Aim/Purpose The relationship between music and language is well established in developmental psychology and educational research. Nevertheless, important questions remain, particularly concerning children aged 0-6 years, the educational setting, and the extent to which music training supports the early development of linguistic abilities. Background This systematic review addressed these issues by examining studies on typically developing children within the 0-6 age range in educational services. Methodology The methodology comprised a search strategy across five databases, a screening process, data extraction, quality appraisal, assessment of risk of bias, and narrative synthesis of the results. The eligibility criteria for the review included studies involving typically developing 0-6-year-olds that implemented music training conducted in nursery and kindergarten settings, did not include comparisons with older age groups, and reported outcomes related to language. Only evidence-based studies published in English were selected. Contribution This systematic review contributes to the body of knowledge on music-based interventions for the development of linguistic skills in educational services. Findings Thirteen studies were included in the final review, involving participant samples ranging from 25 to 201 individuals. The selected studies included journal articles and master’s and doctoral theses from various countries. Most of the studies reported that music training positively influenced the development of language in preschoolers in educational services. Recommendations for Practitioners Given the results, educational professionals should consider this systematic review when designing music-based interventions to enhance the growth and well-being of children and their communities within an integrated 0-6-year perspective. Recommendations for Researchers However, some limitations emerged. Researchers need to implement music-based interventions for the 0-3 age group and focus on specific language aspects, such as their use. Impact on Society Despite the limitations, this systematic review has an impact on the growth and well-being of children and communities, informing the design of educational programs. Future Research Finally, this systematic review focused on a typical 0-6 age population. Future research should focus on children with atypical developmental trajectories to provide a clearer overview of existing evidence on music-based interventions in educational services.
Aim/Purpose: This study investigates gender bias, an important social dimension in Requirements Engineering (RE), with a special emphasis on identifying challenges and mitigation strategies through a Systematic Literature Review (SLR). Background: Though an important activity, RE is heavily influenced by stakeholders’ social dynamics, particularly gender bias in software requirements. The less represented genders in RE may negatively influence the process, including a lack of inclusiveness in software products and limited diversity of perspectives. However, researchers and practitioners are exploring a comprehensive understanding of gender bias across various RE activities, and this research area is still emerging. Methodology: We conducted an SLR and explored the challenges and the mitigation strategies, techniques, and solutions reported in the literature to address gender bias in RE. This review investigates the ongoing challenges of gender bias in RE and the potential to mitigate them. Due to bias, the software design may lead to poorer outcomes, and the needs of diverse groups may be overlooked. The Kitchenham SLR guidelines are followed in this review to investigate relevant research studies, as they help identify the challenges, mitigation techniques, and the effectiveness of existing validation methods. During initial scanning, almost 3,889 studies on gender bias were found from computing sources. These studies are further screened for inclusion and exclusion criteria to select the most appropriate studies for formulating research questions. After applying the three major steps of Kitchenham SLR guidelines, gender bias challenges and mitigation techniques are identified. Contribution: The contribution of our work is multifaceted: (1) conducting a systematic review of existing literature, (2) identifying key challenges of gender bias in RE, and (3) highlighting the effectiveness of gender bias mitigation techniques to overcome the challenges. Findings: The findings indicate the persistent challenges posed by gender bias in RE and highlight existing mitigation strategies. Furthermore, gender bias in RE can result in poorly designed software and neglected diverse user needs. Recommendations for Practitioners: It is recommended that practitioners integrate inclusive practices across RE activities, adopt models and frameworks that cater to diverse users, and actively address gender bias. Recommendation for Researchers: Researchers should further investigate the validation of available mitigation techniques that address gender bias in RE. Also, new methods are needed to address gender bias in RE-related activities to ensure equity and fairness in software products. Impact on Society: The outcome of this study is helpful in addressing gender bias in RE, integrating inclusivity into software systems, and developing equitable systems well-aligned with the needs of diverse user groups. Future Research: In the future, more empirical studies will be conducted to validate gender-inclusive methods and tools across different RE scenarios. Promote continuous gender-sensitization and awareness programs for all stakeholders involved in RE to ensure long-term impact.
Aim/Purpose This paper addresses the need to understand how digital transformation, often framed as a technological process, is concretely translated into human resource management (HRM) practices. It examines how HR managers interpret and manage the organizational, cultural, and skill-related changes associated with digital transformation, situating these practices within the emerging Industry 5.0 landscape. Background While digital transformation is widely discussed in terms of technologies and future skills, less attention has been paid to how these changes are operationalized within everyday HR practices. This study addresses this gap by exploring how HR professionals experience and implement digital transformation in recruitment, talent management, and training. Methodology An exploratory qualitative design was adopted. Data were collected through 14 semi-structured interviews with HR managers, consultants, founders, and innovation managers from organizations of varying sizes across Northern and Central Italy. Interviews were transcribed verbatim and analyzed using thematic analysis informed by Corbin and Strauss (2008), with coding and constant comparison conducted iteratively. Contribution The paper contributes empirical evidence on how human-centered models of digital transformation are enacted in HR practices. It advances understanding of HRM as a strategic mediator between technological innovation and the human experience of work, particularly within the Industry 5.0 perspective. Findings The findings indicate that recruitment practices are progressively moving beyond a narrow focus on technical expertise, placing greater emphasis on candidates’ adaptability, learning agility, and digital mindset. At the same time, talent management is evolving toward more dynamic and flexible models that prioritize continuous learning, cross-functional collaboration, and inclusive development pathways that support fluid career trajectories. Training is increasingly understood as a strategic lever for fostering human–technology complementarity, requiring multidimensional, experiential, and personalized learning approaches that address both technical and transversal competencies. Overall, across all domains, digital transformation is not merely a technological upgrade but a broader cultural and organizational shift that reshapes roles, expectations, and ways of working. Recommendations for Practitioners Organizations should redesign recruitment processes to assess adaptability and learning orientation, develop talent management systems that support cross-functional mobility and continuous learning, and invest in experiential and personalized training that addresses both technical and soft skills. Leaders should foster psychological safety and support employees’ adaptation to technological change. Recommendations for Researchers Researchers should further investigate digital transformation through multi-level and multi-actor perspectives, integrating managerial and employee experiences. There is also a need for longitudinal and comparative studies to examine how HR practices evolve alongside specific technologies. Impact on Society By emphasizing human-centered HR strategies, the findings highlight pathways to implementing digital transformation that support employee development, engagement, and sustainable organizational change, contributing to more inclusive and resilient workplaces. Future Research Future research should triangulate managerial perspectives with employee-level data, examine sectoral differences, and assess the impact of specific technologies, such as AI-enabled tools and predictive analytics, on HR practices and employee experiences.
Aim/Purpose Workplace relationships are beneficial to organizations, but not all relationships are equally significant for enhancing performance. The study investigated the impact of supervisory relationships on employee performance through positive psychological characteristics comprising perceptions of organizational support, emotional intelligence, thriving at work, and employee resilience. Methodology Data were gathered using snowball sampling in a cross-sectional study of 395 entry-level employees at commercial banks in southern Nigeria and analyzed using partial least squares modeling to test hypotheses. Contribution The study presents a research model guided by social exchange theory and conservation of resources theory, which clarifies how supportive supervisory relationships enhance entry-level employee performance in Nigeria. Findings Supportive supervisory relationships and employee performance were positively related, and this effect was mediated by perceptions of organizational support, thriving at work, and employee resilience. The mediation of emotional intelligence was insignificant. Additionally, perceptions of organizational support, employee resilience, and emotional intelligence enhanced thriving at work, forming a sequence in which these relationships positively affect employee performance. Although the mediating role of emotional intelligence was not supported, it may facilitate other psychological responses, such as thriving at work, that are significant predictors of employee performance. Recommendations for Practitioners Nigerian organizations, particularly commercial banks, should adopt a task- and employee-centered supervisory approach to support the performance improvement of entry-level employees. Organizations should revise policy documents to reflect supportive behaviors that foster goal-oriented workplace relationships throughout the organization. Training should be provided to supervisors and employees to develop behaviors that build productive workplace relationships. Training modules should emphasize supportive leadership, employee support, resilience-building, thriving at work, and emotional intelligence. Management should also recognize the centrality of these employees’ psychological qualities, especially thriving at work, given their interrelatedness and strong correlation with superior performance. Periodic psychometric assessment can be conducted to gauge the mental state and development of entry-level employees. This can help supervisors balance the diverse needs, resources, and expectations related to tasks and employees, and ensure that employees feel comfortable expressing a variety of psychological qualities. Recruiting individuals with active-learning abilities and enthusiasm to work can have a profound effect on performance amid evolving work demands and expectations. Recommendations for Researchers Researchers can explore additional psychological dimensions and their mediating relationships. Examining the distinct effect of task- and employee-based relationships can provide more insights into the relationships among the concepts. Impact on Society The research framework shapes the development and performance of entry-level employees by informing strategic changes in supervisory practices within Nigerian organizations. Reframing these practices enhances employees’ psychological well-being and improves organizational performance in dynamic, competitive environments. Future Research Future research should focus on the individual effects of task- and employee-centered workplace relationships and use longitudinal data to provide more detailed insight into causal relationships.
Aim/Purpose This study explored the associations among stress, eating attitudes, self-esteem, physical activity, and wearable device engagement (use experience and usage period), alongside related health app use and health-tracking practices, among female university students in Kuwait. Background The proliferation of wearable health-monitoring technologies has reshaped personal healthcare and self-management among young adults. However, adoption and sustained use among female university students may be influenced by intersecting psychological and behavioural factors, including stress, self-esteem, physical activity, and eating attitudes, particularly in academic settings where stress and irregular health habits are common. Methodology The study utilised validated instruments: the Perceived Stress Scale, Eating Attitudes Test (EAT-26), Rosenberg Self-Esteem Scale, and the International Physical Activity Questionnaire. To achieve the study’s objectives, 325 female students were surveyed quantitatively. Descriptive statistics, correlation analysis, and linear regression were performed using SPSS. Contribution The study contributes to the extant literature on health informatics and behavioural psychology by providing a comprehensive understanding of how monitoring devices supporting self-care and health behavior management, and their sustained use among female university students, remain uneven and are shaped by the matter of health wearable devices in Kuwait. The study supports a shift toward holistic approaches to student well-being in higher education and public health. Findings The results revealed a positive self-rated health and moderate physical activity, alongside prominent academic-related stress and notable weight- and shape-related concerns. Stress and eating attitudes were strongly and reciprocally associated, while self-esteem showed a protective association with eating attitudes. Physical activity duration, but not intensity, was positively associated with self-esteem. Wearable device use experience was associated with higher physical activity intensity, whereas longer usage period was positively associated with self-esteem and eating attitudes, suggesting mixed effects of sustained self-tracking. Non-use was primarily attributed to lack of perceived need and cost, while many non-users expressed openness to future adoption. Future Research Future research should explore longitudinal or prospective designs to clarify temporal ordering and potential reciprocal effects, particularly between stress and eating attitudes. To better identify leverage points for targeted interventions, future work should test more comprehensive explanatory models that incorporate contextual and psychosocial variables (e.g., academic stress exposure, coping style, body image, and social support). To enhance the generalizability of the findings, a larger-scale survey across a broader geographical range would be beneficial.
Aim/Purpose This paper examines how robot anthropomorphism, gender, and individual characteristics shape perceptions, attitudes, and intentions toward robot bartenders. Background The paper examines human–robot interaction in a bar setting by exploring factors that promote positive perceptions and interactions between consumers and robot bartenders. Methodology The study was conducted through an in loco survey administered during recreational events. A between-subjects design was employed. Participants (N = 192) completed an online questionnaire by scanning a QR code and evaluating a randomly assigned robot image. The robot stimuli varied in levels of anthropomorphism and gender, resulting in four different robot conditions. Two questionnaires were used: the need for affiliation, measured using the Interpersonal Orientation Scale (Hill, 1987), and participants’ perceptions of the robot, assessed with items adapted from T. Kim et al. (2023). Contribution The paper contributes to the Human-Robot Interaction literature by highlighting how individual differences and social context shape perceptions and acceptance of service robots in the hospitality sector. Findings The findings indicate that male participants reported greater optimism and a stronger intention to use robot bartenders compared to female participants. Anthropomorphic robots were perceived as more human-like; however, they also elicited higher levels of consumer resistance. Additionally, participants attending the event alone perceived the robots as more human-like than those in group settings. Finally, a positive correlation emerged between Need for Affiliation and resistance to interacting with robot bartenders, suggesting that individuals with stronger interpersonal orientation may be more reluctant to engage with robotic service providers. Recommendations for Practitioners Hospitality providers, robot designers, and service managers should consider both robot design features and customers’ psychological and social characteristics to enhance acceptance of robot bartenders. While aligning robot gender with societal service-role stereotypes may increase user comfort, this approach risks reinforcing biased expectations and raising ethical concerns. Therefore, moderately anthropomorphic or gender-neutral robots that emphasize functionality and relational appropriateness may be more suitable for bar settings. Practitioners are also encouraged to adopt flexible, hybrid human–robot service models that adapt to different social contexts and customer preferences, while ensuring ethical, inclusive, and user-centred design choices. Recommendations for Researchers Researchers are encouraged to include individual and contextual variables in studies on service robot acceptance and to adopt theoretical models that integrate human psychological factors with robot-related features. Impact on Society The study highlights the importance of designing human–robot interactions that account for individual, psychological, and social differences to foster comfortable, socially acceptable customer experiences. By promoting more inclusive and user-centred robot design, the findings support the responsible integration of service robots into public and recreational environments. Future Research Future research should examine how consumers’ emotional states, familiarity, and prior experience shape acceptance, trust, and interactions with service robots. Further studies are needed on psychological evaluation processes, robot gender attribution, and the balance between human-like and machine-like features. Longitudinal and multi-user interaction studies would also help clarify group dynamics and sustained engagement in hospitality settings.
Aim/Purpose To diagnose the internal state of municipal digital transformation by identifying and characterizing the perception gaps between employees’ current and targeted states of back-office e-government systems (process efficiency, data integration, technological competence, digital stress). Background Despite large investments in municipal ICT and national digital strategies, back-office integration remains understudied; employee experiences may reveal implementation shortfalls that system metrics alone miss. This paper mobilizes a socio-technical and public-value perspective to address that gap. Methodology Online survey of municipal employees (final analysis, N = 386) using 30 paired Likert items (current vs. targeted). Quantitative analyses included paired-samples t-tests, effect sizes (Cohen’s d), exploratory factor analysis (EFA), K-means clustering, MANOVA/MANCOVA, and linear discriminant analysis (LDA). Missing data and standard diagnostics were reported and handled as described in the manuscript. Contribution Provides a diagnostic assessment of employee perceptions, offering an informative foundation for understanding the discrepancies between digital policy goals and operational realities. Findings Large perception gaps exist in all four dimensions: process efficiency, data integration (the largest gap), technological competence, and digital stress (current stress > target). Gaps vary by municipality type (districts have larger gaps than metros) and department (IT has smaller gaps). EFA supported three latent constructs; clustering yielded four user profiles (optimistic adapters, process challengers, technology strugglers, comprehensive gap experiencers). Recommendations for Practitioners Prioritize cross-departmental data integration, adopt a process-first IS redesign, expand distributed competence-building beyond IT units, and implement design/support measures to monitor and reduce digital stress, with a special focus on district municipalities. Recommendations for Researchers Use longitudinal and mixed methods designs to triangulate subjective perceptions with objective usage logs and performance metrics; evaluate targeted interventions experimentally; and conduct cross-national comparisons to assess contextual generalizability. Impact on Society Closing identified gaps can increase operational efficiency, equity of access, and public value of municipal services; failure to act risks deepening service inequalities and producing persistent administrative burdens and employee burnout. Future Research Longitudinal studies tracking perception change after targeted interventions; integration of system logs and outcome indicators; causal evaluation of training/process-redesign programs; and comparative studies across governance contexts.
In this editorial paper, I pose some questions about the role of informing science. I do so by considering the current global situation of polycrisis: war conflicts, genocides, humanitarian crisis, the climate change and the exacerbation of social inequalities occurring in a polarized violent public opinion perpetuating racist and discriminatory ideology. What is the purpose of academic writing in a world in which there are lives that do not matter? I take into account the spirit of informing science and the idea of transdisciplinary research to launch questions for prospective papers. The idea principle of solidarity is presented as a means for research-conducting, theory-building and informing science.
Aim/Purpose This paper investigates the marginal presence of psychodynamic perspectives in contemporary Western Work and Organizational Psychology (W-WOP), addressing concerns that such approaches remain overlooked despite their relevance to understanding the emotional and unconscious dimensions of work. Background Drawing on a Critical Work and Organizational Psychology (CWOP) perspective, the study examines how epistemic norms and disciplinary assumptions shape the visibility of psychodynamics within mainstream scientific venues. Methodology A documentary analysis of the most recently available conference programs from EAWOP and SIOP was conducted. Titles, countries of origin, psychodynamic topics, and contribution types were extracted and analyzed descriptively using frequency counts. Contribution The paper empirically maps the representation of psychodynamic scholarship in two major W-WOP conferences and offers a critical interpretation of its marginalization through the lens of epistemic hegemony. As a key theoretical insight, it suggests that the marginalization of psychodynamic approaches reflects broader patterns of epistemic hegemony, whereby certain paradigms are privileged while others are systematically excluded, shaping what counts as legitimate knowledge. Findings Out of 2,620 reviewed contributions, only nine (0.34%) explicitly referenced psychodynamic approaches. These appeared mostly as low-visibility posters, covered fragmented topics, and originated from a small set of countries. No psychodynamic content was integrated into high-profile programme formats. Recommendations for Practitioners Practitioners are encouraged to incorporate psychodynamic concepts when addressing organizational issues related to emotion, conflict, identity, and other processes that may relate to unconscious phenomena. Recommendations for Researchers Researchers are urged to engage with psychodynamic frameworks to expand epistemic diversity and to critically reflect on dominant assumptions shaping what counts as legitimate knowledge in W-WOP. Impact on Society Broadening W-WOP’s epistemological horizons may enhance the discipline’s capacity to address complex forms of suffering, inequality, and emotional strain in contemporary workplaces. Future Research Further studies should examine publication patterns, editorial practices, and doctoral training to better understand the institutional mechanisms driving epistemic marginalization.
Aim/Purpose The current research examines the impact of emotional regulation on job satisfaction and organizational citizenship behaviour (OCB) among nurses in selected government hospitals in Haryana. Background With the expansion of the service industry and increased competition, employees’ capacity to control their emotions has become an essential aspect of work effectiveness. In jobs like nursing that involve direct contact with patients or clients, employees are required to express emotions that project professionalism over their actual feelings. Methodology A purposive sampling method was employed to select the hospitals and study participants. The data was gathered from 200 nurses, and structural equation modelling (SEM) was used for data analysis. Contribution This research shows that emotional labour is a strong predictor of both job satisfaction and organizational citizenship behaviour among nurses. Findings The results showed that surface acting did not significantly contribute to influencing job satisfaction, while deep acting significantly boosted job satisfaction. Furthermore, surface acting had a negative effect on OCB, while deep acting significantly contributed to OCB. Job satisfaction also positively predicted OCB. The findings highlight the significance of promoting genuine emotional involvement among nurses to increase their job satisfaction and promote positive organizational behaviours. Recommendations for Practitioners The study provides practical implications for hospital managers and policy-makers to develop supportive emotional work areas that enhance employee well-being and organizational effectiveness. Recommendations for Researchers Future researchers can expand this research across multiple industries and can conduct a comparative study. Longitudinal and mixed-method designs will allow for more in-depth perspectives into emotional management and work-place behaviour. Adding other variables such as emotional intelligence, resilience, and leadership support will make future models more robust. Impact on Society The results indicate that healthcare organizations need to institute training, emotional support systems, and workplace policies that assist nurses in better regulation of emotions, thus enhancing job satisfaction and voluntary behaviour. Future Research Emotional labour can also be studied in other industries, for instance, banking institutions, lawyers and judges, bill collectors, frontline managers, the aviation industry, and call centres.
Aim/Purpose This study aims to explore the relationships among the negative effects of social media, academic pressure, and academic procrastination among college students. Background While social media facilitates interpersonal interaction, excessive use has been associated with distraction and psychological strain among students. Prior studies suggest that frequent social media engagement may reduce learning motivation, increase academic pressure, and be associated with procrastination. Methodology Grounded in stress-coping theory, this study employs structural equation modeling (SEM) to examine the interplay among the key variables. A total of 500 questionnaires were distributed across different academic years in college, with 456 valid responses used for analysis. Contribution This research offers a theoretical and empirical framework for examining the associations between social media use, academic behaviors, and psychological well-being. Findings The findings reveal that the negative effects of social media are significantly associated with higher academic pressure, which in turn is related to academic procrastination. Additionally, the negative impact of social media also shows a direct association with procrastination. Recommendations for Practitioners Educational interventions and awareness programs that address social media use and academic pressure may support students in managing procrastination behaviors. Recommendations for Researchers Future research could benefit from examining procrastination through cross-cultural lenses and assessing the long-term effects of digital distractions across diverse educational settings. Moreover, longitudinal studies are encouraged to track changes in social media usage patterns and their ongoing impact on academic outcomes over time. Impact on Society The findings underscore the relevance of digital exposure for student mental health and academic performance, suggesting the importance of promoting balanced technology use in educational contexts. Future Research Future research should investigate cultural variations in procrastination behaviors and examine the longitudinal effects of digital distractions on academic performance, particularly within the context of post-pandemic educational environments.
Aim/Purpose This paper critically examines how remote and hybrid work, though widely celebrated for increasing flexibility and sustainability, can reproduce or exacerbate structural, organizational, and psychological inequalities among employees. Background While remote work is often associated with positive outcomes, mainstream discussions underrepresent the disparities it can generate. This paper addresses this gap by applying a Critical Work and Organizational Psychology (CWOP) perspective to analyze inequities across access, control, and well-being. Methodology This is a concept-driven critical review. The selection of literature prioritized theoretical depth and relevance rather than exhaustive coverage. The analysis is interpretative and interdisciplinary, informed by work psychology, organizational studies, and labor sociology. Contribution The paper introduces a multidimensional critique of remote work, offering theoretical insights and practical recommendations to promote equity in remote and hybrid work environments. Findings Remote work access is stratified by job level, socioeconomic status, and digital infrastructure. Organizational control, biased monitoring, and visibility bias reinforce hierarchies. Individual disparities, such as psychological capital, caregiving burdens, and digital competence, further marginalize certain groups. Recommendations for Practitioners Organizations should adopt role-based eligibility, provide equitable resources, use outcome-based evaluations, and support caregivers and mental health needs. Recommendations for Researchers Future studies should assess the long-term impact of remote work on marginalized groups and examine how emerging technologies affect workplace equity. Impact on Society The findings highlight the risk that remote work may deepen societal inequalities if equity is not a central design goal. Future Research Research should explore intersectional impacts and the ethical integration of AI and digital tools in remote work.
Aim/Purpose This study aims to explore the dynamics of interreligious dialogue (IRD) among Buddhist, Hindu, Muslim, and Christian leaders in Sri Lanka and the Philippines using Ludwig Wittgenstein’s concepts of language games and rule-following. It seeks to: (1) analyze how religious traditions function as distinct yet overlapping language games; (2) identify barriers to effective IRD (e.g., political exploitation, historical grievances); and (3) develop context-sensitive strategies to foster interreligious harmony in pluralistic societies. Background Asia’s religious diversity presents opportunities for enrichment but also challenges due to linguistic, cultural, and doctrinal differences. Colonial legacies and nationalist projects have exacerbated tensions, transforming religious identities into political markers. Existing IRD models often overlook micro-linguistic barriers, assuming religious concepts are universally translatable. Wittgenstein’s philosophy offers a framework to address these gaps by emphasizing contextual meaning and communal practices over abstract definitions. Methodology The study employed a qualitative narrative inquiry design, engaging 18 religious leaders (10 from Sri Lanka and 8 from the Philippines) representing Buddhism, Hinduism, Islam, and Christianity. Data were collected through in-depth interviews, conducted both face-to-face and virtually, and analyzed using thematic coding with a Wittgensteinian framework. Ethical considerations included obtaining informed consent, ensuring confidentiality through coded identifiers, and conducting member checking to validate findings. Contribution This study makes four key contributions. Theoretically, it pioneers the application of Wittgenstein’s language games to Asian interreligious dialogue, showing how terms like dharma and jihad gain meaning through specific cultural contexts. Methodologically, it innovatively blends narrative inquiry with linguistic analysis to document real-world interfaith encounters. Practically, it offers concrete solutions for peacebuilding, such as creating hybrid terms like “peace guardians” that respect different traditions while fostering mutual understanding. It contributes to the Informing Science discipline by framing interreligious dialogue as an informing process, demonstrating that effective dialogue – like effective informing – requires linguistic humility and shared practices to bridge gaps across communities. Findings Common Ground: Shared ethical values (justice, peace) exist across traditions but are expressed through distinct language games. Misunderstandings: Decontextualized terms (e.g., jihad as “holy war”) fuel conflict; political manipulation and historical grievances persist. Future Aspirations: Leaders emphasize mutual respect, youth education, and structured dialogue to counter extremism. Recommendations for Practitioners Linguistic Mapping: Train facilitators to analyze religious terms within their native contexts. Hybrid Practices: Develop shared rituals (e.g., interfaith community projects) to foster organic understanding. Power Balancing: Ensure minority voices are included in dialogue structures. Recommendations for Researchers Expand studies to digital platforms and longitudinal designs. Compare IRD dynamics across Asian contexts (e.g., Sri Lanka vs. Indonesia). Include marginalized voices (women, youth) in future research. Impact on Society The study highlights how grassroots initiatives (e.g., Mindanao’s peace guardians) can decolonize IRD and build sustainable harmony. By reframing dialogue as shared practice rather than doctrinal debate, it offers pathways to reduce polarization in pluralistic societies. Future Research Explore AI and social media’s role in shaping interreligious dynamics. Investigate meta-language games for irreconcilable doctrinal differences. Examine the long-term efficacy of hybrid language games in conflict resolution.
Aim/Purpose In the past few years, news media organizations have been restructured by the progress in technology in many nations across the globe. This progress includes the utilization of artificial intelligence (AI) in news media. In India, the news media are undergoing changes with the inclusion of AI methods in various areas, such as news production and dissemination. Therefore, it becomes significant to study the impact of AI on news media in India. Background In this paper, the aim is to present a comprehensive survey of research done related to the usage as well as the impact of AI on Indian news media. The study aims to gather knowledge about the impact of AI on the transformation of news media practices in TV, print, and digital news media in our country. Methodology The narrative review methodology has been adopted in the research to conduct the literature review. Contribution The proposed work contributes to giving a comprehensive understanding of the impact of AI in Indian News media. Findings There has not been any comprehensive research related to the impact of AI on news media personnel in India. There is no study comprising the professional and economic impact of AI on news media personnel, such as reporters, producers, anchors, and owners of news media organizations. There has been no study about the perception of AI usage in Indian news media. Also, no study has been done on how AI can be used to enhance customer experience in news media in India. Recommendations for Researchers The proposed work aims to assist media students and researchers in conducting further research associated with the impact of AI in Indian news media based on data and analysis performed in the proposed work. Impact on Society The study can encourage the news media organizations to use AI more efficiently and help them to balance between AI and humans. Future Research As future work, comprehensive research on the impact of the usage of AI in TV, print, and digital Indian news media is proposed. This includes personal and professional experiences of news reporters, news producers, news consumers, and owners of news media organizations.
Aim/Purpose The study aims to critically examine the commonly held belief that role conflict always hampers administrative performance. It seeks to uncover how role conflict can, under certain conditions, enhance efficiency and foster organizational adaptability. Background Traditional management theories portray role conflict as a negative force causing stress and inefficiency. However, recent empirical research suggests that role conflict can stimulate growth, innovation, and better decision-making when well-managed. Methodology The paper systematically reviews multiple theoretical frameworks, including Role Theory, Person-Environment Fit Theory, Organizational Theory, and the JD-R model. By synthesizing these perspectives, it deconstructs simplistic assumptions about the negative impacts of role conflict. Contribution This study offers a nuanced understanding of the relationship between administrative performance and role conflict, moving beyond outdated views. It provides evidence-based insights into how role conflict can be harnessed positively within organizations. Findings The research finds that role conflict does not inherently reduce performance and can enhance administrative efficiency under the right circumstances. Administrators who effectively navigate conflicting responsibilities can drive innovation and adaptability within their organizations. Recommendations for Practitioners Practitioners should shift from avoiding role conflict to learning how to manage and leverage it for organizational improvement. They are encouraged to create environments that support adaptive leadership and embrace role complexity. Recommendations for Researchers Future research should explore the specific conditions and organizational contexts where role conflict becomes a constructive force. Researchers are also advised to develop models and tools that help quantify the positive impacts of managed role conflict. Impact on Society By reframing role conflict as a potential strength, this study supports more resilient and innovative organizations, ultimately benefiting societal governance and service delivery. It encourages a cultural shift toward embracing complexity in leadership, which can enhance institutional adaptability in the face of change. Future Research Future research should empirically test when role conflict improves administrative performance across various contexts. It should also develop practical tools or frameworks to help organizations manage role conflict effectively for positive outcomes.
Aim/Purpose This study explored public perceptions of the smart city concept in Kuwait and assessed their understanding of its features and dimensions. Background Over the past decade, the notion of “smart cities” has gained significant traction, with numerous urban areas eager to embrace this digital evolution. For a city to transition into a smart city, it must develop a service strategy that places the public as the primary beneficiary of the smart city services. Methodology The study employed the Smart City Wheel model, encompassing six key dimensions of a smart city: governance, mobility, people, economy, living, and environment. The ‘smartness’ of a city is assessed based on the level of advancement in these six key dimensions. To achieve the study’s objectives, 434 individuals were surveyed quantitatively. Contribution Existing studies highlight growing awareness of smart cities and the impact of visibility and demographics but often lack analysis of public perceptions of specific technologies. This study bridges that gap by examining public awareness and perceptions of Smart Cities in Kuwait. Findings The results revealed that just under half of the participants had some understanding of Smart Cities, reflecting moderate community awareness. More than a third of those aware believe their city is working towards becoming smart. However, over half of the respondents are unaware of the concept, indicating a significant knowledge gap. Among the unaware, more than a quarter think local authorities have made efforts to inform the public. Despite this, over three-quarters are interested in learning about Smart Cities, and two-thirds want to engage in city development decisions through digital platforms, demonstrating a potential for public involvement in smart city initiatives. Respondents strongly associate the six key dimensions with the Smart City concept, ranking their importance as follows: smart governance, smart mobility, smart environment, smart living, smart economy, and smart people. The most frequent activities were observed in smart people, smart economy, and smart living. Improvement needs are diverse, with frequent calls for enhancement in smart environment, smart living, and smart mobility. The results also reveal notable variations in the perceived importance of the dimensions and their correlations with the Smart City concept based on employment status, age, and education. Future Research Future research should explore alternative models and dimensions to provide a more comprehensive understanding of smart cities. To enhance the generalizability of the findings, a larger-scale survey conducted over a more comprehensive geographical range would be beneficial.
Aim/Purpose Technology adoption and utilization in educational institutions have increased since the pandemic. Recently, the learning management system has become crucial in the educational sector, enabling the efficient execution of online learning. In this study, we performed clustering on group learners to understand students’ concerns with the mobile Learning Management System (m-LMS) based on the clusters. Furthermore, we employed classification using the technology acceptance model to evaluate the correlation among factors necessitating the acceptance and use of m-LMS. Background Mobile learning (m-learning) is a prevalent method of education where educational content is accessed on the go via mobile devices such as smartphones and tablets. The acceptance and deployment of mobile learning in higher education institutions has become essential in Education 4.0, a reskilling approach associated with Industry 4.0. Since the pandemic, mobile learning management systems have seen increased usage among educational institutions. Methodology The study modified the standard data mining and knowledge discovery methodology. This study’s data set includes 446 students from the University of Education, Winneba, Ghana. The K-means algorithm was implemented to determine the number of clusters from the dataset according to the features. Subsequently, we employed a Pearson correlation coefficient heatmap to ascertain the predictability of perceived ease of use, perceived usefulness, attitude towards using, and actual system use of the features via the technology acceptance model. Then, a classifier was built by comparing five classification algorithms. Contribution A novel study on the application of a machine learning algorithm for a mobile learning management system dataset in Ghana. Implementing K-means, heatmap, and feature selection to understand learners’ concerns while using m-LMS in Ghana. Findings The findings indicate that Cluster 1 members disagree with the benefits of using m-LMS. The disagreement cuts across all the investigated variables: perceived usefulness, perceived ease of use, attitude toward using, and actual use. Cluster 2 members agree strongly with the benefits of using m-LMS across all the investigated variables. Cluster 0, with the highest number of members, moderately agrees with the benefits of using m-LMS. In addition, a strong correlation exists between perceived ease of use, perceived usefulness, and attitude towards using. Furthermore, the attitude towards using was predicted by perceived usefulness. However, there was an unreliable relationship between attitude towards using and actual system use. Recommendations for Practitioners Cluster segmentation of students using m-LMS facilitates the formulation of an implementation policy, enabling educational authorities to address the issues contributing to student dissatisfaction with m-LMS. Furthermore, the results imply that, even though students desire to use a mobile learning management system, they are not using it. It means there are challenges surrounding using the mobile learning management system at the University of Education, Winneba. Recommendations for Researchers The use of K-means, elbow function, and correlation heatmap in the technology acceptance model for variable correlation test reveals detailed predictability patterns that necessitate a new research direction using machine learning. Impact on Society Stakeholders in education should embrace and support machine learning implementation in the educational sector to reveal data patterns for improved teaching and learning. Future Research Subsequent research will broaden the data on mobile learning management systems to include the majority of tertiary institutions in Ghana. The data will be indicative, allowing for the generalisation of inferences regarding national policy directions on m-LMS.
Aim/Purpose This paper addresses the need for more holistic informing frameworks that bridge cognitive-centric approaches with embodied, relational, and imaginative modes of knowledge transfer, especially within complex transdisciplinary contexts where conventional informing processes often fail to facilitate deep understanding. Background Current Informing Science frameworks primarily focus on cognitive processing and linear data flow, leaving significant gaps in understanding how knowledge can be effectively transferred through non-cognitive pathways. This paper extends Informing Science by integrating diverse epistemologies, including non-Western and phenomenological perspectives, into a cohesive visual model. Methodology Using practice-led research methodology, this study developed and tested the Transdisciplinary Informing Model (TIM) through the creation and implementation of an immersive sensory experience (Fractals of Nature). Approximately 150 participants, including art students, alumni, community members, and change-makers, engaged with three sensory stations, generating creative artifacts that were analyzed for evidence of relational knowledge creation. Contribution This paper contributes to Informing Science by visualizing and operationalizing Montuori’s principles of transdisciplinary inquiry and extending Cohen’s three-environment model to include embodied, sensory, and imaginative dimensions of knowledge transfer. The hexagonal model structure illustrates previously unseen interdependencies between principles, creating a practical framework for cross-epistemological synthesis. Findings Evidence from the Fractals of Nature case study demonstrates that TIM effectively facilitates: (1) relational knowledge creation that bridges individual perspectives with ecological awareness; (2) cross-paradigmatic synthesis across scientific, cultural, and imaginative domains; and (3) embodied knowledge processing through multisensory engagement, enabling deeper, more integrated understanding than cognitive processing alone. Recommendations for Practitioners Practitioners should consider incorporating sensory, relational, and imaginative elements into informing processes, particularly in educational, organizational, and sustainability contexts where complex, systemic understanding is essential. TIM provides a structured yet flexible framework for designing transdisciplinary experiences that engage multiple ways of knowing. Recommendations for Researchers Future research should explore TIM’s applications across diverse cultural contexts, develop metrics for evaluating its impact on knowledge transfer, and investigate the long-term effects of embodied informing approaches. Researchers should also consider combining TIM with other informing frameworks to create hybrid approaches that leverage multiple models’ strengths. Impact on Society TIM’s approach to knowledge transfer has significant implications for addressing complex societal challenges that require integrated understanding across disciplines, cultures, and knowledge systems. By fostering embodied, relational understanding of interconnectedness, TIM could enhance public engagement with systemic issues like climate change, social inequality, and technological transformation. The framework’s emphasis on ethical relationality provides a foundation for more inclusive decision-making processes that honor diverse epistemologies, potentially contributing to more equitable and sustainable social systems that bridge intellectual understanding with embodied, collective wisdom. Future Research Building on this paper’s findings, future research should: (1) investigate TIM’s effectiveness in digital and virtual environments where sensory engagement takes different forms; (2) explore applications in cross-cultural collaborations where diverse epistemologies must be bridged; (3) develop quantitative and qualitative metrics to assess the depth and retention of knowledge gained through embodied informing processes; (4) examine how TIM might enhance informing processes in complex fields like healthcare, environmental management, and technology ethics where siloed knowledge creates barriers to holistic understanding; and (5) investigate the relationship between embodied informing and behavior change, particularly in sustainability contexts where knowledge alone often fails to motivate action.
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.
Aim/Purpose: To optimize healthcare resource allocation using residual convolutional neural networks. Background: In the early stages, several traditional methods were adopted and implement-ed; however, the rise of AI and its technologies increased development in the healthcare sector and made it reach a better height in Industry 4.0. In the early stages, several traditional methods were adopted and implemented; however, the rise of AI and its technologies increased development in the healthcare sector and made it reach a better height in Industry 4.0. The main problem of this research is focusing on the inefficient allocation of healthcare resources, which leads to less outcome and accuracy. This research’s main novelty and objective is to implement a predictive model that may allocate resources based on several factors. Methodology: In the proposed method, Residual CNNs, a deep learning architecture well-known for its efficacy in image classification applications, we assess healthcare data and estimate ideal resource distribution. Residual CNNs are well-trained in the dataset on several factors and characteristics. The model produces predictions of resource allocation that maximize healthcare outcomes using comprehension of complex relationships and patterns in the data. Contribution: The novel feature of this work is the integration of the state-of-the-art deep learning architecture Residual CNNs into the domain of healthcare resource allocation. The proposed method, Residual CNNs, is well-trained in the dataset on several factors and characteristics. The model produces predictions of resource allocation that maximize healthcare outcomes by comprehending complex relationships and patterns in the data. Findings: We show experimentally that the proposed approach effectively allocates healthcare resources. The residual CNN model outperforms traditional methods in accurately predicting resource allocation needs across different regions and demographic groups. We find significant increases in resource allocation efficiency by applying deep learning techniques, which enhance healthcare outcomes and reduce treatment disparities. Recommendation for Researchers: Investigations should prioritize the validation of the algorithm in various healthcare environments to assess its efficacy in clinical application. Future Research: This work can be enhanced in future research using several deep-learning algorithms to achieve better accuracy and performance.
