<div>(1) Analysis of main indexes</div><div>Based on the analysis of supply chain data governance ecosystem
perspective, the system governance system mainly consists of four
indexes: data governance subject, governance technology, governance
environment, and data and services. By analyzing the main indexes A and
B, the index ranking of index centrality and cause degree is integrated
to obtain the mean value of cause degree of A-level indexes (listed in
the order of cause degree) as A2, A4, A1, A3, and the centrality degree
as A3, A2, A1, A4, respectively. It can be seen that the cause factors
of the first-level indexes are data governance technology and data and
services; the result elements are data governance subject and data
governance environment. The centrality of data governance technology as
the cause factor ranks second, indicating that data governance
technology dominates the governance system and has a high degree of
influence on other indexes. The centrality of data governance
environment is in the first place, and because it is the result element,
it indicates that data governance environment also plays an important
role in the governance system, but it is less stable and vulnerable to
other indexes. The data governance subject as the governance subject of
the supply chain data governance ecosystem is classified as the result
element, which reflects that the current governance situation of the
data governance subject is more and more passive, and the governance
behavior needs to rely on data governance technology, data and services
as support.</div><div>According to the comparison of the centrality of B-level indexes,
technology and tools, internal environment, users and supply chain
services are ranked high, among which the internal environment and users
are more influenced, resulting in their centrality ranking among the
top, that is, technology and tools and supply chain services are the key
factors affecting the governance system, while internal environment and
users are in a passive position in the system.</div><div>(2) Causal elements and centrality analysis</div><div>C-level indexes can more accurately and comprehensively assess the
optimization effectiveness of supply chain data governance ecosystem.
Based on the positive and negative comparison of C-level indexes, we can
find that the supply chain data governance ecosystem index system
consists of 13 cause elements and 11 result indexes, and the order of
index centrality is C14, C9, C7, C24, C4, C10, C21, C12, C5, C19, C22,
C8, C16, C15, C13, C23, etc. Combining the cause elements and
centrality, it can be seen that C9, C24, C21, C12, C5, C22, C8 and C16
are the key impact indexes in the governance system, which can directly
shape the governance effectiveness fluctuations and have a greater
impact on other indexes.</div><div>Among them, data operation technical support has the greatest direct
impact among all indexes, indicating that data technical support in the
process of governance is a key bearing index for the effectiveness of
governance optimization, and improving the level of data operation
technology of supply chain enterprises and industrial Internet can
guarantee the perfection of data governance infrastructure, effectively
resist the problems of data circulation, storage, collection, exchange
and sharing to upstream and downstream subjects of supply chain and
industrial Internet platform through supply chain. It helps to enhance
the intelligent construction of industrial Internet and strengthen the
core competitiveness of enterprises, construct a good service and
innovation environment for the information platform, and promote the
sustainable development of supply chain data governance ecosystem.</div><div>(3) Resulting elements and centrality analysis</div><div>Combining the result factors and centrality, it can be found that the
cause degree of C14, C7, C4, and C6 become negative and their are
affected to a greater degree. This suggests that they are vulnerable to
fluctuations in the governance system. Although their centrality is
high, they are not counted in the screening of key indexes in this study
due to the low ranking of the influence degree of the indexes.</div><div>C13, C15 and C23 are ranked in the middle in terms of centrality and
reason and they are influenced by a greater degree. They are the easiest
governance points and also belong to the key indexes. Data governance
subjects should focus on these four indexes in the governance process.
Therefore, in order to effectively improve the effectiveness of data
governance optimization, it is necessary to collaborate with all value
subjects in the governance system. Each subject should not only
reasonably plan the data governance optimization system and improve data
governance organization construction, but also open up the data flow of
each business node and information system and enhance the core
competitiveness of supply chain node enterprises and industrial Internet
enterprises.</div><div>4.1.7. Cause-and-effect four-quadrant diagram analysis</div><div>Based on the data in Table 3, the inter-index causality diagram for
supply chain data governance optimization is established by quadrant
determination method with centrality as the x-axis and causality as the
y-axis, and the values of each index are plotted one by one in the
diagram (Fig. 1). Among them, since the median indicates the sample
distribution based on the middle value, the set of values can be
stratified equivalently. Therefore, the median x=4.41, which corresponds
to the centrality of 24 indexes, is added to the graph as the internal
auxiliary axis z. The purpose is to visualize the centrality and
causality of indexes, so as to visually observe the distribution pattern
of indexes and reasonably screen the key indexes.</div>