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The purpose of this paper is to investigate two areas of interest: first, to determine business student customer satisfiers that could be contributors to students’ current and predicted retention in a higher educational institution (HEI) and second, to use these satisfiers to inform HEI marketing planning.

The survey used 10 per cent of the sampling frame from the faculty total business students population. Descriptive statistics and correlation were employed to describe and measure the relationship between the teaching and non-teaching antecedents of student satisfaction and their five constructs (academic experience, teaching quality, campus life, facilities and placement support) and current and intended retention. Standard multiple regressions were run to measure the β and significant values of the composite variables as stated.

Quantitative results revealed that students were most satisfied with academic experience and it was also the most dominant predictor of students’ retention. Other elements such as quality teaching, facilities and internship, though important for student satisfaction, were not predictors of retention.

Findings based on one Malaysian institution could not be used as a representation of other institutions either locally or internationally.

Suggestions are made as to how HEIs can defend and safeguard their existing and future position by giving maximum attention to both “hard” and “soft” student satisfiers which would add customer value and strengthen their competitive position.

Based on teaching and non-teaching antecedents and constructs, enable HEIs to predict retention and so inform marketing planning in a highly competitive higher education environment.

Organisations involved in relief delivery tend to have cross-boundary mandates, which cause ambiguity of roles during delivery of relief services to the targeted victims. Having no clear role, specialisation affects service timeliness and increases resource duplication among the relief organisations. The objective of this study is to understand how organisational networks and organisational learning as complex adaptive system metaphors improve both organisational adaptability and role clarity in humanitarian logistics.

Using ordinary partial least squares regression through SmartPLS version 3.3.3, the authors tested the study hypotheses basing on survey data collected from 315 respondents who were selected randomly to complete a self-administered questionnaire from 101 humanitarian organisations. Common method bias (CMB) associated with surveys was minimised by implementing both procedural and post statistics methods.

The results indicate that organisational networks and organisational learning have a significant influence on organisational adaptability and role clarity. The results also show that organisational adaptability partially mediates in the relationship between organisational networks, organisational learning and role clarity.

The major limitation of the study is that the authors have used cross-sectional data to test this research hypotheses. However, this was minimised following Guide and Ketokivi's (2015) recommendation on how to address the limitations of cross-sectional data or the use of longitudinal data that can address CMB and endogeneity problems.

Managers in humanitarian organisations can use the authors’ framework to understand, first, how complex adaptive system competence can be used to create organisational adaptability and, second, how organisational adaptability can help organisational networks and organisational learning in improving role clarity among humanitarian organisations by collaboratively working together.

This research contributes to the existing body of knowledge in humanitarian logistics and supply chain management by empirically testing the anecdotal and conceptual evidence. The findings may be useful to managers who are contemplating the use of organisational networks, organisational learning and organisational adaptability to improve role clarity in disaster relief-related activities.

This paper aims to propose a new microfluidic portable experimental platform for quick detection of heavy metal ions (HMIs) in picomolar range. The experimental setup uses a microfabricated piezoresistive sensor (MPS) array of eight cantilevers with ion-selective self-assembled monolayer's (SAM).

Most of the components used in this experimental setup are battery operated and, hence, portable to perform the on-field experiments. HMIs (antigen) and thiol-based SAM (antibody) interaction start bending the microcantilever. This results in a change of resistance, which is directly proportional to the surface stress produced due to the mass of targeted HMIs. The authors have used Cysteamine and 4-Mercaptobenzoic acid as a thiol for creating SAM to test the sensitivity and identify the suitable thiol. Some of the cantilevers are blocked using acetyl chloride to use as a reference for error detection.

The portable experimental platform achieves very small detection time of 10-25 min with a lower limit of detection (LOD) 0.762 ng (6.05 pM) for SAM of Cysteamine and 4-Mercaptobenzoic acid to detect Mn2+ ions. This technique has excellent potential and capability to selectively detect Hg2+ ions as low as 2.43 pM/mL using SAM of Homocysteine (Hcys)-Pyridinedicarboxylic acid (PDCA).

As microcantilever is very thin and fragile, it is challenging to apply a surface coating to have selective detection using Nanadispenser. Some of the cantilevers get broken during this process.

The excessive use and commercialization of NPs are quickly expanding their toxic impact on health and the environment. Also, LOD is limited to nanomolar range. The proposed method used the combination of thin-film, NPs, and MEMS-based technology to overcome the limitation of NPs-based technique and have picomolar range of HMIs detection.

This paper aims to propose a semi-analytical benchmarking framework for enthalpy-based methods used in problems involving phase change with latent heat. The benchmark is based on a class of semi-analytical solutions of spatially symmetric Stefan problems in an arbitrary spatial dimension. Via a public repository this study provides a finite element numerical code based on the FEniCS computational platform, which can be used to test and compare any method of choice with the (semi-)analytical solutions. As a particular demonstration, this paper uses the benchmark to test several standard temperature-based implementations of the enthalpy method and assesses their accuracy and stability with respect to the discretization parameters.

The class of spatially symmetric semi-analytical self-similar solutions to the Stefan problem is found for an arbitrary spatial dimension, connecting some of the known results in a unified manner, while providing the solutions’ existence and uniqueness. For two chosen standard semi-implicit temperature-based enthalpy methods, the numerical error assessment of the implementations is carried out in the finite element formulation of the problem. This paper compares the numerical approximations to the semi-analytical solutions and analyzes the influence of discretization parameters, as well as their interdependence. This study also compares accuracy of these methods with other traditional approach based on time-explicit treatment of the effective heat capacity with and without iterative correction.

This study shows that the quantitative comparison between the semi-analytical and numerical solutions of the symmetric Stefan problems can serve as a robust tool for identifying the optimal values of discretization parameters, both in terms of accuracy and stability. Moreover, this study concludes that, from the performance point of view, both of the semi-implicit implementations studied are equivalent, for optimal choice of discretization parameters, they outperform the effective heat capacity method with iterative correction in terms of accuracy, but, by contrast, they lose stability for subcritical thickness of the mushy region.

The proposed benchmark provides a versatile, accessible test bed for computational methods approximating multidimensional phase change problems. The supplemented numerical code can be directly used to test any method of choice against the semi-analytical solutions.

While the solutions of the symmetric Stefan problems for individual spatial dimensions can be found scattered across the literature, the unifying perspective on their derivation presented here has, to the best of the authors’ knowledge, been missing. The unified formulation in a general dimension can be used for the systematic construction of well-posed, reliable and genuinely multidimensional benchmark experiments.

This paper aims to report an insightful portable microfluidic system for rapid and selective sensing of Hg²⁺ in the picomolar (pM) concentration using microcantilever-based piezoresistive sensor. The detection time for various laboratory-based techniques is generally 12–24 h. The majority of modules used in the proposed platform are battery oriented; therefore, they are portable and handy to carry-out on-field investigations.

In this study, the authors have incorporated the benefit of three technologies, i.e. thin-film, nanoparticles (NPs) and micro-electro-mechanical systems, to selectively capture the Hg²⁺ at the pM concentration. The morphology and topography of the proposed sensor are characterized using field emission scanning electron microscopy and verification of the experimental results using energy dispersive X-ray.

The proposed portable microfluidic system is able to perform the detection in 5 min with a limit of detection (LOD) of 0.163 ng (0.81 pM/mL) for Hg²⁺, which perfectly describes its excellent performance over other reported techniques.

A microcantilever-based technology is perfect for on-site detection, and a LOD of 0.163 ng (0.81 pM/mL) is outstanding compared to other techniques, but the fabrication of microcantilever sensor is complex.

Many researchers used NPs for heavy metal ions sensing, but the excess usage and industrialization of NPs are rapidly expanding harmful consequences on the human life and nature. Also, the LOD of the NPs-based method is limited to nanomolar concentration. The suggested microfluidic system used the benefit of thin-film and microcantilever devices to provide advancement over the NPs-based approach and it has a selective sensing in pM concentration.

The purpose of this work is to improve the air entrainment capacity of a concrete by using fine mineral admixtures such as fly ash (FA) and silica fume (SF) as cement substitute, and coal bottom ash (CBA) as fine aggregate substitute. Air entrainment capacity has been studied indirectly as a measure of heat resistance of concrete. Literature has suggested that mineral admixtures improve the air absorption in the paste component of the concrete, on the one hand, whereas they perform pore and grain size refinement, on the other, thereby reducing the air entrainment. CBA, which being porous, creates the possibility of air adsorption by the aggregate component. Therefore, the study finds out whether a double benefit of adding both of these materials will be achieved, or CBA will try to improve the deficiency in the air entrainment created by the mineral admixtures.

Air-entrained concrete (AEC) mixes were constituted in three groups. First group represents mixes with natural fine aggregates only, and second with 25% fine aggregates substituted by CBA. Progressively, the third group has 50% fine aggregates substituted with CBA. In all the three groups, cement was substituted with FA and SF @ 0%, 20% and 40%, and 0%, 5% and 10%, respectively, thereby creating four binary and four ternary mixes corresponding to each group. Compressive and flexural strength tests were conducted at 28 days on the concrete mixes pre and post high-temperature heat treatment, i.e. 100°C, 200°C and 400°C, respectively. This study also examines the microstructure characteristics of AEC after 14 days of curing via X-ray diffraction. Sorptivity test was also conducted to estimate the capillary and air-entrained voids in concrete.

It was found that a concrete mix containing 20% FA and 10% SF along with 50% CBA could give similar post-heated strength to a normal (without mineral admixtures) AEC. In AECs where only CBA is present and cement paste is not substituted, both of the pre- and post-heated strengths of concrete reduce. Also, some mixtures containing large amounts of mineral admixtures in concrete with nil CBA show a high reduction in post-heated strength though they show good pre-heated strength. Therefore, mineral admixtures and CBA complement each other in improving the post-heated strength. Air pore structure found from sorptivity test also verifies these results.

AEC is very helpful for insulation of buildings during summer season by absorbing heat waves. AEC containing FA and CBA reduces carbon footprint because of substitution of cement and it also helps to conserve natural resources by the use of CBA in place of fine aggregates.

Despite the growing numbers of internationally active nonprofit organizations (NPOs), research on various facets of NPOs’ internationalization has been limited. The purpose of this paper is to investigate the impact of target-country related factors on international market selection of NPOs.

Analysis is based on a logistic regression procedure using a self-compiled data set of 2,440 observations of de-facto entry or non-entry occurrences made by 19 large development-focused NPOs.

The study reveals that NPOs select target markets that are less developed, characterized by greater risk profiles, where other NPOs tend to cluster, and those that are preferred by their home-country governments. Moreover, findings suggest that with respect to institutional strength, NPOs balance mission to help strengthen institutions where needed, and avoidance of environments with extremely dysfunctional institutions, hence opting to operate in environments with medium levels of institutional strength.

The study only looked at external environmental factors, it must be acknowledged that a more complete understanding of NPO market selection decisions must also include variables internal to the organization. Further the study is based on a sample of NPOs dealing with poverty alleviation, which limits the generalization. Finally, the use of data from secondary sources creates its own limitations.

This study represents one of the few cross country studies done on the area, thus contributing for the development of the field.

The purpose of this paper is to design novel tunnel field effect transistor (TFET) using graphene nanoribbons (GNRs).

To design the proposed TFET, the bilayer GNRs (BLGNRs) have been used as the channel material. The BLGNR-TFET is designed in QuantumATK, depending on 2-D Poisson’s equation and non-equilibrium Green’s function (NEGF) formalism.

The performance of the proposed BLGNR-TFET is investigated in terms of current and voltage (I-V) characteristics and transconductance. Moreover, the proposed device performance is compared with the monolayer GNR-TFET (MLGNR-TFET). From the simulation results, it is investigated that the BLGNR-TFET shows high current and gain over the MLGNR-TFET.

This paper presents a new technique to design GNR-based TFET for future low power very large-scale integration (VLSI) devices.

The purpose of this paper is to examine what types of shipping knowledge are crucial in order for shipping companies to survive in dynamic business environment, and to investigate how the shipping knowledge affects the company’s performance (i.e. organizational innovation and logistics value). This paper also diagnoses the moderating effect of absorptive capacity on the relationship between the shipping knowledge and its effectiveness.

Based on the literature, a theoretical framework and relevant hypotheses are established so as to show associated relationships between shipping knowledge, absorptive capacity, and organizational innovation and logistics value. Data are collected for an empirical analysis and a moderated hierarchical regression analysis is conducted to test the hypotheses.

Results show that a high level of shipping knowledge has a positive influence on the organizational innovation and logistics value of shipping companies. The findings also indicate that, while the absorptive capacity of shipping companies moderates the positive impact of shipping knowledge on the logistics value, it directly affects the improvement of organizational innovation.

This research verifies that effective knowledge management of shipping companies plays a significant role in developing organizational innovation and improving logistics performance. The research findings provide shipping companies with a strategic insight into the identification of critical sources for competitive advantage and greater organizational performance from an organizational learning perspective.

This line of research is served as an indicator of a good strategic direction for the practitioners engaged in the maritime transport and logistics industry, in order for them to become better integrated entities in a global logistics system as well as maximize their competitive advantages.

This paper makes the first attempt in its kind at empirically examining the types of shipping knowledge and its overall effectiveness in terms of the improvement of organizational innovation and logistics value. The moderating role of absorptive capacity on the impact of knowledge on organizational performance has also been initiated in the maritime logistics research.

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.