Using Data Envelopment Analysis and Multi-Criteria Decision-Making Methods to Evaluate Teacher Performance in Higher Education

PurposeThis study aims to experimentally evaluate the effects of strategic planning and financial system management on the performance of higher education institutions. Additionally, it examines how financial system management mediates the relationship between strategic planning and organizational performance in higher education (HE).Design/methodology/approachThis study adopts a quantitative approach. Offline and online questionnaires were distributed to academic staff at private universities in Indonesia to gather data for hypothesis testing. The SPSS macro was used to analyze responses from 249 participants and assess the proposed associations.FindingsThe findings indicate that strategic planning and financial system management have a direct impact on institutional performance. Strategic planning exerts a significant and positive influence on financial system management. Furthermore, financial system management serves as a significant mediating variable in the relationship between strategic planning and organizational performance.Practical implicationsTo effectively implement quality management in higher education, administrators must recognize the distinct roles of strategic planning and financial system management in improving organizational performance. To achieve optimal performance, higher education institutions must allocate resources to establish robust strategic planning and financial management practices.Originality/valueAlthough numerous studies have explored the relationship between strategic planning and organizational performance in higher education, research on financial system management in this context remains limited. This study is among the first to adopt a multidimensional approach to both strategic planning and financial system management in higher education, providing insights into their interdependence and practical significance for institutional leaders.

Planning strategies to achieve higher competitiveness of ports are becoming increasingly important in business environment. Therefore, strategic competitive position and efficiency analysis needs to be performed to increase ports’ effectiveness and competitiveness. This matches with one of targets of new concept e-Navigation to increase the agility and efficiency of ports. The purpose of this study was to apply Boston Consulting Group matrix to analyze competitive positioning of major ports in Korea and China in term of several main cargo types and then use a combination of Data Envelopment Analysis and Principal Component Analysis model to calculate efficiencies. Results show that, at the moment, Chinese ports are still on the top with high position and efficiency score for the representative-Shanghai port. However, result also points out that except container type, Korean ports have chance to compete in other cargo types. Moreover, Gwangyang port is regarded as efficient. It has better position time. It is believed that Gwangyang port together with Busan port can compete with Chinese port in the near future.

Value co-creation has become an increasingly important issue in higher education. Existing studies point out that value co-creation has many effects on students and teaching, but there are few studies on the effects of value co-creation on students’ course performance. Whether the degree of instructional value co-creation is reflected in student performance is the main issue of this study. Thus, with the course Digital Publication Design as the case study, this study uses a one-way analysis of variance (ANOVA) with a sample of 33 students to investigate the relationship between value co-creation and students’ course performance in higher education. The results indicate that the degree of value co-creation in the course does not positively affect the course grade, which may be related to the inadequacy of existing scoring mechanisms and the degree of student motivation to engage in co-creation. The paper concludes with further discussions of modifications to the experimental study to and for subsequent use of co-creation in higher education.

In the last decades, integral municipal solid waste management (IMSWM) has become one of the most challenging areas for local governmental authorities, which have struggled to lay down sustainable and financially stable policies for the sector. In this paper a model that evaluates the efficiency of IMSWMs through a combination of Data Envelopment Analysis (DEA) and an Artificial Neural Network (ANN) is presented. In a first stage, applying DEA, municipal administrations are classified according to the efficiency of their garbage processing systems. This is done in order to infer what modifications are necessary to make garbage handling more efficient. In a second stage, an ANN is used for predicting the necessary resources needed to make the waste processing system efficient. This methodology is applied on a toy model with 50 towns as well as on a real-world case of 21 cities. The results show the usefulness of the model for the evaluation of relative efficiency and for guiding the improvement of the system.

The appreciative democratic voice of DEA: A case of faculty academic performance evaluation

This study aims to determine the factors influencing the students' mathematics performance in higher education in Riau Province. The research population was all students in higher education in Riau Province majoring in mathematics. The samples of this research were some students in higher education majoring in mathematics education which were taken randomly with a proportional random sampling approach. The instrument in this research was a questionnaire developed and validated by experts and distributed to mathematics education students. The data analysis used in this research was path analysis. The results showed that there was an effect of learning motivation on mathematics performance, there was no effect of learning interest on mathematics performance, with a T Value of 1.28, (12) there was no effect of self-efficacy on mathematics performance, with T Values of 1.38, there was an effect of self-regulated on mathematics performance, with T Values of 2.23, and (15) there was no effect of learning involvement on mathematics performance, with T Value of 1.39 The dominant and significant factor in influencing the students' mathematics performance in higher education in Riau province during the COVID-19 Pandemic was learning motivation and self-regulation.

The emergence of digital society in industry 4.0 is one of the most visible changes in the XXI century. The creation of digitization has led to significant changes in accounting and financial management as features of an innovative University. This study aims to analyze the development of digital accounting and examine its impact on economic performance in higher education by using IBM SPSS Statistics 25 and the feasibility of the investment using the payback period approach. The development of digital accounting is based on a web 2.0-based ICT system using the Software Development Life Cycle (SDLC) method with the waterfall model and applying the latest financial accounting standards. Analysis of the impact of accounting digitization was carried out on 247 educational staff as a population and involved 152 respondents as samples selected using the Slovin formula. Data analysis consisted of descriptive statistics, correlation, and multiple regression analysis with an error rate of 5%. The findings showed a positive correlation between financial performance and accounting digitization. Accounting digitization significantly affected financial arrangement with a P-value of 0.000 is smaller than the alpha (α) of 0.05 or sig.T< 0.05, which means significant. The investment feasibility test using the payback period concludes that digital accounting is feasible to implement in higher education. The eligibility criteria based on the results of calculating the rate of return on investment is three years and two months, faster than the required payback period of four years.
 
 Received: 18 December 2022 / Accepted: 10 February 2023 / Published: 5 March 2023

The intensification of competition in higher education has heightened the strategic importance of brand communication in shaping enrolment performance, particularly in digitally mediated and adult-learning contexts. This focused literature review synthesizes prior research on enrolment performance in higher education regional institutions. The review of this study examines how enrollment as performance outcomes of higher education institution. The analysis reveals a clear evolution of enrolment performance from a narrow quantitative indicator to a multidimensional construct encompassing conversion effectiveness, cost efficiency, learner–institution fit, and sustainability. However, significant gaps persist in operationalizing enrolment performance, linking brand communication to intermediate digital metrics such as conversion rates, and incorporating adult learner perspectives in less-developed regions. By consolidating fragmented findings across disciplines, this review clarifies the conceptual and practical perspective of enrolment performance and identifies directions for future empirical research. The study contributes to higher education marketing scholarship by advancing a more integrated understanding that can support sustainable enrolment outcomes in competitive and resource-constrained environments.

Revenue management (RM) deals with selling the right product to the right customer at the right time at the right price through the right channel to maximise revenue. The innovation of RM lies in the way decisions are made. The performance of revenue management approaches can be evalu- ated against several criteria. Both discrete and continuous multicriteria models can be used to analyse RM. The performance pyramid is a comprehensive, fully integrated per- performance system that captures multiple perspectives such as internal, financial, customer and innovation. The assessment is based on a combina- tion of Analytic Hierarchy Process (AHP), Analytic Network Process (ANP) and Data Envelopment Analysis (DEA) approaches. Customer behavior modeling is gaining increasing attention in revenue management. Customer choice models can be extended with more inputs and more outputs. Evaluation of alternatives can be performed using DEA- based evaluation methods. The search for an efficient frontier in a DEA model can be formulated as a multiobjective linear programming problem. We propose to use an Aspiration Level Oriented Procedure (ALOP) to solve the problem. Keywords: revenue management, performance measurement, multiple criteria, Analytic Hierarchy Process (AHP), Analytic Network Process (ANP), Data Envelopment Analysis (DEA), customer behavior, efficient frontier, Aspiration Level Oriented Procedure (ALOP)

Data Envelopment Analysis (DEA) models and Free Disposal Hull (FDH) models were proposed almost simultaneously in the scientific literature. In DEA models, the constraints generate a convex set. For this reason, optimization methods and software are widely used for modeling and computations for these models. Non-convexity of production possibility set of FDH models refrained significantly the development of these models. In this paper, two methods are proposed for two-and three-dimensional frontier visualization for DEA and FDH models. Computational experiments using real-life datasets documented reliability and effectiveness of proposed methods.

Data envelopment analysis (DEA) is a non-parametric technique for measuring the efficiency of decision making units (DMU) with exact input and output terms. So far, a number of DEA models with interval data have been developed. The radial DEA model such as CCR or BCC model with interval data are well known as basic DEA models with interval data. However, these radial DEA models have some defects. In this study, we develop a new approach based upon the slacks-based measurement (SBM) of super-efficiency model for dealing with interval data in DEA. The SBM super-efficiency DEA model can not only discriminate the performance of efficient DMUs from inefficient ones, but can distinguish between the efficient DMUs. In addition, this model can overcome the drawback that the super-efficiency model can be infeasible under variable returns to scale (VRS) assumption. An illustrative example is provided to verify the idea of this paper and show its potential application and validity.

In the ever-changing world of higher education services, examining factors that impact students’ performance is important in making sure that student’s learning experience can be improved to reach academic success. This research investigates the impact of University Servicescape (USc) and Information Systems Implementation Quality (ISQ) on student performance in higher education institutions in Malang. USc refers to the physical environment and facilities provided by the university. At the same time, the ISQ pertains to the effectiveness and efficiency of the technological systems employed for academic and administrative purposes. Both factors have been deeply researched separately in the context of higher education service management, but no research has delved into both at the same time. A quantitative empirical survey-based study is employed to examine this topic. The sample consists of university students studying in Malang, East Java, Indonesia. The results empirically show that USc and ISQ significantly impact university student performance in higher education, particularly within institutions in Malang, East Java, Indonesia. These findings should be useful for policymakers, university administrators, and educators in enhancing the delivery of educational services in higher education institutions across Indonesia

Relevance. Public health effectiveness is crucial for population health, especially in the face of global challenges like the COVID-19 pandemic. The study applies the Data Envelopment Analysis (DEA) model to measure the efficiency of operating costs in the health care system across various regions of Kazakhstan from 2017 to 2021. Existing methods for assessing healthcare effectiveness often overlook the system's complexity, which turns DEA into a valuable tool to identify inequalities in healthcare availability and quality. Research objective. This study aims to employ the DEA model to measure the efficiency of operating costs in the health care system across regions of Kazakhstan in 2017-2021. Data and methods. The DEA model was chosen for its ability to analyze the efficiency of operating costs. Data were collected from the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan. Results. Our findings indicate the need for increased healthcare financing in specific regions, emphasizing the importance of transparent spending. The study concludes that the DEA model can regularly assess health financing, ensuring resources are directed where most needed. The novelty lies in establishing a link between financing and health outcomes. Conclusions. The study's results and methodology can be used by public health authorities in assessing operating costs' effectiveness, allocating resources judiciously, and making informed decisions to enhance the healthcare system.

Efficiency and performance evaluation is an important task in governmental decision making. This paper aims in application of analytic hierarchy process (AHP) for efficiency analysis of a general set of decision making units (DMUs). Conventional tool for analysis of efficiency of DMUs is data envelopment analysis (DEA). DEA models allow splitting the set of DMUs into two subsets - efficient and inefficient. The inefficient ones can be ranked according to their efficiency scores given by the DEA model but the efficient units cannot be ranked easily as their have identical maximal efficiency score. Various models have been proposed for ranking of efficient units in DEA. The aim of the paper is to discuss the possibility of application of AHP models for ranking of efficient or entire set of DMUs. The proposed approach is illustrated on performance evaluation of 19 Czech economic faculties. The results given by the AHP ration model are compared to those given by conventional approaches.

The paper aims in application of analytic hierarchy process (AHP) for efficiency analysis of the set of decision making units (DMUs).Conventional tool for analysis of efficiency of DMUs is data envelopment analysis (DEA).DEA models allow splitting the set of DMUs into two subsets -efficient and inefficient.The inefficient ones can be ranked according to their efficiency scores given by the DEA model but the efficient units cannot be ranked easily as their have identical maximal efficiency score.Many models have been proposed for ranking of efficient units in DEA models.The aim of the paper is to discuss the possibility of application of AHP models for ranking of efficient or entire set of DMUs.Numerical experiments are realized on the set of 20 commercial banks operating on the Czech financial market.The study is based on a real data set containing financial characteristics of the banks.