Displaying publications 81 - 88 of 88 in total

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  1. Mohd Hassan NZA, Bahari MS, Aminuddin F, Mohd Nor Sham Kunusagaran MSJ, Zaimi NA, Mohd Hanafiah AN, et al.
    Front Public Health, 2022;10:959812.
    PMID: 36684911 DOI: 10.3389/fpubh.2022.959812
    INTRODUCTION: Ambulance services are pivotal in any country's healthcare system. An efficient ambulance service not only decreases patient mortality rate but also allows resource prioritization for better outputs. This study aims to measure the efficiency of ambulance services provided by health facilities in the Ministry of Health (MOH), Malaysia.

    METHODS: This cross-sectional study analyzed the efficiency of 76 Decision-Making Units (DMUs) or health facilities, consisting of 62 health clinics and 14 hospitals. Data Envelopment Analysis (DEA) was used for computing efficiency scores while adopting the Variable Return to Scale (VRS) approach. The analysis was based on input orientation. The input was the cost of ambulance services, while the output for this analysis was the distance coverage (in km), the number of patients transferred, and hours of usage (in hours). Subsequent analysis was conducted to test the Overall Technical Efficiency (OTE), the Pure Technical Efficiency (PTE), the Scale Efficiency (SE), and the Return to Scale with the type of health facilities and geographical areas using a Mann-Whitney U-test and a chi-square test.

    RESULTS: The mean scores of OTE, PTE, and SE were 0.508 (±0.207), 0.721 (±0.185), and 0.700 (±0.200), respectively. Approximately, 14.47% of the total health facilities were PTE. The results showed a significant difference in OTE and SE between ambulance services in hospitals and health clinics (p < 0.05), but no significant difference in PTE between hospitals and clinics (p>0.05). There was no significant difference in efficiency scores between urban and rural health facilities in terms of ambulance services except for OTE (p < 0.05).

    DISCUSSION: The ambulance services provided in healthcare facilities in the MOH Malaysia operate at 72.1% PTE. The difference in OTE between hospitals and health clinics' ambulance services was mainly due to the operating size rather than PTE. This study will be beneficial in providing a guide to the policymakers in improving ambulance services through the readjustment of health resources and improvement in the outputs.

    Matched MeSH terms: Efficiency, Organizational*
  2. Hamzah NM, See KF
    Health Care Manag Sci, 2019 Sep;22(3):462-474.
    PMID: 30868325 DOI: 10.1007/s10729-019-09470-8
    Various pharmacy services are offered in public health facilities, ranging from distributive activities (dispensing) to patient-oriented services (pharmaceutical care). These activities are monitored through indicators established at the national level. In Malaysia, the indicators have not been transformed into a measurement of hospital pharmacy service efficiency. The main objectives of this study were to assess the relative performance of hospital pharmacy services and to investigate the factors that may affect the performance levels. Double-bootstrap data envelopment analysis was applied to measure the technical efficiency levels of 124 public hospital pharmacies in 2014. An input-oriented variable returns to scale model was adopted in the study, while bootstrap truncated regression was conducted to identify the factors that may explain the differences in the efficiency levels. The average bias-corrected technical efficiency score varies according to the hospital size (0.84, 0.78 and 0.82 in small, medium and large hospitals, respectively). The hospital size, hospital age, urban location and information technology are important determinants of the efficiency levels. The study contributes to establishing baseline technical efficiency information for public hospital pharmacy services in Malaysia. The measurement of hospital pharmacy efficiency can guide future policy making to improve performance and ensure the optimum level of available resources.
    Matched MeSH terms: Efficiency, Organizational*
  3. Javed I, Md Dawal SZ, Nukman Y, Ahmad A
    Int J Occup Saf Ergon, 2022 Dec;28(4):2238-2249.
    PMID: 34556003 DOI: 10.1080/10803548.2021.1984673
    Work productivity is one of the most important economic measures in the manufacturing industry. However, the physical, psychosocial and individual risk factors of an industrial work environment affect workers' physical or mental health, resulting in work productivity loss, absenteeism and presenteeism. Therefore, this study aims to identify the most critical risk factors and develop statistical models for predicting work productivity loss, absenteeism and presenteeism of garment industry workers. A sample of 224 sewing machine operators was taken for data collection through observation and self-reported studies. The results indicated that the average work productivity loss, absenteeism and presenteeism was 38.21, 2.35 and 37.23%, respectively. Finally, the statistical models of work productivity loss, absenteeism and presenteeism was developed using multiple linear regression with precision of 69.9, 53.7 and 84.0%, respectively. Hence, this study will help garment industries to improve their work productivity by taking initiatives based on the developed models.
    Matched MeSH terms: Efficiency*
  4. Aliero MS, Pasha MF, Toosi AN, Ghani I
    Environ Sci Pollut Res Int, 2022 Dec;29(57):85727-85741.
    PMID: 35001275 DOI: 10.1007/s11356-021-17862-z
    The enforcement of the Movement Control Order to curtail the spread of COVID-19 has affected home energy consumption, especially HVAC systems. Occupancy detection and estimation have been recognized as key contributors to improving building energy efficiency. Several solutions have been proposed for the past decade to improve the precision performance of occupancy detection and estimation in the building. Environmental sensing is one of the practical solutions to detect and estimate occupants in the building during uncertain behavior. However, the literature reveals that the performance of environmental sensing is relatively poor due to the poor quality of the training dataset used in the model. This study proposed a smart sensing framework that combined camera-based and environmental sensing approaches using supervised learning to gather standard and robust datasets related to indoor occupancy that can be used for cross-validation of different machine learning algorithms in formal research. The proposed solution is tested in the living room with a prototype system integrated with various sensors using a random forest regressor, although other techniques could be easily integrated within the proposed framework. The primary implication of this study is to predict the room occupation through the use of sensors providing inputs into a model to lower energy consumption. The results indicate that the proposed solution can obtain data, process, and predict occupant presence and number with 99.3% accuracy. Additionally, to demonstrate the impact of occupant number in energy saving, one room with two zones is modeled each zone with air condition with different thermostat controller. The first zone uses IoFClime and the second zone uses modified IoFClime using a design-builder. The simulation is conducted using EnergyPlus software with the random simulation of 10 occupants and local climate data under three scenarios. The Fanger model's thermal comfort analysis shows that up to 50% and 25% energy can be saved under the first and third scenarios.
    Matched MeSH terms: Efficiency
  5. Jawahar N, Ponnambalam SG, Sivakumar K, Thangadurai V
    ScientificWorldJournal, 2014;2014:458959.
    PMID: 24790568 DOI: 10.1155/2014/458959
    Products such as cars, trucks, and heavy machinery are assembled by two-sided assembly line. Assembly line balancing has significant impacts on the performance and productivity of flow line manufacturing systems and is an active research area for several decades. This paper addresses the line balancing problem of a two-sided assembly line in which the tasks are to be assigned at L side or R side or any one side (addressed as E). Two objectives, minimum number of workstations and minimum unbalance time among workstations, have been considered for balancing the assembly line. There are two approaches to solve multiobjective optimization problem: first approach combines all the objectives into a single composite function or moves all but one objective to the constraint set; second approach determines the Pareto optimal solution set. This paper proposes two heuristics to evolve optimal Pareto front for the TALBP under consideration: Enumerative Heuristic Algorithm (EHA) to handle problems of small and medium size and Simulated Annealing Algorithm (SAA) for large-sized problems. The proposed approaches are illustrated with example problems and their performances are compared with a set of test problems.
    Matched MeSH terms: Efficiency*
  6. Hossain MK, Kamil AA, Baten MA, Mustafa A
    PLoS One, 2012;7(10):e46081.
    PMID: 23077500 DOI: 10.1371/journal.pone.0046081
    The objective of this paper is to apply the Translog Stochastic Frontier production model (SFA) and Data Envelopment Analysis (DEA) to estimate efficiencies over time and the Total Factor Productivity (TFP) growth rate for Bangladeshi rice crops (Aus, Aman and Boro) throughout the most recent data available comprising the period 1989-2008. Results indicate that technical efficiency was observed as higher for Boro among the three types of rice, but the overall technical efficiency of rice production was found around 50%. Although positive changes exist in TFP for the sample analyzed, the average growth rate of TFP for rice production was estimated at almost the same levels for both Translog SFA with half normal distribution and DEA. Estimated TFP from SFA is forecasted with ARIMA (2, 0, 0) model. ARIMA (1, 0, 0) model is used to forecast TFP of Aman from DEA estimation.
    Matched MeSH terms: Efficiency*
  7. Shair F, Shaorong S, Kamran HW, Hussain MS, Nawaz MA, Nguyen VC
    Environ Sci Pollut Res Int, 2021 Apr;28(16):20822-20838.
    PMID: 33405126 DOI: 10.1007/s11356-020-11938-y
    This paper investigates the efficiency and total factor productivity (TFP) growth of the Pakistani banking industry and determines the impact of risk and competition on the efficiency and TFP growth. The data envelopment analysis (DEA)-based Malmquist productivity index is used to measure efficiency and TFP growth of the Pakistani banking industry. The generalized method of moments (GMM) model is applied to observe the impact of risk and competition on efficiency and TFP growth. The motivation behind the use of GMM model is its ability to overcome unobserved heterogeneity, autocorrelation, and endogeneity issues. The results of the study show that the credit and liquidity risks have positive while insolvency risk has negative effect on the efficiency and TFP growth. The competition leads to improve technological efficiency but declines the technical efficiency growth. Among other explanatory variables, operational cost management, banking sector development, GDP growth rate, and infrastructure development show significant relationships with various efficiencies and TFP growth. The banks also facilitate for the purchase of carbon-intensive products in order to reduce carbon emissions. Strong banking development successfully allocate their financial resources for the development of energy-efficient technology while banking sector development is found to be negatively related with environmental sustainability. The strong banking sector possesses a significant negative influence on carbon reduction and environmental degradation.
    Matched MeSH terms: Efficiency*
  8. Zhong C, Hamzah HZ, Yin J, Wu D, Cao J, Mao X, et al.
    Environ Sci Pollut Res Int, 2023 Mar;30(15):44490-44504.
    PMID: 36692722 DOI: 10.1007/s11356-023-25410-0
    As an important indicator of sustainable development, industrial eco-efficiency (IEE) has aroused growing attention from governments all over the world including China, in recent decades. The Chinese government has introduced numerous environmental regulations; however, the environmental pollution issue does not appear to have been solved. Moreover, although several earlier studies have shown that environmental regulations may promote innovation, there is no consensus on their ultimate effects on IEE. Therefore, this study took a critical look at the connection between environmental regulations and IEE in 36 Chinese sub-sectors from 2009 to 2018. Based on the weak Porter hypothesis (weak PH) and strong Porter hypothesis (strong PH), this paper constructed two panel regression models and conducted group analysis by pollution intensity to check the relationships among environmental regulations, technological innovation, and IEE. It was found that environmental regulations can improve technological innovation and IEE, but these impacts vary across different pollution groups. Specifically, environmental regulations have a U-shaped or inverted U-shaped relationship with technological innovation and IEE. Of the 36 sub-sectors, 26 prove the existence of the Weak PH while 10 verify the Strong PH, indicating that environmental regulations generally advocate technological innovation for most sub-sectors but only promote IEE in a few sub-sectors at present. Finally, differentiated policy implications for environmental regulations and technological innovation are provided for decision-makers.
    Matched MeSH terms: Efficiency*
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