PurposeThis study explores food delivery app users and technology acceptance model as a theoretical underpinning. This study thus investigated the determinants of usefulness, ease of use and intention to use for food delivery app service.Design/methodology/approachThe variables of delivery time, diverse menu, quarantine, review quality and ease of use are employed as determinants of usefulness. The antecedents of ease of use are easy registration and easy payment. This study also examined the association between ease of use, usefulness and intention to use. This study collected data using Amazon Mechanical Turk, and the number of valid observations for statistical analysis was 484. A structural equation model was used to test the hypotheses.FindingsRegarding the results, usefulness was positively affected by delivery time, quarantine, review quality and ease of use. Additionally, ease of use was positively impacted by easy registration and easy payment. Finally, this study showed that ease of use positively affects both usefulness and intention to use, and usefulness is positively associated with intention to use.Originality/valueThis study contributes to the literature by ensuring the explanatory power of technology acceptance model for food delivery app.

Using indigenous minorities in Xijian Miao Village in China as a case research, this research examined how residents' perceptions of tourism development could influence their affective commitment, altruistic behavior, and civic virtue. A total of 449 residents took part in the survey. Using structural equation modeling (SEM), this study found that affective commitment was significantly influenced by perceptions of tourism development. It also found that altruistic behavior and civic virtue had a positive relationship with residents' affective commitment.

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Abstract:We present and validate a method of reconstructing high-resolution sea surface wind fields from multi-sensor satellite data over the Grand Banks of Newfoundland off Atlantic Canada. Six-hourly ocean wind fields from blended products (including multi-satellite measurements) with 0.25° spatial resolution and 226 RADARSAT-2 synthetic aperture radar (SAR) wind fields with 1-km spatial resolution have been used to reconstruct new six-hourly wind fields with a resolution of 10 km for the period from August 2008 to December 2010, except July 2009 to November 2009. The reconstruction process is based on the heapsort bucket method with topdown search and the modified Gauss-Markov theorem. The result shows that the mean difference between the reconstructed wind speed and buoy-estimated wind speed is smaller than 0.6 m/s, and the standard deviation is smaller than 2.5 m/s. The mean difference in wind direction between reconstructed and buoy estimates is 3.7°; the standard deviation is 40.2°. There is fair agreement between the reconstructed wind vectors and buoy-estimated ones.