Aim/Purpose This research aims to investigate the relationship between digital citizenship behavior and political engagement among Generation Z (Gen Z) in Indonesia, with a particular focus on their participation in online boycott movements. The study examines the factors underlying Gen Z’s consumer activism in the digital era. Background People often perceive Gen Z as being tech-savvy and socially aware, but there has been limited research on how their online actions influence their political or consumer behavior in the real world. This article fills that gap by examining how digital citizenship activity is linked to political activism and boycotting. Methodology This study employed a quantitative methodology, surveying 100 Gen Z participants in Bandung City, Indonesia, utilizing electronic questionnaires disseminated via social media and Google Forms. Data were examined utilizing Structural Equation Modeling-Partial Least Squares (SEM-PLS) to evaluate the associations of digital citizenship activity, political involvement, and boycott behavior. Contribution This research expands existing knowledge by presenting empirical evidence on the non-significance of digital citizenship activity in predicting political activism and boycott behavior, while highlighting political activism as a key predictor of boycotts among Generation Z. Findings Key findings indicate that: (1) digital citizenship behavior does not significantly affect political activism or boycott behavior; (2) political activism positively influences boycott behavior; and (3) political activism does not mediate the relationship between digital citizenship behavior and boycott behavior. Recommendations for Practitioners Marketers and governments must acknowledge that although Gen Z is digitally engaged, their political and consumer behaviors are driven more by activism and specific issues than by generic internet activity. Recommendations for Researchers Future research should investigate alternative mediators, including ethical awareness, social influence, and perceived consumer efficacy, to enhance understanding of the connections between digital behavior, activism, and consumer choices. Impact on Society The findings underscore the importance of promoting meaningful political engagement among young people, as political activism, in conjunction with digital literacy, influences their social and consumer behaviors, thereby potentially shaping the future civic and economic environments. Future Research Future research should employ larger and more diverse samples, disaggregate the dimensions of digital citizenship, and include previously unexamined factors such as peer influence and trust in institutions to enhance the understanding of Generation Z’s activism and boycott behavior.

Aim/Purpose: In the field of primary and secondary healthcare, the widespread adoption of electronic health record (EHR) systems has resulted in the availability of a vast quantity of clinical data that is simple to access. From where we were before, this is a significant advancement in our situation. Background: Melanoma is a common skin cancer; nevertheless, despite the fact that it has a high death rate, medical professionals frequently make an incorrect diagnosis of it. It is essential to refer patients to arrive at an accurate prognosis from the beginning. Methodology: Within the scope of this investigation, we develop an ensemble evolutionary framework in order to classify cancer disorders through the utilization of electronic health information. Contribution: Electronic health record systems are responsible for this influence. The majority of this data originates from clinical reports that were either spoken or recorded by medical professionals. These reports were not arranged in any way. Findings: The proposed method outperforms the other approaches in terms of the classification rate, as we discovered when we ran the simulation to evaluate how well the model functions. Recommendation for Researchers: This work can be recommended for developing a novel framework that uses deep learning algorithms to effectively optimize the provision of healthcare services and address these issues. Future Research: This work can be enhanced using several deep-learning algorithms for better accuracy and performance.

Aim/Purpose This study examines how e-recruitment and employer branding influence Gen Z’s job application intentions in Indonesian SOEs, filling a gap in research on employer branding’s mediating role. Background This study aims to answer the extent to which e-recruitment affects the intention to apply through the mediating role of employer branding. Methodology This study employed a quantitative approach. Data collection was facilitated by questionnaires disseminated to 300 new graduates interested in applying to state-owned companies in Indonesia. The collected data were then analyzed using the SEM-PLS technique, supported by SmartPLS 4.0 software. Contribution This research provides a theoretical contribution to the literature on the intention to apply among Generation Z, especially in the context of state-owned enterprises in Indonesia. This research also provides practical implications for state-owned enterprises to increase their attractiveness as employers. Findings The study’s findings indicated that e-recruitment significantly influences employer branding but does not directly impact the intention to apply. However, employer branding plays a crucial role as it significantly affects the intention to apply. Moreover, employer branding also acts as a significant mediating factor in the relationship between e-recruitment and the intention to apply, further strengthening the indirect impact of e-recruitment on potential applicants’ intentions. Recommendations for Practitioners Indonesian state-owned enterprises are advised to strengthen their employer branding strategies that are creative and in line with the preferences of Gen Z, as well as to ensure transparency and responsiveness in the e-recruitment process to increase their attractiveness as a workplace of choice. Recommendations for Researchers Future researchers are encouraged to explore additional variables that influence intention to apply, such as the role of digital technology and social media. Comparison of various sectors and generations can also yield valuable insights and offer a more comprehensive perspective. Impact on Society The findings of this study contribute to improving the competitiveness of the Generation Z labor force and assist state-owned enterprises in Indonesia in their efforts to attract a greater number of young professionals, thereby reducing youth-based unemployment within the Indonesian workforce. Future Research Future research could explore the role of employer branding in various industry contexts further and include longitudinal analysis to observe changes in Generation Z’s preferences for employment.

Table of Contents for Volume 28 of Informing Science: The International Journal of an Emerging Transdiscipline, 2025

Aim/Purpose: The major goal of this work is to establish prediction patterns that can influence better diagnosis and treatment strategies using unidentified interactions between genes. Background: Driven by the rapid advances in genomics, knowledge of the factors causing disease depends more on deciphering the deep linkages existent in the data of gene expression. Common approaches typically fail to grasp temporal links when dealing with always-changing living biological systems. This work overcomes this restriction by leveraging the sequential learning abilities of LSTM together with the improved pattern recognition capacity of SVM. Methodology: Our method uses a hybrid model combining LSTM and SVM to forecast gene expression. Working together, the LSTM and SVM components find relevant features in the gene expression data, clarifying trends in the data. Furthermore, the LSTM component oversees data temporal dependencies. Regarding accuracy and interpretability, this extra method helps to improve prediction models used in the healthcare industry. Contribution: There are many ways to get a key insight from data on gene expression. The LSTM and SVM for biclustering gene expression data offer much for healthcare informatics. Findings: The proposed LSTM-based SVM is used to evaluate numerous current methods of evaluating performance metrics. Using these opens several opportunities for the development of customized medicine and the customization of therapies in line with personal genetic profiles. Recommendation for Researchers: Examining the LSTM-SVM hybrid model that has been proposed using a variety of healthcare-related datasets Future Research: This work can be enhanced using several deep-learning algorithms to achieve better accuracy and performance.

Aim/Purpose: Traditional hyperparameter tuning methods’ inefficiency and low accuracy in diabetes prediction. Application and evaluation of Bayesian optimization aim to increase the accuracy of diabetes prediction models. Background: Bayesian optimization (BO) has emerged as a powerful technique for hyperparameter tuning in machine learning models with its methodical approach for optimizing complex functions with expensive evaluations. Selecting the optimal hyperparameters for models can significantly increase prediction accuracy in the healthcare sector, particularly for diabetes prediction, hence improving patient outcomes and resource management. Methodology: Among the well-known diabetes databases used in the study is the Pima Indian Diabetes Database. Among the machine learning models developed and whose hyperparameters are modified via Bayesian optimization are Support Vector Machines (SVM), Random Forest, and Gradient Boosting Machines (GBM). The optimization process is compared with traditional tuning methods to assess improvements in model performance. Contribution: Problems include the increasing prevalence of diabetes worldwide and the role vital function prediction models play in early diagnosis and therapy. Especially when dealing with enormous datasets common in healthcare, grid search, and random search are sometimes computationally taxing and inefficient. However, Bayesian optimization promises a more practical and economical approach by selecting hyperparameters iteratively based on earlier evaluations. Findings: Bayesian optimization not only yields faster calculation times but also outperforms traditional methods. More precisely, models adapted by Bayesian optimization show greater sensitivity and specificity, which are crucial for accurate and prompt diabetes diagnosis. Recommendation for Researchers: By highlighting the specific elements and network characteristics that are behind the anomalies it discovers, on a real-time or large scale dataset. Future Research: This work can be improvised using several recent artificial intelligence algorithms with the integration of IoT on real-time datasets.

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

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

Aim/Purpose: Labeling a journal as “predatory” can do great damage to the journal and the individuals that have contributed to it. This paper considers whether the predatory classification has outlived its usefulness and what might replace it. Background: With the advent of open access publishing, the term “predatory” has increasingly been used to identify academic journals, conferences, and publishers whose practices are driven by profit or self-interest rather than the advancement of science. Absent clear standards for determining what is predatory and what is not, concerns have been raised about the misuse of the label. Methodology: Mixed methods: A brief review of the literature, some illustrative case studies, and conceptual analysis. Contribution: The paper provides recommendations for reducing the impact of illegitimate journals. Findings: Current predatory classifications are being assigned with little or no systematic research and virtually no accountability. The predatory/not predatory distinction does not accommodate alternative journal missions. Recommendations for Researchers: The distinction between legitimate and illegitimate journals requires consideration of each journal’s mission. To serve as a useful guide, a process akin to that used for accrediting institutions needs to be put in place. Impact on Society: Avoiding unnecessary damage to the careers of researchers starting out. Future Research: Refining the initial classification scheme proposed in the paper.