• The Journal of Industrial Distribution & Business
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• v.11 no.10
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• pp.59-73
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• 2020

Purpose: The ultimate purpose of this work is to investigate gender differences in the relationships between product quality cues and perceived values at a food select shop. Specifically, this study examines the effects of internal and external cues, which are indicators of product quality, on emotional and social values based on gender differences. Research design, data and methodology: In this study, a questionnaire technique was used to collect the data necessary to test the proposed model. 183 data were collected through this technique. PLS SEM (Partial Least Squares Structured Equation Model) was used to test the research model. Results: First, there is no gender difference between intrinsic cue and emotional value. When using male and female data, there was no significant causal relationship between intrinsic cues and emotional values. Second, we found no gender difference between intrinsic cue and social value. When analyzed with female data, there was no significant causal relationship between intrinsic cue and social value. On the other hand, in the case of men, it was found that a weak causal relationship exists. Third, this study found gender difference between extrinsic cue and emotional value. In the case of men, it was found that a weak causal relationship exists, whereas in the case of women, a strong causal relationship exists between extrinsic cue and emotional value. Fourth, we found gender difference between extrinsic cue and social value. In the case of men, there was no causal relationship, whereas in the case of women, there was a strong causal relationship between extrinsic cue and social value. Finally, we found that there are moderating roles of gender in the relationship between external cues and perceived quality. Conclusions: As a result of analysis, it is necessary to focus on extrinsic clues of product in order to increase the perceived emotional and social values of women. On the other hand, in order to improve the perceived emotional and social values of men, it is necessary to pay attention to both intrinsic and extrinsic cues of product. Therefore, it is necessary to consider what clues and values are important to core customers.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.4
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• pp.133-143
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• 2020

The paper investigates the factors affecting the profitability of commercial banks in Asian developing countries, including Vietnam, Malaysia and Thailand. We use panel data of four entities; ten banks in Vietnam, eight banks in Malaysia, nine banks in Thailand and all 27 commercial banks from the period 2012 to 2016. Particularly, Return on Asset, Return on Equity and TOBINQ are defined as profitability indicators, which are impacted by three main types of independent variables, namely bank-specifics, which include CAR, NPL, Cost to income, Liquidity ratio and Bank size, industry-specific variable-concentration HHI and macroeconomic-specific variables, which consist of GDP growth and Inflation. Using panel data regressions, the paper identifies several similarities and differences among empirical results on the models of four entities, each of three countries and the overall sample. The most outstanding similarity is that all entities record the significantly negative relationship between operational risk and banking profitability. Likewise, the significantly negative influence of bank size to profitability is found on models of Vietnam and Thailand and no significant effect on the model of Malaysia. Meanwhile, the most controversial result comes up with the negative relationship between CAR and profitability indicators as well as the positive association between credit risk and banking profitability.

• Journal of Distribution Science
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• v.12 no.10
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• pp.37-45
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• 2014

Purpose - This study aims to analyze the relationship between trends in innovative EU industries and market distribution in smaller emerging markets under an open economy. Research design, data, and methodology - Although innovation was well-distributed, due to socio-economic factors following European integration, CEE had not achieved sustainable economic growth. However, this paper analyzes the differences among changes in CEE innovation for smaller emerging markets dominated since 2000. Market distribution has facilitated new markets for innovative industries, according to EU surveys and economic indicators. Results - The dominance of the local industrial market distribution has deterred innovation investment the survey shows that innovation investment has been shrinking, despite the EU's open innovation policy for CEE employment and R&D. For the CEE case, there were expectation gaps and uncertainty about whether to use the new distribution dominance or TNCs' innovation in smaller emerging countries without local industrial innovation. Conclusions - Innovation generates market growth and distribution power however, small growth requires stimulation, and creativity and innovative edge need further focus in local public and corporate strategy.

• Journal of Distribution Science
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• v.14 no.3
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• pp.63-71
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• 2016

Purpose - A variety of indicators are used for the diagnosis of economic situation. However, most indicators explain the past economic situation because of the time difference between the measurement and announcement. This study aims to argue for the resurrection of an idea: electricity demand can be used as an indicator of economic activity. In addition, this study made an endeavor to develop a new Real Business Index(RBI) which could quickly represent the real economic condition based on the sales statistics of industrial and public electricity. Research design, data, and methodology - In this study monthly sales of industrial and public electricity from 2000 to 2015 was investigated to analyze the relationship between the economic condition and the amount of electricity consumption and to develop a new Real Business Index. To formulate the Index, this study followed next three steps. First, we decided the explanatory variables, period, and collected data. Second, after calculating the monthly changes for each variable, standardization and estimating the weighted value were conducted. Third, the computation of RBI finalized the development of empirical model. The principal component analysis was used to evaluate the weighted contribution ratio among 3 sectors and 17 data. Hodrick-Prescott filter analysis was used to verify the robustness of out model. Results - The empirical results are as follows. First, compatibility of the predictability between the new RBI and the existing monthly cycle of coincident composite index was extremely high. Second, two indexes had a high correlation of 0.7156. In addition, Hodrick-Prescott filter analysis demonstrated that two indexed also had accompany relationship. Third, when the changes of two indexes were compared, they were found that the times when the highest and the lowest point happened were similar, which suggested that it is possible to use the new RBI index as a complementing indicator in a sense that the RBI can explain the economic condition almost in real time. Conclusion - A new economic index which can explain the economic condition needs to be developed well and rapidly in a sense that it is useful to determine accurately the current economic condition to establish economic policy and corporate strategy. The salse of electricity has a close relationship with economic conditions because electricity is utilized as a main resource of industrial production. Furthermore, the result of the sales of electricity can be gathered almost in real time. This study applied the econometrics model to the statistics of the sales of industrial and public electricity. In conclusion, the new RBI index was highly related with the existing monthly economic indexes. In addition, the comparison between the RBI index and other indexes demonstrated that the direction of the economic change and the times when the highest and lowest points had happened were almost the same. Therefore, this RBI index can become the supplementary indicator of the official indicators published by Korean Bank or the statistics Korea.

• Korean Journal of Clinical Laboratory Science
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• v.48 no.4
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• pp.312-320
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• 2016

This study analyzed the distribution of the blood glucose level according to the fasting status. Moreover, a relationship was analyzed between fasting blood glucose level and glycemic control indicators. A total of 707 outpatients, who visited Dankook University Hospital, were included and classified into either the fasting group and the non-fasting group. The mean blood glucose level of each group was calculated and analyzed by sex, age, and clinic. In addition, blood glucose, HbA1c, fructosamine, and 1,5-AG were measured in 153 fasting health check-up patients, and the correlation between the blood glucose level and glycemic control indicators was evaluated. Blood glucose averages between the two groups (non-fasting 111.9 vs. fasting 103.6 mg/dL) were different (p<0.05); and the mean difference was lower in women (4.8 mg/dL) than in men (12.2 mg/dL). A significant difference of the median glucose values among the age groups was only observed in the non-fasting group (Kruskal-Wallis test, p<0.01), and not in the fasting group. A 1,5-Anhydroglucitol was estimated to be significantly correlated with the fast blood glucose level in the range of the criteria of impaired fasting glucose (IFG). We presented an assessment of the distribution of blood glucose level in accordance with the fasting status among outpatients, and estimated that 1,5-anhydroglucitol was well correlated with the fasting blood glucose than fructosamine and HbA1c, through the analysis of results of health screening subjects. It is suggested that the use of glycemic indicators that reflect short-term blood glucose control can be used together with the blood glucose measurement in the screening of diabetes mellitus.

• Korean Management Science Review
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• v.30 no.2
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• pp.1-10
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• 2013

Case studies are made to investigate the relationship between the accuracy of energy production estimation and project feasibility indicators such as rate of return on equity (ROE) and debt service coverage ratio (DSCR) for three wind farm projects. It is found out that 1% improvement in the accuracy of energy production estimation may enhance the ROE by more than 0.5% in the case of P95, thanks to improved financing terms. AHP survey shows that MCP correlation of measured in situ wind data with long term wind speed distribution and hands-on experiences of flow analysis are more important than other factors for more precise annual energy production estimation.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.999-1007
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• 2020

This study aimed to investigate the influence of spiritual leadership on innovative work behavior and the effect of knowledge sharing on job crafting. Furthermore, the roles of knowledge sharing as a mediator for the impact of spiritual leadership on innovative work behavior, and job crafting as a mediator for the relationship between variables, were also examined. This research employed quantitative analysis, including the PLS-SEM approach; SMART-PLS, a measurement and structural equation model was employed to explain the relationship between variables, and the effect of mediation. The population study consisted of all lecturers at the Faculty of Economics and Faculty of Economics and Business at the PTKIN in East Java, Indonesia, comprising 220 randomly-selected samples. The result showed spiritual leadership does not directly influence innovative work behavior, while knowledge sharing directly affects job crafting. The findings indicated knowledge sharing mediates the impact of spiritual leadership on innovative work behavior, and the role of job crafting as a mediator for the relationship between variables was accepted. Therefore, this research confirms a positive influence of knowledge sharing on job crafting, and indicates both factors play an important role in mediating between variables, and are important for lecturers' innovative work behavior.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.237-249
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• 2021

Indonesia has successfully increased its ranking to 40th place in the 2019 Travel & Tourism Competitiveness Index. While tourism has become the country's second largest foreign exchange contributor, there is no existing competitive advantage model for Indonesian tourist destinations. The purpose and novelty of this study is to develop and formulate a competitive advantage model for Indonesia's tourism industry. The model will be based on the supply-side perception analysis of competitiveness indicators from Bali and five designated super-priority destinations in Indonesia. This model is expected to become a guideline for policymakers to design an effective and focused strategy. Data were obtained from in-depth interviews with, and questionnaires given to, 62 qualified industry players from the public and private sectors. This data-driven approach builds a relationship between competitiveness indicators and competitive advantages using a combination of importance-performance analysis and confirmatory factor analysis, thereby leveraging these advantages to generate a strategic model to compete in the international tourism industry. This would also be the first study to use this method in defining the competitive advantage of a destination. Using structural equation modeling, the study found that there are 54 indicators representing twelve dimensions of competitive advantages with good fit criteria.

• Journal of Preventive Medicine and Public Health
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• v.39 no.1
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• pp.30-38
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• 2006

Objectives: We examined whether the neighborhood socioeconomic position predicts the smoking rates after adjusting for individual socioeconomic position indicators. Methods: Data were obtained from the 2001 Seoul Health Indicators Survey. The neighborhood socioeconomic position was the residential distribution of the high class (power elites), as measured by the location quotients (LQ) for each administrative dong (district). A high LQ denotes a high neighborhood socioeconomic status. The individual socioeconomic position included education, occupation and income. Age-adjusted smoking rates according to the LQ level were computed with the direct method. The total number of subjects in this study (26,022 men and 28,007 women) was the reference. A multilevel logistic regression analysis was conducted with the individuals at the first level and the neighborhoods at the second level to estimate the odds ratios of smoking with 95% confidence intervals. Results: For men, the age-adjusted smoking rates increased with a decrease in the LQ. For women, the relationship between the age-adjusted smoking rate and the LQ was not clear. The odds of smoking for both genders were greater among those subjects with lower incomes and lower education. The manual occupational class had greater odds of smoking than the non-manual class for the males, while the odds ratio of smoking among females with a manual occupation tended to be lower than those females with a non-manual occupation. For the males, the LQ levels independently predicted smoking after adjustment for individual income. However, this relation between the LQ and smoking in males was explained by full adjustment for the individual socioeconomic position indicators (education, occupation and income). Conclusions: A low level of neighborhood socioeconomic position was associated with higher smoking rates among the men residing in Seoul. This association between the neighborhood socioeconomic position and smoking in men was explained by the individual socioeconomic position. Anti-smoking efforts to reduce geographical inequality in smoking should be directed at reducing the smoking rates between the individuals with different socioeconomic backgrounds in the metropolitan city of Seoul, South Korea.

• Journal of Digital Convergence
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• v.16 no.5
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• pp.75-84
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• 2018

The purpose of this study was to analyze the regional distribution of the number of social welfare facilities per 100,000 population by using the concentration index(CI) and to evaluate the relationship with the local welfare environment. The results of the analysis are as follows. First, the distribution of social welfare facilities between urban and rural area were distributed in rural areas. And concentration of rural area was gradually decreasing. Second, the concentration index of the social welfare institution was calculated as the negative index. Therefore, social welfare facilities are concentrated in rural areas. However, the absolute value of concentration index decreased. Finally, there are many social welfare facilities in areas with poor economic conditions, low incomes, low welfare budget input, and poor social demolition indicators. In the future, the relationship between inequality of regional distribution of welfare resources and the relationship between local welfare environment should be continuously monitored.