• Asian Journal for Public Opinion Research
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• v.11 no.1
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• pp.31-53
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• 2023

This study aims to investigate the relationship between human resource competency, economic potential, and productivity of village-based enterprises, as well as understand the role of governance in mediating this relationship. This study was conducted in several village-based enterprises in Bali, Indonesia and the data were collected using questionnaires. Furthermore, the collected data were analyzed quantitatively using partial least analysis to confirm the relationship between variables. The findings indicate that human resource competency has an impact on governance, but it failed to explain the productivity of village-based enterprises. In addition, economic potential can have an impact on the governance and productivity of village-based enterprises in Bali, Indonesia. This study also showed a robust link between governance and productivity. Lastly, based on the statistical analysis, it was found that governance can mediate the relationship between human resource competency, economic potential, and productivity of village-based enterprises.

• Resources Recycling
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• v.29 no.3
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• pp.24-35
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• 2020

Management of resource productivity is important for the reduction of natural resources and energy consumption. This is closely linked to circular economy which has recently been stressed worldwidely. Resource productivity is a key indicator which is to be managed in various industry sectors. Especially Korea which is heavily dependent on the natural resources import from overseas needs to give attention to this point. Nevertheless resource productivity related domestic researches and policies are extremely rare. This paper thus presents trends on resources productivities and their management policies of European countries and OECD G7 countries compared to the situation of Korea. In addition, the decoupling phenomenon of DMC (domestic material consumption) and GDP of Europe is analyzed and the resource productivity promotion strategy of Korea is proposed.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.4
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• pp.381-389
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• 2021

This study aims to examine the effect of strategic planning, human resource management, and asset management on increasing the productivity of the rural economy. This research is a quantitative approach. The research sample was carried out by simple random sampling and data collection using a questionnaire so that 129 respondents were determined. The research test was conducted using multiple linear regression with the OLS (Ordinary Least Square model. The results obtained were that strategic planning, human resource management, and asset management had a significant positive effect on increasing the productivity of the rural economy. This shows that strategic planning is the most important thing in industry, companies, or organizations as a guideline to achieve optimal performance. In addition, human resource management and asset management are positive supports for increasing the economic productivity of rural communities to achieve welfare goals. This research proves that strategic planning must be carried out by considering the existing potential, both sources. natural resources, human resources, and economic resources Meanwhile, human resource management and asset management are mandatory to support the sustainability of an organization or company so that the benefits of the study as study material in strategic decision making, both in business and public policy.

• The Korean Journal of Health Service Management
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• v.10 no.2
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• pp.71-82
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• 2016

Objectives : This study purposed to analyze the productivity trends of regional health care resource uses in South Korea. Methods : Data was provided from the regional health care statistics by the National Health Insurance Service(NHIS) and collected from 2011 to 2014 at the 226 administrative regions such as Si(city in Korean), Gun(county in Korean), Gu(district in Korean). Productivity trend was analyzed with Malmquist Productivity Index(MPI). Input variables were the number of medical personnels, facilities, and major medical equipments. Output variables were the number of inpatient and outpatients in model A, and the amount of inpatient and outpatient reimbursements in model B. Results : In model A, the productivity of 62 regions were increased but it was decreased in 164 regions. In model B, the productivity of 123 regions were increased but it was decreased in 123 regions. Conclusions : If these trends were continued, there will be problems with the efficiency of national regional healthcare resource utilization. Health policy makers will require to focus in solving this phenomenon.

• Clean Technology
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• v.30 no.3
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• pp.276-286
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• 2024

Since the Paris Agreement and the surge in global interest in climate change, the importance of measuring and managing national-level resource productivity has steadily grown. However, concerns about the reliability of productivity indicators persist due to inherent uncertainties. This study estimated the metal and non-metal resource productivities of 38 OECD countries through multiple regression analysis and conducted a comparative analysis of their ranking changes according to their current resource productivities. The study results revealed that the 38 OECD countries could be classified into four categories. First, countries with low overall resource productivities due to a high economic dependence on low-value metal resources by weight exhibited a substantial rise in their non-metal resource productivity rankings. Second, countries that have minimal metal industries in their national economies but generate high value-added from these sectors showed a notable increase in their metal resource productivity rankings. Third, countries with a low proportion of metal industry in their economies and low metal resource productivities experienced significant declines in their metal resource productivity rankings. Fourth, countries with a small disparity between their metal and non-metal resource productivities showed minimal changes in their rankings for both categories. These results highlight that changes in metal resource productivity rankings were more pronounced than those for non-metal resources, which implies that the influence of non-metal resources (biomass, fossil fuels, non-metallic minerals) dominates national-level resource productivity because their economic value is higher than metal resources. These findings suggest that it is necessary to manage the economic value of each resource type as distinct statistical data to provide a more nuanced understanding of national resource productivity.

• Resources Recycling
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• v.20 no.6
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• pp.43-49
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• 2011

This study calculated the three indices of Korea's resource productivity (and raw material productivity), material circulation rate and decoupling factor to evaluate the sustainability of domestic economic activities and resource consumption and examine the extent of dematerialization. Korea's resource productivity improved 22% from 1.32 million KRW/ton in 2000 to 1.61 million KRW/ton in 2007, with the annual average growth of resource productivity during the period standing at 2.88%. Raw material inputs accounted for 73-76% of domestic material consumption (DMC); raw material productivity for the year 2007 was 2.11 million KRW/ton, growing 3% on annual average from 2000 through 2007. The wastes released are circulated into the economic system through recycling and energization. Korea's material circulation went up from 10.9% in 2000 to 15.6% in 2007, growing by an annual average of 5.3% during the period. The rate of change in year-on-year growth, however, was found to be on the gradual decrease. This study also showed that Korea's economic activities were decoupled with its resource consumption as the country heads toward dematerialization through sustainable resource management.

• Asian Journal of Innovation and Policy
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• v.3 no.2
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• pp.193-215
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• 2014

This study analyzes the factors on the determinants of research productivity. In addition, this study uncovers the relationships between research productivity and various explanatory variables, and between explanatory variables. As for research productivity, 3 indices were used such as the number of papers, patents, and a combination of them. The data is the 3-year average from 2010-2012 by 1,383 researchers from 6 disciplines such as physics, chemistry, biology, mechanical engineering, electricity and electronics, and chemical engineering, reported to the National Research Foundation of Korea. Personal factors such as sex, age, academic rank and location of affiliation show the group difference for productivity. In addition, most resource factors such as the number of graduate students and research funds showed the same result with personal factors. As for the determinants, master and doctoral students and government funds are the most powerful factors for research productivity, but industry funds for patent and overall productivity.

• Korean Journal of Construction Engineering and Management
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• v.24 no.2
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• pp.37-49
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• 2023

In this study, we proposed resource allocation methodologies to improve the productivity of steel bridge manufacturing plants based on the constraint theory which is very popular in the area of manufacturing industries. To this end, after defining the painting process as a bottleneck, three resource allocation methodologies were developed: Operation Specific Resource Allocation (OSRA), Product Specific Resource Allocation (PSRA), and General Resource Allocation (GRA). As a result of experiments for performance evaluation using a simulation model of the steel bridge supply chain, GRA showed the best performance in terms of the Number of Work-In-Process (NWIP) and Waiting Time (WT), in particular, as workload itself and its variability were increased, the performance gap with the specific resource allocation became further deepened. On average, GRA reduced NWIP by 36.2% and WT by 34.6% compared to OSRA, and reduced NWIP by 71.0% and WT by 70.4% compared to PSRA. The reduction of NWIP and WT means alleviating the bottleneck of the painting process, which eventually means that the productivity of the steel bridge manufacturing plant has improved.

• Journal of Nutrition and Health
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• v.27 no.8
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• pp.864-871
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• 1994

The productivity and 13 influencing variables in 14 conventional hospital foodservice systems the total direct and non-direct labor hours required to produce and serve the total number of patient meals plus the number of cafeteria meals. Human resource variable significantly influencing the productivity level was the labor cost. As this index decreased, the meals served per human hour worked increased. System resource variables correlating significantly with productivity were the length of cycle menu, the ratio of staff meals, and modified patient meal ratio. As the length of cycle menu and the ratio of modified patient meal decreased, more meals were produced per human hour. However, as staff meal ratio increased, the meals served per human hour worked increased. The stepwise regression analysis suggests that around 53% of the variance in productivity is explained by labor cost.

• Clean Technology
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• v.28 no.3
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• pp.258-266
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• 2022

Resource productivity (GDP/DMC) is defined as GDP divided by DMC. However, it has shortcomings when estimating the value-added generated from material processing. In this paper, an energy coefficient is applied to GDP to develop a sub-indicator (referred to as GDPe/DMC). Consequently, South Korea, which is a secondary industry-oriented country, created 1,094.60 USD/ton from input materials and was ranked 4th on the OECD list, which is 10 levels higher than the level estimated by GDP/DMC. However, Luxembourg, which is a tertiary industry-oriented country, is ranked 16th on the OECD list, which is 12 levels lower than the level estimated by GDP/DMC. The resource productivity estimated by the sub-indicator (GDPe/DMC) developed in this study indicates that secondary industry-oriented countries are undervalued in the existing main GDP/DMC calculation. On the other hand, tertiary industry-oriented countries are downgraded due to the industrial features of the GDPe/DMC calculation. As a result of this paper, GDPe/DMC could be considered a more reasonable indicator to directly reflect the material input effect compared to the existing main indicator, GDP/DMC. This means that GDPe/DMC-induced resource productivities could be estimated to be slightly higher than the GDP/DMC-induced resource productivities for secondary industry-oriented countries. It is expected that the sub-indicator, GDPe/DMC, proposed in this study could be useful especially for comparing and analyzing the resource productivities between countries that have different industry structures. This study intended to consider a structurally energy/resource-intensive industry in estimating and analyzing national-level resource productivity. Thus, the sub-indicator, GDPe/DMC, may help minimize the distortion of interpreting national resource productivities in various situations, and be utilized as a more efficient tool when used together with GDP/DMC.