Inter-organisational networks, value creation and the process of technology integration in research and development

Traditional methods of R&D management are no longer sufficient for embracing innovations and leveraging complex new technologies to fully integrated positions in established systems. This paper presents the view that the technology integration process is a result of fundamental interactions embedded in inter-organisational activities. Emerging industries, high technology companies and knowledge intensive organisations owe a large part of their viability to complex networks of inter-organisational interactions and relationships. R&D organisations are the gatekeepers in the technology integration process with their initial sanction and motivation to develop technologies providing the first point of entry. Networks rely on the activities of stakeholders to provide the foundations of collaborative R&D activities, business-to-business marketing and strategic alliances. Such complex inter-organisational interactions and relationships influence value creation and organisational goals as stakeholders seek to gain investment opportunities. A theoretical model is developed here that contributes to our understanding of technology integration (adoption) as a dynamic process, which is simultaneously structured and enacted through the activities of stakeholders and organisations in complex inter-organisational networks of sanction and integration.

Towards an ethics of engagement in education in global times

Starting from the observation that patterns of educational inequality are widely known but largely invisible in public debates on education, this article argues for the importance of an ethics of education which challenges simple acceptance of 'things as they are'. It suggests possibilities for working with discourses of ethics, rights and citizenship in contingent and strategic ways, and argues for the importance of engaging ethically across difference in current global times. It proposes three interrelated dimensions for an ethics of engagement in education: an ethics of commitment to intellectual rigour; an ethics of civility; and an inter-human ethics of care.

Moving and dancing towards decolonisation in education: An example from an Indigenous Australian performance classroom

This paper explores the special type of thinking, moving and dancing place which is opened up for decolonisaton when students engage in an embodied pedagogical practice in Indigenous education. The author examines what decolonisation means in this context by describing the ways in which the curriculum, the students and teacher, and more generally the discipline of ethnomusicology itself, undergo a process to question, critique, and move aside the pedagogical script of colonialism in order to allow Indigenous ways of understanding music and dance to be presented, privileged and empowered. Key questions are: What is the relationship between embodiment and disembodiment and decolonisation and colonisation? In what ways is embodiment more than, or other than, the presence of moving bodies? In what ways is performativity an aspect of power/knowledge/subject formations? How can it be theorised? What could the pedagogical scripts of decolonisation look like?

Identification of success and failure factors for technology transfer in biotechnology: case studies and surveys from Academic Sinica in Taiwan

Academia Sinica is the leading research institute in Taiwan founded in 1928. Its Office of Technology Transfer (OTT) was established in 1998. It made great efforts to dramatically turn around the technology transfer activity of Academia Sinica, especially in biotechnology. Academia Sinica has more than 80 cases of experience in biotechnology transfer with companies in Taiwanese industry in the past five years. The purpose of this study is to identify potential success and failure factors for biotechnology transfer in Taiwan. Eight cases were studied through in-depth interview. The results of the analysis were used to design two surveys to further investigate 81 cases (48 successful and 33 failure cases) of biotechnology transfer in Academia Sinica from 1999–2003. The results indicated that 10 of the 14 success factors were cited in more than 40% of the cases as contributing to the success of technology transfer. By contrast, only 5 out of 16 key factors were present in more than 30% of the failure cases.

Consumer-identified barriers and strategies for optimizing technology use in the workplace

Purpose. This article explores the experiences of 26 assistive technology (AT) users having a range of physical impairments as they optimized their use of technology in the workplace. Method. A qualitative research design was employed using in-depth, open-ended interviews and observations of AT users in the workplace. Results. Participants identified many factors that limited their use of technology such as discomfort and pain, limited knowledge of the technology's features, and the complexity of the technology. The amount of time required for training, limited work time available for mastery, cost of training and limitations of the training provided, resulted in an over-reliance on trial and error and informal support networks and a sense of isolation. AT users enhanced their use of technology by addressing the ergonomics of the workstation and customizing the technology to address individual needs and strategies. Other key strategies included tailored training and learning support as well as opportunities to practice using the technology and explore its features away from work demands. Conclusions. This research identified structures important for effective AT use in the workplace which need to be put in place to ensure that AT users are able to master and optimize their use of technology.

Rule extraction from technology IPOs in the US stock market

Machine learning techniques for prediction and rule extraction from artificial neural network methods are used. The hypothesis that market sentiment and IPO specific attributes are equally responsible for first-day IPO returns in the US stock market is tested. Machine learning methods used are Bayesian classifications, support vector machines, decision tree techniques, rule learners and artificial neural networks. The outcomes of the research are predictions and rules associated With first-day returns of technology IPOs. The hypothesis that first-day returns of technology IPOs are equally determined by IPO specific and market sentiment is rejected. Instead lower yielding IPOs are determined by IPO specific and market sentiment attributes, while higher yielding IPOs are largely dependent on IPO specific attributes.