Uncovering the root cause of ethnic difference in ability testing:differential test functioning, test familiarity and trait optimism as explanations of ethnic group differences

The present research represents a coherent approach to understanding the root causes of ethnic group differences in ability test performance. Two studies were conducted, each of which was designed to address a key knowledge gap in the ethnic bias literature. In Study 1, both the LR Method of Differential Item Functioning (DIF) detection and Mixture Latent Variable Modelling were used to investigate the degree to which Differential Test Functioning (DTF) could explain ethnic group test performance differences in a large, previously unpublished dataset. Though mean test score differences were observed between a number of ethnic groups, neither technique was able to identify ethnic DTF. This calls into question the practical application of DTF to understanding these group differences. Study 2 investigated whether a number of non-cognitive factors might explain ethnic group test performance differences on a variety of ability tests. Two factors – test familiarity and trait optimism – were able to explain a large proportion of ethnic group test score differences. Furthermore, test familiarity was found to mediate the relationship between socio-economic factors – particularly participant educational level and familial social status – and test performance, suggesting that test familiarity develops over time through the mechanism of exposure to ability testing in other contexts. These findings represent a substantial contribution to the field’s understanding of two key issues surrounding ethnic test performance differences. The author calls for a new line of research into these performance facilitating and debilitating factors, before recommendations are offered for practitioners to ensure fairer deployment of ability testing in high-stakes selection processes.

Brand extensions in emerging markets:theory development and testing in China

Brand extensions are increasingly used by multinational corporations in emerging markets such as China. However, understanding how consumers in the emerging markets evaluate brand extensions is hampered by a lack of research in the emerging markets contexts. To address the knowledge void, we built on an established brand extension evaluation framework in the West, namely Aaker and Keller (1990)1. Aaker , D. A. and Keller , K. L. 1990 . Consumer evaluations of brand extensions . Journal of Marketing , 54 ( 1 ) : 27 – 41 . [CrossRef], [Web of Science ®] View all references, and extended the model by incorporating two new factors: perceived fit based on brand image consistency and competition intensity in the brand extension category. The additions of two factors are made in recognition of the uniqueness of the considerations of consumers in the emerging markets in their brand extension evaluations. The extended model was tested by an empirical experiment using consumers in China. The results partly validated the Aaker and Keller model, and evidence that both newly added factors were significant in influencing consumers' evaluation of brand extensions was also found. More important, one new factor proposed, namely, consumer-perceived fit based on brand image consistency, was found to be more significant than all the factors in Aaker and Keller's original model, suggesting that the Aaker and Keller model may be limited in explaining how consumers in the emerging markets evaluate brand extensions. Further research implications and limitations are discussed in the paper.

Elaboration and testing of new methodologies for automatic abstracting

The primary objective of this research was to understand what kinds of knowledge and skills people use in `extracting' relevant information from text and to assess the extent to which expert systems techniques could be applied to automate the process of abstracting. The approach adopted in this thesis is based on research in cognitive science, information science, psycholinguistics and textlinguistics. The study addressed the significance of domain knowledge and heuristic rules by developing an information extraction system, called INFORMEX. This system, which was implemented partly in SPITBOL, and partly in PROLOG, used a set of heuristic rules to analyse five scientific papers of expository type, to interpret the content in relation to the key abstract elements and to extract a set of sentences recognised as relevant for abstracting purposes. The analysis of these extracts revealed that an adequate abstract could be generated. Furthermore, INFORMEX showed that a rule based system was a suitable computational model to represent experts' knowledge and strategies. This computational technique provided the basis for a new approach to the modelling of cognition. It showed how experts tackle the task of abstracting by integrating formal knowledge as well as experiential learning. This thesis demonstrated that empirical and theoretical knowledge can be effectively combined in expert systems technology to provide a valuable starting approach to automatic abstracting.

Developing and leveraging human capital resource to promote service quality:testing a theory of performance

Grounded in Vroom’s motivational framework of performance, we examine the interactive influence of collective human capital (ability) and aggregated service orientation (motivation) on the cross-level relationship between high-performance work systems (HPWS) and individual-level service quality. Results of hierarchical linear modeling (HLM) revealed that HPWS related to collective human capital and aggregated service orientation, which in turn related to individual-level service quality. Furthermore, both HLM and ordinary least squares regression analyses revealed a cross-level interaction effect of collective human capital and aggregated service orientation such that high levels of collective human capital and aggregated service orientation influence individual-level service quality.

Testing the assertion that 'local food is best':the challenges of an evidence-based approach

Advocates of ‘local food’ claim it serves to reduce food miles and greenhouse gas emissions, improve food safety and quality, strengthen local economies and enhance social capital. We critically review the philosophical and scientific rationale for this assertion, and consider whether conventional scientific approaches can help resolve the debate. We conclude that food miles are a poor indicator of the environmental and ethical impacts of food production. Only through combining spatially explicit life cycle assessment with analysis of social issues can the benefits of local food be assessed. This type of analysis is currently lacking for nearly all food chains.

Serious games for energy social science research

This paper proposes a set of criteria for evaluation of serious games (SGs) which are intended as effective methods of engaging energy users and lowering consumption. We discuss opportunities for using SGs in energy research which go beyond existing feedback mechanisms, including use of immersive virtual worlds for learning and testing behaviours, and sparking conversations within households. From a review of existing SG evaluation criteria, we define a tailored set of criteria for energy SG development and evaluation. The criteria emphasise the need for the game to increase energy literacy through applicability to real-life energy use/management; clear, actionable goals and feedback; ways of comparing usage socially and personal relevance. Three existing energy games are evaluated according to this framework. The paper concludes by outlining directions for future development of SGs as an effective tool in social science research, including games which inspire reflection on trade-offs and usage at different scales.

Stress-testing centralised model stores

One of the current challenges in model-driven engineering is enabling effective collaborative modelling. Two common approaches are either storing the models in a central repository, or keeping them under a traditional file-based version control system and build a centralized index for model-wide queries. Either way, special attention must be paid to the nature of these repositories and indexes as networked services: they should remain responsive even with an increasing number of concurrent clients. This paper presents an empirical study on the impact of certain key decisions on the scalability of concurrent model queries, using an Eclipse Connected Data Objects model repository and a Hawk model index. The study evaluates the impact of the network protocol, the API design and the internal caching mechanisms and analyzes the reasons for their varying performance.