Contextualising social capital in online brand communities

Online brand communities (OBC) are growing in number and becoming an increasingly important interface where marketers can effectively facilitate the relationship between their brand and consumers. A qualitative study using a four-month netnography over three OBCs followed by focus groups with OBC members explored the dynamics of social capital in these communities. Findings indicate that social capital is an important driver in the success of OBCs, and all the elements of social capital including a shared language, shared vision, social trust and reciprocity are evident. Moreover, results from this study indicate that these elements are crucial in developing the network ties that are integral to building loyalty and brand equity

Activity-based sleep-wake identification in infants

Actigraphy offers one of the best-known alternatives to polysomnography for sleep-wake identification. The advantages of actigraphy include high accuracy, simplicity of use and low intrusiveness. These features allow the use of actigraphy for determining sleep-wake states in such highly sensitive groups as infants. This study utilizes a motion sensor (accelerometer) for a dual purpose: to determine an infant\u27s position in the crib and to identify sleep-wake states. The accelerometer was positioned over the sacral region on the infant\u27s diaper, unlike commonly used attachment to an ankle. Opposed to broadly used discriminant analysis, this study utilized logistic regression and neural networks as predictors. The accuracy of predicted sleep-wake states was established in comparison to the sleep-wake states recorded by technicians in a polysomnograph study. Both statistical and neural predictors of this study provide an accuracy of approximately 77-92% which is comparable to similar studies achieving prediction rates of 85-95%, thus validating the suggested methodology. The results support the use of body motion as a simple and reliable method for determining sleep-wake states in infants. Nonlinear mapping capabilities of the neural network benefit the accuracy of sleep-wake state identification. Utilization of the accelerometer for the dual purpose allows us to minimize intrusiveness of home infant monitors