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This study aims to examine the reuse of plastic and fly ash (FA) to improve the soil and achieve sustainable development goals.

Sand from the Anzali port was reinforced with Geopet (GP) and stabilized with FA plus 3% sodium hydroxide. The GP was placed in FA-stabilized soil and the California bearing ratio (CBR), and unconfined compressive strength (UCS) tests were performed on samples at the optimum moisture content.

The results showed that the improvement in the optimum CBR was 174.9%. The UCS increased 15.25% and 48.65% in soil reinforced with three layers of GP plus 15% FA over those containing 10% and 5% FA, respectively. Additionally, the current analysis used response surface methodology (RSM) to investigate the impact of FA percentage, GP layers and their interaction on CBR. The results highlight the efficacy of the used RSM model, as evidenced by the significantly low p-value (<0.0001).

This demonstrates the suitability and effectiveness of RSM for evaluating CBR in this scientific study.

Induction heating as an energy source is a novel, recent method in extrusion-based metal additive manufacturing. The purpose of this paper is to develop an optimized coil for extrusion-based metal wire additive manufacturing. The optimized coil is so designed that uniform temperature distribution can be achieved in the extruder, achieving uniform material deposition in a semi-solid state, which is required for additive manufacturing.

Coil shape optimization is achieved by using arrangement of coil turns as a control variable in the form optimization process, and the objective function is to minimize the gradient in the distribution of the magnetic field to achieve uniform heating in the extruder for maintaining consistent solid and liquid fraction during material deposition. A combination of numerical solutions and geometrical optimization has been used for this study.

Experimental and simulation results reveal that the optimized induction coil produced a more uniform axial temperature distribution in the extruder, which is suitable for maintaining a uniform solid-to-liquid fraction ratio during material deposition.

The author has investigated the use of optimized-shaped induction coils in extrusion-based additive manufacturing. The optimized coil can achieve a more uniform temperature distribution in the extruder in comparison to the standard helical coil used in the existing process, which means optimized coil achieves a more uniform solid-to-liquid ratio during printing in comparison to existing standard coil shapes used for heating extruders and fulfils the requirement of additive manufacturing.

This study aims to investigate the direct effect of intellectual capital on the organizational performance of Indonesian state-owned enterprises (SOEs) and their subsidiaries. Furthermore, it also examines whether the relationship is mediated by open innovation and moderated by organizational inertia.

This study is designed as quantitative research. A survey method is employed to collect data by distributing questionnaires to the upper-level managers of the SOEs and their subsidiaries. A total of 293 questionnaires were distributed to the respondents, and 97 responses were obtained for further analysis. The partial least square structural equation modeling (PLS-SEM) is used to test the hypotheses. A mediation-moderation research framework is employed.

The results show that intellectual capital has a positive effect on organizational performance. Further results also demonstrate that open innovation mediates the intellectual capital–organizational performance relationship and organizational inertia moderates the intellectual capital–organizational performance relationship. Theoretically, the findings contribute to the resource-based view (RBV) and knowledge-based view (KBV) by providing empirical evidence of the importance of distinctive internal resources in achieving superior organizational performance. Practically, the findings provide strategic information for managers that they should properly manage intellectual capital, open innovation and organizational inertia because of their effects on organizational performance.

First, this study addresses the previous research gaps by confirming that intellectual capital has a positive effect on organizational performance in the research setting of an emerging market. Second, by using a mediation research framework, this study shows that open innovation mediates the relationship between intellectual capital and organizational performance. Third, by using a moderating research framework, this study also reveals that organizational inertia weakens the relationship between intellectual capital and organizational performance. Those associations are rarely researched.

This paper aims to present a predictive model approach to estimate the tensile behavior of polylactic acid (PLA) under uncertainty using the fused deposition modeling (FDM) and American Society for Testing and Materials (ASTM) D638’s Types I and II test standards.

The prediction approach combines artificial neural network (ANN) and finite element analysis (FEA), Monte Carlo simulation (MCS) and experimental testing for estimating tensile behavior for FDM considering uncertainties of input parameters. FEA with variance-based sensitivity analysis is used to quantify the impacts of uncertain variables, resulting in determining the significant variables for use in the ANN model. ANN surrogates FEA models of ASTM D638’s Types I and II standards to assess their prediction capabilities using MCS. The developed model is applied for testing the tensile behavior of PLA given probabilistic variables of geometry and material properties.

The results demonstrate that Type I is more appropriate than Type II for predicting tensile behavior under uncertainty. With a training accuracy of 98% and proven presence of overfitting, the tensile behavior can be successfully modeled using predictive methods that consider the probabilistic nature of input parameters. The proposed approach is generic and can be used for other testing standards, input parameters, materials and response variables.

Using the proposed predictive approach, to the best of the authors’ knowledge, the tensile behavior of PLA is predicted for the first time considering uncertainties of input parameters. Also, incorporating global sensitivity analysis for determining the most contributing parameters influencing the tensile behavior has not yet been studied for FDM. The use of only significant variables for FEA, ANN and MCS minimizes the computational effort, allowing to simulate more runs with reduced number of variables within acceptable time.

The comfort of apparel is not only a feeling of perception but also a tangible measure. The fit and fabric of clothing can exert a perception of comfort for the wearer, whereas actual comfort largely depends on physiological and emotional soothing. However, there is still no solid work on connecting the bridge between physiological and emotional feelings to the comfort of clothing. In this study, we have conceptualized, formulated and proven the relation between physiological and emotional parameters with clothing fit and fabric to find the true comfort of the wearer.

A mixed-method research design using physiological and emotional parameters for different fabric and fit combinations were used for this study. The physiological comfort parameters (i.e. heart rate and respiration rate) are extracted from the subjects using gold-standard clinical devices for various fit and fabric combinations. For the emotional response, a survey was conducted for the same subjects wearing all the fit and fabric combinations. Statistical analysis and modeling were performed to obtain the results.

Physiological indicators such as heart rate are closely linked with user comfort. Due to the limitations in environmental control, the physiological changes obtained did not significantly vary for different fabric and fit combinations of the clothing. However, a significant change in emotional response indicated a definite relationship between different fabric and fit types. Based on the participants’ responses, weather conditions, size of the clothing item, types of fabrics and style also influence the participants’ choice of clothing.

The research was conducted to discover the relation between true comfort (physiological and emotional parameters) and clothing (fit and fabric), which is unique to the field. This study closes the gap and builds up the relationship, which can help introduce clothing comfort to users in the future. The findings of this study help us understand how fabric types (natural or synthetic) and clothing fit types (loose or fitted) can affect physiological and emotional responses, which can provide the consumer with satisfactory clothing with the suitable properties needed.

This paper aims to explore the relationship between CEO overconfidence and earnings management examined by the discretionary accruals and if this relationship is moderated by business ethics.

Data from a sample of 246 European firms selected from the Stoxx Europe 600 Index between 2010 and 2022 were used to test the model using panel data and multiple regressions. This paper considered the feasible generalized least squares (FGLS) estimation for linear panel data models. A multiple regression model is used to analyze the moderating effect of business ethics on the association between CEO overconfidence and earnings management. For robustness analyses, this paper included the alternative measure of the dependent variable and independent variable.

Using discretionary accruals as a proxy for earnings management, the empirical results show a positive relationship between CEO overconfidence and earnings management. Furthermore, the results suggest that business ethics negatively moderates the relationship between CEO overconfidence and earnings management.

This paper makes a significant contribution to stakeholders such as investors, financial decision-makers and auditors. It underscores the importance of integrating ethical considerations into corporate governance practices for fostering accountability and transparency. In addition, it highlights the moderating role of business ethics in transforming the positive effect of CEO overconfidence on earnings management into a negative impact. This emphasizes the pivotal role of ethical norms in financial decision-making processes and extends implications to standard setters and policymakers in the regulatory domain.

To the best of the authors’ knowledge, this is the first study to examine the moderating role of business ethics on the relationship between CEO overconfidence and earnings management in the European context. It is also the first study to document that business ethics can reduce the effect of CEOs’ biased behavior and their scope for discretion, thereby reducing the amount of earnings management. This study fills a research gap by extending the existing literature, which generally focuses on the impact of CEO overconfidence and earnings management.

While scholarly studies focus on the role of technology in digital transformation, an important direction of research still requires examining HR-related factors in this regard specifically. This study aims to analyze factors pertaining to human and organizational resources in the context of digital transformation within healthcare enterprises. The study examines the possible impacts of organizational energy (OE) and human resource flexibility (HRF) on digital transformation (DT). The study also seeks to investigate the influence of organizational inertia (OI) on the relationships being examined, according to the theory of change principles.

The empirical study used a survey method on 355 Mansoura University Hospitals employees, Egypt. The study data were analyzed using structural equations modeling with WarpPLS V. 8.0.

The results showed that all OE dimensions directly affected DT and HRF dimensions. Through HRF, OE indirectly affected DT. The study also found that all dimensions of OI negatively moderated the OE-DT and HRF-DT relationships. Based on the study's results, theoretical and practical implications were drawn.

This study develops a novel model to empirically investigate the quantitative relationships between OE, HRF, OI, and DT. This study provides an addition to understanding how human resources and organizational mechanisms work in technology-based experiments such as digital transformation and adds contributions in this regard to the health sector in particular.

This study aims to respond to the latest research calls to precisely revisit the nexus between corporate green innovation (CGI) and financial decisions through deeply investigating the mediating effect of corporate environmental performance measured by the effectiveness of emission reduction.

This study analyzes nonfinancial-listed firms on the Australian Securities Exchange from 2002 to 2019 using multiple regression analysis on a panel data set. Initially, different static panel data approaches were used. To account for the potential endogeneity issue and generate robust outcomes, the authors apply the one-step system generalized method of moment, two-stage least squares and lagged model approaches.

The results provide a clear indication that the practices of green innovation can favorably contribute to the level of environmental performance, which in turn affect the firm’s ability in opening the new financial doors and shape solid capital structure. In this context, the effective environmental performance fully mediates the nexus between CGI and capital structure of a firm. More importantly, the outcomes are robust and coherent across different estimation techniques.

The originality of this study lies in its utilization of mediation analysis to explore the relationship between CGI and a firm's financial structure. This approach distinguishes it from previous research by offering a thorough and nuanced understanding of how green innovation practices influence the financing decisions of a firm.

Climate change has led to a rise in the frequency, intensity and scope of droughts, posing significant implications for businesses. This study examines the impact of local community drought levels on audit pricing. Additionally, it explores the moderating effects of high-tech industries, auditor busyness and the level of local community concern regarding the drought crisis.

This study employs a mixed-methods approach to rigorously test the research hypotheses. The quantitative phase of the study utilizes a sample of 1,278 firm-year observations from Iran’s capital market. For the analysis of the quantitative data, ordinary least squares regression with clustered robust standard errors is used. Additionally, this research supplements its quantitative findings with qualitative evidence obtained through semi-structured interviews with 19 Iranian audit partners.

The results suggest that firms operating in provinces facing severe droughts experience notably higher audit fees. Furthermore, the positive relationship between drought and audit fees is weakened when auditors are busy, local community concern regarding the drought crisis is high or the firm operates within high-tech industries. These findings are supported by a range of robustness checks and qualitative evidence gathered from the field.

This research contributes to the growing literature on climate change by examining the influence of local community drought levels on audit pricing within an Iranian context. Additionally, our study sheds light on how high-tech industries, auditor workload and the level of local community concern regarding the drought crisis moderate the relationship between drought and audit fees. Importantly, our study pioneers in providing mixed-methods evidence of the association between drought severity and audit fees.

This paper aims to study numerically the non-Newtonian solution of carboxymethyl cellulose in water along with copper oxide nanoparticles, which flow turbulently through twisted smooth and finned tubes.

The twisted-tape inserts of rectangular and triangular sections are investigated under constant wall heat flux and the nanoparticle concentration varies between 0% and 1.5%. Computational fluid dynamics simulation is first validated by experimental information from two test cases, showing that the numerical results are in good agreement with previous studies. Here, the impact of nanoparticle concentration, tube twist and fins shape on the heat transfer and pressure loss of the system is measured. It is accomplished using longitudinal rectangular and triangular fins in a wide range of prominent parameters.

The results show that first, both the Nusselt number and friction factor increase with the rise in the concentration of nanoparticles and twist of the tube. Second, the trend is repeated by adding fins, but it is more intense in the triangular cases. The tube twist increases the Nusselt number up to 9%, 20% and 46% corresponding to smooth tube, rectangular and triangular fins, respectively. The most twisted tube with triangular fins and the highest value of concentration acquires the largest performance evaluation criterion at 1.3, 30% more efficient than the plain tube with 0% nanoparticle concentration.

This study explores an innovative approach to enhancing heat transfer in a non-Newtonian nanofluid flowing through an oval tube. The use of twisted-tape inserts with rectangular and triangular sections in this specific configuration represents a novel method to improve fluid flow characteristics and heat transfer efficiency. This study stands out for its originality in combining non-Newtonian fluid dynamics, nanofluid properties and geometric considerations to optimize heat transfer performance. The results of this work can be dramatically considered in advanced heat exchange applications.