Survey of eResearch practices and skills at QUT, Australia

Queensland University of Technology (QUT) is a multidisciplinary university in Brisbane, Queensland, Australia, and has 40,000 students and 1,700 researchers. Notable eResearch infrastructure includes the QUT ePrints repository, Microsoft QUT Research Centre, the OAK (Open Access to Knowledge) Law Project, Cambia and leading research institutes. ---------- The Australian Government, via the Australian National Data Service (ANDS), is funding institutions to identify and describe their research datasets, to develop and populate data repositories and collaborative infrastructure, and to seed the Australian Research Data Commons. QUT is currently broadening its range of research support services, including those to support the management of research data, in recognition of the value of these datasets as products of the research process, and in order to maximize the potential for reuse. QUT is integrating Library and High Performance Computing (HPC) services to achieve its research support goals. ---------- The Library and HPC released an online survey using Key Survey to 1,700 researchers in September 2009. A comprehensive range of eResearch practices and skills was presented for response, and grouped into areas of scholarly communication and open access publishing, using collaborative technologies, data management, data collection and management, computation and visualization tools. Researchers were asked to rate their skill level on each practice. 254 responses were received over two weeks. Eight focus groups were also held with 35 higher degree research (HDR) students and staff to provide additional qualitative feedback. A similar survey was released to 100 support staff and 73 responses were received.---------- Preliminary results from the researcher survey and focus groups indicate a gap between current eResearch practices, and the potential for researchers to engage in eResearch practices. Researchers are more likely to seek advice from their peers, than from support staff. HDR students are more positive about eResearch practices and are more willing to learn new ways of conducting research. An account of the survey methodology, the results obtained, and proposed strategies to embed eResearch practices and skills across and within the research disciplines will be provided.

An application of Keller’s Brand Equity Model in a B2B context

Powerful brands create meaningful images in the minds of customers (Keller, 1993). A strong brand image and reputation enhances differentiation and has a positive influence on buying behaviour (Gordon et al., 1993; McEnally and de Chernatony, 1999). While the power of branding is widely acknowledged in consumer markets, the nature and importance of branding in industrial markets remains under-researched. Many business-to-business (B2B) strategists have claimed brand-building belongs in the consumer realm. They argue that industrial products do not need branding as it is confusing and adds little value to functional products (Collins, 1977; Lorge, 1998; Saunders and Watt, 1979). Others argue that branding and the concept of brand equity however are increasingly important in industrial markets, because it has been shown that what a brand means to a buyer can be a determining factor in deciding between industrial purchase alternatives (Aaker, 1991). In this context, it is critical for suppliers to initiate and sustain relationships due to the small number of potential customers (Ambler, 1995; Webster and Keller, 2004). To date however, there is no model available to assist B2B marketers in identifying and measuring brand equity. In this paper, we take a step in that direction by operationalising and empirically testing a prominent brand equity model in a B2B context. This makes not only a theoretical contribution by advancing branding research, but also addresses a managerial need for information that will assist in the assessment of industrial branding efforts.

A modified quality control method for manufacturing process in mask industry

Masks are widely used in different industries, for example, traditional metal industry, hospitals or semiconductor industry. Quality is a critical issue in mask industry as it is related to public health and safety. Traditional quality practices for manufacturing process have some limitations in implementing them in mask industries. This paper aims to investigate the suitability of Six Sigma quality control method for the manufacturing process in the mask industry to provide high quality products, enhancing the process capacity, reducing the defects and the returned goods arising in a selected mask manufacturing company. This paper suggests that modifications necessary in Six Sigma method for effective implementation in mask industry.