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

Table of Contents for Volume 22 of Informing Science: the International Journal of an Emerging Transdiscipline, 2019

Aim/Purpose: The Informing Science Institute (ISI) is an informing system, designed using informing science principles, for the express purpose of informing researchers who study problems related to informing. This paper describes the ISI as an applied instance of an informing system and analyzes the channels, informers, and clients of the ISI. Background: This paper begins with a brief overview of the current activity of the ISI, as well as an introduction to informing science philosophy and an explanation of the need for a transdiscipline. The ISI is a non-profit organization that provides several informing channels, including 13 open-access, peer-reviewed journals, as well as conferences, books, and outreach activities. Methodology: Statistical analyses of the authors, institutions, and countries of origin were conducted for every ISI paper published between 1998 and December of 2019. Additionally, interviews were conducted with 5 current and former Editors-in-Chief of ISI journals. Contribution: This paper provides a current description and analysis of the ISI informing system’s channels, informers, and clients. Findings: The ISI has published over 4,100 articles by over 4,500 authors from over 600 universities. Statistical analyses of articles published in ISI journals demonstrated that the ISI is characterized in part by robust international participation, with significant participation by authors from countries that have been traditionally under-represented in academic publications. The ISI achieved these outcomes through the use of the philosophical principles and design guidelines for informing science.

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

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

Aim/Purpose: There is a need to find a way to utilize narrative storytelling in film to make students more aware of the impacts of global problems and how they are perceived. Background: Two films from the year 2015 from two very different places in the world explore the encroachment and secondary effects of urban civilization upon indigenous cultures. Methodology: An interpretive, qualitative, methodology was used in addressing and discussing the use of these two films as a persuasive communication teaching aid. Contribution: This paper offers an approach to using narratives of films on indigenous issues in education to inform students about real-world issues and the wide impacts of those on various cultures and populations. Findings: Through the discussion of the two films, we suggest that using films with indigenous themes is beneficial to a course curriculum in a variety of subjects from communication to history and politics, to help students visualize the problems at hand. Anecdotally, the authors note that students are more engaged and willing to discuss topics if they have watched films or clips that deal with those topics than if they have simply read about them. Recommendation for Researchers: Technology and use of visuals are used as teaching tools in a variety of fields. Film narratives can be used as a teaching tool in multiple fields and provide insight about a variety of ideas. Identifying films such as those with indigenous themes provides an example of how one film can bring up multiple, real-world, topics and through led discussion student reflection can potentially lead to self-insights and have lasting impacts. Future Research: Additional research and assessment can be done on the impact of teaching with films and their compelling story telling of issues, and what types of questions should be asked to maximize learning and the impact of film narratives.

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.

Table of Contents for Volume 23 of Informing Science: The International Journal of an Emerging Transdiscipline, 2020.

Aim/Purpose. This paper, although conceived earlier than the emergence of COVID-19 pandemic, addresses the problem of informing agility as part of organizational agility that has become a rather important issue for business survival. Background. While the general issues of business informing, and business intelligence (BI) in particular, have been widely researched, the dynamics of informing, their ability to act in accord with changes in business and preserve the key competencies has not been widely researched. In particular, the research on BI agility is rather scattered, and many issues need to be clarified. Methodology. A series of in-depth interviews with BI professionals to determine relations between organizational agility and BI agility, and to round up a set of key factors of BI agility. Contribution. The paper clarifies a candidate set of key factors of BI agility and gives ground for future research in relations with areas like corporate and BI resilience and culture. Findings. The interview results show the relations between organizational changes, and changes in BI activities. BI has limited potential in recognizing important external changes but can be rather helpful in making decision choices and detecting internal problems. Lack of communication between business and IT people, existence of data silos and shadow BI, and general inadequacy of organizational and BI culture are the key factors impairing BI agility. Recommendations for Practitioners. There are practical issues around BI agility that need solving, like the reason-able coverage of standards or creation of a dedicated unit to care about BI potential. Recommendations for Researchers. The research is still in its starting phase, but additional interesting directions start to emerge, like relations between BI agility, resilience and corporate agility, or the role of informing culture and BI culture for BI agility issues. Impact on Society. Agile business, especially in times of global shocks like COVID-19, loses less value and has more chances to survive. Future Research. Most likely this will be focused on the relations between BI agility, resilience, and corporate agility, and the role of informing culture and BI culture for BI agility issues.

Table of Contents for Volume 24 of Informing Science: The International Journal of an Emerging Transdiscipline, 2021

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: The integration of knowledge through the transdisciplinary method with the three concepts civilization, ideology, and geopolitics (CIG) enables the analysis of international relations in a new perspective and the informing strategists of countries, organizations, analysts, clients, etc. These three concepts express the transdisciplinarity that offers a new theoretical explanation and the informing science approach. Background: The integration of knowledge using the three concepts for the analysis of international relations has found adequate explanations from 1890 until the withdrawal of the United States from Afghanistan. Therefore, the CIG model theoretically and practically finds support for more than a century, as argued in the paper. Methodology: The present paper uses a mixed theory based on transdisciplinary methodology and informing science. The literature was reviewed to find and build the theoretical basis and provide appropriate examples. The theory is also based on the model used by Francis Fukuyama in his books on building and dissolution of states (middle-range theory). Contribution: This paper enables the rethinking of the limitations of research on a theoretical and practical basis that is done in many scientific circles, not to eliminate others but to enrich science even more. Findings: In the paper, the main findings are the following: Integrating the three CIG concepts according to the transdisciplinary method offers a new perspective to explain international relations using the IS method; The integration of the three concepts is worthwhile after 1980, when the model of cabinet governments falls, Bismarck falls, and public opinion starts to emerge; It was after 1980 that theories of civilization and geopolitics began to emerge along with ideologies to apply in practice; These three concepts offer explanations based on a CIG zone and in the periphery of the CIG zone. In the CIG zone the security sphere is more stable and long-term, while in periphery the cooperation is temporary and not long termed; The paper shows that the Cold War period is divided into two periods; The paper also finds that CIG explains with examples the events that happened after the Cold War and until present days; The paper also shows, based on the strategies of the superpowers, how they are extending their influence based on the CIG concepts. The paper also shows new patterns of cooperation and clashes between the superpowers’ security zones, which also provide an explanatory perspective for the USA withdrawal from Afghanistan. (We do not talk in the paper about the Afghanistan issue and USA withdrawal). Recommendation for Researchers: Scientific attributes in the integration of knowledge give researchers a more open and comprehensive perspective to make more accurate and practical analyses of international relations. According to this model, other theories are enriched that use the transdisciplinary method, IS, and the CIG as a model for the integration of knowledge. Future Research: Researchers and practitioners of this CIG model can find answers such as “Why did the USA fail in Afghanistan and why was it successful in Kosovo?” as well as other questions about finding a solution for Iraq, cooperation with China, etc.

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.

Table of Contents for Volume 25 of Informing Science: The International Journal of an Emerging Transdiscipline, 2022

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

Aim/Purpose: The aim of this study is to examine the role of psychological ownership for safety in boosting employee performance and the impact of Perceived Organizational Support for Safety (POSS) on workers’ well-being, considering the psychological aspects associated with workplace safety and exploring the mediating effect of employees’ commitment. Background: It is widely recognized that promoting workplace safety goes beyond purely physical measures and must also consider the psychological aspects associated with safety management. However, while some studies have shown the direct effect of POSS and Safety Ownership on safety outcomes, very few studies have explored the underlying mediating mechanism, as well as their impact on distal outcomes, such as well-being and performance. Methodology: The cross-sectional study was conducted on a convenience sample of a metal mechanic enterprise’s employees through an online self-assessment questionnaire. Contribution: This study contributes to understanding the mechanisms through which psychological ownership for safety, organizational support for safety, and psychological factors related to safety collectively influence organizational outcomes. Findings: Two indirect significant effects are described. The first is between POSS and well-being, and the second significant relation is between psychological ownership for safety and job performance. When employees perceive that their organization cares about safety, they will experience a stronger sense of commitment and, in turn, they will be more satisfied in the work context, and they will improve their job performance. Recommendation for Researchers: Researchers should take a transdisciplinary approach to enable the integration of knowledge and perspectives from different fields that are essential to understanding the full range of implications and applications of safety management. Future Research: It could be interesting to investigate a different point of view on safety (e.g., top management or health and safety officers) and explore concerns about how to successfully communicate and transfer safety climate during remote working activities.

Aim/Purpose: The aim of the present paper is to present a Noise Decision (ND) scale. First, it reports the development and validation of the instrument aimed at examining organizational factors that have an influence on decision-making and the level of noise. Second, it validates this rating scale by testing its discriminant and convergent validity with other measures to assess decision-making qualities. Background: According to the literature, the concept of noise is the unwanted variability present in judgments. The notion of noise concerns the systematic influence to which individuals are exposed in their environment. The literature in the field has found that noise reduction improves the perception of work performance. Methodology: The first study involves the development of a scale (composed of 36 items) consisting of semi-structured interviews, item development, and principal component analysis. The second study involves validation and convergent validity of this scale. In the first study, there were 43 employees from three medium-sized Italian multinationals. For the second study, a sample of 867 subjects was analysed. Contribution: This paper introduces the first scale aimed at assessing noise within individuals and, in the organizational context, within employees and employers. Findings: Results show that the estimated internal reliability for each of the ND subscales and also the correlations between the subscales were relatively low, suggesting that ND correctly measures the analyzed components. Furthermore, the validation of the psychometric qualities of the ND allowed for the assertion that the influence of noise is present in the decision-making process within the context of work environments, validating the initial hypotheses. Recommendation for Researchers: This paper aims to improve theory and research on decision-making; for example, by providing a possible implementation for scales for evaluating decision-making skills. Furthermore, detecting and limiting noise with a systematic method could improve both the quality of decisions and the quality of thought processes. Future Research: Given the measurement of ND, the study can be a starting point for future research on this topic. Since there is no literature about this construct, it would be necessary to spend more time researching, so that the topic becomes clearer. System noise has been tested by some researchers with a “noise audit,” which means giving the same problem to different people and measuring the differences in their responses. Repeating this kind of audit in conjunction with the ND in a specific work environment could be helpful to detect but also measure the influence of noise.

Aim/Purpose: This is an introductory paper for the developing special series on applied psychology and informing science. It takes into account the spirit of informing science to launch the first of three articles in the series on applied psychology. The paper concludes by raising questions for future investigations.

Table of Contents for Volume 26 of Informing Science: The International Journal of an Emerging Transdiscipline, 2023

Aim/Purpose: The aim of this paper is to examine Gen Z students located in a representative region of the United States when it comes to technology use, news and information gathering behaviors, civic engagement, and social concerns and whether differences exist based on institutional type. The purpose is to report this information so that academics can better understand the behaviors, priorities, and interests of current American students. Background: This paper investigates the mindset of Generation Z students living in the United States during a period of heightened civic unrest. Through the lens of the Theory of Generations, Uses and Gratifications Theory, and Intersectional Theory, this study aims to examine the Gen Z group and compare findings across populations. Methodology: An electronic survey was administered to students from 2019 through 2022. The survey included a combination of multiple responses, Likert scaled, dichotomous, open-ended, and ordinal questions. It was developed in the Survey Monkey system and reviewed by content and methodological experts to examine bias, vagueness, or potential semantic problems. The survey was pilot-tested in 2018 before implementation in order to explore the efficacy of the research methodology. It was then modified accordingly before widespread distribution to potential participants. The surveys were administered to students enrolled in classes taught by the authors, all of whom are educators. Participation was voluntary, optional, and anonymous. Contribution: This paper provides insight into the mindset of Generation Z students living in the United States, which is helpful to members of academia who should be informed about the current generation of students in higher education. Studying Generation Z helps us understand the future and can provide insight into the shifting needs and expectations of society. Findings: According to the findings, Gen Z are heavy users of digital technologies who use social media as their primary source for gathering news about current events as well as information for schoolwork. The majority of respondents considered themselves to be social activists. When institutional type was considered, there were notable differences with the students at the Historically Black College or University (HBCU), noting the greatest concern with a number of pressing issues, including racial justice/Black Lives Matter, women’s rights, gun violence, immigration reform, and human trafficking. Less significance across groups was found when LGBTQIA+ rights and climate change were considered. Recommendation for Researchers: As social media continues to proliferate in daily life and become a vital means of news and information gathering, additional studies such as the one presented here are needed. In other countries facing similarly turbulent times, measuring student interest, awareness, and engagement is highly informative. Future Research: Future research will explore the role that influencers have in opinion formation and the information-gathering habits of Gen Z.

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: In this paper we propose a framework identifying many of the unintended consequences of information technology and posit that the increased complexity brought about by IT is a proximate cause for these negative effects. Background: Builds upon the three-world model that has been evolving within the informing science transdiscipline. Methodology: We separate complexity into three categories: experienced complexity, intrinsic complexity, and extrinsic complexity. With the complexity cycle in mind, we consider how increasing complexity of all three forms can lead to unintended consequences at the individual, task and system levels. Examples of these consequences are discussed at the individual level (e.g., deskilling, barriers to advancement), the task level (e.g., perpetuation of past practices), as well as broader consequences that may result from the need to function in an environment that is more extrinsically complex (e.g., erosion of predictable causality, shortened time horizons, inequality, tribalism). We conclude by reflecting on the implications of attempting to manage or limit increases of complexity. Contribution: Shows how many unintended consequences of IT could be attributed to growing complexity. Findings: We find that these three forms of complexity feed into one another resulting in a positive feedback loop that we term the Complexity Cycle. As examples, we analyze ChatGPT, blockchain and quantum computing, through the lens of the complexity cycle, speculating how experienced complexity can lead to greater intrinsic complexity in task performance through the incorporation of IT which, in turn, increases the extrinsic complexity of the economic/technological environment. Recommendations for Practitioners: Consider treating increasing task complexity as an externality that should be considered as new systems are developed and deployed. Recommendation for Researchers: Provides opportunities for empirical investigation of the proposed model. Impact on Society: Systemic risks of complexity are proposed along with some proposals regarding how they might be addressed. Future Research: Empirical investigation of the proposed model and the degree to which cognitive changes created by the proposed complexity cycle are necessarily problematic.

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

Table of Contents for Volume 27 of Informing Science: The International Journal of an Emerging Transdiscipline, 2024

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

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

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

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

An optimisation-based decision-making support is proposed in this study in the form of fuzzy-probabilistic programming, which can be used to solve integrated order allocation, production planning, and inventory management problems in fuzzy and probabilistic uncertain environments. The problem was modelled in an uncertain mathematical optimisation model with two objectives: maximising the expectation of production volume and minimising the expectation of total operational cost subject to demand and other constraints. The model belongs to fuzzy-probabilistic bi-objective integer linear programming, and the generalised reduced gradient method combined with the branch-and-bound algorithm was utilised to solve the derived model. Numerical simulations were performed to illustrate how the optimal decision was formulated. The results showed that the proposed decision-making support was successful in providing the optimal decision with the maximum expectation of the production volume and minimum expectation of the total operational cost. Therefore, the approach can be implemented by decision-makers in manufacturing companies.

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.

This study addresses a critical chain project scheduling (CCPS) problem regarding the feeding buffer. The main contribution of this study lies in determining the critical chain when the feeding buffer is considered along with the project buffer, a less addressed issue in the critical chain literature. Using a mixed-integer nonlinear programming (MINLP) model, the critical chain of a project with no break-down and no overflow is found. Moreover, the impact of the feeding buffer on the criticality of activities is discussed. The problem is solved using the Lingo software package for validation in small-sized instances. Since the CCPS is known as an NP-hard problem, a genetic algorithm (GA) is also designed to solve large-scale instances. The algorithm's performance is confirmed using various project scheduling library test problems. Sensitivity analysis is implemented based on some crucial parameters, and the critical chain is analysed after conducting several experiments. It is shown how considering the feeding buffer makes different critical chains and how shortlisting activities and resources are optimally managed.

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

Shuoyan LIU,Chao LI,Yuxin LIU,Yanqiu WANG, Vol.E107-D, No.11, pp.1468-1471
Escalators are an indispensable facility in public places. While they can provide convenience to people, abnormal accidents can lead to serious consequences. Yolo is a function that detects human behavior in real time. However, the model exhibits low accuracy and a high miss rate for small targets. To this end, this paper proposes the Small Target High Performance YOLO (SH-YOLO) model to detect abnormal behavior in escalators. The SH-YOLO model first enhances the backbone network through attention mechanisms. Subsequently, a small target detection layer is incorporated in order to enhance detection of key points for small objects. Finally, the conv and the SPPF are replaced with a Region Dynamic Perception Depth Separable Conv (DR-DP-Conv) and Atrous Spatial Pyramid Pooling (ASPP), respectively. The experimental results demonstrate that the proposed model is capable of accurately and robustly detecting anomalies in the real-world escalator scene.
Publication Date: 2024/11/01

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

Nat PAVASANT,Takashi MORITA,Masayuki NUMAO,Ken-ichi FUKUI, Vol.E107-D, No.11, pp.1453-1457
We proposed a procedure to pre-process data used in a vector autoregressive (VAR) modeling of a temporal point process by using kernel density estimation. Vector autoregressive modeling of point-process data, for example, is being used for causality inference. The VAR model discretizes the timeline into small windows, and creates a time series by the presence of events in each window, and then models the presence of an event at the next time step by its history. The problem is that to get a longer history with high temporal resolution required a large number of windows, and thus, model parameters. We proposed the local density estimation procedure, which, instead of using the binary presence as the input to the model, performed kernel density estimation of the event history, and discretized the estimation to be used as the input. This allowed us to reduce the number of model parameters, especially in sparse data. Our experiment on a sparse Poisson process showed that this procedure vastly increases model prediction performance.
Publication Date: 2024/11/01

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

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

The Republic of India has witnessed an enormous leap in financial transactions after a sudden demonetisation in 2016. The study represents an in-depth analysis of the factors influencing e-wallets usage post-COVID situation covering the National Capital Region. The scientifically collected data were subjected to Pearson's correlation to recognise the correlation amongst the selected e-wallets. The usage of e-wallets is observed mainly during recharge, UPI payments, and utility payments. Through psychometric response and interaction analysis, six factors were selected and examined for data distribution and stable observation using standard deviation and variance coefficient. The coefficient of variance for six factors was observed ≤ 1. The weight of the factors noted to be secured way (0.184), to take advantage of cashback (0.182), low risk of theft (0.169), fast service (0.1689), ease to use (0.156), and saves time (0.139) using principal component eigenvectors analysis. Freecharge and Tez wallets reveal a maximum 99.2% correlation.

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.

Recent innovations in additive manufacturing (AM) have proven its efficacy for not only the manufacturing industry but also the healthcare industry. Researchers from Cal Poly, San Luis Obispo, and California State University Long Beach are developing a model that will determine the optimal locations for additive manufacturing hubs that can effectively serve both the manufacturing and healthcare industries. This paper will focus on providing an overview of the healthcare industry's unique needs for an AM hub and summarise the specific inputs for the model. The methods used to gather information include extensive literature research on current practices of AM models in healthcare and an inclusive survey of healthcare practitioners. This includes findings on AM's use for surgical planning and training models, the workflow to generate them, sourcing methods, and the AM techniques and materials used. This paper seeks to utilise the information gathered through literature research and surveys to provide guidance for the initial development of an AM hub location model that locates optimal service locations.

Collaboration between various stakeholders is crucial for healthcare digitalisation and eHealth utilisation. Given that valuable outcomes can emerge from collaborative interactions among multiple stakeholders, exploring a quadruple helix (QH) approach to collaboration may be fruitful in involving the public sector, business, citizens, and academia. Therefore, this study aimed to explore stakeholder views on eHealth collaboration from a QH perspective using the grounded theory methodology. First, an inductive qualitative study involving all stakeholders in the QH was conducted. Subsequently, the findings were related to the actor-resource-activity (ARA) model of business relationships. The results emphasise the role of considering diverse perspectives on collaboration because digitalisation and eHealth require teamwork to benefit the end users within various settings. A model depicting the various aspects of the ARA model related to digitalisation in a healthcare QH setting is presented.

Background and Objective: In response to the challenges of poor mapping outcomes and susceptibility to obstacles encountered by indoor mobile vehicles relying solely on pure cameras or pure LiDAR during their movements, this paper proposes an obstacle avoidance method for indoor mobile vehicles that integrates image and LiDAR data, thus achieving obstacle avoidance for mobile vehicles. Materials and Methods: This method combines data from a depth camera and LiDAR, employing the Gmapping SLAM algorithm for environmental mapping, along with the A* algorithm and TEB algorithm for local path planning. In addition, this approach incorporates gesture functionality, which can be used to control the vehicle in certain special scenarios where “pseudo-obstacles” exist. The method utilizes the YOLO V3 algorithm for gesture recognition. Results: This paper merges the maps generated by the depth camera and LiDAR, resulting in a three-dimensional map that is more enriched and better aligned with real-world conditions. Combined with the A* algorithm and TEB algorithm, an optimal route is planned, enabling the mobile vehicles to effectively obtain obstacle information and thus achieve obstacle avoidance. Additionally, the introduced gesture recognition feature, which has been validated, also effectively controls the forward and backward movements of the mobile vehicles, facilitating obstacle avoidance. Conclusion: The experimental platform for the mobile vehicles, which integrates depth camera and LiDAR, built in this study has been validated for real-time obstacle avoidance through path planning in indoor environments. The introduced gesture recognition also effectively enables obstacle avoidance for the mobile vehicles.

Ph.D. Dissertation Defense Modeling and Extracting Information about Cybersecurity Events from Text Taneeya Satyapanich 9:30-11:30 Monday, 18 November, 2019, ITE346? People now rely on the Internet to carry out much of their daily activities such as banking, ordering food, and socializing with their family and friends. The technology facilitates our lives, but also comes with […]

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Reinforcement Quantum Annealing: A Quantum-Assisted Learning Automata Approach We introduce the reinforcement quantum annealing (RQA) scheme in which an intelligent agent interacts with a quantum annealer that plays the stochastic environment role of learning automata and tries to iteratively find better Ising Hamiltonians for the given problem of interest. As a proof-of-concept, we propose a […]

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Results using the reinforcement learning technique on two SAT benchmarks using a D-Wave 2000Q quantum processor showed significantly better solutions with fewer samples compared to the best-known quantum annealing techniques.

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Do firms learn from their failed innovation attempts? Answering this question is important because failure is an integral part of exploratory learning. In this study, we explore whether and under what circumstances firms learn from their small failures in experimentation. Building on organizational learning literature, we examine the conditions under which prior failures influence firms' R&D output amount and quality. An empirical analysis of voluntary patent expirations (i.e., patents that firms give up by not paying renewal fees) in 97 pharmaceutical firms between 1980 and 2002 shows that the number, importance, and timing of small failures are associated with a decrease in R&D output (patent count) but an increase in the quality of the R&D output (forward citations to patents). Exploratory interviews suggest that the results are driven by a multi-level learning process from failures in pharmaceutical R&D. The findings contribute to the organizational learning literature by providing a nuanced view of learning from failures in experimentation.

Power in business schools is ubiquitous. We develop individuals for powerfull positions. Yet, the way we deal with power is limited by our utilitarian focus, avoiding the visceral nature of power. In relation to this we address two questions business schools don't ask: what is the experiential nature of power? How are we teaching power? We use experiential, aesthetic developments on power in the social sciences to critique the rational-utilitarian stance on power found in business schools, drawing on the work of Dewey and French philosopher Levinas to treat power as a lived phenomenon. We overview and critique approaches to teaching power in business curricula informed by our own research on Executive MBA students learning through choral conducting. Taking an appreciative-positive stance, this research showed students developing new, non-rational, non-utilitarian understandings of power. They developed nuanced learning on the feeling, relationality and responsibility of exercising power. Coming out of this we argue for more experiential and reflexive learning methods to be applied to the phenomena of power. Finally we shine a reflexive light on ourselves and our 'power to profess', suggesting ways we can change our own practice to better prepare our students for the power they wield.

Beside making organizations look like their peers through the adoption of similar attributes (which we call alignment), this paper highlights the fact that conformity also enables organizations to stand out by exhibiting highly salient attributes key to their field or industry (which we call conventionality). Building on the conformity and status literatures, and using the case of major U.S. symphony orchestras and the changes in their concert programing between 1879 and 1969, we hypothesize and find that middle-status organizations are more aligned, and middle-status individual leaders make more conventional choices than their low- and high-status peers. In addition, the extent to which middle-status leaders adopt conventional programming is moderated by the status of the organization and by its level of alignment. This paper offers a novel theory and operationalization of organizational conformity, and contributes to the literature on status effects, and more broadly to the understanding of the key issues of distinctiveness and conformity.