Purpose-This paper aims to critique a facilitated knowledge management (KM) process that utilises filtered big data and, specifically, the process effectiveness in overcoming barriers to small and medium-sized enterprises' (SMEs') use of big data, the processes enablement of SME engagement with and use of big data and the process effect on SME competitiveness within an agri-food sector. Design/methodology/approach-From 300 participant firms, SME owner-managers representing seven longitudinal case studies were contacted by the facilitator at least once-monthly over six months. Findings-Results indicate that explicit and tacit knowledge can be enhanced when SMEs have access to a facilitated programme that analyses, packages and explains big data consumer analytics captured by a large pillar firm in a food network. Additionally, big data and knowledge are mutually exclusive unless effective KM processes are implemented. Several barriers to knowledge acquisition and application stem from SME resource limitations, strategic orientation and asymmetrical power relationships within a network. Research limitations/implications-By using Dunnhumby data, this study captured the impact of only one form of big data, consumer analytics. However, this is a significant data set for SME agri-food businesses. Additionally, although the SMEs were based in only one UK region, Northern Ireland, there is wide scope for future research across multiple UK regions with the same Dunnhumby data set. Originality/value-The study demonstrates the potential relevance of big data to SMEs' activities and developments, explicitly identifying that realising this potential requires the data to be filtered and presented as market-relevant information that engages SMEs, recognises relationship dynamics and supports learning through feedback and two-way dialogue. This is the first study that empirically analyses filtered big data and SME competitiveness. The examination of relationship dynamics also overcomes existing literature limitations where SMEs' constraints are seen as the prime factor restricting knowledge transfer.

Luxury, historically an exclusive, rare and elitist phenomenon, is changing. This is predominantly driven by technological developments, particularly social media, and the rising level of consumer empowerment in the marketplace. A maturing stream of research has emerged assessing the effects of social media platforms on luxury brands, offerings and consumers. However, there has been no comprehensive analysis of this extant literature synthesizing the current state of knowledge and postulating future research directions. This paper addresses this gap by utilizing a systematic literature review approach. A total of 115 articles were collected and analysed and five core themes were identified, examining(1) luxury brand strategy, (2) luxury brand social media communications, (3) luxury consumer attitudes and perceptions, (4) engagement and (5) social media's influence on brand performance-related outcomes. These themes are comprehensively explored to understand the myriad impacts of social media on luxury businesses before conceptualizing the themes as a holistic framework explaining social media's role within luxury. The framework developed highlights the fragmented yet progressive nature of research on the confluence of social media and luxury, and signals fruitful avenues for further inquiry. It is proposed that scholarly attention is directed towards multiple lines of inquiry, including social media's role in luxury brand construction online, social media's role in facilitating 'moments of luxury', younger consumers' luxury consumption, as well as the integration of both future innovative technological developments and novel social media platforms within luxury branding.

This pilot randomised controlled trial of a focussed narrative intervention demonstrated an improvement in mean changes in scores for depression and anxiety at 2, 4, and 8 weeks. We suggest this intervention may have beneficial effects on depression and anxiety, but a larger powered trial is required to determine the full effects.

The ability to drive is often affected in individuals with multiple sclerosis (MS) because of the motor, visual, or cognitive deficits commonly associated with the condition. In this study, we investigated the accuracy with which the Stroke Driver Screening Assessment (SDSA), an established battery for the prediction of driving performance of stroke survivors, would predict driving performance of individuals with MS. Driving performance of 44 individuals with relapsing-remitting MS (mean ± SD age, 46 ± 11 years; 37 females and 7 males) who were currently driving at least once a month was predicted using their performance on the SDSA. Outcomes of a road test and the Useful Field of View (UFOV) test were used as measures of driving ability. Participants' performance on both the road and UFOV tests was predicted with more than 80% accuracy. The SDSA was more accurate in predicting who would pass the two tests than who would fail the tests. The SDSA battery appears to be a good predictor of driving performance of individuals with relapsing-remitting MS, especially those who have sufficient cognitive skills to continue driving. Larger studies are needed to definitively establish its predictive accuracy and confirm the validity of the predictions. Int J MS Care. 2012;14:65-70.

Evaluations on fitness-to-drive of individuals with multiple sclerosis (MS) usually involve the administration of several physical, visual, and cognitive tests. In some instances, a practical road test is also administered. The use of several tests, many of which are only remotely driving-related, increases the time, cost, and human resources involved in the evaluation process, and sometimes lead to erroneous decisions. In this study, we investigated the usefulness of using a short battery of a few highly predictive tests to predict fitness-to-drive of individuals with MS. Fortyfour individuals with relapsing-remitting MS (age = 46 ± 11 years, 37 females) and Expanded Disability Status Scale values between 1 and 7 were administered selected physical, visual and cognitive tests including the Stroke Driver Screening Assessment (SDSA) battery. Performance on 12 cognitive and three visual tests were significantly associated with participants' performance on a practical road test. The Stroop Color test, Direction, Compass, and Road Sign Recognition tests from the SDSA, and the Speed of Processing test from Useful Field of View test battery together explained 59% of the variance and predicted the pass or fail outcome on the road test with 91% accuracy, 70% sensitivity, and 97% specificity. The five psychometric/off-road tests, which together can be administered in less than 45 minutes, cost approximately $150, and is 91% accurate, can be used as a screening battery. Those who pass should be further tested on-road to finally decide their fitness-to-drive while those of fail should be further evaluated, trained, or advised on alternative transportation means. Future studies are needed to confirm and validate the findings in this study.