• Title/Summary/Keyword: Co-orientation Model

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An Analysis on Affecting Factors of Healthcare Applications Continuous Usage Intention and their Relationships (헬스케어 어플리케이션 지속적 사용의도 영향 요인 및 요인 간 관계에 대한 분석)

  • Ki, Yeon-Su;Ahn, Sung-Mahn;Cho, Min-Guk;Choi, Byounggu
    • The Journal of Society for e-Business Studies
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    • v.24 no.1
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    • pp.49-89
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    • 2019
  • Many studies have been conducted on adoption of healthcare applications. However, few studies have paid their attention to continuous usage intention of healthcare applications even though success of healthcare applications is determined by Continuous usage intention rather than adoption. Therefore, this study tried to identify the factors affecting the continuous usage intention of healthcare applications and examined the relationship between them empirically. In addition, the role of gender and age in the relationship was investigated. The results showed that self-efficacy and innovation had a significant effect on perceived ease of use of healthcare application, while self-efficacy, health information seeking, and enjoyment had a significant effect on perceived usefulness. Perceived ease of use and usefulness showed positive impact on continuous usage intention of healthcare application. Finally, age and gender had a moderator effect the relationship between perceived usefulness and continuous usage intention. This study is expected to make contributions to the existing research by identifying the factors affecting the Continuous usage intention of healthcare applications, but also to give a guideline for managers who want to provide healthcare application services.

The Effects of CRM Commitment and Organizational Culture on CRM Performance (CRM 몰입과 조직문화가 CRM 성과에 미치는 영향)

  • Park, Tae Hoon;Lim, Young Kyun
    • Asia Marketing Journal
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    • v.10 no.2
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    • pp.31-69
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    • 2008
  • The purpose of this study is to identify the organizational characteristics that enhance CRM performances of a company. Based on a review of diverse definitions of CRM performance, this study examines the relationships among CRM performance measures and organizational characteristics. A questionnaire survey of 123 CRM managers of Korean companies was conducted to test the proposed research model, and a series of structural equation modeling identified the strong effects of organizational characteristics on CRM performance. It was found that top management commitment to CRM and a firm's strategic readiness lead to high levels of CRM investment, which, in turn, enhance directly task-related performance and indirectly customer-related performance. This study also confirmed that customer orientation is significantly related to task-related CRM performance and that the variables of CRM commitment and organizational culture may enhance customerrelated performance indirectly through their effects on the task-related performance. However, organizational members' resistance to change was found to have no effects on CRM performance. Overall our research broadly supports the role of organizational characteristics revealed in the CRM literature.

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A study on the factors to affect the career success among workers with disabilities (지체장애근로자의 직업성공 요인에 관한 연구)

  • Lee, Dal-Yob
    • 한국사회복지학회:학술대회논문집
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    • 2003.10a
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    • pp.185-216
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    • 2003
  • This study was aimed at investigating important factors influencing career success among regular workers. The current researcher scrutinized the degree to which variables and factors affect the career success and occupational turnover rates of the research participants. At the same tune, two hypothetical path models established by the researcher were examined using linear multiple regression methods and the LISREL. After examining the differences among the factors of career success, a comparison was made between the disabled worker group and the non-disabled worker group. A questionnaire using the 5-point Likert scale was distributed to a group of 374 workers with disabilities and 463 workers without disabilities. For the data analysis purpose, the structural equation model, factor analysis, correlation analysis, and multiple regression analysis were carried out. The results of this study ran be summarized as follows. First, the results of factor analysis showed important categories of conceptual themes of career success. The initial conceptual factor model did not accord with the empirical one. A three-factorial model revealed categories of personal, family, and organizational factor respectively. The personal factor was composed of the self-esteem and self-efficiency. The family factor was consisted of the multi-roles stress and the number of children. Finally, the organizational factor was composed of the capacity for utilizing resources, networking, and the frequency of mentoring. In addition, the total 10 sub areas of career success were divided by two important aspects; the subjective career success and the objective career success. Second, both research participant groups seemed to be influenced by their occupational types. However, all predictive variables excluding the wage rate and the average length of work years had significant impact on job success for the disabled work group, while all the variables excluding the frequency of advice and length of working years had significant impact on job success for the non-disabled worker group. Third, the turnover rate was significantly influenced by the age and the experience of turnover of the research participants. However, the number of co-workers was the strongest predictive variable for the worker group with disabilities, but the occupation choice variable for the worker group without disabilities. For the disabled worker group, the turnover rate was differently influenced by the type of occupation, the length of working years, while multi-role stress and the average working years at the time of turnover for the worker group without disabilities. Fifth, as a result of verifying the hypothetical path model, it showed that the first model was somewhat proper and could predict the career success on both research participant groups. In the second model, the Chi-square, the degree of freedom (($x^2=64.950$, df=61, P=0.341), and the adjusted Goodness of Fit Index (AGFI) were .964, and the Comparative Fit Index (CFI) were .997, and the Root Mean Squared Residual (RMR) was respectively. .038. The model was best fitted and could predict the career success more highly because the goodness of fit index in the whole models was within the allowed range. In conclusion, the following research implications can be suggested. First, the occupational type of research participants was one of the most important variables to predict the career success for both research participant groups. It means that people with disabilities require human development services including education. They need to improve themselves in this knowledge-based society. Furthermore, for maintaining the career success, people with disabilities should be approached by considering the subjective career success aspects including wages and the promotion opportunities than the objective career success aspects.

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A Study on Singapore Startup Ecosystem using Regional Transformation of Isenberg(2010) (싱가포르 창업생태계 연구: Isenberg(2010) 프레임워크의 지역적 변용을 통한 질적 연구를 중심으로)

  • Kim, Soyeon;Cho, Minhyung;Rhee, Mooweon
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.15 no.2
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    • pp.47-65
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    • 2020
  • With the era of the Fourth Industrial Revolution in sight, innovative business models utilizing new technologies are emerging, and startups are enjoying an abundance of opportunities based on the agility to respond to disruptive innovations and the opening to new technologies. However, what is most important in creating a sustainable start-up ecosystem is not the start-up itself, but the process of research-start-investment-investment-the leap to listing and big business-in order to build a virtuous circle of startups that leads to re-investment. To this end, the environment created in the hub area where start-ups were conducted is important, and these material and non-material environmental factors are described as being inclusive by the word "entrepreneurial ecosystem." This study aims to provide implications for Korea's entrepreneurial ecosystem through the study of the interaction of the elements that make up the start-up ecosystem and the relationship of ecosystem participants in Singapore. Singapore has been consistently mentioned as the top two Asian countries in assessing the start-up environment and business environment. In this process, six elements of the entrepreneurial ecosystem presented by Isenberg(2010)-policies, finance, culture, support, human resources, and market-are the best frameworks for analyzing entrepreneurial ecosystems in terms of well encompassing prior studies related to entrepreneurial ecosystem elements, and a model of regional transformation is formed focusing on some elements to suit Singapore, the target area of study. By considering that Singapore's political nature would inevitably have a huge impact on finance, Smart Nation policy was having an impact on university education related to entrepreneurship, and that the entrepreneurial networks and global connectivity formed within Singapore's start-up infrastructure had a significant impact on Singapore's start-up's performance, researches needed to look more at the factors of policy, culture and market. In addition, qualitative research of participants in the entrepreneurial ecosystem was essential to understand the internal interaction of the elements of the start-up ecosystem, so the semi-structured survey was conducted by visiting the site. As such, this study examined the status of the local entrepreneurial ecosystem based on qualitative research focused on policies, culture and market elements of Singapore's start-up ecosystem, and intended to provide implications for regulations related to start-ups, the role of universities and start-up infrastructure through comparison with Korea. This could contribute not only to the future research of the start-up ecosystem, but also to the creation of a start-up infrastructure, boosting the start-up ecosystem, and the establishment of the orientation of the start-up education in universities.