Linear Structural Equation Models Research Articles

The cooperative interaction of AOB and comammox clade A drives nitrification and N2O emissions in a long-term organic fertilized paddy soil

The newly discovered complete ammonia oxidizer (comammox Nitrospira) is able to single-step nitrification capability, and increased our understanding of soil nitrogen cycling. However, the response of comammox and ammonia-oxidizing bacteria (AOB) and archaea (AOA) to long-term fertilization and rhizosphere effects in paddy soils and their relative contribution to the nitrification-derived N2O emissions is still unclear. Here, we collected rhizosphere and bulk soils with thirty years of different fertilization strategies, i.e., non-fertilization (CK), chemical N, P, and K application (NPK), and NPK plus pig manure application (NPKM), respectively, to test changes in nitrification potential rate (PNR), N2O emission fluxes, abundance of ammonia oxidizers and their significant drivers. The result showed that NPKM significantly increased soil C and N levels, the proportion of soil middle-size particles (40.35–148.00 μm class), and soil PNR, but decreased soil N2O emissions, especially in the drying time of paddy (P < 0.05), compared to NPK fertilization. NPKM had the highest values of AOA, AOB, and comammox clade A amoA gene copy numbers (P < 0.05), but clade B was increased by the NPK in the rhizosphere soil. Furthermore, fertilization showed greater effects on ammonia oxidizers (except for clade B) than the rhizosphere effect. Mantel test showed that SOM, TP, pH, NH4+, and NO3− were main abiotic factors causing the niche separation among ammonia oxidizers. Linear regression analysis and structural equation model (SEM) showed that both PNR and N2O emission fluxes were significantly associated with the abundance of AOB and comammox clade A (P < 0.05). Therefore, our results underline the importance of AOB together with comammox clade A in nitrification and N2O production in long-term organic fertilized paddy fields, which could provide new ideas for the mitigation of N2O emission by adopting organic fertilization scenarios in Chinese paddy fields.

Brain structure and connectivity mediate the association of lifestyle and cognition: the Maastricht study

Abstract Life-course exposure to risk and protective factors impacts brain macro- and micro-structure, which in turn affects cognition. The concept of Brain Age Gap (BAG) assesses brain health by comparing an individual’s neuroimaging-based predicted age with their calendar age. Higher BAG implies accelerated brain aging and is expected to be associated with worse cognition. In this study, we comprehensively modelled mutual associations between brain-health and lifestyle factors, brain age, and cognition in a large, middle-aged population. For this study, cognitive test scores, lifestyle, and 3T MRI data for n=4881 participants (mean age (±SD) = 59.2 (±8.6), 50.1% male) were available from The Maastricht Study, a population-based cohort study with extensive phenotyping. Whole brain volumes (grey matter (GM), cerebrospinal fluid (CSF), white matter hyperintensity (WMH)), cerebral microbleeds (CMB), and structural white matter connectivity were calculated. Lifestyle factors were combined into an adapted LIfestyle for BRAin health (LIBRA) weighted sum score, with higher score indicating greater dementia risk. Cognition was calculated by averaging z-scores across three cognitive domains (memory, information processing speed, executive function and attention). BAG was calculated by comparing calendar age to predictions from a neuroimaging-based multivariable regression model. Paths between LIBRA tertiles, BAG and cognitive function were tested using linear regression and structural equation modelling, adjusting for sociodemographic and clinical confounders. Results show that CSF, GM, WMH and CMB best predicted BAG (R2 = 0.455, RMSE = 6.44). In regression analysis, higher LIBRA scores (greater dementia risk) were associated with higher BAG (standardized regression coefficient ß = 0.126, p &amp;lt; 0.001) and worse cognition (ß = -0.046, p = 0.013), while higher BAG was associated with worse cognition (ß=-0.163, p&amp;lt;0.001). In mediation analysis, 24.7% of the total difference in cognition between the highest and lowest LIBRA tertile was mediated by BAG (ßindirect = -0.049, p &amp;lt; 0.001; ßtotal = -0.198, p &amp;lt; 0.001), and an additional 3.8% was mediated via connectivity (ßindirect = -0.006, p &amp;lt; 0.001; ßtotal = -0.150, p &amp;lt; 0.001). Findings suggest that associations between health- and lifestyle-based risk/protective factors (LIBRA) and cognition can be partially explained by structural brain health markers (BAG) and white matter connectivity markers. Lifestyle interventions targeted at high-risk individuals in mid to late life may be effective in promoting and preserving cognitive function in the general public.

Enhancing ESG learning outcomes through gamification: An experimental study.

This study investigates the effectiveness of gamification in enhancing learning outcomes in Environmental, Social, and Governance (ESG) education. Employing a cluster randomized experiment, the research involved 22 classes from four universities, divided into gamified and traditional teaching groups. The gamified group engaged with ESG concepts through interactive, game-like elements, while the control group followed standard educational practices. The study aimed to determine whether gamification could improve ESG course effectiveness and enhance Psychological Ownership and Perceived Importance, thereby influencing learning outcomes. Data collected through post-experiment surveys were analyzed using multiple linear regression and Structural Equation Modeling (SEM). Results indicated that students in the gamified group performed significantly better in ESG exams compared to the control group, demonstrating the effectiveness of gamification in enhancing academic achievement. The SEM analysis further revealed that gamification positively impacted Psychological Ownership and Perceived Importance, which in turn significantly improved academic performance. These findings suggest that incorporating gamification in ESG education can effectively engage students and deepen their understanding of complex sustainability issues. This study contributes to the field by highlighting the potential of gamification as a transformative tool in higher education, particularly in teaching abstract and multifaceted subjects like ESG.

Effects of plant diversity and community structure on ecosystem multifunctionality under different grazing potentials in the eastern Eurasian steppe

Grazing potential represents the potential carrying capacity of steppe livestock production. Understanding the impact of changes in plant diversity and community structure on ecosystem multifunctionality (EMF) at different grazing potentials is crucial for the sustainable management of steppe ecosystems. We examined the associations between plant diversity, community structure, above-ground ecosystem multifunctionality (AEMF), and below-ground ecosystem multifunctionality (BEMF) at various grazing potentials. Our assessment employed generalized linear mixed-effects models and structural equation models to determine the impact of these factors on ecosystem multifunctionality. Our study results indicated that ecosystem multifunctionality differed depending on the level of grazing potential and decreased as grazing potential declined. The impact of plant diversity and community structure on above- and below-ground ecosystem multifunctionality varied. Plant diversity and community structure correlated more with AEMF than BEMF. Plant diversity had the most significant effect on EMF under high grazing potential, while community structure had the greatest effect on EMF under moderate and low grazing potential. These improve our understanding of the correlation between steppe plant diversity, community structure, and above- and below-ground ecosystem multifunctionality. This understanding is necessary to develop strategies to increase plant diversity or regulate community structure and the sustainability of steppes.

A Causal Framework for the Comparability of Latent Variables

Measurement invariance (MI) describes the equivalence of measurement models of a construct across groups or time. When comparing latent means, MI is often stated as a prerequisite of meaningful group comparisons. The most common way to investigate MI is multi-group confirmatory factor analysis (MG-CFA). Although numerous guides exist, a recent review showed that MI is rarely investigated in practice. We argue that one reason might be that the results of MG-CFA are uninformative as to why MI does not hold between groups. Consequently, under this framework, it is difficult to regard the study of MI as an interesting and constructive step in the modeling process. We show how directed acyclic graphs (DAGs) from the causal inference literature can guide researchers in reasoning about the causes of non-invariance. For this, we first show how DAGs for measurement models can be translated into path diagrams used in the linear structural equation model (SEM) literature. We then demonstrate how insights gained from this causal perspective can be used to explicitly model encoded causal assumptions with moderated SEMs, allowing for a more enlightening investigation of MI. Ultimately, our goal is to provide a framework in which the investigation of MI is not deemed a “gateway test” that simply licenses further analyses. By enabling researchers to consider MI as an interesting part of the modeling process, we hope to increase the prevalence of investigations of MI altogether.

Non-parametric Regression Among Factor Scores: Motivation and Diagnostics for Nonlinear Structural Equation Models.

We provide a framework for motivating and diagnosing the functional form in the structural part of nonlinear or linear structural equation models when the measurement model is a correctly specified linear confirmatory factor model. A mathematical population-based analysis provides asymptotic identification results for conditional expectations of a coordinate of an endogenous latent variable given exogenous and possibly other endogenous latent variables, and theoretically well-founded estimates of this conditional expectation are suggested. Simulation studies show that these estimators behave well compared to presently available alternatives. Practically, we recommend the estimator using Bartlett factor scores as input to classical non-parametric regression methods.

Influence of moderate-to-high intensity physical activity on depression levels: a study based on a health survey of Chinese university students

ObjectiveThe study aims to examine how moderate-to-vigorous physical activity (MVPA) affects the severity of depression symptoms among Chinese college students. Additionally, it seeks to analyze the mediating mechanisms involving self-rated health and general self-efficacy.MethodsThe study utilized data from the 2023 Chinese College Health Tracking Survey and employed multiple linear regression and structural equation modeling techniques to investigate the impacts of MVPA on depression levels and its underlying mediating mechanisms among college students. The primary cohort comprised 49,717 enrolled college students from 106 universities in China.ResultsA total of 41,620 valid questionnaires were collected (response rate: 83.7%), with females accounting for 58.6%. In the past month, approximately 30.2% of college students engaged in MVPA. Self-rated health (B = − 0.282, P < 0.001) and general self-efficacy (B = − 0.133, P < 0.001) significantly influenced college students’ depression scores. Even after controlling for other variables, participating in MVPA remained significantly associated with reduced depression scores (B = − 0.062, P = 0.002). The results of the structural equation model showed that MVPA not only directly decreased college students’ depression scores but also indirectly reduced the likelihood of depression occurrence by improving their physical health status and general self-efficacy.ConclusionThe lack of physical activity among Chinese college students is evident. Engaging in MVPA can reduce the likelihood of depression among college students. MVPA achieves this reduction by enhancing college students’ general self-efficacy and improving their physical health. The factors influencing depression levels among college students are multifaceted. For future interventions targeting college students’ mental health, comprehensive approaches that incorporate behavioral and psychological factors should be emphasized.

Trees diversity explains variations in biodiversity-ecosystem function relationships across environmental gradients and conservation status in riparian corridors

Riparian ecosystems are recognized as large reservoirs of biodiversity providing important ecosystem services. However, the relationship between tree species diversity and ecosystem functions and the underlying ecological mechanisms have less been studied in riparian corridors. This study assessed the effect of tree diversity (taxonomic, functional, and phylogenetic) on riparian ecosystem functions (habitat quality–HbQ and aboveground carbon–AGC) across environmental gradients (distances to stream bed) and conservation status. Data were collected from 96 inventory plots installed in a 1 km buffer zone on either side of permanent streams in the Upper Ouémé watershed in northern Benin. We employed linear mixed effects models and structural equation modeling to analyze the data. We found that ecosystem functions (HbQ, AGC) and diversity attributes including species richness (SR), Faith’s phylogenetic diversity index (PD) and community-weighted mean of maximum height (CWMHmax) were significantly lower away from the streambed than nearby. The correlation between SR and ecosystem functions was significant and positive across and within the distance gradient and conservation status. We also found that the CWMHmax was the best predictor of both ecosystem functions, and that PD mediated the effect of SR on AGC and HbQ in areas close to the streambed and in unprotected areas, respectively. Our study reveals the influence of human activities on biodiversity and ecosystem functioning relationships in riparian corridors and provides new insights into the importance of tall stature trees and species with distant lineages for the functioning of these ecosystems. Based on the variables measured and tested in this study, we argue that riparian corridor management policies should consider plant traits and phylogeny and promote wider riparian buffers for the co-benefits of biodiversity conservation and climate change mitigation.

Does inclusive leadership influence employee innovation? A multilevel investigation

PurposeThe purpose of this research is to investigate the cross-level effects and mechanisms of inclusive leadership on employee innovation in team contexts, and further explore the boundary conditions of inclusive leadership.Design/methodology/approachThis study collected data from 237 leader-member dyads in 60 teams of Chinese firms. The research utilized multilevel linear models and multilevel structural equation models in the R language to test the hypothesized model.FindingsThe findings suggest that inclusive leadership has a positive impact on both employee incremental and radical innovation. Team psychological safety and employee role breadth self-efficacy mediate the effects. Employee risk avoidance propensity negatively moderates the mediating role of role breadth self-efficacy in the relationship between inclusive leadership and incremental innovation.Practical implicationsLeaders should pay attention to team psychological safety, employee role breadth self-efficacy and employee individual risk avoidance propensity that influence employee innovation to maximize the effectiveness of inclusive leadership.Originality/valueThis research expanded the level of analysis from individual to team, exploring cross-level effects and mechanisms of inclusive leadership on employee innovation in team contexts, and clarified the effectiveness conditions of inclusive leadership.

Breaking the budget chains: Empowering Iraqi small- and medium-sized enterprises through Beyond Budgeting

Background: Traditional budgeting has faced criticism, leading researchers to explore alternative management control methods such as Beyond Budgeting. Despite its potential benefits, Beyond Budgeting adoption remains limited.Aim: This research investigates Beyond Budgeting’s effect on Iraqi small- and medium-sized enterprise (SME) performance, focusing on competitive advantage.Setting: The study targets Iraqi SMEs, considering their diverse business landscape. A random sample of 353 accountants was chosen from a research community of 22 974 individuals. SPSS and AMOS 26 software and a custom questionnaire were used.Method: The authors conducted multiple linear regression analysis and Structural Equation Modeling to address our study’s objectives. Additionally, we utilised maximum likelihood procedures to assess factor loadings, construct validity and reliability.Results: Beyond Budgeting implementation significantly affected both financial and nonfinancial performance. It demonstrated positive effects on cost leadership and competitive advantage differentiation. However, an indirect negative impact on nonfinancial performance was observed through the influence on cost leadership, suggesting a trade-off between cost reduction and other nonfinancial factors.Conclusion: The study acknowledges limitations in sample size and the need for considering additional factors. Further research is required to understand Beyond Budgeting’s limited adoption in Iraq. The study contributes valuable insights on Beyond Budgeting as a substitute for traditional approaches, benefiting managers and policymakers.Contribution: This study emphasises Beyond Budgeting’s significant impact on Iraqi SME performance, highlighting the relationship between Beyond Budgeting, competitive advantage strategies, financial and nonfinancial performance. The findings provide insights for enhancing budgeting practices in Iraqi SMEs.

Early-life cumulative exposure to excess bodyweight and midlife cognitive function: longitudinal analysis in three British birth cohorts

Excess bodyweight (BMI >25 kg/m2) in midlife (age 40-65 years) has been linked to future cognitive decline and an increased risk of dementia. Whether chronic exposure to excess bodyweight in the early decades of life (<40 years) is associated with compromised cognitive function by midlife, however, remains unclear. This study therefore aimed to test potential bidirectional direct and indirect pathways linking cumulative exposure to excess bodyweight and cognitive function in the early decades of life. In this longitudinal analysis, harmonised measures of BMI and cognitive function were available in 19 742 participants aged 47-53 years recruited to the 1946 National Survey of Health and Development (n=2131), the 1958 National Child Development Study (n=9385), and the 1970 British Cohort Study (n=8226). Individual BMI trajectories spanning three decades from age 10-40 years were created for each participant and excess bodyweight duration, BMI change between ages, and cumulative excess bodyweight exposure were calculated. Harmonised measures of verbal and non-verbal ability, mathematical ability, and reading ability were used to create a latent factor for childhood cognitive function, and immediate and delayed recall, animal naming, and letter-search speed tests were used for midlife cognitive function. Multivariable linear regression and structural equation models (SEM) were used to test for potential bidirectional relationships between cognition and excess bodyweight in both individual cohorts and pooled datasets while accounting for other potential early-life confounders. Increases in BMI during adolescence and greater cumulative exposure to excess bodyweight across early life were associated with lower midlife cognitive function in all cohorts (eg, pooled difference in cognitive function per 10 years excess bodyweight duration -0·10; 95% CI -0·12 to -0·08; p<0·001). Further adjustment for childhood cognitive function attenuated many of these associations towards the null (eg, pooled difference in cognitive function per 10 years excess bodyweight duration -0·04; 95% CI -0·06 to -0·02; p=0·001), however, with any remaining associations then fully attenuating once further adjusted for other early-life factors (eg, pooled difference in cognitive function per 10 years excess bodyweight duration 0, -0·03 to 0·01; p=0·38). In the reverse direction, low childhood cognition was associated with greater cumulative exposure to excess bodyweight over the next four decades, although much of this relationship was found to probably be explained via other potentially modifiable upstream early-life factors such as childhood disadvantage. SEM in all cohorts suggested the presence of modest direct and indirect pathways connecting earlier cognitive function to later excess bodyweight, but scarce evidence for an effect of early-life excess bodyweight on cognitive function by midlife. The association between cumulative exposure to excess bodyweight in early life and lower cognitive function in midlife is probably confounded by a persistently lower cognitive function from childhood. Initiatives to improve early-life factors such as childhood disadvantage and education, however, might exert dual but independent benefits on both of these factors before old age. Alzheimer's Research UK, Diabetes Research and Wellness Foundation, Diabetes UK, British Heart Foundation, and Medical Research Council.

Factors affecting the implementation of STEAM education among primary school teachers in various countries and Vietnamese educators: comparative analysis

ABSTRACT STEAM education, recognised as an innovative model with wide-ranging benefits for students, can be challenging for teachers to implement, impacting their readiness. This study delves into the international experiences related to the preparedness of educators to implement STEAM education at the elementary level, drawing insights from 477 primary school teachers across 30 Vietnamese provinces. Utilising direct and online questionnaires, data was analyzed using linear structural equation modelling. The findings offer valuable insights into the effectiveness of STEAM education, particularly in elementary schools. Additionally, the research explores factors influencing STEAM education implementation in Vietnam, contributing to the global academic community and identifying elements impacting the global trend toward STEM/STEAM education. This study's comprehensive approach sheds light on the challenges faced by teachers and aims to enhance the knowledge base, making a significant contribution to the discourse on STEAM education.

Changes in Relationship between Forest Biomass Productivity and Biodiversity of Different Type Subtropical Forests in Southern China

Forest productivity is influenced by various factors, including biodiversity, environmental factors, functional traits, and forest types. However, the relative importance of these factors in determining the productivity of subtropical forests in southern China remains controversial. In this study, we analyzed a dataset of 24 forest plots from four subtropical forest types in the Nanling Mountains with the main goal of identifying and quantifying the relative contribution of the main driving factors of forest productivity in these forests. Generalized linear regression and structural equation modeling were used to examine the relationship between forest biomass productivity (aboveground, belowground and total), biodiversity (taxonomic diversity, phylogenetic diversity and functional diversity), and environmental variables (i.e., physiography and climate). The results indicated that both environmental factors and biodiversity played pivotal roles in explaining the biomass productivity of the Nanling subtropical forests. Environmental factors had the greatest influence on total productivity, while the impacts of different types of biodiversity on various productivity components (aboveground and belowground) varied notably. Taxonomic diversity showed the strongest positive effect on the aboveground and belowground biomass productivity. However, phylogenetic and functional diversity had negative effects on productivity. Furthermore, these relationships also exhibited variations when considering different altitude gradients, with low altitudes generally leading to negative biodiversity–productivity correlations. We contextualized our results regarding the three state-of-the-art theories about biodiversity–productivity relationships (selection probability, niche complementarity, and biomass ratio) and concluded that both selection probability and niche complementarity are the driving mechanisms of productivity in the subtropical forests of the Nanling Mountains. This study offers valuable insights into the functioning and biodiversity mechanisms of subtropical forest ecosystems in southern China.

Promises of parallel outcomes

Summary A key challenge in causal inference from observational studies is the identification and estimation of causal effects in the presence of unmeasured confounding. In this paper, we introduce a novel approach for causal inference that leverages information in multiple outcomes to deal with unmeasured confounding. An important assumption in our approach is conditional independence among multiple outcomes. In contrast to existing proposals in the literature, the roles of multiple outcomes in the conditional independence assumption are symmetric; hence, the name parallel outcomes. We show nonparametric identifiability with at least three parallel outcomes and provide parametric estimation tools under a set of linear structural equation models. Our proposal is evaluated through a set of synthetic and real data analyses.

LeCaSiM: Learning Causal Structure via Inverse of M-Matrices with Adjustable Coefficients

The objective of causal discovery is to uncover the causal relationships among natural phenomena or human behaviors, thus establishing the basis for subsequent prediction and inference. Traditional ways to reveal the causal structure between variables, such as interventions or random trials, are often deemed costly or impractical. With the diversity of means of data acquisition and abundant data, approaches that directly learn causal structure from observational data are attracting more interest in academia. Unfortunately, learning a directed acyclic graph (DAG) from samples of multiple variables has been proven to be a challenging problem. Recent proposals leverage the continuous optimization method to discover the structure of the target DAG from observational data using an acyclic constraint function. Although it has an elegant mathematical form, its optimization process is prone to numerical explosion or the disappearance of high-order gradients of constraint conditions, making the convergence conditions unstable and the result deviating from the true structure. To tackle these issues, we first combine the existing work to give a series of algebraic equivalent conditions for a DAG and its corresponding brief proofs, then leverage the properties of the M-matrix to derive a new acyclic constraint function. Based on the utilization of this function and linear structural equation models, we propose a novel causal discovery algorithm called LeCaSiM, which employs continuous optimization. Our algorithm exploits the spectral radius of the adjacency matrix to dynamically adjust the coefficients of the matrix polynomial, effectively solving the above problems. We conduct extensive experiments on both synthetic and real-world datasets, the results show our algorithm outperforms the existing algorithms on both computation time and accuracy under the same settings.

Association between skeletal muscle and left ventricular mass in patients with hyperthyroidism.

This study aims to investigate the relationship between skeletal muscle and left ventricular mass (LVM) in patients with hyperthyroidism, providing theoretical and data-based foundations for further research on the interaction between secondary muscle atrophy and cardiac remodeling. A retrospective data collection was conducted, including 136 patients with hyperthyroidism (Study group) and 50 healthy participants (control group). The Study group was further divided into Group A (high LVM) and Group B (low LVM) based on LVM size. Multiple linear regression analysis was performed to examine the correlation between skeletal muscle and LVM, with model evaluation. Based on the results, further nonlinear regression analysis was conducted to explore the detailed relationship between skeletal muscle and LVM. Compared to the control group, the Study group exhibited significantly lower LVM, skeletal muscle mass index (SMI), and skeletal muscle mass (SMM) (P<0.05). Within the subgroups, Group A had significantly higher SMI, SMM, and hand grip strength compared to Group B (P<0.05). The results of the multiple linear regression showed a certain correlation between SMI (β=0.60, P=0.042, 95% CI=0.02~1.17) and hand grip strength (β=0.34, P=0.045, 95% CI=0.01~0.67) with LVM. However, the residuals of the multiple regression did not follow a normal distribution (K-S=2.50, P<0.01). Further results from a generalized linear model and structural equation modeling regression also demonstrated a correlation between SMI (β=0.60, P=0.040, 95% CI=0.03~1.17) (β=0.60, P=0.042, 95% CI=0.02~1.17) and hand grip strength (β=0.34, P=0.043, 95% CI=0.01~0.67) (β=0.34, P=0.045, 95% CI=0.01~0.67) with LVM. Patients with hyperthyroidism may exhibit simultaneous decreases in LVM, SMM, and SMI. The LVM in patients is correlated with SMM and hand grip strength, highlighting the need for further exploration of the causal relationship and underlying mechanisms. These findings provide a basis for the prevention and treatment of secondary sarcopenia and cardiac pathology in patients with hyperthyroidism.

The Impact of the Employee’s Personal Characteristics on the Abuse of Sickness Absence: Empirical Evidence From Poland

Abstract Objective The tendency to abuse sickness absence is a complex problem conditioned by many factors, that can be divided, depending on the level of impact, into three groups: micro (related to personal characteristics), meso (related to the work environment), and macro (related to the broader environment). The subject of interest in the article is the first level (micro). The aim is to evaluate the impact of various personal factors on the declared abuse of sickness leave in Poland. Research Design &amp; Methods The data was gathered using the CAWI survey. The research sample consisted of 1067 respondents (full-time employees). Statistical analysis incorporated multivariable linear regression and structural equation modelling. Findings Some personal characteristics have a significant impact on the declared abuse of sick leave. These factors are: gender, age, number of children, place of living, marital status, and subjective health. We found no impact of education and financial status. Implications &amp; Recommendations Although abusing sick leave is a serious economic and organisational problem, its causes still remain relatively poorly recognised. Personal characteristics determine the propensity to abuse sick leave, and they need to be taken into account under the process of managing absence behaviours. Contribution &amp; Value Added The added value of the study is drawing attention to the new personal factors which were not previously identified as a determinant of abuse of sick leave. These are: the number of children, place of living, and marital status.

Thriving in Constraints: Exploring the Interplay of Human Capital, Social Capital, and Financial Constraints in Frugal Innovation within Family Businesses

This study aims to learn the impact of human capital, social capital, and financial constraints on frugal innovation as perceived by family businesses in the Philippines. Quantitative research was performed using data collected from 93 family businesses, which were analyzed using simple linear regression and structural equation modeling. The results showed that human capital, social capital, and financial constraints, individually and collectively, have a significant impact on frugal innovation. The results also indicated that all measures used for human capital and financial constraints are acceptable, while some measures of social capital and frugal innovation were deemed unfit and were removed from the model. The academe should expand or improve its discussion and curriculum on frugal innovation and continue to look at this through the lenses of its theoretical and practical aspects. Moreover, professors and students should study the relationship further and ultimately expand knowledge and understanding. Family businesses should prioritize improving their human capital to enhance their frugal innovation capabilities. Implementing efficient financial procedures, investigating alternative funding sources, and actively seeking external finance opportunities are crucial. Moreover, family businesses should develop robust social networks. Lastly, the Philippine government should actively encourage continuous learning through mentorship programs and networks.

The relationship between student engagement and dropout risk in early adolescence

One of the most reliable predictors of school effectiveness is student engagement, which is not only related to students’ current achievement but also long-term outcomes. Using linear regression and structural equation modeling procedures, the present study was aimed at examining the relationship between dropout risk, dimensions of student engagement, and family background. The survey study involved 3251 7th grade Hungarian students who completed the adapted Student Engagement Instrument and self-reported background questionnaire. According to the results, student performance is mainly related to parents’ educational attainment, but a moderate or weak correlation with behavioral, academic, and cognitive engagement is also detectable. While affective engagement shows a weak association with performance, it correlates with other engagement dimensions linked to achievement. This result suggests that support from parents, peers, and teachers may have an indirect effect on achievement; however, the present study could not confirm this hypothetical model. Based on our data, parental educational attainment and student engagement account for approximately 41 % of student performance which draws attention to the complexity of the relationship between student engagement and performance and highlights the importance of a comprehensive approach to dropout and student engagement in this context.

What Is the Most Influential Authenticity of Beliefs, Places, or Actions on the Pilgrimage Tourism Destination Attachment?

Religious tourism attracts many pilgrims and tourists to travel to a sacred space, and the issue of its authenticity has become increasingly important. Convenience sampling was used to conduct a survey at Dajia Jenn Lann Temple, Taichung City, Taiwan, and 487 valid questionnaires were obtained. The linear structural equation model constructs the analysis results as follows: (1) The “authenticity of place” and “action authenticity” have a positive relationship on the “place attachment” and act as a mediator variable for the effects of “authenticity of belief” on “authenticity of action”. (2) Tourists who have visited twice or more have a higher impact on “authenticity of belief” than those who have visited once. (3) Among the factors of the “authenticity of belief”, “concept of life” and “concept of God” are the most important; among the factors of the “authenticity of the place”, “spiritual sustenance” is the most important; and among the factors of “authenticity of action”, “experiential action” and “consequential actions” are the most important. The “place identity” is the essential aspect of the “place attachment” factor. This study developed a scale of the authenticity of belief, place, and action. Research results can provide a reference for religious tourism development.