Comparison of recent literature (2023–2025) and the present study
| Dimension | Related Studies (2023–2025) | Present study |
|---|---|---|
| Research focus | Tickle et al. (2024) investigated how 4PL adoption influences agility, adaptability, and alignment (AAA) in humanitarian supply chains Rashid et al. (2025) analyzed the impact of digital transformation and smart logistics on disaster response Shakibaei et al. (2024) examined supply chain resilience in dynamic settings | This study integrates interpersonal (soft) skills with big data and predictive analytics to enhance humanitarian supply chain performance in Chinese NGOs, thereby addressing the gap in studies on the synergy between human resources and advanced data technologies |
| Theoretical framework | Recent studies often use qualitative approaches such as case studies, mixed methods, or semi-structured interviews, focusing on single variables | Utilizes a quantitative approach with 411 valid survey responses and employs structural equation modeling (SEM) to validate the mediating and moderating relationships, ensuring robust and generalizable findings |
| Research background | Focused on conflict zones, post-disaster scenarios, or settings in low- to middle-income countries (e.g. DRC, CAR, Kenya) | Focused on humanitarian supply chain management within Chinese NGOs, considering China’s unique sociocultural and organizational environment, thereby providing a localized yet representative empirical case |
| Key constructs/variables | Emphasis on logistics risks, facility location, 4PL adoption, or isolated performance indicators (Tickle et al., 2024; Rashid et al., 2025) | Simultaneously, interpersonal skills, BDPA, and resilience are examined to reveal the synergistic mechanisms influencing HSCP |
| Contributions/research gap | While advances have been made in digital transformation and technology applications, studies (Tickle et al., 2024; Rashid et al., 2025; Shakibaei et al., 2024) generally address single dimensions without integrating human resource factors systematically | This study is the first to systematically integrate interpersonal skills with big data and predictive analytics, extending RBV and DCT in the humanitarian supply chain context and offering concrete managerial recommendations for Chinese NGOs |
| Dimension | Related Studies (2023–2025) | Present study |
|---|---|---|
| Research focus | This study integrates interpersonal (soft) skills with big data and predictive analytics to enhance humanitarian supply chain performance in Chinese NGOs, thereby addressing the gap in studies on the synergy between human resources and advanced data technologies | |
| Theoretical framework | Recent studies often use qualitative approaches such as case studies, mixed methods, or semi-structured interviews, focusing on single variables | Utilizes a quantitative approach with 411 valid survey responses and employs structural equation modeling (SEM) to validate the mediating and moderating relationships, ensuring robust and generalizable findings |
| Research background | Focused on conflict zones, post-disaster scenarios, or settings in low- to middle-income countries (e.g. DRC, CAR, Kenya) | Focused on humanitarian supply chain management within Chinese NGOs, considering China’s unique sociocultural and organizational environment, thereby providing a localized yet representative empirical case |
| Key constructs/variables | Emphasis on logistics risks, facility location, 4PL adoption, or isolated performance indicators ( | Simultaneously, interpersonal skills, BDPA, and resilience are examined to reveal the synergistic mechanisms influencing HSCP |
| Contributions/research gap | While advances have been made in digital transformation and technology applications, studies ( | This study is the first to systematically integrate interpersonal skills with big data and predictive analytics, extending RBV and DCT in the humanitarian supply chain context and offering concrete managerial recommendations for Chinese NGOs |
Source(s): Authors’ own creation/work
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