Mathematical Problems in Engineering / 2021 / Article / Tab 3 / Research Article
Research on the Dynamic Evolution of Scientific and Technological Innovation Efficiency in Universities and Identification of Influencing factors—based on Markov Chain Estimation and GMM Model Table 3 2007–2019 calculation result.
Region 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Mean Eastern Beijing 0.934 0.988 0.998 1.054 1.117 1.139 1.142 1.206 1.233 1.248 1.323 1.334 1.168 1.145 Tianjin 0.852 0.995 0.803 0.729 0.683 0.748 0.758 0.516 0.519 0.539 0.537 0.545 0.583 0.677 Hebei 0.818 0.799 0.739 0.718 0.758 0.799 0.787 0.749 0.691 0.973 0.789 0.801 0.806 0.787 Liaoning 0.688 0.894 0.772 0.788 0.897 0.762 0.926 0.869 0.832 0.787 0.798 0.764 0.773 0.812 Shanghai 1.285 1.193 0.975 0.979 0.962 0.952 0.985 0.918 0.871 0.832 0.833 0.824 0.913 0.963 Jiangsu 0.939 1.133 0.977 0.991 1.024 1.052 1.093 1.023 1.035 1.119 1.161 1.078 1.017 1.049 Zhejiang 0.816 1.023 0.981 0.983 0.949 0.932 0.905 0.878 0.868 0.889 0.905 0.915 0.927 0.921 Fujian 0.518 0.574 0.544 0.583 0.768 0.438 0.549 0.524 0.618 0.914 0.823 0.834 0.852 0.657 Shandong 1.235 1.148 0.931 0.944 0.959 0.867 0.893 0.722 0.604 0.819 0.733 0.756 0.749 0.874 Guangdong 0.749 0.984 0.788 0.763 0.755 0.736 0.704 0.656 0.623 0.778 0.689 0.784 0.789 0.754 Hainan 0.935 0.946 0.952 1.113 1.124 1.231 0.943 0.959 0.962 0.977 0.981 0.997 1.006 1.010 Eastern mean 0.888 0.971 0.860 0.877 0.909 0.878 0.880 0.820 0.805 0.898 0.870 0.876 0.871 0.877 Central Shanxi 0.736 0.848 0.851 0.986 0.852 0.861 0.896 0.817 0.882 0.834 0.783 0.804 0.808 0.843 Jilin 0.813 0.795 0.773 0.781 0.915 0.562 0.528 0.851 0.684 0.788 0.796 0.732 0.746 0.751 Heilongjiang 0.426 0.465 0.479 0.516 0.949 0.558 0.591 0.873 0.583 0.798 0.839 0.785 0.701 0.659 Anhui 0.947 0.959 0.846 0.855 0.966 0.841 0.833 0.922 0.941 0.958 0.875 0.895 0.902 0.903 Jiangxi 0.445 0.551 0.541 0.673 0.884 0.695 0.778 0.918 0.529 0.465 0.476 0.564 0.578 0.623 Henan 0.319 0.349 0.353 0.373 0.786 0.395 0.473 0.635 0.473 0.478 0.496 0.502 0.521 0.473 Hubei 0.839 0.948 0.951 1.053 1.086 0.879 0.788 0.948 0.765 0.786 0.733 0.679 0.688 0.857 Hunan 0.625 0.639 0.661 0.674 0.886 0.557 0.649 0.678 0.588 0.694 0.804 0.817 0.824 0.700 Central mean 0.644 0.694 0.682 0.739 0.916 0.669 0.692 0.830 0.681 0.725 0.725 0.722 0.721 0.726 Western Neimenggu 0.592 0.499 0.485 0.561 0.536 0.528 0.739 0.654 0.676 0.682 0.711 0.733 0.753 0.627 Guangxi 0.438 0.479 0.446 0.558 0.626 0.674 0.594 0.503 0.551 0.403 0.459 0.477 0.495 0.516 Chongqing 0.549 0.853 0.762 0.849 0.986 0.939 0.987 1.041 0.933 0.969 0.728 0.798 0.811 0.862 Sichuan 0.411 0.528 0.612 0.649 0.626 0.638 0.609 0.543 0.547 0.551 0.559 0.603 0.662 0.580 Guizhou 0.727 0.836 0.631 0.539 0.586 0.855 0.573 0.598 0.611 0.625 0.697 0.723 0.756 0.669 Yunnan 0.624 0.535 0.629 0.841 0.816 0.761 0.684 0.699 0.612 0.623 0.678 0.712 0.749 0.689 Shaanxi 0.732 0.942 0.936 0.951 0.886 0.874 0.889 0.762 0.724 0.633 0.755 0.788 0.796 0.821 Gansu 0.512 0.527 0.519 0.543 0.586 0.568 0.589 0.588 0.599 0.613 0.637 0.686 0.693 0.589 Qinghai 0.378 0.384 0.371 0.373 0.386 0.392 0.403 0.414 0.433 0.457 0.453 0.437 0.488 0.410 Ningxia 0.317 0.344 0.331 0.339 0.386 0.361 0.378 0.388 0.393 0.403 0.482 0.424 0.444 0.378 Xinjiang 0.334 0.343 0.332 0.352 0.386 0.375 0.389 0.303 0.325 0.339 0.449 0.354 0.372 0.350 Western mean 0.510 0.570 0.550 0.596 0.619 0.633 0.621 0.590 0.582 0.573 0.601 0.612 0.638 0.590 National mean 0.684 0.750 0.699 0.737 0.804 0.732 0.735 0.739 0.690 0.732 0.733 0.738 0.746 0.732
