Seasonal and interannual variability in wind field and commercial catch rates of austroglossus pectoralis (soleidae)

The impact of deviations in the direction and strength of the wind field on the spatial, seasonal and interannual variability in catch rates of Agulhas sole Austroglossus pectoralis was investigated. Temporal variabilityin the wind cycle on the Agulhas Bank during the period 1981–1996 was deduced mainly from trends in the pressure gradient, measured from south of Cape Agulhas (35°S) to the region of westwind drift (40°S).Because interannual deviations in the catch rates differed between seasons, catch rates were assessed by season. Coastal catch rates of Agulhas sole between Cape Agulhas and Cape Infanta were high in autumn and winter, when offshore north-westerly winds prevailed, and low in spring and late summer, when onshore south-easterly winds dominated. There was often a secondary peak in catch rates in November–December,coincident with a midsummer change in the pressure gradient. Between the period 1982 and 1996, catch rates in autumn and early winter (April–July) were highest during years when the winter north-westerly winds were strongest (r2 = 0.62, p < 0.01). Catch rates usually peaked in May–June. This pattern changed in some years, depending on the timing and rate of change to winter wind conditions. Seasonal and interannual fluctuations in catch rate are associated with deviations in the wind field, but the  mechanism whereby this  effect is mediated remains unknown

Analysis of Factors that Influence Customers' Willingness to Leave Big Data Digital Footprints on Social Media: A Systematic Review of Literature

Big data has been discussed extensively in existing scholarly works but scant consideration is given to customers’ willingness to generate and leave big data digital footprints on social media, especially in the light of the profusely debated issue of privacy and security. The current paper endeavours to address this gap in the literature by developing a conceptual framework. In doing so, this paper conducts a systematic review of extant literature from 2002 to 2017 to identify and analyse the underlying factors that influence customers’ willingness to leave digital footprints on social media. The findings of this review reveal that personal behaviour (intrinsic psychological dispositions), technological factors (relative advantage and convenience), social influence (social interaction, social ties and social support) and privacy and security (risk, control and trust) are the key factors that influence customers’ willingness to generate and leave big data digital footprints on social media. The conceptual framework presented in this paper advances the scholarship of technology adoption and use and provides useful direction for future empirical research for both academics and practitioners