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The objective of this research was to develop a new and highly accurate approach based on a fuzzy inference system (FIS) for the evaluation of usability based on ISO 9241-210:2019. In this study, a fully automated method of usability evaluation is used for interactive systems with a special look at interactive social robots.

Fuzzy logic uses as an intelligent computing technique to deal with uncertainty and incomplete data. Here this system is implemented using MATLAB fuzzy toolbox. This system attempted to quantify four criteria that correlate highly with ISO 9241-210:2019 criteria for the evaluation of interactive systems with maximum usability. Also, the system was evaluated with standard cases of computer interactive systems usability evaluation. The system did not need to train various data and to check the rules. Just small data were used to fine-tune the fuzzy sets. The results were compared against experimental usability evaluation with the statistical analysis.

It is found that there was a high strong linear relation between the FIS usability assessment and System Usability Scale (SUS) based usability assessment, and authors’ new method provides reliable results in the estimation of the usability.

In human-robot systems, human performance plays an important role in the performance of social interactive systems. In the present study, the proposed system has considered all the necessary criteria for designing an interactive system with a high level of user because it is based on ISO 9241-210:2019.

For future research, the system could be expanded with the training of historical data and the production of rules through integrating FIS and neural networks.

This system considered all essential criteria for designing an interactive system with a high level of usability because it is based on ISO 9241-210:2019. For future research, the system could be expanded with the training of historical data and the production of rules through integrating FIS and neural networks.

The set of 2,509 documents related to the human-centric aspect of manufacturing were retrieved from Scopus database and systmatically analyzed. Using an unsupervised machine learning approach based on Latent Dirichlet Allocation we were able to identify latent topics related to human-centric aspect of Industry 5.0.

This study aims to create a scientific map of the human-centric aspect of manufacturing and thus provide a systematic framework for further research development of Industry 5.0.

In this study a 140 unique research topics were identified, 19 of which had sufficient research impact and research interest so that we could mark them as the most significant. In addition to the most significant topics, this study contains a detailed analysis of their development and points out their connections.

Industry 5.0 has three pillars – human-centric, sustainable, and resilient. The sustainable and resilient aspect of manufacturing has been the subject of many studies in the past. The human-centric aspect of such a systematic description and deep analysis of latent topics is currently just passing through.

The purpose of this paper is to introduce the concept of meaning as a relevant but missing link in understanding the building blocks of service innovation informed by service-dominant (S-D) logic. In exploring the role of meaning in service innovation, especially related to new value propositions, resource integration and new value cocreation, the authors suggest using the conceptualization of meaning within human-centered design, which has an established body of knowledge on addressing how actors engage and interact.

The paper builds an actionable conceptual framework that relates meaning to central tenets of service innovation, such as resource integration, value propositions and cocreation of value. It delineates the central building blocks of service innovation and conceptually integrates them with meaning to explain the underlying mechanisms of service innovation related both to its development and adoption.

The findings highlight how and why meaning precedes value creation and directs resource integration. Indicating that meaning is driven by experience of earlier interactions it delineates its relationships with new value formation and positions resource interpretation as a driver of this process.

This paper extends the understanding of service innovation in relation to S-D logic, with meaning as a conceptual link to aspects of S-D logic that claim a phenomenological nature. Meaning contributes to S-D logic by providing an understanding of how beneficiaries form intentions to engage in value creation and resource integration. Additionally, by integrating service and design research domains, this paper suggests possibilities for multidisciplinary contributions in future research.

Self-regulated learning (SRL) is crucial for successful learning and lifelong learning in today’s rapidly changing world, yet research has shown that many learners need support for SRL. Recently, learning analytics has offered exciting opportunities for better understanding and supporting SRL. However, substantial endeavors are still needed not only to detect learners’ SRL processes but also to incorporate human values, individual needs and goals into the design and development of self-regulated learning analytics (SRLA). This paper aims to examine the challenges that lifelong learners faced in SRL, their needs and desirable features for SRLA.

This study triangulated data collected from three groups of educational stakeholders: focus group discussions with lifelong learners (n = 27); five teacher interviews and four expert evaluations. The groups of two or three learners discussed perceived challenges, support needs and willing-to-share data contextualized in each phase of SRL.

Lifelong learners in professional development programs face challenges in managing their learning time and motivation, and support for time management and motivation can improve their SRL. This paper proposed and evaluated a set of design principles for SRLA.

This paper presents a novel approach for theory-driven participatory design with multistakeholders that involves integrating learners, teachers and experts’ perspectives for designing SRLA. The results of the study will answer the questions of how learners’ voices can be integrated into the design process of SRLA and offer a set the design principles for the future development of SRLA.

Guidelines for the design of knowledge-based e-learning usability systems are absent from the current recognized set of usability design heuristics and from an established evaluation methodology of e-learning system developments. Such systems can help Web designers and instructional designers design for different user needs and decide which properties are of a higher priority, thus meriting more design and development efforts. The authors aim to help students develop higher-order thinking skills, such as application, evaluation and syntheses of knowledge.

The authors applied Merrill ' s first principles of instruction and usability properties as pedagogical and usability design guidelines, knowledge management (KM) and hierarchical task analysis as methodological knowledge bases. The authors proposed a KM e-learning usability framework which frames our mapping of Web usability attributes to e-learning usability properties. The authors aim to investigate whether adopting Merrill ' s first principles of instruction and usability properties as knowledge-based guidelines/design factors would help learners develop higher-order thinking skills and whether this design would result in positive technology acceptance. The authors also developed a method matrix to map the selected methods of cognitive engineering to its potential uses in the KM e-learning usability framework of this paper and mapped e-learning usability tools with components in the KM e-learning usability system.

Findings indicated that our design effectively helped learners to demonstrate higher-order thinking skills and positive technology acceptance, promising indications toward the design and development of knowledge-based usability frameworks and systems.

The sample size of this paper is small. Hence, conclusions are not generalizable at this moment.

The authors’ contributions are twofold: First, the authors proposed a KM e-learning usability framework, which frames the mapping of KM processes to e-learning principles and usability properties. Second, the authors proposed a method matrix which maps the selected methods of cognitive engineering to its potential uses in their KM e-learning usability framework. Based on these mappings and focusing on the usability properties navigation and learning support, the authors used ICT/Web2.0 tools to present/visualize information more clearly and more sensibly/manageably to students, to help trigger new knowledge and develop higher-order thinking skills, such as application, evaluation and syntheses of knowledge and articulate information from different perspectives throughout the KM life cycle.

The purpose of this research is to explore the mechanisms of knowledge management (KM) for innovation and provide an approach for enterprises to leverage KM activities into continuous innovation.

By reviewing the literature from multidisciplinary fields, the concepts of knowledge, KM and innovation are investigated. The physical, human and technological perspectives of KM are distinguished with the identification of two core activities for innovation: knowledge creation and knowledge usage. Then an essential requirement for continuous innovation – an internalization phase – is defined. The systems thinking and human‐centered perspectives are adopted for providing a comprehensive understanding about the mechanisms of KM for innovation.

A networking process of continuous innovation based on KM is proposed by incorporating the phase of internalization. Three sources of organizational knowledge assets in innovation are identified. Then, based on the two core activities of innovation, a meta‐model and a macro process of KM are proposed to model the mechanisms of KM for continuous innovation. Then, in order to operationalize the KM mechanisms, a hierarchical model with four layers is constructed by integrating three sources of knowledge assets, the meta‐model and the macro process into the process of continuous innovation.

According to the lessons learned about KM practices in previous research, the three perspectives of KM should collaborate with one another for successful implementation of KM projects for innovation; the networking process of innovation provides a new way to integrate KM process in innovation; the hierarchical model provides a suitable architecture to implement systems of KM for innovation.

The meta‐model and macro process of KM explain how the next generation of KM can help the value creation and support the continuous innovation from the systems thinking perspective. The hierarchical model illustrates the complicated knowledge dynamics in the process of continuous innovation.

The purpose of this paper is to explore the impact that occupational stereotypes held by customers have on value co-creation processes in human-centered service systems (HCSSs) like hospitals. Specifically, by exploring if and how customers’ (i.e. patients’) stereotypes toward frontline employees (e.g. nurses) affect their satisfaction as co-creators of value, this study responds to current service research priorities attempting to understand value co-creation in collaborative contexts like healthcare, and addresses calls to investigate the changing role of health care customers therein.

A field study was conducted in the context of German hospitals, which provides unique empirical evidence into the relationship between patients’ stereotypes toward healthcare professionals and their satisfaction with health services as well as the mediating mechanisms through which such stereotypes affect patient satisfaction.

Negative (positive) stereotypes patients hold toward healthcare occupations decrease (increase) their satisfaction and are associated with perceptions of reduced (improved) patient orientation and patient participation in co-creation. However, only perceived patient orientation partially mediates the link between occupational stereotypes and patient satisfaction.

This study develops and tests new hypotheses related to occupational stereotyping in complex HCSSs, and extends previous research on stereotypes in service by exploring the previously unknown mediating mechanisms through which these impact value co-creation processes overall. It furthermore provides important guidance for future research about stereotyping in general, and its impact on value co-creation and HCSS, in particular.

The evolution of management underlines the importance of the human, systemic, technological and contingency element and their interaction along with an amplified awareness of organizations for achieving excellence. This paper aims to discuss whether the fusion of digital, biological and physical world leads to a new excellence perspective and to investigate the potential value of informative neuroscientific findings for setting the foundations for smart services.

This study is based on a literature review regarding the advances of neurosciences and its implications for business. Their usefulness and potential contribution for the provision of smart services are investigated.

The fusion of technological evolution and biological sciences may potentially give birth to a new excellence conceptualization complemented by genetic data whose consequences are hard to predict. Neurosciences offer insights for various human behavior areas that can be used by business practitioners, to refine their thinking and management style and build brain-friendly organizational contexts. The combination of using neuroscientific evidence and technology in service systems sets the foundations for an “intelligent” provision of services in a quality context.

The paper investigates the conceptual development of excellence within the receding context of the “smart era” and the potential contribution of neurosciences for the provision of smart services with reference to quality pioneers’ theories and ideas.

The purpose of this research was to investigate how VR-mediated sports, as opposed to 2-D screens, affect the emotional and cognitive experiences of fans with the game and its sponsors.

The current study employed a single-factorial experimental design, in which participants were randomly assigned to either watch a soccer game through a VR headset or a 2-D screen. Physiological and self-reported measures were used to measure levels of presence, arousal, attention and memory.

Participants who watched sports through VR experienced a higher level of presence, greater psychophysiological arousal, and exhibited higher levels of attention toward the game. However, they showed lower recognition for in-stadium signage compared to those who watched the game on a 2-D screen.

The results suggest that sports teams can use VR to create a more immersive and engaging experience for fans. Additionally, in-stadium signage advertising may not be as effective in VR sport broadcasting contexts, and sports practitioners may want to explore alternative forms of advertising that are better suited for VR environments.

Methodologically, this study used a combination of self-reported and real-time physiological measures to capture dynamic and spontaneous changes in fans while watching games. Theoretically, this study utilized the Dynamic Human-Centered Communication System Theory to adopt a human-centered approach to understand how VR impacts the experience of sport game viewers.

This chapter reviews the ability of the emerging human performance modeling technologies to support the design and operation of complex systems. The ability of existing technologies to meet current application needs is analyzed, and the results are then used to assess the areas where additional research and development is most needed. Following a brief history of human performance modeling, a taxonomy of models and modeling techniques is established, as a framework for remaining discussion. The human performance modeling technology base is separately analyzed for its ability to support system design processing and to support system operation. The system design process analysis considers the various roles that human performance models may play during that process, ranging from generating design concepts to affording simulation-based range of roles, from training to performance support to automation. These analyses demonstrate that human modeling technology has reached a sufficient state of maturity and has become a proven contributor of the complex systems engineering process. Challenges for further high-payoff research are also presented in five categories: cognition, knowledge management, team and organizational structure and processes, predictive models of training, and human-centered systems engineering.