Path Model Research Articles

ANALYSIS OF PATH NONPARAMETRIC TRUNCATED SPLINE MAXIMUM CUBIC ORDER IN BANKING CREDIT OF RISK BEHAVIOR MODEL

Path analysis tests the relationship between variables through cause and effect. The assumption of linearity must be met before conducting further tests on path analysis. If the shape of the relationship is nonlinear and the shape of the curve is unknown, a nonparametric approach is used, one of which is a truncated spline. The purpose of this study is to estimate the function and obtain the best model on the nonparametric truncated spline path of linear, quadratic, and cubic orders with 1 and 2-knot points and determine the significance of the best function estimator in banking credit of risk behavior model through the jackknife resampling method. This study uses secondary data through questionnaires to KPR debtor consumers, as many as 100 respondents. Based on the results of the analysis, it is known that the best-truncated spline nonparametric path model is the quadratic order of 2 knots with a coefficient of determination of 85.50%; the significance of the best-truncated spline nonparametric path estimator shows that all exogenous variables have a significant effect on endogenous variables.

Passenger Mobility Impact on Customer Satisfaction and Environmental Degradation Through Air Transportation Crowdshipping

Authors: This study investigates the impact and implications of passenger mobility through crowdshipping on customer satisfaction and environmental degradation. A questionnaire was used to collect data from customers who have been aeroplane passengers at Hang Nadim Airport in Batam, Indonesia. SmartPLS software was used to evaluate the quality of the questionnaire data and test the research hypotheses. The SmartPLS path model analysis results show that passenger mobility affects Crowdshipping, customer satisfaction, and environmental degradation; Crowdshipping affects passenger mobility and environmental degradation, and customer satisfaction affects environmental degradation. The findings of this study help understand and quantify potential strategies for logistics delivery by utilizing aeroplane passenger crowd shipping. Consequently, it can help policymakers and air transport companies develop air transport-based crowd shipping models to estimate the possible impacts from an economic and environmental point of view as well as environmental utilization.

Exploring the minimum cost conflict mediation path to a desired resolution within the inverse graph model framework

The existing inverse graph model for conflict resolution (GMCR) research primarily concentrates on identifying the required preferences of decisions makers (DMs) such that a desired state is an equilibrium. However, the process of transitioning from the current state to the desired equilibrium is not explored. In this paper, we propose a minimum adjustment cost model taking account of preference adjustment costs to identify the required preferences for a desired state to be an equilibrium. Subsequently, we introduce the concept of transition costs for the first time to quantify expenses involved in guiding a DM transition from one state to another and develop a minimum cost conflict mediation path model. This model aims to identify the most efficient path that minimizes the cost of transitioning from the current state to the desired equilibrium. Moreover, to accommodate the consideration of multiple desired equilibria, we extend the minimum cost conflict mediation path model to analyze and determine the optimal path for transitioning from the current state to one of the identified desired equilibria with the overall minimum cost. Furthermore, to address uncertainty surrounding transition costs, we formulate a probability maximizing conflict mediation path model that considers a limited budget available for the mediation process. Finally, a real-world dispute, the fracking conflict in the province of New Brunswick, Canada, is utilized to demonstrate the application of the proposed models.

The Influence of 'Ugly Cute' Intellectual Property Anthropomorphism on the Purchase Intention of Cultural and Creative Products Based on the Mediating Role of Intellectual Property Identity

Under the background of "museum fever" starting from intellectual property anthropomorphism (IP anthropomorphism), this paper introduces the variable of intellectual property identity (IP identity), constructs the functional path model of consumers' purchase of "ugly cute" cultural and creative products, and analyzes the data by using questionnaires and mathematical models to explore how IP anthropomorphism affects consumers' purchase intention and analyze the mediating function that IP identity carries out between IP anthropomorphism and consumers' purchase intention in the process. This study shows that both IP anthropomorphism and IP identity have a direct positive influence on consumers' purchase intention, and IP identity does play a mediating role in the influence of IP anthropomorphism on consumers' purchase intention. Based on the results of the study, this paper proposes creative suggestions about IP design to the design department in the museum in order to help the museum increase sales of cultural and creative products and make its products meet the different needs of consumers at the same time.

An Investigation of the Longitudinal Bidirectional Associations Between Interactive Versus Passive Social Media Behaviors and Youth Internalizing Difficulties. A Within-Person Approach.

Ongoing concerns about the mental health of young people have intensified interest in the role of social media, with research suggesting that the nature of social media behaviors-whether interactive or passive-may differentially impact mental health. However, the bidirectional relationships between specific types of social media use and internalizing difficulties (anxiety and depression) remain underexplored, particularly at the within-person level over time. Data were extracted from the Dutch population-based Longitudinal Internet Studies for the Social Sciences (LISS) panel. Four yearly studies assessing time spent on interactive (communication) and passive use of social media in October (2019-2022) and four annual studies evaluating internalizing difficulties (anxiety and depression) in November (2019-2022) were used. Respondents who were 16- 25 years old in October 2019 (N = 321; M = 20.49; SD = 2.94; 61.7% female). Random Intercept Cross Lagged Path Models were used to analyze the data. There were no significant associations between passive social media use and internalizing difficulties at the within-person level over time. Within-person interactive use was associated with decreases in internalizing difficulties at one time point (2021 to 2022). The results provide marginal evidence that distinct social media behaviors are prospective factors associated with internalizing difficulties in young people.

Eucalyptus and Native Broadleaf Mixed Cultures Boost Soil Multifunctionality by Regulating Soil Fertility and Fungal Community Dynamics.

The growing recognition of mixed Eucalyptus and native broadleaf plantations as a means of offsetting the detrimental impacts of pure Eucalyptus plantations on soil fertility and the wider ecological environment is accompanied by a clear and undeniable positive impact on forest ecosystem functions. Nevertheless, the question of how mixed Eucalyptus and native broadleaf plantations enhance soil multifunctionality (SMF) and the mechanisms driving soil fungal communities remains unanswered. In this study, three types of mixed Eucalyptus and native broadleaf plantations were selected and compared with neighboring evergreen broadleaf forests and pure Eucalyptus plantations. SMF was quantified using 20 parameters related to soil nutrient cycling. Partial least squares path modeling (PLS-PM) was employed to identify the key drivers regulating SMF. The findings of this study indicate that mixed Eucalyptus and native broadleaf plantations significantly enhance SMF. Mixed Eucalyptus and native broadleaf plantations led to improvements in soil properties (7.60-52.22%), enzyme activities (10.13-275.51%), and fungal community diversity (1.54-29.5%) to varying degrees compared with pure Eucalyptus plantations. Additionally, the mixed plantations exhibit enhanced connectivity and complexity in fungal co-occurrence networks. The PLS-PM results reveal that soil properties, fungal diversity, and co-occurrence network complexity directly and positively drive changes in SMF. Furthermore, soil properties exert an indirect influence on SMF through their impact on fungal diversity, species composition, and network complexity. The findings of this study highlight the significant role of mixed Eucalyptus and native broadleaf plantations in enhancing SMF through improved soil properties, fungal diversity, and co-occurrence network complexity. This indicates that incorporating native broadleaf species into Eucalyptus plantations can effectively mitigate the negative impacts of monoculture plantations on soil health and ecosystem functionality. In conclusion, our study contributes to the understanding of how mixed plantations influence SMF, offering new insights into the optimization of forest management and ecological restoration strategies in artificial forest ecosystems.

Evaluation of the Effect of Commercialization of Technology in Creating Sustainable Competitive Advantage of Knowledge-based Companies Emphasizing the Moderating Role of Environmental Factors

The present study aimed at designing a structural equation model of the effect of technology commercialization performance on creating sustainable competitive advantage of knowledgeable companies with an emphasis on the moderating environmental factors.Research population includes 133 managers of knowledge based companies at the center for the growth and development of science and technology Park of East Azerbaijan University and based on the Cochran formula, the sample size was measured to be 99, and selection by stratified random sampling method, and the standard questionnaire is distributed among them. The research is applied in nature and the method is descriptive and survey. Then, the data were analyzed using smart pls software for partial least squares (PLS) path modeling. The results show that the technology commercialization performance has a positive effect on the competitive sustainable advantage of knowledge-based companies, as well as the role of variable moderating environmental factors (market turbulence, competitive intensity and technological turbulence) in the path between the technology commercialization performance and the sustainable competitive advantage of knowledge-based companies.

Arbuscular mycorrhizal fungal inoculum and N2-fixing plants in ecological reclamation of arid mining areas: nutrient limitation of the moss biocrust microbiome.

Ecoenzymatic stoichiometry can reflect the ability of soil microorganisms to acquire energy and nutrients and to determine their response to environmental stresses. However, the drivers of metabolic limitation of the moss biocrust microbiome during the ecological restoration of coal mining areas are poorly understood. Therefore, in this study, enzymatic stoichiometry modeling and high-throughput sequencing were used to simultaneously determine moss biocrust microbial metabolic limitation and its relationship with moss biocrust nutrients and arbuscular mycorrhizal fungal (AMF) diversity in five arid and semi-arid revegetation types (Hippophae rhamnoides, Amorpha fruticosa, Cerasus humilis, Cerasus szechuanica, and Xanthoceras sorbifolium) and two microbial treatments (AMF-inoculated and uninoculated). The activities of moss biocrust carbon (C)-, nitrogen (N)-, and phosphorus (P)-acquiring enzymes and organic carbon fractions in the AMF-inoculated treatment were significantly higher than those in the uninoculated control. Moss biocrust microbial community C and P limitations were observed in the five revegetation types, with lower limitation in general in the AMF-inoculated treatment. Dinitrogen-fixing plants (Amorpha fruticosa and Hippophae rhamnoides) significantly mitigated moss biocrust microbiome C and P limitation, especially in the AMF-inoculated treatment. Furthermore, partial least squares path modeling (PLS-PM) shows that moss biocrust organic carbon fractions (- 0.73 and - 0.81 of the total effects, respectively) and AMF diversity (- 0.73 and - 0.81 of the total effects) had negative effect on microbial C and P limitation, suggesting that more efficient active nutrients and AMF diversity are important factors alleviating limitation of moss biocrust microbial metabolism. This indicates that moss biocrust microbial communities under N2-fixing species with AMF inoculation were more stable under environmental stress; thus, AMF inoculation and/or N2-fixing plants may be recommended as preferred options for the ecological restoration of arid mining areas.

The effect of postfire regeneration pattern on soil respiration in the boreal forest of China

BackgroundAs the second largest carbon flux between the atmosphere and terrestrial ecosystems, soil respiration involves multiple components of ecosystem production. Revealing soil respiration in forests with different postfire regeneration patterns is critical for determining appropriate restoration strategies in response to increasing wildfire disturbances. Here, we examined the influence of five postfire regeneration patterns (L: Larix gmelinii monocultures, LB: L. gmelinii and Betula platyphylla mixed plantations, P: Pinus sylvestris var. mongolica monocultures, PB: P. sylvestris var. mongolica and B. platyphylla mixed plantations, N: naturally regenerated forests) on soil heterotrophic respiration (Rh) and total respiration (Rs).MethodsTrenching was implemented to monitor soil heterotrophic respiration. We used partial least squares path modeling methods to estimate the different environmental factors regulating soil respiration across forest types.ResultsThe results showed that forest type and season had significant effects on Rs and Rh. Rh was the dominant part of Rs for all forest types (68.84 ~ 90.20%). Compared to naturally regenerated forests, Rs and Rh under L, LB, and PB had higher rates (P < 0.05), while Rs and Rh under P had lower rates (P < 0.05). The temperature sensitivities of Rs under different forest types were 2.316 (L), 1.840 (LB), 1.716 (P), 1.665 (PB), and 2.096 (N).ConclusionsForests regenerated with artificial participation established their plant communities visibly faster than naturally regenerated forests. Mixed species plantation regeneration demonstrated an improvement in soil respiration compared to naturally regenerated forests but had a lower temperature sensitivity of soil respiration than their respective monocultures. Soil temperature and moisture dominated the influence factors on soil respiration throughout the broader seasonal shifts. However, for a single season, forest productivity and soil properties have a greater impact on soil respiration. This study extends our knowledge of the interaction mechanism between soil respiration and environmental variables in boreal forests and contributes to improving confidence in global carbon cycling model predictions.

The Effect of Transformational Leadership Towards Affective Commitment In Vocational Schoolof West Kalimantan

&lt;p&gt;In the era of industrial revolution 4.0, the functional reformation must be conducted to vocational education. The vocational education sector has been in a crucial position to prepare good quality human resources (teachers and students) that are well-prepared in the era of industrial revolution 4.0. An ability of computer literacy and noble character (akhlakul karimah) of human resources are two essential aspects that have been concern in the effort of the superior human preparation. Therefore, this aim of this study is to develop a new model of affective commitment and see its impact to transformational leadership in vocational school across west Kalimantan. A quantitative approach using partial least squares path modeling (PLS-SEM) Wrappls version 7 was used to calculate 254 data sample from 29 private and public vocational high schools throughout West Kalimantan. The result revealed that the role of affective commitment as a mediating variable had been able to provide a positive and significant influence as well as this variable was able to improve the performance of leaders and teachers in vocational high schools throughout West Kalimantan through exogenous variables in the form of transformational leadership.&lt;/p&gt;

Online secondary path modeling algorithm without auxiliary noise for narrowband active noise control

Online secondary path modeling (SPM) is a practical method for real-time noise reduction in narrowband active noise control (NANC) systems, particularly when addressing variations in the secondary path. However, the common practice of using auxiliary noise for online SPM increases the residual noise power and deteriorates the noise reduction performance. The present study proposes a strategy that does not rely on auxiliary noise for online SPM in NANC systems. The proposed algorithm comprises two stages: Stage A models the primary path, whereas Stage B concurrently engages in online SPM and active noise control. The control signal is used to model the discrete Fourier transform (DFT) coefficients of the secondary path, avoiding the need for an auxiliary noise and significantly reducing the computational complexity. Moreover, the predicted primary path from Stage A is employed to obtain the pure desired signal of the online SPM. This strategy decorrelates the primary noise and the modeling signal, and accelerates the convergence of the algorithm. Simulations of recorded data demonstrate that the proposed algorithm can quickly track variations in both the primary and secondary paths, and maintain the noise reduction performance and stability of the system.

Exploring the Impact of E-WOM Information via Social Media on Customer Purchasing Decision: A Mediating Role of Customer Satisfaction

The study investigates the impact of E-WOM information on purchasing decisions, using customer satisfaction as a mediator. It examines E-WOM information as independent variables, such as quality, quantity, and credibility, and as dependent variables, such as consumer satisfaction and purchasing decisions, with customer satisfaction serving as a mediator to investigate the relationship between E-WOM information and purchasing decisions. A questionnaire was issued to 307 social media-active clients, and the hypotheses were tested using quantitative methods. Data analysis comprised descriptive statistics, Cronbach's alpha, skewness and kurtosis, and Pearson correlation coefficient, as well as a fit model for measuring questionnaire reliability and validity, regression for sub-hypotheses, and a path model for evaluating main hypotheses. The findings revealed that all three dimensions of E-WOM information had a positive impact on customer satisfaction and purchase decisions, both individually and jointly. Customer satisfaction has a positive influence on purchasing decisions. Furthermore, E-WOM information has been shown to positively impact purchasing decisions via consumer satisfaction. The study suggests that organizations should understand the dimensions that impact customer satisfaction and purchasing decisions in order to fulfill their goals, remain ahead of the competition, and obtain a competitive advantage. Proper tracking of social media reviews, comments, and recommendations may help organizations deliver answers, increase customer satisfaction, and aid in making purchasing decisions

Influence of spectral and molecular composition of dissolved organic matter on labile Cd mobility in riparian soils in the Three Gorges Reservoir, China

The periodic anti-seasonal inundation of the Three Gorges Reservoir (TGR) leads to changes in the molecular composition of dissolved organic matter (DOM) in riparian soils, further impacting the geochemical processes and ecological risk of heavy metals. However, the intrinsic driving mechanisms of DOM influencing the cadmium (Cd), a major pollutant in riparian soils in TGR, at the molecular level remain unclear. In this study, the DOM molecular composition, labile Cd in riparian soils and the key driving mechanism before and after flooding were explored using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), the diffusive gradients in thin films (DGT) and partial least squares path modeling (PLS-PM). A spectral analysis revealed that after flooding, the relative abundance of terrestrial humic-like substances decreased whereas that of microbial humic-like substances increased. Furthermore, FT-ICR MS analysis revealed that the relative abundance of lignin, the main molecular components of DOM in riparian soils, increased after flooding. The linkage of DOM with the concentration and kinetic processes of labile Cd indicated that the higher aromaticity and unsaturation, larger molecular weight, and higher humification level of DOM promoted the mobility of labile Cd from the soil solid phase to the liquid phase. In particular, our findings indicated that at the molecular level, the most significant factor influencing the mobility of labile Cd was lignin, which was primarily governed by the complexation of lignin with labile Cd. The complexation mechanism between lignin and labile Cd resulted in increased ecotoxicological risk of labile Cd after flooding, while the overall ecotoxicological risk was low in riparian soils in TGR. This study provides better insight into the geochemical cycling and fate of toxic elements in reservoir ecosystems under the change of hydrological regime.

More social media friends, more life satisfaction?– why fear of missing out leads to contrary effects

Fear of Missing Out is a focus of research in social sciences, especially with respect to social media use. This study examined the extent to which social media use (active and passive, respectively) elicits Fear of Missing Out due to greater perceived bridging and bonding social. In addition, the extent to which Fear of Missing Out affects feelings of stress and life satisfaction was investigated. In an online survey 1230 participants were included. Within the framework of a path model, the assumption of an indirect effect of both active and passive social media use via social capital, Fear of Missing Out, and stress on life satisfaction was confirmed. Finally, further study results as well as implications and limitations of this research are discussed.

Impact of Supply Chain Agility and Collaboration on Supply Chain Performance: The Moderating Role of Artificial Intelligence

Supply chain resilience is not a novel concept in the supply chain industry; however, its significance importance is increasing, especially in the face of global disruptive events like natural and man-made disasters. Agility and collaboration are critical supply chain resilience elements for enhancing supply chain performance. However, the influence of artificial intelligence (AI) on the impact of agility and collaboration on performance remains unexplored. Therefore, the major objective of this study was to examine the impact of supply chain agility and collaboration on supply chain performance within the healthcare sector in Qatar. In the same vein, it examined the moderating role of AI in these relationships. The study utilized 564 responses from supply chain and clinical unit managers in Qatar and was analysed using the partial least squares (PLS) path modelling technique. The findings of the study indicate a significant positive relationship between supply chain agility, collaboration, and performance. Furthermore, these relationships are found to be positively moderated by AI. This study supports the research paradigm and provides evidence regarding supply chain agility and collaboration and their impact on supply chain performance. More importantly, this study is among the first to provide empirical evidence on the moderating role of AI in enhancing these relationships.

Physics-based digital twin updating and twin-based explainable crack identification of mechanical lap joint

The mechanical joints, including the lap joint, weld, bolt, and pin, are vulnerable to fatigue failure because of stress concentration and internal flaws. Digital twin (DTw) strategies were proposed to prevent catastrophic system failure by fatigue damage in mechanical joints. In previous studies, the data-driven approach, such as deep learning and machine learning were utilized to estimate severity of the damage. However, it needs to improve its prediction accuracy because of insufficient data and physical interpretability. In this study, the physics-based digital twin model updating and twin-based crack identification of fatigue damage in riveted lap joints were proposed using lamb waves with consideration of uncertain crack growth path. The proposed approach is based on three techniques; (i) Data pre-processing, including filtering and optimization-based signal synchronization, (ii) Lamb-wave propagation analysis with sensor dynamics model and uncertain crack path, and (iii) Optimization based physics-based model updating and inference. In data pre-processing, the excitation frequency magnitude and truncation time are estimated using the observed actuator signal in the Lamb-wave test. The sensor dynamic model and model parameters are updated using the Bayesian optimization method to minimize both the errors in the predicted (y^t) and observed (yt) wave signal and the errors in the inferred (l*) and observed (l) crack length. The crack growth path is sampled based on angular and spline schemes to consider uncertain crack propagation paths. The validity of the proposed method is demonstrated using an open data set (2019 PHM society data challenge). The results conclude that the proposed digital twin approach can improve estimation accuracy considering both the crack growth path and sensor dynamics model.

The omnichannel effect: Evaluating consumer satisfaction in the wake of e-commerce closure among Bandung's MSMEs

This research delves into the impact of the government's closure of TikTok shop's online marketing interaction channel on MSMEs, emphasizing the reduction in offline interaction channels and resulting business losses. The study's primary objective is to dissect and assess the multifaceted omnichannel interaction framework, comprising online, offline, and cross channels, and its influence on consumer experience value and satisfaction. Conducted in Bandung, Indonesia, the research engaged 425 participants who interact through various marketing channels. Utilizing the partial least squares path model, the study deduces that while online and cross channels significantly influence experience value and consumer satisfaction, offline channels do not. This insight calls for a reevaluation of the TikTok shop closure decision, considering the profound role of satisfaction in purchasing decisions. The research, however, recognizes its limitations in terms of the temporal scope, analytical methods, and potential for hypothesis refinement. Future studies could broaden the geographic scope to incorporate diverse cities, offering insights shaped by varying local characteristics. Overall, the study contributes to the understanding of omnichannel interactions' effects on consumer satisfaction, presenting a nuanced perspective for academics and practitioners to enhance consumer shopping experiences.

Development of a Simulator for Submarine Path Estimation and Optimization of Sonobuoy Deployment Patterns

Due to specificity in the underwater environment, the difficulty of detecting submarine and the threat of submarine are increasing. The probability of detecting a submarine can be increased by estimation submarine path and optimizing sonobuoy deployment. In this paper, marine data collection, dynamics of submarine, submarine tracking path modeling, acoustic wave propagation modeling, detection probability modeling are applied in the simulator as similar to reality as possible. A simulator is developed to design submarine path estimation and sonobuoy deployment optimization scenario and to check result according to the scenario.

A longitudinal path model examining the transactional nature of parenting and child externalizing behaviors in a large, sociodemographically diverse sample.

Children's externalizing behaviors are associated with impairments across the lifespan. Developmental psychopathology theories propose transactional (bidirectional) associations between child externalizing behaviors and parenting during childhood and adolescence. Yet, these foundational relations in early childhood are not well-studied. Utilizing a large, mixed-sex sample, we examined the reciprocal nature of parenting and child externalizing behaviors across early childhood using robust repeated-measures models. Repeated measures data were drawn from a socioeconomically diverse, longitudinal pregnancy cohort of 1287 (64% Black, 31% White) mother-child dyads at four time points (ages one to six). Three variables were included in cross-lagged panel models: observed parenting quality, child externalizing symptoms, and a maternal risk composite. In covariate-adjusted models, higher parenting quality at Wave 1 predicted lower child externalizing symptoms at Wave 2. Higher externalizing symptoms at Wave 1 and Wave 2 predicted lower parenting quality at Wave 2 and Wave 3, respectively. Maternal risk and parenting quality were not significantly associated. Findings showed both parent-driven and child-driven effects across early childhood that did not vary by child sex. The transactional nature of the parent-child relationship begins in infancy, underscoring the importance of early screening and provision of supports for families to minimize and prevent the development of serious psychopathology.

Dropout Intention among University Students with ADHD Symptoms: Exploring a Path Model for the Role of Self-Efficacy, Resilience, and Depression

Dropout Intention among University Students with ADHD Symptoms: Exploring a Path Model for the Role of Self-Efficacy, Resilience, and Depression