• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.18 no.5
• /
• pp.33-44
• /
• 2023

Entrepreneurial self-efficacy is an important variable that explains people's attitudes and behaviors toward start-ups. In this study, we focused on individual psychological characteristics variables such as luck in belief and positive cognitive bias that affect entrepreneurial self-efficacy. Among these variables, we paid particular attention to luck in belief. The belief that business success depends on luck is widespread, but scientific verification about it has not been much. The reason for the academic indifference is that luck is a kind of superstition, related to precognition or extrasensory perception, and randomly caused by the external environment. The study of luck began in earnest as a measure to measure luck as an individual characteristic variable such as personality was developed. The purpose of this study is to examine the existing studies on luck in belief and to examine the effect of this luck in belief on positive cognitive bias and entrepreneurial self-efficacy through empirical analysis. For empirical analysis, this study conducted an on-line survey of 400 ordinary people and conducted a structural equation model analysis using AMOS 21.0 to verify the hypothesis. As a result of hypothesis testing, all hypotheses that luck in belief would have a positive effect on positive cognitive bias(self-enhancement bias, illusion of control bias, unrealism optimistic bias) were adopted. The hypothesis that positive cognitive bias(self-enhancement bias, illusion of control bias, unrealistic optimism bias) will have a positive effect on entrepreneurial self-efficacy was also adopted. Additional analysis was conducted to examine the mediating role of positive cognitive bias in the relationship between luck in belief and entrepreneurial self-efficacy, which showed that 'luck in belief→positive cognitive bias →entrepreneurial self-efficacy' were statistically significant. Through this, we confirmed the mediating effect of positive cognitive bias in the relationship between luck in belief and entrepreneurial self-efficacy. In the conclusion, the implications and limitations of the study were presented based on the results of this study.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
• /
• v.17 no.5
• /
• pp.67-80
• /
• 2022

This study was conducted to derive policy measures such as fostering and supporting by examining the actual conditions of domestic startups. The subject of this study was the start-ups located in Seongnam-si, where Pangyo Techno Valley, which is the highest-level innovation cluster in Korea and is evaluated as a start-up mecca. Startups were defined as startups under 7 years old based on new technologies such as IT, BT, and CT, and the subjects of the study were selected. This can be seen as a step forward from previous research in that it embodies the concept of a startup that was previously abstract in a quantitatively measurable way. As a result of the analysis, about 94% of startups are distributed in the so-called "Death Valley" growth stage, and startups above scale-up, which means full-scale growth beyond BEP, account for about 6%. appeared to be occupied. He cited the problem of start-up funds as the biggest difficulty in the early stages of startups, and cited the loan evaluation method that prioritizes sales or collateral in raising funds as the biggest problem. In addition, start-ups rated the access to private investment capital such as VC, AC, and angel investors at a low level compared to policy funds, which are public funds. Most startups showed a lot of interest in overseas expansion, and they chose matching overseas investors such as overseas VCs as the biggest support for overseas expansion. The overall competitiveness in the overseas market was 49.6 points, which is less than 50 points out of 100, indicating that the overall competitiveness was somewhat inferior. It was analyzed that public support and investment in overseas sales channels (sales channels, distribution networks, etc.) should be prioritized along with enhancement of technological competitiveness in order for domestic startups to increase their competitiveness in overseas markets as well as in the domestic market.

• Korean Journal of Environment and Ecology
• /
• v.38 no.2
• /
• pp.217-226
• /
• 2024

This study aimed to investigate the influence of anions in the air on the purification of fine dust (PM10 and PM2.5) and to evaluate the effects of plants on the generation of anions in the air and the purification of fine dust. Subsequently, the fine dust reduction models were compared according to each factor and plant volume. The characteristics of anion generation by each factor were observed to be in the order of Type N.I (negative ion generator; 204,133.33 ea/cm³) > Type P₃₀ (plant vol. 30%; 362.55 ea/cm³) > Type C (control; 46.22 ea/cm³), indicating that the amount of anion generation in the anion generator treatment group and the plant arrangement group were approximately 4,417 times and 7 times higher, respectively, than that in the untreated group. Consequently, the fine dust reduction characteristics by anion generation source showed that for PM10, Type NI had a purification efficiency 2.52 times higher than Type C, and Type P₃₀ was 1.46 times higher, while for PM2.5, Type NI had a purification efficiency 2.26 times higher than Type C, and Type P₃₀ was 1.31 times higher. The efficiency of fine dust purification by plant volume was in the order of Type P₂₀ (84.60 minutes) > Type P₃₀ (106.50 minutes) = Type P₂₅ (115.50 minutes) = Type P₁₅ (117.60 minutes) > Type P₅ (125.25 minutes) = Type P₁₀ (129.75 minutes), and for ultrafine dust, Type P₂₀ (104.00 minutes) > Type P₃₀ (133.20 minutes) = Type P₂₅ (144.00 minutes) = Type P₁₅ (147.60 minutes) > Type P₅ (161.25 minutes) = Type P₁₀ (168.00 minutes). Thus, a quantitative analysis of the anions and plants for purifying fine dust and suggested matters to be considered for future green space planning and plant planting considering fine dust purification.

• Journal of the Korean Society of Radiology
• /
• v.84 no.3
• /
• pp.638-652
• /
• 2023

Purpose To investigate the MRI markers for the prediction of amyloid β (Aβ)-positivity in mild cognitive impairment (MCI) and Alzheimer's disease (AD), and to evaluate the differences in MRI markers between Aβ-positive (Aβ [+]) and -negative groups using the machine learning (ML) method. Materials and Methods This study included 139 patients with MCI and AD who underwent amyloid PET-CT and brain MRI. Patients were divided into Aβ (+) (n = 84) and Aβ-negative (n = 55) groups. Visual analysis was performed with the Fazekas scale of white matter hyperintensity (WMH) and cerebral microbleeds (CMB) scores. The WMH volume and regional brain volume were quantitatively measured. The multivariable logistic regression and ML using support vector machine, and logistic regression were used to identify the best MRI predictors of Aβ-positivity. Results The Fazekas scale of WMH (p = 0.02) and CMB scores (p = 0.04) were higher in Aβ (+). The volumes of hippocampus, entorhinal cortex, and precuneus were smaller in Aβ (+) (p < 0.05). The third ventricle volume was larger in Aβ (+) (p = 0.002). The logistic regression of ML showed a good accuracy (81.1%) with mini-mental state examination (MMSE) and regional brain volumes. Conclusion The application of ML using the MMSE, third ventricle, and hippocampal volume is helpful in predicting Aβ-positivity with a good accuracy.

• Information Systems Review
• /
• v.21 no.4
• /
• pp.1-29
• /
• 2019

The knowledge resources take a role in promoting the sustainable growth of organization. Therefore, it is important for the members of organization to acquire knowledge consistently so that the company can continue to grow. Knowledge service is the field that provides information and infrastructure which enable the members of organization to acquire new knowledge. As we recognized the importance of knowledge services, we analyzed the level of knowledge service management and development through the impact of knowledge quality on user capabilities. First, the matrix of knowledge patterns was presented based on the type of information and the level of customer interaction. According to patterns, the knowledge service was classified into three types of information providing, information analysis, and infrastructure, and then the results of structural model analysis were presented for each type. It found that the impact of knowledge service quality on user competence was different according to the type of service. The results suggested new indicators for measuring the performance of knowledge services, and provided information for reconstructing services based on the user considering the integrated operation of knowledge service and organizational designing knowledge service.

• Journal of Distribution Research
• /
• v.15 no.3
• /
• pp.71-110
• /
• 2010

1. Introduction Today Internet is recognized as an important way for the transaction of products and services. According to the data surveyed by the National Statistical Office, the on-line transaction in 2007 for a year, 15.7656 trillion, shows a 17.1%(2.3060 trillion won) increase over last year, of these, the amount of B2C has been increased 12.0%(10.2258 trillion won). Like this, because the entry barrier of on-line market of Korea is low, many retailers could easily enter into the market. So the bigger its scale is, but on the other hand, the tougher its competition is. Particularly due to the Internet and innovation of IT, the existing market has been changed into the perfect competitive market(Srinivasan, Rolph & Kishore, 2002). In the early years of on-line business, they think that the main reason for success is a moderate price, they are awakened to its importance of on-line service quality with tough competition. If it's not sure whether customers can be provided with what they want, they can use the Web sites, perhaps they can trust their products that had been already bought or not, they have a doubt its viability(Parasuraman, Zeithaml & Malhotra, 2005). Customers can directly reserve and issue their air tickets irrespective of place and time at the Web sites of travel agencies or airlines, but its empirical studies about these Web sites for reserving and issuing air tickets are insufficient. Therefore this study goes on for following specific objects. First object is to measure service quality and service recovery of Web sites for reserving and issuing air tickets. Second is to look into whether above on-line service quality and on-line service recovery have an impact on overall service quality. Third is to seek for the relation with overall service quality and customer satisfaction, then this customer satisfaction and loyalty intention. 2. Theoretical Background 2.1 On-line Service Quality Barnes & Vidgen(2000; 2001a; 2001b; 2002) had invented the tool to measure Web sites' quality four times(called WebQual). The WebQual 1.0, Step one invented a measuring item for information quality based on QFD, and this had been verified by students of UK business school. The Web Qual 2.0, Step two invented for interaction quality, and had been judged by customers of on-line bookshop. The WebQual 3.0, Step three invented by consolidating the WebQual 1.0 for information quality and the WebQual2.0 for interactionquality. It includes 3-quality-dimension, information quality, interaction quality, site design, and had been assessed and confirmed by auction sites(e-bay, Amazon, QXL). Furtheron, through the former empirical studies, the authors changed sites quality into usability by judging that usability is a concept how customers interact with or perceive Web sites and It is used widely for accessing Web sites. By this process, WebQual 4.0 was invented, and is consist of 3-quality-dimension; information quality, interaction quality, usability, 22 items. However, because WebQual 4.0 is focusing on technical part, it's usable at the Website's design part, on the other hand, it's not usable at the Web site's pleasant experience part. Parasuraman, Zeithaml & Malhorta(2002; 2005) had invented the measure for measuring on-line service quality in 2002 and 2005. The study in 2002 divided on-line service quality into 5 dimensions. But these were not well-organized, so there needed to be studied again totally. So Parasuraman, Zeithaml & Malhorta(2005) re-worked out the study about on-line service quality measure base on 2002's study and invented E-S-QUAL. After they invented preliminary measure for on-line service quality, they made up a question for customers who had purchased at amazon.com and walmart.com and reassessed this measure. And they perfected an invention of E-S-QUAL consists of 4 dimensions, 22 items of efficiency, system availability, fulfillment, privacy. Efficiency measures assess to sites and usability and others, system availability measures accurate technical function of sites and others, fulfillment measures promptness of delivering products and sufficient goods and others and privacy measures the degree of protection of data about their customers and so on. 2.2 Service Recovery Service industries tend to minimize the losses by coping with service failure promptly. This responses of service providers to service failure mean service recovery(Kelly & Davis, 1994). Bitner(1990) went on his study from customers' view about service providers' behavior for customers to recognize their satisfaction/dissatisfaction at service point. According to them, to manage service failure successfully, exact recognition of service problem, an apology, sufficient description about service failure and some tangible compensation are important. Parasuraman, Zeithaml & Malhorta(2005) approached the service recovery from how to measure, rather than how to manage, and moved to on-line market not to off-line, then invented E-RecS-QUAL which is a measuring tool about on-line service recovery. 2.3 Customer Satisfaction The definition of customer satisfaction can be divided into two points of view. First, they approached customer satisfaction from outcome of comsumer. Howard & Sheth(1969) defined satisfaction as 'a cognitive condition feeling being rewarded properly or improperly for their sacrifice.' and Westbrook & Reilly(1983) also defined customer satisfaction/dissatisfaction as 'a psychological reaction to the behavior pattern of shopping and purchasing, the display condition of retail store, outcome of purchased goods and service as well as whole market.' Second, they approached customer satisfaction from process. Engel & Blackwell(1982) defined satisfaction as 'an assessment of a consistency in chosen alternative proposal and their belief they had with them.' Tse & Wilton(1988) defined customer satisfaction as 'a customers' reaction to discordance between advance expectation and ex post facto outcome.' That is, this point of view that customer satisfaction is process is the important factor that comparing and assessing process what they expect and outcome of consumer. Unlike outcome-oriented approach, process-oriented approach has many advantages. As process-oriented approach deals with customers' whole expenditure experience, it checks up main process by measuring one by one each factor which is essential role at each step. And this approach enables us to check perceptual/psychological process formed customer satisfaction. Because of these advantages, now many studies are adopting this process-oriented approach(Yi, 1995). 2.4 Loyalty Intention Loyalty has been studied by dividing into behavioral approaches, attitudinal approaches and complex approaches(Dekimpe et al., 1997). In the early years of study, they defined loyalty focusing on behavioral concept, behavioral approaches regard customer loyalty as "a tendency to purchase periodically within a certain period of time at specific retail store." But the loyalty of behavioral approaches focuses on only outcome of customer behavior, so there are someone to point the limits that customers' decision-making situation or process were neglected(Enis & Paul, 1970; Raj, 1982; Lee, 2002). So the attitudinal approaches were suggested. The attitudinal approaches consider loyalty contains all the cognitive, emotional, voluntary factors(Oliver, 1997), define the customer loyalty as "friendly behaviors for specific retail stores." However these attitudinal approaches can explain that how the customer loyalty form and change, but cannot say positively whether it is moved to real purchasing in the future or not. This is a kind of shortcoming(Oh, 1995). 3. Research Design 3.1 Research Model Based on the objects of this study, the research model derived is