Modeling Approach Research Articles

Can logistics enterprises improve their competitiveness through ESG in the context of digitalization? Evidence from China

PurposeThis investigation endeavors to examine the routes by which environmental–social–governance (ESG) performance influences the competitive landscape for logistics enterprises, with a particular emphasis on the function of digitalization in this complex process. The research underscores the significance of the ESG context in the realm of digitalization, providing valuable insights into its impact on the overall competitiveness of logistics enterprises.Design/methodology/approachThis research gathers information from a total of 90 logistics enterprises that are publicly traded on the Shanghai and Shenzhen A-share stock markets for analysis and model testing. Due to the multiple pathways of influence and the constrained size of the sample, it has been decided that the Piecewise structural–equation–modeling (SEM) approach will be employed.FindingsThe research reveals that ESG factors positively impact enterprises' competitiveness (EC). The augmentation of competitiveness is attributed to the moderating role of green technology innovation (GTI) and agency costs between ESG and EC. In the context of digitalization, the level of digitalization of logistics enterprises may create a capital squeeze effect on environmental performance, weakening competitiveness. Conversely, the level of digitalization positively regulates the promoting effect of governance performance on competitiveness.Originality/valueThis research provides a sound theoretical foundation for understanding how ESG contributes to boosting the competitiveness of Chinese logistics enterprises and extends the application of Piecewise SEM in the research field of logistics enterprise competitiveness. Furthermore, it offers a practical pathway for companies to implement ESG practices and foster competitiveness in digital environments.

A multifunctional life cycle assessment of durum wheat cropping systems

Agricultural systems strongly impact ecosystems by driving terrestrial degradation, water depletion, and climate change. The Life Cycle Assessment allows for comprehensive analyses of the environmental impacts of food production. Nonetheless, its application still faces challenges due to cropping systems’ increased complexity and multifunctionality. Past research has emphasized the need for more holistic approaches to consider dynamic crop interactions and diverse functions of cropping systems, beyond just meeting the demand for foods and feeds. In this context, this study applied an alternative combined and multifunctional modelling approach to compare the environmental performances of two durum wheat cropping systems. The latter differed in crop rotation schedules, farming methods, tillage techniques, and genotypes grown (including both modern and old ones). Novel methodological choices were adopted in this study, aiming at best representing the complexity and peculiarities of these systems, by considering crop rotation effects and reflecting the main durum wheat stakeholders’ perspectives. The results showed that the organic low-input landrace-growing system (Case 1) had considerably lower environmental impacts than the conventional high-input one (Case 2), regardless of the functional unit. The environmental hotspots were the increased land occupation and the bare fallow for Case 1 and Case 2, respectively. At the endpoint level, the most affected impact categories for both the systems of analysis were land use, fine particulate matter formation, global warming (human health), and human non-carcinogenic toxicity. Also, the midpoint analysis pointed out important differences in terms of other assessed impact categories, with Case 1 better performing for the majority of them. The identified improvement solutions include the following: the enhancement of the yield performances and the optimization of nitrogen provision from the leguminous crop for Case1, the shift toward a more efficient rotational scheme, the reduction of the use of external inputs, and the avoidance of unnecessary soil tillage operations for Case 2.

Feasibility of vehicle-to-grid (V2G) implementation in Japan: A regional analysis of the electricity supply and demand adjustment market

Vehicle-to-Grid (V2G) technology forms a critical bridge between electric vehicles (EVs) and renewable energy, playing a transformative role in the global shift towards a low-carbon future. Despite its promise, the impact of regional differences on V2G potential, particularly within specific application scenarios, remains largely unexplored. This study employs an agent-based modeling approach to evaluate V2G potential across Japan's 47 prefectures, with a focus on its integration into an energy reserve service business model. Our analysis reveals that EV ownership is the dominant factor influencing regional variability, with the Tokyo Metropolitan Area, Aichi, and Kanagawa emerging as top candidates for V2G deployment. Interestingly, when EV ownership is excluded from consideration, regions like Okinawa, Kagoshima, and Ibaraki show leadership in V2G potential. These findings highlight the existence of regional priorities for V2G application. Moreover, a ‘High Demand Disparity’ is observed in the power supply and demand adjustment market, where V2G systems are often either underutilized or overwhelmed, leaving many idle. The study underscores the need for region-specific strategies and the integration of diverse business models to fully capitalize on V2G's potential in various demand adjustment scenarios.

Inclusion of phase III clinical trial costs in health economic evaluations

IntroductionProtocol-driven trial activities contribute to the utility gain demonstrated in the phase III clinical trial of a new drug. If this utility gain cannot be distinguished from the effects of the new drug itself, protocol-driven trial costs cannot be easily dismissed for consistency reasons. This study aims to estimate the impact of including per-patient costs of phase III clinical trials on the incremental cost-effectiveness ratio (ICER).MethodsThe analysis utilized a modeling approach with secondary data from an ad-hoc literature review, considering both societal and payer perspectives. While the costs of phase III clinical trials may cancel out during the period of “normal” life-years due to the incremental cost calculation, they do not cancel out when differential early treatment termination occurs (e.g., due to differential mortality). Assuming the presence of differential mortality, per-patient phase III trial costs were calculated for the period of added life-years. These costs were then included in the ICER of a new drug, under the assumption that direct patient-related costs constitute 30–70% of the total trial costs. Capital costs were also incorporated from a societal perspective.ResultsBased on assumptions of $40,000 out-of-pocket expenses per patient enrolled in a phase III trial and a life expectancy gain of three months, incremental costs increased by $27,000 from a societal perspective. From a payer perspective, the estimate was $12,000.ConclusionsThe costs of phase III trials are a relevant component of the ICER, and excluding it is generally not appropriate for consistency reasons. Properly considering these trial costs is essential for a comprehensive evaluation of a new drug’s cost-effectiveness.

Muscle Volume Adaptations To Resistance Training Drive Changes In Dynamic Strength: A Causal Modeling Approach

Muscle Volume Adaptations To Resistance Training Drive Changes In Dynamic Strength: A Causal Modeling Approach

Exploring research topics and trends in early childhood education using structural topic modeling

Early childhood education plays a key role in fostering child development and preparing children for school and life. The aim of the present paper is to give an overview of research topics in early childhood education research based on the analysis of 39,926 scientific articles published between 2000 and 2021 and to explore research trends over time. Therefore, a structural topic modelling approach was used. The analyses show a strong increase in publication activity over the last years as well as the diversity of research topics, which provide important insights for achieving the UN Sustainable Development Goals in various areas (cultural diversity, design of inclusive learning environments, educational institutions, professional development issues, educational policy and reforms, etc.). Beside topics like cultural diversity, and inclusive learning environments more specific research topics, for example self-regulation, executive functions, numeracy, language development and physical activity have been increasingly addressed in publications over the years.

Modelling of Glass Soiling Due to Air Pollution Exposure at Urban and National Scales: Coimbra (Portugal) Case Study

Impacts of air pollution are not limited to human health and ecosystems, but are also important for building materials. The main objective of this study is the quantification and mapping of air pollution effects on the materials, namely the soiling effect of modern glass. An integrated modelling approach was implemented to quantify and analyze the spatial distribution of glass soiling due to exposure to air pollution. The methodology is based on an integrated modelling approach (transportation-emissions-dispersion modelling) applied with high spatial resolution for Coimbra (Portugal) urban area and compared with national scale modelling, showing the important contribution of local pollution sources affecting spatial variability in the soiling effect. Air quality data from CAMS (Copernicus Atmosphere Monitoring Service) were used to quantify the soiling effect at national scale. The results are presented and analyzed in terms of haze. The results obtained at national scale suggest that the average time to reach a 1% haze is 320 days, and this time is reduced to 180 days in the most affected areas. However, urban scale modelling applied with a detailed characterization of local pollution sources in Coimbra provides significantly different results and reveals that in the most affected areas, near road traffic, 1% haze could be reached in approximately 80 days. The methodology proposed and implemented in this study provides relevant information for the maintenance and preservation of building materials and highlights the importance of integrated modelling with high spatial resolution for the assessment of the soiling effect in the built environment.

Unveiling the link between test anxiety, online engagement, and academic achievement: insights from LMS interaction data

ABSTRACT There is a growing body of literature that recognizes the importance of test anxiety in learning contexts. However, currently little is known about test anxiety experienced in online assessment and its role in online learning efforts and outcomes based on insights from Learning Management Systems (LMS) interaction data. This study investigated the mediating role of test anxiety in the relationship between behavioral engagement and academic achievement. To test the research model, the study data were analyzed using the Partial Least Squares Structural Equation Modelling approach. The analyses drew on data from 2994 online distance learners. Behavioral engagement of students was derived from learning analytics indicators based on LMS interaction data. Our results showed that test anxiety reduces the positive effect of online behavioral engagement on academic achievement. This study provides valuable insights for educators, students, and test designers in understanding the dynamics between online test anxiety, behavioral engagement and academic achievement and developing effective strategies for online learning. This analysis highlights the importance of understanding the interplay between these factors for educators, students, and test designers to develop effective online learning strategies.

Towards spatially disaggregated cocaine supply chain modeling

Despite the global reach and economic scale of cocaine trafficking, our best geographic understanding of the global trade remains coarse. A more spatially disaggregated understanding of how the cocaine supply chain embeds across multiple locations is necessary for informing security policies and anticipating the spread and intensity of social and environmental harms associated with the cocaine trade. In this research, modeling methods used for legal supply chains are adapted to spatially disaggregate illicit supply chain flows. Profit and supply maximization model versions were compared to elucidate key decision parameters cocaine traffickers might be facing. Cocaine flows to EU+3 (Norway, Turkey, and United Kingdom) markets were estimated based on the smuggling capacity of major Central American ports and bilateral trade volumes of selected commodities most often seized with cocaine shipments. The resulting estimates of cocaine volumes diverted to EU+3 countries from Central America ranged between 938 and 1526 metric tons (MT). Generally, easier concealment and storage in Central America led to less volume supplied to the United States (US) and increased shipments to EU+3 markets. Importantly, the value of this modeling approach is not in the quantitative estimates produced, but in the methodological approach that provides the ability to rigorously ground any quantitative estimates of clandestine phenomenon in the best available data.

Cultivating flexibility: the relationship between flexible organizational values, participation climate, and job attitudes from an employee perspective

AbstractAdopting a flexible organizational culture have the potential to be a remedy for organizations that face globalization, technological advancements, and higher expectations from the workforce. However, research on the mechanism between organizational culture and its outcomes remain understudied. This study adopts an employee-centric approach, suggesting that employees’ perception of a participation climate act as a mediator between flexible organizational culture values (clan and adhocracy values) and employees’ organizational commitment and readiness for change. Cross-sectional data was collected from 619 police employees and analyzed by a two-step structural equation modeling approach. The results supports participation climate as a mediator. Participation climate partially mediated the relationship between clan culture and organizational commitment, adhocracy culture and organizational commitment, and adhocracy culture and readiness for change. Full mediation was found for the relationship between clan culture and readiness for change. Theoretically, this study provides supporting evidence of a relationship between employees’ perceptions of flexible organizational values and a climate for participation, grounded in the notion that organizational climate is the surface level manifestation of organizational culture. Practically, the results offer valuable insight for leaders and organizations who seek knowledge on flexible values, participation climate, employee commitment and readiness for change.

A coupled hydrological and hydrodynamic modeling approach for estimating rainfall thresholds of debris-flow occurrence

Abstract. Rainfall-induced hydrological processes and surface-water flow hydrodynamics may play a key role in initiating debris flows. In this study, a new framework based on an integrated hydrological and hydrodynamic model is proposed to estimate the intensity–duration (ID) rainfall thresholds that trigger debris flows. In the new framework, intensity–duration–frequency (IDF) analysis is carried out to generate design rainfall to drive the integrated models and calculate grid-based hydrodynamic indices (i.e., unit-width discharge). The hydrodynamic indices are subsequently compared with hydrodynamic thresholds to indicate the occurrence of debris flows and derive rainfall thresholds through the introduction of a zone threshold. The capability of the new framework in predicting the occurrence of debris flows is verified and confirmed by application to a small catchment in Zhejiang Province, China, where observed hydrological data are available. Compared with the traditional statistical approaches to derive intensity–duration (ID) thresholds, the current physically based framework can effectively take into account the hydrological processes controlled by meteorological conditions and spatial topographic properties, making it more suitable for application in ungauged catchments where historical debris-flow data are lacking.

Effect of automation of routine and non-routine tasks on labour demand and wages

Artificial intelligence and associated technology advances have progressively diffused from routine tasks to non-routine tasks, causing disruptions in the labour market. In this work, we study the effect of automation on the labour market outcomes for low-skilled and high-skilled workers. We use the agent-based modelling approach to model firms and workers as rational agents with defined objective functions, endowments, and interactions. Using extensive simulations, we analyse the emergent phenomenon of employment levels and wage inequality in the labour market under varying scenarios. The key findings of our simulations indicate that automation of routine tasks increases wage inequality, whereas automation of non-routine tasks reduces it. Based on our results, we propose policy prescriptions regarding the job categories in which automation can be introduced for societal benefits, the skill enhancement programme needed for the workers, and guidelines on the redeployment of labour displaced through automation.

Assessing the Multi-dimensional Effects of Air Pollution on Maternal Complications and Birth Outcomes: A Structural Equation Modeling Approach

Assessing the Multi-dimensional Effects of Air Pollution on Maternal Complications and Birth Outcomes: A Structural Equation Modeling Approach

Assessment of the impact of greenhouse rainwater harvesting managed aquifer recharge on the groundwater system in the southern Jeju Island, South Korea: Implication from a numerical modeling approach

Managed aquifer recharge (MAR) is increasingly being adopted worldwide to mitigate groundwater depletion and ensure the sustainability of water resources. Rainwater harvesting (RWH)-MAR can augment aquifer storage and reduce flood damage in rural areas with dense greenhouse facilities. This study has assessed the feasibility of greenhouse RWH-MAR in Namwon agricultural areas in the southern part of Jeju Island, South Korea, by considering the injection rate and location of MAR using a numerical model. The model results showed that groundwater level increases were directly related to the infiltration rate, although spatial differences in head rise were observed owing to the spatial variability of hydraulic conductivity. In addition, installing the RWH-MAR in highland areas (>100 masl) enhanced the water level rise when compared to the expected values, indicating that a higher hydraulic gradient and thick unsaturated zone facilitated more effective MAR outcomes than in lowland areas. To optimize the contribution of source water to the agricultural water demand, placing the RWH-MAR near the pumping well improved the availability of injected rainwater to agricultural wells. This study highlights the importance of designing RWH-MAR schemes considering MAR objectives and the topographic and hydrogeological characteristics of the site.

A 3D design of the hydrodynamic pocketed thrust bearing with slip engineered for eliminating cavitation

Nowadays, researchers are interested in surface modification of bearings by adding texture to increase bearing performance. Regrettably, modifications in surface roughness can induce cavitation. Conversely, slip engineering can enhance pressure to effectively eliminate cavitation. The objective of this work is to present a 3D design for thrust bearing that integrates pockets and slip engineering techniques in order to improve the load carrying capacity of the bearing and reduce cavitation. The originality of this study on thrust bearing is in the integration of surface texture, slip engineering, and cavitation. A CFD modeling approach is employed to simulate the slip formation in the design. Implementing slip induces hydrophobicity on the surface by introducing velocity to the fluid at the contact with the bearing pad. The simulation involves two types of bearings: radial pocket and multitexture, each with various slip positions. The important study's findings indicate that the radial pocket design, which incorporates slip formations both between and inside the pocket, can enhance the load carrying capacity by as much as 259.2 % compared to the absence of slip formation. When using the multitexture type, the load bearing capability can rise by up to 179 %. In the multitexture configuration, pressure is uniformly distributed throughout the bearing surface. To enhance the comprehensiveness of the research, the findings of this study are also compared to those of earlier conducted studies on circumferential pocket and closed pocket types. Arranging slip correctly has been empirically shown to enhance the load carrying capability of bearings.

Eco-climatological modeling approach for exploring spatiotemporal dynamics of ecosystem service values in response to land use and land cover changes in Riyadh, Saudi Arabia

Eco-climatological modeling approach for exploring spatiotemporal dynamics of ecosystem service values in response to land use and land cover changes in Riyadh, Saudi Arabia

Hydrogeological mapping of fracture networks using earth observation data to improve rainfall–runoff modeling in arid mountains, Saudi Arabia

Abstract Rainfall–runoff modeling is essential for the hydrological analysis of basins; however, the traditional modeling approach does not incorporate geological features such as fractures and fissures in the modeling task. These features are significant in the water loss during a rainstorm, which should be incorporated to obtain realistic rainfall–runoff results. A novel approach is presented here in to quantify the geological features and link them to the curve number (CN) method. The proposed methodology has not been applied in the literature. This approach is validated on five gauged basins, namely, Yiba, Al Lith, Liyya, Habawnah, and Tabalah, in the southwest part of Saudi Arabia. Four major stages are conducted. The first stage is the extraction of the geological lineaments using remote sensing and geographical information system technology; the second stage is estimating CN from rainfall–runoff data; the third stage is developing a relationship between CN and lineament density (LD); and the final stage is evaluating the developed equations on hydrological response. The least-squares method is employed to minimize the difference between observed and predicted runoff and determine the optimum range of CN. The research provides a comprehensive understanding of hydrological processes in fractured geologic systems and explores the influence of fractures on curve number. This study identifies two major lineament trends aligned with the Arabian trend direction, namely, north-northwest (NNW)–south-southeast (SSE) and north-northeast (NNE)–south-southwest (SSW). Furthermore, a moderate inverse correlation is established between LD and CN, highlighting the significance of geologic fractures on the hydrological response. The findings of this study provide insight into how the geological fissures in the mountainous region affected the rainfall–runoff response that leads to a low value of CN due to the water loss in the fissures and faults. As a result, this study clearly demonstrates the importance of the geological structures on rainfall–runoff responses.

Model the evolutionary pattern of N species and pool size in groundwater continuum by utilizing measured source and sink rates of nitrate and ammonium

Nitrate and ammonium are primary nitrogen (N) contaminants in groundwater and effective restoration strategies depend on understanding the interactions of N transformation processes along redox gradients. Utilizing the 15N tracing technique, we assess nitrate removal rates, focusing on denitrification and anammox in a N-rich groundwater of the Hetao Basin, a typical semiarid region in western China. Results showed that N removal rate (0.36–22.01µM d−1) was composed mainly of denitrification (73 ± 18%), with rates increasing from upstream oxidizing environment to downstream reducing areas. In reducing downstream, both denitrification and anammox adhered to substrate-driven Michaelis-Menten kinetics. Integrating data on all source and sink rates of nitrate and ammonium pools (denitrification, anammox, dissimilatory nitrate reduction ammonia, nitrification, mineralization), we constructed a N-transfer-dynamics model based on chemical stoichiometry. This model effectively captured the observed spatial N transfer patterns and highlighted that the balance of oxidants and biodegradable organic N inputs influences N species retention and removal in groundwater. Our combined experimental and modeling approach underscores the importance of reducing organic N and/or adding oxidants to mitigate groundwater N pollution. These findings provide crucial insights for optimizing high N groundwater remediation strategies and potentially inform for wastewater management practices.

Point cloud data-driven modelling of high-strength steel wire corrosion pits considering orientation features

We propose a corrosion pit modelling approach of high-strength steel wires considering orientation features using surface point cloud data, collected by three-dimensional laser scanning. Corrosion pits were identified through density-based spatial clustering of applications with noise (DBSCAN). The identified corrosion pits could be modelled as a semiellipsoid considering orientation features. The Gaussian copula model was utilised to describe the joint distribution of the geometric parameters of the corrosion pits. This approach will be valuable for simulation of the surface morphology of corroded high-strength steel wires.

The mediating effect of resilience between physical activity and mental health: a meta-analytic structural equation modeling approach

BackgroundWhile the correlation between physical activity (PA) and mental health is well known, the mediating mechanism of resilience between the two variables remains unclear.ObjectivesTo systematically evaluate the relationship between PA and mental health, and explore the mediating role of resilience between them.MethodsA systematic search of electronic databases (PubMed, Web of Science, ProQuest, Ebsco, China Knowledge, and China Biomedical Database) was conducted to identify relevant studies, and meta-analytic procedures were used to assess the strength of the relationships between PA and mental health. Furthermore, a meta-analytic structural equation model (MASEM) was used to assess the mediating effects of resilience, ensuring the reliability of our findings.ResultsThe findings of 15 studies (17,043 subjects) were subjected to meta-analysis and route analysis. The findings of the meta-analysis revealed a statistically significant positive correlation of 0.288 (95% CI, 0.166–0.402) between PA and positive indicators of mental health, as well as a statistically significant negative correlation (95% CI, −0.342 to −0.171) with negative indicators of mental health. Furthermore, the results of MASEM path analysis indicated that PA may indirectly impact both positive and negative indicators of mental health through the mediating factor of resilience. The indirect effect values were 0.108 (95% CI, 0.080–0.141) and −0.074 (95% CI, −0.100 to −0.051), respectively, accounting for 40.15% of the total effect value and 28.91%.ConclusionPhysical activity is positively correlated with positive indicators of mental health and negatively correlated with negative indicators of mental health. Moreover, PA can positively influence mental health through the mediating role of resilience.