Search results

Occupant feedback is crucial for healthy, comfortable and productive offices. Existing facility management (FM) systems are limited in effective use of occupant feedback, as they fail to collect the vital contextual information (e.g. related building element, space) associated with the feedback. The purpose of this study is to formalise the contextual information requirements for structured collection of occupant feedback for rapid diagnosis and resolution of problems and integrating occupant feedback with building information modelling (BIM) for making use of its visualisation and analysis capabilities, and eventually for effective use of occupant feedback in FM operations.

A mixed-methods approach was conducted in four steps: (1) identifying occupant feedback types (e.g. echo in meeting room) in office buildings, (2) examining the current practice in collecting and processing occupant feedback via use cases, (3) determining the contextual information requirements via expert interviews and (4) validation of the information requirements via a BIM-integrated prototype.

The findings present the contextual information requirements for 107 occupant feedback types grouped under thermal comfort, indoor air quality, acoustic comfort, visual comfort, building design and facility services.

Feedback-specific contextual information items enable structured data collection and help to avoid missing data and minimise the time lost in manual data entry and recursive interaction with the occupants during FM operations.

The contextual information requirements determined are expected to enhance occupant satisfaction and FM performance in office buildings by better use of the occupant feedback and integration into BIM-enabled FM and can be extended to other building types in future studies by using the proposed methodology.

The purpose of this study is not only to develop an integrated model of subjective well-being (SWB) by using confirmatory factor analysis (CFA) and structural equation modeling (SEM) but also to prioritize the subfactors of personality and SWB that affect the contextual performance (CP) of an employee by using a fuzzy-analytical hierarchy process (FAHP), which has not been done in the past.

The data were collected from 15 field experts and 412 employees of information technology (IT) companies operating in India. The data analysis was performed in two stages. The first stage includes CFA and SEM. The second stage includes prioritizing the factor through FAHP.

The results of SEM analysis manifested that all the dimensions of personality have a significant impact on CP. However, in the case of SWB, only two components (satisfaction with life and positive affect) have a significant impact on CP. Results of FAHP show that SWB is more important in predicting CP than the Big Five personality dimensions.

This research is a novel attempt to test and prioritize the factors affecting the CP of IT employees. The findings of the research will be useful for managers in increasing the performance of their employees. Further, the findings of the research will contribute to the literature on the factors affecting CP.

As a business executive and philanthropist, Mary Kay Ash is legendary as a glass-ceiling breaker. With the belief that Mary Kay Ash is both modern and relevant, while simultaneously legendary, the overall purpose of this paper is to explore the role of Mary Kay Ash as an influential entrepreneur. This research responds to the call by Cogliser and Brigham (2004) for an increased understanding of how entrepreneurial leaders influence, challenge, inspire and develop followers.

Following on research by Hoppe (2013), this objective was accomplished via a pentadic analysis of Mary Kay Ash’s rhetoric aimed to influence the mental mindset of readers (followers) over the course of generations. Burke’s pentad was the sense-making tool used for examining Ash’s rhetoric of influence as an entrepreneurial leader. The data used in the pentadic analysis were also analyzed via Linguistic Inquiry and Word Count (LIWC) and IBM Watson Emotion Analysis to see where analyses might converge or diverge.

Based on the analysis of her written work, Mary Kay Ash resided at the intersection of leadership and entrepreneurship and, in so doing, was an influencer. Her primary rhetorical approach to influencing was idealism. Interwoven in her writings, she also exhibited both pragmatism and realism. She knew that she had to start the business to have the future she desired and that she needed to train her team appropriately for success to be forthcoming. The motivation in Mary Kay Ash’s rhetoric was that of influencing people so they would be the best that they could be.

Qualitative research brings with it an array of inevitable research problems. Pentadic analysis cannot be judged by the basic objective standards of reliability and validity because objective reality does not exist in personal interpretation. That is, one person as a critic cannot be impartial because the interpretation is only one personal way of viewing the data and another critic might view the same pentads and come up with different ratios. With this subjectivity in mind, however, the data used in the pentadic analysis were also analyzed via LIWC and IBM Watson Emotion Analysis to see where analyses might converge or diverge.

The findings from this research denote clearly that Mary Kay Ash was a forerunner of the modern day influencer. As a primogenitor of the influencer marketing phenomenon, Mary Kay Ash’s entrepreneurial legacy is expected to continue through generations of followers. This finding speaks to the importance of today’s entrepreneurs using the spoken and written word to influence others and create a lasting organizational legacy.

Countless scholars have used pentadic analysis, with a variety of artifacts, to examine the motives behind the rhetoric. However, rhetoric as a means of persuasion and influence has received little attention within the context of the written works by management gurus (Jones et al., 2009), and, aside from the exploration by Berglund and Wigren (2012), the narrative of entrepreneurial influence has not benefitted from close examination.

The purpose of this study is to investigate the entropy generation in different nanofluids flow over a vertically moving rotating disk. Unlike the classical Karman flow, water-based nanofluids have various suspended nanoparticles, namely, Cu, Ag, Al₂O₃ and TiO₂, and the disk is also moving vertically with time-dependent velocity.

The Keller box technique numerically solves the governing equations after reduction by suitable similarity transformations. The shear stress and heat transport features, along with flow and temperature fields, are numerically computed for different concentrations of the nanoparticles.

This study is done comparatively in between different nanofluids and for the cases of vertical movement of the disk. It is found that heat transfer characteristics rely not only on considered nanofluid but also on disk movement. Moreover, the upward movement of the disk diminishes the heat-transfer characteristics of the fluid for considered nanoparticles. In addition, for the same group of nanoparticles, an entropy generation study is also performed, and an increasing trend is found for all nanoparticles, with alumina nanoparticles dominating the others.

This research is a novel work on a vertically moving rotating surface for the water-conveying nanoparticle fluid flow with entropy generation analysis. The results were found to be in good agreement in the case of pure fluid.

The calculation and design of the structures are carried out with the aim of obtaining a sufficiently ductile behavior to allow the structure to undergo displacements, without risk of sudden breaks or loss of stability. The purpose of this study is to develop and validate a computer program (Thin beam2), allowing the modeling and simulation of the nonlinear behavior of reinforced concrete elements, on the other part, it is estimating the local and global ductility of the sections or elements constituting these structures.

The authors present two nonlinear analysis methods to carry out a parametric study of the factors influencing the local and global ductility of reinforced concrete structures. The first consists in evaluating the nonlinear behavior at the level of the cross-section of the reinforced concrete elements used in the elaborate Sectenol 1 program, it allows us to have the local ductility. The second, allows us to evaluate the nonlinear behavior of the element used in the modified thin beam 2 program, it allows us to estimate the overall ductility of the element.

The validation results of the Thin beam2 program are very satisfactory, by conferring the analytic and experimental results obtained by various researchers and the parametric study shows that each factor such as the compressive strength of the concrete has a favorable effect on ductility. Conversely, the normal compression force and the high resistance of tensioned reinforcements adversely affect ductility.

The reliability of the two programs lies in obtaining the local and global ductility of reinforced concrete structures because the calculation and design of the structures are carried out with the aim of obtaining ductile behavior without risk of breakage and instability.

AlSi10Mg alloy is commonly used in laser powder bed fusion due to its printability, relatively high thermal conductivity, low density and good mechanical properties. However, the thermal conductivity of as-built materials as a function of processing (energy density, laser power, laser scanning speed, support structure) and build orientation, are not well explored in the literature. This study aims to elucidate the relationship between processing, microstructure, and thermal conductivity.

The thermal conductivity of laser powder bed fusion (L-PBF) AlSi10Mg samples are investigated by the flash diffusivity and frequency domain thermoreflectance (FDTR) techniques. Thermal conductivities are linked to the microstructure of L-PBF AlSi10Mg, which changes with processing conditions. The through-plane exceeded the in-plane thermal conductivity for all energy densities. A co-located thermal conductivity map by frequency domain thermoreflectance (FDTR) and crystallographic grain orientation map by electron backscattered diffraction (EBSD) was used to investigate the effect of microstructure on thermal conductivity.

The highest through-plane thermal conductivity (136 ± 2 W/m-K) was achieved at 59 J/mm³ and exceeded the values reported previously. The in-plane thermal conductivity peaked at 117 ± 2 W/m-K at 50 J/mm³. The trend of thermal conductivity reducing with energy density at similar porosity was primarily due to the reduced grain size producing more Al-Si interfaces that pose thermal resistance. At these interfaces, thermal energy must convert from electrons in the aluminum to phonons in the silicon. The co-located thermal conductivity and crystallographic grain orientation maps confirmed that larger colonies of columnar grains have higher thermal conductivity compared to smaller columnar grains.

The thermal properties of AlSi10Mg are crucial to heat transfer applications including additively manufactured heatsinks, cold plates, vapor chambers, heat pipes, enclosures and heat exchangers. Additionally, thermal-based nondestructive testing methods require these properties for applications such as defect detection and simulation of L-PBF processes. Industrial standards for L-PBF processes and components can use the data for thermal applications.

To the best of the authors’ knowledge, this paper is the first to make coupled thermal conductivity maps that were matched to microstructure for L-PBF AlSi10Mg aluminum alloy. This was achieved by a unique in-house thermal conductivity mapping setup and relating the data to local SEM EBSD maps. This provides the first conclusive proof that larger grain sizes can achieve higher thermal conductivity for this processing method and material system. This study also shows that control of the solidification can result in higher thermal conductivity. It was also the first to find that the build substrate (with or without support) has a large effect on thermal conductivity.

Knowledge management (KM) significantly affects supply chain management (SCM) and its performance in today's highly competitive corporate climate. It is crucial to consider this relationship to achieve optimal supply chain performance (SCP). This study aims to assess this impact by defining and examining the multi-dimensional relationships between KM Process Elements (KMPEs) and SCP Evaluation Criteria (SCPEC) within a comprehensive theoretical framework.

Integrating KMPEs and SCPEC becomes an uncertain decision-making problem due to data deficiency and the vagueness of decision-makers’ judgments. To address uncertainties, this study uses interval-valued neutrosophic (IVN) sets and proposes an IVN model consisting of SWARA, which is one of the effective multi-criteria decision-making (MCDM) approaches, and house of quality (HOQ) methods. IVN-SWARA is used to weight the SCPEC while IVN-HOQ establishes relationships and prioritizes the KMPEs and SCPEC.

The results show that reliability is the most significant SCP evaluation criterion. Among the KMPEs, capitalization, sharing, and transfer exhibit stronger associations with the SCPEC compared to the other elements. Capitalization as one of the KMPEs was found to be the most critical one, and efficiency is the criterion most affected by all elements of the KM process.

This study uses innovative methodologies to evaluate the adoption of KM processes on SCP under uncertain environments and involving multi-decision-makers. The proposed integrated model demonstrates flexibility and practicality in combining KM and SCM, leading to improved SCP. Notably, this study presents the development of IVN-SWARA and the use of the integrated IVN-SWARA - IVN-HOQ decision tool, which are novel contributions to the existing literature.

In practical engineering, oil filters often work under asymmetric cyclic loading. In order to improve the prediction accuracy of fatigue life of the oil filters under asymmetric cyclic loading, the effect of strain ratio and low cycle fatigue plastic deformation on fatigue life need to be considered. This paper aims to discuss the aforementioned objective.

First, strain-controlled fatigue tests with strain ratios of 0, 0.5 and −1 were carried out on the oil filter material 2A70-T6 aluminum alloy, and the test data were used to obtain strain fatigue life curves at three strain ratios. Then, based on the idea of the constant life curve method, the average value of the ratio of the strain amplitude corresponding to different strain ratios under the same partial life was defined as the strain ratio factor. Finally, the elastic-plastic factor was modified by the strain ratio factor, and a new fatigue life prediction model considering the effect of strain ratio was proposed.

The proposed model was validated, respectively, by fatigue test data of 2A70-T6 aluminum alloy, 2124-T851 aluminum alloy and oil filter and the results of the proposed model were compared with the Coffin–Manson equation, Morrow model and Smith–Watson–Topper (SWT) model, showing that the proposed model had higher applicability and accuracy.

In this work, a strain ratio factor is established based on the idea of the constant life curve method, and the strain ratio factor is used to modify the introduced elastic-plastic factor, and then a new fatigue life prediction model considering the influence of strain ratio and low cycle fatigue plastic deformation on material fatigue damage accumulation is proposed. The results show that the prediction results of the proposed model are in good agreement with the experimental data, and the proposed model has good fatigue life prediction ability considering the influence of strain ratio and lays a foundation for the fatigue life prediction of the oil filter.

This study aims to provide a valuable contribution by exploring the moderating effect of women directors on the relationship between corporate social responsibility (CSR) and corporate tax avoidance of Malaysian listed companies.

The study is based on a sample consisting of 78 Malaysian firms over the 2010–2017 period. A moderation model that specifies the interaction between CSR, women directors and corporate tax avoidance motivates this study.

The results show that a high level of CSR is negatively associated with corporate tax avoidance in firms with a higher percentage of women on the board.

The findings may be of interest to the academic researchers, investors and regulators. For academic researchers, it is interested in discovering the dynamic relation between CSR, woman on the board and tax avoidance. For investors, the results show that the existence of female directors on the board reduces the corporate tax avoidance. For regulators, the results advise the worldwide policy maker to give the importance of female roles to improve the engagement firms in CSR reporting.

This paper extends the existing literature by examining the moderating effect of women directors on the relationship between CSR and corporate tax avoidance in the Malaysian context.

Conventional sportswear design does not take into account body size changes that many individuals experience (e.g. through pregnancy, puberty, menstruation, etc.). This paper aims to detail both the construction of a novel wearable shape-adaptive composite and a new meso-scale material design method, which enables the optimal creation of these structures.

This work reports the development of a predictive computational model and a corresponding design tool, including results of a tensile testing protocol to validate their outputs. A mathematical model was developed to explore the geometric parameter space of a bi-stable composite system, which then feeds into an optimization design tool.

The authors found that it is possible to fabricate shape-adaptive composites via 3D printing bi-stable structures, and adhering them to a base textile. Experimental mechanical tensile testing showed good agreement with the predictive model in mid-range unit cell amplitude designs. To illustrate how the optimization design tool works this paper details two design examples, one for expected shape change during pregnancy and one for targeted compression for high performance swimwear. The optimized design parameters are shown to replicate the target parameters, however there is potential for further improvement with a lower stiffness base textile.

Although there is a wealth of research on multi-stable mechanisms, there is a dearth of studies that apply these structures in the wearable composite space. Additionally, there is a need for design methods which leverage the structurally-programmable capabilities of multi-stable structures to create optimized, high-performance functional composites.