• PNF and Movement
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• v.17 no.3
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• pp.487-497
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• 2019

Purpose: This tutorial review investigated the effect of prior fatigue and passive stretches on eccentric contraction-induced muscle injuries, as well as the underlying mechanisms of eccentric contraction-related injuries. Methods: Contraction-induced muscle damage is the most common disabling problem in sports and routines. The mechanisms underlying the pathology and prevention of muscle damage lessened by prior fatigue or stretches are critical in assessing musculoskeletal injuries. Even though there are treatments to reduce eccentric contraction-induced muscle injuries, fatigue negatively influences them. Therefore, we reviewed previous studies on eccentric contraction-induced muscle injuries with prior treatments using the MEDLINE and PubMed databases. Results: Prior passive stretching had a preventative and therapeutic effect, but prior lengthening contractions did not. On the other hand, prior isometric contractions involving relatively small forces may not provide a sufficient stimulus to induce protection. As a result, high force isometric contractions may be necessary. The studies supported the positive effects of prior fatigue, concluding that it was a factor in determining the amount of damage caused by eccentric exercise. This was due to a reduction in force and increased temperature. Studies that did not support the positive effects of prior fatigue concluded that a shift in optimal length to a longer length and reduced energy absorption during lengthening are evidence that fatigue is not related to muscle injuries induced by lengthening. Conclusion: The variability of the experiment models, conditions, muscles, and treatment methods make it necessary to interpret the conditions of previous studies carefully and draw conclusions without making direct comparisons. Thus, additional studies should be carefully conducted to investigate the positive effect of fatigue on lengthening.

• Journal of Korea Trade
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• v.27 no.5
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• pp.91-112
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• 2023

Purpose - This study empirically investigates how the effects of localized knowledge spillovers on technology adoption are conditional on the organizational capabilities of potential adopters. Design/methodology - The empirical model utilized in this study examines how the presence of prior adopters of advanced manufacturing technologies affects a plant's technology adoption decision differently based on its organizational capabilities, measured by plant size and plant status (single-plant firm vs. multi-plant firm). Moreover, this study investigates how the scope of knowledge spillovers from prior adopters, both in terms of geographical and functional proximities, differ for plants with different organizational capabilities. Findings - The main findings of this study are as follows: 1. Although plants with lower organizational capabilities are less likely to adopt advanced technologies, such plants receive greater marginal benefits from knowledge spillovers from prior adopters in their region. 2. Plants with greater organizational capabilities can benefit from knowledge spillovers from a wider set of prior adopters. In other words, while plants with lower organizational capabilities tend to benefit from knowledge spillovers from "similar" and "local" adopters, plants with greater organizational capabilities can also benefit from knowledge spillovers from "not-too-similar" or are geographically distant prior adopters. Originality/value - While existing studies mainly focus on the effects of the various kinds of regional agglomeration, few studies investigate localized knowledge spillovers in technology adoption. Moreover, no prior studies have explored how the effects of knowledge spillovers on technology adoption depend on a plant's organizational capabilities and how the scope of knowledge spillovers differs for plants with different organizational capabilities. This study is the first to empirically investigate this topic.

• Journal of Distribution Science
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• v.12 no.5
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• pp.15-26
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• 2014

Purpose - This study addresses an acquisition's impact on a firm's strategic relationship based on findings of existing academic studies and theoretical assertions. Through examining existing research results and theoretical grounds for an acquisition's impact on various stakeholders, this study indirectly approaches the impact on stakeholders including alliance partners. Research design, data, and methodology - This research identified a variety of related theoretical foundations and empirical studies. Research objectives of prior studies mainly focused on merging firms and direct participants of acquisition activity. In addition, academic attention on the impact on rival firms has recently been growing. However, little research on alliance partners was found. Prior studies simultaneously employed event study methodology and cross-sectional analysis to make further theoretical contributions. Results and Conclusions - Based on the findings of prior studies, this research proposed a complementary research model for future academic inquiry into the impact of an acquisition on an alliance partner's return and for predicting an acquisition announcement's effect on alliance partners.

• Communications for Statistical Applications and Methods
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• v.15 no.1
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• pp.13-26
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• 2008

Inference on the present data will be more reliable when the data arising from previous similar studies are available. The data arising from previous studies are referred as historical data. The power prior is defined by the likelihood function based on the historical data to the power $a_0$, where $0\;{\le}\;a_0\;{\le}\;1$. The power prior is a useful informative prior for Bayesian inference such as model selection and model comparison. We utilize the historical data to perform multiple comparison in the one-way ANOVA model. We demonstrate our results with some simulated datasets under a simple order restriction between the treatments.

• Korean Journal of Child Studies
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• v.34 no.1
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• pp.21-34
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• 2013

The purposes of this study were (1) to investigate the differences in the level of children's knowledge and reasoning skills due to the sloping phenomenon according to their ages and the types of tasks they were asked to perform, and (2) to investigate whether children's prior knowledge is changed to post knowledge through their reasoning. A total of 120 subjects, forty from each of the age groups 4, 6 and 8 were selected for the study. The major findings are presented below : 8-year old children showed higher levels of prior knowledge than 6-year old children. The prior knowledge level of the "size" task was higher than that of the "weight" task. 6-and 8-year old children showed higher levels of reasoning than 4-year old children. The reasoning level of the "size" task was higher than that of the "weight" task. 6-and 8-year old children showed higher levels of post knowledge than 4-year old children. However, there was no difference in children's post knowledge according to task difference. Through the different types of reasoning involved in the children's performances of the two tasks, changes in the prior knowledge of the sloping phenomenon were observed among all age groups.

• Korean Association of Arts Management
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• no.54
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• pp.59-93
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• 2020

The development of digital technology has made consumers more knowledgeable about products than ever before. In this regard, experts have defined consumers in the digital age as knowledge seekers and pointed out that they are proficient in acquiring and sharing product knowledge prior to purchase. For service goods such as musicals, product prior knowledge executes strong effect due to such characteristics as intangibility, inseparabilit y,and heterogeneity. Prior studies in the field of performing arts, including musicals, have revealed that the prior knowledge of the audience has a positive effect on the satisfaction of the audience and WOM(word-of-mouth) intention. However, studies in the marketing field argue that consumers' high prior knowledge may have a negative impact on customer satisfaction and product evaluation depending on conditions, as they are more likely to compare, review, and expect products more closely. Therefore, in this study, we tried to identify under what conditions the musical prior knowledge enhances audience satisfaction and WOM intention. According to the results of previous studies, a mediating effect model was established in which the musical prior knowledge enhances the WOM intention through the mediation of the audience satisfaction. Then, Transportation was introduced as a mediation variable and it was verified whether the level changed the audience satisfaction and WOM intention. The reason for the introduction of the transportation construct reflects the results of previous research that the story is important component of musical. The results showed that the musical prior knowledge has a significant effect on WOM intention through the mediation of audience satisfaction. The moderating effect of transport was also significant on the relationship between musical prior knowledge and audience satisfaction. Lastly, through moderated-mediation analysis, it was confirmed that transportation moderates the mediating effect that prior knowledge affects on the WOM intention through audience satisfaction. Based on the results, we demonstrated that a musical story is fairly important to satisfy audiences with high prior knowledge. This study could contribute to the related filed in that it introduced the transportation construct for the first time, thereby broadening the understanding of the musical audiences in the era of smart consumers.

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.161-175
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• 2001

Meta-analysis refers to quantitative methods for combining results from independent studies in order to draw overall conclusions. Hierarchical models including selection models are introduced and shown to be useful in such Bayesian meta-analysis. Semiparametric hierarchical models are proposed using the Dirichlet process prior. These rich class of models combine the information of independent studies, allowing investigation of variability both between and within studies, and weight function. Here we investigate sensitivity of results to unobserved studies by considering a hierachical selection model with including unknown weight function and use Markov chain Monte Carlo methods to develop inference for the parameters of interest. Using Bayesian method, this model is used on a meta-analysis of twelve studies comparing the effectiveness of two different types of flouride, in preventing cavities. Clinical informative prior is assumed. Summaries and plots of model parameters are analyzed to address questions of interest.

• Communications for Statistical Applications and Methods
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• v.30 no.3
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• pp.311-330
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• 2023

The present work describes simulation studies to compare the performances in terms of averaged mean squared error of bayesian wavelet shrinkage methods in estimating component curves from aggregated functional data. Five bayesian methods available in the literature were considered to be compared in the studies: The shrinkage rule under logistic prior, shrinkage rule under beta prior, large posterior mode (LPM) method, amplitude-scale invariant Bayes estimator (ABE) and Bayesian adaptive multiresolution smoother (BAMS). The so called Donoho-Johnstone test functions, logit and SpaHet functions were considered as component functions and the scenarios were defined according to different values of sample size and signal to noise ratio in the datasets. It was observed that the signal to noise ratio of the data had impact on the performances of the methods. An application of the methodology and the results to the tecator dataset is also done.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.875-888
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• 2017

The Rayleigh distribution has been commonly used in life time testing studies of the probability of surviving until mission time. We focus on a reliability function of the Rayleigh distribution and deal with prior distribution on R(t). This paper is an effort to obtain Bayes estimators of rayleigh distribution with three different prior distribution on the reliability function; a noninformative prior, uniform prior and inverse gamma prior. We have found the Bayes estimator and predictive density function of a future observation y with each prior distribution. We compare the performance of the Bayes estimators under different sample size and in simulation study. We also derive the most plausible region, prediction intervals for a future observation.

• Journal of the Korean Statistical Society
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• v.34 no.4
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• pp.331-344
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• 2005

Inference on current data could be more reliable if there exist similar data based on previous studies. Ibrahim and Chen (2000) utilize these data to characterize the power prior. The power prior is constructed by raising the likelihood function of the historical data to the power $a_o$, where $0\;{\le}\;a_o\;{\le}\;1$. The power prior is a useful informative prior in Bayesian inference. However, for model selection or model comparison problems, the propriety of the power prior is one of the critical issues. In this paper, we suggest two joint power priors for the power law process and show that they are proper under some conditions. We demonstrate our results with a real dataset and some simulated datasets.