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The use of waste polyethylene terephthalate (PET) plastics derived from shredded bottles in concrete is not formalized yet, especially in reinforced members such as beams and columns. The disposal of plastic wastes in concrete is a viable alternative to manage those wastes while minimizing the environmental impacts associated to recycling, carbon dioxide emissions and energy consumption.

This paper evaluates the suitability of 2D deterministic and stochastic finite element (FE) modeling to predict the shear strength behavior of reinforced concrete (RC) beams without stirrups. Different concrete mixtures prepared with 1.5%–4.5% PET additions, by volume, are investigated.

Test results showed that the deterministic and stochastic FE approaches are accurate to assess the maximum load of RC beams at failure and corresponding midspan deflection. However, the crack patterns observed experimentally during the different stages of loading can only be reproduced using the stochastic FE approach. This later method accounts for the concrete heterogeneity due to PET additions, allowing a statistical simulation of the effect of mechanical properties (i.e. compressive strength, tensile strength and Young’s modulus) on the output FE parameters.

Data presented in this paper can be of interest to civil and structural engineers, aiming to predict the failure mechanisms of RC beams containing plastic wastes, while minimizing the experimental time and resources needed to estimate the variability effect of concrete properties on the performance of such structures.

To understand how organizations, public or private, must increase their productivity perception (PP), independently of the sector. This article aims to analyze PP in the digital transformation (DT) process to determine how it is affected by technostress (TS) and work engagement (WE), two concepts that seem to be forces opposing PP.

The authors use data from a questionnaire addressed to personnel in two organizations (public and private). The analysis applies partial least squares technique to the 505 valid responses obtained from these organizations. This analysis is based not on representativeness but on uniqueness.

The results suggest a positive, significant relationship between DT and PP. This article integrates DT and its effects on aspects of people's health, PP and WE. The model thus includes interactions of technology with human elements. In both business and administrative environments, PP is key to optimizing resources and survival of organizations.

DT processes are different and complex because every organization is different. The authors recommend expanding this study to other sectors in both spheres, public and private. Aligning the objectives of the institutions for aid with DT is also quite complicated.

This study contributes to improving participating organizations. It also provides government institutions with a clear foundation from which to encourage actions that promote the health and WE of their workforce without reducing productivity. In addition, this study adds novelty to the research line.

The authors have deepened this line of research by developing fuller knowledge of the relationships among novel and necessary variables in organizations. The authors provide complementary, different and inspiring value in addressing this line of research.

Micro-regeneration can effectively enhance a neighborhood’s commercial vitality and serve as a viable approach to boost economic benefits. However, the small scale of micro-regeneration efforts and the fragmented nature of information currently limit the availability of strong empirical evidence demonstrating its impact on neighborhood commercial vitality. The aim of the study was to examine the link between micro-regeneration and neighborhood commercial vitality, focusing on the average, time-lag, spatial spillover, and spatial heterogeneity effects.

Using the panel data set of 1,755 neighborhoods in Chongqing from 2016 to 2021 as the research sample, the difference-in-differences (DID) method was employed in this study to explore the impact micro-regeneration has on neighborhood commercial vitality.

The results illustrate that: (1) micro-regeneration can promote neighborhood commercial vitality in terms of the number and types of local consumption amenities by 27.76 and 5.89%, respectively, with no time-lag effect; (2) the positive spillovers can exist within the range of 5,000 meters–5,500 meters of regenerated neighborhoods; and (3) the effect of micro-regeneration on neighborhood commercial vitality can be greater in peripheral areas than in core areas of the city.

The findings fill the knowledge gap on the relationship between micro-regeneration and neighborhood commercial vitality. Additionally, the results on the time-lag effect, spatial spillover effects, and spatial heterogeneity provide practical implications that can support the government and private sector in developing temporal and spatial arrangements for micro-regeneration projects.

Land value varies at a micro level depending on the location’s economic, geographical and political determinants. The purpose of this study is to present a comprehensive assessment of the determinants affecting land value in the Indian city of Thiruvananthapuram in the state of Kerala.

The global influence of the identified 20 explanatory variables on land value is measured using the traditional hedonic price modeling approach. The localized spatial variations of the influencing parameters are examined using the non-parametric regression method, geographically weighted regression. This study used advertised land value prices collected from Web sources and screened through field surveys.

Global regression results indicate that access to transportation facilities, commercial establishments, crime sources, wetland classification and disaster history has the strongest influence on land value in the study area. Local regression results demonstrate that the factors influencing land value are not stationary in the study area. Most variables have a different influence in Kazhakootam and the residential areas than in the central business district region.

This study confirms findings from previous studies and provides additional evidence in the spatial dynamics of land value creation. It is to be noted that advanced modeling approaches used in the research have not received much attention in Indian property valuation studies. The outcomes of this study have important implications for the property value fixation of urban Kerala. The regional variation of land value within an urban agglomeration shows the need for a localized method for land value calculation.

Managers of public organizations in liberalized sectors face the dual imperative of retaining skilled employees who might be poached by commercial competitors and improving service performance levels without a free hand to invest resources. While employee work engagement (EWE) has been previously suggested as a solution to such management challenges, limitations in its ability to retain employees have been identified. We therefore examine how a social identity crafting (SIC) approach to public leadership that confers a sense of group identity among team members can enhance and extend beyond EWE in addressing this dual imperative.

We report findings from a survey of employees (n = 199) at “ATCO,” a state-owned national airline that is facing challenges from commercial rivals within a new, competitive environment.

We confirm previously identified limitations of EWE and, further, demonstrate that a social identity approach to leadership offers a promising avenue for public managers, not only by enhancing employee engagement but, more importantly, by enhancing retention and service performance.

We contribute to studies of leadership, particularly for managers operating in the public sector and resource-constrained environments, demonstrating how SIC, which does not require costly investment to attain, can deliver improved service performance and reduced employee turnover intention, operating beyond EWE, which reaches a plateau in respect of the latter.

The purpose of the study is to examine the efficiency of linear, nonlinear and artificial neural networks (ANNs), in predicting property prices.

The present study uses a dataset of 1,468 real estate transactions from 2020 to 2022, obtained from the Department of Property Taxes of Republic of Kosovo. Beginning with a fundamental linear regression model, the study tackles the question of overlooked nonlinearity, employing a similar strategy like Peterson and Flanagan (2009) and McCluskey et al. (2012), whereby ANN's predictions are incorporated as an additional regressor within the ordinary least squares (OLS) model.

The research findings underscore the superior fit of semi-log and double-log models over the OLS model, while the ANN model shows moderate performance, contrary to the conventional conviction of ANN's superior predictive power. This is notably divergent from the prevailing belief about ANN's superior predictive power, shedding light on the potential overestimation of ANN's efficacy.

The study accentuates the importance of embracing diverse models in property price prediction, debunking the notion of the ubiquitous applicability of ANN models. The research outcomes carry substantial ramifications for both scholars and professionals engaged in property valuation.

Distinctively, this research pioneers the comparative analysis of diverse models, including ANN, in the setting of a developing country's capital, hence providing a fresh perspective to their effectiveness in property price prediction.

Little research has focused on empowering leadership (EL) in the context of public organizations. Thus, this study aims to explore the relationship between EL and public employees' well-being (EWB). In addition, utilizing a moderated mediation mechanism, this study investigates the mediating role of psychological empowerment (PE) and the moderating role of time pressure (TP) and collectivist orientation in the proposed model.

Quantitative data were collected from 643 public servants working in wards (grassroot-level government) in Vietnam. Partial least squares structural equation modeling (PLS-SEM) was employed to test the proposed relationships.

The results show that EL and PE have a significant positive effect on EWB. Moreover, PE has a complementary effect on this nexus. The results also lent credence to the moderating roles of TP and collectivist orientation.

The empirical results of this inquiry provide valuable implications for public managers. The findings suggest that public managers can promote EWB by implementing EL and enhancing PE. Moreover, when designing and implementing tasks, managers should ensure sufficient time for their followers.

This study advances the understanding of public sector EWB via the predictive role of empowering leaders and the mediation mechanism of PE. Moreover, this study is among the pioneering studies exploring the moderating role of TP and collectivist orientation on these relationships.

This study aims to perform three-dimensional numerical computations for blood flow through a double stenosed carotid artery. Pulsatile flow with Womersley number (Wo) of 4.65 and Reynolds number (Re) of 425, based on the diameter of normal artery and average velocity of inlet pulse, was considered.

Finite volume method based ANSYS Fluent 20.1 was used for solving the governing equations of three-dimensional, laminar, incompressible and non-Newtonian blood flow. A high-quality grid with sufficient refinement was generated using ICEM CFD 20.1. The time-averaged flow field was captured to investigate the effect of severity and eccentricity on the lumen flow characteristics.

The results show that an increase in interspacing between blockages brings shear layer instability within the region between two blockages. The velocity profile and wall shear stress distribution are found to be majorly influenced by eccentricity. On the other hand, their peak magnitude is found to be primarily influenced by severity. Results have also demonstrated that the presence of eccentricity in stenosis would assist in flow development.

Variation in severity and interspacing was considered with a provision of eccentricity equal to 10% of diameter. Eccentricity refers to the offset between the centreline of stenosis and the centreline of normal artery. For the two blockages, severity values of 40% and 60% based on diameter reduction were permuted, giving rise to four combinations. For each combination, three values of interspacing in the multiples of normal artery diameter (D), viz. 4D, 6D and 8D were considered.

This is the first article to apply a machine learning approach to the analysis of time on market on real estate markets.

The random survival forest approach is introduced to the real estate market. The most important predictors of time on market are revealed and it is analyzed how the survival probability of residential rental apartments responds to these major characteristics.

Results show that price, living area, construction year, year of listing and the distances to the next hairdresser, bakery and city center have the greatest impact on the marketing time of residential apartments. The time on market for an apartment in Munich is lowest at a price of 750 € per month, an area of 60 m2, built in 1985 and is in a range of 200–400 meters from the important amenities.

The findings might be interesting for private and institutional investors to derive real estate investment decisions and implications for portfolio management strategies and ultimately to minimize cash-flow failure.

Although machine learning algorithms have been applied frequently on the real estate market for the analysis of prices, its application for examining time on market is completely novel. This is the first paper to apply a machine learning approach to survival analysis on the real estate market.