University Resource Allocation Research Articles

Practice and Reflection on the Transformation of Performance-Oriented Higher Education Financial Digitization Platform

The realization of performance-oriented transformation of financial intelligence in universities is an inevitable choice for universities to achieve high-quality education in the new era. How to achieve deep integration of university finance and intelligence transformation based on performance, and how to optimize the allocation of university resources based on the construction of intelligent platforms, are issues that need to be studied at the current stage. This paper first introduces the background of performance-oriented transformation of financial intelligence in universities, revealing the practical background of this research. Then, it starts with the connotation and significance of performance-oriented financial intelligence transformation, focusing on the system architecture of financial intelligence transformation in universities. It elaborates on the system architecture of financial intelligence transformation from four aspects: budgeting, execution, monitoring, and evaluation. Furthermore, platform design is conducted based on this, specifically introducing the construction of three major modules of the university intelligence platform: financial service system, financial data exchange center, and financial decision system. Finally, this paper puts forward some suggestions for the intelligent transformation of university finance.

Do Financial Investment, Disciplinary Differences, and Level of Development Impact on the Efficiency of Resource Allocation in Higher Education: Evidence from China

Optimizing the allocation of university resources to improve the efficiency of inputs and outputs is an important issue for the high-quality development of universities. In recent years, China has become an important growth pole for the development of global higher education. In particular, Chinese agricultural universities, with their distinctive disciplinary characteristics and outstanding professional advantages, have made important contributions to the sustainable development of agricultural education around the world. In contrast, academic research on the efficiency of resource allocation in Chinese agricultural universities is very limited. To fill this gap, this study was guided by econometrics and took high-level agricultural universities in China as the research object to measure the effects of financial investment, disciplinary differences, and development level on the level of resource allocation efficiency of universities. With the help of a data envelopment model (DEA) and a Malmquist index decomposition model, we found that the overall level of resource allocation efficiency in the sample universities was high, but there were great disparities in resource input–output effectiveness between universities. In many universities, marginal inputs exceeded marginal outputs, resulting in input redundancy and resource wastage. In addition, this study shows that for high-level agricultural universities, the regression of capital input technology is preventing a sustained increase in productivity, which places the total factor productivity of resource allocation in a diminishing state.

Exploration and Practice of Reasonable Allocation of Inorganic Chemistry Laboratory Resources in Universities

Exploration and Practice of Reasonable Allocation of Inorganic Chemistry Laboratory Resources in Universities

Optimizing Allocation of Course Resources in the Colleges of Science and Engineering: a Case Study on the Course Enrollment Database of a University in Beijing

A course selection (CS) model is constructed based on the course enrollment database from a Chinese university in this research. By using big-data analysis on the database, we study the factors that may determine the students’ CS and we investigate how to optimize allocation of course resources. Our results reveal that the allocation of course resources (type of courses) and the recent revision of academic programs will significantly influence students’ CS. Courses on natural science and engineering (type-b courses), as well as on literature and art (type-d courses), are becoming most popular in course enrollment, which are followed by practical employment-related courses (type-c courses) such as law and management. The core courses of the major (type-a courses) are least selected. Since the new academic program was implemented, type-b courses have been becoming more popular but type-c and type-d courses are less enrolled than before. Our findings can be referenced by policy makers to improve the allocation of course resources in universities, which will benefit the students’ CS and satisfy the demands from society. Our results will also serve as important information for improving education efficiency.

Benchmarking in Vietnam universities: teaching and research and revenue efficiencies

Assessing university resource allocation or misallocation is necessary to understand its impact on research and teaching productivity. To achieve this insight, this study conducts a two-stage data envelopment analysis to judge the “teaching and research efficiency” and “revenue efficiency” of 61 universities in Vietnam. We analyze what variables have the most effect on the efficiencies of the universities through improving results. Moreover, this research applies scale elasticity to distinguish the benchmark performance leader among Vietnam universities. Results indicate that universities are more efficient in terms of “revenue efficiency” than “teaching and research efficiency.” The scale elasticity decomposition findings show that multidisciplinary universities perform better than those specializing in science and technology and social science and economics. Finally, the competitive map to performance advancement strategies is exhibited. This map helps the university management to enhance their efficiencies.

The struggle to satisfy need: exploring the institutional cues for teaching support staff

ABSTRACTThe decision-making around resource allocation in universities is complex. It plays out through the structures of governance and bureaucracy, through interactions with colleagues, workplace cultures and through day-to-day individual work practices. To survive and succeed within this complex environment, teaching support staff need to be sensitive to the cues provided by their institution. This paper focuses on the cues available to teaching support staff within university strategic plans and considers the effects these cues may have on their day-to-day decision-making. The results provide a sample of the competing cues that have an impact on teaching support staff and provide a foundation for a reconsidered approach to university strategic planning.

Evaluation of Chongqing municipal universities' scientific research performance

Objective To improve the utilization efficiency of scientific research resources and optimize the allocation of resources in universities on the basis of scientific research performance evaluation. Methods This article selects the data envelopment analysis study for twelve universities in Chongqing, using MaxDEA 6.0 software to get the results of effectiveness of universities scientific research performance. Results DMU6 and DMU8 are in a fully effective state, DMU4, DMU5, DMU10, DMU11 are in invalid state, the remaining eight universities are in effective or weak state. Conclusion There are only two universities in Chongqing ordinary higher institutions whose scientific research input and output are relatively reasonable. The rest universities need to make more or less improvement and most universities need to make a little change. Key words: Universities; Performance of scientific research; Data envelopment analysis; The distribution of resources

Implications of University Resource Allocation under Limited Internal Adjustability

This paper provides a theoretical framework for explaining counterintuitive behaviors of a university choosing an unfavorable consequence in the long term while attempting to optimally allocate its resources in the short term. Our analysis demonstrates the process through which conflicting interests among different departments within an institution may lead to an internal allocation arrangement, which would not necessarily yield the highest possible outcome for the whole.

A Cloud-computing-based Resource Allocation Model for University Resource Optimization

The resource allocation is the basic guarantee for the effective implementation of the university development strategy, while resource allocation mechanism is an effective control measure to strengthen the university management. So the importance of resource allocation has caused widespread attention and concern of university administrators. Combining with the actual situations and encountered problems of university resource management, we introduced cloud computing ideas and proposed a cloud-computing-based resource allocation model to conduct a preliminary exploration and research on this issue. We first formulated the resource allocation problem, and then proposed the resource allocation concept model and its corresponding application model in universities. Based on the proposed model, we further expanded detailed analyses and descriptions on resource definition and description, resource allocation rules and methods, resource management mode, and a general mathematical model of resource allocation optimization in university. Finally, we gave a cloud-computing-based university resource allocation framework to offer references and consult for further applications of technology based on cloud computing in the university resource construction, aiming to achieve optimal university resource allocation and improve teaching quality and efficiency.

Impact of a formal mentoring program on academic promotion of Department of Medicine faculty: A comparative study

Purpose: To evaluate the impact of a formal mentoring program on time to academic promotion and differences in gender-based outcomes.Methods: Comparisons of time to promotion (i) before and after implementation of a formal mentoring program and (ii) between mentored and non-mentored faculty matched for covariates. Using paired-samples t-testing and mixed repeated measures ANCOVA, we explored the effect of mentor assignment and influence of gender on time to promotion.Results: Promotional data from 1988 to 2010 for 382 faculty members appointed before 2003 were compared with 229 faculty members appointed in 2003 or later. Faculty appointed in 2003 or later were promoted 1.2 years (mean) sooner versus those appointed before 2003 (3.7 [SD = 1.7] vs. 2.5 [SD = 2], p < 0.0001). Regardless of year of appointment, mentor assignment appears to be significantly associated with a reduction in time to promotion versus non-mentored (3.4 [SD = 2.4] vs. 4.4 [SD = 2.6], p = 0.011). Gender effects were statistically insignificant. Post hoc analyses of time to promotion suggested that observed differences are not attributable to temporal effects, but rather assignment to a mentor.Conclusions: Mentoring was a powerful predictor of promotion, regardless of the year of appointment and likely benefited both genders equally. University resource allocation in support of mentoring appears to accelerate faculty advancement.

Intellectual capital and university performance in Taiwan

Assessing university performance is an important yet complex issue. Knowing whether policy is effective in achieving its goal of advancing teaching and research is critical. Furthermore, at the level of implementation, it is necessary to understand if university resource allocation is sufficiently efficient for delivering expected results. To achieve this insight, this study utilizes a two-stage data envelopment analysis to evaluate the cost and teaching and research efficiencies of public universities in Taiwan. Additionally, this paper also employs a truncated-regression to discuss whether intellectual capital affects the operating efficiency of universities. The results demonstrate that the universities are much better at handling cost efficiencies than teaching and research efficiencies. The regression analysis indicates that intellectual capital does play an important role in influencing teaching and research efficiency. Finally, the conceptual roadmap to performance improvement strategies, which helps the manager and/or authorities to improve their operating efficiencies, also is presented.

The University and Social Justice

Considerations of social justice pertain to universities with respect to reserved spaces for applicants from disadvantaged groups, targeted hiring, differential student fees or faculty workloads and salaries, and similarly contested matters. This paper displaces debates over what constitutes just allocation of university resources from those over theories of justice in general to those about alternative visions of the proper goal of universities. To this end, educational and democratic theories of John Dewey are drawn on as an alternative to elitist conceptions and the implications of these competing viewpoints for specific justice-related issues are explicated.

Budgeting and resource allocation in universities: a public choice approach

The calls for colleges and universities to improve their productivity are coming thick and fast in Brazil. Many studies are suggesting evaluation systems and external criteria to control the quality of teaching and research in universities. Since universities and colleges are not profit-oriented organizations (considering only the legitimate and serious research and teaching organizations, of course), the traditional microeconomics and administrative variables used to measure efficiency do not have any direct function. An alternative would be to create an "as if" market control system to evaluate performance in universities and colleges. Internal budget and resources allocation mechanism can be used as incentive instruments to improve quality and productivity. It will be the main issue of this article.

TRANSPARENCY, ACCOUNTING KNOWLEDGE AND PERCEIVED FAIRNESS IN UK UNIVERSITIES' RESOURCE ALLOCATION: RESULTS FROM A SURVEY OF ACCOUNTING AND FINANCE

This paper provides the first published ‘bottom up’, as opposed to ‘top down’ view of how universities allocate resources to academic subjects. It reports results from a survey of how university resource allocation is seen and understood by a particular academic subject group, Accounting and Finance, the one subject group which may be assumed to be professionally competent to deal with resourcing methods. It shows that there are significant differences amongst UK universities in the use of financial information for academic management and in the transparency to academic subject groups of university planning and resource allocation. Perhaps the most important findings are that it is only with a high degree of such transparency that resource allocations are likely to be perceived to be fair and that this perceived fairness may be related to formal features of accounting knowledge.

The Security Survey: Creating A Proactive Foundation for Campus Crime Prevention

Crime on American campuses is an issue of concern to students, parents, staff and community leaders. While various methods of crime prevention and security have been initiated by campus communities, both large and small, little attention has been placed on the importance of the security survey as a vehicle for developing proactive crime prevention strategies and allocation of university resources. This article reviews applicable literature and substantively defines the necessary components for a campus security survey and its proper implementation.

Three-phase hierarchical allocation of university resources via interactive fuzzy goal programming

This paper proposes interactive fuzzy goal programming models for the efficient allocation of financial and academic resources in universities, which addresses both the problem of making the most satisficing decisions among alternative courses of action and the efficient substitution and expansion of university resources by means of feedback from and interaction with decision makers. The proposed modeling procedures take into account both decision making in a fuzzy environment and the decentralized nature of decision processes within the university, which are largely ignored by the existing literature on academic resource allocation problems. In order to model the hierarchical allocation process in a way which takes account of different levels of decision making, i.e. university, college and department level allocation decisions, we develop multiphase decomposition submodels. The decomposition modeling schemes are designed for predicting how lower-level decision makers will react once higher-level decisions are made. Finally, applications of the mathematical models to the Ohio State University are presented and discussed.

A multiobjective planning model for university resource allocation

Application of systematic approaches and dynamic planning for efficient resources allocation in institutions of higher education has been quite prevalent the past fifteen years. However, most models developed for university management have focused upon the analysis of input (budget/resource) requirements. They have generally neglected the existing environment, unique institutional values, and bureaucratic decision structures. In this study, a large scale goal programming model is developed for an efficient allocation of resources for an entire university for a five year planning period. The results of the model have been implemented in the form of administrative actions to achieve a set of multiple objectives.

Resource allocation models and the budgeting process

AbstractA powerful yet straightfonoard computer‐based approach to university resource allocation has been successfully integrated with group process techniques to assist top‐level administrators in making difficult choices.

University planning, decentralization and resource allocation

This paper proposes a system of resource allocation in universities which addresses both the problem of useful simulation of alternatives and efficient substitution of resources. It is the authors' view that the reasons why various university planning models proposed in the last few years have not been found useful in practice is that they take inadequate account of the decentralized nature of decisionmaking within universities. In this regard the three main points of the paper are: (1) university planning models should have flexible aggregation categories which can be determined and re-adjusted by the decisionmaker as he uses it; (2) resource constraints in university planning models should be flexible and negotiable, and negotiation over resources should be part of the analyst's domain of inquiry; (3) planning in universities must take into account the problem of introducing incentives which cause the behavior of individuals within the university to be directed to the needs of the institution's clienteles.

Incentives and Resource Allocation in Universities

How universities should adapt to an environment in which growth, both of enrollments and of public financial support, will be much slower than in the past is an important contemporary issue. In the years between World War II to the mid-sixties, intensified instructional and research demands contributed to a rapid expansion of almost all university programs. In the recent past, however, a perceived lessening of the rate of return to higher education, combined with a declining college age population, has contributed to a diminished growth rate of both demand and support. These changing historical circumstances have made resource allocation a critical problem confronting university administrators, who in the 1970s face contracting budgets, and who are saddled with economic and political problem-solving mechanisms inherited from an era of nearly unlimited growth. A new resource allocation mechanism is needed that will allow universities the flexibility and that will provide the incentives to adapt to changing educational demands in the coming decades. One currently proposed method of university resource allocation is a