rural areas, as well as other pre-existing frameworks.

Findings: To account for the unique challenges of electricity supply in rural developing nations, a comprehensive ‘Rural Power System Resilience Framework’ is introduced, including technical, economic, and social resilience.

Social implications: To better understand the elements contributing to the stability of electricity grids in developing nations and rural areas, this resilience framework may be utilised by global markets, system owners and operators, government officials, non-governmental organisations, and communities.

Originality: Through establishing this framework, this study sets the path for developing suitable and ‘effective resilience standards’ tailored for implementation in these rural areas, with the ultimate goal of facilitating the fulfilment of achieving domestic and worldwide sustainability objectives.

This chapter focuses on critical thinking as a new, powerful, and specialized tool and technique for understanding and analyzing the subtle operations of the free enterprise capitalist market system and its ethics and morality. Everything in the world of consumers and market enterprise systems are determined by our supply–demand system that in turn are determined by our presumed limitless production–distribution and consumption (LDPC) systems. From a critical thinking viewpoint, we study the free enterprise capitalist system (FECS) as a dynamic, interconnected organic system and not as a discrete or compartmentalized body of disaggregate parts. Systems thinking with critical thinking calls for a shift of our mindset from seeing just parts to seeing the whole reality in its structured dynamic unity; both mandate that we see ourselves as active participators or partners of FECS and not as mere cogs in its wheels or as mere factors of its production processes. Critical thinking seeks to identify the “structures” that underlie complex situations in FECS with those that bring about high- versus low-leveraged changes in various versions of capitalism. Specifically, this chapter applies critical thinking to FECS as defined by its founder, Adam Smith, in 1776 to its fundamental and structural assumptions, and as supported or critiqued by serious scholars such as Karl Marx, Maynard Keynes, C. K. Prahalad and Allen Hammond (inclusive capitalism), John Mackey and Rajendra Sisodia (conscious capitalism), and others.

To operate with high efficiency and minimise the risks of power failures, power systems require careful monitoring. The availability of real-time data is crucial for assessing the performance of the grid and assisting operators in gauging the present security of the grid. Traditional supervisory control and data acquisition (SCADA)-based systems actually employed provides steady-state measurement values which are the calculation premise of State Estimation. More often, however, the power grid operates under dynamic state and SCADA measurements can lead to erroneous and inaccurate calculation results. The introduction of the phasor measurement unit (PMU) which provides real-time synchronised voltage and current phasors with very high accuracy is universally recognised as an important aspect of delivering a secure and sustainable power system. PMUs are a relatively new technology and because of their high procurement and installation costs, it is imperative to develop appropriate methodologies to determine the minimum number of PMUs as well as their strategic placements to guarantee full observability of a power system. Thus, the problem of the optimal PMU placement (OPP) is formulated as an optimisation problem subject to various constraints to minimise the number of PMUs while ensuring complete observability of the grid. In this chapter, integer linear programming (ILP), genetic algorithm (GA) and non-linear programming (NLP) constrained models of the OPP problem are presented. A new methodology is proposed to incorporate several constraints using the NLP. The optimisation methods have been written in Matlab software and verified on the standard Institute of Electrical and Electronics Engineers (IEEE) 14-bus test system to authenticate their effectiveness. This chapter targets United Nations Sustainable Development Goal 7.

This chapter explores a pathway towards achieving a sustainable and inclusive future through the implementation of systems innovation, systems leadership and systems change. The author highlights the importance of understanding complex systems and identifies several models that can be employed to drive systems change, including the iceberg model and multi-level perspective. The author stresses the significance of systems leadership and innovation in creating a sustainable and inclusive future. This means that leaders and managers need to shift their mindset from reductionism to systems thinking. Reductionism views complex systems as a collection of separate parts that can be studied independently. In contrast, systems thinking acknowledges the interconnectedness of all parts and how they influence each other. When they embrace systems thinking, leaders and managers can make systems innovation and drive systems change to achieve sustainable and inclusive growth. Achieving a sustainable and inclusive future requires a collective effort from individuals, organizations and governments. It demands a comprehensive understanding of the interdependencies and interactions within complex systems, as well as a willingness to adopt new ways of thinking and leading. This chapter presents a compelling case for adopting systems innovation, systems leadership and systems change as critical components in building a sustainable and inclusive future.

In the mid-2000s, the operator of New York City’s mass transit network committed more than a half-billion dollars to military contractor Lockheed Martin for a security technology capable, in part, of inferring threats based on analysis of data streams, of developing response strategies, and taking automated action toward alerts and calamities in light of evolving circumstances. The project was a failure. This chapter explores the conceptualization and development of this technology – rooted in cybernetics – and compares its conceptual underpinnings with some situated problems of awareness, communication, coordination, and action in emergencies as they unfold in one of the busiest transport systems in the world, the New York subway. The author shows how the technology, with all the theatrical trappings of a “legitimate” security solution, was apparently conceived without a grounded understanding of actual use-cases, and the degree to which the complex interactions which give rise to subway emergency can be anticipated in – and therefore managed through – a technological system. As a case-study, the chapter illustrates the pitfalls of deploying technology against problems which are not well-defined in the first place, to the neglect of investments against much more fundamental problems – such as inadequate communication systems, and unstable relationships with emergency response agencies – which might offer guaranteed benefits, and indeed lay a firm groundwork for future deployment of more ambitious technology.