Certain trends in scientific research have important relevance to bioethics theory and practice. A growing stream of literature relates to increasing transparency and inclusivity of populations (stakeholders) in scientific research, from high volume data collection, synthesis, and analysis to verification and ethical scrutiny. The emergence of this stream of literature has implications for bioethics theory and practice. This paper seeks to make explicit these streams of literature and to relate these to bioethical issues, through consideration of certain extreme examples of scientific research where bioethical engagement is vital. Implications for theory and practice are derived, offering useful insights derived from multidisciplinary theory. Arguably, rapidly developing fields of citizen science such as informing science and others seeking to maximise stakeholder involvement in both research and bioethical engagement have emerged as a response to these types of issues; radically enhanced stakeholder engagement in science may herald a new maximally inclusive and transparent paradigm in bioethics based on lessons gained from exposure to increasingly uncertain ethical contexts of biomedical research.

The main aim of this paper is to provide a theoretically and empirically grounded discussion on IT-based organizational creativity support. This study attempts to answer the following questions: (1) what is the issue of organizational creativity and its IT-based support, (2) what is the demand for IT –based organizational creativity support; (3) what are the main determinants and barriers to IT-based organizational creativity support; and (4) what success factors are crucial for IT-based organizational creativity support. This paper presents the analysis results of a survey conducted in 25 selected organizations. The paper provides valuable information on the possibilities of IT applications in organizational creativity support as well as the associated success factors. It makes useful contribution to our better understanding of IT-based organizational creativity support issues.

Aim/Purpose Information Technology students’ learning outcomes improve when teaching methodology moves away from didactic behaviorist-based pedagogy toward a more heuristic constructivist-based version of andragogy. Background There is a distinctive difference, a notable gap, between the academic community and the business community in their views of the level of preparedness of recent information technology program graduates. Understanding how Information Technology curriculum is developed and taught along with the underpinning learning theory is needed to address the deficient attainment of learning outcomes at the heart of this matter. Methodology The case study research methodology has been selected to conduct the inquiry into this phenomenon. This empirical inquiry facilitates exploration of a contemporary phenomenon in depth within its real-life context using a variety of data sources. The subject of analysis will be two Information Technology classes composed of a combination of second year and third year students; both classes have six students, the same six students. Contribution It is the purpose of this research to show that the use of improved approaches to learning will produce more desirable learning outcomes. Findings The results of this inquiry clearly show that the use of the traditional behaviorist based pedagogic model to achieve college and university IT program learning outcomes is not as effective as a more constructivist based andragogic model. Recommendations Instruction based purely on either of these does a disservice to the typical college and university level learner. The correct approach lies somewhere in between them; the most successful outcome attainment would be the product of incorporating the best of both. Impact on Society Instructional strategies produce learning outcomes; learning outcomes demonstrate what knowledge has been acquired. Acquired knowledge is used by students as they pursue professional careers and other ventures in life. Future Research Learning and teaching approaches are not “one-size-fits-all” propositions; different strategies are appropriate for different circumstances and situations. Additional research should seek to introduce vehicles that will move learners away from one the traditional methodology that has been used throughout much of their educational careers to an approach that is better suited to equip them with the skills necessary to meet the challenges awaiting them in the professional world.

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: The aim of this paper is to identify the possibilities for reducing the second and third levels of the digital divide (or inequality) through conscious application of digital technologies, especially through the promotion of digital means for information, enlightenment, and entertainment. Background: This article reviews studies carried out between 2000 and 2017, which investigate the social benefits of digital technology use for disadvantaged user groups and, especially, of their outcomes in terms of increasing digital skills and motivation to use information and communication technologies. Methodology: The literature review of the selected texts was carried out using thematic content analysis. The coding scheme was open but based on the theory of three levels of digital divide by van Dijk. Contribution: The results of the analysis show the difficulties related to the attempts of reducing the digital divide on the second and third level using only digital interventions, but also reveal the potential of these interventions. Findings: The literature review confirms the connection of different levels of digital divide with other relational and structural inequalities. It provides insights into the strengths and weaknesses of digital interventions aimed at the reduction of digital inequalities. Their success depends on the consideration of the context and participants needs as well as on carefully planned strategies. The paper summarizes and demonstrates the shortcomings and limitations of poorly designed interventions in reducing the digital divide but emphasizes the possibilities of raising the motivation and benefits for the participants of strategically planned and implemented projects. Recommendations for Practitioners: While planning a digital intervention with the aim of reducing digital inequalities, it is necessary to assess carefully the context and the needs of participants. Educational interventions should be based on suitable didactic and learning strategies. Recommendation for Researchers: More research is needed into the factors that increase the effectiveness of digital interventions aimed at reducing the digital divide. Future Research: We will apply the findings of this literature review in an intervention in the context of Lithuanian towns of different sizes.

Aim/Purpose: In this paper, we discuss how a Transdisciplinary (TD) and a Community Based Participatory Research (CBPR) initiative was conceptualized, developed, implemented, and sustained at a small academic institution with limited research infrastructure, emphasizing the role of capacity building. Background: Most examples of the implementation of TD research come from large-scale initiatives in research-intensive institutions or centers with multiple resources to establish collaborations among experts from different disciplines. However less is known about the implementation of TD and CBPR initiatives in small academic settings. Methodology: This paper includes a discussion of the challenges and lessons learned of this process in a teaching-intensive Hispanic Serving Institution (HSI), which included a research component as part of the institutional priorities when it transitioned to a 4-year college in 2001. Contribution: We hope that our experience helps other researchers in similar institutions to engage in this type of research. Findings: In this case, a collaborative TD and CBPR initiative was successfully implemented despite limited resources for capacity building and research infrastructure, as well as diversity among researchers and community members. Recommendation for Researchers: To sustain institutional collaborative capacity in this type of institution, authors recommend continuous capacity building efforts and the development of modules and/or courses to provide formal TD training for junior faculty while encouraging researchers to interact and collaborate. In addition, the importance of the role of the community liaison is highlighted. Impact on Society: Successful TD and CBPR initiatives may have a positive impact on the reduction or elimination of health disparities which involve complex phenomena that requires a broad view from different perspectives. Future Research: Even though capacity building can facilitate the implementation of TD and CBPR, many challenges arise as an inherent result of community engagement and the integration of different disciplines. Thus, the need of continuous reflection to acknowledge them becomes critical for advancing TD and CBPR efforts.

Aim/Purpose: This paper describes the regulatory affairs discipline as a useful case in the study of both inter- and transdisciplinary science and dynamics related to communication across multiple boundaries. We will 1) outline the process that led to the development of transnational competencies for regulatory affairs graduate education, 2) discuss how the process highlights the transdisciplinary character of regulatory affairs, 3) provide implications for how to communicate the influence of this characterization to future healthcare professionals, and 4) draw conclusions regarding how our lessons-learned might inform other programs of study. Background: In the past few decades, the regulatory affairs profession has become more internationalized. This prompted the need for new competencies grounded in the transnational and cross-disciplinary contexts in which these professionals are required to operate. Methodology: A convenience sample of experienced regulatory affairs professionals from multiple disciplines contributed to the development of transnational competencies for a master’s program in regulatory affairs using a transdisciplinary framework. Contribution: An applied exemplar in which to understand how transdisciplinary characteristics can be communicated and applied in higher education. Recommendations for Practitioners: This paper recommends how competencies developed from a regulatory affairs program can serve as exemplars for other applied transdisciplinary higher education programs. Impact on Society: This framework provides a seldom-used reflective approach to regulatory affairs education that utilizes cross-disciplinary theory to inform competence-based formation of professionals.

Aim/Purpose: This paper introduces a Social Machine for collaborative sensemaking that the developers have configured to the requirements and challenges of transdisciplinary literature reviews. Background: Social Machines represent a promising model for unifying machines and social processes for a wide range of purposes. A development team led by the author is creating a Social Machine for activities that require users to combine pieces of information from multiple online sources and file types for various purposes. Methodology: The development team has applied emergent design processes, usability testing, and formative evaluation in the execution of the product road map. Contribution: A major challenge of the digital information age is how to tap into large volumes of online information and the collective intelligence of diverse groups to generate new knowledge, solve difficult problems, and drive innovation. A Transdisciplinary Social Machine (TDSM) enables new forms of interactions between humans, machines, and online content that have the potential to (a) improve outcomes of sensemaking activities that involve large collections of online documents and diverse groups and (b) make machines more capable of assisting humans in their sensemaking efforts. Findings: Preliminary findings suggest that TDSM promotes learning and the generation of new knowledge. Recommendations for Practitioners: TDSM has the potential to improve outcomes of literature reviews and similar activities that require distilling information from diverse online sources. Recommendation for Researchers: TDSM is an instrument for investigating sensemaking, an environment for studying various forms of human and machine interactions, and a subject for further evaluation. Impact on Society: In complex areas such as sustainability and healthcare research, TDSM has the potential to make decision-making more transparent and evidence-based, facilitate the production of new knowledge, and promote innovation. In education, TDSM has the potential to prepare students for the 21st century information economy. Future Research: Research is required to measure the effects of TDSM on cross-disciplinary communication, human and machine learning, and the outcomes of transdisciplinary research projects. The developers are planning a multiple case study using design-based research methodology to investigate these topics.

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: The complexity of scientific problems has spurred the development of transdisciplinary science, in which experts are brought together to collaborate across disciplinary and practice boundaries. These knowledge diverse teams can produce novel solutions, but they often fail to achieve their potential. Background: Leaders have a crucial role to play in enabling effective collaboration among these diverse experts. We propose that a critical predictor of whether a newly formed interdisciplinary team will perform well is the leader’s multidisciplinary breadth of experience, which we define as a leader’s possession of significant experience in multiple areas of research and practice. We suggest that these leaders will have the capability to skillfully manage the interactions within the team. Methodology: We test our prediction in a sample of 52 newly formed interdisciplinary medical research teams. We also observe and examine the communication patterns in a subset of these teams. Contribution: There is a lack of systematic study of the impact leaders have on newly formed interdisciplinary science teams whose members have little or no prior collaborative experience with each other, possess specialized knowledge, and have limited overlapping expertise. This study combines quantitative and qualitative methods to examine the effect of leader multidisciplinary experience on team communication patterns and innovation. Findings: Our study finds that teams are more innovative when their leader has a moderate breadth of multidisciplinary expertise. Exploration of team communication patterns suggests that leaders with moderate multidisciplinary breadth of experience actively stimulated information sharing across expert domains by choosing cross-cutting topics and drew individuals’ attention to the knowledge and approaches of others in the team. Recommendations for Practitioners: Insights from this work can have practical implications regarding how to best select and train leaders to facilitate cross-boundary collaboration in transdisciplinary science. This study elucidates a variety of communication strategies that leaders can to enhance the team innovativeness. Recommendation for Researchers: Further investigation into the underlying psychological states that these communication strategies elicit is needed. Future research should investigate psychological mediators such as knowledge consideration, perspective taking, and cognitive flexibility. Impact on Society: Transdisciplinary science is needed to solve society’s most complex problems. The more insight we gather about factors that can help these knowledge diverse teams to be successful, but more society will benefit. Future Research: More research is needed on team formation, leader experience, and team outcomes in transdisciplinary science teams in a variety of contexts.

Aim/Purpose: Given that leadership has been shown to play a key role in knowledge-producing organizations, leaders of transdisciplinary science have received surprisingly little empirical attention. This study addresses the research gap by examining leadership in the context of a new transdisciplinary research organization. Background: Drawing on complexity leadership theory—a framework developed for identifying behaviors that facilitate creativity, learning, and adaptability in complex adaptive systems—this study examines leadership roles and practices that affect the generation of adaptive dynamics in transdisciplinary science. Methodology: The study is based on a longitudinal, qualitative in-depth case study on a newly formed transdisciplinary research center and its leadership team. The data includes ethnographic observations from leadership meetings and interviews with leaders. Contribution: This unique empirical case contributes to the study of transdisciplinary science by shedding light on the actions of academic leaders as they try to support transdisciplinary conversation, learning, and collaboration in a new center. Findings: The analysis shows that the leaders relied on both enabling and administrative leadership practices in a way that made them the focal point of transdisciplinary knowledge integration and thus jeopardized the creation of adaptive dynamics throughout the organization. Recommendations for Practitioners: The study highlights the importance of having knowledge brokers and hybrid scholars in strategic positions at different levels of the transdisciplinary research organization already in its early stages. Recommendation for Researchers: Longitudinal qualitative case studies that rely on different types of data provide rich information on how new leadership conceptualizations are implemented in organizations and the complex ways in which they relate to knowledge creation processes and outcomes. Impact on Society: Transdisciplinary science has the potential to find cures to complex diseases. Understanding leadership in transdisciplinary science can help in maintaining transdisciplinary research activities in the long run and thus make it more impactful. Future Research: The use of leadership roles and practices will be examined at different developmental stages in the transdisciplinary research process.

Aim/Purpose: To understand the process of social change creation in social entrepreneurial ventures (SEVs), specifically emphasizing the role and nature of the communicative process in social change creation. Background: Drawing on data from seven SEVs from India and the US and employing a grounded theory methodology, this research scrutinizes the social change process and uncovers the role and characteristics of dialogue in this process. Methodology: Qualitative data was collected from seven social entrepreneurial organizations over a period of eight months from July 2011 to February 2012. Semi-structured interviews were conducted with a wide range of members within these social entrepreneurial organizations (n=27) with additional informal interviews with field workers and volunteers. Data from the semi-structured interviews and notes from observations were integrated with analyses of archival resources. Contribution: There is little scholarship about the process of social change creation and the necessary conditions to promote social change over time. Understanding the process of social change creation and the individual, interpersonal, and organizational conditions that facilitate the process is central to design of effective trans-sector TD problem solving ventures. This paper focuses on the process of social change creation in social entrepreneurial settings, specifically emphasizing the role and nature of the communicative process in social change creation. Findings: The reflections and experiences of the members of SEVs revealed that social entrepreneurship is a collective endeavor and this collective character is essential to its success. Collective organization and synergy, deep intra-organizational communication, and a conducive organizational context are critical for the creation of collective wisdom and knowledge networks for long-term collaborative community capacity building. Dialogue emerged as a central category linking the other categories to explain the process of social change creation. Organic organizational structure enables knowledge creation and integration through the process of organizational learning through deep and continuous social interaction, or dialogue. Recommendations for Practitioners: This research elucidated the key characteristics of the organizational context required to support the creation of social change. It also identified the critical role and characteristics of the communicative process required to generate structural knowledge and collective wisdom at the organizational level. Recommendation for Researchers: For individual and organizational learning, trans-sector transdisciplinary organizations require an appropriate organizational context. Key elements of such an organizational context include (1) understanding the ecology of the social problem; (2) organic organizational structure; (3) continuous and deep social interaction among all levels of the organization; (4) employee and community autonomy and empowerment; and (5) attention to subtle environmental changes in the system. These elements in combination lead to the creation of collective wisdom. Collective wisdom then feeds back into the conception, planning, and action stages of the iterative cycle of organizational knowledge creation to create positive social change. Impact on Society: Same as above Future Research: Future research model theoretically and study empirically the ecology of social entrepreneurship and trans-sector TD problem solving more broadly. For example, the ways in the personal attributes of social entrepreneurs (e.g., their leadership style, networking abilities) combine with circumstances at organizational, institutional, and international levels to influence the effectiveness of their efforts to promote positive social change within local and global communities. Second, the grounded theoretical framework developed here should be further refined and elaborated through the identification of additional key contextual factors that affect SEVs’ capacity to promote positive social change and to achieve sustainability in different socio-environmental contexts. There is also a need to translate the findings from this research to facilitate the creation of more inclusive problem solving contexts and practices.

Aim/Purpose: Collaborative, interdisciplinary research is growing rapidly, but we still have limited and fragmented understanding of what is arguably the heart of such research—collaborative, interdisciplinary reasoning (CIR). Background: This article integrates neo-Pragmatist theories of reasoning with insights from literature on interdisciplinary research to develop a working definition of collaborative, interdisciplinary reasoning. The article then applies this definition to an empirical example to demonstrate its utility. Methodology: The empirical example is an excerpt from a Toolbox workshop transcript. The article reconstructs a cogent, inductive, interdisciplinary argument from the excerpt to show how CIR can proceed in an actual team. Contribution: The study contributes operational definitions of ‘reasoning together’ and ‘collaborative, interdisciplinary reasoning’ to existing literature. It also demonstrates empirical methods for operationalizing these definitions, with the argument reconstruction providing a brief case study in how teams reason together. Findings: 1. Collaborative, interdisciplinary reasoning is the attempted integration of disciplinary contributions to exchange, evaluate, and assert claims that enable shared understanding and eventually action in a local context. 2. Pragma-dialectic argument reconstruction with conversation analysis is a method for observing such reasoning from a transcript. 3. The example team developed a strong inductive argument to integrate their disciplinary contributions about modeling. Recommendations for Practitioners: 1. Interdisciplinary work requires agreeing with teammates about what is assertible and why. 2. To assert something together legitimately requires making a cogent, integrated argument. Recommendation for Researchers: 1. An argument is the basic unit of analysis for interdisciplinary integration. 2. To assess the argument’s cogency, it is helpful to reconstruct it using pragma-dialectic principles and conversation analysis tools. 3. To assess the argument’s interdisciplinary integration and participant roles in the integration, it is helpful to graph the flow of words as a Sankey chart from participant-disciplines to the argument conclusion. Future Research: How does this definition of CIR relate to other interdisciplinary ‘cognition’ or ‘learning’ type theories? How can practitioners and theorists tell the difference between true intersubjectivity and superficial agreeableness in these dialogues? What makes an instance of CIR ‘good’ or ‘bad’? How does collaborative, transdisciplinary reasoning differ from CIR, if at all?

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 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: 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: Use of the term “rigor” is ubiquitous in the research community. But do we actually know what it means, and how it applies to transdisciplinary research? Background: Too often, rigor is presumed to mean following an established research protocol scrupulously. Unfortunately, that frequently leads to research with little or no impact. Methodology: We identify a sample of 62 articles with “rigor” in the title and analyze their content in order to capture the range of perspectives on rigor. We then analyze how these findings might apply to informing science. Contribution: This paper offers an approach to defining rigor that is theory based and appropriate for transdisciplinary research. Findings: Rigor definitions tend to fall into one of two categories: criteria-based and compliance-based. Which is appropriate depends on the research context. Even more variation was found with respect to relevance, which is often used as a catch-all for research characteristics that aren’t associated with rigor. Recommendations for Practitioners: Recognize that when researchers are referring to rigor and relevance, they of-ten mean these to apply to other researchers rather than to practice. When funding research, it is important to understand who the rigor and relevance are directed towards. Recommendations for Researchers: When using the term “rigor”, think carefully about which meaning is intended and be transparent about that meaning in your writing. Impact on Society: A great deal of public money is invested in achieving research rigor. Society should be aware of what it is buying with that funding. Future Research: Developing a better understanding of research fitness and the factors that contribute to it.

Aim/Purpose: The research problem of this study refers to the manner in which old and new mass media represented the significant social development surrounding two crashes of the Boeing 737 MAX airplane. Methodology: The study follows a qualitative case study methodology based on a sample of newspaper articles, TV programming, specialized technical publications, Twitter posts, and Facebook content. Contribution: The study contributes to understanding specifics and differences in representing extraordinary socio-economic events by different types of media. Findings: Key findings are that these media have constructed different realities surrounding the tragic events and exhibited informing distortions to different degrees. Recommendations for Practitioners: Practical implications of this study are relevant for the institutional and individual clients of informing with regard to selecting appropriate media for use. There are also implications for informers with regard to reducing distortions in informing. Recommendation for Researchers: Social media could be a channel for alternative learning rather than manipulation. Mainstream media were confirmed to be a loudspeaker for authorities as postulated in critical media research, and analytical media provided influential, deeper technical analysis. Future Research: As the Boeing case unfolds, it would be interesting to investigate any evolution in mediated realities.

Aim/Purpose: To discuss the Design Science Research approach by comparing some of its canons with observed practices in projects in which it is applied, in order to understand and structure it better. Background: Recent criticisms of the application of the Design Science Research (DSR) approach have pointed out the need to make it more approachable and less confusing to overcome deficiencies such as the unrealistic evaluation. Methodology: We identified and analyzed 92 articles that presented artifacts developed from DSR projects and another 60 articles with preceding or subsequent actions associated with these 92 projects. We applied the content analysis technique to these 152 articles, enabling the preparation of network diagrams and an analysis of the longitudinal evolution of these projects in terms of activities performed and the types of artifacts involved. Contribution: The content analysis of these 152 articles enabled the preparation of network diagrams and an analysis of the longitudinal evolution of these projects in terms of the activities and types of artifacts involved. Evidence was found of a precedence hierarchy among different types of artifacts, as well as nine new opportunities for entry points for the continuity of DSR studies. Only 14% of the DSR artifacts underwent an evaluation by typical end users, characterizing a tenth type of entry point. Regarding the evaluation process, four aspects were identified, which demonstrated that 86% of DSR artifact evaluations are unrealistic. Findings: We identified and defined a set of attributes that allows a better characterization and structuring of the artifact evaluation process. Analyzing the field data, we inferred a precedence hierarchy for different artifacts types, as well as nine new opportunities for entry points for the continuity of DSR studies. Recommendation for Researchers: The four attributes identified for analyzing evaluation processes serve as guidelines for practitioners and researchers to achieve a realistic evaluation of artifacts. Future Research: The nine new entry points identified serve as an inspiration for researchers to give continuity to DSR projects.

Aim/Purpose: In this paper we propose an ecosystem for translational learning that combines core learning principles with a multilevel construct that embraces the tenets of translational research, namely, teaming, translating, and implementing. The goal of the paper is to argue that knowledge of learning sciences is essential at the individual, team, and organizational levels in the translational science enterprise. Background: The two decades that we can now call the translational era of health and medicine have not been without challenges. Many inroads have been made in navigating how scientific teaming, translating knowledge across the health spectrum, and implementing change to our health systems, policies, and interventions can serve our changing global environment. These changes to the traditional health science enterprise require new ways of understanding knowledge, forging relationships, and managing this new tradition of science. Competency requirements that have become important to the enterprise are dependent on a deep understanding about how people learn as individuals, in teams, and within organizations and systems. Methodology: An individual, team, and organizational conceptual framework for learning in translational ecosystems is developed drawing on the learning science literature, a synthesis of 9 key learning principles and integrated with core competencies for translational science. Contribution: The translational learning ecosystem is a means by which to understand how translational science competencies can be reinforced by core learning principles as teaming, translating, and implementation intersect as part of the translational science enterprise. Findings: This paper connects learning science to tailored principles in a simplified way so that those working translational science with less knowledge of theories of learning and pedagogy may be able to access it in a clear and concise way. Recommendation for Researchers: This paper provides a framework for researchers who engage in the education of translational scientists as well as those who are charged with training new scientists in an emerging field critical to health and medicine. Future Research: The translational ecosystem described can serve to expand how teaching and learning impact scientific advances. In addition, it serves as a means in which to understand the impact of learning on micro, meso, and macro levels.

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: There is ample evidence that team processes matter more than the characteristics of individual team members; unfortunately, very few empirical studies have examined communication process variables closely or tied them to team outcomes. Background: The University of Miami Laboratory for Integrated Knowledge (U-LINK) is a pilot funding mechanism that was developed and implemented based on empirically-established best practices established in the literature on the Science of Team Science (SciTS). In addition to addressing grand societal challenges, teams engaged in processes designed to enhance the process of “teaming”. This study uses the Inputs-Mediator-Outputs-Inputs (IMOI) model as a blueprint for an investigation into how team communication processes (shared communication, shared leadership, formal meetings, informal meetings) influence intermediary team processes (goal clarity, role ambiguity, process clarity, trust) and team outcomes (team satisfaction, team productivity). Methodology: Monte Carlo methodologies were used to explore both longitudinal self-report (survey of communication and team outcome variables) data and objective data on scholarly productivity, collected from seventy-eight members of eleven real-world intact interdisciplinary teams to explore how team communication processes affect team outcomes. Contribution: This study is among the few that centers communication practice and processes in the operationalization and measurement of its constructs and which provides a test of hypotheses centered on key questions identified in the literature. Findings: Communication practices are important to team processes and outcomes. Shared communication and informal meetings were associated with increased team satisfaction and increased research productivity. Shared leadership was associated with increased research productivity, as well as improved process and goal clarity. Formal meetings were associated with increased goal clarity and decreased role ambiguity. Recommendation for Researchers: Studying intact interdisciplinary research teams requires innovative methods and clear specification of variables. Challenges associated with access to limited numbers of teams should not preclude engaging in research as each study contributes to our larger body of knowledge of the factors that influence the success of interdisciplinary research teams. Future Research: Future research should examine different team formation and funding mechanisms and extend observation and data collection for longer periods of time.

The purpose of this paper is to provide a model to help explain why ideas about reality differ. Misinformation is an important topic that in the past several years has gained prominence. The author developed a model of informing.

Aim/Purpose: Developing Digital Platform Ecosystems (DPE) to transform conventional Knowledge Management Systems (KM/KMS) scenarios promises significant benefits for individuals, institutions, as well as emerging knowledge economies. Background: The academic entrepreneurship project presented is aiming for such a KMS-DPE configuration. Having consolidated this author’s own and external re-search findings, realization is currently commencing with a start-up in a business incubator. Methodology: Design science research applying mixed one-sample case study and illustrative scenario approach focusing on conceptual analysis and entrepreneurship. Contribution: Although (academic) entrepreneurship is a young research area with recently growing interest, publications focusing on this transitional stage between maturing research and projected commercial viability of digital technologies are rare. Findings: A roadmap looking beyond the immediate early-start-up perspective is out-lined by integrating recent development-stage-related DPE-research and by addressing stakeholders diverse informing needs essential for system realization. Recommendations for Practitioners and Researchers: As this transdisciplinary perspective combines KM, informing, design science, and entrepreneurial research spaces, it may assist other researchers and practitioners facing similar circumstances and/or start-up opportunities. Impact on Society: The article advances the understanding of how DPE 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. Future Research: As the entrepreneurial agenda will complement (not substitute) the academic research, research priorities have been highlighted aligned to three future stages.

Aim/Purpose: This paper examines the impact of the transformational, servant, and paternalistic leadership styles on employee performance at the middle and senior levels. Background: Transdisciplinary research promotes the integration and development of various sciences. It provides more choices for leaders to adopt ways and practical activities to promote enterprise development. Complexity leadership theory emphasizes that effectively functioning organizations need distinct forms of leadership to work together. Leaders rely on different leadership practices in an emergent collaborative context, and finding an optimal balance is challenging. Many scholars have attempted to explore which leadership styles have a more significant impact on employees by distinguishing and defining types of leadership styles and explaining the process by which they influence employee behavior and performance. Various scholars have further explored and empirically demonstrated the impact of these three types of leadership styles (transformational, servant, paternalistic)on employee performance. While transformational and servant leadership have their roots in the West, paternalistic leadership has roots in China. Few scholars have conducted comparative studies on their positive impact on employee performance. How do these three leadership styles affect employee performance at the middle and senior levels in the Chinese context? Which combination of middle and senior leadership styles performs best? These are the second area that this paper will attempt to explore. Methodology: This study constructs a three-tier model at the senior, middle, and grassroots levels. A questionnaire survey was used to collect data. SPSS 22.0 and Amos were used for data analysis. Contribution: Through its construction of a three-tier model (senior, middle, and grassroots levels), the paper explores the combined effect of three leadership styles (transformational, servant, and paternalistic) on grassroots employees. It explores the impact of senior leaders across levels on grassroots employee performance, which is expected to provide a valuable addition to theories on leadership styles. It is also instructive to examine which leadership style performs better and what middle and senior leadership configurations are more conducive to driving beneficial employee behavior and, ultimately, corporate growth. Findings: The transformational, servant, and paternalistic leadership styles, both at the top and middle levels, have a significant positive relationship with employee performance; the middle leadership style plays a positive mediating role between the top leadership style and employee performance. In terms of impact on employee performance, transformational leadership shows the best results at both the top and middle levels, with paternalistic leadership second and servant leadership at the same level. Regarding which middle and senior leadership style pairing is the best, the sample is relatively small, and the gap between various pairing combinations is not evident from the data. If the sample size is enlarged, the coefficient will likely expand year-on-year. Therefore, we can assume that the pairing effect of top servant leadership and middle transformational leadership is the best, top paternalistic leadership and middle transformational leadership is the second-best, and the combination of top paternalistic leadership and middle-level servant leadership leaders is the weakest. Recommendation for Researchers: This paper extends the study of top and middle leadership’s combined effect on employee performance as a positive response to the call for multi-layer or cross-layer analysis in leadership research. The findings further enrich the literature on leadership style-related theories. The middle leadership style plays a positive mediating role between the top leadership style and employee performance. The trickle-down effect is further verified, i.e., the top leadership will have a permeating influence on employees through the middle leadership, and the top’s influence on the middle is generally more significant than the influence on grassroots employees. However, the difference between the influence of the middle leadership on the grassroots and that of the top on the grassroots is not apparent, which is inconsistent with the trickle-down effect that the middle leadership communicates more with the grassroots and has more influence on the grassroots, and further verification is needed. All three types of leaders positively affected employee performance, with the best being transformational leadership, paternalistic leadership, and servant leadership. This finding is consistent with some scholars and inconsistent with some scholars. The interested scholars can do further research. The better performance of diverse pairings in middle and senior leadership combinations is consistent with previous research suggesting that leadership styles have their own strengths and can be complementary. This paper further provides a comparative study of multiple leadership styles to validate the recognition and adaptability of leadership styles and further explain the complex relationship between leadership styles and employee job performance. Scholars can conduct comparative research on other leadership styles, and there may be different results. Future Research: Because of the cross-sectional data taken, the findings’ generalizability still needs further validation. There are many types of leadership styles, and there are other types of leadership styles that can be explored comparatively, perhaps leading to different findings. From another point of view, various leaders have their strengths, and they are not mutually hindering. More research is needed on team formation in a variety of contexts. Organic organizational structure enables knowledge creation and integration through the process of organizational learning through deep and continuous social interaction or dialogue. So we can further examine the influence process of leaders on employees from how to give full play to their advantages, such as improving shared leadership and shared communication.

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 Covid-19 pandemic has created many adverse effects. It overloads the healthcare system, causes deaths, and angers some at anti-covid restrictions. This study examines the feasibility of using technical and technological ideas to overcome these effects. The solution is based on new knowledge about the virus, its nature, formation, and activation in the environment. Background: The rapid spread of a new coronavirus infection is taking place against the background of a lack of time required to create new treatment scenarios for the disease, development, production, and vaccine safety research. In such a situation, it became necessary to gain this time for organizing and conducting events that could reduce the burden on the healthcare system. Methodology: The science that studies the morphology, physiology, genetics, ecology, and evolution of viruses is virology. The modern development of virology is moving towards a more accurate and comprehensive description of the mechanisms of interaction of viruses with the host organism. This contributed to the emergence of genomics, transcriptomics, proteomics, and immunomics. However, in virology, there is no particular discipline that sets itself three fundamental goals: to substantiate a single concept of the emergence of viruses; to study the natural mechanisms of formation of virus molecules in the environment; to describe the natural mechanisms of activation of certain viruses in the environment that cause viral pandemics. As a result, there are many articles among the published scientific articles on viruses dealing with the mechanisms of interaction of viruses with the host organism. However, there are no articles on the natural mechanisms of formation and activation of certain viruses in the environment. In the absence of such specialized articles, we were forced to use the method of systems transdisciplinary generalization of disciplinary knowledge to achieve our article’s purpose. Generalization created new knowledge about the nature of viruses, about the mechanisms of their formation and activation in the environment and cells of biological organisms. It is logical to assume that to synchronize the state of biological objects of all functional ensembles on the planet, it is necessary to create and activate appropriate “technological tools.” We have suggested and proved that RNA viruses play the role of such tools. Piezoelectricity activates viruses. It occurs during the compression and stretching of sedimentary rocks and bases of continental plates in different territories. Contribution: The systems transdisciplinary generalization of the knowledge of scientific disciplines made it possible to edit the concept of viruses, to eliminate stereotypes that arose due to the use of unsuccessful analogies. As a result of this generalization, it was possible to prove that viruses are not intracellular parasites. The virus is a “technological tool” of the planetary organizing component. This “tool” aims to correct the genetic programs of organisms of all functional ensembles (plants, animals, people), which will maintain the state of organisms and the parameters of their metabolism in changing environmental conditions. Findings: The viruses that triggered pandemics in the 20th century and early 21st century are RNA viruses. RNA molecules play the role of “technological tools” that the planetary organizing component uses to carry out short-term and long-term adjustments and constant support of the genetic programs of biological organisms. Therefore, in such a situation, it is advisable to talk not about the fight against the virus but only about eliminating the negative manifestations of the Covid-19 pandemic: reducing the number of people in need of emergency hospitalization, eliminating cases of the acute course of the disease and deaths. It is proposed to use certain technical and technological ideas and solutions to eliminate these negative manifestations. Recommendation for Researchers: This paper recommends that researchers use new interdisciplinary and transdisciplinary approaches. They challenge assumptions and conclusions about the nature of viruses, and the mechanisms of their formation and activation in the environment can initiate. Such new research might describe the mechanisms that form and activate viruses in the environment and the body’s cells. They also might provide practical use of this knowledge to eliminate the multiple speculations and fears that arise against the background of reports of the likely appearance of more deadly viruses and viral infections. Future Research: The results of a systems transdisciplinary generalization of disciplinary knowledge about the nature and purpose of viruses are essential for expanding the horizon of the scientific worldview. Future fundamental research on the mechanisms of objective organizing constituents, a general description given in this article, will contribute to a deeper understanding of chemical and biological evolution mechanisms in which modern humanity is involved. In due time, such an understanding will allow a new look at the existing scenarios of the world socio-economic order, explore and describe new principles of sustainable development of society.

Aim/Purpose: In this article, the subjective perspectives of young people in Ghana on the use of digital media are elaborated. The aim is to make the positions of young people visible in the often adult-dominated discourse on digital media and to overcome adult-centered considerations in academic and public debates. In addition, the focus on young people from the Global South is intended to help make their underrepresented voices present in this discourse. Background: Digital media devices and Internet access are conditional on people’s social, economic, and educational participation. Many people in the Global South in particular are not yet granted such access. For children and young people worldwide, the educational opportunities offered by digital media are associated with potential threats to mental health and well-being. However, young people’s views on digital media are rarely addressed, especially in the Global South. Methodology: Based on a qualitative thematic analysis of responses to open-ended questionnaire questions, young Ghanaians’ views on smartphone use and how it affects academic success are examined. Contribution: By focusing on the subjective perspectives of young people, especially from the Global South, voices that have hardly been heard in the discourse on digital media are made audible. This should help overcome the dominant adult-centered perspectives in this discourse. Findings: For young people in Ghana, digital media are part of their everyday lives and often necessary to succeed at school. At the same time, they are concerned about the dangers, e.g., from overuse or cybercrime, for which they have few strategies to deal with. In their answers, they refer to socio-culturally specific discourses and values as well as to generational hierarchies that they perceive and deal with, which go far beyond the topic of digital media use. This makes clear the social tensions in which the debate about digitalization is embedded. Recommendation for Researchers: Young people’s knowledge of and perspectives on digital media is an important resource for learning to use them in an emancipated way. Future Research: Future research should recognize young people as experts in their own right on the issue, explore ways to include their perspectives in the discourse on digital media use and work with them to harness the future potential of the technology and avoid risks.

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: The amount of information published has increased dramatically due to the information explosion. The issue of managing information as it expands at this rate lies in the development of information extraction technology that can turn unstructured data into organized data that is understandable and controllable by computers Background: The primary goal of named entity recognition (NER) is to extract named entities from amorphous materials and place them in pre-defined semantic classes. Methodology: In our work, we analyze various machine learning algorithms and implement K-NN which has been widely used in machine learning and remains one of the most popular methods to classify data. Contribution: To the researchers’ best knowledge, no published study has presented Named entity recognition for the Kikuyu language using a machine learning algorithm. This research will fill this gap by recognizing entities in the Kikuyu language. Findings: An evaluation was done by testing precision, recall, and F-measure. The experiment results demonstrate that using K-NN is effective in classification performance. Recommendation for Researchers: With enough training data, researchers could perform an experiment and check the learning curve with accuracy that compares to state of art NER. Future Research: Future studies may be done using unsupervised and semi-supervised learning algorithms for other resource-scarce languages.

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: With a focus on promoting sustainable career paths, this article investigates the intricate relationship between age diversity management and techno-complexity, emphasizing the pivotal role of a supportive work environment. Background: In the modern workplace, the dynamics of age diversity emerge as a crucial element influencing the well-being and productivity of employees, particularly amidst the swiftly evolving digital landscape. This becomes especially pertinent when considering workers’ unique challenges adapting to technological advancements. Methodology: Utilizing a cross-sectional design, data were collected from 160 employees in an Italian multinational company within the metalworking sector. Contribution: This study provides valuable insights into the complex dynamics between the aging climate, colleagues’ support, and techno-complexity. It emphasized the importance of considering the direct effects of organizational factors and their in-direct influences through social dynamics and support structures within the workplace. Findings: The results revealed the mediating role of colleagues’ support in the relationship between the aging climate and techno-complexity. These findings highlight the importance of a supportive work environment in the context of sustainable career development, contributing to a comprehensive understanding of diversity management within the modern digital era. Recommendation for Researchers: Our results open to a series of implications and future directions. First, the unexpected finding regarding the direct relationship between the aging climate and technostress calls for a deeper exploration of the intricacies involved. Future studies could delve into specific organizational contexts, technological demands, and individual differences that may modulate this relationship. Future Research: Future studies could delve into specific organizational contexts, technological demands, and individual differences that may modulate this relationship.

Aim/Purpose: This paper applies informing science principles to analyze the evolution of United States (U.S.) healthcare delivery, exploring how policy shifts, technological advancements, and changing practices have transformed informing processes within this complex system. By examining healthcare delivery through a transdisciplinary lens, we aim to enhance the understanding of intricate informing environments and their dynamics. Background: The U.S. healthcare system epitomizes a complex, evolving transdisciplinary domain intersecting information systems, policy, economics, and public health. Recent transformations in stakeholder information flow necessitate an informing science perspective to comprehend these changes fully. Methodology: We synthesize literature on U.S. healthcare delivery changes, employing informing science frameworks such as Cohen’s “informing environment” concept to analyze the evolution of healthcare informing processes. Contribution: This study expands informing science theory by examining how changes in a complex transdisciplinary system impact information flow, decision-making, and stakeholder interactions. The results provide insights into challenges and opportunities within evolving informing environments. Findings: Our analysis reveals significant alterations in the U.S. healthcare informing landscape due to policy, regulatory, and technological changes. We identify key transformations in client-sender-delivery system relationships, shifts in information asymmetry, and the emergence of novel informing channels and barriers. Recommendation for Researchers: Future studies should develop informing science models capable of capturing the complexity and dynamism of healthcare delivery systems, particularly amidst rapid technological and policy changes. Future Research: Further investigation is needed into how emerging technologies reshape healthcare informing processes and their impact on care quality, accessibility, and cost-effectiveness.

Aim/Purpose: The rise of virtual communication technologies and hybrid work contexts has brought significant changes to leadership dynamics, highlighting the need for effective management of teams operating in both face-to-face and virtual settings, known as hybrid teams. Background: This systematic review examines leadership models utilized in face-to-face and virtual teams, factors contributing to leadership emergence in these contexts, and effective strategies for leading hybrid teams. Methodology: In this study, three scientific databases were searched, resulting in the retrieval of 1,707 studies. These studies were then subjected to a review process following the PRISMA guidelines, ultimately leading to the inclusion of 15 research contributions in the final review. Contribution: Given the results, key strategies for practitioners include the development of strong communication skills, providing constructive feedback, and implementing efficient remote management techniques. Findings: The findings emphasize three prominent leadership models – transformational leadership, leader-member exchange (LMX), and shared leadership – all of which play crucial roles in hybrid team settings. Personality factors drive leadership emergence in face-to-face settings, while virtual settings benefit more from task-related behaviors. Recommendation for Researchers: This review informs researchers seeking to enhance leadership efficacy in modern group settings, aiding leaders in navigating the complexities of hybrid team environments.

Aim/Purpose: The paper discusses various factors contributing to disagreements, such as differing experiences, perspectives, and historical narratives, leading to disagreements within families and societies. It explores how beliefs, values, and biases feed into disagreements, with confirmation bias affecting decision-making and the media. Cultural values also play a role, showcasing conflicts between meritocracy and inclusivity in ethical decision-making. Haidt's Moral Foundations Theory highlights differences in value priorities between Western and Eastern societies. The impact of Western values like rationalism, freedom, and tolerance, under threat from Marxist illiberalism on campuses, is dis-cussed. The text also delves into disinformation, emotions in warfare, and the use of fake information and images for propaganda purposes. The need for diligent reporting to avoid spreading disinformation is emphasized, given its potential to create misconceptions and harm diplomatic relations.

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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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.

Mental illnesses are common among college students as well as their non-student peers, and the number and severity of these problems are increasing. It can be difficult to identify people suffering from mental illness and get the help they need early. So in this paper, the SqueezeR_MobileNet method is proposed. It performs feature fusion and early mental health prediction. Initially, outliers in the input data are detected and removed. After that, using missing data imputation and Z-score normalisation the pre-processing phase is executed. Next to this, for feature fusion, a combination of the Soergel metric and deep Kronecker network (DKN) is used. By utilising bootstrapping data augmentation is performed. Finally, early mental health prediction is done using SqueezeR_MobileNet, which is the incorporation of residual SqueezeNet and MobileNet. The devised approach has reached the highest specificity of 0.937, accuracy of 0.911 and sensitivity of 0.907.

This work demonstrates a hybrid deep learning (DL) model for lung cancer (LC) detection using CT images. Firstly, the input image is passed to the pre-processing stage, where the input image is filtered using a BF and the obtained filtered image is subjected to lung lobe segmentation, where segmentation is done using squeeze U-SegNet. Feature extraction is performed, where features including entropy with fuzzy local binary patterns (EFLBP), local optimal oriented pattern (LOOP), and grey level co-occurrence matrix (GLCM) features are mined. After completing the extracting of features, LC is detected utilising the hybrid efficient-ShuffleNet (HES-Net) method, wherein the HES-Net is established by the incorporation of EfficientNet and ShuffleNet. The presented HES-Net for LC detection is investigated for its performance concerning TNR, and TPR, and accuracy is established to have acquired values of 92.1%, 93.1%, and 91.3%.

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.

Data envelopment analysis (DEA) is widely used in various fields and for various models. Inverted data envelopment analysis (inverted DEA) is an extended model of DEA. Regression analysis (RA) is a statistical process for estimating the relationships among variables based on the model of averaged image. There are no essential relations among DEA and RA and inverted DEA. We creatively combine DEA, RA and inverted DEA to propose a new model: DEA-RA-Inverted DEA model. The model realises the efficiency estimation and evaluation through a discussion of the residual variables and the residual ratio coefficients. In addition, we will demonstrate the effectiveness of the model by applying it to efficiency estimation and evaluation of 16 Chinese logistics enterprises.

Takahito YOSHIDA,Takaharu YAGUCHI,Takashi MATSUBARA, Vol.E107-D, No.11, pp.1458-1462
Accurately simulating physical systems is essential in various fields. In recent years, deep learning has been used to automatically build models of such systems by learning from data. One such method is the neural ordinary differential equation (neural ODE), which treats the output of a neural network as the time derivative of the system states. However, while this and related methods have shown promise, their training strategies still require further development. Inspired by error analysis techniques in numerical analysis while replacing numerical errors with modeling errors, we propose the error-analytic strategy to address this issue. Therefore, our strategy can capture long-term errors and thus improve the accuracy of long-term predictions.
Publication Date: 2024/11/01

Myung-Hyun KIM,Seungkwang LEE, Vol.E107-D, No.11, pp.1449-1452
White-box cryptographic implementations often use masking and shuffling as countermeasures against key extraction attacks. To counter these defenses, higher-order Differential Computation Analysis (HO-DCA) and its variants have been developed. These methods aim to breach these countermeasures without needing reverse engineering. However, these non-invasive attacks are expensive and can be thwarted by updating the masking and shuffling techniques. This paper introduces a simple binary injection attack, aptly named clear & return, designed to bypass advanced masking and shuffling defenses employed in white-box cryptography. The attack involves injecting a small amount of assembly code, which effectively disables run-time random sources. This loss of randomness exposes the unprotected lookup value within white-box implementations, making them vulnerable to simple statistical analysis. In experiments targeting open-source white-box cryptographic implementations, the attack strategy of hijacking entries in the Global Offset Table (GOT) or function calls shows effectiveness in circumventing run-time countermeasures.
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

Yuan LI,Tingting HU,Ryuji FUCHIKAMI,Takeshi IKENAGA, Vol.E107-D, No.11, pp.1396-1407
1 millisecond (1-ms) vision systems are gaining increasing attention in diverse fields like factory automation and robotics, as the ultra-low delay ensures seamless and timely responses. Superpixel segmentation is a pivotal preprocessing to reduce the number of image primitives for subsequent processing. Recently, there has been a growing emphasis on leveraging deep network-based algorithms to pursue superior performance and better integration into other deep network tasks. Superpixel Sampling Network (SSN) employs a deep network for feature generation and employs differentiable SLIC for superpixel generation. SSN achieves high performance with a small number of parameters. However, implementing SSN on FPGAs for ultra-low delay faces challenges due to the final layer’s aggregation of intermediate results. To address this limitation, this paper proposes an aggregated to pipelined structure for FPGA implementation. The final layer is decomposed into individual final layers for each intermediate result. This architectural adjustment eliminates the need for memory to store intermediate results. Concurrently, the proposed structure leverages decomposed layers to facilitate a pipelined structure with pixel streaming input to achieve ultra-low latency. To cooperate with the pipelined structure, layer-partitioned memory architecture is proposed. Each final layer has dedicated memory for storing superpixel center information, allowing values to be read and calculated from memory without conflicts. Calculation results of each final layer are accumulated, and the result of each pixel is obtained as the stream reaches the last layer. Evaluation results demonstrate that boundary recall and under-segmentation error remain comparable to SSN, with an average label consistency improvement of 0.035 over SSN. From a hardware performance perspective, the proposed system processes 1000 FPS images with a delay of 0.947 ms/frame.
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

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.

In Italy, the reimbursement provided to healthcare organisations for medical and surgical procedures is based on the diagnosis related group weight (DRGW), which is an increasing function of the complexity of the procedures. This makes the reimbursement an upper unlimited function. This model does not include the relation of the volume with the complexity. The paper proposes a mathematical model for the optimisation of the reimbursement by determining the optimal mix of volume/procedure, considering the relation volume/complexity and DRGW/complexity. The decreasing, linear, and increasing returns to scale have been defined, and the optimal solution found. The comparison of the model with the traditional approach shows that the proposed model helps the healthcare system to discern the quantity of the reimbursement to provide to health organisations, while the traditional approach, neglecting the relation between the volume and the complexity, can result in an overestimation of the reimbursement.