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Details

Autor(en) / Beteiligte
Titel
Systematic evaluation of integration between China's digital economy and sports industry: Two-stage grey relational analysis and vector autoregressive model
Ist Teil von
  • PloS one, 2024-05, Vol.19 (5), p.e0303572-e0303572
Ort / Verlag
United States: Public Library of Science
Erscheinungsjahr
2024
Link zum Volltext
Quelle
MEDLINE
Beschreibungen/Notizen
  • The development of the digital economy constitutes a key component of China's endeavors to advance towards "Digital China." The sports industry functions as a new catalyst for high-quality economic growth. This study systematically evaluated the integration between these two sectors. First, we conducted two levels of grey relational analysis to assess their integration between 2016 and 2021. Second, we conducted a VAR analysis to determine whether their integration between 2009 and 2021 represents a causal relationship. At the macro level, the grey relational analysis reveals that the sports industry (grade = 0.770) ranked second among China's eight key economic sectors in terms of digital economy integration. At the meso level, a wide variation (ranging from 0.606 to 0.789) existed in the grade of integration between the digital economy and the sub-sectors of the sports industry. According to the VAR model, the digital economy does not Granger cause (p = 0.344) the growth of the sports industry. This study yielded two added values to the existing literature: First, there exists a sectoral imbalance in the digitization process; second, the explosive growth of the sports industry was not primarily caused by the digital economy. Accordingly, the "sports + digital" complex is still in the first wave of technological integration. We propose three policy recommendations, namely, sectoral synergistic development, overtaking via esports IP, and new economy and new regulation. Collectively, these findings provide updated insights for the digital transformation towards "building a leading sports nation" and "Digital China."
Sprache
Englisch
Identifikatoren
ISSN: 1932-6203
eISSN: 1932-6203
DOI: 10.1371/journal.pone.0303572
Titel-ID: cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11090320

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