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This study uses annual data of The Enterprise Survey and Provincial Competitiveness Index to analyze determinants of TFP of the fisheries sector and fishery firms in 28 coastal provinces of Vietnam. The paper evaluated the effects of different institutional variables on TFP at the firm level. In addition, impacts of macro variables on sector’s TFP were also analyzed using sector aggregated TFP. Analyses of the study show that the industry’s macro environment and firm characteristics significantly affect the fisheries sector’s productivity. At the macro level, the more transparent the environment is, the higher the TFP. Thus, it is suggested that the local authorities of the coastal provinces of Vietnam need to speed up their reforms in administrative procedures, creating a favorable business environment for firms. At the micro-level, the variable of firm size is positively correlated with the TFP in the fisheries sector. The larger the size of the firm, the higher the productivity. In a labor-intensive industry such as fisheries, productivity increases with labor, indicating a low science and technology application level. To increase the sector’s productivity, state support to expand the application of advanced technologies for domestic firms is essential.

Research on ridesharing platforms under the gig economy has focused much on the incentives and barriers of users, leaving many gaps in understanding drivers’ intention to provide ridesharing services. This paper aims to explore, from the perspective of driver-partners, motives that encourage them to continue being gig workers. Data for the study are based on a cross-sectional survey of ridesharing drivers in three metropolitan areas in three regions (North, Central, and South) of Vietnam, conducted from June to July 2022. The paper regresses behavioral intention to continue being a gig driver on their demographic characteristics and self-estimation of economic benefit, time preference, and enjoyment of being a gig driver via ordered probit models. For all three regions, the result suggests that economic benefit, time preference, and enjoyment are good predictors of drivers’ intention to provide the services. Specifically, the probability of remaining in gig work among drivers decreases with their educational and economic status. Higher economic benefit does not predict a higher intention of drivers to stay longer in gig work. Similarly, those with higher levels of enjoyment of traveling and vehicles have a lower intention to remain in this sphere. In the North, the interaction terms between time preference and enjoyment level are significant, suggesting that the effect of enjoyment levels becomes less damaging with an increase in time preference. In other words, time preference is vital in keeping gig drivers in this type of work.