Effects of entrepreneurial knowledge on entrepreneurial intentions: a longitudinal study of selected South-east Asian business students

Drawing on the theory of planned behaviour, this study examines the direct and indirect effects of knowledge gained from a formal entrepreneurship education programme on an individual’s entrepreneurial intentions (EI). It tracks the changes in students’ entrepreneurial knowledge (EK), perceptions of desirability of, and self-efficacy in, engaging in entrepreneurship and the impact of those changes on students’ EI upon completion of an entrepreneurship course. It uses longitudinal survey data of 245 business students in a Philippine university. Using cross-lagged panel method and partial-least squares-based structural equation modelling, the study builds and tests the measurement and structural models to examine the hypothesised interactions of EK, perceived desirability of, self-efficacy towards entrepreneurship, and EI. The findings underscore the importance of developing knowledge to nurture students’ self-confidence and attitudinal propensity to engage in entrepreneurship.

Improved 2D‐HPLC of red wine by incorporating pre‐process signal‐smoothing algorithms

Twomultidimensional HPLC separations of an Australian red wine are presented, >70% of the available separation space was used. A porous graphitic carbon (PGC) stationary phase was used as the first dimension in both separations with both RP core–shell and hydrophilic interaction chromatography fully porous columns used separately in the second dimension. To overcome peak analysis problems caused by signal noise and low detection limits, the data were pre-processed with penalised least-squares smoothing. The PGC × RP combination separated 85 peaks with a spreading angle of 71 and the PGC × hydrophilic interaction chromatography separated 207 peaks with a spreading angle of 80. Both 2D-HPLC steps were completed in 76 min using a comprehensive stop-and-go approach. A smoothing step was added to peak-picking processes and was able to greatly reduce the number of false peaks present due to noise in the chromatograms. The required thresholds were not able to ignore the noise because of the small magnitude of the peaks; 1874 peaks were located in the non-smoothed PGC × RP separation that reduced to 227 peaks after smoothing was included.

Organisational and professional commitment of early career accountants: do mentoring and organisational ethical climate matter?

This study assesses the effects of mentoring and organisational ethical climate (OEC) on the organisational and professional commitment (PC) of early career accountants (ECAs) (i.e. accounting graduate recruits with three or less years of working experience). The empirical data are based on a questionnaire survey from 86 ECAs in Australian public accounting firms, and hypothesis testing utilises partial least squares analysis. Our results indicate when a career development style of mentoring is adopted there is greater organisational as well as PC. By contrast, a social support mentoring style has no significant impact on organisational commitment (OC) and a negative effect on PC. Further, our data also reveal OEC to be positively associated with OC, and OC in turn having a positive impact on PC. The results imply that fostering a career-focused mentoring environment and an OEC can increase an ECA's OC and PC. These results have various implications for human resource management at both the accounting firm and professional levels.

State dependent asymmetric loss and the consensus forecast of real U.S. GDP growth

It has been well documented that the consensus forecast from surveys of professional forecasters shows a bias that varies over time. In this paper, we examine whether this bias may be due to forecasters having an asymmetric loss function. In contrast to previous research, we account for the time variation in the bias by making the loss function depend on the state of the economy. The asymmetry parameter in the loss function is specified to depend on set state variables which may cause forecaster to intentionally bias their forecasts. We consider both the Lin–Ex and asymmetric power loss functions. For the commonly used Lin–Ex and Lin–Lin loss functions, we show the model can be easily estimated by least squares. We apply our methodology to the consensus forecast of real U.S. GDP growth from the Survey of Professional Forecasters. We find that forecast uncertainty has an asymmetric effect on the asymmetry parameter in the loss function dependent upon whether the economy is in expansion or contraction. When the economy is in expansion, forecaster uncertainty is related to an overprediction in the median forecast of real GDP growth. In contrast, when the economy is in contraction, forecaster uncertainty is related to an underprediction in the median forecast of real GDP growth. Our results are robust to the particular loss function that is employed in the analysis.

Development and evaluation of a raman flow cell for monitoring continuous flow reactions

We show how in-line Raman spectroscopy can be used to monitor both reactant and product concentrations for a heterogeneously catalysed Suzuki cross reaction operating in continuous flow. The flow system consisted of an HPLC pump to drive a homogeneous mixture of the reactants (4-bromobenzonitrile, phenylboronic acid, and potassium carbonate) through an oven heated (80°C) palladium catalyst immobilised on a silica monolith. A custom built PTFE in-line flow cell with a quartz window enabled the coupling of an Ocean Optics Raman spectrometer probe to monitor both the reactants and product (4-cyanobiphenyl). Calibration was based on obtaining multivariate spectral data in the range 1530 cm–1 and 1640 cm–1 and using partial least-squares regression (PLSR) to obtain a calibration model which was validated using gas chromatography–mass spectrometry (GCMS) analysis. In-line Raman monitoring of the reactant and product concentrations enable (i) determination of reaction kinetic information such as the empirical rate law and associated rate constant and (ii) optimisation of either the product conversion (61 % at 0.02 mL min–1 generating 17 g h–1) or product yield (14 % at 0.24 mL min–1 generating 53 g h–1).

Rapid discrimination and determination of polyunsaturated fatty acid composition in marine oils by FTIR Spectroscopy and Multivariate Data Analysis

A rapid analytical approach for discrimination and quantitative determination of polyunsaturated fatty acid (PUFA) contents, particularly eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), in a range of oils extracted from marine resources has been developed by using attenuated total reflection Fourier transform infrared spectroscopy and multivariate data analysis. The spectral data were collected without any sample preparation; thus, no chemical preparation was involved, but data were rather processed directly using the developed spectral analysis platform, making it fast, very cost effective, and suitable for routine use in various biotechnological and food research and related industries. Unsupervised pattern recognition techniques, including principal component analysis and unsupervised hierarchical cluster analysis, discriminated the marine oils into groups by correlating similarities and differences in their fatty acid (FA) compositions that corresponded well to the FA profiles obtained from traditional lipid analysis based on gas chromatography (GC). Furthermore, quantitative determination of unsaturated fatty acids, PUFAs, EPA and DHA, by partial least square regression analysis through which calibration models were optimized specifically for each targeted FA, was performed in both known marine oils and totally independent unknown n - 3 oil samples obtained from an actual commercial product in order to provide prospective testing of the developed models towards actual applications. The resultant predicted FAs were achieved at a good accuracy compared to their reference GC values as evidenced through (1) low root mean square error of prediction, (2) good coefficient of determination close to 1 (i.e., R 2≥ 0.96), and (3) the residual predictive deviation values that indicated the predictive power at good and higher levels for all the target FAs. © 2014 Springer Science+Business Media New York.

FTIR microspectroscopy for rapid screening and monitoring of polyunsaturated fatty acid production in commercially valuable marine yeasts and protists

The increase in polyunsaturated fatty acid (PUFA) consumption has prompted research into alternative resources other than fish oil. In this study, a new approach based on focal-plane-array Fourier transform infrared (FPA-FTIR) microspectroscopy and multivariate data analysis was developed for the characterisation of some marine microorganisms. Cell and lipid compositions in lipid-rich marine yeasts collected from the Australian coast were characterised in comparison to a commercially available PUFA-producing marine fungoid protist, thraustochytrid. Multivariate classification methods provided good discriminative accuracy evidenced from (i) separation of the yeasts from thraustochytrids and distinct spectral clusters among the yeasts that conformed well to their biological identities, and (ii) correct classification of yeasts from a totally independent set using cross-validation testing. The findings further indicated additional capability of the developed FPA-FTIR methodology, when combined with partial least squares regression (PLSR) analysis, for rapid monitoring of lipid production in one of the yeasts during the growth period, which was achieved at a high accuracy compared to the results obtained from the traditional lipid analysis based on gas chromatography. The developed FTIR-based approach when coupled to programmable withdrawal devices and a cytocentrifugation module would have strong potential as a novel online monitoring technology suited for bioprocessing applications and large-scale production.

Synchrotron-FTIR microspectroscopy enables the distinction of lipid accumulation in thraustochytrid strains through analysis of individual live cells

The superior characteristics of high photon flux and diffraction-limited spatial resolution achieved by synchrotron-FTIR microspectroscopy allowed molecular characterization of individual live thraustochytrids. Principal component analysis revealed distinct separation of the single live cell spectra into their corresponding strains, comprised of new Australasian thraustochytrids (AMCQS5-5 and S7) and standard cultures (AH-2 and S31). Unsupervised hierarchical cluster analysis (UHCA) indicated close similarities between S7 and AH-7 strains, with AMCQS5-5 being distinctly different. UHCA correlation conformed well to the fatty acid profiles, indicating the type of fatty acids as a critical factor in chemotaxonomic discrimination of these thraustochytrids and also revealing the distinctively high polyunsaturated fatty acid content as key identity of AMCQS5-5. Partial least squares discriminant analysis using cross-validation approach between two replicate datasets was demonstrated to be a powerful classification method leading to models of high robustness and 100% predictive accuracy for strain identification. The results emphasized the exceptional S-FTIR capability to perform real-time in vivo measurement of single live cells directly within their original medium, providing unique information on cell variability among the population of each isolate and evidence of spontaneous lipid peroxidation that could lead to deeper understanding of lipid production and oxidation in thraustochytrids for single-cell oil development.

Organisational and professional commitment of early career accountants: do mentoring and organisational ethical climate matter?

This study assesses the effects of mentoring and organisational ethical climate (OEC) on the organisational and professional commitment (PC) of early career accountants (ECAs) (i.e. accounting graduate recruits with three or less years of working experience). The empirical data are based on a questionnaire survey from 86 ECAs in Australian public accounting firms, and hypothesis testing utilises partial least squares analysis. Our results indicate when a career development style of mentoring is adopted there is greater organisational as well as PC. By contrast, a social support mentoring style has no significant impact on organisational commitment (OC) and a negative effect on PC. Further, our data also reveal OEC to be positively associated with OC, and OC in turn having a positive impact on PC. The results imply that fostering a career-focused mentoring environment and an OEC can increase an ECA's OC and PC. These results have various implications for human resource management at both the accounting firm and professional levels.

Indices for cashmere fleece competition and across farm comparisons: The role of staple length in identifying goats of higher cashmere production

A single focus on mean fibre diameter (MFD, μm) as the definition of cashmere quality overlooks the effects of fibre length, softness and fibre curvature on cashmere processing, textile quality and consumer acceptance. Many farmers overlook the importance of cashmere staple length (SL, cm) in their fleece assessments. We aimed to determine the importance of SL in comparison with MFD when evaluating cashmere production and to identify how across farm comparisons of cashmere fleeces can be objectively undertaken. A sample of 1244 commercial cashmere fleeces from goats originating from many Australian farms was used. Least squares models, relating the logarithm of clean cashmere production (CCMwt, g) to MFD and SL, were fitted. Six years of data from the Australian cashmere industry between farm fleece competitions were analysed to determine the relation between CCMwt and MFD. In the research flocks, adjusting CCMwt of individual goats across farms for MFD only accounted for 2% of the variance, whereas SL accounted for 39% of the variance. The least squares additive model involving only SL was: log10(CCMwt)=1.570+0.06010×SL. Thus CCMwt was proportional to: 100.06010×SL=1.1484SL. It was appropriate to adjust CCMwt for SL by a factor 1/1.1484(SL-SL0) where SL0 is a standard SL of 7.5cm. The between farm index for cashmere weight equals: cleancashmerestaplelengthindex=2.823×CCMwt/1.1484SL. For industry fleece competitions, regression analysis indicated that there was no association between cashmere production and MFD (P=0.81), similar to the research data. Adjusting CCMwt for MFD in across farm comparison and fleece competitions appears to be ineffective. For farm comparisons and in fleece competitions it is important to assess cashmere SL. The use of the Clean Cashmere Staple Length Index will provide a more robust comparison of cashmere productivity between farms as it is an indirect indicator of desirable skin secondary follicle development. The results have application in development projects where obtaining a cashmere MFD test is costly or unavailable. © 2013 Elsevier B.V.

ICT Interventions for girls : factors influencing ICT career intentions

Intervention programs aimed at promoting study and work opportunities in the Information and Communications Technology (ICT) field to schoolgirls have been encouraged to combat a decline in the interest among girls to study ICT at school. The goal of our study is to investigate the influence of such interventions on schoolgirls’ intentions to choose a career in the ICT field by analysing comprehensive survey data (n = 3577), collected during four interventions in Australia, using the Partial Least Squares method. Our study is also aimed at identifying other factors influencing ICT career intentions. We found that the attitude towards interventions has an indirect influence on ICT career intentions by affecting interest in ICT. Our results also challenge several existing theoretical studies by showing that factors that had previously been suggested as influencers were found to have little or no impact in this study, these being same-sex education and computer usage.

A general pose estimation algorithm in a multi-Kinect system

 Microsoft Kinect which has been primarily aimed at the computer gaming industry has been used in bio-kinematic research related implementations. A multi-Kinect system can be useful in exploiting spatial diversity to increase measurement accuracy. One of the main problems in deploying multi-Kinect systems is to estimate the pose, including the position and orientation of each Kinect. In this paper, a singular value decomposition (SVD) least-squares algorithm is extended to a more generic time-series based approach to solve this pose estimation problem utilising 3D positions of one or more joints in skeletons obtained from a multi-Kinect system. Additionally, computer simulations are performed to demonstrate the use and to evaluate the efficiency of the proposed algorithm. The former is further validated with a commercial Vicon system.

On exploratory factor analysis: a review of recent evidence, an assessment of current practice, and recommendations for future use

Exploratory factor analysis (hereafter, factor analysis) is a complex statistical method that is integral to many fields of research. Using factor analysis requires researchers to make several decisions, each of which affects the solutions generated. In this paper, we focus on five major decisions that are made in conducting factor analysis: (i) establishing how large the sample needs to be, (ii) choosing between factor analysis and principal components analysis, (iii) determining the number of factors to retain, (iv) selecting a method of data extraction, and (v) deciding upon the methods of factor rotation. The purpose of this paper is threefold: (i) to review the literature with respect to these five decisions, (ii) to assess current practices in nursing research, and (iii) to offer recommendations for future use. The literature reviews illustrate that factor analysis remains a dynamic field of study, with recent research having practical implications for those who use this statistical method. The assessment was conducted on 54 factor analysis (and principal components analysis) solutions presented in the results sections of 28 papers published in the 2012 volumes of the 10 highest ranked nursing journals, based on their 5-year impact factors. The main findings from the assessment were that researchers commonly used (a) participants-to-items ratios for determining sample sizes (used for 43% of solutions), (b) principal components analysis (61%) rather than factor analysis (39%), (c) the eigenvalues greater than one rule and screen tests to decide upon the numbers of factors/components to retain (61% and 46%, respectively), (d) principal components analysis and unweighted least squares as methods of data extraction (61% and 19%, respectively), and (e) the Varimax method of rotation (44%). In general, well-established, but out-dated, heuristics and practices informed decision making with respect to the performance of factor analysis in nursing studies. Based on the findings from factor analysis research, it seems likely that the use of such methods may have had a material, adverse effect on the solutions generated. We offer recommendations for future practice with respect to each of the five decisions discussed in this paper.

On the asymptotic distribution of the Dickey Fuller-GLS test statistic

In a very influential paper, Elliott et al. [Efficient tests for an autoregressive unit root. Econometrica. 1996;64:813–836] show that no uniformly most powerful test for the unit root testing problem exits, derive the relevant power envelope and characterize a family of point-optimal tests. As a by-product, they also propose a ‘generalized least squares (GLS) detrended’ version of the conventional Dickey–Fuller test, denoted DF-GLS, that has since then become very popular among practitioners, much more so than the point-optimal tests. In view of this, it is quite strange to find that, while conjectured in Elliott et al. [Efficient tests for an autoregressive unit root. Econometrica. 1996;64:813–836], so far there seems to be no formal proof of the asymptotic distribution of the DF-GLS test statistic. By providing three separate proofs, the current paper not only substantiates the required result, but also provides insight regarding the pros and cons of different methods of proof.