A metaverse is a virtual shared space connected to the real world, an alternative reality that enables economic activities, exchanges, and transactions as well as formation of relationships between user avatars and non-player characters (NPCs). Initial experiences of the metaverse were not very satisfactory; new virtual world metaverses may or may not survive as information services or platforms. The purpose of this empirical study is to identify the characteristics of a virtual world metaverse and their effects on intention to continue usage of the platform. Considering the metaverse as a new type of user experience and a powerful mode of communication, we examine the mediating role of these characteristics according to Pine and Gilmore's (1998) experience economy theory, which enriches our understanding of the factors affecting the success of a metaverse. In addition, since social interaction is important in metaverses, we extend Pine and Gilmore's experience economy model by including Schmitt's (2011) relate experience for better understanding.

Drawing on the MOA framework, this study establishes a research model that explains the usage intention of robo-advisors. In the model, three predictors that consist of technology relative advantage, technology herding, and technology familiarity influence usage intention of robo-advisors directly and indirectly via the partial mediation of trust. At the same time, the effects of the three predictors on trust are hypothetically moderated by learning goal orientation and perceived performance risk respectively. Statistical analyses are provided using the data of working professionals from the insurance industry in Taiwan. Based on its empirical findings, this study discusses important theoretical and practical implications.

The study investigated the influence of ebullient supervision on employee commitment in a Ghanaian public university through the mediating role of employee engagement. The simple random sampling technique was used to draw 302 administrative staff of the university to respond to the self-administered questionnaire on the constructs. Furthermore, the partial least square structural equation technique was deployed to test the research hypotheses in the study. The results showed that ebullient supervision had a significant positive relationship with employee commitment and employee engagement. The findings further revealed that employee engagement positively correlated with employee commitment. Finally, the study's findings established that employee engagement partially mediated the link between ebullient supervision and employee commitment. The study emphasised that various supervisors in a university's administration should create an environment that favours fun where subordinates can form ties with one another.

Aim/Purpose: Although many computer science measures have been proposed, visualizing individual students’ capabilities is difficult, as those measures often rely on specific tools and methods or are not graded. To solve these problems, we propose a rubric for measuring and visualizing the effects of learning computer programming for elementary school students enrolled in computer science education (CSE), which is independent of the programming language being used. Background: In this research, we proposed a rubric based on existing CSE standards and criteria having a programming education-learning goal. We then applied this rubric to actual lessons to visualize the educational effects. Methodology: The proposed new rubric for teaching computer programming, based on existing standards and criteria, was applied to fourth- and sixth-grade students in Japan. We assessed which skills were cultivated through quizzes before and after the teaching. Contribution: This paper contributes on how to make and utilize a rubric for programming education in computer science. We evaluated and visualized the proposed rubric’s learning effects on children and found that our proposed rubrics are independent of any particular method or tool. Findings: The results of this survey are twofold: (1) we proposed a rubric of programming education in computer science, independent of the programming tools used and (2) we succeeded in visualizing students’ learning stages by applying the proposed rubric to programming education conducted in a Japanese elementary school. Recommendations for Practitioners: Evaluating educational effects in CSE is important. In particular, graded assessments of learner abilities can reveal individual characteristics. This research is useful for assessing CSE because it focuses specifically on programming education. Recommendation for Researchers: The rubric’s suggestions and quality improvements in CSE help learners assess their learning progress and will clarify the cultivated computer science skills. Impact on Society: This research evaluates CSE based on a rubric in the programming education field. Future Research: Future work is needed to improve the proposed rubric’s quality and relevance. Also, this rubric should be applied to many classes to increase the number of evaluations and analyses.

To better explore the application of unsupervised learning neural networks in psychological interventions for college students, this study investigates the relationships among latent psychological variables from the perspective of neural networks. Firstly, college students' psychological crisis and intervention systems are analysed, identifying several shortcomings in traditional psychological interventions, such as a lack of knowledge dissemination and imperfect management systems. Secondly, employing the Human-Computer Interaction (HCI) approach, a structural equation model is constructed for unsupervised learning neural networks. Finally, this study further confirms the effectiveness of unsupervised learning neural networks in psychological interventions for college students. The results indicate that in psychological intervention for college students. Additionally, the weightings of the indicators at the criterion level are calculated to be 0.35, 0.27, 0.19, 0.11 and 0.1. Based on the results of HCI, an emergency response system for college students' psychological crises is established, and several intervention measures are proposed.

Voice Activity Detection (VAD) distinguishes speech segments from noise or silence areas. An efficient and noise-robust VAD system can be widely used for emerging speech technologies such as wireless communication and speech recognition. In this paper, we propose two versions of an unsupervised Arabic VAD method based on the combination of the Short-Time Energy (STE) and the Spectral Centroid (SC) features for formulating a typical threshold to detect speech areas. The first version compares only the STE feature to the threshold (STE-VAD). In contrast, the second compares the SC vector and the threshold (SC-VAD). The two versions of our VAD method were tested on 770 sentences of the Arabphone corpus, which were recorded in clean and noisy environments and evaluated under different values of Signal-to-Noise-Ratio. The experiments demonstrated the robustness of the STE-VAD in terms of accuracy and Mean Square Error.

Students in teaching-focused business-schools need a level of assistance and advisement broader and more profound than what is needed in R1&R2 schools. We investigate the informal interdependencies among marketing, finance, operation, and management core courses in these schools. By conducting hypothesis tests on a large dataset, we identify a flexible network showing the preferred sequencing of these courses to improve students' performance as measured by the course grade. Better performances in this context may also lead to higher retention-rates and lower time-to-degree. We recommend taking Finance or Finance and Management as the first course(s). Marketing should be the next course before or concurrent with Operations Management. Regarding the lower division courses, it is recommended to take Statistics before Economics and Accounting courses and Accounting before or concurrent with Economics. We also consider the significant role of a milestone course that links the lower division and core courses.

As academia in general, and research funders in particular, place ever greater importance on data as an output of research, so the value of good research data management practices becomes ever more apparent. In response to this, the Innovative Design and Manufacturing Research Centre (IdMRC) at the University of Bath, UK, with funding from the JISC, ran a project to draw up a data management planning regime. In carrying out this task, the ERIM (Engineering Research Information Management) Project devised a visual method of mapping out the data records produced in the course of research, along with the associations between them. This method, called Research Activity Information Development (RAID) Modelling, is based on the Unified Modelling Language (UML) for portability. It is offered to the wider research community as an intuitive way for researchers both to keep track of their own data and to communicate this understanding to others who may wish to validate the findings or re-use the data.

The article describes the integrated adoption of Fedora Commons and MediaMosa for managing a digital repository. The integration was experimented along with the development of a cooperative project, Sapienza Digital Library (SDL). The functionalities of the two applications were exploited to built a weaving factory, useful for archiving, preserving and disseminating of multi-format and multi-protocol audio video contents, in different fruition contexts. The integration was unleashed by means of both repository-to-repository interaction, and mapping of video Content Model's disseminators to MediaMosa's Restful services. The outcomes of this integration will lead to a more flexible management of the dissemination services, as well as to economize the overproduction of different dissemination formats.

In 2008 the University of Hull, Stanford University and University of Virginia decided to collaborate with Fedora Commons (now DuraSpace) on the Hydra project. This project has sought to define and develop repository-enabled solutions for the management of multiple digital content management needs that are multi-purpose and multi-functional in such a way as to allow their use across multiple institutions. This article describes the evolution of Hydra as a project, but most importantly as a community that can sustain the outcomes from Hydra and develop them further. The data modelling and technical implementation are touched on in this context, and examples of the Hydra heads in development or production are highlighted. Finally, the benefits of working together, and having worked together, are explored as a key element in establishing a sustainable open source solution.

The study aims to review the literature on mobile wallet payment and align research trends using a systematic literature review with bibliometric and network visualisation analysis over two decades. It uses bibliometric analysis of the literature research retrieved from the Web of Science database. The study period was from 2001 to 2021, with 1,134 research papers. It also provides the indicators like citation trends, cited reference patterns, authorship patterns, subject areas published on the mobile wallet, top contributing authors, and highly cited research articles using the database. Furthermore, network visualisation analysis, like the co-occurrence of author keywords and keywords plus terms, has also been examined using VOSviewer software. The bibliometric analysis shows that the Republic of China dominates mobile wallet payment, and India is a significant contributor. Furthermore, the constructions of the network map using a co-citation analysis and bibliographic coupling shows an interesting pattern of mobile wallet payment.

Aim/Purpose: The purpose of this paper is to illuminate the learning that happens in assuming a supervisee’s role during the postgraduate study. Background: The facilitators and barriers students encountered while pursuing postgraduate studies, strategies to achieve success in postgraduate studies, and how to decrease attrition rates of students, have been sufficiently explored in literature. However, there is little written about the personal and professional impact on students when they are being supervised to complete their postgraduate studies. Methodology: Autoethnographic method of deep reflection was used to examine the learning that transpired from the supervisee’s perspective. Two lecturers (a Senior Lecturer in Nursing and an Aboriginal Tutor) focused on their postgraduate journeys as supervisees, respectively, with over 30 years of study experience between them, in Australia and abroad. Contribution: Future postgraduate students, researchers, would-be supervisors and experienced supervisors could learn from the reflections of the authors’ postgraduate experiences. Findings: Four themes surfaced, and these were Eureka moments, Critical friend(s), Supervisory relationship, and Transformative learning. The authors highlighted the significance of a supervisory relationship which is key to negotiating the journey with the supervisor. Essential for these students also were insights on finding the path as well as the destination and the transformative aspects that happened as a necessary part of the journey. Conclusion. The postgraduate journey has taught them many lessons, the most profound of which was the change in perspective and attitude in the process of being and becoming. Personal and professional transformative learning did occur. At its deepest level, the authors’ reflections resulted in self-actualization and a rediscovery of their more authentic selves. Recommendations for Practitioners: This article highlights the importance of the supervisory relationship that must be negotiated to ensure the success of the candidate. Reflections of the transformation are recommended to support the students further. Recommendation for Researchers: Quality supervision can make a significant influence on the progress of students. Further research on the supervisory relationship is recommended. Impact on Society: The support in terms of supervision to ensure postgraduate students’ success is essential. Postgraduate students contribute to the human, social, professional, intellectual, and economic capital of universities and nations globally. Future Research: Further reflections of the transformative learning will advance the understanding of the personal and professional changes that occur with postgraduate supervision.

Aim/Purpose. This study examined the self-perception of adolescents and young people aged 17-21 – how they perceived their personal characteristics, self-image, vitality, belonging to a local and global (glocal) society, happiness index and activity, media usage habits in general and smartphones in particular – in other words, it sought to produce a sketch of their character. Background. Different age groups are influenced by various factors that shape them, including living environment, technological developments, experiences, common issues, events of glocal significance, and more. People belonging to Gen Z were born at the end of the previous century and the beginning of the 21st century (up to 2010). This generation was born into the digital technological age and is the first one born into the environment defined by smartphones, and social media. Its members are referred to as “digital natives” because they were born after the widespread adoption of digital technology in the Western world. They entered an environment characterized by the widespread daily use of smartphones, the Internet, and technology in general. Methodology. This was a quantitative study based on a sample of 418 Israeli adolescents and young people aged 17-21. The following questionnaires were administered anonymously and disseminated online to an audience of youths aged 17-21 across Israel: A demographic questionnaire; Self-esteem; Vitality; Belonging vs. alienation; Social-emotional aspects; Usage habits in digital environments; Usage habits of learning on a smartphone; Open questions. Contribution. The current study tried to define clusters to characterize adolescents and youth aged 17-21. Findings Results show that study participants had high self-esteem and vitality, felt be-longing, happy, and satisfied with their life, and perceived themselves as active and enterprising at an average level or above. The study identified two clusters. Participants in Cluster 1 were characterized by higher parameter averages than those in Cluster 2 on the self-image, vitality, belonging, happiness, and activism scales. Participants in Cluster 1 felt that using a smartphone made life easier, helped them solve everyday problems, made everyday conduct easier, and allowed them to express themselves, keep up to date with what is happening with their friends, disseminate information conveniently, be involved in social life, and establish relationships with those around them. They thought that it was easy to collaborate with others and to plan activities and events. Recommendations for Practitioners. When examining cluster correlations with data in relation to other variables, it is apparent that participants in Cluster 1 had more options to reach out for help, report more weekly hours spent talking and meeting with friends and feel that using a smartphone makes everyday life easier and facilitates their day-to-day conduct than did participants in Cluster 2. The smartphone allows them to express themselves, keep updated regarding what is happening with their friends and disseminate information easily, helps them be involved in social life and establish connections with those around them. They find it easy to communicate and cooperate with others and to plan activities and events. By contrast, participants in Cluster 2 felt that the smartphone complicates things for them and creates problems in their daily lives. They feel that the use of social networks burdens them and that the smartphone prevents them from being more involved in their social life, and from establishing relationships with those around them. They felt that communication by smartphone creates more problems in understanding messages. Recommendations for Researchers. One of the challenges of this generation is forming an independent identity and self-regulation in a digital, global, across-the-border era that offers a variety of possibilities and communities. They must examine the connection between the digital and personal spaces, to be able to enjoy virtual communities and a sense of togetherness, and at the same time maintain privacy, autonomy, and individuality. Many studies point to the blurring of boundaries between the private-personal and the public, at numerous problems in social networks, including social problems, shaming, and exclusion from various groups and activities. The fear of shaming and the desire to keep up with everything that is happening create a state of mental stress, and adolescents often feel that they urgently need to check their smartphones. Sharing with others can help them deal with negative content and experiences and avoid the dangers lurking in their web surfing. Yet sharing, especially with friends, often causes intimate content to become public and leads to shaming and invasion of privacy. Impact on Society. Gen Z was born into an environment where smartphones, the Internet, and technology in general, are widely used in everyday routine, and they make extensive use of technological means in all areas of life. One of the characteristics of this generation is “globalization.” The present study showed that about 84% of participants felt to a moderate degree or higher that they were citizens of the world. Future Research. The findings of this study revealed a significant difference in self-image between males and females. An attempt was made to explain the findings in light of previous studies, but the need arose for studies on the self-image of young people of Gen Z that would shed light on the subject.

Aim/Purpose: This journal paper seeks to understand historical aspects of data management, leading to the current data issues faced by organizational executives in relation to big data and how best to present the information to circumvent big data challenges for executive strategic decision making. Background: This journal paper seeks to understand what executives value in data visualization, based on the literature published from prior data studies. Methodology: The qualitative methodology was used to understand the sentiments of executives and data analysts using semi-structured interview techniques. Contribution: The preliminary findings can provide practical knowledge for data visualization designers, but can also provide academics with knowledge to reflect on and use, specifically in relation to information systems (IS) that integrate human experience with technology in more valuable and productive ways. Findings: Preliminary results from interviews with executives and data analysts point to the relevance of understanding and effectively presenting the data source and the data journey, using the right data visualization technology to fit the nature of the data, creating an intuitive platform which enables collaboration and newness, the data presenter’s ability to convey the data message and the alignment of the visualization to core the objectives as key criteria to be applied for successful data visualizations Recommendations for Practitioners: Practitioners, specifically data analysts, should consider the results highlighted in the findings and adopt such recommendations when presenting data visualizations. These include data and premise understanding, ensuring alignment to the executive’s objective, possessing the ability to convey messages succinctly and clearly to the audience, having knowledge of the domain to answer questions effectively, and using the right technology to convey the message. Recommendation for Researchers: The importance of human cognitive and sensory processes and its impact in IS development is paramount. More focus can be placed on the psychological factors of technology acceptance. The current TAM model, used to describe use, identifies perceived usefulness and perceived ease-of-use as the primary considerations in technology adoption. However, factors that have been identified that impact on use do not express the importance of cognitive processes in technology adoption. Future Research: Future research requires further focus on intangible and psychological factors that could affect technology adoption and use, as well as understanding data visualization effectiveness in corporate environments, not only predominantly within the Health sector. Lessons from Health sector studies in data visualization should be used as a platform.

Aim/Purpose: In this research, we examined the influence of the information system (IS) quality dimensions proposed by Wixom and Todd on reading satisfaction of online newspaper readers in Bangladesh, especially the readers’ intention to revisit and recommendations through electronic word-of-mouth (eWOM). Background: We identified the top 50 most visited websites, of which 13 were online newspapers, although their ranking among Bangladesh online newspapers varies from month to month. The literature illustrates that, despite the wide availability of online news portals and the fluctuations in frequency of visits, little is known about the factors that affect the satisfaction, word-of-mouth, and frequency of visits of readers. An understanding of reader satisfaction will help to gain richer insights into the phenomenon of readers’ intention to revisit and recommendation by eWOM. Stakeholders of online newspapers can then focus on those factors to increase visits to their websites, which will help them attract online advertisements from different organisations. Methodology: Data were collected using a structured questionnaire, from 217 people who responded to the survey. We used SmartPLS 3 to analyze the data collected, as it is based on second-generation analysis, which in turn is based on structural equation modeling (SEM). Contribution: This research explores the impacts of technological dimensions on readers’ satisfaction, as most of the previous research has focused on cultural or social dimensions. Findings: The results supported all of the hypothesized relationships between technological dimensions and reader satisfaction with online newspapers, except for one. The first, information, was predicted with accuracy and completeness, while the second object-based belief, system quality, was predicted by its accessibility, flexibility, reliability, and timeliness. Overall, quality factors influencing readers’ satisfaction were shown to lead to word-of-mouth revisit intentions. Our proposed model was empirically tested and has contributed to a nascent body of knowledge about readers’ revisit intentions and eWOM recommendations regarding online newspapers. It was also shown that strong satisfaction leads to higher revisit intention and eWOM. Recommendations for Practitioners: To keep the users satisfied, online newspapers need to focus on improving information quality (IQ) and system quality (SQ). If they do this well, they will be rewarded with higher revisit intention and recommendations by eWOM. Recommendation for Researchers: This study extends Oh’s customer loyalty model by integrating the Wixom-Todd model. This study reinforces an alternative rationale of the construct satisfaction. Future Research: We ignored negative stimulus like technostress, which can have an impact on satisfaction. In future, we will test the relationship between technostress and its impact on online newspaper reading.

Aim/Purpose: This study describes a conceptual model, based on the principles of concept algebra that can provide intelligent academic advice using adaptive, knowledge-based feedback. The proposed model advises students based on their traits and academic history. The system aims to deliver adaptive advice to students using historical data from previous and current students. This data-driven approach utilizes a cognitive knowledge-based (CKB) model to update the weights (values that indicate the strength of relationships between concepts) that exist between student’s performances and recommended courses. Background: A research study conducted at the Public Authority for Applied Education and Training (PAAET), a higher education institution in Kuwait, indicates that students’ have positive perceptions of the e-Advising system. Most students believe that PAAET’s e-Advising system is effective because it allows them to check their academic status, provides a clear vision of their academic timeline, and is a convenient, user-friendly, and attractive online service. Student advising can be a tedious element of academic life but is necessary to fill the gap between student performance and degree requirements. Higher education institutions have prioritized assisting undecided students with career decisions for decades. An important feature of e-Advising systems is personalized feedback, where tailored advice is provided based on students' characteristics and other external parameters. Previous e-Advising systems provide students with advice without taking into consideration their different attributes and goals. Methodology: This research describes a model for an e-Advising system that enables students to select courses recommended based on their personalities and academic performance. Three algorithms are used to provide students with adaptive course selection advice: the knowledge elicitation algorithm that represents students' personalities and academic information, the knowledge bonding algorithm that combines related concepts or ideas within the knowledge base, and the adaptive e-Advising model that recommends relevant courses. The knowledge elicitation algorithm acquires student and academic characteristics from data provided, while the knowledge bonding algorithm fuses the newly acquired features with existing information in the database. The adaptive e-Advising algorithm provides recommended courses to students based on existing cognitive knowledge to overcome the issues associated with traditional knowledge representation methods. Contribution: The design and implementation of an adaptive e-Advising system are challenging because it relies on both academic and student traits. A model that incorporates the conceptual interaction between the various academic and student-specific components is needed to manage these challenges. While other e-Advising systems provide students with general advice, these earlier models are too rudimentary to take student characteristics (e.g., knowledge level, learning style, performance, demographics) into consideration. For the online systems that have replaced face-to-face academic advising to be effective, they need to take into consideration the dynamic nature of contemporary students and academic settings. Findings: The proposed algorithms can accommodate a highly diverse student body by providing information tailored to each student. The academic and student elements are represented as an Object-Attribute-Relationship (OAR) model. Recommendations for Practitioners: The model proposed here provides insight into the potential relationships between students’ characteristics and their academic standing. Furthermore, this novel e-Advising system provides large quantities of data and a platform through which to query students, which should enable developing more effective, knowledge-based approaches to academic advising. Recommendation for Researchers: The proposed model provides researches with a framework to incorporate various academic and student characteristics to determine the optimal advisory factors that affect a student’s performance. Impact on Society: The proposed model will benefit e-Advising system developers in implementing updateable algorithms that can be tested and improved to provide adaptive advice to students. The proposed approach can provide new insight to advisors on possible relationships between student’s characteristics and current academic settings. Thus, providing a means to develop new curriculums and approaches to learning. Future Research: In future studies, the proposed algorithms will be implemented, and the adaptive e-Advising model will be tested on real-world data and then further improved to cater to specific academic settings. The proposed model will benefit e-Advising system developers in implementing updateable algorithms that can be tested and improved to provide adaptive advisory to students. The approach proposed can provide new insight to advisors on possible relationships between student’s characteristics and current academic settings. Thus, providing a means to develop new curriculums and approaches to course recommendation.

Aim/Purpose: This study investigated a model of mobile esports acceptance among urban citizens based on an extended Technology Acceptance Model (TAM). Background: Currently, esports are increasingly popular and in demand by the public. Supported by the widespread development of mobile devices, it has become an interactive market trend to play games in a new model, mobile esports. Methodology: This study collected data from 400 respondents and analyzed it using partial least squares-structural equation modeling (PLS-SEM). Contribution: This study addresses two research gaps. The first gap is limited esports information systems studies, particularly in mobile esports acceptance studies. The second gap is limited exploration of external variables in online gaming acceptance studies. Thus, this study proposed a TAM extended model by integrating the TAM native variables with other external variables such as visual appeal, enjoyment, social interaction, and competition to explore mobile esports acceptance by urban citizens. Findings: Nine hypotheses were accepted, and four were rejected. The visual appeal did not affect the acceptance. Meanwhile, social interaction and enjoyment significantly affected both perceived ease of use and usefulness. However, perceived ease of use surprisingly had an insignificant effect on attitude toward using mobile esports. Moreover, competition significantly affected the acceptance, particularly on perceived usefulness. Recommendations for Practitioners: Fresh and innovative features, such as new game items or themes, should be frequently introduced to enhance players’ continued enjoyment. Moreover, mobile esports providers should offer a solid platform to excite players’ interactions to increase the likelihood that users feel content. On the other hand, the national sports ministry/agency or responsible authorities should organize many esports competitions, big or small, to search for new talents. Recommendation for Researchers: Visual appeal in this study did not influence the perceived ease of use or usefulness. However, it could affect enjoyment. Thus, it would be worth revisiting the relationship between visual appeal and enjoyment. At the same time, perceived ease of use is a strong driver for the continued use of most online games, but not in this study. It could indicate significant differences between mobile esports and typical online games, one of which is the different purposes. Users might play online games for recreational intention, but players would use mobile esports to compete, win, or even get monetary rewards. Therefore, although users might find mobile esports challenging and hard to use, they tend to keep playing it. Thus, monetary rewards could be considered a determinant of the continuation of use. Impact on Society: Nowadays, users are being paid for playing games. It also would be an excel-lent job if they become professional esports athletes. This study investigated factors that could affect the continued use of mobile esports. Like other jobs, playing games professionally in the long term could make the players tedious and tired. Therefore, responsible parties, like mobile esports providers or governments, could use the recommendations of this study to promote positive behavior among the players. They will not feel like working and still con-sider playing mobile esports a hobby if they happily do the job. In the long run, the players could also make a nation’s society proud if they can be a champion in prestigious competitions. Future Research: A larger sample size will be needed to generalize the results, such as for a nation. It is also preferable if the sample is randomized systematically. Future works should also investigate whether the same results are acquired in other mobile esports. Furthermore, to extend our knowledge and deepen our understanding of the variables that influence mobile esports adoption, the subsequent research could look at other mobile esports acceptability based on characteristics of system functionality and moderator effects. Finally, longitudinal data-collecting approaches are suggested for future studies since behavior can change over time.

Aim/Purpose: The rise of modern artificial intelligence (AI), in particular, machine learning (ML), has provided new opportunities and directions for knowledge management (KM). A central question for the future of KM is whether it will be dominated by an automation strategy that replaces knowledge work or whether it will support a knowledge-enablement strategy that enhances knowledge work and uplifts knowledge workers. This paper addresses this question by re-examining and updating a critical argument against KM by the sociologist of science Steve Fuller (2002), who held that KM was extractive and exploitative from its origins. Background: This paper re-examines Fuller’s argument in light of current developments in artificial intelligence and knowledge management technologies. It reviews Fuller’s arguments in its original context wherein expert systems and knowledge engineering were influential paradigms in KM, and it then considers how the arguments put forward are given new life in light of current developments in AI and efforts to incorporate AI in the KM technical stack. The paper shows that conceptions of tacit knowledge play a key role in answering the question of whether an automating or enabling strategy will dominate. It shows that a better understanding of tacit knowledge, as reflected in more recent literature, supports an enabling vision. Methodology: The paper uses a conceptual analysis methodology grounded in epistemology and knowledge studies. It reviews a set of historically important works in the field of knowledge management and identifies and analyzes their core concepts and conceptual structure. Contribution: The paper shows that KM has had a faulty conception of tacit knowledge from its origins and that this conception lends credibility to an extractive vision supportive of replacement automation strategies. The paper then shows that recent scholarship on tacit knowledge and related forms of reasoning, in particular, abduction, provide a more theoretically robust conception of tacit knowledge that supports the centrality of human knowledge and knowledge workers against replacement automation strategies. The paper provides new insights into tacit knowledge and human reasoning vis-à-vis knowledge work. It lays the foundation for KM as a field with an independent, ethically defensible approach to technology-based business strategies that can leverage AI without becoming a merely supporting field for AI. Findings: Fuller’s argument is forceful when updated with examples from current AI technologies such as deep learning (DL) (e.g., image recognition algorithms) and large language models (LLMs) such as ChatGPT. Fuller’s view that KM presupposed a specific epistemology in which knowledge can be extracted into embodied (computerized) but disembedded (decontextualized) information applies to current forms of AI, such as machine learning, as much as it does to expert systems. Fuller’s concept of expertise is narrower than necessary for the context of KM but can be expanded to other forms of knowledge work. His account of the social dynamics of expertise as professionalism can be expanded as well and fits more plausibly in corporate contexts. The concept of tacit knowledge that has dominated the KM literature from its origins is overly simplistic and outdated. As such, it supports an extractive view of KM. More recent scholarship on tacit knowledge shows it is a complex and variegated concept. In particular, current work on tacit knowledge is developing a more theoretically robust and detailed conception of human knowledge that shows its centrality in organizations as a driver of innovation and higher-order thinking. These new understandings of tacit knowledge support a non-extractive, human enabling view of KM in relation to AI. Recommendations for Practitioners: Practitioners can use the findings of the paper to consider ways to implement KM technologies in ways that do not neglect the importance of tacit knowledge in automation projects (which neglect often leads to failure). They should also consider how to enhance and fully leverage tacit knowledge through AI technologies and augment human knowledge. Recommendation for Researchers: Researchers can use these findings as a conceptual framework in research concerning the impact of AI on knowledge work. In particular, the distinction between replacement and enabling technologies, and the analysis of tacit knowledge as a structural concept, can be used to categorize and analyze AI technologies relative to KM research objectives. Impact on Society: The potential of AI on employment in the knowledge economy is a major issue in the ethics of AI literature and is widely recognized in the popular press as one of the pressing societal risks created by AI and specific types such as generative AI. This paper shows that KM, as a field of research and practice, does not need to and should not add to the risks created by automation-replacement strategies. Rather, KM has the conceptual resources to pursue a (human) knowledge enablement approach that can stand as a viable alternative to the automation-replacement vision. Future Research: The findings of the paper suggest a number of research trajectories. They include: Further study of tacit knowledge and its underlying cognitive mechanisms and structures in relation to knowledge work and KM objectives. Research into different types of knowledge work and knowledge processes and the role that tacit and explicit knowledge play. Research into the relation between KM and automation in terms of KM’s history and current technical developments. Research into how AI arguments knowledge works and how KM can provide an enabling framework.

The article presents Personal Knowledge Management (PKM) as an overdue individualized as well as a collaborative approach for knowledge workers. Designing a PKM-supporting system, however, resembles a so-called “wicked” problem (ill-defined; incomplete, contradictory, changing requirements, complex interdependencies) where the information needed to understand the challenges depends on upon one’s idea for solving them. Accordingly, three main areas are attended to. Firstly, in dealing with a range of growing complexities, the notion of Popper’s Worlds is applied as three distinct spheres of reality and further expanded into six digital ecosystems (technologies, extelligence, society, knowledge worker, institutions, and ideosphere) that not only form the basis for the PKM System Concept named ‘Knowcations’ but also form a closely related Personal Knowledge Management for Development (PKM4D) framework detailed in a separate dedicated paper. Reflecting back on a United Nations scenario of knowledge mass production (KMP) over time, the complexities closely related to the digital ecosystems and the inherent risks of today’s accelerating attention-consuming over-abundance of redundant information are scrutinized, concluding in a chain of meta-arguments favoring the idea of the PKM concept and system put forward. Secondly, in light of the digital ecosystems and complexities introduced, the findings of a prior article are further refined in order to assess the PKM concept and system as a potential General-Purpose-Technology. Thirdly, the development process and resulting prototype are verified against accepted general design science research (DSR) guidelines. DSR aims at creating innovative IT artifacts (that extend human and social capabilities and meet desired outcomes) and at validating design processes (as evidence of their relevance, utility, rigor, resonance, and publishability). Together with the incorporated references to around thirty prior publications covering technical and methodological details, a kind of ‘Long Discussion Case’ emerges aiming to potentially assist IT researchers and entrepreneurs engaged in similar projects.

Aim/Purpose: The main aim of the research is to examine the performance of second language English speaking students enrolled in the Business Statistics course and to investigate the academic performance of students when taught under the constructivist and non-constructivist approaches in a classroom environment. Background: There are different learning theories that are established based on how students learn. Each of these theories has its own benefits based on the different type of learners and context of the environment. The students in this research are new to the University environment and to a challenging technical course like Business Statistics. This research has been carried out to see the effectiveness of the constructivist approach in motivating and increasing the student engagement and their academic performance. Methodology : A total of 1373 students were involved in the quasi-experiment method using Stratified Sampling Method from the year 2015 until 2016. Contribution: To consider curriculum adjustments for first year programs and implications for teacher education. Findings: The t-test for unequal variances was used to understand the mean score. Results indicate students have high motivation level and achieve higher mean scores when they are taught using the constructivist teaching approach compared to the non-constructivist teaching approach. Recommendations for Practitioners: To consider the challenges faced by first year students and create a teaching approach that fits their needs. Recommendation for Researchers: To explore in depth other teaching approaches of the Business Statistics course in improving students’ academic performance. Impact on Society : The constructivist approach will enable learning to be enjoyable and students to be more confident. Future Research: The research will assist other lectures teaching Business Statistics in creating a more conducive environment to encourage second language English speaking students to overcome their shyness and be more engaged.

Aim/Purpose: Personal Knowledge Management (PKM) has been envisaged as a crucial tool for the growing creative class of knowledge workers, but adequate technological solutions have not been forthcoming. Background: Based on former affordance-related publications (primarily concerned with communication, community-building, collaboration, and social knowledge sharing), the common and differing narratives in relation to PKM are investigated in order to suggest further PKM capabilities and affordances in need to be conferred. Methodology: The paper follows up on a series of the author’s PKM-related publications, firmly rooted in design science research (DSR) methods and aimed at creating an innovative PKM concept and prototype system. Contribution: The affordances presented offer PKM system users the means to retain and build upon knowledge acquired in order to sustain personal growth and facilitate productive collaborations between fellow learners and/or professional acquaintances. Findings: The results call for an extension of Nonaka’s SECI model and ‘ba’ concept and provide arguments for and evidence supporting the claims that the PKM concept and system is able to facilitate better knowledge traceability and KM practices. Recommendations and Impact on Society: Together with the prior publications, the paper points to current KM shortcomings and presents a novel trans-disciplinary approach offering appealing opportunities for stakeholders engaged in the context of curation, education, research, development, business, and entrepreneurship. Its potential to tackle opportunity divides has been addressed via a PKM for Development (PKM4D) Framework. Future DSR Activities: After completing the test phase of the prototype, its transformation into a viable PKM system and cloud-based server based on a rapid development platform and a noSQL-database is estimated to take 12 months.

Aim/Purpose: This paper describes an empirical examination of how users’ willingness to disclose personal data is influenced by the amount of information provided on landing pages – standalone web pages created explicitly for marketing or advertising campaigns. Background: Provision of information is a central construct in the IS discipline. Content is a term commonly used to describe the information made available by a website or other electronic medium. A pertinent debate among scholars and practitioners relate to the behavioral impact of content volume: Specifically, does a greater amount of information elicit engagement and compliance, or the other way around? Methodology: A series of large-scale web experiments (n= 535 and n= 27,900) were conducted employing a between-subjects design and A/B testing. Two variants of landing pages, long and short, were created based on relevant behavioral theories. Both variants included an identical form to collect users’ information, but different amounts of provided content. User traffic was generated using Google AdWords and randomized between the page using Unbounce.com. Relevant usage metrics, such as response rate (called “conversion rate”), location, and visit time were recorded. Contribution: This research contributes to the body of knowledge on information provision and its effectiveness and carries practical and theoretical implications to practitioners and scholars in Information Systems, Informing Science, Communications, Digital Marketing, and related fields. Findings: Analyses of results show that the shorter landing pages had significantly higher conversion rates across all locations and times. Findings demonstrate a negative correlation between the content amount and consumer behavior, suggesting that users who had less information were more inclined to provide their data. Recommendations for Practitioners: At a practical level, results can empirically support business practices, design considerations, and content strategy by informing practitioners on the role of content in online commerce. Recommendation for Researchers: Findings suggest that the amount of content plays a significant role in online decision making and effective informing. They also contradict prior research on trust, persuasion, and security. This study advances research on the paradoxical relationship between the increased level of information and online decision-making and indicates that contrary to earlier work, not all persuasion theories‎ are ‎effective online. Impact on Society: Understanding how information drives behavior has implications in many domains (civic engagement, health, education, and more). This has relevance to system design and public communication in both online and offline contexts. Future Research: Using this research as a starting point, future research can examine the impact of content in other contexts, as well as other behavioral drivers (such as demographic data). This can lead to theoretical, methodological, and practical recommendations.

Lihan TONG,Weijia LI,Qingxia YANG,Liyuan CHEN,Peng CHEN, Vol.E107-D, No.11, pp.1472-1475
We present Ksformer, utilizing Multi-scale Key-select Routing Attention (MKRA) for intelligent selection of key areas through multi-channel, multi-scale windows with a top-k operator, and Lightweight Frequency Processing Module (LFPM) to enhance high-frequency features, outperforming other dehazing methods in tests.
Publication Date: 2024/11/01

Building on prior work showing that abusive supervision is a reaction to subordinates' poor performance, we develop a self-control framework to outline when and why supervisors abuse poor performing subordinates. In particular, we argue poor performing subordinates instill in supervisors a sense of hostility towards the subordinate, which in turn leads to engaging in abusive supervision. Within this self-control framework, poor performance is more likely to lead to abusive supervision when (a) the magnitude of the hostility experienced is higher (e.g., for those with a hostile attribution bias), or (b) the translation of hostility into abusive supervision is unconstrained (e.g., for those who are low in trait mindfulness). In two experimental studies with full-time supervisors where we manipulated the independent variable (Study 1) and the mediator (Study 2), and in a multi-wave and multi-source field study with data collected from supervisor-subordinate teams (50 supervisors and 206 subordinates) at two time points (Study 3), we found overall support for our predictions. Implications for how to reduce the occurrence of abusive supervision in the workplace are discussed.

Growing workforce diversity increases the likelihood that supervisors and subordinates will differ along demographic lines, a situation that has important implications for their relationship quality and individual outcomes. In a sample of 1,253 employees from 54 work-units, we investigate the effects of differences in disability status between supervisors and subordinates on leader-member-exchange (LMX) quality and subsequent performance ratings, and find that incongruence in general is related to lower LMX quality and lower performance. In addition, we propose and find an asymmetrical effect of disability incongruence, such that LMX quality is worse in dyads in which the supervisor has a disability than in dyads in which the subordinate has a disability. Furthermore, we investigate the moderating role of unit-level climate for inclusion on this relationship and find support for a buffering effect of inclusive climates on the negative incongruence-LMX relationship for scenarios in which the supervisor, but not the subordinate, has a disability. We build relevant theory for the relational demography, disability, LMX, and organizational climate literatures by predicting these effects on the basis of status mechanisms. These findings have important practical implications, as they provide companies with a feasible way to manage their diverse workforce.