Do staff capacity and performance-based budgeting improve organisational performance? Empirical evidence from Chinese public universities

The COVID-19 pandemic exacerbated financial challenges for higher education institutions, increasing the focus on efficiency and effectiveness. Performance-based budgeting (PBB), which links funding to results, is gaining traction as a resource allocation method. This study focuses on Chinese public universities, a context characterized by a centralized management system and a lifetime employment system for accounting staff, which may hinder PBB adoption. The research aims to understand the influence of staff capacity on PBB implementation and organizational performance in this specific context. It leverages contingency theory and resource dependency theory to examine the relationships between staff capacity, PBB implementation, and university performance, also investigating the moderating influence of top management support. The study addresses a gap in the literature by examining these factors within Chinese public universities and using a multi-method approach combining PLS-SEM and NCA, a combination not previously explored in accounting research. This research is significant as it provides insights for improving university funding efficiency, lowering costs, and increasing revenue within the unique context of Chinese public universities.

The literature review establishes the theoretical foundation by integrating contingency theory and resource dependency theory (RDT). Contingency theory emphasizes that the optimal organizational structure is dependent on the specific circumstances, whereas RDT highlights the importance of resource control and power dynamics within organizations. The review discusses previous research on staff capacity, defining it as possessing necessary skills and knowledge, receiving appropriate training, and having sufficient numbers. Existing studies on the impact of staff capacity on PBB implementation have yielded mixed results. The literature on PBB implementation in higher education institutions, especially in contexts outside the United States, is limited. The concept of top management support (TMS) is defined as providing adequate resources, direction, and commitment. The review explains how university performance is multifaceted, encompassing both financial and non-financial aspects, and acknowledging the challenges of accurate measurement in this context. The review also discusses the impact of China's unique governmental policies and cultural context on university budgeting and management.

This study uses a quantitative research design employing a questionnaire survey. Purposive sampling was used to select 271 participants from the financial and audit departments of Chinese public universities, ensuring that respondents possessed relevant knowledge and experience with PBB. A power analysis determined the minimum required sample size (159). The questionnaire items were adapted from existing literature and underwent a pilot study to ensure clarity and comprehensibility. The survey was administered online using Wenjuanxing, WeChat, and QQ groups. Data analysis involved PLS-SEM to assess the structural model and relationships between constructs, the PROCESS macro for moderated mediation analysis, and NCA to identify necessary conditions. Measures were assessed for reliability (Cronbach's alpha, composite reliability), convergent validity (factor loadings, AVE), and discriminant validity (Fornell-Larcker criterion, HTMT). Common method bias was addressed using Harman's single-factor test and an ULMC approach. Robustness checks included CTA-PLS for measurement models and RESET tests for nonlinearity in the structural model. The Johnson-Neyman technique was used to determine the range of top management support for which the moderation effect was significant.

PLS-SEM analysis revealed that staff capacity significantly and positively affects PBB implementation (β = 0.712, p < 0.001). PBB significantly and positively impacts university performance (β = 0.694, p < 0.001). However, the direct effect of staff capacity on university performance was not significant (β = 0.059, p = 0.405). Mediation analysis showed a significant indirect effect of staff capacity on university performance through PBB (β = 0.494, p < 0.001), indicating indirect-only mediation. Moderated mediation analysis, using PROCESS model 59, showed that top management support positively moderates the relationships between staff capacity and PBB, staff capacity and university performance, and negatively moderates the relationship between PBB and university performance. The Johnson-Neyman technique revealed that the moderating effect was significant when top management support scores were below 1.291 or above 2.983. NCA confirmed that both staff capacity and PBB are meaningful and significant necessary conditions for university performance, with PBB exhibiting a stronger necessary condition effect (d = 0.324, p = 0.000). The bottleneck analysis showed that achieving higher levels of university performance requires increasingly higher levels of both staff capacity and PBB. Robustness checks supported the model's validity and the linearity of the relationships.

The findings provide strong support for the hypotheses and address the research questions. The results demonstrate the critical role of both staff capacity and PBB in achieving high university performance in the Chinese context. The mediating role of PBB highlights the importance of effective budgeting systems in translating staff capacity into improved organizational outcomes. The moderating role of top management support underscores the significance of leadership commitment and resource allocation in successful PBB implementation. The study's findings are particularly relevant given the current emphasis on efficiency and effectiveness in higher education institutions, especially in China, where its unique organizational structure and the lifetime employment system might affect PBB implementation. The study's findings contribute to existing literature by showing that the necessary conditions for university performance include both sufficient staff capacity and the implementation of PBB.

This study makes several significant contributions. It pioneers the combined use of PLS-SEM and NCA in accounting research, enriching methodological approaches. It integrates contingency theory and RDT to provide a robust theoretical framework for understanding PBB implementation in Chinese public universities. It highlights the critical role of staff capacity and PBB, along with the moderating influence of top management support, in improving university performance. The study's limitations include its focus on a single country and the use of self-reported data. Future research could explore cross-cultural comparisons, investigate the long-term effects of PBB, and examine other factors influencing university performance in more detail.

The study's generalizability is limited by its focus on Chinese public universities. The findings may not be directly transferable to other contexts with different organizational structures, cultural norms, or governmental regulations. Furthermore, the reliance on self-reported data increases the possibility of bias, although steps were taken to mitigate this issue. Future research should consider incorporating multiple data sources to validate the findings.