63 research outputs found

    Conceptual framework.

    No full text
    The importance of digital transformation (DGT) for increasing productivity cannot be negated and Chinese firms are rapidly embracing the digital transformation for their sustainability. But the mechanism and impact of digital transformation on total factor productivity (TFP) of firms is still unclear and this study is intended to fill this gap using the data of 3112 listed firms of China during 2011 to 2022. We applied various econometric techniques like stepwise regression analysis, instrumental variable approach, differences in difference approach, and mediating analysis to determine the relationship between digital transformation and TFP and robustness of estimated findings. The findings indicate that DGT has a positive impact on overall TFP of firms in China while operating efficiency, cheaper costs, and a stronger capacity for innovation mediates this relationship. Moreover, it is explored that conventional information and communication technologies have not significant impact on TFP of firms. The findings of the study remain valid even applying many robustness checks and attempts to control the issue of endogeneity. To fully leverage the potential benefits of digital transformation on TFP, it is essential to focus on enhancing digital literacy and skills among the workforce. Governments and relevant stakeholders should prioritize and invest in comprehensive digital literacy and skills training programs to empower the workforce with the knowledge and expertise needed to navigate the digital age effectively.</div

    Traditional ICT and TFP.

    No full text
    The importance of digital transformation (DGT) for increasing productivity cannot be negated and Chinese firms are rapidly embracing the digital transformation for their sustainability. But the mechanism and impact of digital transformation on total factor productivity (TFP) of firms is still unclear and this study is intended to fill this gap using the data of 3112 listed firms of China during 2011 to 2022. We applied various econometric techniques like stepwise regression analysis, instrumental variable approach, differences in difference approach, and mediating analysis to determine the relationship between digital transformation and TFP and robustness of estimated findings. The findings indicate that DGT has a positive impact on overall TFP of firms in China while operating efficiency, cheaper costs, and a stronger capacity for innovation mediates this relationship. Moreover, it is explored that conventional information and communication technologies have not significant impact on TFP of firms. The findings of the study remain valid even applying many robustness checks and attempts to control the issue of endogeneity. To fully leverage the potential benefits of digital transformation on TFP, it is essential to focus on enhancing digital literacy and skills among the workforce. Governments and relevant stakeholders should prioritize and invest in comprehensive digital literacy and skills training programs to empower the workforce with the knowledge and expertise needed to navigate the digital age effectively.</div

    Digital transformation and TFP: Mediating affects.

    No full text
    Digital transformation and TFP: Mediating affects.</p

    Instrumental variables approach.

    No full text
    The importance of digital transformation (DGT) for increasing productivity cannot be negated and Chinese firms are rapidly embracing the digital transformation for their sustainability. But the mechanism and impact of digital transformation on total factor productivity (TFP) of firms is still unclear and this study is intended to fill this gap using the data of 3112 listed firms of China during 2011 to 2022. We applied various econometric techniques like stepwise regression analysis, instrumental variable approach, differences in difference approach, and mediating analysis to determine the relationship between digital transformation and TFP and robustness of estimated findings. The findings indicate that DGT has a positive impact on overall TFP of firms in China while operating efficiency, cheaper costs, and a stronger capacity for innovation mediates this relationship. Moreover, it is explored that conventional information and communication technologies have not significant impact on TFP of firms. The findings of the study remain valid even applying many robustness checks and attempts to control the issue of endogeneity. To fully leverage the potential benefits of digital transformation on TFP, it is essential to focus on enhancing digital literacy and skills among the workforce. Governments and relevant stakeholders should prioritize and invest in comprehensive digital literacy and skills training programs to empower the workforce with the knowledge and expertise needed to navigate the digital age effectively.</div

    S1 Data -

    No full text
    The importance of digital transformation (DGT) for increasing productivity cannot be negated and Chinese firms are rapidly embracing the digital transformation for their sustainability. But the mechanism and impact of digital transformation on total factor productivity (TFP) of firms is still unclear and this study is intended to fill this gap using the data of 3112 listed firms of China during 2011 to 2022. We applied various econometric techniques like stepwise regression analysis, instrumental variable approach, differences in difference approach, and mediating analysis to determine the relationship between digital transformation and TFP and robustness of estimated findings. The findings indicate that DGT has a positive impact on overall TFP of firms in China while operating efficiency, cheaper costs, and a stronger capacity for innovation mediates this relationship. Moreover, it is explored that conventional information and communication technologies have not significant impact on TFP of firms. The findings of the study remain valid even applying many robustness checks and attempts to control the issue of endogeneity. To fully leverage the potential benefits of digital transformation on TFP, it is essential to focus on enhancing digital literacy and skills among the workforce. Governments and relevant stakeholders should prioritize and invest in comprehensive digital literacy and skills training programs to empower the workforce with the knowledge and expertise needed to navigate the digital age effectively.</div

    Differences in difference approach.

    No full text
    The importance of digital transformation (DGT) for increasing productivity cannot be negated and Chinese firms are rapidly embracing the digital transformation for their sustainability. But the mechanism and impact of digital transformation on total factor productivity (TFP) of firms is still unclear and this study is intended to fill this gap using the data of 3112 listed firms of China during 2011 to 2022. We applied various econometric techniques like stepwise regression analysis, instrumental variable approach, differences in difference approach, and mediating analysis to determine the relationship between digital transformation and TFP and robustness of estimated findings. The findings indicate that DGT has a positive impact on overall TFP of firms in China while operating efficiency, cheaper costs, and a stronger capacity for innovation mediates this relationship. Moreover, it is explored that conventional information and communication technologies have not significant impact on TFP of firms. The findings of the study remain valid even applying many robustness checks and attempts to control the issue of endogeneity. To fully leverage the potential benefits of digital transformation on TFP, it is essential to focus on enhancing digital literacy and skills among the workforce. Governments and relevant stakeholders should prioritize and invest in comprehensive digital literacy and skills training programs to empower the workforce with the knowledge and expertise needed to navigate the digital age effectively.</div

    Stepwise regression results.

    No full text
    The importance of digital transformation (DGT) for increasing productivity cannot be negated and Chinese firms are rapidly embracing the digital transformation for their sustainability. But the mechanism and impact of digital transformation on total factor productivity (TFP) of firms is still unclear and this study is intended to fill this gap using the data of 3112 listed firms of China during 2011 to 2022. We applied various econometric techniques like stepwise regression analysis, instrumental variable approach, differences in difference approach, and mediating analysis to determine the relationship between digital transformation and TFP and robustness of estimated findings. The findings indicate that DGT has a positive impact on overall TFP of firms in China while operating efficiency, cheaper costs, and a stronger capacity for innovation mediates this relationship. Moreover, it is explored that conventional information and communication technologies have not significant impact on TFP of firms. The findings of the study remain valid even applying many robustness checks and attempts to control the issue of endogeneity. To fully leverage the potential benefits of digital transformation on TFP, it is essential to focus on enhancing digital literacy and skills among the workforce. Governments and relevant stakeholders should prioritize and invest in comprehensive digital literacy and skills training programs to empower the workforce with the knowledge and expertise needed to navigate the digital age effectively.</div

    Descriptive statistics.

    No full text
    The importance of digital transformation (DGT) for increasing productivity cannot be negated and Chinese firms are rapidly embracing the digital transformation for their sustainability. But the mechanism and impact of digital transformation on total factor productivity (TFP) of firms is still unclear and this study is intended to fill this gap using the data of 3112 listed firms of China during 2011 to 2022. We applied various econometric techniques like stepwise regression analysis, instrumental variable approach, differences in difference approach, and mediating analysis to determine the relationship between digital transformation and TFP and robustness of estimated findings. The findings indicate that DGT has a positive impact on overall TFP of firms in China while operating efficiency, cheaper costs, and a stronger capacity for innovation mediates this relationship. Moreover, it is explored that conventional information and communication technologies have not significant impact on TFP of firms. The findings of the study remain valid even applying many robustness checks and attempts to control the issue of endogeneity. To fully leverage the potential benefits of digital transformation on TFP, it is essential to focus on enhancing digital literacy and skills among the workforce. Governments and relevant stakeholders should prioritize and invest in comprehensive digital literacy and skills training programs to empower the workforce with the knowledge and expertise needed to navigate the digital age effectively.</div

    Proteomic Identification of Genes Associated with Maize Grain-Filling Rate

    Get PDF
    <div><p>Grain filling during the linear phase contributes most of the dry matter accumulated in the maize kernel, which in turn determines the final grain yield. Endosperms and embryos of three elite maize hybrids (Zhengdan 958, Nongda 108, and Pioneer 335) were sampled 17, 22, 25, and 28 days after pollination, during the linear phase of grain filling, for proteomic analysis to explore the regulatory factors critical for grain filling rate. In total, 39 and 43 protein spots that showed more than 2-fold changes in abundance at <i>P</i><0.01 between any two sampling stages in the endosperm and embryo were analyzed by protein mass spectrometry. The changing patterns in expression index of these proteins in the endosperm were evenly distributed, whereas up-regulation patterns predominated (74%) in the embryo. Functional analysis revealed that metabolism was the largest category, represented by nine proteins in the endosperm and 12 proteins in the embryo, of the proteins that significantly changed in abundance. Glycolysis, a critical process both for glucose conversion into pyruvate and for release of free energy and reducing power, and proteins related to redox homeostasis were emphasized in the endosperm. Additionally, lipid, nitrogen, and inositol metabolism related to fatty acid biosynthesis and late embryogenesis abundant proteins were emphasized in the embryo. One protein related to cellular redox equilibrium, which showed a more than 50-fold change in abundance and was co-localized with a quantitative trait locus for grain yield on chromosome 1, was further investigated by transcriptional profile implying consistent expression pattern with protein accumulation. The present results provide a first step towards elucidation of the gene network responsible for regulation of grain filling in maize.</p> </div

    Annotation of differentially expressed proteins identified in the endosperm and embryo of the three maize hybrids during the linear phase of grain filling.

    No full text
    a<p>Number of identified differentially expressed protein spots on each 2-D map. Preferentially accumulated proteins: more than 2-fold changes; <i>t</i>-test or ANOVA: <i>P</i><0.01 in three independent biological replicates.</p>b<p>Accession number of each protein identified by MS.</p>c<p>Identified proteins obtained from the NCBI <i>Zea mays</i> protein sequence database using the TurboSEQUEST algorithm.</p>d<p>Functional annotation of each protein identified by MS.</p>e<p>Molecular weight of protein on gel/predicted molecular weight of protein.</p>f<p>pI of protein on gel/predicted pI of protein.</p>g<p>Number of peptides matching the corresponding protein.</p>h<p>Calculated by weighting ion score (based on the probability that ion fragmentation matches are non-random) events for all individual peptides matched to the protein. Ion scores for duplicated matches are excluded from the calculation.</p>i<p>Confidence level of the total ion score.</p>j<p>Calculated by Mascot search (−10×Log<i>P</i>) for identified proteins.</p>k<p>Percentage of coverage of the identified proteins.</p>l<p>Probability that the peptide mass matches are non-random events.</p
    • …
    corecore