Search

Abstract Cybercrime is a complex human behavior and social phenomenon. The COVID-19 pandemic has significantly altered socioeconomic activities, potentially causing changes in crime patterns. However, there has been limited research on how the interaction between the pandemic and socioeconomic factors affects cybercrime. Here we explore the spatiotemporal patterns of police-recorded cybercrime, including fraud and cyber-dependent crime, and employ a machine learning approach to assess the correlation of various factors on cybercrimes at the level of internal regions and police areas within the United Kingdom. Our results show that fraud and cyber-dependent crime are mainly concentrated in London and the southeast region of England. Moreover, following the implementation of the third national lockdown, these areas experienced a noticeable increase, while changes in other regions were not as pronounced. The spatial autocorrelation analysis further suggests that there are significant spatial heterogeneities among regions, with spatiotemporal hotspots centered around London and cold spots mainly concentrated in the northeast of England. Additionally, we found that the identified patterns of fraud and cyber-dependent crime are primarily associated with socioeconomic factors, followed by government containment measures and mobility factors. These findings can help law enforcement and regulatory agencies better understand the social-environmental factors contributing to the prevalence of cybercrime within those areas.

Abstract This study aims to investigate the influence of the school principal’s ethical leadership on teachers’ organizational behavior, attitudes, and perceptions and the moderating effect of some variables in this relationship. For this purpose, a meta-analysis of data collected from a total of 47 empirical studies involving 18,423 participants was performed. A random effects model was used to measure the overall effect sizes. The results showed that ethical leadership has a very strong positive effect on organizational trust and organizational justice, and a strong positive effect on job satisfaction, motivation, and organizational commitment. The analysis also revealed that ethical leadership has a strong negative relationship with organizational silence and a moderate negative relationship with mobbing and organizational cynicism. Among the tested moderators, only the level of education was found to moderate the effect of ethical leadership on organizational commitment. It was also concluded that ethical leadership has a greater effect on organizational commitment in primary schools. The current study evidenced that the ethical leadership of the school principal is an important variable in the organizational behavior, attitudes, and perceptions of teachers.

Abstract In national economic development, the unique geographical conditions of different regions lead to differences in the level of public services, with diverse impacts on attracting immigrant entrepreneurs with different educational backgrounds. This paper empirically analyses the impact of urban public services on attracting immigrant entrepreneurs with diverse educational backgrounds, using matching data from the 2017 China Migrants Dynamic Survey (CMDS) and the characteristics of 276 prefecture-level cities. We found that urban higher education has a significantly positive effect on attracting urban low-educated immigrant entrepreneurs. Higher education in urban areas, primary education in urban areas, and medical services have positive and significant effects on attracting immigrant entrepreneurs educated in urban areas. Higher education in urban areas, primary education in urban areas, and urban cultural services have positive and significant effects on attracting highly educated immigrant entrepreneurs from urban areas. Mechanism testing indicates that urban innovation capability and the intensity of government regulation plays a significantly moderating role in the impact of urban public services on the attractiveness of cities to urban immigrant entrepreneurs with different educational backgrounds. The research conclusions of this paper provide guidance for cities to manage the flow of immigrant entrepreneurial talent between regions through the provision of public services, optimized spatial allocation of human resources, balanced regional development, and higher levels of urbanization.

Abstract This study investigates the effects of teacher-led questioning within blended synchronous learning environments (BSLEs) on formative assessment practices in Teaching English as a Foreign Language (TEFL) classrooms. Integrating principles from formative assessment, sociocultural, and constructivist theories, a comprehensive framework has been developed to understand how strategic questioning enhances learning outcomes. Employing a mixed-method approach, including classroom observations, conversation analysis, and interviews with teachers and students, this study examines effective communication and assessment strategies in culturally diverse educational settings in China. Analysis tools such as the GFIP model (Gap, Feedback, Involvement, Progression) and the ESRU cycle (Elicit, Student response, Recognition of student response, Use of Information) reveal inconsistencies in leveraging student responses for pedagogical adjustments and emphasize the impact of cultural and linguistic factors on assessment efficacy. The proposed Culturally Responsive Formative Assessment through Engaged Dialog (CRFAED) framework advocates for customized questioning techniques that integrate culturally sensitive practices with technology to enhance learning outcomes. Results indicate that strategic teacher-led questioning in BSLE settings substantially improves student engagement and learning outcomes. The critical role of culturally responsive pedagogy in optimizing formative assessment practices is also highlighted. The CRFAED framework demonstrates effectiveness in bridging cultural gaps, facilitating better teacher–student interactions, and promoting an inclusive and responsive learning environment. This study offers insights for improving educational practices through culturally responsive pedagogy and technology integration in BSLE settings, contributing valuable knowledge to the global TEFL community.

Abstract While prior studies have emphasized that overqualified employees are considered valuable and scarce resources for organizational innovation, there has been insufficient exploration of the process through which these employees utilize their advantageous resources to gain additional new resources and ultimately foster innovative behaviors. This study draws on conservation of resources theory to build a theoretical model that outlines how overqualified employees affect their acquisition of competence-based resource (i.e., role breadth self-efficacy) and subsequent innovative work behavior. Results from a multiwave field study revealed that perceived overqualification is positively associated with employees’ role breadth self-efficacy, which in turn prompts them to engage in innovative work behavior. The positive indirect effect of overqualification on innovative work behavior via role breadth self-efficacy is stronger when overqualified employees perceive a higher (versus lower) level of job autonomy. Overall, this study extends theory by demonstrating how overqualified employees engage in resource acquisition and utilization processes to overcome potential resource depletions and foster innovative work behavior.

Abstract The label “Sentinelese” was etymologically derived from the island’s name by the researchers, administrators, and persons who had briefly contacted them, and not the tribes themselves. The conundrum is that their language, customary laws, traditional knowledge systems, and other social practices are still unknown. They are the most well-built and reclusive band of people with no affinity to neighboring tribes of the same archipelago. From prior contacts, it is evident that they still rely on Stone Age tools like bows, metal arrows, and adzes making them hunter-gatherers of modern times. The populace solely relies on nature for their mundane sustenance and survival. Such intimate relationships and interaction between ecology and social life have shaped a different cultural backdrop among the “Sentinelese” populace. Intriguingly, within such socio-cultural proximities, Jarawas, Onges, and Great Andamanese had developed dissimilar sub-cultures of their own. Time again, researchers and administrators tried to establish contact; herein, some individuals, including the second author, had made amicable contact in goodwill expeditions, but mostly, several other individuals who made contact were faced with unfriendly attitudes. In due course, in post-tsunami expeditions and later various other surveys, a ‘hands-off eyes on’ approach predominated the scene. Following such a suit, the present paper seeks to delve into the complex fabric of the tenable knowledge systems of the “Sentinelese” populace and revisit the various narratives of colonial and post-colonial visits, including that of the second author’s account of the North Sentinel Island.

Abstract In order to explore the application potential of artificial intelligence (AI) and text mining technology in educational policy analysis and evaluate their impact on the psychological perception of policy audiences, this study firstly introduces the application of AI and text mining technology in education. Secondly, it explores the application of psychological theories in educational policy analysis. Finally, this study constructs an educational policy text analysis model and verifies the feasibility of the optimized model through performance comparison experiments and case analysis. The experimental results show that the optimized model exhibits higher accuracy, recall rate, and F1 score compared to traditional models when handling educational policy text analysis tasks with different data volumes. This finding highlights the importance of optimizing models for specific tasks and the potential of improving the understanding and analysis capabilities of models for specific text types through careful adjustments. In addition, the application of psychological theories to the analysis of educational policy texts provides a new perspective and method for understanding the impact of policies on audience psychological states, which helps in formulating more effective and humanized policies. Therefore, the study has certain reference significance for the use of AI and text mining technology to support educational policy analysis and formulation, providing valuable insights and guidance for future related research and practice.

Abstract This mixed-methods study investigates the impact of digital game-based learning (DGBL) on enjoyment, ideal L2 self, and intrinsic motivation among Chinese English as a Foreign Language (EFL) learners. Seventy participants were divided into DGBL and control groups. The DGBL group engaged in Duolingo activities, while the control group received traditional EFL instruction. Data collection included pre-post self-determination theory (SDT) questionnaires, experience sampling method (ESM) to assess real-time enjoyment, and stimulated recall interviews. Quantitative analysis using paired-samples t-tests, one-way ANCOVAs, and multilevel modeling revealed that DGBL significantly enhanced enjoyment and ideal L2 self-perception, with pre-existing autonomy and ideal L2 self predicting greater enjoyment during gameplay. Qualitative findings highlighted increased engagement, perceived learning gains, and a sense of autonomy fostered by DGBL. Importantly, this study demonstrates that integrating DGBL into EFL classrooms can significantly boost enjoyment and cultivate a positive self-concept as language learners among Chinese students. These findings have practical implications for educators, suggesting that incorporating well-designed game-based activities can create a more motivating and effective learning environment, addressing the specific challenges faced by Chinese EFL learners.

Abstract Approximately, one-quarter of India’s land area comprises common-pool resources, e.g., pasture land, forests, and water bodies, upon which the livelihoods of over 300 million rural people depend. Despite their importance, these resources are subjected to encroachment and degradation, raising important questions about what can be done to promote their protection and restoration. Since 2001, the Foundation for Ecological Security (FES) has worked with over 7000 villages to secure their rights to the commons, while facilitating collective action and access to finance to promote their restoration. To evaluate the impact of FES’s intervention model, we compare prioritized common land areas in 24 intervention and 24 control villages located in two districts in the state of Rajasthan—Bhilwara and Pratapgarh. We employ Propensity Score Matching (PSM) to control for program placement bias while contrasting changes in key ecological indicators over time derived through remote sensing. Based on data collected through village surveys (n = 48), household surveys (n = 911), systematic biophysical data collection (n = 480), and remote sensing, we find evidence that the rollout of FES’s intervention model (a) was relatively greater in the intervention villages but below expectation; and (b) facilitated significant increases in tree cover and tree and shrub diversity, while significantly reducing encroachment, particularly in the intervention villages intervened before 2011. We further find that the institutional strengthening dimension of FES’s work is a plausible mechanism that gave rise to these effects.

Abstract This paper provides an in-depth analysis of how management efficiency affects sustainable development in China’s top 10 private energy companies from 2005 to 2021, using the CUP-FM technique. The study finds a notable correlation: a 1% improvement in management efficiency results in a 0.21% reduction in energy expenditure. This highlights the significance of efficient management practices, such as streamlined processes, better resource allocation, and advanced technology use, in optimizing energy consumption and promoting sustainability. Conversely, a 1% increase in the number of employees leads to a 0.49% increase in energy expenditure due to increased operational activities and resource needs. The research also explores the impact of other variables, including earnings per share (EPS), tax payments, and technology spending, on energy expenditure among listed energy companies in China. To foster innovation among employees through improved management efficiency, the paper suggests practical policies such as enhancing sustainable literacy, providing green loans, implementing standardized reporting, and encouraging collaboration and knowledge sharing among energy companies.

Abstract Based on the annual reports and input–output table data of Chinese listed companies from 2008 to 2020, this paper measures the level of digital transformation of enterprises by using the keyword word frequency index in the annual reports of listed companies and reveals the impact and mechanism of digital transformation of enterprises on industry chain elasticity by using a panel data model. Additionally, it provides a theoretical explanation of how the digital revolution of businesses affects industrial chain resilience. The outcome shows that improving industrial chain resilience can be facilitated by businesses undergoing a digital transition. Moreover, factor mismatch can be reduced by corporate digital transformation, which enhances industrial chain resilience. Furthermore, the beneficial effects of the digital revolution on industrial chain resilience will be enhanced by politically linked businesses. The main conclusions contribute to our understanding of the relationship between industrial chain resilience and enterprises’ digital transformation. It also offers crucial policy recommendations and guidance that the government can use to create sensible digital economy policies and successfully direct businesses’ digital transformations in order to strengthen the industrial chain resilience.

Abstract Internationalisation at home (IaH) has gained prominence in higher education, emphasising the cosmopolitan aspects of curricula, teaching, and learning. This case study, grounded in the concept of cosmopolitan learning as a sociological approach, focuses on three dimensions—cosmopolitan engagement, critical reflections on global and local issues, and ethical judgements—made by 23 Chinese university students participating in IaH at a prestigious Chinese university. It explores these students’ cosmopolitan learning experiences through IaH and their gains and learning challenges. The results show that the student participants exhibited more cosmopolitan engagement through the IaH curricula. Cosmopolitan engagement also enabled them to reflect critically on global and local issues, such as inequality in access to cosmopolitan learning resources, the impact of the global social imaginaries, and asymmetrical geo-power relations on the situatedness of knowledge, people, and learning. Accordingly, they made judgements to pursue ethical and meaningful changes. The challenges identified by students in cosmopolitan learning emphasise the need to further develop IaH cosmopolitan curricula to promote equity among diverse students in cosmopolitan learning, support multilingual learning, and empower students through a plural, egalitarian, and critical epistemology in addressing ethical change. Consequently, comprehensive proposals for the construction of cosmopolitan IaH curricula are presented.

Abstract Machine learning for financial risk prediction has garnered substantial interest in recent decades. However, the class imbalance problem and the dilemma of accuracy gain by loss interpretability have yet to be widely studied. Symbolic classifiers have emerged as a promising solution for forecasting banking failures and estimating creditworthiness as it addresses class imbalance while maintaining both accuracy and interpretability. This paper aims to evaluate the effectiveness of REMED, a symbolic classifier, in the context of financial risk management, and focuses on its ability to handle class imbalance and provide interpretable decision rules. Through empirical analysis of a real-world imbalanced financial dataset from the Federal Deposit Insurance Corporation, we demonstrate that REMED effectively handles class imbalance, improving performance accuracy metrics while ensuring interpretability through a concise and easily understandable rule system. A comparative analysis is conducted against two well-known rule-generating approaches, J48 and JRip. The findings suggest that, with further development and validation, REMED can be implemented as a competitive approach to improve predictive accuracy on imbalanced financial datasets without compromising model interpretability.

Abstract Fundamental principles of agency theory and incentive mechanisms suggest that executive compensation should align with a company’s developmental goals. This paper aims to explore whether the executive compensation of listed companies in the Chinese capital market aligns with their ESG (Environmental, Social, and Governance) practices, and the underlying mechanisms of this influence. For the first time, this study integrates ESG practices with executive compensation, creating a novel analytical framework and filling a gap in the existing literature. Employing empirical research methods such as the PSM-DID (Propensity Score Matching – Difference-in-differences) model, fixed effects model, heterogeneity analysis, and tests for mediating effects, the study concludes that ESG practices of Chinese listed companies significantly increase executive compensation, demonstrating consistency between the two. Additionally, the beneficial impact of ESG practices on executive compensation incentives is more pronounced in state-owned enterprises compared to non-state-owned ones. Financial performance, company reputation, and investor relations partially mediate the relationship between a company’s ESG practices and executive compensation. Specifically, financial performance acts as a negative mediator, while company reputation and investor relations serve as positive mediators. Initially, participation in ESG practices tends to exacerbate ‘income inequality’ between executives and other employees. However, as companies continue to enhance their ESG practice levels, this ‘income inequality’ gradually diminishes. Finally, the paper offers several suggestions: Firstly, Chinese listed companies can attract and retain top executive talents by strengthening ESG practices. Although initial ESG practices may lead to pay imbalances, long-term involvement will help reduce this disparity. Secondly, investors can conduct a more comprehensive assessment of a company’s future performance, governance structure, and corporate social responsibility by analyzing how ESG practices are reflected in executive compensation. Lastly, the paper provides valuable insights for policymakers, suggesting that regulators should develop more targeted policies and guidelines based on the relationship between a company’s ESG practices and executive compensation.

Abstract This exploratory research uses in-depth interviews with journalists and editors of print news media outlets to explore how new forms of journalism support and augment the news production process. The paper employs labor theory as a theoretical framework to examine how the use of technology and financial influence has transformed the role of reporters and the tasks that they perform. The study findings reveal that the print media industry has leveraged the digital media space and is trying to understand its intricacies and possibilities post-COVID-19 pandemic. Media professionals are acquiring digital skills beyond text in audio and video formats for financial viability. This shift to digital content has led to adopting diverse journalistic forms and given momentum to producing quality news.

Abstract This research examines the intricate connections among three key elements: an individual’s ability to tolerate sources of stress, their willingness to adapt to new situations, and various psychological factors that influence human behavior. To analyze these relationships, the study employs a sophisticated statistical technique known as partial least squares structural equation modeling (PLS-SEM). A total of 327 Kazakhstan residents voluntarily participated in the study, comprising 84.6% women and 15.4% men, with ages ranging from 14 to 67 years old. “Stress Source Tolerance Scale” examined stress tolerance, “Personality Readiness Scale” measured readiness to change, and “Fatigue, Monotony, Satiety and Stress Questionnaire” investigated psychological states. The results indicate significant direct and indirect effects of self-esteem, others’ perceptions, and world perceptions on stress tolerance, readiness for change, and psychological states. Moreover, systematic preference has a significant mediating effect on the relationship between openness to change and psychological states. Results suggest that understanding these complex relationships may have implications for health, organizational effectiveness, and psychological well-being.

Abstract Soundscape quality is important for fostering social interactions in urban public spaces. This study focuses on how and to what extent the compositions of the soundscape affect the sociability of urban public spaces where human sound is focused. Four 360° experimental soundscape samples were designed as foreground/background/no human sound type and signal sound type, based on the raw data collected in Peace Gardens, Sheffield, United Kingdom. Following Affordance Theory, sociability was analyzed by the experimental survey through two aspects—suitability and stimulation level—through a questionnaire consisting of Soundscape Quality evaluation (SQE) and Level of Willingness for social interactions (LoW), respectively. 120 participants were recruited in the same site representing the compositions of space users. Results show that only foreground human sound type significantly enhanced both suitability and stimulation levels, other samples were evaluated with either high suitability/low stimulation or low suitability/high stimulation. Results indicate people prefer a human sound dominated soundscape with high complexity and this preference was varied among different companion types and age groups. To achieve high sociability, it is suggested to create a complex and eventful soundscape within the range of pleasantness accompanied by a centripetal spatial form, and concerns users' diverse demographic backgrounds.

Abstract A data mining technique called Self-Organized Maps (SOM) was used to select the surnames with populational information (monophyletic) to be used in the reconstruction of past demographic processes, in order to show the historical population migrations that have generated the current structure of the Spanish population. The technique made possible to identify groups of surnames with the same origin. Once the origin of each surname has been established, we can assume that each surname found outside its origin would have moved, at some point in the past, out of that original area, which allows to study historical movements. The observed movements reveal the existence of two main migratory arcs. Both migrations have moved along the coast; the first following the Mediterranean and the second following the Cantabrian Sea. It appears that these two arcs are those that have provided the backbone of the Spanish population, dividing it into two halves that would reach the limits of areas of influence of these arcs. Several types of movement have taken place (Isolation due to distance, Short-distance movements, Medium-distance movements, Long-distance movements). Those of short-medium distance have been the most frequent and most determinant in the current structure.

Abstract Smart voice systems, such as voice assistants and smart speakers, are integral to domains such as smart homes, customer service, healthcare, and smart learning. The effectiveness of these systems relies on user comprehension performance, which is crucial for enhancing user experience. In this study, the primary factors influencing comprehension performance in multilanguage smart voice systems are examined, and the efficacy of various analytical methods, including LASSO regression, SEM, PLS-SEM, CNN, and BiLSTM, are assessed by identifying and improving these factors. Using a diverse dataset from human–computer interaction experiments made publicly available on GitHub, these five methods are applied to discern the impact of environmental and user-specific factors on comprehension. The key findings indicate the following: 1) Noise types and noise sound levels markedly affect comprehension. Noise sound level exhibited an inverted U-shape curve (parameter: 0.088) due to the low and high levels of noise. Certain rhythmic noises, such as those from clocks (parameter: 0.033), enhance comprehension by fostering a conducive auditory environment. 2) Analytical method comparisons reveal that while LASSO regression (MSE = 0.026), SEM, and PLS-SEM effectively map the linear relationships and pathways affecting comprehension, deep learning approaches such as CNN and BiLSTM (MSE = 0.019) excel at handling complex, multidimensional data, offering superior predictive performance.3) In a non-native language environment, the evaluation of user comprehension models is notably different from that in native language settings (native R 2: 0.545; non-native R 2: 0.347). Specifically, in non-native language environments, the variables and mechanisms influencing user comprehension models are clearer, more controllable, and more susceptible to proficiency levels (parameter: 0.164). This comprehensive study presents a novel comparison of traditional statistical and machine learning methods in analyzing smart voice system interaction across languages. These findings emphasize the significance of tailoring smart voice systems to user diversity in language proficiency, age, and educational background and suggest optimizing these systems under varied environmental conditions to improve comprehension and overall effectiveness. The insights from this study are critical for policymakers and designers aiming to refine the adaptability and user-centric nature of smart voice systems.

Abstract Taxes are undeniably the lifeblood of a country’s financing. However, tax evasion is becoming increasingly rampant in Indonesia, resulting in substantial state losses. Enhanced tax enforcement policies are necessary to combat this crime. The Organization for Economic Cooperation and Development (OECD) has established principles for fighting tax crimes; however, the Indonesian government has been unable to integrate these principles into its tax enforcement policies, leading to gaps related to strategy, investigative powers, organizational structure, resources, and cooperation, which prevent the current measures from being fully effective. This article conducts a descriptive, evaluative, and comparative study of the Directorate General of Taxes’ (DGT) current tax enforcement policy and proposed practices based on the OECD’s principles to identify and elaborate on these gaps and analyse internal and external obstacles hindering effective implementation. This study’s findings reveal a fundamental difference between tax and legal interests that must be appropriately managed within their boundaries; therefore, the key to improving tax enforcement policy in Indonesia lies in combining Primum Remedium (criminal sanctions as the initial response) and Ultimum Remedium (criminal sanctions as the last resort) strategies. Additionally, the provision of adequate investigative powers, sufficient resources, gradual policy implementation, and necessary law amendments are also crucial factors. This study aims to provide the Indonesian government with insights and recommendations to enhance the tax enforcement policy, to combat tax crimes more comprehensively.

Abstract Drawing on diachronic and synchronic collexeme analyses, this paper investigated preferences of interpersonal metaphor of modality, which is realized by explicit subjective orientation, explicit objective orientation and implicit objective orientation, in academic disciplines of Corpus of Contemporary American English or COCA. The findings demonstrate that explicit subjective orientation is generally avoided by academic writers in later phases of COCA and more rarely used in natural sciences than in social and human sciences. Explicit objective orientation that denotes low modal value of probability, i.e., possible, and median value of obligation, i.e., important and necessary, is insensitive to both three phases and academic disciplines in COCA. Implicit objective orientation, inclusive of significantly attracted possibility and importance, employs probability and obligation that denote median value of probability and high value of obligation respectively to mask the subjective judgments of scholars regarding the proposition under scrutiny. This research is significant in shedding light on the use of interpersonal metaphor of modality in academic writings across disciplines.

Abstract This research focuses on the recent efforts to improve STEM skills among future science educators in Oman. It details the development and application of a questionnaire aimed at evaluating self-efficacy in teaching science through engineering design. A survey was given to 326 aspiring science teachers to gauge their views on incorporating engineering design in science education. A quantitative methodology was used, with Rasch analysis used in the analysis of the survey instrument. The survey revealed two distinct dimensions: Personal Self-efficacy (SE) and Outcome Expectancy (OE). The reliability of person and item measures fell within acceptable limits. The analysis of the category probability curves showed effective rating scale measurements. The Wright map corresponded well with theoretical predictions, offering insightful implications for training science teachers in Oman. This research adds to the existing body of knowledge, particularly in Arab regions, by providing data on science education from Omani preservice science teachers. It further explores how these findings can enhance the quality of science teaching and learning.

Abstract Mobile phishing has emerged as one of the most severe cybercrime threats; thus, research must examine the factors affecting people’s likelihood of becoming instant messaging phishing targets. In this study, we draw on the cyber-routine activity theory (Cyber-RAT) and heuristic-systematic model (HSM) to predict Gen-Zers’ phishing susceptibility. Based on online survey data (n = 361), the proposed research model was validated via structural equation modeling conducted with SmartPLS 4. Findings indicate that engaging in online risky behavior (social media: instant messaging, vocational, and leisure activities) increases Gen-Zers’ exposure to phishers, increasing their likelihood of becoming instant messaging phishing targets. Phishing messages with a desirable or relevant topic (high message involvement) significantly impact Gen-Zers’ phishing susceptibility. Gen-Zers’ phishing susceptibility is also influenced by phishing messages with persuasive cues. While knowledge of the phishing domain does not directly influence Gen-Zers’ susceptibility to phishing attacks, it significantly motivated them to adopt effective online security management practices on social instant messaging platforms. This paper discusses how these findings implicate online users and inform agencies to promote knowledge for understanding and detecting phishing attacks to avoid victimization.

Abstract The ‘decade of action’ intended to accomplish the ambitious 17 Sustainable Development Goals (SDGs) faces notable challenges. Our investigation into the impact of the COVID-19 crisis on SDG progress reveals important lessons for shaping effective policy interventions to ensure resilient societies and overall well-being. Through systematic mapping and a rapid review approach, our analysis reveals that nearly 90% of the SDGs, specifically 144 targets, were adversely affected by the COVID-19 pandemic. Yet, there is a glimmer of opportunity: 66 targets stand to gain from the crisis-induced transformations, provided that the right choices are made. Achieving this goal demands a comprehensive approach and decisive leadership to steer an inclusive economic recovery that also safeguards the environment while safeguarding the environment. The intricate interplay between the ongoing planetary and post-COVID-19 crises, environmental challenges, and conflicts underscores the need for a proactive, deliberate and well-informed approach, marked by collaborative decision-making, which is imperative for effectively steering the ‘decade of action’ toward achieving the SDGs. These complex challenges demand collective, decisive action, all with the overarching aim of securing a just and sustainable future for all.

Abstract Despite the growing consumer interest in local and artisanal foods over the past decades, there have still been few empirical studies on consumer behavior toward crafted food. This study aims to be the first to investigate consumer behavior towards craft bakery products by using the Theory of Planned Behavior model. Data were collected in Hungary, the sample of 418 respondents was weighted by gender and age group to ensure representativeness. Covariance-based structural equation modeling was used as the data analyzing method. The results showed that positive consumer attitudes and the effects of perceived behavioral control explained consumer intention and behavior towards craft bakery products well, but the influence of the consumer’s environment was not confirmed. Based on the results, the main activities proposed to the stakeholders of craft bakery products are those that highlight the availability and affordability of craft bakery products, while raising awareness of sustainability and health aspects. It is worth organizing festivals and events where the consumption of artisan baked goods is combined with pleasant stimuli and aromas. The results of the study provide a good starting point for further research, in which adding more factors to the model would increase its explanatory power.

Abstract Early Islam, spanning its nascent centuries from the early 7th century, encompasses a pivotal epoch covering the life and teachings of the Prophet Muhammad, the establishment of Islamic principles, the codification of the Qur’ān, and the evolution of Islamic law and theological thought. This article outlines the findings of a pioneering bibliometric analysis of 764 high-value articles on early Islam from the Web of Science (WoS) database and unveils critical trends. This study, which notably highlights increased academic activities, particularly interdisciplinary expansion into archaeology and related fields, demonstrates a contemporary upsurge in scholarly engagement within humanities and social sciences. Global contributions from 60 countries, led by the USA, showcase an international landscape, and English emerges as the predominant language. (Der) Islam-Zeitschrift für Geschichte und Kultur des Islamischen Orients and Journal of Archaeological Science Reports stand out as the most prolific journals across all fields, followed by Journal of Archaeological Science. This highlights the growing significance of archaeology in the research on early Islam. The top authors with the most publications N. Schibille, I. Taxel, and G. Bar-oz and most cited authors I. C. Freestone, J. Henderson, and Y. Avni shape the field. Financial support from organizations like the European Research Council (ERC), the Spanish Government and the Israel Science Foundation signals strategic investments in Islamic studies. Lastly, a keyword analysis emphasizes prevalent themes, such as Islam, early Islam, early Islamic period, and Qur’ān, providing a concise snapshot of the field’s contemporary focus. These insights underscore the rising international importance of Islamic research. Recognizing the limitations of the present study, this bibliometric analysis offers a foundational framework for future research by inspiring further scholarly exploration of emerging trends and thematic gaps in the field.

Abstract The rapid adoption of artificial intelligence (AI) in organizations has transformed the nature of work, presenting both opportunities and challenges for employees. This study utilizes several theories to investigate the relationships between AI adoption, job stress, burnout, and self-efficacy in AI learning. A three-wave time-lagged research design was used to collect data from 416 professionals in South Korea. Structural equation modeling was used to test the proposed mediation and moderation hypotheses. The results reveal that AI adoption does not directly influence employee burnout but exerts its impact through the mediating role of job stress. The results also show that AI adoption significantly increases job stress, thus increasing burnout. Furthermore, self-efficacy in AI learning was found to moderate the relationship between AI adoption and job stress, with higher self-efficacy weakening the positive relationship. These findings highlight the importance of considering the mediating and moderating mechanisms that shape employee experiences in the context of AI adoption. The results also suggest that organizations should proactively address the potential negative impact of AI adoption on employee well-being by implementing strategies to manage job stress and foster self-efficacy in AI learning. This study underscores the need for a human-centric approach to AI adoption that prioritizes employee well-being alongside technological advancement. Future research should explore additional factors that may influence the relationships between AI adoption, job stress, burnout, and self-efficacy across diverse contexts to inform the development of evidence-based strategies for supporting employees in AI-driven workplaces.

Abstract The study empirically examines the impact of firm digital transformation (DT) on the performance of Chinese-listed enterprises in the areas of environmental, social, and governance (ESG) from 2013 to 2022. We utilized OLS, IV 2SLS causal mediating effect, and moderating effect models to analyze the linkages and deep mechanisms between corporate DT and ESG performance. The empirical findings demonstrate that (i) DT has an effectively positive effect on the performance of firms’ ESG; (ii) DT enhances firms’ ESG performance by enhancing information transparency (TRANS), fostering green innovation (Green), and strengthening internal control (Inter) mechanisms; moreover, (iii) According to the study, common institutional ownership (CIO) effectively facilitates the positive effects of the DT impact on the ESG performance of listed enterprises, and firms’ subjective perception of economic policy uncertainty (SEPU) negatively influences the effect of digital change on firms’ ESG performance; (iv) the impact of DT on ESG performance is more significant in the listed companies of western region and state-owned enterprises. Our findings provide valuable insights into whether and how DT affects the firms’ ESG performance, providing practical recommendations for corporate managers and government decision-making agencies.

Abstract Economic growth in leading tourist destinations faces challenges requiring investment, technological advancement, and resource management. This study examines the impact of tourism, Fintech, FDI, and digitalization on economic growth in Austria, France, Germany, Greece, Italy, Mexico, Spain, Turkey, the UK, and the USA. These countries, identified by UNWTO for 2022, represent 46% of the global tourism market. Utilizing yearly data from 2010 to 2022 from sources like the World Bank, Crunchbase, and UNWTO, we apply Pooled OLS, PCSEs, FGLS, and Two-Step GMM models using Stata v17.0. Additionally, Necessary Condition Analysis (NCA) was conducted using SmartPLS v.4.3 software. Our findings reveal that Fintech, tourism, FDI, and digitalization significantly contribute to economic growth, with varying degrees of impact across different models. Specifically, digitalization and tourism demonstrate the most substantial positive effects, while FDI and Fintech also play crucial roles. The study highlights the necessity of integrating these factors to foster sustainable economic growth in top tourist destinations. These results provide actionable insights for policymakers, stakeholders, and government officials, emphasizing the importance of strategic investments in Fintech, tourism, FDI, and digital infrastructure to enhance economic performance. The implications of this research extend to informing policy formulation and strategic decision-making aimed at leveraging technological advancements and investments for sustained economic development in major tourist economies.

Abstract Well-being has been touted for many years as a critical factor in achieving positive outcomes for students in schools across Australia, Aotearoa New Zealand, and globally. Despite extensive reporting of student well-being concerns, further research is needed to fully understand this complex construct. This paper presents a scoping review aimed at developing a comprehensive understanding of student well-being by examining key factors highlighted in the literature. Using the PRISMA-ScR approach, a search was conducted using Google Scholar to identify studies published between 2010 and 2023 that focus on student well-being in Australian and Aotearoa New Zealand school contexts. Additional relevant grey literature, including policy documents, contributed to this review. A total of 46 studies met the eligibility criteria for more detailed analysis. The review identified three primary themes influencing student well-being: the role of student voice, the impact of the physical environment (which we call perivallon), and the nature of student relationships with teachers, peers, and themselves. These factors were found to be interrelated, with relationships serving as both an independent influence and a mediating factor affecting the other dimensions. The literature review leads to a multi-dimensional complexity model of well-being. This model suggests potential mechanisms by which a small change to an external factor can have far reaching, and potentially unexpected, impacts on student well-being. The implications and limitations of such a model are discussed, and avenues for future research are suggested.

Abstract The utilization of accolade awards to motivate reviewers is widespread, but their effectiveness remains uncertain. We aim to explore how receiving an accolade award affects reviewers’ subsequent number of reviews. In contrast to small-scale, unrepresentative experiments, we perform a large-scale, global, and all-disciplinary analysis based on quasi-natural experiments. By integrating the Publons, ORCID, MAG, SciSciNet, and OpenAlex databases, a large dataset that tracks the reviewers’ annual number of reviews and their bibliometric indicators is compiled, encompassing 179,794 individuals. Among them, 6605 individuals who receive the “Publons Global Peer Review Award” in 2018 are constituted as the experimental group. Those non-winners are then matched to form a control group. Using propensity score matching (PSM), 711 and 762 reviewers are matched as the experimental and control groups respectively. An analysis employing the difference-in-differences (DiD) method is conducted to examine the impact of an accolade award on reviewers’ subsequent number of reviews. It is found that, following the receipt of an accolade award, reviewers, on average, reviews about four fewer manuscripts, with the reduction exhibiting a V-shaped pattern. Additional analyses are conducted to examine how individual differences and socio-economic factors influence the awarding effects. Besides, we analyze the mechanisms underlying the awarding effect and propose strategies to motivate reviewers. In brief, the sharp decrease in marginal utility of accolades, the voluntary nature of peer review, and the unexpected properties of accolade awards are the potential mechanisms that generate the negative effect. The academic community should reassess the existing incentive strategies for reviewers.

Abstract Despite extensive research on leadership’s role in influencing employee outcomes, there is limited understanding of the specific impact of servant leadership on employee task performance. Little is known about how servant leadership enhances employee promotive voice behavior, which in turn influences task performance. Additionally, the potential moderating role of leader-leader exchange in this relationship has been underexplored, leaving a gap in understanding how interactions between leaders may further shape these outcomes. Based on social exchange theory, this study examined how servant leadership affects employee task performance through the mediating role of employee promotive voice and the moderating role of leader-leader exchange. Using a time-lagged data collection approach, data for this study were gathered from 392 employees working in project-based organizations in the information technology sector in Pakistan. The study’s hypotheses were tested using structural equation modeling and the Process Hayes Model. The findings reveal that servant leadership significantly influences employee task performance by mediating the role of employee promotive voice. Furthermore, it was confirmed that leader-leader exchange positively moderates the relationship between employee promotive voice and task performance. This research, further adds to the existing pool of knowledge that holds implications for organizations, top management, academia, researchers, and government concerning leadership behaviors, promotive voice, employee task performance, leader-leader exchange, and preparation for challenges in the future.

Abstract Knowledge hoarding has gained significant attention as a counterproductive behavior within organizations. This study explores the impact mechanism and boundary condition of organizational inclusion on employee knowledge hoarding through a survey of 366 knowledge employees in China. The findings indicate that psychological security and perceived cohesion mediate the relationship between organizational inclusion and employee knowledge hoarding, and organizational inclusion can inhibit employee knowledge hoarding by increasing their psychological security and perceived cohesion. Learning goal orientation negatively moderates the indirect influence of organizational inclusion on employee knowledge hoarding through psychological security and perceived cohesion. Organizational inclusion practices should be strongly supported and implemented. Especially for individuals with low learning goal orientation, they are more likely to benefit from organizational inclusion and reduce their knowledge hoarding.

Abstract As the aging population creates mounting pressures on society, the economy, and public health systems, the rational and equitable distribution of elderly care resources becomes increasingly essential. This study applies various methods, such as kernel density estimation, spatial autocorrelation analysis, and Gini coefficient decomposition, to examine provincial panel data on elderly care institutions in both urban and rural regions in China covering the period from 2008 to 2021. This research seeks to assess and improve the accessibility and equity of elderly care resources. The results indicate that the degree of population aging in China has significantly intensified, with urban elderly care institutions’ resource allocation increasing annually and surpassing that of rural institutions. However, inequalities in the allocation of elderly care resources between urban and rural areas, as well as among different regions, still exist. The uneven distribution of resources in rural elderly care institutions, the overall enhancement of resource allocation in urban areas, and the clustering of elderly care resources are the key features observed. Drawing on these insights, the study offers a set of policy recommendations to address the disparities and inconsistencies in the allocation of elderly care resources between urban and rural regions.

Abstract In the context of digital transformation, financial centralization has emerged as a crucial strategy for enhancing the efficiency and effectiveness of corporate financial management. This paper explores the role of Artificial Intelligence (AI) in financial centralization within Chinese enterprises, particularly under the framework of digital corporate financial management. By analyzing multiple case studies, the research demonstrates how AI applications streamline financial processes, mitigate risks, and improve decision-making accuracy. The study focuses on three key AI-driven applications: automated reconciliation, intelligent report generation, and big data-based risk management. Additionally, the research examines the unique challenges and opportunities that private and state-owned enterprises face during AI-driven financial transformation. Through in-depth analysis, the paper offers valuable insights into how AI is reshaping the financial landscape, providing both practical and theoretical contributions. These findings offer valuable implications for financial managers, policymakers, and researchers seeking to leverage AI in the evolving field of intelligent financial management.

The rapid convergence of urbanization and digital technologies is fundamentally reshaping city governance through data-driven systems. This transformation, however, is largely controlled by surveillance capitalist entities, raising profound concerns for democratic values and citizen rights. As private interests extract behavioral data from public spaces without adequate oversight, the principles of transparency and civic participation are increasingly threatened. This erosion of data sovereignty represents a critical juncture in urban development, demanding urgent interdisciplinary attention. This comment proposes a paradigm shift in urban data governance, advocating for the reclamation of data sovereignty to prioritize community interests over corporate profit motives. The paper explores socio-technical pathways to achieve this goal, focusing on grassroots approaches that assert ‘data dignity’ through privacy-enhancing technologies and digital anonymity tools. It argues for the creation of distributed digital commons as viable alternatives to proprietary data silos, thereby democratizing access to and control over urban data. The discussion extends to long-term strategies, examining the potential of blockchain technologies and decentralized autonomous organizations in enabling self-sovereign data economies. These emerging models offer a vision of ‘crypto-cities’ liberated from extractive data practices, fostering environments where residents retain autonomy over their digital footprints. By critically evaluating these approaches, the paper aims to catalyze a reimagining of smart city technologies aligned with principles of equity, shared prosperity, and citizen empowerment. This realignment is essential for preserving democratic values in an increasingly digitized urban landscape.

Abstract This research explores the driving pathways for building a high-level rural e-commerce entrepreneurial ecosystem, providing valuable insights for responding to global policies promoting rural entrepreneurship and innovation and accelerating rural industrial development. However, existing studies on the “rural e-commerce entrepreneurial ecosystem” lack in-depth exploration. Based on the CAS (Complex Adaptive System) theory and TOE (Technological, Organizational, and Environmental) framework, we conducted a comprehensive case study across 31 Chinese provinces, focusing on seven key indicators within three dimensions: technology, organization, and environment. Employing the Fuzzy Set Qualitative Comparative Analysis (fsQCA) method, we examined key factors and driving pathways influencing the establishment of successful rural e-commerce entrepreneurial ecosystems in China. The main findings of this study are as follows: (1) The construction of a rural e-commerce entrepreneurial ecosystem is not driven by a single element but is the result of the combined effects of multiple facets and factors. (2) The number of leading agricultural enterprises and the establishment of e-commerce cooperatives are critical factors promoting the high-level construction of rural e-commerce entrepreneurial ecosystems. (3) Typical driving pathways for advancing the construction of rural e-commerce entrepreneurial ecosystems can be categorized into three types: technology-organization-government-driven, organization-environment-driven, and holistic synergy-driven. The research findings are instrumental in guiding the government to formulate systematic policies that support the development of leading agricultural enterprises and e-commerce cooperatives. Additionally, these policies should be tailored to the specific characteristics of different regions to create differentiated driving paths. Implementing these measures can effectively promote rural e-commerce entrepreneurship.

Abstract In the global digital economy, the use of digital platforms in supporting innovation across organizational boundaries has attracted more concentration. By using the fuzzy set qualitative comparative analysis method, this paper examines survey data from 319 firms located in the Yangtze River Delta region in China. This paper investigates how digital collaboration capability, absorptive capability, digital platform, stakeholder pressure, and external support enable firms’ open innovation through a collaborative symbiosis. Findings reveal that although the above factors are not strictly necessary for firms to achieve high-level open innovation, they contribute to some degree. This paper identifies two comparable paths that facilitate inbound open innovation for firms: the “platform-enabling subject collaborative type,” which focuses on engaging relevant entities, and the “platform-enabling internal and external linkage-type,” which emphasizes integrating firms’ internal and external resources. In addition, a single path supports firms in achieving outbound open innovation, i.e., the “platform–external support collaborative type,” which relies on constructing digital platforms and obtaining external support. This paper offers some significant theoretical and managerial implications for firms, especially those in emerging markets, seeking to integrate into more innovation ecosystems and engage in open innovation through the use of digital platforms.

Abstract The increasingly serious problem of food waste in China has become an important bottleneck constraining sustainable development, posing a great challenge to food security, resource and the environment. Therefore, it is urgent to reduce food waste. However, the inconsistency between consumers’ intention to reduce food waste and their behavior weakens the effectiveness of anti-food waste efforts to some extent. Based on the extended MOA model, this study examines consumers’ intention-behavior gap in reducing food waste and explores the moderating effects of opportunity, ability and face consciousness on the conversion of food waste reduction intention into actual behavior in the context of China. In addition, we further categorize consumers into high and low face consciousness groups to explore the differences in the moderating effects of opportunity and ability. The results show that there is indeed a gap between consumers’ food waste reduction intention and behavior. In terms of the moderating effects, the factors of external environment, emotional information, and ability have a significant positive moderating effect on the conversion of food waste reduction intention into actual behavior, while rational information has no significant moderating effect. Notably, face consciousness plays a significant negative moderating effect. For the high face consciousness group, only emotional information has a significant positive moderating effect; while for the low face consciousness group, external environment, emotional information, and ability have a significant positive moderating effect. What’s more, rational information has a non-significant moderating effect on both the high and low face consciousness groups.

Abstract This paper introduces a contingent claim analysis to examine sustainable insurance practices. It investigates how life insurers participate in sustainable lending by financing borrowing firms committed to environmentally friendly practices for cleaner production. We establish a capped call option model, where the capped function explicitly considers credit risks associated with borrowing firms in a supply chain engaged in the cap-and-trade mechanism regulated by environmental policies. Our findings reveal that tightening the cap within the cap-and-trade system and reducing green loans can enhance insurer’s interest margins. Conversely, an escalation in the green input ratio across the supply chain may reduce these margins for the insurer. However, reducing low-margin insurance offerings could jeopardize the stability of insurance. The insurer faces financial challenges while supporting borrowing firms in their efforts toward carbon reduction and sustainable production. Notably, the substantial impact of climate change fueled by carbon emissions significantly influences the underwriting of life insurance policies related to human health. Policymakers need to navigate these intricacies to establish a careful balance between environmental objectives and the financial stability of sustainable insurance.

Abstract The COVID-19 pandemic led to a global crisis that forced governments to implement restrictive measures to control the spread of the disease. Although these restrictions, such as community quarantines, played a pivotal role in stabilizing healthcare systems, they also caused forced closures of various economic sectors that resulted in huge societal costs and severely impacted the marginalized. In order to understand and quantify the economic impact of the COVID-19 pandemic in the Philippines, an integrated modeling approach, which combined an epidemiological compartmental model and an economic model, was utilized. The evolving nature of COVID-19 required continuous updating of the integrated model which this paper illustrates by applying three versions of the model in three different phases of the pandemic. Scenario-based estimates of active COVID-19 cases and economic losses, expressed in terms of foregone income, are produced for each of the model versions. Analysis of the results provided a retrospective view of the losses the economy had incurred during the pandemic, along with implications for public policy. The insights presented in this paper emphasize the importance of using an integrated modeling approach to guide pandemic response.

Abstract The ownership of trust property is a debatable issue in China due to the ambiguity of the Chinese Trust Law, and there are several relevant theories. In 2019, the Supreme People’s Court of China issued the Minutes of the National Conference on Civil and Commercial Trials which emphasized the absolute independence of trust property in China, that is different from traditional trust property theories. This could be summarized as a new theory of “Absolutely Independent Trust Property” which is, in the duration of trust, trust property is absolutely separated from the inherent property of settlors, trustees and beneficiaries. In China, court judgments play a significant social governance role in making policies and clarifying ambiguous legal rules. Therefore, it is necessary to test the new theory through empirical research of court judgments for advancing trust legal theories and improving relevant rules. Based on the approach of “practical reasoning”, it is assumed that, in China, the theory of “Absolutely Independent Trust Property” is applied in judicial practice. Based on the research of 252 Chinese court judgments related to trust property ownership from 2001 to 2023, the “Absolutely Independent Trust Property” theory is verified to some extent, especially after 2019, and some consensus on the nature of trust property has been formed in judicial practice. However, there still exists confusion and contradiction regarding trust property ownership in China, causing practical challenges to citizens’ constitutional property rights and violating the “Morality of Law” theory. In practice, to solve the problems caused by the unclear ownership of trust property, the Chinese government has adopted several systems regarding trust property, however, there still exits some problems. Chinese Trust Law will be revised soon, it is supposed to clarify the ownership of trust property. At the same time, more supportive and applicable laws and regulations should be issued to improve the trust registration system and trust property registration system. Moreover, the rule of trust taxation and a complete trust taxation system should be established in China.

Abstract The central aim of this research is to investigate the underlying mechanism between parental involvement and externalizing problem behaviors in Chinese rural adolescents. While earlier studies have investigated this link, the pivotal influences of peer relationships, mental health, and problematic social media use have not been thoroughly addressed. In this analysis, 3157 rural Chinese adolescents aged 13–19 years participated by filling out an anonymous self-report questionnaire. Our findings revealed that: (1) parental involvement acted as a protective factor against the emergence of externalizing problem behaviors; (2) both peer relationships and mental health served as mediators in the connection between parental involvement and externalizing problem behaviors; (3) parental involvement indirectly influenced externalizing problem behaviors through the sequential mediation of peer relationships and mental health; and (4) as problematic social media use escalated among rural adolescents, the protective impact of parental involvement on externalizing problem behaviors weakened. Building on these findings, the study has identified possible causes and suggested practical interventions to mitigate externalizing problem behaviors among rural adolescents.

Abstract This study adopted a content-analysis method to examine the differences in how the topic of functions was handled by Finnish, Singaporean, and Taiwanese middle-grade mathematics textbooks for children aged 13–15 (seventh-ninth grade). The results showed that the three countries’ textbooks used different methods to introduce the concept of functions, with the Finnish ones using function machines with input and output tables; the Taiwanese ones, verbal and visual representations; and the Singaporean ones, verbal representations only. In all three countries, most function-related mathematics problems were provided in a purely mathematical form. However, the Finnish textbooks were more balanced in this regard, including some problems presented visually or verbally, whereas the Taiwanese and Singaporean textbooks were inclined to use purely mathematical presentations. The Singaporean textbooks featured more open-ended problems than the Finnish or Taiwanese textbooks did. And, as compared with the textbooks from the two Asian countries, the Finnish ones included both a greater overall number of problems and less difficult problems.

Abstract This study explores the effectiveness of Data-Driven Learning (DDL) in teaching noun collocations to pre-tertiary learners in Hubei Province, China, using the online corpus tool ‘Corpusmate’. Acknowledging the importance and challenge of mastering collocations in learning a foreign language, this study focuses on the effects of DDL on pre-tertiary learners, an area less examined previously due to the complexities associated with using corpus tools. Conducted over two months, the research employed pre-tests, post-tests, and delayed post-tests to measure learners’ comprehension and retention of noun collocations. Additionally, a questionnaire was distributed to gather feedback on learners’ experiences with the DDL approach and ‘Corpusmate’. Results indicated that the experimental group, which received DDL training, showed significant improvements in test scores compared to the control group, which used traditional resources. The experimental group’s scores remained high in the delayed post-test, suggesting that the DDL approach facilitated long-term retention of collocational knowledge, although a notable proportion of learners expressed neutral or negative perceptions of the DDL activities. These results highlight the need for further investigation into the attitudes of the participants. Overall, most participants provided positive feedback on the use of ‘Corpusmate’ in learning noun collocations. These results advocate for the incorporation of corpus consultation into language teaching practices. The study underscores that with appropriate training and tools like ‘Corpusmate’, the DDL approach can potently aid in the sustained learning of complex language elements, such as collocations, even for younger learners.

Abstract Core occupational adaptability (COA) is a crucial occupational competency and workplace competitiveness for employees. This study identified significant antecedent variables that impact COA and constructed a structural equation model to test the relationships among these variables. A questionnaire survey was administered to 519 employees from Chinese manufacturing enterprises to validate the model. The results revealed that perceived organizational support (POS), proactive personality (PP), and career-related continuous learning (CCL) positively predicted an employee’s COA. PP and POS indirectly predicted COA through the mediating role of CCL, respectively. Moreover, employees’ age moderated the direct effect between PP and COA positively, while employees’ positions positively moderated the direct effect between POS and COA. This study demonstrated that CCL is critical in enhancing employee initiative, providing organizational support, promoting vocational learning, and improving overall COA levels among employees.

Abstract In an age of advancing information technology, widespread internet access has facilitated a rise in profit-driven cybercrime. Empirical research has found that cybercrime is now highly industrialised. Cybercrime operations have evolved into an assembly of various malicious acts, some of which do not require advanced technical abilities. While extensive research on cybercrime has been conducted globally, there is a lack of detailed investigation into the cybercrime landscape in China, despite it being a vast economic entity with a significant number of cybercrime incidents. Drawing on interviews and secondary data from China collected between 2020 and 2022, this paper seeks to address this gap by offering a comprehensive examination of Chinese cybercrime. It explores the degree of industrialisation within Chinese cybercrime and discusses its impact on the work performed by Chinese cybercriminals. Echoing findings from previous studies on the industrialisation of cybercrime, the current study reveals an elaborate industry built around cyber fraud, populated by various market players working on diverse tasks to support the successful operation of cyber fraud. The research also uncovers the existence of cybercriminal firms that closely mimic the structural and operational approaches of legitimate companies. Similar to how the Industrial Revolution reshaped traditional manufacturing, the industrialisation of cybercrime has transformed it into an assembly line operation, where each cybercriminal carries out basic, tedious, and repetitive tasks on a daily basis.

Abstract Despite extensive research on the relationship between social exchange and employee innovation in teams, a comprehensive and quantitative synthesis of research findings is necessary to enhance and expand our understanding. A meta-analysis allows for the comparison of different social exchange relationships and their effects on employee innovation, as well as an investigation into the underlying mechanisms of innovation realization. The results showed that compared to Leader-Member Exchange (LMX), Team-Member Exchange (TMX) demonstrated the stronger relationship with employee innovation. Moreover, cognition and motivation mediated the relationship between TMX and innovation, while affect, cognition and motivation mediated the relationship between LMX and innovation. This paper synthesized a body of critical and thriving literature, thereby endeavoring to furnish evidence that can provide information for theoretical advancements, research methodologies, and updated policy recommendations concerning social exchange relationships for individual innovation.

Abstract The present article examines and compares the diverse online electoral advertising strategies employed by the Socialist Party (PS) and the Democratic Party (PD) in Albania’s national and municipal elections. The purpose of this study is to analyze the themes, communication techniques, and tones used in campaign advertising and to evaluate how these components vary depending on the type of election and the political party participating. It focuses on discrepancies in tone, themes, and the priority placed on candidate image versus policy issues. This research uses content analysis methods to reveal significant differences in the content and strategies of electoral advertisements across various election types and political parties. The study highlights clear disparities in the political communication tactics used in national and municipal elections, as well as between the Socialist and Democratic Parties. This study’s findings reveal differences in advertising content and strategies across national and municipal elections for Democratic and Socialist parties. This has significant implications for political groups, advertising, and lawmakers, particularly given the increasing impact of social media on citizen participation in the democratization process.

Abstract The aim of this paper is to assess the extent of educational disparities among Ecuadorians attributed to their geographical location. For this purpose, a novel two-stage hierarchical decomposition of inequality for the half of the square of the coefficient of variation is introduced. This method, an extension of the one-stage (within/between) decomposition, is applicable to variables that can take the value zero, such as the ‘years of schooling’ variable. Using microdata bases from Ecuador’s National Survey of Employment, Unemployment and Underemployment (encompassing all twenty-four provinces and four regions in 2014 and 2021), we estimated the ‘years of schooling’ for individuals aged 24 and over, determining provincial, regional and national mean values. The proposed method allows the identification of the extent to which educational disparities among Ecuadorians (total inequality) can be attributed to differences between provinces and regions (spatial inequality), and the extent to which such educational inequality is due to variations among individuals within provinces. Moreover, it measures the educational inequality within each province and evaluates the contribution of each province to intra-provincial inequality. The results indicate that, although spatial inequality increased between the study years, total educational inequality decreased. This is because the contribution of spatial inequality to total inequality was practically negligible compared to the influence of disparities among individuals within provinces. Consequently, the reduction in the intra-provincial inequality is the reason for the decrease in educational differences among Ecuadorians. The findings potentially reflect individual-focused policies, socioeconomic features of Ecuador’s provinces and align with the official educational statistics.