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All Journal Indonesian Journal of Multidisciplinary on Social and Technology Green Inflation: International Journal of Management And Strategic Business Leadership
Andiko Tongga
Universitas Esa Unggul
Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Social Sciences

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Viral Negative Social Media, Cancel Culture, and Private Hopital Reputation: Moderating Roles of Positive eWOM Andiko Tongga; Lionis Pratiwi; Muhamad Riski Aldair
Green Inflation: International Journal of Management and Strategic Business Leadership Vol. 3 No. 3 (2026): August : Green Inflation: International Journal of Management and Strategic Bus
Publisher : Asosiasi Riset Ilmu Manajemen Kewirausahaan dan Bisnis Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61132/greeninflation.v3i3.759

Abstract

The increasing use of social media has enhanced private hospitals’ exposure to negative digital content that may affect public perceptions and trigger cancel culture. This study investigates the relationships among Negative Social Media Content Virality, Positive Electronic Word-of-Mouth (eWOM), Corporate Reputation Shield, and Cancel Culture to identify digital reputation protection mechanisms in private hospitals. A quantitative cross-sectional approach was conducted involving 196 respondents selected through purposive sampling. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS and 5,000 bootstrap subsamples. The results indicate that Positive eWOM and Corporate Reputation Shield simultaneously influenced Negative Social Media Content Virality (R² = 0.216; p < 0.001). Negative Social Media Content Virality significantly affected Cancel Culture (β = −0.332; p < 0.001), while Corporate Reputation Shield reduced Negative Social Media Content Virality (β = −0.459; p < 0.001). However, Positive eWOM and Corporate Reputation Shield did not significantly moderate the relationship between Negative Social Media Content Virality and Cancel Culture. These findings highlight that Corporate Reputation Shield functions more effectively as a direct predictor. Strengthening reputation through service quality, transparent communication, patient safety, and stakeholder engagement can help hospitals manage negative digital issues.
Strengthening Fiscal Transparency through Digital Public-Sector Accountability, Data-Driven Governance, and Artificial Intelligence Retno Ulfayatun Hidayah; Noor Sidharta; Indah Mustikawati; Andiko Tongga
Indonesian Journal of Multidisciplinary on Social and Technology Vol. 4 No. 3 (2026): Juli - Oktober
Publisher : PT Ilmu Data Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.69693/ijmst.v4i3.14476

Abstract

Transformasi digital dapat memperkuat akuntabilitas sektor publik dan transparansi fiskal, meskipun efektivitasnya bergantung pada tata kelola data dan pemanfaatan kecerdasan buatan (artificial intelligence/AI) secara bertanggung jawab. Penelitian ini mengkaji hubungan antara akuntabilitas digital sektor publik dan transparansi fiskal, termasuk peran mediasi tata kelola berbasis data dan pemanfaatan AI di Provinsi Sumatera Selatan. Penelitian menggunakan pendekatan kuantitatif eksplanatori melalui survei terhadap 100 pegawai bidang akuntansi, keuangan, audit, dan teknologi informasi pada instansi pemerintah daerah terpilih. Responden dipilih menggunakan purposive sampling, sedangkan data dikumpulkan melalui kuesioner terstruktur berskala Likert lima poin. Partial Least Squares Structural Equation Modeling (PLS-SEM) digunakan untuk mengevaluasi model pengukuran dan model struktural serta menguji pengaruh tidak langsung melalui bootstrapping dengan 5.000 resampling. Hasil menunjukkan bahwa akuntabilitas digital berpengaruh positif dan signifikan terhadap transparansi fiskal (β = 0,256; p < 0,001). Tata kelola berbasis data memediasi hubungan tersebut (pengaruh tidak langsung β = 0,263; p < 0,001; IK 95% [0,181; 0,366]), demikian pula pemanfaatan AI (β = 0,156; p < 0,001; IK 95% [0,076; 0,247]). Model menjelaskan 68,5% variasi transparansi fiskal (R² = 0,685). Temuan ini menegaskan pentingnya mengintegrasikan akuntabilitas digital, tata kelola data yang andal, dan AI dengan pengawasan memadai untuk mendukung pengelolaan fiskal yang transparan dan akuntabel.
Co-Authors Indah Mustikawati Lionis Pratiwi Muhamad Riski Aldair Noor Sidharta Retno Ulfayatun Hidayah