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Understanding and tailoring the solidification characteristics and microstructure evolution in as-built parts fabricated by laser powder bed fusion (LPBF) is crucial as they influence the final properties. Experimental approaches to address this issue are time and capital-intensive. This study aims to develop an efficient numerical modeling approach to develop the process–structure (P-S) linkage for LPBF-processed Inconel 718.

In this study, a numerical approach based on the finite element method and cellular automata was used to model the multilayer, multitrack LPBF build for predicting the solidification characteristics (thermal gradient G and solidification rate R) and the average grain size. Validations from published experimental studies were also carried out to ensure the reliability of the proposed numerical approach. Furthermore, microstructure simulations were used to develop P-S linkage by evaluating the effects of key LPBF process parameters on G × R, G/R and average grain size. A solidification or G-R map was also developed to comprehend the P-S linkage.

It was concluded from the developed G-R map that low laser power and high scan speed will result in a finer microstructure due to an increase in G × R, but due to a decrease in G/R, columnar characteristics are also reduced. Moreover, increasing the layer thickness and decreasing the hatch spacing lowers the G × R, raises the G/R and generates a coarse columnar microstructure.

The proposed numerical modeling approach was used to parametrically investigate the effect of LPBF parameters on the resulting microstructure. A G-R map was also developed that enables the tailoring of the as-built LPBF microstructure through solidification characteristics by tuning the process parameters.

The purpose of the paper is to conduct a numerical and experimental investigation into the properties of nanofluids containing spherical nanoparticles of random sizes flowing through a porous medium. The study aims to understand how the thermophysical properties of the nanofluid are affected by factors such as nanoparticle volume fraction, permeability of the porous medium, and pore size. The paper provides insights into the behavior of nanofluids in complex environments and explores the impact of varying conditions on key properties such as thermal conductivity, density, viscosity, and specific heat. Ultimately, the research contributes to the broader understanding of nanofluid dynamics and has potential implications for engineering and industrial applications in porous media.

This paper investigates nanofluids with spherical nanoparticles in a porous medium, exploring thermal conductivity, density, specific heat, and dynamic viscosity. Studying three compositions, the analysis employs the classical Maxwell model and Koo and Kleinstreuer’s approach for thermal conductivity, considering particle shape and temperature effects. Density and specific heat are defined based on mass and volume ratios. Dynamic viscosity models, including Brinkman’s and Gherasim et al.'s, are discussed. Numerical simulations, implemented in Python using the Langevin model, yield results processed in Origin Pro. This research enhances understanding of nanofluid behavior, contributing valuable insights to porous media applications.

This study involves a numerical examination of nanofluid properties, featuring spherical nanoparticles of varying sizes suspended in a base fluid with known density, flowing through a porous medium. Experimental findings reveal a notable increase in thermal conductivity, density, and viscosity as the volume fraction of particles rises. Conversely, specific heat experiences a decrease with higher particle volume concentration.xD; xA; The influence of permeability and pore size on particle volume fraction variation is a key focus. Interestingly, while the permeability of the medium has a significant effect, it is observed that it increases with permeability. This underscores the role of the medium’s nature in altering the thermophysical properties of nanofluids.

This paper presents a novel numerical study on nanofluids with randomly sized spherical nanoparticles flowing in a porous medium. It explores the impact of porous medium properties on nanofluid thermophysical characteristics, emphasizing the significance of permeability and pore size. The inclusion of random nanoparticle sizes adds practical relevance. Contrasting trends are observed, where thermal conductivity, density, and viscosity increase with particle volume fraction, while specific heat decreases. These findings offer valuable insights for engineering applications, providing a deeper understanding of nanofluid behavior in porous environments and guiding the design of efficient systems in various industrial contexts.

Increasing overhang of serviced apartments poses a serious concern to the national property market. This study aims to examine the impacts of macroeconomic determinants, namely, gross domestic product (GDP), consumer confidence index (CF), existing stocks (ES), incoming supply (IS) and completed project (CP) on serviced apartment price changes.

To achieve more accurate, quality price changes, a serviced apartment price index (SAPI) was constructed through a self-developed hedonic price index model. This study has collected 1,567 transaction data in Kuala Lumpur, covering 2009Q1–2018Q4 for price index construction and data were analysed using the vector autoregressive model, the vector error correction model and the fully modified ordinary least squares (OLS) (FMOLS).

Results of the regression model show that only GDP, ES and IS were significantly associated with SAPI, with an R² of 0.7, where both ES and IS have inverse relationships with SAPI. More precisely, it is predicted that the price of serviced apartments will be reduced by 0.56% and 0.21% for every 1% increase in ES and IS, respectively.

Therefore, government monitoring of serviced apartments’ future supply is crucial by enforcing land use-planning regulations via stricter development approval of serviced apartments to safeguard and achieve more stable property prices.

By adopting an innovative approach to estimating the response of price change to supply and demand in a situation where there is no price indicator for serviced apartments, the study addresses the knowledge gap, especially in terms of understanding what are the key determinants of, and to what extent they influence, the SAPI.

Research on employee non-/compliance to information security policies suffers from inconsistent results and there is an ongoing discussion about the dominating survey research methodology and its potential effect on these results. This study aims to add to this discussion by investigating discrepancies between what the authors claim to measure (theoretical properties of variables) and what they actually measure (respondents’ interpretations of the operationalized variables). This study asks: How well do respondents’ interpretations of variables correspond to their theoretical definitions? What are the characteristics of any discrepancies between variable definitions and respondent interpretations?

This study is based on in-depth interviews with 17 respondents from the Swedish public sector to understand how they interpret questionnaire measurement items operationalizing the variables Perceived Severity from Protection Motivation Theory and Attitude from Theory of Planned Behavior.

The authors found that respondents’ interpretations in many cases differ substantially from the theoretical definitions. Overall, the authors found four principal ways in which respondents interpreted measurement items – referred to as property contextualization, extension, alteration and oscillation – each implying more or less (dis)alignment with the intended theoretical properties of the two variables examined.

The qualitative method used proved vital to better understand respondents’ interpretations which, in turn, is key for improving self-reporting measurement instruments. To the best of the authors’ knowledge, this study is a first step toward understanding how precise and uniform definitions of variables’ theoretical properties can be operationalized into effective measurement items.

Traditional management models are no longer viable in this complex era, with fast-pacing markets and various emergent properties affecting organizational success. The present study acknowledges the need for developing a coherent framework that leaders may use to evaluate their organizational adaptive ability.

This paper uses theoretical analysis.

This paper proposes the CAL-R framework, which identifies key characteristics of complex adaptive systems (CAS). These actionable elements, manifested in respective behaviors, will increase organizational adaptability. Adaptability is then suggested to be the mediating factor between complex adaptive leadership practice and organizational performance.

The suggested actionable elements are developed based on a theoretical, non-measurable approach; however, the need for statistical rigorousness is also acknowledged. Further research and a quantitative approach are also suggested for the development of a sound measurement scale.

Applying effective complex adaptive leadership will potentially provide organizations with a competitive advantage by making them more innovative, able to transform and adapt to environmental needs and changes and eventually meet their goals and reach their vision. Leaders may use the identified actionable elements as benchmarks against which they can evaluate their organizations' complex adaptive leadership readiness (CAL-R).

The CAL-R framework may be used by leaders in order to evaluate their organization’s current adaptive maturity level (ability) and identify the elements they need to focus on more and develop in order to become more adaptive and competitive.

The purpose of this paper is to conceptualize the notion of thin crossing points from a social network perspective and to outline the concrete networking strategies that enable salespeople to foster mutually valuable resource exchange (i.e. to thin crossing points) across a selling ecosystem.

The authors integrate extant theoretical perspectives to advance a conceptual framework of sales-related networking across three key actors in a selling ecosystem: intraorganizational selling actors and actors in customers and external partner organizations.

Thin crossing points are defined as figurative transaction points at the boundary between organizations or organizational subunits at which actors engage in mutually valuable resource exchange in the process of value cocreation. To thin crossing points with key ecosystem actors, salespeople must adapt networking strategies considering the time and trust constraints inherent in a network relationship. Such constraints inform the most advantageous network centralities (degree, eigenvector and betweenness) and actions to impact key network properties (tie strength, contact diversity) that enable salespeople to efficiently develop social capital and thus to optimally thin crossing points across a selling ecosystem.

To the best of the authors’ knowledge, this study is the first social network-based exploration of salespeople’s role in thinning crossing points with key ecosystem actors. It advances a novel conceptual framework of sales-related networking strategies that foster social capital development and optimally thin crossing points across a selling ecosystem.

The role of local authorities is crucial in addressing the essential needs of communities, and they possess the right to impose property taxes on all properties within their territory. Property taxes are levied on all properties, contributing to approximately 60% of the local authority’s finances. However, their role in this policy is not frequently understood, primarily in executing property tax reassessment. Hence, this paper aims to reveal property tax reassessment implementation and identify its key challenges.

The latest tone of the list record was extracted from the local government division, Ministry of Housing and Local Government Malaysia, to answer the research objective. The data were received on November 2021 by email. Furthermore, through the literature review, the most significant challenges in property tax reassessment were identified, compared and presented.

The results highlight that property tax reassessment implementation in West Malaysia is at the level of concern where only two councils have the latest tone of the list. However, larger councils have a higher performance compared to smaller councils. The findings also reveal various challenges in property tax reassessment, such as insufficient human resources, inadequate property systems and software and lack of financial capacity. Others include a shortage of competent assessors, lower public education, political interference and socioeconomic uncertainty.

This study offers practical implications to policy and decision-makers in the West Malaysian local authorities. Despite inferior performance by West Malaysian local authorities, there is a need for conducting property tax reassessment activity to ensure the quality and uniformity of the assessment. This study suggests that local government stakeholders and managers should devote more attention to formulating long-term plans and promoting the property tax reassessment practice. The property tax reform could solve the current situation of substandard reassessment activity.

This study explains, compares and interprets the actual statistical data through the figures and summarises the challenges of property tax reassessment activity among local authorities.

As an advanced manufacturing method, additive manufacturing (AM) technology provides new possibilities for efficient production and design of parts. However, with the continuous expansion of the application of AM materials, subtractive processing has become one of the necessary steps to improve the accuracy and performance of parts. In this paper, the processing process of AM materials is discussed in depth, and the surface integrity problem caused by it is discussed.

Firstly, we listed and analyzed the characterization parameters of metal surface integrity and its influence on the performance of parts and then introduced the application of integrated processing of metal adding and subtracting materials and the influence of different processing forms on the surface integrity of parts. The surface of the trial-cut material is detected and analyzed, and the surface of the integrated processing of adding and subtracting materials is compared with that of the pure processing of reducing materials, so that the corresponding conclusions are obtained.

In this process, we also found some surface integrity problems, such as knife marks, residual stress and thermal effects. These problems may have a potential negative impact on the performance of the final parts. In processing, we can try to use other integrated processing technologies of adding and subtracting materials, try to combine various integrated processing technologies of adding and subtracting materials, or consider exploring more efficient AM technology to improve processing efficiency. We can also consider adopting production process optimization measures to reduce the processing cost of adding and subtracting materials.

With the gradual improvement of the requirements for the surface quality of parts in the production process and the in-depth implementation of sustainable manufacturing, the demand for integrated processing of metal addition and subtraction materials is likely to continue to grow in the future. By deeply understanding and studying the problems of material reduction and surface integrity of AM materials, we can better meet the challenges in the manufacturing process and improve the quality and performance of parts. This research is very important for promoting the development of manufacturing technology and achieving success in practical application.

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.