An overview of manufacturing knowledge sharing in the product development process

This paper provides an overview of reported research relevant to the management of manufacturing related knowledge and highlights the sharing of knowledge in the product development process. Previous research and concepts reported by international researchers and examples of the research projects carried out by the authors’ research teams will also be introduced. Publications reviewed are in the scope of information, communication and knowledge management technologies in product development and manufacturing. Some key concepts and issues in knowledge management are introduced first, as a foundation for the remainder of the review. The different approaches to knowledge management and knowledge sharing, and the different types of knowledge and key issues in the product development process are discussed. Then manufacturing knowledge and its application in the product development is reviewed. The focus is given to the discussion of the approaches to sharing manufacturing knowledge relating to the product development process and indicating the future challenges and research directions

Advances in computational modelling for personalised medicine after myocardial infarction

Myocardial infarction (MI) is a leading cause of premature morbidity and mortality worldwide. Determining which patients will experience heart failure and sudden cardiac death after an acute MI is notoriously difficult for clinicians. The extent of heart damage after an acute MI is informed by cardiac imaging, typically using echocardiography or sometimes, cardiac magnetic resonance (CMR). These scans provide complex data sets that are only partially exploited by clinicians in daily practice, implying potential for improved risk assessment. Computational modelling of left ventricular (LV) function can bridge the gap towards personalised medicine using cardiac imaging in patients with post-MI. Several novel biomechanical parameters have theoretical prognostic value and may be useful to reflect the biomechanical effects of novel preventive therapy for adverse remodelling post-MI. These parameters include myocardial contractility (regional and global), stiffness and stress. Further, the parameters can be delineated spatially to correspond with infarct pathology and the remote zone. While these parameters hold promise, there are challenges for translating MI modelling into clinical practice, including model uncertainty, validation and verification, as well as time-efficient processing. More research is needed to (1) simplify imaging with CMR in patients with post-MI, while preserving diagnostic accuracy and patient tolerance (2) to assess and validate novel biomechanical parameters against established prognostic biomarkers, such as LV ejection fraction and infarct size. Accessible software packages with minimal user interaction are also needed. Translating benefits to patients will be achieved through a multidisciplinary approach including clinicians, mathematicians, statisticians and industry partners

A Cognitive Model Of Trust In E-Commerce: Evidence From A Field Study In China

Trust formation in the virtual environment is a complex process and is influenced by a plethora of factors.  This paper proposes a cognitive model of trust in e-commerce based on consumer research and the trust literature. It argues that perceived informativeness, perceived entertainment, and perceived irritation of online shopping, coupled with trust propensity, contribute to a customer’s general trust in e-commerce and intention to use e-commerce.  This model is tested in a field study in China via a survey instrument. Path analysis of data collected shows that all proposed relationships in the model are supported in the hypothesized directions. Results demonstrate that online marketers and Web system designers alike should pay keen attention to elements that may influence an Internet shopper’s cognitive perceptions in order to nurture consumers’ trust in e-commerce and realize the full potentials of doing business online

Applying The Extended Technology Acceptance Model To The Use Of Clickers In Student Learning: Some Evidence From Macroeconomics Classes

This paper applies the extended technology acceptance model (exTAM) in information systems research to the use of clickers in student learning. The technology acceptance model (TAM) posits that perceived ease of use and perceived usefulness of technology influence users’ attitudes toward using and intention to use technology. Research subsequent to TAM has added perceived enjoyment as a factor in predicting attitude and behavioural intentions. This study tests the validity of this extended TAM model while applied to clickers via data collected from three macroeconomics classes.  Path analytic results show that most of the hypotheses are supported in the expected directions, providing evidence that exTAM is applicable to examining factors influencing learner attitude and behaviour in relation to the use of interactive learning technologies, such as clickers in the classroom