• Asia Marketing Journal
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• v.18 no.4
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• pp.125-138
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• 2017

The goal of the study is to understand how consumers' constraint as opposed to utility structure gives rise to final decision when consumers purchase more than one variant of product at a time, i.e., horizontal variety seeking or multiple-discreteness. Purchase and consumption decision not only produces utility but also involves some sort of cognitive pressure. Past consumption or last purchase is likely to be linked to this burden we face such as concern for obesity, risk of harm, and guilt for mischief. In this research, the existence and the role of dynamic constraint are investigated through a microeconomic utility model with multiple dynamic constraint. The model is applied to the salty snacks data collected from field study where burden for spiciness serves as a constraint. The results are compared to the conventional multiple discreteness choice models of static constraints, and policy implications on price discounts is explored. The major findings are that first, one would underestimate the level of consumer preference for product offerings when ignoring the carry-over of the concern from the past consumption, and second, the impact of price promotion on demand would be properly evaluated when the model allows for the role of constraint as both multiple and dynamic. The current study is different from the existing studies in two ways. First, it captures the effect of 'mental constraint' on demand in formal economic model. Second, unlike the state dependence well documented in the literature, the study proposes the notion of state dependence in different way, via constraint rather than utility.

• Korean Security Journal
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• no.19
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• pp.1-21
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• 2009

Manpower demand forecasting in private security industry can be used for both policy and information function. At a time when police agencies have fewer resources to accomplish their goals, forming partnership with private security firms should be a viable means to choose. But without precise understanding of each other, their partnership could be superficial. At the same time, an important debate is coming out whether security industry will continue to expand in numbers of employees, or level-off in the near future. Such debates are especially important for young people considering careers in private security industry. Recently, ARIMA model has been widely used as a reliable instrument in the many field of industry for demand forecasting. An ARIMA model predicts a value in a response time series as a linear combination of its own past values, past errors, and current and past values of other time series. This study conducts a short-term forecast of manpower demand in private security industry using ARIMA model. After obtaining yearly data of private security officers from 1976 to 2008, this paper are forecasting future trends and proposing some policy orientations. The result shows that ARIMA(0, 2, 1) model is the most appropriate one and forecasts a minimum of 137,387 to maximum 190,124 private security officers will be needed in 2013. The conclusions discuss some implications and predictable changes in policing and coping strategies public police and private security can take.

• Safety and Health at Work
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• v.14 no.1
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• pp.85-92
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• 2023

Background: Presenteeism is closely related to work performance, work quality and quantity, and productivity at work. According to the job demand-control-support model, job demand, job control, and support play important roles in presenteeism. The present study investigated job characteristics profiles based on the job demand-control-support model and identify the association between job characteristics profiles and presenteeism. Methods: This secondary data analysis used the Sixth Korean Working Condition Survey, a nationwide cross-sectional dataset. The study included 25,361 Korean wage workers employed in the workplace with two or more workers. Participants were classified into four job characteristics profiles based on the job demand-control-support model, using latent profile analysis, and logistic regression was performed to examine the association between study variables. Results: Overall, 11.0 % of study participants reported experience of presenteeism in the past 12 months. Age, sex, location, monthly income, shift work, work hours, health problems, and sleep disturbances were significantly associated with presenteeism. The rate of presenteeism was the highest in the passive isolate group. The passive collective, active collective, and low-stain collective groups had a 23.0%, 21.0%, and 29.0% lower likelihood of experiencing presenteeism, respectively, than the passive isolate group. Conclusions: The job demand-control-support profiles and the risk of presenteeism were significantly associated. The most significant group that lowered the experience of presenteeism was the low-strain collective group, which had a low level of demand and high levels of control and support. Therefore, we need a policy to reduce job demand and increase job control and support at the organizational and national levels.

• Journal of the Korean housing association
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• v.16 no.6
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• pp.139-147
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• 2005

The purpose of this study was to determine the factors which affect older people's innovativeness toward technologies and factors which affect their demand of home automation system. The study collected data from 289 persons who are 50 years and older with experience living in an apartment currently or past. Innovativeness toward technologies of respondents were low level and the significant factors which affected their innovativeness were age, education, employment, marital status, current housing types, health status of self and spouse, consideration of home automation system for a newly-moved house. Education, employment types, consideration of home automation system for a newly-moved house, and plan for moving were the major factors which affect demand of home automation system. Also, older people's innovativeness toward technologies was the most important factor which affected demand of home automation system. Th results of this study explained that high technologies which are adopted in residential environment should be considered target consumers' abilities and attitudes for acceptance toward new ideas. Especially, for older consumers, various ideas to expand their understanding of new technologies should be developed and the positive effect of technologies to increase the quality of their later life should be educated.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.2
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• pp.147-159
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• 2011

In this paper the demand and supply of labor are forecasted over the next 10 years for customized nurturing human resource focused on Manufacturing Industry in Chung-Nam Province. Despite that the industrial structure is rapidly changing, industrial labors are nurturing on the basis of past industrial structure. This research is conducted for reducing mismatched labors throughout forecasting human resources until 2020. As a practical approach, the BLS Methodology is partially utilized. And the previous researches and official statistics data are reviewed. In conclusion, this study presents that more human resources on Manufacturing Industry than other Industries will be needed in Chung-Nam province. In details, it shows that there will be required more Industrial labors for strategic industries for examples, Audio and Video related industry, and Car related industry which is propelling by overall local government. In additions, policy implications are developed by analyzing current status and forecasting the labor demand and supply in the Chung-Nam Manufacturing sector.

• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2005.11a
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• pp.67-72
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• 2005

The purpose of this study was to determine the factors which affect older people's innovativeness toward technologies and factors which affect their demand of home automation system. The study collected data from 289 persons who are 50 years and older with experience living in an apartment currently or past. Innovativeness toward technologies of respondents were low level and the significant factors which affect their innovativeness were age, education, employment, marital status, current housing types, health status of self and spouse, consideration of home automation system for a newly-moved house. Education, employment types, consideration of home automation system for a newly-moved house, and plan for moving were the major factors which affect demand of home automation system. Also, older people's innovativeness toward technologies was the most important factors which affect demand of home automation system. Th results of this study explained that high technologies which are adopted in residential environment should be considered target consumers' abilities and attitudes for acceptance toward new ideas. Especially, for older consumers, various ideas to expand their understanding of new technologies should be developed and the positive effect of technologies to increase the qualify of their later life should be educated.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.1
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• pp.385-393
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• 2021

This study investigates the effect of infrastructure, economic sectors and its status, foreign direct investment and private investment, as well as the role of political stability in enhancing the tourism demand in the ASEAN region. The research collected the secondary data from the World Bank database and the UNWTO website of 10 ASEAN countries over 17 years from 2000 to 2016. Applying the generalized method of moments, this research found that, "private investment", "economic sectors", "exchange rate and infrastructure measured by "using of the internet" can increase the tourism demand of a country in the ASEAN region. This research provided evidence indicating that the "foreign direct investment" and "inflation" are two detrimental factors for tourist attraction. The major finding confirmed the positive role of "political stability" in increasing tourist arrivals. First, attracting tourists to a country always poses many challenges to its government. It has been observed in the past decades that though there were many documents, which confirmed that industry can help in promoting tourism, very few studies investigated the role of both agriculture and manufacturing sectors in tourism promotion. Secondly, there are only a few studies which verifies the stability of the political system to the tourism demand in the ASEAN region and that this variable (political stability) has the strongest impact.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.139-145
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• 1996

A forecast on the past output data sets of small bar steels is very important information to make a decision on the future production quantities. In many cases, however, it has been mainly determined by experience (or rule of thumb). In this paper, past basic data sets of each small bar steels are statistically analyzed by some graphical and statistical forecasting methods. This work is mainly done by SAS. Among various quantitative forecasting methods in SAS, STEPAR forecasting method was best performed to the above data sets. By the method, the future production quantities of each small bar steels are forecasted. As a result of this statistical analysis, 95% confidence intervals for future forecast quantities are very wide. To improve this problem, a suitable systematic database system, integrated management system of demand-production-inventory and integrated computer system should be required.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.98-103
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• 2021

Recently, as the need for food resources has increased both domestically and internationally, support for the agricultural sector for stable food supply and demand is expanding in Korea. However, according to recent media articles, the biggest problem in rural communities is the unstable profit structure. In addition, in order to confirm the profit structure, profit forecast data must be clearly prepared, but there is a lack of auxiliary data for farmers or future returnees to predict farm income. Therefore, in this paper we analyzed data over the past 15 years through time series analysis and proposes an artificial intelligence farm income prediction algorithm that can predict farm household income in the future. If the proposed algorithm is used, it is expected that it can be used as auxiliary data to predict farm profits.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.39-48
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• 2020

Recently, the study and development of environment-friendly energy technique have increased in worldwide due to environmental pollution and energy resources problems. In vehicle industry, the development of electric vehicle(EV) is now on progress, and also, many other governments support the study and development and make an effort for EV to become widely available. In addition, though they strive to construct the EV infra such as a charge station for EV, the techniques related to managing charge demand and peak power are not enough. The standard of EV communication has been already established as ISO/IEC 15118, however, most of implemented EVs and EV charge stations do not support any communication between each of them. In this paper, an improved slow charge scheme for non-communication EVs is proposed and designed by using predicting charge demand. The proposed scheme consists of distributed charge model and charge demand prediction. The distributed charge model is designed to manage to distribute charge power depending on available charge power and charge demand. The charge demand prediction is designed to be used in the distributed charge model. The proposed scheme is based on the collected data which were from EV slow charge station in business building during the past 1 year. The system-level simulation results show that the waiting time of EV and the charge fee of the proposed scheme are better than those of the conventional scheme.