Aim/Purpose: Professional companies selling persuasive-communication services via the World Wide Web need to be exemplars of effective informing practices. Their credibility is at risk if their websites do not excel in marketing message and use of medium. Their unique brands need to be expressed through website technology and content, or they cannot compete successfully. Background: Compares marketing communication consultants’ websites with expert criteria. Methodology: Content analysis of 40 advertising agency websites. Contribution: Links an evaluation of advertising agency compliance with expert website criteria to established branding constructs. Findings: Most small advertising agencies could improve their brand reputations through better compliance with experts’ recommended website design and content criteria. Recommendations for Practitioners: A hierarchy of recommendations for practitioners is offered, addressing ease and importance. Impact on Society: Clarity and credibility of message and medium improve our ability to practice effective informing. Future Research: Explore online communications of specialized populations such as digital marketing experts.

Aim/Purpose: The media and research have made significant noise about young people’s addictions to technology, however the American Psychological Association (APA) has reserved judgment on the clinical diagnosis of technology addiction. Research to understand technology addiction is important to the future of information systems development and behavioral usage understanding. Background: Addiction implies that there is a problem from which an IS client needs to try to recover, further implying a negative impact on life. Multiple defini-tions and outcomes of addictions have been studied in the information systems discipline, with virtually no focus on quality of life of the IS client. Methodology: This research employs a survey of students at a large southwestern United States university. Measures were adopted from previously validated sources. The final sample includes 413 usable responses analyzed using PLS. Contribution: This research broadens theoretical and practical understanding of SNS IS client perceptions by relating technology addiction to a broader impact on an individual’s life. By doing so, it provides guidance on society’s understanding of frequent technology use, as well as the development of new systems that are highly used. Findings: This research indicates diminished impulse control, distraction, social influence and satisfaction are all highly correlated with technology addiction; specifically, 55% of the variance in addiction is explained by these four indicators. However, the model further shows addiction has no significant relationship with overall satisfaction of life, indicating that IS clients do not correlate the two ideas. Recommendations for Practitioners: Heavy technology use may indicate a paradigm shift in how people inter-act, instead of a concern to be addressed by the APA. Recommendation for Researchers: Research needs to clearly define technology dependence, addiction, and overuse so that there is a strong understanding of what is meant. These findings help guide assumptions about the dark side of Information Technology. Impact on Society: While technology use is increasing, younger generations may find the use to be acceptable and less of a problem then older generations. Future Research: Future research should replicate these findings on other technology artifacts and other technology addiction definitions. In the future, there is also opportunity to delve deeper into the outcome variable of satisfaction with life.

Aim/Purpose: This paper aims to investigate how Kuwaiti Academic Libraries (KALs) have responded to the rapidly evolving Smartphone-Apps (SP-Apps) environment, as well as exploring the level of electronic services provided in these libraries. Background: This study can illustrate whether the governmental, academic libraries in the State of Kuwait have already benefited from the mobile services provided by smart phones or not. Methodology: In this study, the researchers use both qualitative and quantitative methods. Therefore, questionnaires and interviews are used in order to collect in-depth data in this field. The questionnaire sample was 400 respondents. They divided in two KALs: Kuwait University Library (KUL) and Public Authority of Applied Education Training Library (PAAETL), while eight individual interviews were conducted one-to-one in this research. Contribution: This paper may be important for academic libraries to identify shortcomings in the smartphones’ content and services they provide and in highlighting efforts by libraries to address their users’ needs in this area. Findings: The findings show that most participants expressed the need to introduce an SP-App to their library. They also confirmed that there are many difficulties in creating an SP-App including lack of budget, lack of awareness of library management, lack of clarity about library management strategic objectives, and vision for an SP-App. Recommendations for Practitioners: Designing SP-Apps that have reliable content and user interface that is easy to use is a considerable challenge. For this reason, the study highly recommends introducing SP-Apps for KALs as soon as possible. Future Research: The recommendations proposed are relevant to Kuwait. Further research may be useful in this field in other developing countries, in order to test or develop the suggested strategy.

Aim/Purpose : An important objective of any firm is escalation of its performance and the achievement of competitive advantages. Supply chain agility plays a prominent role to enhance the level of firm’s performance. Moreover, information technology (IT) plays a foundational role in supply chain management practices. Hence, this study proposes the relationship between IT integration as the competency of IT and firm’s market performance both directly and through mediating role of supply chain agility. Background: Many studies have been done to date on the impact of supply chain agility on overall firm’s performance. However, the effect of an agile supply chain on firm’s market performance per se needs to be studied. Furthermore, there is a gap in the literature about the effect of IT competency such as IT integration on firm’s market performance both directly and through mediating role of supply chain agility. Recommendation for Researchers: The first direction this study gives to researchers is to consider the different factors which have significant effect on the agility of supply chain, particularly the IT related ones. The second direction is about the study on the effect of IT competencies and supply chain agility on each category of firm’s performance separately instead of considering it as a one construct. Impact on Society : Although this is a conceptual study, it can highlight the importance of IT competency not only in our daily life, but also in our businesses and industries. Future Research: This study only proposes some relationships based on theory and literature. Future researchers can test these proposed relationships in different contexts and compare the results. Furthermore, this study proposes the relationships for large manufacturing sector in developing countries. The model could be tested for SMEs as well. In addition, the proposed theoretical model in this study might be tested in both developing as well as developed countries to compare the results which will be contributed to the body of knowledge.

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 explores the implications of machine-mediated communication on human interaction in cross-disciplinary teams. The authors explore the relationships between Open Science Theory, its contributions to team science, and the opportunities and challenges associated with adopting open science principles. Background: Open Science Theory impacts many aspects of human interaction throughout the scholarly life cycle and can be seen in action through various technologies, which each typically touch only one such aspect. By serving multiple aspects of Open Science Theory at once, the Open Science Framework (OSF) serves as an exemplar technology. As such it illustrates how Open Science Theory can inform and expand cognitive and behavioral dynamics in teams at multiple levels in a single tool. Methodology: This concept paper provides a theoretical rationale for recommendations for exploring the connections between an open science paradigm and the dynamics of team communication. As such theory and evidence have been culled to initiate a synthesis of the nascent literature, current practice and theory. Contribution: This paper aims to illuminate the shared goals between open science and the study of teams by focusing on science team activities (data management, methods, algorithms, and outputs) as focal objects for further combined study. Findings: Team dynamics and characteristics that will affect successful human/machine assisted interactions through mediators of workflow culture, attitudes about ownership of knowledge, readiness to share openly, shifts from group-driven to user-driven functionality, group-organizing to self-organizing structures, and the development of trust as teams regulate between traditional and open science dissemination. Recommendations for Practitioners: Participation in open science practices through machine-assisted technologies in team projects/scholarship should be encouraged. Recommendation for Researchers: The information provided highlights areas in need of further study in team science as well as new primary sources of material in the study of teams utilizing machine-assisted methods in their work. Impact on Society: As researchers take on more complex social problems, new technology and open science practices can complement the work of diverse stakeholders while also providing opportunities to broaden impact and intensify scholarly contributions. Future Research: Future investigation into the cognitive and behavioral research conducted with teams that employ machine-assisted technologies in their workflows would offer researchers the opportunity to understand better the relationships between intelligent machines and science teams’ impacts on their communities as well as the necessary paradigmatic shifts inherent when utilizing these technologies.

Aim/Purpose: Transdisciplinarity is considered as a framework for understanding knowledge producing teams (KPTs). Features of transdisciplinary knowledge producing teams (TDKPTs) are provided using a complex adaptive systems (CAS) lens. TDKPT features are defined and linked to complexity theory to show how team participants might develop skills that more truly express complex adaptive conditions. Background: TDKPTs are groups of stakeholder participants tasked with producing knowledge across disciplinary, sectoral, and ecological boundaries. TDKPTs reflect components of complex adaptive systems (CAS) and exemplify how CAS behave and function. Methodology: The paper accesses literature from the Science-of-Team-Science (SciTS), complexity theory, and systems theory to construct a typology of the features of TDKPTs. Contribution: This paper provides a list of features developed from a diverse body of literature useful for considering complexity within TDKPTs. Findings: The paper proposes a series of features of transdisciplinary knowledge producing teams. In addition, the authors identify important skill building aspects needed for TDKPTs to be successful. Recommendations for Practitioners: The paper provides a framework by which team functioning can be considered and enhanced within TDKPTs. Recommendation for Researchers: The paper suggests categorical features of transdisciplinary teams for research on the collaborative processes and outcomes of TD teams. Future Research: Knowledge producing team members need to engage in theoretical, episte-mological, and methodological reflections to elucidate the dynamic nature of TD knowledge producing teams. Understanding how conflict, dissonance, and reciprocal interdependencies contribute to knowledge generation are key areas of future research and inquiry.

Aim/Purpose: The paper explores the success of KGB Operation SIG to incite hatred and create chaos against a democracy Background: About 50 years ago, the KGB created the means to create upheaval in the Mid-dle East. This paper explores one such campaign and its successor campaign, revealing some disinformation techniques in use today. Methodology: The paper brings together literature from many fields in its exploration of Op-eration SIG. Contribution: The paper reveals the role of the KGB in the PLO’s campaign to replace Israel with an Arab Muslim state and the PLO and Hamas’s successor disinformation mechanisms Findings: Operation SIG is an early and extremely successful example of the Sovi-et/Russian campaign to disrupt democracy. Recommendation for Researchers: The recurrence of antisemitism, particularly on campus, can be attributed to Operation SIG.

The present paper identifies a variety of conceptual schemes that have emerged within informing science and consider how they might be applied to fake news. The paper begins with a brief overview of fake news. This is followed presentations of various models identified in a two-volume survey of informing science. The models presented include those dealing with extrinsic (i.e., environmental) complexity, informing transitions, and individual resonance. The potential implications for informing science research into fake news are discussed and questions that may warrant future research are raised. The paper then concludes by describing what current informing science may already be telling us about fake news, its spread and its influence. Through its analysis of the fake news and informing science literature, a number of questions are identified where informing science can possibly contribute to our understanding of fake news. These include: • Does fake news need to disinform its clients if it is to be effective? • Why are certain groups of individuals particularly credible when it comes to communicating fake news? • Under what circumstances will the emotional and social motivations to accept fake news exceed our concern for its truth? • How does the nature of the fake news content and objectives impact the disinformer’s choice of channel? • What are the circumstances under which radically transitional fake news might have an impact?

Aim/Purpose: Many disciplines have addressed the issue of “fake news.” This topic is of central concern to the transdiscipline of Informing Science, which endeavors to understand all issues related to informing. This paper endeavors to build a model to address not only fake news but all informing and misin-forming. To do this, it explores how errors get into informing systems, the issue of bias, and the models previously created to explore the complexity of informing. That is, this paper examines models and frameworks proposed to explore informing in the presence of bias, misinformation, disinformation, and fake news from the perspective of Informing Science. It concludes by intro-ducing a more nuanced model that considers some of the topics explored in the paper Methodology: The issue of informing and disinforming crosses many disciplinary perspectives. Each discipline puts on blinders that limit what it can contribute to its understanding of research topics. It is like trying to study a forest by seeing only the trees and not the animals or the animals but not the trees. Research perspectives that cross disciplinary boundaries are needed to more fully understand complex phenomena. This paper lays out some fundamental cross-disciplinary issues including how errors find their way into informing systems, the issue of bias, and the frameworks used to model this phenomenon. Contribution: The paper introduces the competition framework for understanding informing and misinforming. This framework addresses many of the limitation of prior frameworks. Future Research: The concluding framework offers insights into understanding informing and disinforming. But this framework offers no insights into other forms of informing that are less well explored, such as song, dance, physical art, and architecture. Likewise, this framework does nothing to help the un-derstanding of informing via fideism or psychedelic revelation.

Aim/Purpose: This series of papers on Fake News: Bias, Misinformation, and Disinformation examines fake news from an Informing Science perspective. As such, the papers in this special series make novel con-tributions to the field by viewing the issues through the transdisciplinary lens of informing science. This series makes no claim to summarize or review all that has been written on this topic. Rather it provides a glimpse into this immense literature from the perspective of informing science. Background: It is one small step on the 20+ year quest by the editor to explore better ways to inform from an approach that transcends academic disciplines (Cohen, 1998, 1999) and a 20 year quest to under-stand the issues of how we become misinformed and disinformed (Cohen, 2000). The series pro-vided here gains thrust for two reasons. One reason is that the study has become more popular with academicians due to the blathering of politicians and the attacks by national powers on de-mocracy. The second reason is more mundane; without the deadline that the end-of-year affords, the papers would become richer, fuller, and more detailed. Recommendation for Researchers: Taken together, the results brought forth across these papers is truly scary. Due to their biases, when presented with information, people can and do generate their own misinformation. People tend to communicate such misinformation that they self-generated with others in groups sharing their beliefs, strengthening the misinformation by some and silencing those do not share these thoughts. This process creates divisions in society. How can humanity seek wise decisions when we cannot agree even upon the facts. We see the results of this syndrome in Operation SIG and cur-rent divisions within politics in the West.

Aim/Purpose: The aim of this paper is to propose an ensemble learners based classification model for classification clickbaits from genuine article headlines. Background: Clickbaits are online articles with deliberately designed misleading titles for luring more and more readers to open the intended web page. Clickbaits are used to tempted visitors to click on a particular link either to monetize the landing page or to spread the false news for sensationalization. The presence of clickbaits on any news aggregator portal may lead to an unpleasant experience for readers. Therefore, it is essential to distinguish clickbaits from authentic headlines to mitigate their impact on readers’ perception. Methodology: A total of one hundred thousand article headlines are collected from news aggregator sites consists of clickbaits and authentic news headlines. The collected data samples are divided into five training sets of balanced and unbalanced data. The natural language processing techniques are used to extract 19 manually selected features from article headlines. Contribution: Three ensemble learning techniques including bagging, boosting, and random forests are used to design a classifier model for classifying a given headline into the clickbait or non-clickbait. The performances of learners are evaluated using accuracy, precision, recall, and F-measures. Findings: It is observed that the random forest classifier detects clickbaits better than the other classifiers with an accuracy of 91.16 %, a total precision, recall, and f-measure of 91 %.

Aim/Purpose: In a world of rapidly expanding complexity and exponentially increasing data availability, IT-based knowledge management tools will be needed to manage and curate available information. This paper looks at a particular tool architecture that has been previously proposed: The Personal Knowledge Management System (PKMS). The specific focus is on how the proposed architecture conforms to design science principles that relate to how it is likely to evolve. Background: We first introduce some recent informing science and design science research frameworks, then examine how the PKMS architecture would conform to these. Methodology: The approach taken is conceptual analysis. Contribution: The analysis provides a clearer understanding of how the proposed PKMS would serve the diverse-client ambiguous-target (DCAT) informing scenario and how it could be expected to evolve. Findings: We demonstrate how the PKMS informing architecture can be characterized as a “social machine” that appears to conform to a number of principles that would facilitate its long-term evolution. Future Research: The example provided by the paper could serve as a model future research seeking to integrate design science and informing science in the study of IT artefacts.

Aim/Purpose: The aim is to explore the informing flows framework as interactions within a PhD education practicing a work-integrated learning approach in order to reveal both the perspectives of industrial PhD students and of industry. Background: An under-researched field of university-industry collaboration is explored revealing both the perspectives of industrial PhD students and of industry. Methodology: Qualitative methods were applied including interviews and document studies. In total ten semi-structured interviews in two steps were conducted. The empirical context is a Swedish PhD program in informatics with a specialization in work-integrated learning. Contribution: By broadening the concept of work-integrated learning, this paper contributes empirical results on benefits and challenges in university-industry collaboration focusing on industrial PhD students and industry by applying the informing flows framework. Findings: Findings expose novel insights for industry as well as academia. The industrial PhD students are key stakeholders and embody the informing flows between practice and university and between practice and research. They are spanning boundaries between university and industry generating continuous opportunities for validation and testing of empirical results and models in industry. This may enable increased research quality and short-lag dissemination of research results as well as strengthened organizational legitimacy. Recommendation for Researchers: Academia is recommended to recognize the value of the industrial PhD students’ pre-understanding of the industry context in the spirit of work-integrated learning approach. The conditions for informing flows between research and practice need to continuously be maintained to enable short-term societal impact of research for both academia and industry. For practitioners: This explorative study show that it is vital for practice to recognize that challenges do exist and need to be considered to strengthen industrial PhD pro-grams as well as university-industry collaborations. Additionally, it is of importance to formalize a continuously dissemination of research in the industries. Future Research: Future international and/or transdisciplinary research within this field is encouraged to include larger samples covering other universities and a mix of industrial contexts or comparing industrial PhD students in different phases of their PhD education.

Aim/Purpose: As traditional Knowledge Management (KM) struggles to support the personal needs of knowledge workers in a new era of accelerating information abundance, we examine the shortcomings and put forward alternative scenarios and architectures for developing a novel Personal KM System (PKMS). Background: While prior publications focused on the complementing features compared to conventional dynamic KM models, our emphasis shifts to instantiating a flourishing PKMS community supported by a Digital Platform Ecosystem. Methodology: Design science research focusing on conceptual analysis and prototyping. Contribution: The PKMS concept advances the understanding of how digital platform communities may serve members with highly diverse skills and ambitions better to gainfully utilize the platform’s resources and generative potential in their personal and local settings. Findings: We demonstrate how the needs to tackle attention-consuming rising entropy and to benefit from generative innovation potentials can be addressed. Future Research: As this article has iteratively co-evolved with the preparing of a PKMS implementation, business, and roll-out plan, the prototype’s testing, completion, and subsequent migration to a viable system is of primary concern.

Aim/Purpose: This article takes ‘tourism decision-making behavior’ as an entry point, and deeply analyzes the factors influencing the travel decision-making of Chinese ‘American Travel’ tourists and their degree of influence, so as to provide a reference for the development of Chinese outbound tourism. Background: With the development of China’s economy and the improvement in people’s level, the outbound tourism market of Chinese residents has developed rapidly. The United States has become an important tourism destination country for Chinese residents’ outbound tourism, and China has also become one of the important tourist source countries of American tourism. However, the rapid development of ‘American tourism’ has also caused competition problems in China’s tourism industry. For example, prices and tourism products have become a means of competition among tourism enterprises. As the main body of consumption, tourists’ decision-making behavior will be affected by various factors. Methodology: Drawing lessons from previous scholars’ research results on tourism decision-making behavior, the influencing factors of tourism decision-making behavior are summarized. A theoretical model and index system of factors influencing tourism decision-making behavior of Chinese residents ‘Travel in the United States’ are established, research hypotheses are put forward, questionnaire data are collected, and SPSS and Amos are used to analyze and verify the theoretical model. Contribution: This research expands the literature on topics related to tourism decision-making in research and practice. It establishes a theoretical model and index system for the factors that influence the decision-making behavior of Chinese residents’ ‘American Travel’ tourism. In addition, we propose countermeasures for tourism products, enterprises, and the government. Findings: Prior knowledge and external information have a positive influence on tourism perception and value perception, and a negative influence on risk perception. Risk perception value perception has a positive and negative influence on tourism decision-making and tourism motivation, respectively. Tourism motivation has a positive influence on tourism decision-making and has a positive impact. Recommendation for Researchers: According to the research conclusions of this article, the following counter-measures and suggestions are put forward from three aspects of tourism: products, enterprises, and governments. On the basis of existing tourism products, relevant operating companies should pay more attention to the upgrading and transformation of tourism, leisure and entertainment products in scenic spots to increase the willingness of tourists to travel. When considering corporate marketing and promotion plans, tourism companies operating related businesses should increase the weight of their marketing budgets in online marketing, increase investment in online marketing, and develop mobile applications that meet the preferences of Chinese residents in the United States. Do a good job in the timely publication of safety reminders and local information. Safety is an important foundation for tourism development and the core concern of many tourists. Future Research: Due to the important research on the impact of tourism activities, the influencing factors are many and complex, and the psychological process of tourism decision-making is carried out directly. There are still unconsidered factors that need to be studied in depth. In the future, it is possible to compare multiple resource-featured themes, and increase the characteristics of potential tourists, and the factors affecting the selection behavior of regional cultural tourists, and so forth, in order to make the research more applicable and practical instructive significance.

Aim/Purpose: Nigeria’s university education goes through incessant strikes by the Academic Staff Union of Universities (ASUU). This strike has led to shared emotion on micro-blogging sites like Twitter. This study analyzed selected historical tweets from the “ASUU” to understand citizens’ opinions. Background: The researchers conducted sentiment analysis and topic modelling to understand Twitter users’ opinions on the strike. Methodology: The researchers used the Valence Aware Dictionary for Sentiment Reasoning (VADER) technique for sentiment analysis, and the Latent Dirichlet allocation (LDA) was used for topic modelling. A total of 10,000 tweets were first extracted for the study. After data cleaning, 1323 tweets were left. Contribution: To the researcher’s best knowledge, no published study has presented a sentiment analysis on the topic of the ASUU strike using the Twitter dataset. This research will fill this gap by providing a sentiment analysis and drawing out subjects by exploring the tweets on the phrase “ASUU.” Findings: The sentiment analysis result using VADER returned 567 tweets as ‘Negative,’ with the remaining 544 and 212 categorized as Positive and Neutral. The result of the LDA returned six topics, all comprising seven keywords. The topics were the solution to the strike, ASUU strike effect, strike Call-off, appeal to ASUU, student protest and student appeal. Recommendation for Researchers: Researchers can use this study’s findings to compare with other contexts of opinion mining. Practitioners may also use the research to understand better the attitudes of their staff and students about the strikes to create actionable solutions before the suspension of the strike. Future Research: Future studies can collect information from other social networking and blogging sites.

Aim/Purpose This paper aims to illustrate, through an exploratory ideographic case study, how a Complex Thinking framework can inform the design of scientific events and the facilitation of scientific Inter and Transdisciplinary groups towards positive emergent outcomes, both at the level of the functioning of the group and the collective complexity of their thinking. Moreover, it aims to show how the choice of facilitation strategies can contribute to positive emergent outcomes in the context of a fully online event, with its inherent constraints. Finally, this study aims to conduct an exploratory qualitative evaluation of the participants’ experiences during School, with a focus on the processes and how they relate to the aims of the School and the goals of the facilitation. Background Science needs to embrace modes of knowing capable of generating more complex (differentiated, integrated, recursively organized, emergent), ecologically fit, and creative responses, to meet the complexity of the world’s challenges. New formats and strategies are required that attend to the facilitation of Inter and Transdisciplinary scientific events and meetings, towards creative and complex outcomes. A Complex Thinking framework provides suggestions for the facilitation of Inter and Transdisciplinary meetings and events through targeting key properties which may lead to the emergence of complex and creative outcomes. Methodology We adopt an ideographic case study approach to illustrate how a complex systems approach, in particular a Complex Thinking framework, grounded in an enactive view of cognition, guided the design choices and the facilitation strategies of an online Inter and Transdisciplinary Advanced Training School (Winter School). We aim to illustrate how the facilitation strategies were selected and used to promote deep and creative interactions within the constraints of an online environment. We adopt an exploratory qualitative approach to investigate the participants’ reports of their experiences of the School, in light of the principles and goals that guided its design and facilitation. Contribution This paper opens a new area of theoretical and applied research, under the scope of a Complex Thinking framework, focused on the facilitation of Inter and Transdisciplinarity at scientific events, meetings, and discussions towards complex and creative outcomes. Findings The results of the exploratory qualitative analysis of the participants’ experiences regarding the event suggest a critical role of its methodology in fostering rich, deep, and constructive interactions, in leading to the emergence of a collective group experience, to the integration of ideas, and in facilitating transformative personal experiences, under the effects of the emergent group processes. It suggests that the strategies employed were successful, anticipating and overcoming the particular constraints of an online event. Recommendations for Practitioners This case study suggests that a Complex Thinking framework can fruitfully guide the design of facilitation strategies and activities for scientific events and meetings, activating a number of key relational processes that contribute to or boost the emergence of positive group experiences and the production and integration of novel ideas. Recommendations for Researchers This study calls for action-oriented and applied research focused on the developmental evaluation of innovations, regarding the facilitation of scientific creativity and integration, within the scope of a Complex Thinking approach. Impact on Society This paper calls for new modes of organization and formats of scientific activities, suggesting that Inter and Transdisciplinary events and meetings may benefit from intentional management and facilitation of interactions between participants to produce transformative impacts. It demonstrates the importance of the organizational principles used to plan and run events that engage multiple and various societal agents, from academics to practitioners and social activists, towards enhancing their richness and relevance to complex real-world challenges. Future Research This study highlights the need for process-focused systematic case study research using complex systems-informed designs to explore how and which facilitation strategies may promote which (interaction of) properties of Complex Thinking and associated processes and how, and under which conditions, these lead to more complex and creative outcomes.

Aim/Purpose: A literature review is often criticized for the absence of coherent construction, synthesis of topics, and well-reasoned analysis. A framework is needed for novice researchers to organize and present information obtained from the literature review. Background: Information and communication technologies advancement have yielded overwhelming information. The massive availability of information poses several challenges, including storage, processing, meaningful organization, and presentation for future consumption. Information System Researchers have developed frameworks, guidelines, and tools for gathering, filtering, processing, storing, and organizing information. Interestingly, information system researchers have vast information that needs meaningful organization and presentation to the research fraternity while conducting a literature review on a research topic. Methodology: This paper describes a framework called LACTiC (Location, Author, Continuum, Time, and Category) that we adapted from another framework called LATCH (Location, Alphabetical, Time, Category, and Hierarchy). LATCH was used to organize and present information on e-commerce websites for seamless navigation. We evaluated the LACTiC framework. Contribution: Information System Researchers can use the LACTiC framework to organize information obtained from literature review. Findings: The evaluation reveals that most researchers from information systems organize information obtained from the literature review category-wise, followed by continuum, author, time, and location. Recommendation for Researchers: Overall, the framework works well and can be helpful for researchers for an initial idea for organizing information obtained from the literature review. Future Research: To conceptualize the framework, the study was carried out using Information Systems related literature. To generalize the proposed framework, we may suggest that the study can be extended to other areas of business management, such as marketing, finance, operation, decision sciences, accounting, and economics.

Aim/Purpose: The present study aims to frame the relationship between job and personal resources (namely, organizational identification and emotional intelligence), burnout, and musculoskeletal disorders (i.e., back pain, upper limb pain, lower limb discomfort), into the theoretical framework provided by the JD-R health model. Background: Empirical research indicates a connection between burnout and the onset of musculoskeletal problems, one of the most important occupational health issues affecting all jobs and organizations. In light of the JD-R health model, we investigated the association between personal and job resources with burnout and musculoskeletal disorders. Methodology: An anonymous online questionnaire was answered by 320 workers (82.4% female, Mage = 42.18; SDage = 12.24) investigating their perceived level of burnout, the presence of musculoskeletal pain (back, neck, and shoulder), and their level of organizational identification and emotional intelligence. Descriptive analysis, correlation, and moderated mediation model were performed using SPSS. Contribution: We confirmed the role of personal and organizational resources in the salutogenic process considered by the JD-R health model. Emotional intelligence, decreasing the perceived level of burnout, limited the development of musculoskeletal disorders. Moreover, when organizational identification presented low and medium levels, the association between emotional intelligence and burnout strengthened. Findings: Our results showed a negative, indirect effect of emotional intelligence on musculoskeletal disorders via burnout. Moreover, we found a moderation of organizational organization, indicating that at low and medium levels of identification, the association between emotional intelligence and burnout is stronger. Recommendation for Researchers: In addition to work factors involved in the link between burnout and musculoskeletal disorders, it is also important to consider personal and emotional factors, which can decrease the occurrence of adverse consequences. Future Research: Future research developments could contribute to a deeper understanding of the mechanisms linking emotional intelligence, burnout, and musculoskeletal problems, as well as consider objective indicators of burnout levels or consider using ecological data collection methodologies (e.g., ecological momentary assessment), to identify patterns and associations between burnout and musculoskeletal disorders.

Aim/Purpose: The focus on human well-being has attracted the attention of consumers, organizations, and marketers to understand the various facets of Front of Pack Nutrition Labelling (FOPNL). This study examines the overall research trends in the FPONL domain and identifies the new research areas. Background: FOPNL is becoming increasingly popular and its influence has been widely examined. Different label schemes have been introduced across different regions in the world. Nevertheless, such interventions are limited in developing economies. Methodology: This study uses bibliometric analysis methods to explore Front of Pack Nutrition Labelling (FOPNL) trends using 602 articles published in selected business journals. Contribution: The paper identifies the new FOPNL research avenues. The study indicates that FOPNL has become a crucial research area, and more research is needed at the organization, managerial, and policy levels. Findings: The study identifies four themes. The first theme identified is the effect of harmful nutrients on health and the role of FOPNL nutrition in changing eating habits. The second theme focused on the government's policy and implementation of FOPNL nutrition labeling regulations. The third theme is dedicated to the work on attention, perception, understanding, and influence of multiple traffic light schemes. The fourth theme relates to the Health Star Rating, Nutri Score, and Healthier Choice FOPNL nutrition labeling schemes. Overall, the paper informs consumers, manufacturers, and regulators about the recent trends in the FOPNL research. Recommendation for Researchers: Though FOPNL has been widely examined in the health and nutrition domain, however, limited research has been done in the marketing domain. Research using neuroscientific methods (e.g. eye tracking) should provide more robust findings. Future Research: There is limited research on FOPNL from emerging economies. Future research can examine how FOPNL may influence people, policy, and private entities.

Aim/Purpose: This study builds upon existing research by investigating the elements contributing to or buffering the onset of burnout symptoms. We examine the relationship between empowering leadership and burnout, considering the concurrent mediation effects of interpersonal workplace conflict, work-home conflict, and support from coworkers. Background: Burnout is a phenomenon that has been widely considered in the scientific literature due to its negative effect on individual and organizational well-being, as well as implications for leadership, coworker support, and conflict resolution. A deeper understanding of burnout prevention strategies across various professional contexts is paramount for enhancing productivity and job satisfaction. Methodology: Using a survey-based cross-sectional design, we employed a combination of Structural Equation Modelling (SEM) and Artificial Neural Network (ANN) to investigate the direct and indirect influences of empowering leadership on four dimensions of employee burnout, mediated by coworker support, interpersonal conflict at work, and work-home conflict. Contribution: This study provides initial insights into the direct and indirect influences of empowering leadership on various dimensions of burnout, highlighting the complex interplay with coworker support, work-home conflict, and workplace interpersonal conflicts. Ultimately, the study provides a comprehensive approach to understanding and mitigating burnout. Findings: Empowering leadership and coworker support can significantly reduce burnout symptoms, while high levels of work-home conflict and interpersonal conflict at work can exacerbate them. Our findings underscore the paramount role of interpersonal conflict in predicting burnout, urging organizations to prioritize resolving such issues for burnout prevention. Recommendation for Researchers: Following our findings, organizations should (a) promote empowering leadership styles, (b) foster coworker support and work-life balance, and (c) address interpersonal conflicts to reduce the likelihood of employee burnout while ensuring that these strategies are tailored to the specific context and culture of the workplace. Future Research: Future research should broaden the exploration of leadership styles’ effects on burnout, identify additional mediators and moderators, expand studies across sectors and cultures, examine differential impacts on burnout dimensions, leverage advanced analytical models, and investigate the nuanced relationship between work contract types and burnout.

Aim/Purpose: Embitterment comprises a stress-related response to unjust life experiences. Studies have found that it can have a toll on employees’ well-being. However, research on this matter is still in its infancy. Background: Within the scope of the present study, Ι sought to investigate how embitterment relates to burnout – the prolonged consequence of stress. This study further explored whether breaches of psychological contracts can trigger embitterment. Methodology: The study employed a cross-sectional design where two hundred and eight (N = 208) participants from the general population completed an online survey. Contribution: Findings suggest that the toll of embitterment might be much more than what research has suggested so far. Those who experience embitterment can become emotionally exhausted and cynical and these findings can be especially useful when identifying embitterment. Findings: It was found that embitterment related to higher burnout levels and more specifically emotional exhaustion and cynicism. No significant findings were revealed for the relationship between professional inefficacy and embitterment. Also, psychological contract breach was found to be a significant predictor of embitterment, supporting further the notion that perceptions of injustice can trigger feelings of embitterment. Results also showed that embitterment mediated the relationship between psychological contract breach and burnout. Recommendation for Researchers: The study highlights the notion that fairness is a key precursor of embitterment, and this finding is essential when developing interventions to prevent embitterment from arising. Future Research: Future research could use a longitudinal study design to unravel whether burnout represents a precondition or the consequence of embitterment. Future research should also include more objective measures. For example, it would be useful to pair self-report data with more objective measures on embitterment (e.g. clinical interviews).

Aim/Purpose: The aim of this qualitative study is to explore social workers’ representations of hate speech (HS), the effects it has on the community, and socio-educational actions aimed at combating it. Background: Hate speech is any form of communication that promotes discrimination, hostility, or violence towards individuals or groups based on their identity. Although its spread is facilitated by particular characteristics of the online environment (such as anonymity and ubiquity), HS has pervasive consequences even in offline reality. In the last year, several community-based projects involving social workers have been implemented to address the problem. Professionals who work with the community play a crucial strategic role in the fight against HS. Therefore, it is imperative to begin by considering their perspective to gain a better understanding of HS and how it can be controlled. Methodology: Following a psycho-sociological perspective, six focus groups were conducted with 42 social workers (19 females and 23 males) belonging to associations or organizations of a different nature, such as NGOs, local social promotion organizations, universities, private social organizations, whose mission included the theme of countering hate speech. Contribution: There are no studies in the literature that consider the views of operators working to counter hate speech within communities. Our study contributes to deepening the knowledge of the phenomenon and identifying the most suitable strategies to combat it, starting from an approach that does not only focus on the online or offline dimension but on an integrated “onlife” approach. The study offers an outline of how hate speech affects the daily lives of the communities in the cities of Torino, Palermo, and Ancona. Additionally, it proposes a grassroots strategy to address hate speech. Findings: The results suggest that strategies effective in countering hate speech in offline contexts may not be effective in online environments. The technological revolution brought about by social media has significantly expanded the potential audience while weakening traditional communities. Addressing hate speech in the present context requires efforts to rebuild fragmented communities, gaining a thorough understanding of how the new virtual public space operates, and prioritizing hate speech as a specific concern only after these initial steps. Recommendation for Researchers: Hate speech represents a violation of human rights and a threat to freedom of expression. The spread of hateful messages has a significant impact on society, as it can negatively influence social cohesion, diversity, and inclusion. Understanding the causes and consequences of hate speech can help develop effective strategies to prevent and counter it, which is a crucial challenge for both research and society as a whole. Studying hate speech should involve the use of interdisciplinary methodologies. Future Research: Future research should focus on comparative analysis at the European Union level to assess the ability of civil society in other countries to develop effective strategies against hate speech.

Aim/Purpose: This paper examines the transformative impact of Artificial Intelligence (AI) on professional skills in organizations and explores strategies to address the resulting challenges. Background: The rapid integration of AI across various sectors is automating tasks and reducing cognitive workload, leading to increased productivity but also raising concerns about job displacement. Successfully adapting to this transformation requires organizations to implement new working models and develop strategies for upskilling and reskilling their workforce. Methodology: This review analyzes recent research and practice on AI's impact on human skills in organizations. We identify key trends in how AI is reshaping professional competencies and highlight the crucial role of transversal skills in this evolving landscape. The paper also discusses effective strategies to support organizations and guide workers through upskilling and reskilling processes. Contribution: The paper contributes to the existing body of knowledge by examining recent trends in AI's impact on professional skills and workplaces. It emphasizes the importance of transversal skills and identifies strategies to support organizations and workers in meeting upskilling and reskilling challenges. Our findings suggest that investing in workforce development is crucial for ensuring that the benefits of AI are equitably distributed among all stakeholders. Findings: Our findings indicate that organizations must employ a proactive approach to navigate the AI-driven transformation of the workplace. This approach involves mapping the transversal skills needed to address current skill gaps, helping workers identify and develop skills required for effective AI adoption, and implementing processes to support workers through targeted training and development opportunities. These strategies are essential for ensuring that workers' attitudes and mental models towards AI are adaptable and prepared for the changing labor market. Recommendation for Researchers: We emphasize the need for researchers to adopt a transdisciplinary approach when studying AI's impact on the workplace. Given AI's complexity and its far-reaching implications across various fields including computer science, mathematics, engineering, and behavioral and social sciences, integrating diverse perspectives is crucial for a holistic understanding of AI's applications and consequences. Future Research: Looking ahead, further research is needed to deepen our understanding of AI's impact on human skills, particularly the role of soft skills in AI adoption within organizations. Future studies should also address the challenges posed by Industry 5.0, which is expected to bring about even more extensive integration of new technologies and automation.

Aim/Purpose: The purpose of this study is to determine the impact of pre-listening activities on Arabic-speaking EFL learners’ comprehension of spoken texts. Background: This study aims to contribute to the current research and to increase our understanding about the effectiveness of pre-listening activities. Specifically, this study seeks to clarify some of the research in this area that seems to be incongruent. Methodology: The study investigates two widely implemented activities in second language (L2) classrooms: vocabulary preteaching and content previewing. Ninety-three native-Arabic speaking EFL learners, whose proficiently levels were beginner, intermediate, or advanced, were randomly assigned to a control group or one of three experimental groups: the vocabulary-only (VO) group, content-only (CO) group, or vocabulary + content (VC) group. Each of the experimental groups received one of the treatments to determine which pre-listening activity was more effective and whether additional pre-listening activities yield additional comprehension. Listening comprehension of the aural text was measured by a test comprising 13 multiple-choice and true-false questions. Contribution: The present study provided additional explanations regarding the long-standing contradicting results about vocabulary preteaching and content previewing. Findings: The results showed that pre-listening activities had a positive impact on Arabic-speaking EFL learners’ listening comprehension, with the VO group significantly increasing their scores on the posttest compared to those of the control or other groups. Vocabulary preteaching was particularly beneficial for more advanced learners. With regard to which pre-listening activity contributed the most to better listening comprehension, vocabulary preteaching was the most effective. Content previewing did not increase comprehension for the CO group and had no additional benefit for the VC group. Recommendation for Researchers: This paper recommends that researchers explore new pre-listening activities that have never studied. Future research should be extended to include other nations and contextual situations to extend our knowledge about the effect of pre-listening activities. As far as listening comprehension can only be achieved when listeners are attentive and engaged, the listening text should be interesting and the lexical coverage of the listening text should be appropriate for all participants. Future Research: The results are to be interpreted carefully because they are limited by the students’ L2 proficiency, demographic, and cultural backgrounds (i.e., first language (L1) proficiency, age, gender, Middle Eastern culture). Results might be quite different if the study was conducted with different populations who have different life and language learning experiences (Vandergrift & Baker, 2015). Therefore, the results of this study indicate there is much room for improvement and a need for further research.

Aim/Purpose: To provide a systematic approach to defining task complexity using a three worlds model previously introduced in informing science research. Background: The task complexity construct presents researchers with a quandary. While it appears useful on the surface, repeated attempts to define it rigorously have failed to gain traction in the broader research community. The level of inconsistency between definitions is shown to have changed little in the past 20 years. Methodology: Using a common framework that treats task complexity as a latent construct residing between sources and outcomes, moderated by both task familiarity and task discretion, separate models for each of the three worlds are developed. Contribution: Our paper proposes a potential path forward by showing how many issues in past task complexity research can be reconciled by framing the construct according to the three worlds model: the world we experience, the world of human artifacts, and the “real world.” Findings: The framework defines experienced complexity as occurring in the mind of the task performer while performing a single task instance, intrinsic complexity as a function of the internal characteristics of the problem space used to perform a bounded set of task instances, and extrinsic complexity as the ruggedness of the fitness landscape in which the task is performed. Recommendation for Researchers: It offers a path to convergence for definitions of task complexity. Future Research: The three worlds of task complexity can potentially be applied to many practical problems.

Aim/Purpose: This study aims to explore students’ digital entrepreneurial intention (DEI) in Kuwait. Specifically, the aim is twofold: (i) to identify and examine the factors influencing and predicting students’ DEI, and (ii) to validate a model of DEI. Background: The advent of modern digital technologies has provided entrepreneurs with many opportunities to establish and expand their firms through online platforms. Although the existing literature on DEI has explored various factors, certain factors that could be linked to DEI have been neglected, and others have not been given sufficient attention. Nonetheless, there has been little research on students’ DEI, particularly in Kuwait. Methodology: To fulfill the research’s aims, a study was conducted using a quantitative method (a survey of 305 students at a non-profit university in Kuwait). Contribution: This study aimed to fill the research gap on the limited DEI research among Kuwait’s students. Several recommendations were suggested to improve the DEI among students in Kuwait. Findings: The study identified five factors that could influence an individual’s intention to engage in digital entrepreneurship. These factors include self-perceived creativity, social media use, risk-taking and opportunity recognition, digital entrepreneurship knowledge, and entrepreneurial self-perceived confidence. Significant solid correlations were between all five identified factors and DEI. However, only self-perceived creativity and entrepreneurial self-perceived confidence were identified as significant positive predictors of DEI among undergraduates in Kuwait. Nevertheless, the main contributor to this intention was the students’ self-perceived confidence as entrepreneurs. Recommendation for Researchers: Researchers should conduct further longitudinal studies to understand better the dynamic nature of DEI and execution. Future Research: Additional research is required to utilize probability sampling approaches and increase the sample size for more generalizable findings.

Aim/Purpose: The aim of the present study is to investigate how pre-game superstition and anxiety can drive the consumption and purchase of sports products and objects by triathletes. Methodology: We tested our hypotheses via a cross-sectional study on a sample of N=124 triathletes. Contribution: The originality of our work stands in the provision of empirical evidence on the role of superstition and anxiety in characterized consumer decision-making of triathletes. Theoretically and practically, our results can extend our knowledge of the role of cognitive factors in consumer behaviors among athletes. Findings: The results of the Structural Equation Modelling provided evidence of our hypothesized relationship between pre-game anxiety and superstition, and cognitive biases. Pre-game anxiety increases the level of incidence of specific cognitive biases characterized by intuitive and implicit thinking, while superstition leads to more rational and personal cognitive biases, which affect their purchasing of sports products before games and competitions.

Aim/Purpose: This review paper aims to unveil some underlying machine-learning classification algorithms used for political election predictions and how stack ensembles have been explored. Additionally, it examines the types of datasets available to researchers and presents the results they have achieved. Background: Predicting the outcomes of presidential elections has always been a significant aspect of political systems in numerous countries. Analysts and researchers examining political elections rely on existing datasets from various sources, including tweets, Facebook posts, and so forth to forecast future elections. However, these data sources often struggle to establish a direct correlation between voters and their voting patterns, primarily due to the manual nature of the voting process. Numerous factors influence election outcomes, including ethnicity, voter incentives, and campaign messages. The voting patterns of successors in regions of countries remain uncertain, and the reasons behind such patterns remain ambiguous. Methodology: The study examined a collection of articles obtained from Google Scholar, through search, focusing on the use of ensemble classifiers and machine learning classifiers and their application in predicting political elections through machine learning algorithms. Some specific keywords for the search include “ensemble classifier,” “political election prediction,” and “machine learning”, “stack ensemble”. Contribution: The study provides a broad and deep review of political election predictions through the use of machine learning algorithms and summarizes the major source of the dataset in the said analysis. Findings: Single classifiers have featured greatly in political election predictions, though ensemble classifiers have been used and have proven potent use in the said field is rather low. Recommendation for Researchers: The efficacy of stack classification algorithms can play a significant role in machine learning classification when modelled tactfully and is efficient in handling labelled datasets. however, runtime becomes a hindrance when the dataset grows larger with the increased number of base classifiers forming the stack. Future Research: There is the need to ensure a more comprehensive analysis, alternative data sources rather than depending largely on tweets, and explore ensemble machine learning classifiers in predicting political elections. Also, ensemble classification algorithms have indeed demonstrated superior performance when carefully chosen and combined.

Aim/Purpose: The truism is that leadership fosters or restricts innovation behaviours in organisations, but the extent to which it does depends on the leadership style in practice. This study focuses on one of the contemporary leadership styles, knowledge-oriented leadership [KOL], which has received scant attention in research. In doing so, the contextual factors of psychological safety [PS] and employee voice [EV] were applied to determine how KOL influences are channeled to innovation at the individual level. Methodology: Data were collected from 347 academic staff in public universities in Southern Nigeria and subjected to a partial least square [PLS] analytical procedure for data treatment and hypotheses testing using the SmartPLS 3 software for variance-based structural equation modelling. Contribution: The study formed an integrated research framework that links knowledge-oriented leadership and innovation by accounting for the contextual mechanisms of psychological safety and employee voice. Findings: The PLS results demonstrated that the knowledge-oriented leadership and innovation relationship was positive and significant, and this relationship was partially mediated by two variables, namely, PS and EV. Furthermore, the two mediating variables channeled KOL’s influence on innovation in a sequence. Recommendation for Researchers: Organisations need to consider the practical application of KOL to improve innovation outcomes considerably. By this, leadership training programs should include modules, courses, or topics on KOL to engender the formation of requisite managerial skills. More so, they should consider the criterion of demonstrable KOL abilities for leadership selection and recruitment. As a personal development initiative, managers can attend leadership development programmes as well as obtain certification in knowledge management to improve their KOL abilities. This initiative should be encouraged and supported by organisations. In all, the human resource management framework should be responsive to the dynamics of the knowledge economy regarding leadership. Given that PS and EV function as mediators, organisations should actively cultivate an environment enabling interpersonal risky behaviours founded on trust, respect, and cooperation and encourage/support employees who demonstrate such behaviour accordingly. In this line, they should create and sustain a supportive environment that positively reinforces voice decisions and behaviours. Future Research: The study only determined the links between KOL, PS, EV, and innovation in public universities in Southern Nigeria. Other studies may examine the linkages in other knowledge-intensive organisations as well as expand the geographic scope to make for better generality of findings. Future studies should look at other underlying mechanisms that can affect the KOL-innovation relationship, such as psychological capital, work engagement, work commitment, etc. The role of moderators can be identified and introduced to this integrative framework to demonstrate the conditions affecting the linkages.

This article is part of the 2024 BCLT-BTLJ-CMTL Symposium.  Leo Yu The national security concerns surrounding TikTok appear straightforward: it is China. To many policymakers and scholars, the mere connection to China warrants severe measures, including either divestment to an American firm or a complete shutdown. What renders China’s involvement ...

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By Barbara Rasin, J.D. Candidate, 2027 In Anderson v. TikTok, decided in in late summer 2024, the Third Circuit Court of Appeals held that TikTok’s “For You Page” algorithm was sufficiently creative to bar its protection under §230 of the Communications Decency Act (CDA). This is a significant step towards ...

The post Expanding TikTok’s Liability for the “For You Page” appeared first on Berkeley Technology Law Journal.

[Meg O’Neill] 00:08 Hello and welcome to the Berkeley Technology Law Journal podcast. My name is Meg O’Neill and I am one of the editors of the podcast. Today we are excited to share with you a conversation between Berkeley Law LLM student Franco Dellafiori, and Professor Bertrall Ross. Professor ...

The post Berkeley Technology Law Journal Podcast: Will ChatGPT Tell Me How to Vote? Democracy & AI with Professor Bertrall Ross appeared first on Berkeley Technology Law Journal.

This paper proposes an efficient solution for personalised web directories recommendation using fast FCM+DQN. At first, web directory usage file obtained from given dataset is fed into the accretion matrix computation module, where visitor chain matrix, visitor chain binary matrix, directory chain matrix and directory chain binary matrix are formulated. In this, directory grouping is accomplished based on fast FCM and matching among query and group is conducted based on Kumar Hassebrook and Kulczynski similarity. The user preferred directory is restored at this stage and at last, personalised web directories are recommended to the visitors by means of DQN. The proposed approach has received superior results with respect to maximum accuracy of 0.910, minimum mean squared error (MSE) of 0.0206 and root mean squared error (RMSE) of 0.144. Although the system offered magnificent outcomes, it failed to order web directories in the form of highly, medium and low interested directories.

This paper presents a novel deep learning technique called quantum dilated convolutional neural network-DenseNet (Q-DenseNet) for prediction of heart disease in spark framework. At first, the input data taken from the database is allowed for data partitioning using fast fuzzy C-means clustering (FFCM). The partitioned data is fed into spark framework, where pre-processed by missing data imputation and quantile normalisation. The pre-processed data is further allowed for selection of suitable features. Then, the selected features from the slave nodes are merged and fed into master node. The Q-DenseNet is used in master node for the prediction of heart disease. The performance improvement of the designed Q-DenseNet model is validated by comparing with traditional prediction models. Here, the Q-DenseNet method achieved superior performance with maximum of 92.65% specificity, 91.74% sensitivity, and 90.15% accuracy.

This paper studies a dual-channel supply chain consisting of one risk-averse manufacturer and one risk-averse retailer with stochastic demand. Herein, the manufacturer provides value-added services to enhance channel demand. First, the optimal pricing and service decisions of the channel members are investigated under different settings, i.e., the cooperative game, Bertrand game, and manufacturer Stackelberg (MS) game models. Second, the effects of channel members' risk aversion on optimal channel prices and expected utilities are analysed under the assumption that the manufacturer service is a decision variable and an exogenous variable, respectively. Third, sensitivity analysis and numerical simulation are performed to verify our propositions consistently and seek more managerial implications. The findings suggest that the manufacturer's value-added services in their direct channel will improve the direct price while decreasing the retail price. Consumers' channel loyalty degree has a great influence on the optimal price decisions and the performance of the channel members. The direct price increases while the retail price decreases in the manufacturer's value-added services. The retailer's risk aversion has a greater influence on price decisions than that of the manufacturer.

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

Keitaro NAKASAI,Shin KOMEDA,Masateru TSUNODA,Masayuki KASHIMA, Vol.E107-D, No.11, pp.1444-1448
To automatically measure the mental workload of developers, existing studies have used biometric measures such as brain waves and the heart rate. However, developers are often required to equip certain devices when measuring them, and can therefore be physically burdened. In this study, we evaluated the feasibility of non-contact biometric measures based on the nasal skin temperature (NST). In the experiment, the proposed biometric measures were more accurate than non-biometric measures.
Publication Date: 2024/11/01

Qinghua WU,Weitong LI, Vol.E107-D, No.11, pp.1422-1432
Multi-focus image fusion involves combining partially focused images of the same scene to create an all-in-focus image. Aiming at the problems of existing multi-focus image fusion algorithms that the benchmark image is difficult to obtain and the convolutional neural network focuses too much on the local region, a fusion algorithm that combines local and global feature encoding is proposed. Initially, we devise two self-supervised image reconstruction tasks and train an encoder-decoder network through multi-task learning. Subsequently, within the encoder, we merge the dense connection module with the PS-ViT module, enabling the network to utilize local and global information during feature extraction. Finally, to enhance the overall efficiency of the model, distinct loss functions are applied to each task. To preserve the more robust features from the original images, spatial frequency is employed during the fusion stage to obtain the feature map of the fused image. Experimental results demonstrate that, in comparison to twelve other prominent algorithms, our method exhibits good fusion performance in objective evaluation. Ten of the selected twelve evaluation metrics show an improvement of more than 0.28%. Additionally, it presents superior visual effects subjectively.
Publication Date: 2024/11/01

Naoya NEZU,Hiroshi YAMADA, Vol.E107-D, No.11, pp.1408-1421
Modern memory devices such as DRAM are prone to errors that occur because of unintended bit flips during their operation. Since memory errors severely impact in-memory key-value stores (KVSes), software mechanisms for hardening them against memory errors are being explored. However, it is hard to efficiently test the memory error handling code due to its characteristics: the code is event-driven, the handlers depend on the memory object, and in-memory KVSes manage various objects in huge memory space. This paper presents MemFI that supports runtime tests for the memory error handlers of in-memory KVSes. Our approach performs the software fault injection of memory errors at the memory object level to trigger the target handler while smoothly carrying out tests on the same running state. To show the effectiveness of MemFI, we integrate error handling mechanisms into a real-world in-memory KVS, memcached 1.6.9 and Redis 6.2.7, and check their behavior using the MemFI prototypes. The results show that the MemFI-based runtime test allows us to check the behavior of the error handling mechanisms. We also show its efficiency by comparing it to other fault injection approaches based on a trial model.
Publication Date: 2024/11/01

Zhigang WU,Yaohui ZHU, Vol.E107-D, No.11, pp.1385-1395
This article focuses on improving the BiSeNet v2 bilateral branch image segmentation network structure, enhancing its learning ability for spatial details and overall image segmentation accuracy. A modified network called “BiconvNet” is proposed. Firstly, to extract shallow spatial details more effectively, a parallel concatenated strip and dilated (PCSD) convolution module is proposed and used to extract local features and surrounding contextual features in the detail branch. Continuing on, the semantic branch is reconstructed using the lightweight capability of depth separable convolution and high performance of ConvNet, in order to enable more efficient learning of deep advanced semantic features. Finally, fine-tuning is performed on the bilateral guidance aggregation layer of BiSeNet v2, enabling better fusion of the feature maps output by the detail branch and semantic branch. The experimental part discusses the contribution of stripe convolution and different sizes of empty convolution to image segmentation accuracy, and compares them with common convolutions such as Conv2d convolution, CG convolution and CCA convolution. The experiment proves that the PCSD convolution module proposed in this paper has the highest segmentation accuracy in all categories of the Cityscapes dataset compared with common convolutions. BiConvNet achieved a 9.39% accuracy improvement over the BiSeNet v2 network, with only a slight increase of 1.18M in model parameters. A mIoU accuracy of 68.75% was achieved on the validation set. Furthermore, through comparative experiments with commonly used autonomous driving image segmentation algorithms in recent years, BiConvNet demonstrates strong competitive advantages in segmentation accuracy on the Cityscapes and BDD100K datasets.
Publication Date: 2024/11/01

One of the main tasks in tax administration is debt management. The main goal of this function is tax due collection. Statements are processed in order to select strategies to use in the debt management process to optimise the debt collection process. This work proposes to carry out a data mining process to predict debts of taxpayers with high probability of non-payment. The data mining process identifies high-risk debts using a survival analysis on a dataset from a tax administration. Three groups of tax debtors with similar payment behaviour were identified and a success rate of up to 90% was reached in estimating the payment time of taxpayers. The concordance index (C-index) was used to determine the performance of the constructed model. The highest prediction rate reached was 90.37% corresponding to the third group.

Product innovation has become a crucial part of the sustainability of the coconut agro-industry in Indonesia, covering upstream and downstream sides. To overcome this challenge, it is necessary to create several model stages using a hybrid method that combines machine learning based on multiple criteria decision making and mass balance analysis. The research case study was conducted in Tembilahan district, Riau province, Indonesia, one of the primary coconut producers in Indonesia. The analysis results showed that potential products for domestic customers included coconut milk, coconut cooking oil, coconut chips, coconut jelly, coconut sugar, and virgin coconut oil. Furthermore, considering the experts, the most potential product to be developed was coconut sugar with a weight of 0.26. Prediction of coconut sugar demand reached 13,996,607 tons/year, requiring coconut sap as a raw material up to 97,976,249.

Underpinned by stakeholder and agency theories, this study adopts a qualitative multiple-case study approach to explore and analyse various stakeholder interests and how they affect digitalisation in the health sector of a developing country (DC). The study's findings revealed that four key stakeholder interests - political, regulatory, leadership, and operational - affect digitalisation in the health sector of DCs. Further, the study found that operational and leadership interests were emergent and were triggered by some digitalisation initiatives, which included, inter alia, the use of new eHealth software and the COVID-19 vaccination exercise, which established new structures and worked better through digitalisation. Conversely, political and regulatory interests were found to be relatively enduring since they existed throughout the pre- and post-digitalisation eras. The study also unearthed principal-agent conflicts arising from technological, organisational and regulatory factors that contribute to the paradoxical outcomes of digitalisation in the health sector.

The objective of this study was to explore through the Model of Theory of Planned Behaviour the most important variables that influence the practice of physical and sports activity at home supported by virtual training in the context of the COVID-19 pandemic. A cross-study was proposed between countries from three continents, distributing the questionnaire in Spain (Europe), Pakistan (Asia), and Colombia (South America) to ensure a comprehensive study. The methodology of structural equations using partial least squares was used. The empirical exploratory study supported the hypotheses proposed, with the most important result that confinement due to the COVID-19 pandemic has been a factor causing the practice of physical and sports activity at home. This is one of the first studies to examine sports practice at home and the new context of sports practice that has generated disruptive technologies and the global crisis of the COVID-19 pandemic.

Automated Data Augmentation via Wikidata Relationships Oyesh Singh, UMBC10:30-11:30 Monday, 21 October 2019, ITE 346 With the increase in complexity of machine learning models, there is more need for data than ever. In order to fill this gap of annotated data-scarce situation, we look towards the ocean of free data present in Wikipedia and other […]

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A semantically rich framework to enable real-time knowledge extraction from short length semi-structured documents Lavana Elluri 10:30-11:30 Monday, 4 November 2019, ITE346 Knowledge is currently maintained as a large volume of unstructured text data in books, laws, regulations and policies, news and social media, academic and scientific reports, conversation and correspondence, etc. Most of these […]

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In my knowledge graph class yesterday we talked about the SPARQL query language and I illustrated it with DBpedia queries, including an example getting data about the movie Double Indemnity. I had brought a google assistant device and used it to compare its answers to those from DBpedia. When I asked the Google assistant “Who […]

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A new paper describing a system integrating a GDPR Ontology with blockchain to support checking data operations for compliance.

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