792 resultados para confirmatory factor analysis


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In the current era of global economic instability, business and industry have already identified a widening gap between graduate skills and employability. An important element of this is the lack of entrepreneurial skills in graduates. This Teaching Fellowship investigated two sides of a story about entrepreneurial skills and their teaching. Senior players in the innovation commercialisation industry, a high profile entrepreneurial sector, were surveyed to gauge their needs and experiences of graduates they employ. International contexts of entrepreneurship education were investigated to explore how their teaching programs impart the skills of entrepreneurship. Such knowledge is an essential for the design of education programs that can deliver the entrepreneurial skills deemed important by industry for future sustainability. Two programs of entrepreneurship education are being implemented at QUT that draw on the best practice exemplars investigated during this Fellowship. The QUT Innovation Space (QIS) focuses on capturing the innovation and creativity of students, staff and others. The QIS is a physical and virtual meeting and networking space; a connected community enhancing the engagement of participants. The Q_Hatchery is still embryonic; but it is intended to be an innovation community that brings together nascent entrepreneurial businesses to collaborate, train and support each other. There is a niche between concept product and business incubator where an experiential learning environment for otherwise isolated ‘garage-at-home’ businesses could improve success rates. The QIS and the Q_Hatchery serve as living research laboratories to trial the concepts emerging from the skills survey. The survey of skills requirements of the innovation commercialisation industry has produced a large and high quality data set still being explored. Work experience as an employability factor has already emerged as an industry requirement that provides employee maturity. Exploratory factor analysis of the skills topics surveyed has led to a process-based conceptual model for teaching and learning higher-order entrepreneurial skills. Two foundational skills domains (Knowledge, Awareness) are proposed as prerequisites which allow individuals with a suite of early stage entrepreneurial and behavioural skills (Pre-leadership) to further leverage their careers into a leadership role in industry with development of skills around higher order elements of entrepreneurship, management in new business ventures and progressing winning technologies to market. The next stage of the analysis is to test the proposed model through structured equation modelling. Another factor that emerged quickly from the survey analysis broadens the generic concept of team skills currently voiced in Australian policy documents discussing the employability agenda. While there was recognition of the role of sharing, creating and using knowledge in a team-based interdisciplinary context, the adoption and adaptation of behaviours and attitudes of other team members of different disciplinary backgrounds (interprofessionalism) featured as an issue. Most undergraduates are taught and undertake teamwork in silos and, thus, seldom experience a true real-world interdisciplinary environment. Enhancing the entrepreneurial capacity of Australian industry is essential for the economic health of the country and can only be achieved by addressing the lack of entrepreneurial skills in graduates from the higher education system. This Fellowship has attempted to address this deficiency by identifying the skills requirements and providing frameworks for their teaching.

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Purpose – The purpose of this paper is to segment primary male grocery shoppers based on store and product attribute evaluations. A rich profile for each segment is developed. These developed contemporary shopper typologies are contrasted against earlier works. Design/methodology/approach – Data of 280 male grocery shoppers was attained by a survey questionnaire. Factor analysis, cluster analysis and ANOVA were employed to develop specific segments of male shoppers. Findings – Four distinct cohorts of male shoppers emerge from the data of eight constructs, measured by 46 items. One new shopper type, not found in earlier typology literature, emerged from this research. This shopper presented as young, well educated, at the commencement of their career and family lifecycle, attracted by a strong value offer and willingness to share the family food shopping responsibilities. Practical implications – Research outcomes encourage supermarket retailers to implement targeted marketing and rationalized operational strategies that deliver on attributes of importance. Originality/value – This research makes a contribution to segmentation literature and grocery retail practice in several ways. It presents the first retail typology of male supermarket shoppers, employing a cluster analysis technique. The research provides insights into the modern family food shopping behaviour of men, a channel in which men are now recognised as equal contributors. The research provides the basis for further gender comparative and cross-contextual studies.

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The benefits of applying tree-based methods to the purpose of modelling financial assets as opposed to linear factor analysis are increasingly being understood by market practitioners. Tree-based models such as CART (classification and regression trees) are particularly well suited to analysing stock market data which is noisy and often contains non-linear relationships and high-order interactions. CART was originally developed in the 1980s by medical researchers disheartened by the stringent assumptions applied by traditional regression analysis (Brieman et al. [1984]). In the intervening years, CART has been successfully applied to many areas of finance such as the classification of financial distress of firms (see Frydman, Altman and Kao [1985]), asset allocation (see Sorensen, Mezrich and Miller [1996]), equity style timing (see Kao and Shumaker [1999]) and stock selection (see Sorensen, Miller and Ooi [2000])...

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A pilot study has produced 31 groundwater samples from a coal seam gas (CSG) exploration well located in Maramarua, New Zealand. This paper describes sources of CSG water chemistry variations, and makes sampling and analytical recommendations to minimize these variations. The hydrochemical character of these samples is studied using factor analysis, geochemical modelling, and a sparging experiment. Factor analysis unveils carbon dioxide (CO2) degassing as the principal cause of sample variation (about 33%). Geochemical modelling corroborates these results and identifies minor precipitation of carbonate minerals with degassing. The sparging experiment confirms the effect of CO2 degassing by showing a steady rise in pH while maintaining constant alkalinity. Factor analysis correlates variations in the major ion composition (about 17%) to changes in the pumping regime and to aquifer chemistry variations due to cation exchange reactions with argillaceous minerals. An effective CSG water sampling program can be put into practice by measuring pH at the well head and alkalinity at the laboratory; these data can later be used to calculate the carbonate speciation at the time the sample was collected. In addition, TDS variations can be reduced considerably if a correct drying temperature of 180°C is consistently implemented.

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Coal Seam Gas (CSG) production is achieved by extracting groundwater to depressurize coal seam aquifers in order to promote methane gas desorption from coal micropores. CSG waters are characteristically alkaline, have a neutral pH (~7), are of the Na-HCO3-Cl type, and exhibit brackish salinity. In 2004, a CSG exploration company carried out a gas flow test in an exploration well located in Maramarua (Waikato Region, New Zealand). This resulted in 33 water samples exhibiting noteworthy chemical variations induced by pumping. This research identifies the main causes of hydrochemical variations in CSG water, makes recommendations to manage this effect, and discusses potential environmental implications. Hydrochemical variations were studied using Factor Analysis and this was supported with hydrochemical modelling and a laboratory experiment. This reveals carbon dioxide (CO2) degassing as the principal source of hydrochemical variability (about 33%). Factor Analysis also shows that major ion variations could also reflect changes in hydrochemical composition induced by different pumping regimes. Subsequent chloride, calcium, and TDS variations could be a consequence of analytical errors potentially committed during laboratory determinations. CSG water chemical variations due to degassing during pumping can be minimized with good completion and production techniques; variations due to sample degassing can be controlled by taking precautions during sampling, transit, storage and analysis. In addition, the degassing effect observed in CSG waters can lead to an underestimation of their potential environmental effect. Calcium precipitation due to exposure to normal atmospheric pressure results in a 23% increase in SAR values from Maramarua CSG water samples.

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The purpose of this paper is to segment male and female grocery shoppers based on store and product attribute evaluations. A rich profile for each segment is developed. Gender comparisons are operationalised and these developed contemporary shopper typologies are further contrasted against earlier works. Data of 560 grocery shoppers was attained by a survey questionnaire. Factor analysis, cluster analysis and ANOVA were employed to develop specific segments of shoppers. Four distinct cohorts of male shoppers and three cohorts of female shoppers emerge from the data of eight constructs, measured by 46 items. One new shopper type, not found in earlier typology literature, emerged from this research. This shopper presented as a young, well educated, at the commencement of their career and family lifecycle, attracted by a strong value offer and willingness to share the family food shopping responsibilities. This research makes a contribution to segmentation literature and grocery retail practice in several ways. It presents the first retail typology of male supermarket shoppers, employing a cluster analysis technique. Comparisons between male and female grocery shopping typologies are accordingly facilitated. The research provides insights into the modern family food shopping behaviour of men; a channel in which men are now recognised as equal contributors. Research outcomes encourage supermarket retailers to implement targeted marketing and rationalized operational strategies that deliver on attributes of importance. Finally, this research provides the basis for further cross-cultural, cross-contextual comparative studies.

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This paper investigates the use of mel-frequency deltaphase (MFDP) features in comparison to, and in fusion with, traditional mel-frequency cepstral coefficient (MFCC) features within joint factor analysis (JFA) speaker verification. MFCC features, commonly used in speaker recognition systems, are derived purely from the magnitude spectrum, with the phase spectrum completely discarded. In this paper, we investigate if features derived from the phase spectrum can provide additional speaker discriminant information to the traditional MFCC approach in a JFA based speaker verification system. Results are presented which provide a comparison of MFCC-only, MFDPonly and score fusion of the two approaches within a JFA speaker verification approach. Based upon the results presented using the NIST 2008 Speaker Recognition Evaluation (SRE) dataset, we believe that, while MFDP features alone cannot compete with MFCC features, MFDP can provide complementary information that result in improved speaker verification performance when both approaches are combined in score fusion, particularly in the case of shorter utterances.

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Confidence in a professional role is a key element in the successful transition to competent practice. New graduate dietitians report that whilst they are confident about their general dietetic ability, they are not as confident when working with clients experiencing depression and anxiety. This study aimed to develop and validate a scale which measured confidence about working with clients with depression/anxiety. The 21-item Dietetics Collaborative Practice Scale was developed using research about dietetic practice in mental health, coping self-efficacy literature and collaboration with industry experts. A convenience sample of 189 Australian dietitians completed the questionnaire. Exploratory factor analysis suggests that dietetic confidence is best represented by a two dimensional solution consisting of (a) Client –focused practice (CFP, 50.8% variance) and (b) Advocacy for self and client care (ASC, 9.7% variance). The alpha coefficient of both dimensions (CFP ɑ=0.95, ASC ɑ=0.84) demonstrated the internal consistency of components. Combined, these two components account for 60.5% of variance. The scale components were not related to years of practice or working with mental health clients but were significantly related to overall dietetic confidence (ODC). Correlation coefficients between ODC and CFP were 0.501 (p<0.01), ODC and ASC were correlated at 0.465 (p<0.01) and CFP and number of years as a dietitian were weakly correlated at 0.24 (p<0.05). Results have implications for dietetic training and professional development. Client focus and advocacy for self and client appear to be important factors in overall confidence as a dietitian.

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The aim of this research was to develop and assess the psychometric properties of the Coach Motivation Questionnaire (CMQ). Study 1 focused on the compilation and pilot testing of potential questionnaire items. Consistent with self-determination theory, items were devised to tap into six forms of motivation: amotivation, external regulation, introjected regulation, identified regulation, integrated regulation, and intrinsic motivation. The purpose of the second study (N = 556) was to empirically examine the psychometric properties of the CMQ. Items were subjected to confirmatory factor analyses to determine the fit of the a priori model. In addition, the validity of the questionnaire was assessed through links with the theoretically related concepts of intrinsic need satisfaction, well-being, and goal orientation. Together with test–retest reliability (Study 3), these results showed preliminary support for the psychometric properties of the CMQ. Finally, using an independent sample (N = 254), the fourth study confirmed the factor structure and supports the use of the CMQ in future coaching research.

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This paper proposes the use of Bayesian approaches with the cross likelihood ratio (CLR) as a criterion for speaker clustering within a speaker diarization system, using eigenvoice modeling techniques. The CLR has previously been shown to be an effective decision criterion for speaker clustering using Gaussian mixture models. Recently, eigenvoice modeling has become an increasingly popular technique, due to its ability to adequately represent a speaker based on sparse training data, as well as to provide an improved capture of differences in speaker characteristics. The integration of eigenvoice modeling into the CLR framework to capitalize on the advantage of both techniques has also been shown to be beneficial for the speaker clustering task. Building on that success, this paper proposes the use of Bayesian methods to compute the conditional probabilities in computing the CLR, thus effectively combining the eigenvoice-CLR framework with the advantages of a Bayesian approach to the diarization problem. Results obtained on the 2002 Rich Transcription (RT-02) Evaluation dataset show an improved clustering performance, resulting in a 33.5% relative improvement in the overall Diarization Error Rate (DER) compared to the baseline system.

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Research has shown that a strong relationship exists between belongingness and depressive symptoms; however, the contribution of specific types of belongingness remains unknown. Participants (N=369) completed the sense of belonging instrument, psychological sense of organizational membership, and the depression scale of the depression anxiety stress scales. Factor analysis demonstrated that workplace and general belongingness are distinct constructs. When regressed onto depressive symptoms, these belongingness types made independent contributions, together accounting for 45% of variance, with no moderation effects evident. Hence, general belongingness and specific workplace belongingness appear to have strong additive links to depressive symptoms. These results add support to the belongingness hypothesis and sociometer theory and have significant implication for depression prevention and treatment

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This study explored preservice teacher attitudes towards teaching a deaf student who uses Australian Sign Language (Auslan) compared to a student who is new to Australia and speaks Polish. The participants were 200 preservice teachers in their third or fourth year of university education. A questionnaire was created to measure attitudes, and participants were also asked to list teaching strategies they would use with the two students. A factor analysis yielded two subscales: Teacher Expectations and Teacher Confidence. Results showed that teachers had higher expectations of the Auslan student than the Polish student, and were more confident about teaching the Auslan student. Differences between the two conditions were also found for suggested teaching strategies. The findings have implications for teacher education programs.

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In order to drive sustainable financial profitability, service firms make significant investments in creating service environments that consumers will prefer over the environments of their competitors. To date, servicescape research is over-focused on understanding consumers’ emotional and physiological responses to servicescape attributes, rather than taking a holistic view of how consumers cognitively interpret servicescapes. This thesis argues that consumers will cognitively ascribe symbolic meanings to servicescapes and then evaluate if those meanings are congruent with their sense of Self in order to form a preference for a servicescape. Consequently, this thesis takes a Self Theory approach to servicescape symbolism to address the following broad research question: How do ascribed symbolic meanings influence servicescape preference? Using a three-study, mixed-method approach, this thesis investigates the symbolic meanings consumers ascribe to servicescapes and empirically tests whether the joint effects of congruence between consumer Self and the symbolic meanings ascribed to servicescapes influence consumers’ servicescape preference. First, Study One identifies the symbolic meanings ascribed to salient servicescape attributes using a combination of repertory tests and laddering techniques within 19 semi-structured individual depth interviews. Study Two modifies an existing scale to create a symbolic servicescape meaning scale in order to measure the symbolic meanings ascribed to servicescapes. Finally, Study Three utilises the Self-Congruity Model to empirically examine the joint effects of consumer Self and servicescape on consumers’ preference for servicescapes. Using polynomial regression with response surface analysis, 14 joint effect models demonstrate that both Self-Servicescape incongruity and congruity influence consumers’ preference for servicescapes. Combined, the findings of three studies suggest that the symbolic meanings ascribed to servicescapes and their (in)congruities with consumers’ sense of self can be used to predict consumers’ preferences for servicescapes. These findings have several key theoretical and practical contributions to services marketing.

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Speaker diarization determines instances of the same speaker within a recording. Extending this task to a collection of recordings for linking together segments spoken by a unique speaker requires speaker linking. In this paper we propose a speaker linking system using linkage clustering and state-of-the-art speaker recognition techniques. We evaluate our approach against two baseline linking systems using agglomerative cluster merging (AC) and agglomerative clustering with model retraining (ACR). We demonstrate that our linking method, using complete-linkage clustering, provides a relative improvement of 20% and 29% in attribution error rate (AER), over the AC and ACR systems, respectively.