Structural Modeling Analysis Research Articles

The Effect of Tourism Restriction Policies and Ecology-Oriented Marketing Strategies on Reducing Over-Tourism and Tourist Experience in Indonesia

This research investigates the effectiveness of tourism restriction policies and ecologically oriented marketing strategies in addressing over-tourism and enhancing tourist experiences in Indonesia. A quantitative analysis was conducted using data collected from tourists visiting selected destinations in Indonesia. The measurement model assessment confirmed the reliability and validity of the constructs, while the structural model analysis revealed significant positive relationships between ecology-oriented marketing strategies and both reducing over-tourism and tourist experience, as well as between tourism restriction policies and these outcome variables. The findings highlight the importance of integrating marketing and policy interventions into destination management practices to achieve sustainable tourism development goals. By adopting a holistic approach, destinations can enhance visitor satisfaction, protect natural and cultural resources, and foster long-term sustainability.

Family-customer happiness and its impact on customer citizenship behavior: A study of parent–child consumption in robot restaurants

Academic research on ways to promote family consumers' happiness in technology-enabled service contexts is limited. Based on the value co-creation concept and emotional contagion theory, this study focuses on parent-child consumption and develops a theoretical model of the relationship between customer–robot interaction experience, family emotional bonding, customer happiness, and citizenship behavior in robot restaurants. Further insights into the model were obtained by content analysis of 374 online customer reviews, and the model was tested by a questionnaire survey of 515 family customers. The results of structural model analysis show that customer-perceived child delight and customer engagement in robot services have direct and indirect effects on customer happiness through the enhancement of family emotional bonding. Customer happiness positively affects customer citizenship behavior and mediates the relationship between family emotional bonding and customer citizenship behavior. The study provides guidance for using robotics to promote the happiness of customers and prosperity of restaurants.

Will we be capable? Creating and validating the AVACIE scale to evaluate pre-service teachers’ self-competence in assessing cyberbullying

ABSTRACT Future teachers need to be competent in supporting students and families to detect and cope with cyberbullying. The objectives of this study are to create and validate the AVACIE scale to evaluate future teachers’ self-competence. 332 university students from the Primary Education Teacher Training Degree were recruited. The AVACIE scale consists of four factors and a total of 14 items measured on a 10-point Likert scale. Internal consistency was confirmed by Cronbach’s alpha and McDonald’s omega. The validity of the scale was confirmed through CFA using the maximum likelihood robust method. Finally, multigroup analysis of structural equations models (SEM) was also included to ascertain the possible role of gender in the model. SEM’s goodness of fit was adequate for both genders, and significant differences were found in the correlation between factors. The AVACIE scale could provide a starting point for understanding how to approach university education to face of cyberbullying.

Angular Momentum Fine Structure in InP/ZnSe Quantum Dots.

There is a large experimental and theoretical literature on the angular momentum fine structure of the lowest energy exciton in InP-based quantum dots. This literature is highly contradictory, and no clear picture of the fine structure accounting for all these results is available. This paper presents a quantitative analysis of recently published luminescence anisotropy results and presents an analysis of the different proposed fine structure models that compares radiative lifetimes calculated from those models with experimental values. These analyses show that the lowest energy (dark) state is the mj = ±2 state and the lowest energy bright state is a vibronically allowed phonon level. The splittings between the ±2/±1L states and the ±1U/0U states are the same, about 28 meV. We also find that the manifold of J = 1 states is about 60 meV above the manifold of J = 2 states.

Fuzzy Interpretive Structural Modeling regarding Factors Affecting Employees’ Experience Management in Mashhad University of Medical Sciences

Background: Employees are considered internal customers of the organization, and today, employee’s experience has become a prominent topic in the field of human resources. This study aims to model the factors affecting employees’ experience management in Mashhad University of Medical Sciences using fuzzy interpretive structural modeling. Methods: This applied study was descriptive-analytical conducted in 2023. 10 faculty members, managers, and staff of Mashhad University of Medical Sciences were selected using a purposive sampling method. Interpretive Structural Modeling (ISM) questionnaire consisting of a 7x7 matrix was then given to them, and they were asked to find the contextual relationship between the variables based on the pairwise comparison scale. In the analysis section, fuzzy interpretive structural modeling and MICMAC analysis were used to structure and analyze the status of the factors. Results: 7 organized themes (organizational, physical environment, technological, job, managerial, cultural, and individual factors) were identified for employees’ experience in Mashhad University of Medical Sciences. Findings showed that cultural and managerial factors are at the lowest level of the structure and have more influence and less dependence. In other words, these are the most influential factors on employees’ experience. Job, technology, and organizational factors were placed at the second level. In contrast, individual and physical factors were at the highest level of the structure and had less influence and more dependence on other factors. Conclusion: The findings indicate that Mashhad University of Medical Sciences should focus on strengthening and improving cultural and managerial factors to improve employees’ experience. Additionally, attention to job, technology, and organizational factors, along with addressing individual employee’s needs and providing a favorable physical environment, are essential for employees’ effective experience management at the university. This study, by providing a comprehensive model of factors influencing employees’ experience, assists universities and other organizations in gaining a deeper understanding of this concept and developing effective strategies for its enhancement.

Unlocking circular supply chain 4.0: identifying key barriers through bibliometrics and TISM-MICMAC

PurposeThis paper examines the dynamic interplay between Circular Economy (CE) and Supply Chain (SC). Further, this paper develops a framework indicating the transition from conventional SC to SC 4.0. As it addresses the separate bodies of literature on CE and SC 4.0, the study attempts to bridge the gap by examining barriers to SC 4.0 adoption in CE.Design/methodology/approachThe article integrates bibliometric analysis with Total Interpretive Structural Modeling (TISM) and MICMAC analysis, thereby enriching the methodological rigour in investigating the barriers to SC 4.0 adoption within the CE context.FindingsThe paper provides insights into research trends, influential scholars, journals and prominent institutions through bibliometric analysis. Also, the findings identify four broad areas of driving, autonomous, linkage and dependent barriers to facilitate a comprehensive understanding of their impact and interdependencies.Research limitations/implicationsThe findings imply that effective policy interventions, enhanced management practices, and the adoption of technological innovations are essential for overcoming barriers to SC 4.0. The research recommends that stakeholders focus on fostering collaborative networks, building competencies in line with CE requirements, and leveraging big data for strategic supply chain decision-making.Originality/valueThis work contributes to the advancement of the circular digital supply field by consolidating research streams, uncovering innovation prospects, and shaping a well-informed research agenda. The distinct contribution lies in its categorization of these barriers into driving, autonomous, linkage, and dependent barriers, offering a novel perspective on the structural dynamics impeding the integration of SC 4.0 in CE.

Big data analytic capabilities, intrapreneurship, and service innovation behaviors: a moderated mediation model

ABSTRACT Building on resource-based theory, entrepreneurial orientation theory, and intrapreneurship knowledge spillover theory, this study examined the relationship between big data analytics capabilities and service innovation as mediated by intrapreneurship behavior and moderated by strategic renewal behavior. Data were collected from 442 employees at 33 five-star hotels in Turkey and analyzed using structural modeling analysis. The findings revealed that big data analytics capabilities positively affect service innovation both directly and via intrapreneurship behavior. Strategic renewal behavior positively moderated the positive relationship between big data analytic capabilities and intrapreneurship behavior. This indicates that the impact of big data analytic capabilities on service innovation is influenced by intrapreneurial behavior, and that this influence is strengthened by strategic renewal behavior, that is, the organization's ability to adapt its strategies and processes to incorporate new ideas and innovations.

Local structural modelling and local pair distribution function analysis for Zr–Pt metallic glass

In disordered glass structures, the structural modelling and analyses based on local experimental data are not yet established. Here we investigate the icosahedral short-range order (SRO) in a Zr–Pt metallic glass using local structural modelling, which is a reverse Monte Carlo simulation dedicated to two-dimensional angstrom-beam electron diffraction (ABED) patterns, and local pair distribution function (PDF) analysis. The local structural modelling invariably leads to the icosahedral SRO atomic configurations that are similarly distorted by starting from some different initial configurations. Furthermore, the SRO configurations with 11–13 coordination numbers reproduce almost identical ABED patterns, indicating that these SRO structures are similar to each other. Further local PDF analysis explicitly indicates the presence of the wide distribution of atomic bond distances, which is comparable to the global PDF profile, even at the SRO level. The SRO models based on the conventional MD simulation can be strengthened by comparison with those obtained by the present local structural modelling and local PDF analysis based on the ABED data.

Research on the Influencing Factors of Consumer Seafood Consumption Willingness in the Bohai Rim Area Based on Random Forest and Structural Equation Model

With the increasing prominence of environmental issues, the impact of nuclear pollution events on the marine ecological environment has attracted widespread concern. This study aims to explore the influencing factors of consumers' willingness to consume seafood in the Bohai Rim area when facing nuclear pollution events. By combining the use of random forest and structural equation modeling (SEM), this research conducted an in-depth analysis of the collected survey data. Initially, the random forest model was applied to rank the importance of satisfaction scale indicators, factor analysis was used to reduce the scale indicators to obtain factors affecting consumer satisfaction, and finally, the SEM model was employed to study the impact of various factors and indicators on consumer satisfaction, identifying the key factors affecting the willingness to consume prepared dishes. The study results show that consumers pay high attention to the origin, quality, and nutritional value of seafood, and these factors are proven to have a significant impact on consumption willingness through the measurement model. The structural model analysis reveals the importance of business services and product features in enhancing consumers' willingness to purchase. Additionally, the model fit indices indicate that the proposed model structure fits the actual data well. This study provides targeted marketing strategy recommendations for seafood suppliers to adapt to changes in consumer behavior under environmental changes.

Unveiling the adoption of metaverse technology in Bangkok metropolitan areas: A UTAUT2 perspective with social media marketing and consumer engagement

As the metaverse emerges as a transformative digital realm, its adoption and integration into various aspects of society are subjects of increasing scholarly and practical interest. This research investigated the factors influencing the intention to use metaverse technology (IU) in Bangkok metropolitan areas, with a particular focus on the extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) framework, alongside the role of social media marketing (SMM) and consumer engagement (CE). To verify behavioral intention, gender, age, and experience are proposed as moderating factors affecting the constructs on individuals’ behavioral intention of metaverse technology usage. The study collected data from 403 Thai internet users living in Bangkok and its surrounding areas using an online questionnaire. Subsequently, the PLS-SEM method was employed to validate the research model’s robustness and reliability. Structural model analysis revealed significant relationships among constructs, highlighting SMM’s direct influence on UTAUT2 (β = 0.787) and CE (β = 0.211). Serial mediation analyzes demonstrated a fully mediating role of SMM influencing UI through CE (β = 0.572) and UTAUT2 (β = 0.306). Moderation analyzes revealed the association between SMM and IU, mediated through UTAUT2 and CE, is moderated by age and experience. Additionally, the integration of PLS-SEM and artificial neural network (ANN) models underscored the accuracy and predictive power of the proposed framework. The findings of this study not only contribute to academic literature but also offer practical implications for marketers aiming to navigate the metaverse landscape effectively. They emphasize the pivotal role of UTAUT2 constructs and the subtle interplay between SMM, CE, and IU in shaping successful marketing strategies.

Analysis of Strategic Programs in Planning and Developing Cattle-Oil Palm Integration System

Abstract The cattle-oil palm integration system refers to a farming approach that involves the integration of the plantation sub-sector and the livestock sub-sector. It can be achieved by utilizing the vacant area beneath oil palm plants to graze beef cattle. The combination of oil palm and cattle production systems has significant social, economic, and ecological standpoints. The program strategy for establishing a cattle-oil palm integration system highlights the importance of institutional involvement in supporting a priority program that has achieved success in multiple areas. The study was conducted in the Tanah Bumbu District in the South Kalimantan Province. The place selection was conducted via purposive sampling, considering its potential as a prototype for combining cattle and oil palm development. This research aims to determine the optimal approach for implementing integrated systems in oil palm plantations of various scales. The research findings on the role of institutions in the integration system of oil palm and cattle are crucial for supporting prioritized programs that have been accomplished in multiple domains. The study employed Interpretative Structural Modelling (ISM) analysis to formulate a complex policy structure based on its constituent elements, establish a hierarchy of relationships among these elements, and classify them into four quadrants (autonomous, independent, dependent, and linkage). These include the social functions and the role of institutions in facilitating coordination among different entities. By understanding the significance of institutions, it becomes possible to effectively implement programs to enhance the development of integrated systems of cattle oil palm. The ultimate goal is to bring about positive changes in welfare, participation, trust, communication, and conflict resolution among oil palm smallholders and cattle breeders involved in the cattle-oil palm integration system. In economic function, institutions influence the fluctuations observed in income, production costs, and net profit for individuals engaged in the oil palm-cattle integration system, specifically oil palm smallholders and cattle breeders. Regarding the involvement of the environment, several repercussions arise, including alterations in soil quality, oil palm plantation productivity, biodiversity within ecosystems, greenhouse gas emissions, and deforestation within oil palm plantations engaged in the oil palm-cattle integration system. As a suggestion for achieving sustainability objectives in inclusive and sustainable palm oil plantations, it is advisable to prioritize establishing effective collaboration and partnerships among all relevant stakeholders, sharing expertise and information and the concerted effort to develop robust and mutually beneficial interconnections.

A comprehensive DEMATEL-ISM model-based safety analysis of the Lianghekou earth-rock dam

Earth-rock dam failures account for the largest proportion of all dam failure accidents. There are many factors inducing accidents in hydroelectric projects, and the relationships between them are intricate and complex. Therefore, it is crucial to explore the relationship between the influencing factors and identify the key factors leading to accidents. Through an analysis of the factors influencing earth rock dam failures, an index system for failure influence factors was constructed in this paper. Considering complexity and integration in influence factors analysis, a DEMATEL-ISM model (Decision Making Trial and Evaluation Laboratory; Interpretive Structural Model) analysis method was employed to examine the internal relationship among various factors based on the influence degree between them, and a MICMAC model (Matrix Impacts Cross-reference Multiplication Applied to a Classification methodology) was introduced to analyze the hierarchical relationship between various factors. The results showed that The results show that the seismic capacity and flood discharge capacity of the dam body are the key influencing factors of dam safety during the operation of the earth-rock dams. The comprehensive method employed in this paper overcame the complexity of evaluation results and was capable of more directly presenting relationships of factors. As suggested by these results, the analysis model employed in this paper has great significance for preparing a flexible-efficient management scheme for earth-rock dams.

What Controls Early Restraining Bend Growth? Structural, Morphometric, and Numerical Modeling Analyses From the Eastern California Shear Zone

AbstractRestraining bends influence topography, strike‐slip evolution, and earthquake rupture dynamics, however the specific factors governing their geometry and development in the crust are not well established. These relationships are challenging to investigate in field examples due to cannibalization and erosion of earlier structures with cumulative strain. To address this knowledge gap, we investigated the structure, morphology, and kinematics of 22 basement‐cored restraining bends on low net‐slip faults (<10 km) within the southern Eastern California shear zone (SECSZ) via mapping, topographic analyses, and 3D numerical modeling. The bends are self‐similar in form with most exhibiting focused relief between high‐angle bounding faults with an arrowhead shape in map view and a “whaleback” longitudinal profile. Slight changes in that form occur with increasing size indicating predictable growth that appears to be primarily controlled by local fault geometries (i.e., bifurcation angle), rather than the influence of fault obliquity relative to far‐field plate motion, due to inefficient slip‐transfer across interconnected irregularly trending closely spaced faults. Modeling results indicate that the self‐similar fault‐bound geometry of SECSZ restraining bends may arise from elevated shear strain at the outer corners of single transpressional fault bends with increasing cumulative slip. This, in turn, promotes growth of a new fault leading to efficient accommodation of local convergent strain via uplift between bounding faults. Finally, our results indicate that the kilometer‐scale restraining bends contribute minimally to regional contraction as they only penetrate the upper third of the seismogenic crust and are therefore also unlikely to impede large earthquake surface ruptures.

From click to fork: An empirical analysis of system and food quality influences in online meal kit consumption

This research explores the determinants and implications of brand attachment in the fast-growing online meal-kit industry. The objectives were to explore the components constituting the system and food quality, establish their impact on brand attachment, and examine the subsequent impact on consumer behavioral intentions. Utilizing big data analytics, the study analyzed real-time app content sourced from consumer reviews using a text mining technique and employed structural model analysis to validate a proposed model with five emerging factors from the consumer review data. The findings suggest that system quality parameters—perceived ease of use and perceived usefulness—significantly influenced food quality. Enhanced food quality cultivated brand love yet reduced brand hate. Notably, brand love and hate exhibited opposing correlations with negative electronic word-of-mouth and continuous usage intention. The outcomes secure crucial insights for ongoing engagement with online meal-kit services, significantly contributing to academic research and industry practice.

COVID-19 experiences and cruise booking behavior: Insights from YouTube viewers applying revised protection motivation theory

The purpose of this study is to examine the relationship between risk perceptions (crowding risk perception, health risk perception) and self-protective behavioral intentions and booking intention for COVID-19 using the theory of protection motivation previously verified in the study and to analyze the structural relationship between all variables. In particular, it was intended to investigate the specific impact relationship between COVID-19 risk perception, including crowding risk perception and health risk perception, and self-protective behavior and cruise booking intention. The survey was conducted on subscribers of travel YouTube channels with cruise video content, and the respondents actively responded by providing convenience store beverage coupons. In an online survey conducted for a month from January 15, 2023, 312 samples were collected from travelers who have experienced cruises in the past five years. SPSS and AMOS statistical programs were used, and first, frequency analysis and discriminant validity analysis were verified. In addition, the verification of structural relevance between variables was analyzed by the covariance-based structural equation modeling (CB-SEM). Demographic characteristics, confirmatory factor analysis, correlation analysis, and structural model analysis verified the hypothesis. Based on the results of the analysis, this study presents basic evidence useful for establishing management strategies for cruise companies.

The novel regulator HdrR controls the transcription of the heterodisulfide reductase operon hdrBCA in Methanosarcina barkeri.

Methanogenic archaea play a key role in the global carbon cycle because these microorganisms remineralize organic compounds in various anaerobic environments. The microorganism Methanosarcina barkeri is a metabolically versatile methanogen, which can utilize acetate, methanol, and H2/CO2 to synthesize methane. However, the regulatory mechanisms underlying methanogenesis for different substrates remain unknown. In this study, RNA-seq analysis was used to investigate M. barkeri growth and gene transcription under different substrate regimes. According to the results, M. barkeri showed the best growth under methanol, followed by H2/CO2 and acetate, and these findings corresponded well with the observed variations in genes transcription abundance for different substrates. In addition, we identified a novel regulator, MSBRM_RS03855 (designated as HdrR), which specifically activates the transcription of the heterodisulfide reductase hdrBCA operon in M. barkeri. HdrR was able to bind to the hdrBCA operon promoter to regulate transcription. Furthermore, the structural model analyses revealed a helix-turn-helix domain, which is likely involved in DNA binding. Taken together, HdrR serves as a model to reveal how certain regulatory factors control the expression of key enzymes in the methanogenic pathway.IMPORTANCEThe microorganism Methanosarcina barkeri has a pivotal role in the global carbon cycle and contributes to global temperature homeostasis. The consequences of biological methanogenesis are far-reaching, including impacts on atmospheric methane and CO2 concentrations, agriculture, energy production, waste treatment, and human health. As such, reducing methane emissions is crucial to meeting set climate goals. The methanogenic activity of certain microorganisms can be drastically reduced by inhibiting the transcription of the hdrBCA operon, which encodes heterodisulfide reductases. Here, we provide novel insight into the mechanisms regulating hdrBCA operon transcription in the model methanogen M. barkeri. The results clarified that HdrR serves as a regulator of heterodisulfide reductase hdrBCA operon transcription during methanogenesis, which expands our understanding of the unique regulatory mechanisms that govern methanogenesis. The findings presented in this study can further our understanding of how genetic regulation can effectively reduce the methane emissions caused by methanogens.

Implementation of two policies in physical education in indonesia: structural equiting model analysis

Implementation of two policies in physical education in indonesia: structural equiting model analysis

Exploring factors influencing the acceptance of ChatGPT in higher education: A smart education perspective

AI-powered chatbots hold great promise for enhancing learning experiences and outcomes in today's rapidly evolving education system. However, despite the increasing demand for such technologies, there remains a significant research gap regarding the factors influencing users' acceptance and adoption of AI-powered chatbots in educational contexts. This study aims to address this gap by investigating the factors that shape users' attitudes, intentions, and behaviors towards adopting ChatGPT for smart education systems. This research employed a quantitative research approach, data were collected from 458 of participants through a structured questionnaire designed to measure various constructs related to technology acceptance, including perceived ease of use, perceived usefulness, feedback quality, assessment quality, subject norms, attitude towards use, and behavioral intention to use ChatGPT. Structural model analysis (SEM) Statistical techniques were then utilized to examine the relationships between these constructs. The findings of the study revealed that Perceived ease of use and perceived usefulness emerged as significant predictors of users' attitudes towards ChatGPT for smart education. Additionally, feedback quality, assessment quality, and subject norms were found to positively influence users' behavioral intentions to use ChatGPT for smart educational purposes. Moreover, users' attitudes towards use and behavioral intentions were significantly proved for the actual adoption of ChatGPT. However, a few hypotheses, such as the relationship between trust in ChatGPT and perceived usefulness, were not supported by the data. This study contributes to the existing body information systems applications for the determining factor of technology acceptance in smart education context.

The Impact of Quantitative Easing on Stock Prices in the U.S. Stock Market - Structural VAR Model Analysis

In an effort for future investment implications, the current study examined the relationship between historical Quantitative Easing (QE) programs and the stock market. This study analyzed weekly basis data in the United States between 2007 and 2023. Through a Vector auto-regression (VAR) model, a significant rise following a quick drop in stock prices to a positive shock in QE was discovered, indicating lagged response. Further robustness check proved the validation of relationship, by sectioning the whole data set into 4 periods corresponding to four QE programs, except relatively insignificant effects in QE2 and QE3 periods. These lagged responses were pointed out firstly in this paper and connected with policy motivations and contemporaneous economy environment across programs. The findings may enable investors to anticipate market movements and generate respectable returns in the event of such unconventional money shocks.

Efficient Biodegradation of the Neonicotinoid Insecticide Flonicamid by Pseudaminobacter salicylatoxidans CGMCC 1.17248: Kinetics, Pathways, and Enzyme Properties.

Nitrile-containing insecticides can be converted into their amide derivatives by Pseudaminobacter salicylatoxidans. N-(4-trifluoromethylnicotinoyl) glycinamide (TFNG-AM) is converted to 4-(trifluoromethyl) nicotinoyl glycine (TFNG) using nitrile hydratase/amidase. However, the amidase that catalyzes this bioconversion has not yet been fully elucidated. In this study, it was discovered that flonicamid (FLO) is degraded by P. salicylatoxidans into the acid metabolite TFNG via the intermediate TFNG-AM. A half-life of 18.7 h was observed for P. salicylatoxidans resting cells, which transformed 82.8% of the available FLO in 48 h. The resulting amide metabolite, TFNG-AM, was almost all converted to TFNG within 19 d. A novel amidase-encoding gene was cloned and overexpressed in Escherichia coli. The enzyme, PmsiA, hydrolyzed TFNG-AM to TFNG. Despite being categorized as a member of the amidase signature enzyme superfamily, PsmiA only shares 20-30% identity with the 14 previously identified members of this family, indicating that PsmiA represents a novel class of enzyme. Homology structural modeling and molecular docking analyses suggested that key residues Glu247 and Met242 may significantly impact the catalytic activity of PsmiA. This study contributes to our understanding of the biodegradation process of nitrile-containing insecticides and the relationship between the structure and function of metabolic enzymes.