Career orientations of marketing employees : an empirical analysis

There is a distinct gap in research in marketing in relation to understanding the role of marketing employees in organisational marketing performance, in contrast to the usual focus on identifying the contribution of successfully completing marketing tasks in the pursuit of organisational marketing objectives. The major exception to this has been research related to sales personnel, as a subset of all marketing personnel, but even this has usually been from a sales management perspective and not principally from the viewpoint of individual employees. The current study explored the career orientations of marketing employees in relation to the demographic profile and other work-related characteristics of marketing employees. Operationalised by Schein's (1990) Career Orientations Inventory, the 'internal career' of 78 marketing employees at the Australian headquarters of a major multinational manufacturing firm was examined. Sample means indicated that 'Lifestyle', 'Technical Functionality', and 'Pure Challenge' were the dominant career orientations, but a 'General Managerial' orientation also emerged as important, when individual 'Career Anchors' were examined. An 'Entrepreneurial' anchor was found to be the least dominant of the eight anchors measured, which may be seen as somewhat surprising for Marketing employees. Significant relationships were found between some demographic variables and the dominant career orientations, but overall, career orientation tended to be unrelated to the demographic variables. Future research will examine the relationships between employee career orientation and individual position, and marketing productivity.

Student learning orientations : are there differences between age and gender?

The increasing diversity and mobility of students have challenged universities, world over, to review educational courses and delivery to provide a more satisfying learning environment to students. The continuous improvement of the 'quality' of teaching and learning is one of the key goals of universities endeavouring to fulfil their obligations as learning institutions. Using a revised SPQ2F instrument (Biggs, 2003, Biggs and Leung, 2001), this exploratory study undertakes a comparative analysis of the age and gender differences in the learning orientations of two groups of tertiary students in an Australian University. The results indicate that there are no significant differences in the learning orientations of students but on average they seem to demonstrate deep learning than surface learning although they may differ in terms of the learning contexts.

Comparative analysis of study orientations on on campus and offshore students

Understanding how students learn is fundamental in the quest for improving learning outcomes of students who are becoming increasingly diverse and mobile. Using a revised SPQ2F instrument (Biggs & Leung, 2001), this study undertakes a comparative analysis of the study approaches of on campus and offshore students and their perceptions of their learning strategies related to a marketing unit in an Australian university. The results indicate that the majority of students seem to adopt deep learning rather than surface learning approaches, though on campus students appear to have deep learning orientations compared with off shore campus students.

Determinants of visual size constancy in different orientations in light and darkness

This project was concerned with the perception of size constancy of simple, elongated and planar objects in the light and dark. The main findings are: transverse, vertical and medial axes give rise to different degrees of size constancy; true size and shape of the objects proved to be a factor in size constancy; the size-distance invariance hypothesis (SDIH) cannot explain underconstancy in the light, and perfect constancy in the dark.

Minimum spanning trees for valley and ridge characterization in digital elevation maps

Texture synthesis employs neighbourhood matching to generate appropriate new content. Terrain synthesis has the added constraint that new content must be geographically plausible. The profile recognition and polygon breaking algorithm (PPA) [Chang et al. 1998] provides a robust mechanism for characterizing terrain as systems of valley and ridge lines in digital elevation maps. We exploit this to create a terrain characterization metric that is robust, efficient to compute and is sensitive to terrain properties.

Terrain regions are characterized as a minimum spanning tree derived from a graph created from the sample points of the elevation map which are encoded as weights in the edges of the graph. This formulation allows us to provide a single consistent feature definition that is sensitive to the pattern of ridges and valleys in the terrain Alternative formulations of these weights provide richer characteristicmeasures and we provide examples of alternate definitions based on curvature and contour measures.

We show that the measure is robust, with a significant portion derived directly from information local to the terrain sample. Global terrain characteristics introduce the issue of over- and underconnected valley/ridge lines when working with sub-regions. This is addressed by providing two graph construction strategies, which respectively provide an upper bound on connectivity as a single spanning tree, and a lower bound as a forest of trees.

Efficient minimum spanning tree algorithms are adapted to the context of terrain data and are shown to provide substantially better performance than previous PPA implementations. In particular, these are able to characterize valley and ridge behaviour at every point even in large elevation maps, providing a measure sensitive to terrain features at all scales.

The resulting graph based formulation provides an efficient and elegant algorithm for characterizing terrain features. The measure can be calculated efficiently, is robust under changes of neighbourhood position, size and resolution and the hybrid measure is sensitive to terrain features both locally and globally.

Ridge regression for two dimensional locality preserving projection

Two Dimensional Locality Preserving Projection (2D-LPP) is a recent extension of LPP, a popular face recognition algorithm. It has been shown that 2D-LPP performs better than PCA, 2D-PCA and LPP. However, the computational cost of 2D-LPP is high. This paper proposes a novel algorithm called Ridge Regression for Two Dimensional Locality Preserving Projection (RR- 2DLPP), which is an extension of 2D-LPP with the use of ridge regression. RR-2DLPP is comparable to 2DLPP in performance whilst having a lower computational cost. The experimental results on three benchmark face data sets - the ORL, Yale and FERET databases - demonstrate the effectiveness and efficiency of RR-2DLPP compared with other face recognition algorithms such as PCA, LPP, SR, 2D-PCA and 2D-LPP.

Face recognition using kernel ridge regression

In this paper, we present novel ridge regression (RR) and kernel ridge regression (KRR) techniques for multivariate labels and apply the methods to the problem of face recognition. Motivated by the fact that the regular simplex vertices are separate points with highest degree of symmetry, we choose such vertices as the targets for the distinct individuals in recognition and apply RR or KRR to map the training face images into a face subspace where the training images from each individual will locate near their individual targets. We identify the new face image by mapping it into this face subspace and comparing its distance to all individual targets. An efficient cross-validation algorithm is also provided for selecting the regularization and kernel parameters. Experiments were conducted on two face databases and the results demonstrate that the proposed algorithm significantly outperforms the three popular linear face recognition techniques (Eigenfaces, Fisherfaces and Laplacianfaces) and also performs comparably with the recently developed Orthogonal Laplacianfaces with the advantage of computational speed. Experimental results also demonstrate that KRR outperforms RR as expected since KRR can utilize the nonlinear structure of the face images. Although we concentrate on face recognition in this paper, the proposed method is general and may be applied for general multi-category classification problems.

The influence of cultural orientations on cross-cultural negotiation

This study analysed a series of negotiation simulations conducted between English-speaking background Australians and Arabic-speaking background Gulf Cooperation Council (G.C.C.) nationals. The processes and behaviours of participants within their own cultures and across the two cultures were mapped and explained using prevalent cross-cultural communication theories.

The hedonic and eudaimonic validity of the orientations to happiness scale

The orientations to happiness scale (OTH) was designed to measure three routes to happiness: pleasure (hedonia), meaning (eudaimonia) and engagement (flow). Past research utilising the scale suggests that all orientations predict life satisfaction, with meaning and engagement the stronger predictors relative to pleasure. However, these findings are inconsistent with other research; one plausible explanation being that the OTH scale lacks validity. This was tested by having participants (N = 107) complete the OTH scale and the Satisfaction with Life scale, prior to completing an online diary reporting actual instances of hedonic and eudaimonic behaviour. Although meaning predicted eudaimonic behaviour, the pleasure orientation was unrelated to hedonic behaviour. Further, hedonic behaviour was more strongly related to life satisfaction than eudaimonic behaviour; inconsistent with OTH scale results. These findings challenge the validity of the OTH scale, and subsequently bring into question those conclusions drawn from past research utilising the OTH scale.