Value Co-Creation in Smart Services: A Functional Affordances Perspective on Smart Personal Assistants

In the realm of smart services, smart personal assistants (SPAs) have become a popular medium for value co-creation between service providers and users. The market success of SPAs is largely based on their innovative material properties, such as natural language user interfaces, machine learning-powered request handling and service provision, and anthropomorphism. In different combinations, these properties offer users entirely new ways to intuitively and interactively achieve their goals and thus co-create value with service providers. But how does the nature of the SPA shape value co-creation processes? In this paper, we look through a functional affordances lens to theorize about the effects of different types of SPAs (i.e., with different combinations of material properties) on users’ value co-creation processes. Specifically, we collected SPAs from research and practice by reviewing scientific literature and web resources, developed a taxonomy of SPAs’ material properties, and performed a cluster analysis to group SPAs of a similar nature. We then derived 2 general and 11 cluster-specific propositions on how different material properties of SPAs can yield different affordances for value co-creation. With our work, we point out that smart services require researchers and practitioners to fundamentally rethink value co-creation as well as revise affordances theory to address the dynamic nature of smart technology as a service counterpart

Enhancing Literacy Education with Narrative Richness in the Metaverse

Through an education-centric metaverse learning application, this research aims to assess the use of narrative richness to deliver media, language, and sustainability literacy education. The 21st-century learning needs require teaching and learning resources to be shared and managed more effectively across institutions. The use of metaverse features can help to manage varying narrative richness to boost learning reflection and attitude. Despite its potential, it is unclear how narrative richness in the metaverse can enhance teaching and learning. The study proposed in this research, which includes institutions from four Asian countries, is driven by this knowledge and evidence gap. Module leaders conceptualize and evaluate a purpose-built metaverse-learning application to produce rich and realistic learning experiences. We utilize narratives to enhance the realism of learning experiences and will assess the effects of narrative richness on learning reflection and attitude

Design Knowledge for Virtual Learning Companions from a Value-centered Perspective

The increasing popularity of conversational agents such as ChatGPT has sparked interest in their potential use in educational contexts but undermines the role of companionship in learning with these tools. Our study targets the design of virtual learning companions (VLCs), focusing on bonding relationships for collaborative learning while facilitating students’ time management and motivation. We draw upon design science research (DSR) to derive prescriptive design knowledge for VLCs as the core of our contribution. Through three DSR cycles, we conducted interviews with working students and experts, held interdisciplinary workshops with the target group, designed and evaluated two conceptual prototypes, and fully coded a VLC instantiation, which we tested with students in class. Our approach has yielded 9 design principles, 28 meta-requirements, and 33 design features centered around the value-in-interaction. These encompass Human-likeness and Dialogue Management, Proactive and Reactive Behavior, and Relationship Building on the Relationship Layer (DP1,3,4), Adaptation (DP2) on the Matching Layer, as well as Provision of Supportive Content, Fostering Learning Competencies, Motivational Environment, and Ethical Responsibility (DP5-8) on the Service Layer

Performance in the workplace : a critical evaluation of cognitive enhancement

The popular debates about the future organization of work through artificial intelligence technologies focus on the replacement of human beings by novel technologies. In this essay, we oppose this statement by closely following what has been developed as AI technologies and analyzing how they work, specifically focusing on research that may impact work organizations. We develop this argument by showing that the recent research and developments in AI technologies focus on developing accurate and precise performance models, which in turn shapes organizational patterns of work. We propose that the increased interest in the relationship between human cognition and performance will shortly bring human cognition to the focus on AI systems in workplaces. More specifically, we claim that the cognitive load measurement will shape human performance in manufacturing systems shortly

Integrating Artificial Intelligence into Creativity Education: Developing a Creative Problem-Solving Course for Higher Education

This project aims to develop an introductory college course that integrates Artificial Intelligence (AI) to enhance the Creative Problem Solving (CPS) process. Drawing on best practices for teaching CPS and the latest research of AI, the project outcomes are prototypes of a Master Course Development Document, Student Syllabus, and Lesson Plan with accompanying PowerPoint slides. The course will equip students with the knowledge and skills to apply AI techniques to the CPS process. This project aims to begin to bridge the gap between AI and CPS education, preparing students for the demands of the modern workforce while fostering interdisciplinary thinking

Understanding the Role of Interactivity and Explanation in Adaptive Experiences

Adaptive experiences have been an active area of research in the past few decades, accompanied by advances in technology such as machine learning and artificial intelligence. Whether the currently ongoing research on adaptive experiences has focused on personalization algorithms, explainability, user engagement, or privacy and security, there is growing interest and resources in developing and improving these research focuses. Even though the research on adaptive experiences has been dynamic and rapidly evolving, achieving a high level of user engagement in adaptive experiences remains a challenge. %????? This dissertation aims to uncover ways to engage users in adaptive experiences by incorporating interactivity and explanation through four studies. Study I takes the first step to link the explanation and interactivity in machine learning systems to facilitate users\u27 engagement with the underlying machine learning model with the Tic-Tac-Toe game as a use case. The results show that explainable machine learning (XML) systems (and arguably XAI systems in general) indeed benefit from mechanisms that allow users to interact with the system\u27s internal decision rules. Study II, III, and IV further focus on adaptive experiences in recommender systems in specific, exploring the role of interactivity and explanation to keep the user “in-the-loop” in recommender systems, trying to mitigate the ``filter bubble\u27\u27 problem and help users in self-actualizing by supporting them in exploring and understanding their unique tastes. Study II investigates the effect of recommendation source (a human expert vs. an AI algorithm) and justification method (needs-based vs. interest-based justification) on professional development recommendations in a scenario-based study setting. The results show an interaction effect between these two system aspects: users who are told that the recommendations are based on their interests have a better experience when the recommendations are presented as originating from an AI algorithm, while users who are told that the recommendations are based on their needs have a better experience when the recommendations are presented as originating from a human expert. This work implies that while building the proposed novel movie recommender system covered in study IV, it would provide a better user experience if the movie recommendations are presented as originating from algorithms rather than from a human expert considering that movie preferences (which will be visualized by the movies\u27 emotion feature) are usually based on users\u27 interest. Study III explores the effects of four novel alternative recommendation lists on participants’ perceptions of recommendations and their satisfaction with the system. The four novel alternative recommendation lists (RSSA features) which have the potential to go beyond the traditional top N recommendations provide transparency from a different level --- how much else does the system learn about users beyond the traditional top N recommendations, which in turn enable users to interact with these alternative lists by rating the initial recommendations so as to correct or confirm the system\u27s estimates of the alternative recommendations. The subjective evaluation and behavioral analysis demonstrate that the proposed RSSA features had a significant effect on the user experience, surprisingly, two of the four RSSA features (the controversial and hate features) perform worse than the traditional top-N recommendations on the measured subjective dependent variables while the other two RSSA features (the hipster and no clue items) perform equally well and even slightly better than the traditional top-N (but this effect is not statistically significant). Moreover, the results indicate that individual differences, such as the need for novelty and domain knowledge, play a significant role in users’ perception of and interaction with the system. Study IV further combines diversification, visualization, and interactivity, aiming to encourage users to be more engaged with the system. The results show that introducing emotion as an item feature into recommender systems does help in personalization and individual taste exploration; these benefits are greatly optimized through the mechanisms that diversify recommendations by emotional signature, visualize recommendations on the emotional signature, and allow users to directly interact with the system by tweaking their tastes, which further contributes to both user experience and self-actualization. This work has practical implications for designing adaptive experiences. Explanation solutions in adaptive experiences might not always lead to a positive user experience, it highly depends on the application domain and the context (as studied in all four studies); it is essential to carefully investigate a specific explanation solution in combination with other design elements in different fields. Introducing control by allowing for direct interactivity (vs. indirect interactivity) in adaptive systems and providing feedback to users\u27 input by integrating their input into the algorithms would create a more engaging and interactive user experience (as studied in Study I and IV). And cumulatively, appropriate direct interaction with the system along with deliberate and thoughtful designs of explanation (including visualization design with the application environment fully considered), which are able to arouse user reflection or resonance, would potentially promote both user experience and user self-actualization

Using Artificial Intelligence to Circumvent the Teacher Shortage in Special Education: A Phenomenological Investigation

The purpose of this hermeneutic phenomenological research study was to understand district technology leaders’ receptivity to employing artificial co-teachers, based on their lived experiences with Artificial Intelligence (AI). Facing a problematic teacher shortage in special education, the Jade County School District was not readily employing available AI technologies such as IBM’s WATSON and MIT Media Lab’s TEGA, to aide in filling the instructional voids caused by special education teacher attrition. Veblen’s theory of technological determinism provided the necessary framework for this study, which focused on how district technology leaders described their willingness or apprehension to employ autonomous machines to independently instruct students with disabilities in the classroom. This research study was carried out in a large public-school district with a high number of special education teacher vacancies. Purposeful sampling was used to recruit 11 district-level technology leaders who were responsible for developing and sharing a vision for how new technology could be employed to support the needs of students. The principal researcher applied hermeneutic phenomenology to interpret data from photo-elicitations, audio-recorded focus groups, and individual interviews

Service robots in long-term care: a consumer-centric view

Service robots with advanced intelligence capabilities can potentially transform servicescapes. However, limited attention has been given to how consumers experiencing vulnerabilities, particularly those with disabilities, envisage the characteristics of robots’ prospective integration into emotionally-intense servicescapes, such as long-term care (LTC). We take an interdisciplinary approach conducting three exploratory studies with consumers with disabilities involving Community Philosophy, LEGO® Serious Play® and Design Thinking methods. Addressing a lack of consumer-centric research, we offer a three-fold contribution by: 1) developing a conceptualization of consumer-conceived value of robots in LTC, which are envisaged as a supporting resource offering consumers opportunities to realize value; 2) empirically evidencing pathogenic vulnerabilities as a potential value-destruction factor to underscore the importance of integrating service robots research with a service inclusion paradigm; and 3) providing a theoretical extension and clarification of prior characterizations of robots’ empathetic and emotion-related AI capabilities. Consumers with disabilities conceive robots able to stimulate and regulate emotions by mimicking cognitive and behavioral empathy, but unable to express affective and moral empathy, which is central to care experience. While providing support for care practices, for the foreseeable future service robots will not, in themselves, actualize the experience of ‘being cared for.

Towards Supply Chain 5.0: Redesigning Supply Chains as Resilient, Sustainable, and Human-Centric Systems in a Post-pandemic World

From Springer Nature via Jisc Publications RouterHistory: received 2023-03-19, registration 2023-06-08, accepted 2023-06-08, epub 2023-07-29, online 2023-07-29, collection 2023-09Publication status: PublishedStefania Paladini - ORCID: 0000-0002-1526-3589 https://orcid.org/0000-0002-1526-3589The purpose was to investigate the impact of the Industry 5.0 paradigm on the supply chain research field. Our study contributes to the conceptualization of supply chain 5.0, a term that has been receiving increased attention as supply chains adapt to the fifth industrial revolution. We conducted a systematic literature network analysis (SLNA) to examine the research landscape of Industry 5.0 supply chains. We used VOSViewer software and Bibliometrix R-package for multiple bibliometric analyses using 682 documents published between 2016 and 2022. We present a comprehensive framework of supply chain 5.0, including its key concepts, technologies, and trends. Additionally, this research offers a future research agenda to inspire and support further development in this field. We utilized three academic databases for bibliometric analyses: Dimension, Scopus and Lens. Additional databases could provide a wider research landscape and better field representation. We demonstrate how Industry 5.0 enables supply chain evaluation and optimization to assist companies in navigating disruptions without compromising competitiveness and profitability and provide a unique contribution to the field of supply chain 5.0 by exploring promising research areas and guiding the transition to this new paradigm for practitioners and scholars.pubpu

Shaping the future: the inhumanity of planetary calculation or how to live with digital uncertainty

Planetary computation. An epochal shift rewires humanity by impacting on our capacity to feel, to perceive, to sense and to think. Far from being a mere matter of speed of communication, this change has to do with the creation of new interlocking ecologies where information is sensed and the cognitive, perceptual and affective spheres mutate. Sensation prevails on signification. Data becomes us. Mediation shifts to immediation. This is the 4th Revolution when the digital-online world spills into and merges with the analogue-offline world. In this onlife experience, data is the new currency, code is synchronized to the human and the infosphere becomes synonymous with reality.1 The proliferation of smartalgorithmic environments evolving in real time, the colonization of daily life by social networks, the tsunami of data, the unstoppable googlification of knowledge together create new ecologies of cohabitation and coevolution of the human with the nonhumanity of planetary computation. Given this scenario, two questions emerge as urgent. What is the impact ofthe ongoing informatization of bodies, artefacts and environments on the whole of human cognition, affectivity and perceptual faculties? What kind of narratives, images and fictions are needed to make sense of the ecologies we now inhabit, populated by agents on a continuum between the human and the nonhuman, a mix of the human with machines, dataflows, codes, algorithms; strange entanglements of silicon and carbon