• Title/Summary/Keyword: likelihood of success

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Influencing Factors on the Likelihood of Start-up Success of Researchers in Public Research Institutes: Using PLS and fsQCA (공공연구기관 연구자의 창업성공가능성에 미치는 영향 요인: PLS와 fsQCA 활용)

  • Hwang, Kyung Yun;Sung, Eul Hyun
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.17 no.1
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    • pp.107-120
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    • 2022
  • The purpose of this study is to analyze the net effect and the combined effect of the determinants of the likelihood of start-up success of researchers at public research institutes. Based on the existing literature, the determinants of the researcher's likelihood of start-up success were reviewed, and a conceptual relationship between the determinants of the likelihood of start-up success was established. Data collection was conducted through a survey targeting researchers at public research institutes, and a total of 114 data were collected. The partial least squares (PLS) analysis method was used to analyze the net effect of the likelihood of start-up success determinant, and the fuzzy-set qualitative comparative analysis (fsQCA) was used to analyze the combined effect of the likelihood of start-up success determinant. In the PLS analysis results, it was found that technology commercialization probability and creative self-efficacy had a significant positive effect independently on the likelihood of start-up success. In the fsQCA results, we found a combined effect of increasing the likelihood of start-up success when the technology commercialization probability, technology commercialization capability, and creative self-efficacy were high. These research results provide academic implications for understanding the determinants of the likelihood of start-up success of researchers in public research institutes.

A Study on a Model of Clothing complaining Behavior and relevant Variables (의복불평행동모형구성과 관련변수에 관한 연구)

  • 홍금희
    • Journal of the Korean Society of Clothing and Textiles
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    • v.23 no.2
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    • pp.262-271
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    • 1999
  • This paper presents a conceptual mode of the clothing complaining behavior process following dissatisfaction in a retail environment and influence of relevant variables. The data were collected 250 male and 358 female consumers by questionnaire employing critical incident technique. Given dissatisfaction with clothing the complaining behavior undertaken will be largely dependent on product importance the likelihood of success one's attitude toward complaining and demorgraphic variables. Through empirical research the clothing complaining behavior was dependent on the likelihood of success sex, dimension of complaining cost and product importance, Brand satisfaction was affected by only perceived justice. And repurchasing behavior was dependent upon brand satisfaction education product importance and income.

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An Analytic Network Process(ANP) Approach to Forecasting of Technology Development Success : The Case of MRAM Technology (네트워크분석과정(ANP)을 이용한 기술개발 성공 예측 : MRAM 기술을 중심으로)

  • Jeon, Jeong-Hwan;Cho, Hyun-Myung;Lee, Hak-Yeon
    • IE interfaces
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    • v.25 no.3
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    • pp.309-318
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    • 2012
  • Forecasting probability or likelihood of technology development success has been a crucial factor for critical decisions in technology management such as R&D project selection and go or no-go decision of new product development (NPD) projects. This paper proposes an analytic network process (ANP) approach to forecasting of technology development success. Reviewing literature on factors affecting technology development success has constructed the ANP model composed of four criteria clusters : R&D characteristics, R&D competency, technological characteristics, and technological environment. An alternative cluster comprised of two elements, success and failure is also included in the model. The working of the proposed approach is provided with the help of a case study example of MRAM (magnetic random access memory) technology.

Landslide Susceptibility Analysis and its Verification using Likelihood Ratio, Logistic Regression and Artificial Neural Network Methods: Case study of Yongin, Korea

  • Lee, S.;Ryu, J. H.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.132-134
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    • 2003
  • The likelihood ratio, logistic regression and artificial neural networks methods are applied and verified for analysis of landslide susceptibility in Yongin, Korea using GIS. From a spatial database containing such data as landslide location, topography, soil, forest, geology and land use, the 14 landsliderelated factors were calculated or extracted. Using these factors, landslide susceptibility indexes were calculated by likelihood ratio, logistic regression and artificial neural network methods. Before the calculation, the study area was divided into two sides (west and east) of equal area, for verification of the methods. Thus, the west side was used to assess the landslide susceptibility, and the east side was used to verify the derived susceptibility. The results of the landslide susceptibility analysis were verified using success and prediction rates. The v erification results showed satisfactory agreement between the susceptibility map and the exis ting data on landslide locations.

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Success Factors of Donation-based Crowdfunding : DonorsChoose Case (기부형 크라우드펀딩의 성공 요인 : 도너스츄즈 플랫폼을 중심으로)

  • Park, Hyun-Jung;Shin, Kyung-Shik
    • Journal of Information Technology Services
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    • v.15 no.2
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    • pp.1-19
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    • 2016
  • With various success stories of crowdfunding, government's establishment of crowdfunding act, and expected rapid growth of crowdfunding market, the potential ripple effect of crowdfunding on our society is anticipated to be enormous. This study investigates the influential factors and their impacts on the likelihood of project success in donation-based crowdfunding through the DonorsChoose case. The authors analyze the characteristics of project creator, characteristics of project, and behaviors of project participants in relation to the success or failure of the corresponding project. Consequently, the authors found that participants of donation-based crowdfunding exhibit altruistic behaviors and obtained the following specific results: First, donation participation and social capital of the project creator, and marginal help utility of receivers positively affect the success of project. Second, experience of past project creation of the project creator negatively affects the success of project. Third, past donations of the project creator to others' projects, when not appropriately signaled like on the DonorsChoose platform, may not exert a positive influence on the success of project and the reciprocity principle may not work.

On the Interval Estimation of the Difference between Independent Proportions with Rare Events

  • im, Yongdai;Choi, Daewoo
    • Communications for Statistical Applications and Methods
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    • v.7 no.2
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    • pp.481-487
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    • 2000
  • When we construct an interval estimate of two independent proportions with rare events, the standard approach based on the normal approximation behaves badly in many cases. The problem becomes more severe when no success observations are observed on both groups. In this paper, we compare two alternative methods of constructing a confidence interval of the difference of two independent proportions by use of simulation. One is based on the profile likelihood and the other is the Bayesian probability interval. It is shown in this paper that the Bayesian interval estimator is easy to be implemented and performs almost identical to the best frequentist's method -the profile likelihood approach.

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What Causes Technology Commercialization to Succeed or Fail after Transfer from Public Research Organizations

  • Kim, Yong-Jeong;Shin, Seowon Joseph
    • Asian Journal of Innovation and Policy
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    • v.6 no.1
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    • pp.23-44
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    • 2017
  • This study explores how the technology commercialization process leads to either success or failure after transfer from PROs to SMEs by conducting a binomial logistic regression analysis. We found that the more additional development a firm implements on the transferred technology, the more likely the commercialization is to fail. The higher number of alternative technology and bigger market risk are associated with a greater likelihood of failure. On the other hand, the existence of complementary technology, the degree of cooperation with the technology provider, the size of the target market, the willingness of the CEO, and the funding availability are known to have positive effects on the success of technology commercialization. In addition, the case studies we conducted from the sample companies demonstrated that "market uncertainty," "technological issues depending on the technology-specific characteristics," and "a lack of funding capability" are some of the causes for failure of technology commercialization.

An Empirical Investigation of the Factors Affecting Data Warehousing Success (데이터 웨어하우징의 구현특성요인과 품질간의 관계에 관한 실증적 연구)

  • Kim, Byung-Gon
    • The Journal of Information Technology
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    • v.8 no.3
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    • pp.83-103
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    • 2005
  • The IT implementation literature suggests that various implementation factors play critical roles in the success of an information system; however, there is little empirical research about the implementation of data warehousing has unique characteristics that may impact the importance of factors that apply to it. in this study, a cross-sectional survey investigated a model of data warehousing success. Data warehousing managers and data suppliers from 51 organizations completed paired mail questionnaires on implementation factors and the success of the warehouse. The results from a regression analysis of the data identified relationships between the system quality and data quality factors and perceived net benefits. It was found that management support and resources help to address organizational issues that arise during warehouse implementations, resources, user participation, and highly-skilled project team members increase the likelihood that warehousing projects will finish on-time, on-budget, with the right functionality; and diverse, unstandardized source systems and poor development technology will increase the technical issues that project teams must overcome. The implementation's success with organizational and project issues, in turn, influence the system quality of the data warehouse; however, data quality is best explained by factors not included in the research model.

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A New Product Risk Model for the Electric Vehicle Industry in South Korea

  • CHU, Wujin;HONG, Yong-pyo;PARK, Wonkoo;IM, Meeja;SONG, Mee Ryoung
    • Journal of Distribution Science
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    • v.18 no.9
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    • pp.31-43
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    • 2020
  • Purpose: This study examined a comprehensive model for assessing the success probability of electric vehicle (EV) commercialization in the Korean market. The study identified three risks associated with successful commercialization which were technology, social, policy, environmental, and consumer risk. Research design, methodology: The assessment of the riskiness was represented by a Bayes belief network, where the probability of success at each stage is conditioned on the outcome of the preceding stage. Probability of success in each stage is either dependent on input (i.e., investment) or external factors (i.e., air quality). Initial input stages were defined as the levels of investment in product R&D, battery technology, production facilities and battery charging facilities. Results: Reasonable levels of investment were obtained by expert opinion from industry experts. Also, a survey was carried out with 78 experts consisting of automaker engineers, managers working at EV parts manufacturers, and automobile industry researchers in government think tanks to obtain the conditional probability distributions. Conclusion: The output of the model was the likelihood of success - expressed as the probability of market acceptance - that depended on the various input values. A model is a useful tool for understanding the EV industry as a whole and explaining the likely ramifications of different investment levels.

A Study on the Estimation of Launch Success Probability for Space Launch Vehicles Using Bayesian Method (베이지안 기법을 적용한 우주발사체의 발사 성공률 추정에 관한 연구)

  • Yoo, Seung-Woo;Kim, In-Gul
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.48 no.7
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    • pp.537-546
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    • 2020
  • The reliability used as a performance indicator during the development of space launch vehicle should be validated by the launch success probability, and the launch data need to be fed back for reliability management. In this paper, the launch data of space launch vehicles around the world were investigated and statistically analyzed for the success probabilities according to the launch vehicle models and maturity. The Bayesian estimation of launch success probability was reviewed and analyzed by comparing the estimated success probabilities using several prior distributions and the statistical success probability. We presented the method of generating prior distribution function and considerations for Bayesian estimation.