Assessment of wastewater utilities and priority determination of budget allocation using performance indicators in Korean

2007 ◽  
Vol 7 (5-6) ◽  
pp. 119-129
Author(s):  
S.G. Kim ◽  
J.Y. Koo ◽  
T.Y. Choi ◽  
A. Koizumi
Keyword(s):  
Cluster Analysis ◽  
Environmental Effects ◽  
Performance Indicators ◽  
Budget Allocation ◽  
Maintenance Management ◽  
Management Efficiency ◽  
Individual Scores

A budget of US $ 40.8 billion was allocated for wastewater utilities in Korea for the year 2004, but no definite standard for determining the appropriate budget allotted to wastewater utilities in Korea has been established. Thus, an effective method of determining the conditions of wastewater utilities and the allotment of an appropriate budget has been developed in this study. To this end, 36 indicators of the condition of Korean wastewater utilities were chosen, and then divided into four categories, namely: facilities, maintenance, management efficiency and environmental effects. The wastewater utilities of 48 Korean cities were allocated scores for each category based on their pertinent conditions. Through a cluster analysis, these cities were then subdivided into eight groups based on their individual scores for each category. From the cluster analysis, V and IV groups were found to be very good in all categories, I and II groups were average, III and VII groups required a bigger budget in the facilities category, IV group required a bigger budget in the maintenance category, and VIII group needed a bigger budget for both the facilities and maintenance categories. After examining the scores of all the groups in the different categories, it was determined that the facilities and maintenance categories were of the highest priority for the budget allocation.

Systematic Literature Review on Smart Mobility: A Framework for Future “Quantitative” Developments

2021 ◽  
pp. 088541222199424
Author(s):  
Mauro Francini ◽  
Lucia Chieffallo ◽  
Annunziata Palermo ◽  
Maria Francesca Viapiana
Keyword(s):  
Cluster Analysis ◽  
Literature Review ◽  
Systematic Literature Review ◽  
Performance Indicators ◽  
State Of The Art ◽  
Measurement Model ◽  
Broader Impacts ◽  
Research Goal ◽  
Smart Mobility ◽  
Definition Of

This work aims to reorganize theoretical and empirical research on smart mobility through the systematic literature review approach. The research goal is to reach an extended and shared definition of smart mobility using the cluster analysis. The article provides a summary of the state of the art that can have broader impacts in determining new angles for approaching research. In particular, the results will be a reference for future quantitative developments for the authors who are working on the construction of a territorial measurement model of the smartness degree, helping them in identifying performance indicators consistent with the definition proposed.

Public Accountability or Fiscal Control? Benchmarks of Performance in Australian Schooling

1996 ◽  
Vol 40 (1) ◽  
pp. 104-123 ◽  
Author(s):  
Louise Watson
Keyword(s):  
Performance Indicators ◽  
Service Provision ◽  
School Effectiveness ◽  
Measuring System ◽  
Government Schools ◽  
Public Resources ◽  
Government Education ◽  
Efficiency And Effectiveness ◽  
Performance Benchmarks

The Industry Commission review of service provision in school education aims to define performance benchmarks for Australia's eight government education systems, by providing comparative measures of efficiency in education provision. Such benchmarks are likely to lead to a reduction in the level of public resources for government schools unless it is possible to demonstrate the link between expenditure on schooling and school effectiveness. If efficiency audits like the Industry Commission review are to deal with issues of school effectiveness adequately, they should avoid the tendency of previous public sector audits to focus on financial data on schools expenditure to the exclusion of data on student achievement. This paper suggests an approach to measuring system performance which would establish benchmarks that reflected both the efficiency and effectiveness of Australian school systems, and warns against the misuse of performance indicators as an instrument in the determination of funding levels for schools.

ALOKASI ANGGARAN, INTELLECTUAL CAPITAL, KINERJA KEUANGAN, DAN INDIKATOR KINERJA UTAMA BADAN LAYANAN UMUM

2021 ◽  
Vol 07 (01) ◽  
Author(s):  
Setyo Budi Hartono ◽  
◽  
Wahab Zaenuri ◽  
Fania Mutiara Savitri ◽  
Dessy Noor Farida ◽  
...  
Keyword(s):  
Human Resources ◽  
Financial Performance ◽  
Path Analysis ◽  
Intellectual Capital ◽  
Performance Indicators ◽  
Intangible Assets ◽  
Budget Allocation ◽  
Intangible Asset ◽  
Tangible Assets ◽  
Tangible Asset

Abstrak: Penelitian ini ditujukan pada anggaran dalam bentuk intangible asset (sumber daya manusia) dan tangible asset (aset tetap dan persediaan) yang diprediksi dapat mempengaruhi intellectual capital, kinerja keuangan sekarang dan mendatang, serta indikator kinerja utama. Alokasi anggaran sebagai baromater prioritas dalam mengembangkan intellectual capital ditujukan untuk memenuhi performa keuangan bagi indikator kinerja utama organisasi. Populasi yang juga menjadi sampel yaitu unit dan fakultas pada UIN Walisongo Semarang sebanyak 30 unit. Metode pengambilan sampling menggunakan teknik sampel jenuh yang mengambil seluruh populasi. Data yang digunakan adalah data sekunder berupa laporan tahunan dan laporan pencapaian indikator kinerja utama tahun 2019-2020. Analisis data menggunakan path analysis. Hasil penelitian ini adalah alokasi APBN tahun 2019 UIN Walisongo hanya terfokus pada tangible asset sebesar 82%, sementara 18% dialokasikan untuk intangible asset. Intangible asset tidak berpengaruh secara terhadap semua hubungan, hanya tangible asset saja yang dapat mempengaruhi intellectual capital secara langsung dan kinerja keuangan sekarang secara tidak langsung. Berdasarkan hasil penelitian ini menunjukkan perlu dilakukan audit sumber daya manusia sehingga dapat ditetapkan alokasi kebutuhan anggaran bagi intangible asset-nya. Abstract: This research is aimed at the budget in the form of intangible assets (human resources) and fixed assets and inventories that are predicted to affect intellectual capital, current and future financial performance, as well as key performance indicators. Budget allocation as a priority barometer in developing intellectual capital is aimed at meeting financial performance for the organization's main performance indicators. The population that is also a sample is 30 units and architecture at UIN Walisongo Semarang. The sampling method uses a saturated sample technique that takes the entire population. The data used is secondary data in the form of annual reports and performance indicator reports for 2019-2020. Data analysis using path analysis. The results of this study were that the 2019 State Budget allocation of UIN Walisongo only focused on tangible assets by 82%, while 18% was allocated for intangible assets. Intangible assets do not affect all relationships, only tangible assets can directly affect intellectual capital and current financial performance indirectly. Results Based on this research, it is necessary to conduct an audit of human resources so that they can determine the allocation of budget requirements for intangible assets.

EFFECTIVENESS OF MANAGEMENT IN THE HIGHER EDUCATION

2021 ◽  
Vol 4 (48) ◽  
pp. 5
Author(s):  
O. Vorobyova
Keyword(s):  
Higher Education ◽  
Empirical Research ◽  
Performance Indicators ◽  
Point Of View ◽  
Educational Services ◽  
Management Effectiveness ◽  
Higher Education Management ◽  
Education Management ◽  
Management Efficiency ◽  
Theoretical Approaches

The article presents the results of empirical research of the main theoretical approaches to the concept of efficiency of management services in the field of higher education. It is determined that the concept of efficiency management is a complex multifaceted indicator that includes certain performance indicators related to efficiency, profitability, effectiveness, etc., in economics and management there is no single general approach to determining the effectiveness of management. It is proved that the effectiveness of management is a complex indicator that determines the use of resource opportunities to achieve a certain goal, and these concepts are complementary and interrelated, this approach from the point of view of economics is integrated with all management functions.Ключові слова: higher education; management efficiency; management effectiveness; management efficiency in higher education; educational services.

Development of a model for maintenance performance measurement

2019 ◽  
Vol 26 (1) ◽  
pp. 69-86
Author(s):  
Sungtae Ku ◽  
Changeun Kim
Keyword(s):  
Performance Indicators ◽  
Design Methodology ◽  
Quantitative Measurement ◽  
Maintenance Management ◽  
Case Study Method ◽  
Content Type ◽  
Energy Company ◽  
Practical Implications ◽  
Maintenance Performance

Purpose The purpose of this paper is to develop a model that can measure the equipment maintenance performance of the energy company K-company. Design/methodology/approach The case study method was adopted for the investigation of maintenance performance indicators (MPIs). The development of a model for measuring maintenance performance suggested new ways to apply the methodologies of existing papers to evaluate the level of maintenance. Findings Maintenance indicators, which are managed differently for each plant, were assessed for their performance relevance, applicability and data reliability and then standardized into five key MPIs. The MPI model, which enables comprehensive and quantitative measurement of maintenance performance using the five selected MPIs, was presented, and the criteria for assessing the maintenance level were presented in five stages. Practical implications The authors selected MPIs that match the characteristics of the company and proposed a model that can comprehensively and quantitatively evaluate maintenance performance. The model also standardizes maintenance indicators that are individually managed and provides a basis for comparing and indexing the level of maintenance indicators at each plant. Originality/value The criterion for selecting the key MPIs considering the characteristics of the company and a model that can comprehensively and quantitatively evaluate maintenance performance were presented. In addition, a standard for evaluating the level of maintenance at the global level of maintenance management was suggested.

Developing Maintenance Key Performance Indicators From Maintenance Work Order Data

2018 ◽  
Author(s):  
Michael P. Brundage ◽  
K. C. Morris ◽  
Thurston Sexton ◽  
Sascha Moccozet ◽  
Michael Hoffman
Keyword(s):  
Performance Indicators ◽  
Small And Medium Enterprises ◽  
Key Performance Indicators ◽  
Maintenance Management ◽  
Other Information ◽  
Maintenance Decisions ◽  
Maintenance Technicians ◽  
Maintenance Work ◽  
Maintenance Decision ◽  
Medium Enterprises

Maintenance management for manufacturing is a crucial activity for improving productivity within a facility. Within this process, maintenance work orders (MWOs) are used when tracking and solving any maintenance–related issue. The MWOs often capture the problem, the solution, at what machine the problem occurred, who solved the problem, when the problem occurred, and other information. These MWOs are manually written by maintenance technicians, entered into a database, or recorded directly into maintenance management software. Technicians often describe or record information informally — or do not record it at all — leading to inconsistencies and/or inaccuracies in the data. This paper outlines maintenance key performance indicators (KPIs), developed using MWOs, that show why consistent and accurate data collection is important for maintenance decision making. The maintenance data, or “elements,” and their corresponding KPIs are derived from MWOs from real manufacturers (large manufacturers and small and medium enterprises). While all elements or KPIs are not recorded by every manufacturer, the guideline provided here outlines the elements necessary to calculate specific KPIs. These examples are developed to aid in common maintenance decisions.

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