Structural Modeling Research Articles

Two heads are better than one even within government bureaucracy: how does an inter-departmental network evolve?

ABSTRACT Inter-departmental collaborative networks can contribute to creative ideas, spanning and crossing solid boundaries resulting from formal specialization and departmentalization. This study gives an opportunity to understand how inter-departmental collaborative networks can be formed and persisted. Even though ties among government departments appeared to be influenced by vertical functional coordination, building mechanisms of bonding and bridging nature of networks can still work within government bureaucracy like other networks. Thus this study explores how an inter-departmental collaborative network is formed and persisted, adopting the structural temporal exponential random graph model (STERGM). Findings show that bonding networks serve to elucidate the mechanisms through which actors maintain existing relationships, whereas bridging networks helps to explicate the processes that underlie the identification of new collaboration partners. It is suggested that bonding and bridging networks might seem contradictory at first glance but rather complementary.

The Cycle of Violence: Childhood Abuse, Illicit Drug Use and Adult Intimate Partner Violence Perpetration

ABSTRACTThe evidence consistently suggested a link between childhood abuse and violence perpetration in adulthood. However, the mechanism underlying the relationship between childhood abuse and adult intimate partner violence perpetration was still inadequately explored. In addition, the findings from existing research on gender disparities in the cycle of violence remain highly contentious. This study sought to investigate the correlation between childhood abuse and adult intimate partner violence perpetration from a life‐course perspective, while also exploring the mediating role of illicit drug use and examining gender disparities. A sample comprising 4822 participants (mean age = 28.99 years, SD = 1.77) was derived from Wave IV of the National Longitudinal Study of Adolescent to Adult Health (Add Health). Data analysis employed structural equation modelling (SEM), which encompassed four primary components: measurement model, structural model, bias‐corrected bootstrapping analysis and multigroup analysis. Childhood abuse demonstrated a positive correlation with adult intimate partner violence perpetration. Moreover, the mediating effect of illicit drug use was observed in the relationship between childhood abuse and adult intimate partner violence perpetration. Furthermore, females exhibited a greater propensity to engage in illicit drug use following childhood abuse. This study has not only enhanced our understanding of the underlying mechanisms connecting childhood abuse to violence perpetration in adulthood but also carries implications for both policy and practice.

A Comprehensive and Structured Maturity Model for Measuring AI Adoption Levels in Industry 4.0

Industry 4.0 is driving significant transformations, even in complex and uncertain industrial environments. This concept represents an innovation strategy aimed at redefining the manufacturing sector, enhancing global competitiveness through cost reduction, more agile processes, and superior product quality. Concurrently, Artificial Intelligence (AI) is at the forefront of a profound shift in organizational management and operations, reshaping professional routines and redefining society's interaction with technology. The increasing complexity of business environments, particularly the inherent challenges within industrial sectors, alongside continuous technological advancements, establishes AI as a critical tool not only for fostering innovation but also for optimizing efficiency and enhancing competitiveness across all organizational domains. In this context, this study introduces a structured model grounded in the theoretical exploration of Industry 4.0 maturity models to assess the current maturity levels of AI utilization in the industry. Thus, this work presents the development of a standard for measuring AI adoption levels in Industry 4.0. This index will illuminate companies’ readiness and proficiency in integrating AI into both daily operations and strategic processes. Through the continued application of this tool, companies will also gain insights into their growth across the evaluated domains.

How Valid Is Bandura’s Social Cognitive Theory to Explain Physical Activity Behavior?

(1) Background: Although social cognitive theory (SCT) has been widely tested and applied in numerous interventions aimed at optimizing physical activity behavior, the complete theory has rarely been tested in its entirety. Only selected elements have been tested, and specific samples, some of them pathological, have been studied rather than the general population, for whom a lack of physical activity is a huge problem. The present study addresses these two research gaps and tests the tenability of the theoretical assumptions of SCT to explain physical activity behavior in the general population. (2) Methods: A total of 194 German adults (109 male, 85 female) with a mean age of 26.03 years (SD = 10.33) completed two validated questionnaires concerning their expressions on SCT components (t1) and their physical activity (t2). SCT was modeled using a structural equation model with latent variables. (3) Results: The results showed the very good fit of the structural model, indicating that the theoretically stated relations between the constructs in SCT seem to be corroborated, despite some paths seeming to be more important than others. (4) Conclusions: The use of SCT to explain and predict behavior can be seen as justified, even though it once again appears that some aspects (i.e., self-efficacy) are more crucial than others.

Mapping the two decades of Islamic marketing research using bibliometric analysis and novel machine learning topic modeling

Purpose This study aims to systematically assess and map the evolution, themes and trends within Islamic marketing research, with a focus on identifying areas of high growth potential and guiding future research directions. Design/methodology/approach Using a bibliometric analysis and advanced structured topic modeling (STM) techniques, this research analyzes Islamic marketing studies published between 2000 and 2024. The comprehensive database search, centered on Scopus-listed publications, provides a macroscopic view of the field’s development over the past two decades. Findings This study reveals significant insights into the field of Islamic marketing, including the identification of key research themes, the growth in literature and geographical hotspots of scholarly activity. Emerging trends suggest a growing focus on consumer behavior, brand loyalty, Halal certification and ethical marketing practices. Research limitations/implications This research is limited by its reliance on the Scopus database for source materials, and by focusing primarily on English-language publications. These constraints may have excluded relevant research in other languages or published in nonindexed formats. Practical implications This study offers valuable insights for marketers, businesses and policymakers aiming to engage the Islamic market. Understanding the dynamics of Islamic marketing can help in developing strategies that align with Muslim consumers’ values and preferences. Originality/value This research contributes to the Islamic marketing literature by using bibliometric analysis and STM, offering a unique, comprehensive overview of the field’s evolution, trends and future directions. It underscores the importance and growth of Islamic marketing as an independent academic discipline.

УПРАВЛЕНИЕ ТЕХНОЛОГИЧЕСКИМ ПРОЦЕССОМ КОПЧЕНИЯ РЫБНОЙ ПРОДУКЦИИ НА ОСНОВЕ ОЦЕНКИ ЕЕ КАЧЕСТВА

The purpose of the study is a control system for the technological process of smoking fish products based on instrumental assessment of its quality. The object of research is the technological process of smoking fish products. Theoretical and practical research was carried out on the basis of the department of Management of Technical Systems of the Federal State Budgetary Educational Institution of Higher Education Dalrybvtuz (Vladivostok, Primorsky Region). Organoleptic evaluation scales were built according to the recommendations of GOSTISO 11036-2017 “Organoleptic analysis. Methodology. Characteristics of the structure". Models were built using IDEF0 methodology tools. Organoleptic and instrumental methods for assessing the quality of smoked fish products, methods of structural and functional modeling of processes were used. Research was carried out in several stages: development of a methodology for measuring the color characteristics of smoked fish products, identification of ranges of values of the color characteristics of smoked fish products, development of a model for controlling the technological process of smoking fish products, development of a model for controlling the technological process of smoking fish products, development of a control system for the technological process of smoking fish products. The results of the study made it possible to develop patent № 217961 “Device for controlling the readiness of smoked fish products”, priority date – 12/16/2022. The developed method can serve as the basis for automation of both developed and existing smoking equipment. Its use minimizes the subjectivity of organoleptic methods for monitoring the readiness of smoked fish products, optimizes the duration of the process of processing fish raw materials with smoking means and thereby the energy consumption of the technological process. Further development of this research is possible by improving the data analysis stage at the stage of quality control of smoked fish products using a neural network, which, by analyzing color characteristics data, will offer the operator to vary the ranges of color characteristics values. The relevance of the proposals of a recurrent neural network can be realized using Markov chains.

Dynamic evolution characteristics of meso-structural mechanics performance of coal measure mudstone

Mudstone has peculiar structural properties, which have a significant impact on its strength, deformation, and other characteristics. However, there are few reports on the impact of structural properties on its yield characteristics. For the structural properties of hydrous mudstone on the yield characteristics during isotropic loading, a multifunctional triaxial apparatus was used as a research tool to conduct isotropic loading tests on four types of hydrous mudstone samples. With CT (computerized tomography) technology, the real-time dynamic scanning of mudstone samples is carried out after deformation stabilization, and the macroscopic mechanical indicators are connected with the microscopic scanning data to clarify the structural evolution law of mudstone during the loading process. The results indicate that based on the CT number (Me) reflecting the density of coal in different regions, the variation law of coal structure in resisting external loads during the loading process was explained. Before yielding, the CT number Me increases slowly, but after yielding, Me shows a linear and rapid growth trend. The change of Me values also clearly reflects the yield behavior and structural damage evolution law of mudstone loaded with different water contents. The smaller the moisture content of the mudstone sample, the greater the stress at the mudstone yields, and the structural influence of mudstone on its mechanical deformation characteristics is relatively small, but it has a strong effect on resisting external loads. The research results can provide reference for further establishing structural constitutive models of hydrous mudstone.

Spatio-temporal modelling of extreme low birth rates in U.S. counties

The continuous declining rate of birth may cause severe worldwide problems, including population ageing and demographic imbalance. This paper aims to identify the geographic disparities and potential influential factors of the extreme downward excess of birth rates in the U.S. at the county level from 2003 to 2020. The innovative Bayesian generalized Pareto (GP) quantile regression model is employed for analysing the spatiotemporal pattern of stressful low birth rate and its association with socioeconomic, demographic, and meteorological factors. The optimal stochastic partial differential equation and autoregressive model of order one (SPDE-AR(1)) spatiotemporal structured model is selected based on common Bayesian criteria and scaled threshold weighted continuous ranked probability score, indicating apparent spatial unbalance and deteriorating tendency of falling birth rate. The findings show that elderly, highly educated population structure, city-developed situation, average birth weight, and average age of mother have a significant impact on the stressful downward excess of birth rate, particularly in examples of Charlotte, Sarasota, Collier counties in Florida, and Marin, Santa, Cruuz, San Mateo in California. Conversely, the increasing female proportion and GDP per capita can alleviate the declining birth rate pressure. Our methodology is productive for analysing extreme population stress including but not limited to birth weight and cognitive impairment.

Responsive Magnetic Polymer Nanocomposites through Thermal-Induced Structural Reorganization.

Polymer nanocomposites (PNCs), which feature a hybrid network of soft polymers filled with nanoparticles, hold promise for application in soft robots due to their tunable physiochemical properties. Under certain environmental conditions, PNCs undergo stimuli-responsive structural rearrangement and transform the energy of the ambient environment into diverse uses, for example, repairing the injuries and reconfiguring the shapes of the materials. We develop PNCs with the ability of thermal-responsive restructuring by the stepwise assembly of functional components, including magnetite nanoparticles, silylated cellulose, and polydimethylsiloxane. We investigate the dynamic changes of the nano- and submicron structure of the magnetic PNCs upon the stimulation of heating based on a combined analytical approach: using dynamic mechanical analysis to interpret the viscoelastic properties of the PNC and in situ small-angle X-ray scattering to quantify the clustering of NPs. Based on these results, we formulate a structural model for the heating-induced evolution of the nano- to submicrometer assemblies in the magnetic PNC. Moreover, thermal-induced restructuring of magnetic PNCs leads to additional favorable functions, such as the abilities of healing, welding, reprocessing, and responses to photo and magneto stimuli. Our design provides a versatile means to develop responsive PNCs for applications in soft robots, sensors, and actuators.

Identifying key drivers of supply chain resilience in Indian pharmaceutical industry for enhanced export performance

Purpose This paper aims to explore the key drivers of a resilient supply chain for the Indian pharmaceutical industry for enhanced and sustainable export pursuits in a disruptive business time. Design/methodology/approach This study literarily identifies the key drivers of supply chain resilience in the Indian pharmaceutical industry and methodologically appraises, analyzes and assesses them to derive a structural model that catalytically acts as facilitators and drivers for enhanced export performance. By reviewing relevant literature, it identifies research and development (R&D), procurement and sourcing, manufacturing, distribution and reverse logistics factors. It collects Likert scale feedback from stakeholders and probes interrelationships among them in achieving the enhanced export performance of India’s pharmaceutical sector. Findings The results lucidly identify the key enablers affecting the export performance of India’s pharmaceutical sector. These primarily include developing excellence in manufacturing, reverse logistics and distribution. Furthermore, sourcing and R&D are the antecedents of manufacturing expertise, catalytically contributing to improved export outcomes. Based on the derived structural model, the interrelationships are evaluated to explore causal links in achieving supply chain resilience and simultaneously elucidating the managerial and socio-economic interventions. Originality/value Narrating the results, this paper scholarly identifies the key drivers that need to be factored in for enhanced export outcomes of India’s pharmaceutical sector. The paper explains how to achieve supply chain resilience for export performance in India’s pharmaceutical sector.

Measuring Saudi Arabian Students' Engagement in Synchronous Online Learning of Chinese as a Foreign Language

ABSTRACTBackgroundStudent engagement has been conceptualised and operationalised in various learning environments. However, there is currently a lack of established scales to measure student engagement in synchronous online learning. One possible reason is the existence of the conceptual and structural ambiguity regarding student engagement.ObjectiveWith its context situated in Saudi Arabian students' synchronous online learning of Chinese as a foreign language (L2 Chinese), this study attempts to find out the best representation and measure of synchronous online engagement based on four competing statistical modelling methods, including confirmatory factor analysis (CFA), exploratory structural equation modelling (ESEM), bi‐factor CFA (B‐CFA) and bi‐factor ESEM (B‐ESEM).MethodsA total of 167 Saudi Arabian students voluntarily participated in this online questionnaire‐based study. A 19‐item online questionnaire was adaptively developed to measure students' engagement in synchronous online learning of L2 Chinese from behavioural, cognitive, affective and social dimensions. CFA, ESEM, B‐CFA and B‐ESEM were employed to determine the optimal structure model for representing students' synchronous online engagement in L2 Chinese learning.Results and ConclusionThe results revealed that the B‐ESEM model was the best structure model for both measuring and accounting for the generality and specificity of students' engagement in synchronous online learning of L2 Chinese. More specifically, student online engagement was found to be a general unity with four distinctive subdimensions including behavioural, cognitive, affective and social engagement. This study not only reconciles the construct inconsistency of student engagement in the literature from the synchronous online learning perspective but also provides an optimal representation for measuring students' synchronous online engagement in L2 learning.

The Competitive Conduct of Consumer Cooperatives

ABSTRACTConsumer cooperatives are firms owned by their customers. Although their organizational form should commit these firms not to exploit their market power, in practice, weak governance may allow managers to pursue other objectives. Using data and a structural model, we test whether consumer cooperatives in the Italian supermarket industry act as profit‐maximizing firms. We find no significant deviations from profit maximization. Based on a counterfactual exercise, even a mild degree of internalization of consumer welfare by the cooperatives that we study would yield consumer welfare gains comparable to the regulatory advantages they enjoy.

Effective integration and models of information: lessons from integrative structure modeling

Integrative structure modeling is a method for using information from multiple sources to compute structural models of biomolecular systems. It proceeds via four steps: (i) defining the model representation, which determines the variables whose values will be computed; (ii) constructing a function for scoring alternative models according to how well they accommodate input information; (iii) searching a space of candidate models for acceptable models; and (iv) analyzing acceptable models to evaluate their fit with input information. These steps are iterated until a model adequate for addressing biological questions is found. In this paper, we draw lessons from integrative modeling about effective integration and about modeling. We describe what it means to integrate information from multiple sources: Integration amounts to distributing information among the four steps of integrative modeling. Theory and data alike can be sources of information; this process thus generates models of information, rather than models of theory or models of data. We then propose heuristics for distributing information and designing multiple iterations of modeling. Effective iteration requires prioritizing the most reliable information and minimizing the time required to obtain an adequate model. Rather than being constructed from theory and assessed using data, models are constructed from any available information and assessed in a coherentist manner.

Understanding the role of the Colombian news media in a peace process during crisis times: The 2015 escalation of the conflict

This article contributes to the understanding of the role of the media in peace processes. By applying Wolfsfeld’s politics–media–politics model, the author assesses the role that the Colombian media played at the moment of the worst escalation of the conflict – in 2015 – during the peace negotiation (2012–2016) between the Colombian government and FARC. He does this by drawing upon a triangulation of methods that combines Structural Topic Modelling on 17,688 news articles, thematic analysis (n = 146), and interviews (n = 26) with politicians and journalists. Findings show that the Colombian media considerably amplified the escalation of the conflict and provided a pessimistic narrative with regard to the future of the negotiations. Importantly, the news media embraced an elite-driven approach to report on the events: they tended to deem only FARC accountable for the loss of trust around the negotiations during the crisis (although the government also committed violent attacks). This shows that the news media sided with the government’s communication strategy which aimed to make FARC politically accountable for the crisis. In the end, the crisis reached a positive outcome: an agreement to de-escalate the conflict was reached after the government publicly threatened FARC to end the negotiations in its first public interview. Considering these findings, this article argues that the news media intervened by amplifying the crisis, worsening the political atmosphere of the negotiations and pressuring both delegations to come to an agreement to change the approach of negotiating amidst the conflict.

Identifying natural inhibitors against FUS protein in dementia through machine learning, molecular docking, and dynamics simulation

Dementia, a complex and debilitating spectrum of neurodegenerative diseases, presents a profound challenge in the quest for effective treatments. The FUS protein is well at the center of this problem, as it is frequently dysregulated in the various disorders. We chose a route of computational work that involves targeting natural inhibitors of the FUS protein, offering a novel treatment strategy. We first reviewed the FUS protein's framework; early forecasting models using the AlphaFold2 and SwissModel algorithms indicated a loop-rich protein—a structure component correlating with flexibility. However, these models showed limitations, as reflected by inadequate ERRAT and Verify3D scores. Seeking enhanced accuracy, we turned to the I-TASSER suite, which delivered a refined structural model affirmed by robust validation metrics. With a reliable model in hand, our study utilized machine learning techniques, particularly the Random Forest algorithm, to navigate through a vast dataset of phytochemicals. This led to the identification of nimbinin, dehydroxymethylflazine, and several other compounds as potential FUS inhibitors. Notably, dehydroxymethylflazine and cleroindicin C identified during molecular docking analyses—facilitated by AutoDock Vina—for their high binding affinities and stability in interaction with the FUS protein, as corroborated by extensive molecular dynamics simulations. Originating from medicinal plants, these compounds are not only structurally compatible with the target protein but also adhere to pharmacokinetic profiles suitable for drug development, including optimal molecular weight and LogP values conducive to blood-brain barrier penetration. This computational exploration paves the way for subsequent experimental validation and highlights the potential of these natural compounds as innovative agents in the treatment of dementia.

Evaluación del bootstrapping en la competitividad de las empresas exportadoras

This investigation article presents the result of a scientic research carried out to the Exporting Companies of theAgricultural Sector in the state of Michoacan. Its general objective is to determine the interrelationships betweenthe critical variables that dene the International Competitiveness of companies that export agriculturalproducts to the United States market, located in the state of Michoacan. A theoretical review was made, whichidentied the variables -quality, price, training, indices, and indicators that were integrated into a questionnairecomposed of 38 items and applied to the identied exporting companies in the sector. Once the information wasprocessed, different statistical techniques were used, and with the results obtained a Structural Model wasidentied that describes how these variables are interrelated, based on the Partial Least Square ModelingStatistical Technique (PLS) and the Bootstrapping model. After applying the questionnaire to agriculturalexporting companies, the processing of the data of each of the surveyed companies was continued, throughparametric statistics and the application of variance correlation.

First-Principles Study of Mechanical Properties of Pb(ZrxTi1−x)O3 in the Cubic and Tetragonal Phase

In this study, we employed the first-principles method based on density functional theory to calculate the elastic constants, bulk modulus, shear modulus, Young’s modulus, Poisson’s ratio, and density of states for both cubic and tetragonal phases of Pb(ZrxTi1−x)O3. The structural model of Pb(ZrxTi1−x)O3 was established using the virtual crystal approximation (VCA). Our results demonstrate that the VCA-calculated properties are in excellent agreement with other theoretical predictions and experimental data. As the Zr content increases, the lattice constants of both cubic and tetragonal Pb(ZrxTi1−x)O3 increase, while the c/a ratio initially decreases and subsequently increases. Both cubic and tetragonal Pb(ZrxTi1−x)O3 satisfy the Born stability criteria, indicating mechanical stability. For the cubic phase, the elastic constants, bulk modulus, and shear modulus decrease with increasing Zr content. In contrast, for the tetragonal phase, the elastic and shear moduli exhibit a non-monotonic trend, peaking at a Zr content of 0.5, where Pb(Zr0.5Ti0.5)O3 demonstrates superior mechanical properties. A comparative analysis reveals that as Zr content increases, the cubic phase exhibits enhanced structural resilience, greater electronic structure stability, and increased anisotropy. These characteristics make cubic Pb(ZrxTi1−x)O3 more suitable for advanced manufacturing techniques such as additive manufacturing, offering enhanced design flexibility for ferroelectric materials.

Hubungan Penataan Tempat Duduk Siswa Terhadap Efektifitas Belajar Siswa SMK Negeri 1 Ngasem

The arrangement of seating in the classroom has an important role in increasing the effectiveness of student learning, especially in the Vocational High This study aims to explore the relationship between seating arrangement and student learning effectiveness. Using the interview method, this study collected data from students and teachers regarding the impact of the U-Shape and Cluster structuring models. The results of the study showed that the U-Shape arrangement increased student engagement, focus, and interaction with the teacher, while the Cluster arrangement supported collaboration and comfort in group work. Students also recommend a combination of the two models to create a more optimal learning environment. These findings emphasize the importance of considering seating arrangement as a strategic factor in the effective learning process in vocational schools.School (SMK) environment such as SMK Negeri 1 Ngasem.

Three-Dimensional Modelling Approach for Low Angle Normal Faults in Southern Italy: The Need for 3D Analysis

This paper presents three 3D reconstructions of different analogue models used to reproduce, interpret, and describe the geological setting of a seismogenic area in Southern Italy—the Messina Strait. Three-dimensional analysis is a technique that allows for less sparse and more congruent and coherent information about a study zone whose complete understanding reduces uncertainties and risks. A thorough structural and geodynamic description of the effects of low-angle normal faulting in the same region through analogue models has been widely investigated in the scientific literature. Sandbox models for fault behaviour during deformation and the effects of a Low Angle Normal Fault (LANF) on the seismotectonic setting are also studied. The deformational patterns associated with seismogenic faults, rotational behaviour of faults, and other related problems have not yet been thoroughly analysed. Most problems, like the evolution of normal faults, fault geometry, and others, have been cited and briefly outlined in earlier published works, but a three-dimensional approach is still significant. Here, we carried out a three-dimensional digital model for a complete and continuous structural model of a debated, studied area. The aim of this study is to highlight the importance of fully representing faults in complex and/or non-cylindrical structures, mainly when the shape and dimensions of the fault(s) are key parameters, like in seismogenic contexts.

Navigating the Future: Examining Sustainable and Resilient Drivers Shaping the Integration of Crowdshipping in E‐Commerce Logistics

ABSTRACTThe last mile is often subjected to unique challenges such as congested urban areas, unpredictable customer availability and the need for personalized services. To address these complexities, and to be competitive in the market, companies are increasingly turning towards innovative solutions. One such innovative solution is crowdshipping (CS). The concept of CS was first introduced by Walmart in 2013, where store customers may act as crowdshippers and fulfill the demands of online retailers or shops by transporting packages on their way home with guaranteed compensation. To understand the factors influencing CS and its potential to motivate logistics firms for delivery, this research work determines the 20 key sustainable and resilient factors affecting the adoption of CS in the e‐commerce logistics sector. Furthermore, the Neutrosophic Best‐Worst Method (NBWM) is employed to prioritize these factors, followed by the application of Neutrosophic Interpretive Structural Modeling (NISM) with cross‐impact matrix multiplication applied to classification (MICMAC) analysis to assess the interrelationships amongst the factors. The results of the NBWM reveal that technology for the successful implementation of CS, rating and reward system, delivery cost–time efficiency, CO2 emissions and service quality are the top five highly weighted factors. The results of NISM dictate the technology for the successful implementation of CS, integration of CS with the mainstream (operations research models), government interventions and the usage of back‐up drivers as the factors with the highest driving power. The proposed NBWM and NISM give direction to practitioners and policy managers in planning sustainable and resilient strategies for addressing CS implementation factors in the e‐commerce logistics sector. Further, competent strategies can be developed by the managers based on the prioritization and the driving and dependence power of CS adoption factors.