PurposeBased on the knowledge-based view, this study investigates how firms' information technology (IT) capability broadens and deepens their knowledge base, which consequently improves digital innovation. By further drawing on the institutional theory perspective, this study examines how the relationships between IT capability and knowledge base are moderated by the institutional environments in which the firm operates.Design/methodology/approachThis paper uses 170 samples of Chinese firms and an empirical test conducted by the authors following a hierarchical moderated regression analysis.FindingsThe results find that IT capability positively affects knowledge breadth and knowledge depth, which consequently improves digital innovation. Furthermore, the study reveals the negative moderating effects of enforcement inefficiency on IT capability–knowledge breadth relationship, and the negative moderating effects of government support on IT capability–knowledge depth relationship.Originality/valueThis research is one of the earliest attempts to explore the impact of the institutional environment of emerging economies on IT capability. It also clarifies the impact of knowledge breadth and knowledge depth on digital innovation.

As the Manila Trench is becoming the most tsunami-hazardous, it is necessary to ascertain the wave height and arrival time in the South China Sea region through numerical simulation of tsunamis generated from potential earthquake source along the Manila subduction zone. The Okada model is employed to generate tsunami. The surface elevation and depth-averaged horizontal velocity at first 5 min, coming from the simulation of shallow water equations, are then interpolated in the weakly dispersive model (FUNWAVE) to calculate tsunami propagation and far-field impact. The characteristics of tsunami wave height distribution in South China Sea are analyzed for the assessment of tsunami hazard near coasts around South China Sea due to the hypothetical earthquakes with magnitude of [Formula: see text] and the worst case scenario ([Formula: see text]). The maximum wave height distribution computed by the Boussinesq equations is compared with that by the shallow water equations to investigate the dispersion effects on propagation of tsunami in South China Sea. It is found that the dispersion effects of the tsunami waves propagating in South China Sea are not significant if the earthquake magnitude is large enough.

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Background: Oil and protein content, as well as fatty acid composition, are important quality traits in peanut. Elucidating the genetic mechanisms underlying these traits may help researchers to obtain improved cultivars through molecular breeding techniques.Results: Whole-genome resequencing of an RIL population of 318 lines was performed to construct a high-density linkage map and identify QTLs for peanut quality. The map, containing 4561 bin markers, covered a length of 2032.39 cM with an average marker density of 0.45 cM. A total of 109 QTLs for oil content, protein content, and fatty acid compositions were mapped on the 18 peanut chromosomes. The QTL qA05.1 was detected in four different environments and exhibited a major phenotypic effect on the content of oil, proteins, and six fatty acids. The genomic region spanned by qA05.1, corresponding to a physical interval of approximately 1.50 Mb, contains two polymorphic SNPs between two parents that could cause missense mutations. The two SNP sites were employed as KASP markers and validated using lines with extremely high and low oil contents; these sites may be useful in the marker-assisted breeding of peanut varieties with high oil contents.Conclusions: A high-density genetic map with 4561 bin markers was constructed, and a major and pleiotropic QTL located on LG05 was stably detected for oil, protein and fatty acids across four different environments.

[1] Accurate flood predictions require high resolution inundation numerical models and detailed coastal and land topography data. However, such data are not always available. A new method to obtain topographic information of flood zones from remote sensing data is demonstrated here for Cook Inlet, Alaska, where tidal range reaches 8 -10 m. The moving shoreline is detected from analysis of water coverage in satellite images taken at different tidal stages, and then the shoreline data from different times are combined with water level data from observations and models to produce new topographic maps of previously unobserved mudflats. The remote sensing-based analysis provides for the first time a way to evaluate the flood predictions of the inundation model of the inlet. The new flood-zone topography obtained from the remote sensing data will help to construct a more accurate inundation model in the future.