Quantitative Structural Model Research Articles

A multilayered urban tree dataset of point clouds, quantitative structure and graph models

The significance of urban trees in promoting human health and well-being has been amplified by urbanization and the climate change effects. Simultaneously, advancements in remote sensing techniques have enhanced the opportunities for studying urban trees. The TreeML-Data has been compiled to support these efforts. It consists of labelled point clouds of 40 scanning projects of streets in Munich, 3,755 leaf-off (scans in winter) point clouds of individual trees, quantitative structure models (QSM), tree structure measurements, and tree graph structure models of these trees. The dataset offers valuable data for generating and evaluating models in various scientific disciplines, which include remote sensing, computer vision, machine learning, urban forestry, urban ecosystem, green architecture, and graph analysis. To ensure its quality, the tree structure measurements and QSM have been crosschecked. For instance, the tree diameter at breast height (DBH) in the sample dataset exhibits a deviation of approximately 1.5 cm (4.3%) when compared to manual measurements. In conclusion, the quality checks confirm its reliability for subsequent studies when compared to manual measurements.

Influence of crown morphology and branch architecture on tree radial growth of drought-affected Fagus sylvatica L.

Trees are able to adapt to changing environmental conditions through modifications in their crown morphology and branch architecture. In light-limited environments, tree structures are mainly optimised to increase light interception. This might have side effects on other properties such as the hydraulic system that determines water conduction and tree reactions to drought events. Given the increasing exposure of forest ecosystems to drought stress it is thus crucial to investigate possible correlations between the crown morphology and branch architecture and drought responses. Our study aimed to compare different crown archetypes and branch characteristics of European beech (Fagus sylvatica L.) in their reaction to drought, which was assessed by measuring tree-ring widths of increment cores sampled at breast height. Using Terrestrial Laser Scanning and Quantitative Structure Models, we explored various crown morphological and branch architectural characteristics of 67 beech trees and identified three species-specific crown archetypes. The crown archetypes and branch variables were contrasted with growth responses using linear mixed models. While productivity levels differed, the negative impact of drought stress on radial growth was consistent across all crown archetypes. Nevertheless, certain branch architectural variables were important predictors for radial growth in drought situations. Specifically, long water conduction paths and many branching nodes along those paths were positively influencing growth. Our results indicate that trees showing these characteristics might have a competitive edge regarding drought-affected radial growth compared to others. They could be promoted through thinning measures, which would allow improving the adaption of existing beech forests in situ to climate change and drought stress.

Positive Personality Traits, Organizational Commitment and Work Environment: A Structural Equation Model on Core Job Characteristics of Public School Teachers

This study aimed to determine the best-fit model of core job characteristic as influenced by positive personality traits, organizational commitment, and work environment of public school teachers in Davao Region, Philippines. Descriptive correlational, quantitative non-experimental research design and Structural Equation Model were used in this research. Standardized questionnaire was used to conduct the study among 400 respondents in the public schools of the region. The said respondents were identified using stratified random sampling. The statistical tools used for data analysis were mean, pearson product-moment correlation, multiple regression analysis and structural equation modeling. The results showed a very high level of positive personality traits. While organizational commitment, work environment and core job characteristic received a high mean value. All latent exogenous variables have significant relationship with the endogenous variable core job characteristic. In addition, all exogenous variables significantly influence the core job characteristic. The core job characteristic of teachers is influenced by variables, positive personality traits, organizational commitment and work environment. Furthermore, the best-fit model is 5 which passed the criteria of indices since it apparently displayed all of its three indicators that remained viable to core job characteristic namely: skill’s variety, task identity, task significance, autonomy, and feedback. However, the model displayed only two out of its five indicators that remained viable on core job characteristic, namely, skill’s variety and task identity.

Human Resource Management, Technology Adaptation, and Environmental Policy: A Multi-Variable Study of MSME Entrepreneurship in Indonesia

This research explores the dynamics of Micro, Small, and Medium Enterprises (MSMEs) in Indonesia, focusing on the interplay between Human Resource Management (HRM), Technology Adaptation, Environmental Policy, and MSME entrepreneurship. Despite government support and encouragement, MSMEs face challenges, particularly in managing human resources effectively and adapting to technological advancements. The study investigates the impact of HRM practices, technology adaptation, and environmental policy on MSME success through the lens of entrepreneurship. Using quantitative research design and Structural Equation Modeling (SEM), the study analyzes data collected from a diverse sample of Indonesian MSMEs. The findings highlight the positive influence of effective HRM practices, technology adaptation, and environmental policy compliance on MSME entrepreneurship and success. The implications of the study suggest strategic considerations for entrepreneurs, policymakers, and stakeholders to enhance the growth and sustainability of MSMEs in Indonesia.

East African megafauna influence on vegetation structure permeates from landscape to tree level scales

African savanna elephants (Loxodonta africana) can substantially modify their habitat through their interactions with woody vegetation. Nonetheless, the scale, intensity and characteristics of these relations are not yet fully understood. Consequently, it is unclear how vegetation-megafauna interactions can be disrupted by external factors, such as land management. This study attempted to quantify and characterize structural changes in vegetation caused by elephants, from landscape to tree level scales. We applied multi-scale geospatial tools, including airborne (ALS) and terrestrial laser scanning (TLS), to address the following questions: (1) How do elephants shape landscape level vegetation structure in conservation areas? (2) Are the impacts of elephants evident on individual tree architecture? Our study area was located at the Taita Hills Wildlife Sanctuary in South-eastern Kenya. The occurrence of elephants was estimated using elephant observation records and proximity to elephant tracks. Landscape level structure was assessed using tree density maps calculated based on individually detected treetops from ALS data. Next, TLS measurements of 72 trees were processed using quantitative structural modelling to characterize their architecture. Our results demonstrate a widespread influence of elephants on both landscape and tree level structural characteristics. This influence was strongly mediated by management, as we observed differences in vegetation structure inside and outside conservation areas. Tree density was up to 42% lower (5.84 trees/ha) in conservation areas than in non-conservation areas (10.17 trees/ha). Trees were relatively larger with closer proximity to elephant tracks, while smaller trees were more often observed in areas further away from elephants. At an architectural level, trees closer to elephant tracks had lower ratio between the crown length and the tree height, demonstrating a substantial influence of elephants on the morphological characteristics of trees. Our results highlight the importance of accounting for vegetation fauna interactions when planning conservation areas in African savannahs.

WOOD-LEAF UNSUPERVISED CLASSIFICATION OF SILVER BIRCH TREES FOR BIOMASS ASSESSMENT USING OBLIQUE POINT CLOUDS

Abstract. Forests play a fundamental role in carbon stocking since about a third of the carbon dioxide produced by activities of human origin is absorbed by forests. Forest biomass is an essential indicator of carbon dioxide absorption, enabling an understanding the interaction between forest dynamics and climate change effects. However, biomass and wood material changes are challenging to quantify in forest stands. Nowadays, recent 3D remote sensing technologies, such as laser scanning systems, have allowed accurate measures of single trees. This study evaluates three approaches to classify wood and non-wood materials and quantify biomass based on LiDAR data, aiming at biomass change detection. Specifically, we propose an automated methodology for estimating the single tree-level biomass of a portion of forest monitored through a LiDAR oblique acquisition. The classification of wood and foliage points was performed with machine learning algorithms, while the tree modelling was conducted rigorously through a Quantitative Structure Model (QSM). The purpose of this study is to evaluate (1) two different unsupervised and one semi-supervised classification approaches for wood and foliage separation and (2) the accuracy of the biomass assessment performed on a QSM-based approach on innovative LiDAR acquisitions. The results are promising; the wood-leaf classification performs effectively in all 20 silver birches considered; as regards the biomass, when the noise is limited, it is estimated in a manner consistent with the reference values calculated using an appropriate allometric equation. Higher values are found mainly in dense undergrowth, which negatively affects the modelling of the tree. The research is ongoing, and further tests will be performed to generalize the methodology on different tree species, deepen the multitemporal variability, and improve the accuracy of the assessment.

Measuring academic performance among students during post-COVID-19 reopening through academic engagement and persistence: mediating role of psychological capital

Purpose This study examined the students' academic performance through psychological capital, academic engagement and academic persistence. It also investigated the function of psychological capital in mediating the relationship between academic engagement, persistence and performance.Design/methodology/approach The study utilized a quantitative method and structural equation modeling using PLS-SEM version 3. A total of 900 questionnaires were issued to Chinese university students, and 814 data were analyzed.Findings Findings suggest that academic engagement and persistence significantly and positively impact psychological capital. Psychological capital is also mediated between academic engagement, persistence and performance. Additionally, the study made several recommendations for upcoming researchers and industry professionals.Originality/value Analyzing the pupils' academic achievement after COVID-19 reopening as it indicates their attention and engagement in the study. Although previous studies explored students' academic performance regarding the post-COVID effect, the role of psychological capital and engagement in academia in the study has been studied in a post-COVID context.

Using repeat UAV-based laser scanning and multispectral imagery to explore eco-geomorphic feedbacks along a river corridor

Abstract. Vegetation plays a critical role in the modulation of fluvial process and morphological evolution. However, adequately capturing the spatial and temporal variability and complexity of vegetation characteristics remains a challenge. Currently, most of the research seeking to address these issues takes place at either the individual plant scale or via larger-scale bulk roughness classifications, with the former typically seeking to characterise vegetation–flow interactions and the latter identifying spatial variation in vegetation types. Herein, we devise a method which extracts functional vegetation traits using UAV (uncrewed aerial vehicle) laser scanning and multispectral imagery and upscale these to reach-scale functional group classifications. Simultaneous monitoring of morphological change is undertaken to identify eco-geomorphic links between different functional groups and the geomorphic response of the system. Identification of four groups from quantitative structural modelling and two further groups from image analysis was achieved and upscaled to reach-scale group classifications with an overall accuracy of 80 %. For each functional group, the directions and magnitudes of geomorphic change were assessed over four time periods, comprising two summers and winters. This research reveals that remote sensing offers a possible solution to the challenges in scaling trait-based approaches for eco-geomorphic research and that future work should investigate how these methods may be applied to different functional groups and to larger areas using airborne laser scanning and satellite imagery datasets.

Corporate social responsibility and millennial consumer loyalty: exploring their relationship regarding healthy eating in the fast food sector

The food industry has made substantial investments in the promotion of healthy eating as part of an active lifestyle. These actions are usually part of companies’ corporate social responsibility (CSR) strategies that have a dual purpose: social and business. CSR is built on a network of mutually beneficial relationships between a company and its stakeholders. Therefore, the positive perception of CSR initiatives has an influence on the trust and loyalty of stakeholders. Based on evidence about the effects of the perception of CSR on stakeholder behaviour and on company evaluation, this study proposes and tests a conceptual model of the relationship between CSR perception and customer loyalty in the context of a very important and specific topic and group: healthy eating and millennial consumers. The study employs a quantitative method and structural equation modelling (SEM) with data collected from 500 online surveys. The study also evaluates the influence of other variables: consumers’ interest in fast food companies’ CSR initiatives related to healthy eating (INTEREST) and CSR communication on healthy eating via social media (COMMUNICATION), but unlike previous research, it focuses on variables that can be conditioned by companies. The results confirm the relationship with respect to CSR in general terms, but do not do so in relation to healthy eating. In this case, influence is conditioned by moderating variables, which suggests that COMMUNICATION influences company evaluation only when customers have a prior interest in such initiatives and when correct CSR communication exists on social media, which also affects this relationship, although in a negative direction. This research supports the academic current that promotes CSR as an investment that benefits both the company and society.

Formation of political trust and support for local government actions during crisis: Hotel employees’ perspectives

PurposeThis study explores how institutional and cultural factors influence political trust among hotel employees and its impact on support for local government actions, with implications for hotel leadership and regulatory compliance.Design/methodology/approachEmploying a quantitative approach and structural equation modeling (SEM-PLS), the study integrates institutional and cultural theories of trust. Data were collected from 444 frontline hotel employees via mTurk in May 2021.FindingsThe research reveals insights into the significant role of institutional and cultural factors in shaping political trust among hotel employees. Moreover, it demonstrates a positive correlation between political trust and support for local government actions.Research limitations/implicationsThis research has limitations to acknowledge. The sample size may restrict generalizability, and data from May 2021 might not capture long-term trends. Furthermore, relying solely on quantitative data may overlook individual nuances and complexities.Practical implicationsHotel leadership can leverage these findings to prioritize building political trust among employees, leading to better support for government actions and regulatory compliance.Social implicationsFostering trust between hotel employees and governing bodies can foster more effective collaboration, benefiting the hotel industry and the broader community.Originality/valueThis research contributes to the existing body of knowledge by presenting a novel conceptual model that integrates institutional theory and cultural theory of trust to examine the formation of political trust in the context of hotel employees. The application of this model to the hospitality industry adds to the limited research available in this area.

Improving quantitative structure models with filters based on allometric scaling theory

Improving quantitative structure models with filters based on allometric scaling theory

A structural equation model of CFIR inner and outer setting constructs, organization characteristics, and national DPP enrollment

BackgroundThe National Diabetes Prevention Program (DPP) has made great strides in increasing accessibility to its year-long, evidence-based lifestyle change program, with around 3000 organizations having delivered the program. This large dissemination effort offers a unique opportunity to identify organization-level factors associated with program implementation and reach (enrollment) across diverse settings. The purpose of this study was to quantitatively examine the relationships among Consolidated Framework for Implementation Research (CFIR) Inner Setting and Outer Setting constructs and the implementation outcome of reach.MethodsThis study analyzed data from a 2021 cross-sectional online survey with 586 National DPP Staff (lifestyle coaches, master trainers, program coordinators) with information about their organization, implementation outcomes, and responses to quantitative CFIR Inner Setting and Outer Setting construct items. Structural equation modeling was used to test a hypothesized path model with Inner and Outer Setting variables to explore direct and indirect pathways to enrollment.ResultsThe CFIR items had good internal consistency and indicated areas of implementation strength and weakness. Eight variables included as part of the CFIR structural characteristics and one organization characteristic variable had significant direct relationships with enrollment. The length of delivery, number of lifestyle coaches, number of full-time staff, large organization size, and organizations delivering in rural, suburban, and/or urban settings all had positive significant direct relationships with enrollment, while academic organizations and organizations with only non-White participants enrolled in their National DPP lifestyle change programs had a negative association with enrollment.ConclusionsParticipant reach is an important implementation outcome for the National DPP and vital to making population-level decreases in diabetes incidence in the USA. Our findings suggest that to facilitate enrollment, program implementers should focus on organizational structural characteristics such as staffing. Strengths of this study include the use of adapted and newly developed quantitative CFIR measures and structural equation modeling. Health prevention programs can use the methods and findings from this study to further understand and inform the impact of organization factors on implementation outcomes.

The impact of Industry 4.0 capabilities on operational performance: the mediating effect of supply chain ambidexterity

PurposeThe current work sought to investigate the mediating effect of supply chain ambidexterity on the relationship between Industry 4.0 capabilities and operational performance of manufacturing firms in Jordan.Design/methodology/approachData collection was carried out through a survey with 253 respondents from manufacturing firms in Jordan through the first quarter in 2023. The quantitative approach and structural equation modeling (SEM) were applied to analyze the collected data. Dynamic capabilities view (DCV) theory was the adopted theoretical lens for this work.FindingsThe results demonstrated that Industry 4.0 capabilities positively and significantly affect exploration, exploitation and operational performance. In addition, the results confirmed that exploration and exploitation positively and significantly affect operational performance. Further, it is also found that exploration and exploitation in the supply chain positively and significantly mediate the relationship between Industry 4.0 capabilities and operational performance.Originality/valueThis study focuses on this gap to deepen the understanding of operational performance in a recent manufacturing environment under various factors and perspectives (Industry 4.0 capabilities and supply chain ambidexterity).

Determinan Intensi Berwirausaha Mahasiswa Pascasarjana IPB Pada Bidang Agribisnis

Increasing of population impacted to food needs and unemployment problem. so there is a solution to resolve with entrepreneurship. The aims of this study is to look the characteristics of respondents and the factors that influence the entrepreneurial intention of student at the Postgraduate School of Bogor Agricultural University (SPs-IPB) on agribusiness. The design of this study used cross sectional study. Respondent in this study are postgraduate student from magister program. The sampling technique used proportional stratified random sampling with 122 people. The analytical method used descriptive quantitative analysis and Structural Equation Modelling / SEM. The results showed that as (94%) of respondents have entrepreneurial intentions generally, (86.96%) of the respondents have the intention of entrepreneurship in agribusiness. The study found that entrepreneurial intention are influenced by subjective norm which is the influence of a number of parties that are considered important with regard to the behavior of entrepreneurs.

Assessing the Allometric Scaling of Vectorized Branch Lengths of Trees with Terrestrial Laser Scanning and Quantitative Structure Modeling: A Case Study in Guyana

Allometric scaling is closely related to the morphology, function and behavior of trees, which are of great significance to the study of ecology. However, most of the traditional allometric scaling studies used the scalar attributes of trees, without considering the 3D vector mode of tree growth. In order to investigate the allometric relationships between branch lengths in 3D vector mode, in this study, an accurate and detailed quantitative structure model was used to reconstruct tree architectures from 3D point cloud data collected by terrestrial laser scanning and extract the structural parameters of each branch (length, branching level and zenith angle). The standardized major axis was used to establish and analyze the scalar and vector allometric relationships between branch lengths. Our results show that at the same branching level and using the same allometric model, the scaling exponents between the lengths of branches and the lengths of cumulative child (descendant) branches (no matter whether the lengths are in scalar or vector form) are similar among trees, and there is no significant difference between the scaling exponents of most trees. And the scaling exponents between the lengths of the horizontal components of branches and the cumulative lengths of the horizontal components of the child (descendant) branches are much larger than those between the lengths of the vertical components of branches and the cumulative lengths of vertical components of the child (descendant) branches. At different branching levels, the scaling exponents between the lengths of branches and the cumulative lengths of descendant branches tend to decrease with the increase in the branching level. The allometric models in terms of the cumulative lengths of horizontal components of the child (descendant) branches and the allometric models in terms of the cumulative lengths of child (descendant) branches have similar model accuracy and scaling exponents. The study results of allometric relationships between tree branch lengths in 3D mode are of great importance for understanding the crown morphology and the branching rule, which is helpful to further understand the growth strategies and adaptation mechanisms of trees and explain the growth and development mechanisms of trees from a physiological perspective.

MEDIATING BRAND TRUST, BRAND ATTITUDE, BRAND PSYCHOLOGICAL OWNERSHIP ON CELEBRITY ENDORSERS TO BEHAVIOURAL INTENTION

The marketing type that is found on social media today is celebrity endorsement. To encourage consumer behavioural intention, luxury brand companies take several strategies, including using celebrity endorsers to introduce their brand and to build brand trust, brand attitude, and brand psychological ownership. This study aims to examine the influence of celebrity endorsers on behavioural intention through the mediation of brand trust, attitude, and psychological ownership. A total of 250 samples were determined by purposive sampling. This research used a quantitative approach and structural equation modelling (SEM) AMOS as a data analysis technique. The result showed a mediating effect of brand trust, attitude, and psychological ownership on the relationship between celebrity endorsers and behavioural intention.

Examining the Mediating Role of School Culture on the Relationship between Transformational Leadership, Teacher Commitment and Organizational Change in Elementary School

This study examines the mediating role of school culture on the relationship between transformational leadership, teacher commitment, and organizational change in elementary schools. This study used a quantitative Structural Equation Modeling approach to test the variable model. The subjects of this study were elementary school teachers in Surabaya city, with a total sample of 253. The research instrument used a 5 Likert scale and analyzed data using structural equation modeling. The results showed that transformational leadership and teacher commitment simultaneously and partially affect organizational change. Transformational leadership and teacher commitment also affect school culture. School culture played a role as a mediator in seeing the effect of teacher commitment on organizational change. Furthermore, school culture did not play a role as a mediator in measuring the effect of transformational leadership on organizational change.

Two phases of online food delivery app users’ behavior in Greater Jakarta during the second year of the COVID-19 pandemic: Perceptions of food safety and hygiene

Background: The ongoing COVID-19 pandemic affects several aspects of food safety and food delivery hygiene for online food delivery applications (OFDAs). Several previous studies conducted at various times during the COVID-19 pandemic have yielded interesting results. This study aimed to determine and analyze whether perceptions of food safety and food delivery hygiene are short-term and long-term predictors of behavioral intention to use OFDAs. Methods: A quantitative approach and structural modeling were used in this study. SmartPLS is used to analyze five direct and two mediating effects of the variables used in this study. The data sample consists of OFDA users in Greater Jakarta during the second year of the COVID-19 pandemic. Results: Perceived food safety has a significant effect on behavioral intention to use these applications but does not affect behavioral intention to continue using these applications. Perceived food delivery hygiene does not influence using these apps for either short-term or long-term behavioral purposes. Experience with these apps related to food safety and food delivery hygiene during a pandemic can be indicative of their long-term viability. The mediating effect of behavioral intention to use on behavioral intention to continue using these apps affects perceived food safety but not food delivery hygiene. Conclusion: By emphasizing vaccination and boosting against COVID-19, providing hand sanitizer, and preserving the cleanliness and integrity of food packaging, the findings of this study can be put into practice towards the sustainable usage of OFDAs.

Individual tree volume estimation with terrestrial laser scanning: Evaluating reconstructive and allometric approaches

Accurate estimates of above-ground tree biomass within forest inventories are essential for calibration and validation of biomass mapping products based on Earth observation data. Terrestrial laser scanning (TLS) enables detailed and non-destructive volume estimation of individual trees, which can be converted to biomass with wood basic density. Existing TLS-based approaches range from simple geometrical features to virtual 3D reconstruction of entire trees. Validating such approaches with weight measurements is a key step before the integration of TLS or other close-range technologies into operational applications such as forest inventories. In this study, we firstly evaluate individual tree volume estimation approaches based on 3D reconstruction through quantitative structure models (QSM) against destructive reference data of 60 trees and compare them to operational allometric scaling models (ASM). Secondly, we determine the explanatory power of TLS-derived geometric parameters regarding total wood, stem, coarse wood and fine branch volume. We observe similar accuracy in merchantable (¿7 cm) wood compartments for ASMs (NRMSE = 25 %) and QSMs (NRMSE = 29 %), with QSMs showing better results for broadleaves than conifers and generally overestimating fine branch volume. Feature selection shows that a combination of stem diameters and volume of convex hulls around tree crowns has the most potential to model the entire tree volume including branches, especially for conifers. In cases where the quality of available point clouds is insufficient for QSMs, 3D information can thus still be utilised by deriving geometric parameters. The integration of crown dimension parameters into new allometric models could substantially improve the estimation of branch wood volume.

Increasing Entrepreneurship through Strengthening Innovative and Organizational Culture

This study aims to analyze the relationship between student entrepreneurship and the variables of innovativeness and organizational culture. This study uses a quantitative survey method. Questionnaires were distributed via the Google Form application and the WhatsApp group. The research was conducted from October 2022 - February 2023 with 100 respondents from small business group MSME operational managers in Bogor Regency. Proportional random sampling techniques and using the Solvin formula were used in data collection. Data analysis techniques in quantitative research use structural equation models (SEM) and statistical software SmartPLS 3.2.9. The research results show a significant influence and positive trend between innovative variables and organizational culture on entrepreneurship. The practical implication of this research is that to increase entrepreneurship, it must increase the creative variables and corporate culture.