Human-centered Approach Research Articles

Cognitive digital twin in manufacturing process: integrating the knowledge graph for enhanced human-centric Industry 5.0

Industry 5.0 emphasises human-centric intelligent manufacturing, posing challenges in integrating human expertise with advanced machine capabilities. To address these challenges, a novel three-layer cognitive digital twin model based on knowledge graphs is proposed, designed to integrate workers’ knowledge and experience into intelligent manufacturing processes. This model comprises three layers: an ontology layer that constructs a foundational process knowledge ontology library; a knowledge layer that maps real-time data to dynamically update digital models; and a cognitive layer that utilises machine learning, knowledge reasoning, and knowledge mining for advanced analysis, state understanding, and model evolution. The model promotes user interaction through intuitive interfaces and a Q&A system, leveraging techniques such as knowledge reasoning and querying to support decision-making and enhance worker engagement. Validated through a system implemented for aero-engine blade production, this cognitive digital twin model leverages human expertise and machine capabilities to enhance process control, quality management, and overall efficiency. The proposed approach demonstrates significant potential for advancing personalised human-machine interaction in manufacturing, truly embodying the value of a human-centric approach and paving the way for future developments in the field.

Navigating complex mergers: A blueprint for strategic integration in emerging markets

This study explores strategic integration in mergers and acquisitions (M&A), focusing on emerging markets. As M&A activity in these regions grows, companies face unique challenges due to diverse regulatory environments, cultural dynamics, and operational complexities. This research aims to provide a comprehensive framework to navigate these complexities, identifying core integration components, external influencing factors, technological advancements, and associated challenges. Methodologically, the study synthesizes existing literature on M&A integration, analyzing key strategic approaches across cultural alignment, risk management, and operational harmonization. Key findings indicate that successful strategic integration requires technological and human-centered approaches, including tools like ERP systems, data analytics, and cloud computing, which streamline operations, and emphasize cultural alignment, leadership synergy, and proactive risk management. Additionally, the study underscores the impact of regulatory and economic factors on integration strategies, highlighting the need for adaptable frameworks tailored to the complexities of emerging markets. The study concludes that structured integration strategies and flexible, technology-driven frameworks foster long-term M&A success and competitive advantage. Recommendations include adopting sustainable integration models, enhanced cross-functional collaboration, and robust regulatory compliance strategies. Future research opportunities are outlined, particularly regarding open innovation and sustainable practices in emerging market M&A.

Leveraging AI to enhance active learning strategies in science classrooms: implications for teacher professional development

The integration of artificial intelligence (AI) in educational settings offers transformative potential for enhancing active learning strategies in science classrooms. This paper explores how AI-driven tools can support the implementation of active learning methodologies such as problem-based learning (PBL), interactive simulations, and personalized learning pathways. These strategies have been shown to increase student engagement, foster critical thinking, and deepen the understanding of scientific concepts. The analysis highlights the role of AI in creating adaptive learning environments where students receive real-time feedback and differentiated instruction tailored to their individual learning needs. An essential aspect of leveraging AI for active learning is ensuring that teachers are adequately prepared to implement these technologies effectively. The discussion delves into professional development programs that equip educators with the skills and knowledge to incorporate AI tools into their teaching practices. Such programs should emphasize hands-on training, collaborative workshops, and continuous learning opportunities that align with current advancements in educational technology. By fostering teacher confidence and proficiency, these initiatives ensure that educators can maximize the benefits of AI to enhance student learning outcomes. The paper also considers the implications of adopting AI in teaching for long-term educational practices, including ethical considerations, data privacy concerns, and the importance of maintaining a human-centric approach in classrooms. Examples of successful implementations and case studies provide insights into best practices and the challenges encountered. This comprehensive approach underscores the value of combining innovative technology with strategic teacher development to create enriched, interactive, and sustainable learning environments that promote critical thinking and environmental awareness among students.

Learning performance and physiological feedback-based evaluation for human–robot collaboration

The development of Industry 4.0 has resulted in tremendous transformations in the manufacturing sector to supplement the human workforce through collaboration with robots. This emphasis on a human-centered approach is a vital aspect in promoting resilience within manufacturing operations. In response, humans need to adjust to new working conditions, including sharing areas with no apparent separations and with simultaneous actions that might affect performance. At the same time, wearable technologies and applications with the potential to gather detailed and accurate human physiological data are growing rapidly. These data lead to a better understanding of evaluating human performance while considering multiple factors in human–robot collaboration. This study uses an approach for assessing human performance in human–robot collaboration. The assessment scenario necessitates understanding of how humans perceive collaborative work based on several indicators, such as perceptions of workload, performance, and physiological feedback. The participants were evaluated for around 120 min. The results showed that human performance improved as the number of repetitions increased, and the learning performance value was 92%. Other physiological indicators also exhibited decreasing values as the human performance tended to increase. The findings can help the industry to evaluate human performance based on workload, performance, and physiological feedback information. The implication of this assessment can serve as a foundation for enhancing resilience by refining work systems that are adaptable to humans without compromising performance.

Enhancing patient-centred chiropractic care in Canada: identifying barriers, enablers, and strategies through a qualitative needs assessment

BackgroundThe Canadian Chiropractic Association (CCA) initiated a quality improvement project to develop best practices aimed at enhancing the patient experience.Objectives(1) Identify and prioritise the key moments in the new patient experience that could be improved by providing chiropractors with focused support and resources; (2) explore views, barriers, and enablers to implementing these best practices; and (3) develop recommendations to facilitate the adoption of these practices.MethodsWe conducted a qualitative needs assessment using a human-centred design approach, focused on understanding the needs and experiences of end-users to create tailored solutions. The Theoretical Domains Framework (TDF) was employed to explore chiropractors’ knowledge use and behaviour change, and TDF domains were mapped to Behaviour Change Techniques (BCTs) to develop targeted strategies for addressing identified barriers and enablers. Thirteen chiropractors from across Canada participated in semi-structured interviews and related activities.ResultsThe key moments where participants felt they needed the most support were “treatment”, “report of findings”, “informed consent”, “physical examination”, and “before the appointment”. All participants agreed with the best practices seed statements. Key barriers included gaps in knowledge, communication skills, and resource availability, particularly in rural areas. Enablers included collaboration with other health professionals, mentorship, and access to practice tools. Recommendations include enhanced training in communication and treatment planning, increased access to resources in rural areas, and fostering collaborative relationships among health professionals.ConclusionUnderstanding the barriers and enablers to implementing best practices can inform targeted strategies to improve patient-centred care in chiropractic practice across Canada.

Editorial: Human–robot collaboration in Industry 5.0: a human-centric AI-based approach

Editorial: Human–robot collaboration in Industry 5.0: a human-centric AI-based approach

Exploring the Effects of Integrated Corporate Social Responsibility on the Financial Performance of Project-Oriented Organisations

This article embarks on an in-depth exploration of how corporate social responsibility (hereafter: CSR) shapes the financial performance (hereafter: FP) of Project-Oriented Organizations (hereafter: POOs) within Morocco's dynamic construction sector. By adopting a diligent quantitative research method, this research meticulously examined a diverse sample of 250 organizations through advanced correlation and multivariate linear regression techniques. The results illuminate a compelling and noteworthy favourable relationship between CSR initiatives and the FP, indicating that ethical business practices profoundly enhance economic outcomes. By focusing on the distinctive Moroccan landscape, the article sheds light on the remarkable challenges and opportunities faced by POOs, showing an understanding of the financial benefits of CSR. Acknowledging its limitations, the study suggests avenues for future research and perspectives founded on HSDG wisdom. It advocates the HESG framework by integrating a human-centric approach to encourage healthy, equitable and sustainable societal evolution. The study provides actionable recommendations for policymakers, business leaders, and scholars aiming at promoting sustainable economic growth and long-term societal well-being.

Urban Digital Twins and metaverses towards city multiplicities: uniting or dividing urban experiences?

Urban Digital Twins (UDTs) have become the new buzzword for researchers, planners, policymakers, and industry experts when it comes to designing, planning, and managing sustainable and efficient cities. It encapsulates the last iteration of the technocratic and ultra-efficient, post-modernist vision of smart cities. However, while more applications branded as UDTs appear around the world, its conceptualization remains ambiguous. Beyond being technically prescriptive about what UDTs are, this article focuses on their aspects of interaction and operationalization in connection to people in cities, and how enhanced by metaverse ideas they can deepen societal divides by offering divergent urban experiences based on different stakeholder preferences. Therefore, firstly this article repositions the term UDTs by comparing existing concrete and located applications that have a focus on interaction and participation, including some that may be closer to the concept of UDT than is commonly assumed. Based on the components found separately in the different studied cases, it is possible to hypothesize about possible future, more advanced realizations of UDTs. This enables us to contrast their positive and negative societal impacts. While the development of new immersive interactive digital worlds can improve planning using collective knowledge for more inclusive and diverse cities, they pose significant risks not only the common ones regarding privacy, transparency, or fairness, but also social fragmentation based on urban digital multiplicities. The potential benefits and challenges of integrating this multiplicity of UDTs into participatory urban governance emphasize the need for human-centric approaches to promote socio-technical frameworks able to mitigate risks as social division.

Investigation on matching of individualised requirements and shared manufacturing resources in the context of shared factory runtime

Shared Manufacturing (SharedM) empowers individuals to engage in manufacturing via order-driven, resource-sharing processes, embodying the principles of Industry 5.0 and a human-centric approach. This study tackles the challenges of requirement-resource matching to realise Production Planning and Scheduling (PP&S), stemming from conflicts in the distribution and ownership of shared Manufacturing Resources (MRs). We introduce a factory-level runtime framework alongside a self-organising redundant matching algorithm based on sample average approximation to efficiently manage shared MRs and individualised orders. Then, an industrial case study illustrates the application from the modelling of MRs and individualised requirements, to the generation of the final matching Gantt chart. The findings demonstrate that the proposed shared factory can align idle MRs with personalised consumer demands effectively. This paper presents a viable solution for implementing shared factories in industrial settings, providing valuable insights into social manufacturing, SharedM, and novel manufacturing paradigms focused on human-centric values.

The mental health implications of artificial intelligence adoption: the crucial role of self-efficacy

The rapid adoption of artificial intelligence (AI) in organizations has transformed the nature of work, presenting both opportunities and challenges for employees. This study utilizes several theories to investigate the relationships between AI adoption, job stress, burnout, and self-efficacy in AI learning. A three-wave time-lagged research design was used to collect data from 416 professionals in South Korea. Structural equation modeling was used to test the proposed mediation and moderation hypotheses. The results reveal that AI adoption does not directly influence employee burnout but exerts its impact through the mediating role of job stress. The results also show that AI adoption significantly increases job stress, thus increasing burnout. Furthermore, self-efficacy in AI learning was found to moderate the relationship between AI adoption and job stress, with higher self-efficacy weakening the positive relationship. These findings highlight the importance of considering the mediating and moderating mechanisms that shape employee experiences in the context of AI adoption. The results also suggest that organizations should proactively address the potential negative impact of AI adoption on employee well-being by implementing strategies to manage job stress and foster self-efficacy in AI learning. This study underscores the need for a human-centric approach to AI adoption that prioritizes employee well-being alongside technological advancement. Future research should explore additional factors that may influence the relationships between AI adoption, job stress, burnout, and self-efficacy across diverse contexts to inform the development of evidence-based strategies for supporting employees in AI-driven workplaces.

The Synergy Between Industry 5.0 and Circular Economy for Sustainable Performance in the Chinese Manufacturing Industry

The industrial shift from Industry 4.0 to Industry 5.0 has transformed organizational thinking, moving the focus from purely technological implementation to a more human-centered approach. The current study has focused on the Industry 5.0 technological capabilities to bring into circular economy practices aligned with sustainable development goals, aiming to enhance sustainable performance. Moreover, the resource-based theory has grounded the development of the comprehensive framework on Industry 5.0 technological capabilities (artificial intelligence capabilities, big data analytical capabilities, Internet of Things capabilities, machine learning capabilities, and blockchain technology capabilities) and circular economy practices (eco-design, management system, and investment recovery) to achieve sustainable performance (environmental performance, social performance, and economic performance). Data have been collected from 179 respondents from the Chinese manufacturing industry. Additionally, data have been analyzed using the structural equation modeling technique. The results showed that Industry 5.0 technological capabilities directly affect sustainable performance. Moreover, circular economy practices played a dual, moderating, and mediating role between Industry 5.0 technological capabilities and sustainable performance. The current study has contributed to filling a gap in the literature on Industry 5.0 capabilities, especially in the circular economy and sustainable performance perspective. The practical contribution recommended is that if organizations focused on their Industry 5.0 technological capabilities, it would boost circular economy practices and sustainable performance to achieve sustainable development goals.

Human-centric lighting asset management for LED bulbs: a context-driven approach on prognostics and maintenance strategy development in public libraries

ABSTRACT Traditional asset management of lighting systems typically focuses on functionality, cost, and lifespan. In contrast, a human-centric approach prioritizes social sustainability and user well-being by ensuring lighting assets “provide the right light at the right time” for diverse activities. Light-emitting diode (LED) bulbs, known for energy efficiency and longevity, have become a preferred choice, yet public libraries often struggle to manage these assets sustainably, remaining in a reactive “fix/replace when it breaks” stage. Current predictive methods, such as artificial intelligence and machine learning, rely on laboratory data that often overlook real-world contexts, leading to performance gaps. This paper presents a context-driven, human-centric methodology for LED prognosis and maintenance strategies in public libraries, employing limited degradation data from LED testing. Advanced analytical techniques, including Markov Chain Monte Carlo (MCMC) and Deviance Information Criterion (DIC), support a shift from function-based to performance-based reliability assessment. By incorporating Mean Time of Exposure (MTOE) and Critical Integrated Levels (CILs), the approach defines optimal maintenance inspection intervals. This research enhances sustainable LED lighting management in public libraries, offering a framework adaptable to broader applications and aligned with human-centric goals..

Validation of computer vision-based ergonomic risk assessment tools for real manufacturing environments

This study contributes to understanding semi-automated ergonomic risk assessments in industrial manufacturing environments, proposing a practical tool for enhancing worker safety and operational efficiency. In the Industry 5.0 era, the human-centric approach in manufacturing is crucial, especially considering the aging workforce and the dynamic nature of the entire modern industrial sector, today integrating digital technology, automation, and sustainable practices to enhance productivity and environmental responsibility. This approach aims to adapt work conditions to individual capabilities, addressing the high incidence of work-related musculoskeletal disorders (MSDs). The traditional, subjective methods of ergonomic assessment are inadequate for dynamic settings, highlighting the need for affordable, automatic tools for continuous monitoring of workers’ postures to evaluate ergonomic risks effectively during tasks. To enable this perspective, 2D RGB Motion Capture (MoCap) systems based on computer vision currently seem the technologies of choice, given their low intrusiveness, cost, and implementation effort. However, the reliability and applicability of these systems in the dynamic and varied manufacturing environment remain uncertain. This research benchmarks various literature proposed MoCap tools and examines the viability of MoCap systems for ergonomic risk assessments in Industry 5.0 by exploiting one of the benchmarked semi-automated, low-cost and non-intrusive 2D RGB MoCap system, capable of continuously monitoring and analysing workers’ postures. By conducting experiments across varied manufacturing environments, this research evaluates the system’s effectiveness in assessing ergonomic risks and its adaptability to different production lines. Results reveal that the accuracy of risk assessments varies by specific environmental conditions and workstation setups. Although these systems are not yet optimized for expert-level risk certification, they offer significant potential for enhancing workplace safety and efficiency by providing continuous posture monitoring. Future improvements could explore advanced computational techniques like machine learning to refine ergonomic assessments further.

AI assistance in enterprise UX design workflows: enhancing design brief creation for designers.

The study explores the impact of AI tools on the daily tasks of designers in corporate environments, with a focus on the creation and evaluation processes of design briefs. Given ChatGPT's advanced natural language processing capabilities and its potential to meet the complex communication and analysis needs of design work, this tool was selected to investigate its application in designers' workflows. Through expert interviews, experimental testing, and third-party expert evaluations, we collected and analyzed data to understand the impact of AI on work processes. The findings indicate that AI tools significantly enhance both operational experience and subjective perceptions across most tasks. Additionally, the study provides a visual comparison of the testing process through a user experience map, highlighting AI's positive influence on work efficiency, information retrieval, verification, analysis, communication, and decision-making. However, challenges remain in ensuring information authenticity, protecting content copyright, and maintaining professional identity. The primary objective is to gain a comprehensive understanding of the current state of AI application in business contexts and its impact on designers' roles. By analyzing real-world feedback, the research aims to identify the strengths and weaknesses of AI solutions in enterprises and offer practical recommendations. The study underscores the importance of integrating AI thinking into workflows and adopting a human-centric approach for the future development of corporate work environments.

Bridging the AI Divide: Human and Responsible AI in News and Media Industries

Artificial intelligence (AI) is revolutionizing media and journalism, reshaping processes, content, and audience relationship. This editorial report discusses the opportunities and challenges AI brings to these industries raised by this collection of studies, emphasizing the importance of integrating ethical principles and human-centric approaches to its development. These articles examine how AI reshapes content creation, distribution, and audience interaction while addressing the ethical, political, and economic implications of its integration. Key contributions include discussions on the ethical challenges posed by AI—such as bias, transparency, and accountability—and the need for robust governance structures to foster trust and fairness in AI-driven media systems. A recurring theme in this issue is the AI divide, highlighting the disparity in access to AI technologies between the Global North and South. The special issue offers insights into how this divide exacerbates existing inequalities in media production and consumption. It also advocates for interdisciplinary approaches and collaborative efforts to ensure AI's benefits are equitably distributed across geographical and socio-economic contexts. By exploring both the opportunities and perils of AI adoption in media and news industries, this special issue serves as a comprehensive examination of the evolving relationship between AI, media, and society, offering pathways for responsible innovation and inclusive AI adoption worldwide.

Turning Goodbyes into Growth: A Human-Centered Approach to Offboarding

Offboarding, the process of transitioning employees out of an organization, is often overshadowed by recruitment and onboarding efforts. However, a well-designed, human-centered offboarding process benefits both departing employees and the organization by capturing valuable insights, boosting morale, and maintaining positive long-term relationships. This article explores the research foundations of offboarding and offers practical strategies for implementing an effective process. Key goals include gathering candid feedback through exit interviews, showing appreciation for departing employees, and building engaged alumni networks. Techniques such as third-party exit interviews, personalized thank-yous, and ongoing alumni engagement foster trust and goodwill. Real-world examples, including approaches by Bain & Company, Google, and Microsoft, highlight the importance of strategic offboarding practices. Organizations that treat offboarding as an opportunity for learning, relationship-building, and continuous improvement can create lasting value and maintain a positive employer brand even after employees leave.

Human-Centered Approach for Resilience Assessment of Healthcare Networks Subjected to Sequential Earthquakes

Human-Centered Approach for Resilience Assessment of Healthcare Networks Subjected to Sequential Earthquakes

Role of Design Thinking in Socio-Technical Activity for Product Manufacturing

Human interaction intensively impacts design in product manufacturing through design thinking, interpreted product recognition and perceptual product experience (PPE). While the dominant digitalization and artificial intelligence in generative design present significant opportunities for innovation and optimization, there is a gap in adopting holistic, human-centered approaches. Despite numerous advancements, these methods, including design thinking, are not widely practiced, and there is limited discussion on effective design methodologies. This research aims to address this issue by investigating the influence of human interaction on design processes, integrating socio-technical principles, and analyzing how product form affects user perception and recognition.

Encounters of Care: Technological Kin and Nonhuman Care

Practices of care are not easily categorized. They are often embedded in encounters and interactions but are impossible to frame simply according to species boundaries or the supposedly positive or negative feelings they might elicit. This fluidity of care is also characterized by dualities and contradictions, forcing a reflection on who the participants in this caring network of ontologies are, and what the expected and often unexpected results of these interactions can be. This article explores possibilities of care beyond human agency. In a world in which the human is increasingly entangled with technology, practices of care are no longer only a human prerogative. Caring encounters between the technological other and the human become spaces for the redefinition of cross-species collaborations that defy anthropocentrism and human exceptionalism. Technological practices of care towards the human emphasize the emergence of symbiotic existences that disrupts the logic of a human centered approach to the nonhuman, challenging dominant ideas of merely gentle and positive care. Kawakami Hiromi’s Don’t Get Carried Away by Big Birds (2016) and Kazuo Ishiguro’s Klara and the Sun (2021) subvert the logic of anthropocentrism by describing practices of care enacted by technological others towards the human. In their awareness of the inherent complexities and contradictions embedded in nonhuman-human practices of care, they exemplify Elena Pulcini’s notion that fear for the world means an actual care for the world. The disruptive kinships between technology and the human epitomize the non-romanticized character of technological care. By choosing to avoid both technophobia and technophilia, the two novels express the awareness that human existence is always affected by contradictory but unavoidable encounters with the nonhuman other.

Development of Worksheets for Immunomodulator Shared Decision-Making to Facilitate Patient-Clinician Communication: A Quality Improvement Project Employing Design Thinking Principles.

Shared decision-making (SDM) is a principle of humanistic, patient-centered health care within the field of rheumatology. However, clear communication between patients and their clinicians regarding the benefits and risks of immunomodulators may be challenging in a clinical setting. The design-thinking process is a human-centered approach to quality improvement that can help to identify insights to uphold high-quality communication. The development process adhered to the Stanford design thinking process framework, encompassing 5 stages: (1) empathize, (2) define, (3) ideate, (4) prototype, and (5) test. During the empathy stage, quality improvement members spent 4 hours immersed in the clinical setting observing how patients and clinicians engage in SDM conversations. These observations were augmented by unstructured debriefing sessions to better understand the needs and drivers of high-quality SDM. Following this, a rapid ideation workshop was convened to generate creative solutions. These led to rapid prototyping and testing, yielding a final product. The iterative design process identified 4 critical needs: (1) ensuring comprehensibility of materials, (2) upholding accuracy of information, (3) balancing standardization with individualization, and (4) promoting retention of knowledge. During the rapid ideation workshop, the concept of a Worksheet for Immunomodulator Shared Decision-Making (WISDM) was introduced and selected for further elaboration. This led to the creation of 5 prototypes for methotrexate, which were subsequently tested. These were reconciled and modified to make a final product. The WISDM template contains 7 elements that support SDM. Forty-five WISDMs were created for 23 immunomodulators. Further investigation will focus on how WISDMs exactly impact SDM.