Annual audit planning is a multi-criteria decision-making problem faced by internal audit departments of all organizations. Due to the constrained audit resources, the planning process primarily involves the analysis and evaluation of complex factors for selecting auditable units that maximize the full potential of internal audit. Previous research on internal audit planning only focused on the goal of risk minimization and applied ranking methods to prioritize alternatives. In order to enable internal audit activities to add more value to the organization, the integrated risk-based internal audit planning is proposed to assist audit department in achieving multiple objectives in addition to risk management. Meanwhile, a multi-stage framework is proposed to support the development of such value-added internal audit plan. The new framework integrates the risk assessment of auditable units with the selection of audit activities and resource allocation through a combined analytic hierarchy process (AHP), fuzzy comprehensive evaluation (FCE) and weighted multi-choice goal programming (WMCGP) approach. The model considers both qualitative and quantitative decision criteria. A real-life case study of the development of an integrated risk-based annual audit plan is presented, and sensitivity analysis is performed to illustrate the validity of the proposed approach. The results indicate that the proposed framework is a useful tool for internal audit planning and the implications of the study can be extended to various selection and allocation problems.

As an essential element of higher education, course planning at the program level is a complicated multi-criteria decision making (MCDM) problem. In addition, a course planning process tailored to sustainable development is exceptionally important to sustaining the quality of academic programs. However, there is a scarcity of research on the program course planning problem at the operational level due to a diverse set of stakeholder requirements in practice. Motivated by the challenge, this study proposes an innovative MCDM model for sustainable course planning based on He-Xie management theory. In the introduced framework, the best worst method (BWM) can obtain the optimal weights of sustainability competencies, which are then embedded into the fuzzy filter ranking (FFR) method to generate the ranking of candidate courses by each course module, considering the connectivity between courses and the development of sustainability competencies. Finally, multi-choice goal programming (MCGP) is adopted to allocate each selected course to a semester, aiming to balance total credits and average difficulty level among semesters as much as possible. The practicability and reliability of the proposed course planning model is validated through a case study of an undergraduate accounting program. Results show that the proposed framework is a feasible tool for course planning. This research extends the existing literature on course planning by explicitly capturing the fuzzy nature of human decision making and avoids underestimation of the decision. The implications of the paper are not restricted to developing a sustainable course plan for an accounting program.

Ciphertext policy Attribute-based encryption (CPABE) plays an increasingly important role in the field of fine-grained access control for cloud storage. However, The exiting solution can not balance the issue of user identity tracking and user revocation. In this paper, we propose a CP-ABE scheme that supports association revocation and traceability. This scheme uses identity directory technology to realize single user revocation and associated user revocation, and the ciphertext re-encryption technology guarantees the forward security of revocation without updating the private key. In addition, we can accurately trace the identity of the user according to the decryption private key and effectively solve the problem of key abuse. This scheme is proved to be safe and traceable under the standard model, and can effectively control the computational and storage costs while maintaining functional advantages. It is suitable for the practical scenarios of tracking audit and user revocation.

The establishment of a robust faculty performance evaluation system has become a research hotspot, as it is crucial for the continuous improvement and sustainable development of higher education institutions. However, according to available literature, the need for an easy-to-use management tool for faculty performance evaluation—one that accounts for professional tracks—within the context of China’s application-oriented universities remains unaddressed. This study presents a new evaluation framework for measuring and ranking faculty performance, tailored to the characteristics of application-oriented universities. The proposed model applies hybrid multi-criteria decision making (MCDM) techniques through a three-step approach. First, a set of measurement indicators is developed based on a comprehensive review of existing literature and faculty assessment forms used by application-oriented universities in practice. Second, in line with the classification of faculty members’ career tracks, the MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) method is utilized to determine the weights of evaluation criteria for each professional track. Finally, the FFR (Fuzzy Filter Ranking) approach is employed to rank faculty performance and identify outstanding faculty award winners. The applicability and utility of the proposed methodology are validated through a case study of an application-oriented university in China, which demonstrates its value as an effective evaluation tool and decision-aiding reference for faculty performance assessment. This study offers an intuitive and readily applicable solution for university stakeholders, streamlining the processes of weight assignment and faculty ranking within performance evaluations. Moreover, it can be extended to address other evaluation problems in academia, thereby contributing to the enhancement of educational quality.