Smart Technologies for Sustainable Appliance Consumption

Industry 4.0 is revolutionizing manufacturing and supply chain management through the integration of advanced digital technologies. This chapter provides an overview of Industry 4.0 and its implications for sustainable supply chains. Through interconnected systems, automation, artificial intelligence, and additive manufacturing, Industry 4.0 enhances efficiency, agility, and transparency in supply chain operations. The chapter explores how Industry 4.0 technologies contribute to resource efficiency, energy efficiency, waste reduction, transparency, and social responsibility in supply chains. Challenges and opportunities associated with implementing Industry 4.0 are discussed, along with best practices and case studies showcasing successful implementations. By embracing Industry 4.0, businesses can create more sustainable and efficient supply chains, contributing to a greener future.

The level of fashion consumer awareness and communication regarding sustainable consumption is rising. Organizations are working to provide clarity and guidance on fashion consumption. Brands are experimenting with new materials and supply chain strategies, and suppliers are improving the manufacturing processes and quality of products. However, given the size and complexity of the industrial process, these efforts are not adequate in ensuring a sustainable fashion supply chain. Transparency and traceability in the fashion supply chain are needed to improve the fashion industry by supporting sustainable and ethical practices in the apparel supply chain. Key gaps include a lack of comprehensive and transparent information about how, where, and by whom materials are sourced, processed, and assembled; a lack of transparency in the supply chain practices and procedures affects the environment, working conditions, and human health. The industry has to build the capacity to manage its supply chain, more effectively and responsibly, by improving transparency and traceability as the top goals. So, in this context, the main purpose of this research paper is to study the impacts of transparency and traceability on the dimensions of sustainability in fashion supply chain. The researchers have applied descriptive research methods in which secondary data are collected and analyzed through a literature review of peer-reviewed research papers and the primary data are collected through the survey method by distributing a semi structured questionnaire. The data collected are analyzed using statistical tools and techniques. Finally, the results are discussed and presented.

The rapid pace of digital innovation presents significant challenges to existing privacy laws, necessitating a delicate balance between technological advancement and the protection of individual rights. This paper explores the evolving landscape of privacy law, highlighting the tension between fostering digital innovation and ensuring robust privacy protections. Through a historical overview, the paper traces the development of privacy laws from their inception to the current global regulatory framework, including key legislations such as the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). It delves into the challenges posed by emerging technologies, such as artificial intelligence, the Internet of Things (IoT), and big data, and examines case studies that illustrate these challenges. The analysis reveals a dynamic interplay between innovation and privacy, where stringent regulations may impede technological progress, while lax privacy protections may undermine individual rights. The paper proposes legal reforms and innovative approaches to privacy protection, advocating for a flexible legal framework that can adapt to technological advancements while safeguarding privacy. The conclusion underscores the importance of ethical considerations in shaping future privacy laws and the need for a balanced approach that supports both digital innovation and the protection of individual rights.

Digital social innovation: An overview and research framework

Quantifying adoption rates and energy savings over time for advanced energy-efficient manufacturing technologies

The utilization of Artificial Intelligence (AI) in fishing technology and aquaculture has emerged as a transformative force in the sustainable management and production of seafood. In fishing technology, AI-driven innovations such as autonomous vessels and intelligent fish locating systems optimize fishing operations, enhancing catch efficiency while reducing environmental impact. Real-time monitoring and predictive analytics aid in informed decision-making, ensuring responsible fishing practices and preserving fish stocks for future generations. Furthermore, AI fosters seafood traceability and supply chain transparency, instilling consumer confidence in ethically sourced products. In aquaculture, AI plays a pivotal role in precision farming by analysing environmental data, optimizing feed management, and monitoring fish health. This results in increased productivity, reduced resource wastage, and minimized environmental footprint. AI applications contribute to sustainable aquaculture practices, promoting environmental conservation and responsible resource management. However, as AI adoption accelerates, ethical considerations and data privacy concerns must be addressed. Striking a balance between technological advancement and environmental preservation is vital to safeguard marine ecosystems and support fishing communities' livelihoods. Future research and collaboration among stakeholders are necessary to maximize AI's potential benefits and navigate challenges effectively. Embracing AI in fishing technology and aquaculture offers unparalleled opportunities to meet global seafood demand sustainably, ensuring the continued health and productivity of our oceans for generations to come.

Sustainable consumption plays a crucial role as we are experiencing long-term shifts in climate and weather patterns. To achieve sustainable development, it is essential to understand the opportunities of sustainable consumption. The study focuses on understanding how digital innovations transform consumer buying behavior. The main objective of the study is to analyze current trends in consumer behavior that influence sustainable consumption. The study emphasizes how digital technologies, like blockchain, the Internet of Things, e-commerce platforms, and artificial intelligence, are encouraging sustainable consumer choices. The study used a systematic examination of the literature and key concepts to determine how digital innovations contribute to sustainable consumption practices. The study implies that customers appreciate the information provided by transparent and accessible solutions for making sustainable product decisions. Digital technologies can be a powerful instrument for improving consumers' ethical, sustainable, and ecologically conscious perspectives.

Introduction: Comprehensive health surveillance systems are needed to identify, monitor, and manage infectious disease outbreaks. Deficits in disease surveillance have resulted in poor resource allocation, high rates of morbidity and mortality, and delays in responding to epidemics in Nigeria. Incorporating cutting-edge technologies such as electronic reporting systems, mobile health (mHealth) applications, artificial intelligence (AI), and geospatial mapping offers a revolutionary chance to fortify Nigeria's health surveillance infrastructure in light of the expanding global adoption of digital health innovations. This article evaluates the advantages and disadvantages of Nigeria's present health surveillance system, examines the role of digital technology in epidemic planning and response, and suggests using digital technologies to enhance disease monitoring and control. Materials and Methods: This study adopted a PRISMA-compliant systematic review technique to guarantee an organised and complete examination of available material. Data were sourced from multiple electronic databases, including Web of Science, Scopus, IEEE Xplore, ACM Digital Library, and Google Scholar, using targeted search terms such as "health system surveillance," "digital health innovations," "electronic reporting system," "data-driven approach," and "epidemic preparedness." Inclusion criteria comprised peer-reviewed journal papers, conference proceedings, and book chapters published in English between 2010 and 2020, concentrating on health monitoring, digital innovations, and pandemic preparation. Studies missing actual evidence or presenting just expert opinions were rejected. A total of 1,697 items were initially retrieved, with 1,375 remaining after duplication elimination. Through title and abstract screening, 798 articles were removed, and additional quality evaluation led to a final selection of 205 suitable sources. Data were retrieved using a standardized pro forma, collecting crucial data such as research objectives, procedures, findings, and consequences. The study employed theme synthesis and narrative synthesis methodologies, supported by the Critical Appraisal Skills Programme (CASP) and Mixed Methods Appraisal Tool (MMAT), to promote validity and reliability. Results: Findings from the comprehensive study revealed that Nigeria’s health monitoring system exhibits severe shortcomings, including insufficient infrastructure, inadequate digital reporting procedures, poor internet penetration in remote regions, and limited implementation of AI-driven predictive modeling. However, worldwide best practices reveal that digital technologies have considerably increased epidemic response in other nations. Notable examples include India’s Aarogya Setu mobile surveillance system, AI-powered illness tracking in South Korea, and geospatial mapping tools utilised in the United States for the COVID-19 response. The paper also shows that Nigeria’s Surveillance Outbreak Response Management and Analysis System (SORMAS), although promising, is underutilized owing to infrastructural limitations, poor health worker training, and policy inadequacies. The convergence of AI-driven analytics, cloud-based health surveillance, and mobile-based community reporting systems has the potential to overcome existing gaps and improve Nigeria’s epidemic preparation. Discussion: Comparative research with other countries highlights the importance of investing in digital infrastructure and implementing legislative changes to improve disease surveillance. Stronger epidemic response skills have been demonstrated by nations with interoperable digital platforms, AI-driven early warning systems, and contemporary electronic health records (EHRs). Effective disease monitoring and response have been hampered by Nigeria's digital divide, disjointed surveillance networks, and low rates of technology use. Notwithstanding these obstacles, the study points to a number of opportunities, such as public-private partnerships for internet expansion, training initiatives to raise health workers' digital literacy, and partnerships with international health organisations to improve real-time monitoring and data integration. The results highlight the necessity of a multi-stakeholder approach that combines community involvement, technology advancements, and government actions to modernise Nigeria's health monitoring system. Conclusion: This study underlines the critical need for digital transformation in Nigeria’s health monitoring system to improve epidemic preparedness and response. Strengthening electronic reporting, utilising AI for predictive modeling, integrating geographic mapping technologies, and increasing mHealth applications are crucial for building a strong surveillance framework. Policy changes should focus on boosting internet connectivity, standardizing data-sharing procedures, and promoting engagement with global health institutions. Future studies should examine the practicality of AI-driven health surveillance in resource-constrained contexts and analyse the long-term impact of digital health advances on epidemic management in Nigeria. Implementing these suggestions would strengthen Nigeria’s capacity to recognise and respond to emerging health concerns effectively

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Advances in technological development are ever increasing at all times; consequently, a rapid increase and changes in digital technology have revolutionized healthcare delivery globally. Digital technologies, which are electronic tools, systems, devices, and resources that generate, store or process data, are known to have impacted health care. They have simplified access to health, lower cost of diagnosis and treatments, and improved communication between doctors and patients in the areas of electronic health (eHealth), storage of and access to medical information and data, generating and storing of big data, improving lines of communication between patients and their doctors, electronic health records (EHRs), telemedicine and telehealth, mobile health (mHealth), online learning (eLearning), health applications, and drones. Following the COVID-19 pandemic, the digital health transformation has increased by leap and bound and would likely play a vital role in fighting current and future pandemics by enabling fundamental shifts in medical care, both during the pandemic and in the aftermath. Despite the gains from digital innovation in health care, they did not come without challenges, which are likely to be more with future advancements in digital technology and health. Virtually all technological tools in health care are associated with challenges, limitations or drawbacks. Notable areas of challenges are related to societal problems, ethical issues, connected health solutions, artificial intelligence, and genomics in precision medicine. The challenges are currently being addressed through digital health research, which, hopefully, would proffer lasting solutions.

Achieving high levels of sustainability in the energy sector is central to the UN’s goals. A key strategy for reaching this objective is the integration of sustainable practices within energy supply chains. However, existing research remains fragmented. To address this gap, we conducted a Bibliometric-Systematic Literature Review (B-SLR) of 772 articles (2004–2025) from Scopus, using VOSviewer to map the intellectual landscape of sustainable energy supply chains. Results reveal the need to integrate advanced decision-making models (AI, game theory), deepen studies on circular economy interactions, and explore blockchain’s potential for enhancing transparency, traceability, and optimisation of energy supply chains.

Introduction: In today’s fast-changing corporate market, Organizational Agility (OA) is critical to success. Digital innovation is essential for enabling businesses to respond promptly to changing market conditions and technological advancements. By incorporating digital technologies, businesses improves their flexibility, responsiveness, and competitiveness.Objective: This research seeks to investigate how digital innovation helps OA in quickly changing corporate environments. The research examines the impact of emerging technologies such as artificial intelligence (AI), cloud computing, and the Internet of Things (IoT) on organizational flexibility and responsiveness.Method: This research involves a detailed examination of existing studies that focus on howdigital technology is integrated into organizational frameworks. This research identified significant strategies, themes, and insights into how digital innovations drive organizational agility, such as the roles of leadership, culture, and technical adoption.Result: The findings show that digital innovation improves organizational agility by automating procedures, allowing for real-time decision-making, and increasing data-driven insights. AI and IoT enable faster response times, more consumer engagement, and more efficient operations.Conclusion: Digital innovation is a crucial enabler of organizational agility, providing the tools necessary to adapt to rapidly changing environments. Fully leveraging the benefits of digital transformation requires organizations must align digital strategies with leadership approaches and foster a culture of continuous learning and adaptability.

A market diffusion potential (MDP) assessment model for residential energy efficient (EE) technologies in the U.S.

The Diffusion of Residential Energy Efficient (EE) Technologies has been studied for many years. Finding ways to bridge the energy efficiency gap and increase the diffusion of these technologies have been of much interest to researchers and practitioners alike. However, in most studies, diffusion is equated to adoption of EE technologies by consumers. The present study tries to break this mindset and develops a model to assess the diffusion of residential EE technologies from the market's perspective. The model assesses diffusion of an EE technology based on the market's ability to provide benefits to customers that are identified to be most important. The research contributes in several ways to the existing knowledge bank of residential EE technology diffusion. It provides an elaborate literature review on market attributes with associated components that help to develop the market attributes. The model allows to identify low rating attributes and helps to improve Market Diffusion Potential (MDP) MDP of technology cases by taking appropriate actions. Also, sensitivity analysis provides a snapshot of hypothetical situations that help decision makers to realize what to expect in case of extreme market situations and improve MDP of residential EE technologies by selecting appropriate business inclination strategy for excelling. The model can have several practical applications. The results of MDP assessment would aid in market transformation, utility program selection, as well as feed in information for R & D on prospective EE technologies and a wide array of other organizations with diversified interests in energy savings, climate change and sustainability.

The complexity of human and artificial systems plays a crucial role in Design for Social Innovation (DfSI), an approach that aims to solve social problems through the co-creation of innovative solutions. In this context, design must take into account the dynamic interactions between individuals, communities, and advanced technologies. Indeed, the concept of systemic complexity is fundamental to understanding how heterogeneous elements can interact, influence each other, and generate nonlinear and often unexpected outcomes. In the field of DfSI, the main challenge is to integrate human systems, characterized by diverse behaviors, needs, and values, with artificial systems, such as artificial intelligence (AI) and cybernetic systems, which operate according to algorithmic logic. This integration requires a thorough understanding of socio-technical dynamics, including the analysis of social networks, collective decision-making processes, and technological mediation. Human systems, inherently complex, are defined by a network of social, cultural, and economic relationships. In DfSI, these systems must be viewed not only as recipients of innovations but also as active co-creators. Indeed, human participation is essential to ensure that design solutions are sustainable, accepted, and adapted to local contexts. The systems approach to DfSI, therefore, requires interdisciplinary collaboration that integrates expertise in design, social sciences, technology, and ethics. The goal is to develop design methodologies that are capable of managing complexity and promoting inclusive, sustainable, and adaptive social innovation. Internationally, there are interesting case studies demonstrating the potential of integrating artificial systems into complex social problems in a wide variety of contexts. For example: i) Smart Cities and Social Innovation - Case Study: the city of Barcelona; ii) Healthcare Innovation with AI - Case Study: Babyl in Rwanda; iii) Educational Innovation and AI - Case Study: Adaptive Learning Platforms; iv) Sustainable Agriculture and AI - Case Study: Precision Agriculture in Kenya. In Italy, too, the application of advanced digital technologies in the social context is now widespread. Significant examples include: i) "Educational Robotics" project - Stripes Cooperative; ii) "AI & Welfare" project - Idee in Rete National Consortium; iii) Artificial Intelligence for Social Good project - ABN Consortium; iv) "Care for Carers" project - ASAD Social Cooperative. This research has systematized DfSI initiatives that integrate artificial systems into complex social problems currently present in the Umbria Region, with the aim of addressing the challenge of scalability, i.e., the ability to adapt design solutions to different contexts and communities. This process aims to create a map of criticalities and potentials, facilitating interactions, as well as the development of operational guidelines that can stimulate the emergence of new creative and innovative opportunities. The goal is to develop design methodologies that can manage complexity and promote inclusive, sustainable, and adaptive social innovation. In conclusion, the complexity of human and artificial systems is a key challenge in DfSI, but it also offers significant opportunities to develop more effective and resilient solutions. The interaction between these systems must be carefully managed to ensure that social innovation is driven by people's needs and supported by technologies in an ethical and responsible manner. 1. Manzini, E. (2015). Design, When Everybody Designs: An Introduction to Design for Social Innovation. MIT Press. 2. Mulgan, G. (2019). Social Innovation: How Societies Find the Power to Change. Policy Press. 3. Latour, B. (2005). Reassembling the Social: An Introduction to Actor-Network-Theory. Oxford University Press. 4. Smith, A., & Stirling, A. (2018). Grassroots Innovation and Innovation Democracy. Science and Technology Studies, 31(2), 35-52. 5. Ratti, C., & Claudel, M. (2016). The City of Tomorrow: Sensors, Networks, Hackers, and the Future of Urban Life. Yale University Press. 6. Fu, Z., & Zhou, Y. (2020). Research on human–AI co-creation based on reflective design practice. CCF Transactions on Pervasive Computing and Interaction, 2(1), 33-41. 7. Dionisio, M. et al., (2023) The role of digital social innovations to address SDGs: A systematic review Environmental Management and Sustainable Development” (23 February 2023), Springer 8. Cila, N., Giaccardi, E., Trotto, A., & Bogers, S. (2017). Products as agents: Metaphors for designing the products of the IoT age.