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This study aims to test the effect of a falsely balanced message (i.e. exposure to two opposing arguments) on perceived expert consensus about an interrogation practice.

Participants (N = 254) read a statement about minimization tactics and were assigned randomly to one of four conditions, where true expert consensus about the tactic was either presented as high or low, and a balanced message (i.e. read two opposing arguments about the factual nature of the tactic) was present or absent.

Results showed that exposure to balanced messages led to less perceived expert consensus; especially when true expert consensus about the tactic was high. Exposure to balanced messages also reduced public support for experts testifying about the interrogation tactic.

Such findings suggest that pairing expert knowledge (i.e. empirical evidence) about investigative interviewing issues with denials might be powerful enough to override scientific beliefs about important matters in this field.

Researchers in the field of investigative interviewing have put much effort into developing evidence-based interviewing practices and debunking misconceptions on the field. While knowledge mobilization is particularly important in this consequential, applied domain, there are some individuals who aim to hinder the advancement and reform of investigative interviewing. Falsely balancing scientific findings (e.g. minimization tactics imply leniency) with denials is but one of many practices that can distort the public’s perception of expert consensus on an issue. It is crucial for investigative interviewing researchers to recognize such strategies and develop ways to combat science denialism.

This study aims to develop a theoretical framework that marketing practitioners and scholars can adopt to enhance their understanding of how firms can effectively deploy and use digital human avatars as part of their global digital marketing strategy. By doing so, we inform investors of ongoing digital transformations of marketing practices that will equip marketeers to provide scalable, tailored, reliable and relevant digital self-service interactions to users, consequently improving the user/customer experience.

Thematic analysis was used to discover factors to enable the successful implementation of digital human avatars, drawing on in-depth interviews with fourteen executives of digital human avatars developer companies worldwide and analysis of ten podcasts and webinars with artificial intelligence (AI) experts.

Digital human avatars revitalise the international dynamic marketing capabilities (IDMCs) of firms by integrating advanced technologies that transform user interactions, improve engagement and facilitate knowledge acquisition, dissemination and usage across various sectors and business units globally. This integration promotes a dynamic approach to international brands, customer relationships and marketing knowledge management capabilities, offering profound value to users and firms.

Our first limitation is a lack of diversity in data sources. As digital human avatars are an emerging field, we had to limit our study to 14 experts in AI and 10 podcasts. While this method provides deep insights into the perspectives of those directly involved in the development and implementation of digital human avatars, it may not capture the views of end-users or consumers who interact with these avatars, which can be an avenue for further research. Our second limitation is the potential bias in the interpretation of our interview data and podcasts. This study’s approach to data analysis, where themes are derived from the data itself, carries a risk of subjective interpretation by the researchers. Future studies are encouraged to investigate the impact of digital human avatars across different organisational contexts and ecosystems, especially focusing on how these technologies are integrated and perceived in various international markets.

The novel framework has direct implications for innovators and marketing practitioners who aim to adopt digital human avatars in their marketing practices to enhance the effectiveness of international marketing strategies.

The adoption of digital human avatars can alleviate loneliest elderly and vulnerable people by being a companion. The human-like characteristics can impact sense of presence and attachment.

The novelty of our study lies in exploring the characteristics of technologies and practical factors that maximise the successful adoption of digital human avatars. We advance and contribute to the emerging theory of avatar marketing, IDMCs and absorptive capacity by demonstrating how digital human avatars could be adopted as part of a firm’s global digital marketing strategy. We focus specifically on six dimensions: outcomes and benefits, enhancements and capabilities, applications and domains, future implications, foundational elements and challenges and considerations. This framework has direct implications for innovators and marketing practitioners who aim to adopt digital human avatars in their marketing practices to enhance the effectiveness of international marketing strategies.

In India, more than 21.9% of the total population is below the poverty line, which compelled the government to initiate several policies for alleviating poverty and food insecurity. It can be argued that often non-poor households may become food insecure due to their irrational expenditure behaviour. The widespread consumerism and commercialism in rural India as a result of globalization often drive rural households to spend more on non-food items than food items. As a result, it is frequently observed that non-poor farmers excluded from the social security programs are highly malnourished as a result of food insecurity, which pushes them back into the poverty trap. This study reviews critically the methodologies applied to measure household poverty and food insecurity and examine the relationship between the two using primary data collected from two villages of the Balasore district of Odisha whose major livelihood relies on agriculture using the m-logit model for data analysis. Results show even households living above the poverty line suffer from the problem of food insecurity. About 20.5% of the non-poor are food insecure in the study villages. The study also finds a location-specific spatial autocorrelation of Multidimensional Poverty Index (MPI) and headcount ratio among the districts of the state using Moran's I. Hence, there is a need for properly targeted policy interventions and to revise the methodologies applied to measure household poverty and identify beneficiaries so that non-poor households are not deprived of food security programmes.

Transformational leadership has attained immense attraction in contemporary research for its positive contribution in implementation of Education 4.0. Drawing on social bond theory and employee stewardship theory, this study aims to examine the mediating roles of employee engagement and organisational citizenship behaviour between transformational leadership and Education 4.0 in higher educational institutions.

Data was collected through survey questionnaire by using three-wave time lagged study design from regular faculty members of Indian higher educational institutions. Hayes Process Macro was used for testing the parallel mediation model.

Transformational leadership has a positive and significant impact on Education 4.0. The results of this study indicate that employee engagement and organisational citizenship behaviour partially mediate the relationship between transformational leadership and Education 4.0. Furthermore, the analysis explains that employee engagement and organisational citizenship behaviour leveraged under transformational leadership act as parallel mediators, and there is no statistical difference between them.

To the best of the authors’ knowledge, this study is first in itself to consider more than one factor influencing the relationship between transformational leadership and Education 4.0, thus making ground for parallel mediation. This study addresses the urgent call by United Nations for achieving Sustainable Development Goals (SDGs) by ensuring quality education (SDG 4) and reducing inequality (SDG 10), thereby giving peaceful and strong intuitions (SDG 16).

This paper aims to introduce a novel modularity-based framework, Com_Tracker, designed to detect and track community structures in dynamic social networks without recomputing them from scratch at each snapshot. Despite extensive research in this area, existing approaches either require repetitive computations or fail to capture key community behavioral events, both of which limit the ability to generate timely and actionable insights. Efficiently tracking community structures is crucial for real-time decision-making in rapidly evolving networks, while capturing behavioral events is necessary for understanding deeper community dynamics. This study addresses these limitations by proposing a more efficient and adaptive solution. It aims to answer the following questions: How can we efficiently track community structures without recomputation? How can we detect significant community events over time?

Com_Tracker models dynamic social networks as a sequence of snapshots. First, it detects the community structure of the initial snapshot using a static community detection algorithm. Then, for each subsequent time step, Com_Tracker updates the community structure based on the previous snapshot, allowing it to track communities and detect their changes over time. The locus-based adjacency encoding scheme is adopted, and Pearson’s correlation guides the construction of neighboring solutions.

Experiments conducted on various networks demonstrate that Com_Tracker effectively detects community structures and tracks their evolution in dynamic social networks. The results highlight its potential for real-time tracking and provide promising performance outcomes.

Com_Tracker offers valuable insights into community evolution, helping practitioners across fields such as resource management, public security, marketing and public health. By understanding how communities evolve, decision-makers can better allocate resources, enhance targeted strategies and predict future community behaviors, improving overall responsiveness to changes in network dynamics.

Com_Tracker addresses critical gaps in existing research by combining the strengths of modularity maximization with efficient tracking of community changes. Unlike previous methods that either recompute structures or fail to capture behavioral events, Com_Tracker provides an incremental, adaptive framework capable of detecting both community evolution and behavioral changes, enhancing real-world applicability in dynamic environments.

This chapter presents an international review of the experiences of children and parents regarding care during the COVID-19 pandemic. The pandemic profoundly impacted children and families, magnifying the influence of governmental policies, socio-economic disparities and cultural contexts on children's experiences and exacerbating global inequalities. Vulnerable families faced increased challenges affecting children's rights and well-being, while the transition to digital learning highlighted the critical need for equitable access to technology. Despite extensive documentation of these challenges, research focusing on the pandemic's impact on young children's development, well-being, socialization and learning opportunities, as well as the experiences of parents/carers, remains limited. This scarcity stems from the pandemic's constraints on research activities, requiring reliance on online methods and the increased burdens on parents/carers, making participation in research more challenging.

Employing the PRISMA 2020 method for a literature review, this chapter aggregates international research findings on the subject, examining the impacts of COVID-19 on health and well-being, knowledge of the pandemic, effects on learning, educational strategies, online activity engagement and collaboration with Early Childhood Education and Care (ECEC) services. It concludes with a synthesis of insights and recommendations drawn from the reviewed literature.

The chapter contributes to a comprehensive framework for understanding the pandemic's impact on young children and their families, emphasising the importance of targeted interventions, equitable resource distribution and ongoing support for the ECEC sector to address the challenges and opportunities presented by the COVID-19 pandemic and future crises.

Comparative analyses in education science have traditionally focused on the category of geographic location as the comparative unit. However, comparison may involve many other units of analysis, such as culture, politics, curricula, education systems, social phenomena, and other categories of the lives of societies. Still, categories are inseparably linked to one or several geographic locations. Comparative approaches are often also dictated by the availability heuristic. Studying geographic units as the foci of comparative research is a necessary step for comparative presentation of the topic. According to Bray and Thomas, a researcher must always seek preliminary insight in the geographic unit to be analyzed before making the comparison. In social science research, a unit of analysis relates to the main object of the research, as it answers the question of “who” or “what” is going to be analyzed. The most common units of analysis are people, groups, organizations, artifacts or phenomena, and social interactions. Ragin and Amoroso have noted that comparative methods can be used to explain the commonness or diversity of results. This paper shows how comparative research can be approached in ways that have not been discussed, grounded in the historically variable understanding of the very term “comparison.” They are, for example, The Ogden-Richards triangle, The Porphyrian Tree, Classification strategies – Mill’s Canons, The chaos of the world – the order of science, Weber’s ideal types, Raymond Boudon’s formula, and the Möbius strip in comparativism.

This research examines the employability challenges faced by skilled female migrants in the Australian construction industry, focusing on barriers to employment and their negative impacts on confidence, health and well-being. The paper concludes with recommendations for construction firms and policymakers to improve the employability of these women, offering insights that are applicable internationally.

Using employability theory, the study draws on semi-structured interviews with 16 skilled female migrants seeking employment in the Australian construction industry. The interviews captured the lived experiences of these women, and thematic analysis was applied to identify key barriers and inform recommendations for construction firms and policymakers.

The findings provide new conceptual insights into the multiple barriers which female skilled migrants have to overcome in improving their employability in the construction industry. It is also found that these experiences of seeking employment in construction align with the theoretical concept of “contextualized employability” and have potentially profound negative impacts on skilled female migrants’ confidence, hope, health, well-being and family and community relationships. This is despite the Australian construction industry facing a serious labour and skills shortage and being the most gender segregated industry in Australia. The study highlights the need for tailored support, improved industry practices and collaborative efforts from government and private sectors to enhance the employability and integration of skilled female migrants in the construction industry.

The research is limited by its focus on the Australian context, which may not be generalisable to other countries with different institutional systems, policies and cultural attitudes towards migrants. The sample size of 16 participants, while providing in-depth insights, may not capture the full diversity of experiences among female skilled migrants. Further research is needed in other countries to compare findings and develop more comprehensive strategies. Despite these limitations, the study’s implications highlight the urgent need for better support systems and industry reforms to improve the employability of skilled female migrants in the construction sector.

Improving the employability of skilled female migrants promotes social integration, mental health and stronger community ties. It challenges gender stereotypes and reduces discrimination in the construction industry, contributing to a more diverse and inclusive workforce. Practical recommendations include mentorship programs, inclusive recruitment and tailored training. Social procurement policies could set hiring targets for female migrants in the construction industry, while streamlined qualification recognition and tax incentives can encourage hiring. Non-profits and community organisations can support these efforts through mentorship, networking and internships, helping these women build sustainable careers and strengthen workforce diversity. The recommendations aim at enhancing the job prospects and overall well-being of these women while addressing labour shortages in the construction industry.

This study contributes original insights into the under-researched area of skilled female migrants’ employability in the construction industry. It expands employability theory by highlighting the impact of intersecting factors such as gender, migration status and industry-specific barriers on employment outcomes. Its practical recommendations offer pathways for policymakers and industry leaders to improve the integration and employment outcomes of this untapped talent pool.

Lacking lecturers in higher education is an international issue where society faces insufficient educational services to enlighten one’s future, and lecturer work satisfaction also merits higher attention. Work satisfaction is closely associated with turnover rates, lecturer retention, overall university cohesion, lecturers’ well-being, professional teaching improvement and research and publication performances. This study aims to explore how causes of actions (work–family conflict [WFC] and workload) influence consequences (stress and burnout) which affect the overall attitude (lecturer work satisfaction).

Researchers collected data from 450 Thai lecturers from different universities via survey questionnaires. Furthermore, a structural equation model method was used to analyze the data.

Results showed that lecturer stress was significantly influenced by WFC and workload. Next, stress, workload and WFC were the main predictors of lecturer burnout. Then, lecturer work satisfaction was significantly influenced by burnout, except stress. Finally, a relationship between lecturer stress and work satisfaction was mediated by burnout.

This research proposes a theoretical mechanism to analyze how causes of actions (WFC and workload) influence consequences (stress and burnout) which lead to a development of lecturer attitude (work satisfaction) in higher education.

Many organizations currently transition towards digitalized process design, execution, control, assurance and improvement, and the purpose of this research is to empirically demonstrate how data-based operational excellence techniques are useful in digitalized environments by means of the optimization of a robotic process automation deployment.

An interpretive mixed-method case study approach comprising both secondary Lean Six Sigma (LSS) project data together with participant-as-observer archival observations is applied. A case report, comprising per DMAIC phase (1) the objectives, (2) the main deliverables, (3) the results and (4) the key actions leading to achieving the presented results is presented.

Key findings comprise (1) the importance of understanding how to acquire and prepare large system generated data and (2) the need for better large system-generated database validation mechanisms. Finally (3) the importance of process contextual understanding of the LSS project lead is emphasized, together with (4) the need for LSS foundational curriculum developments in order to be effective in digitalized environments.

This study provides a rich prescriptive demonstration of LSS methodology implementation for RPA deployment improvement, and is one of the few empirical demonstrations of LSS based problem solving methodology in industry 4.0 contexts.